4 further sources (Ethnic Power Relations Dataset, GI-TOC / ENACT, Global Data Lab, World Values Survey) are held but not offered: their licences do not permit commercial redistribution. HERA cites their published findings with attribution and can supply the data to organisations holding their own licence — ask us.
ⓘ 1-in-10 household sample. These tables come from the census long questionnaire, which about one household in ten answered. The National Bureau of Statistics publishes the sample's own counts without scaling them up, so counts here are about a tenth of the real figure: this sample counted 138,657,945 people, against 1,409,778,724 in the full count. Shares, rates and averages can be used as they are; for population totals use the full-count datasets.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_at_first_marriage |
Age at first marriage | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
year_of_first_marriage_total_total |
Year of first marriage > Total > Total | decimal | 0% | - | - |
year_of_first_marriage_total_male |
Year of first marriage > Total > Male | decimal | 0% | - | - |
year_of_first_marriage_total_female |
Year of first marriage > Total > Female | decimal | 0% | - | - |
year_of_first_marriage_1980_subtotal |
Year of first marriage > 1980 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1980_male |
Year of first marriage > 1980 > Male | decimal | 0% | - | - |
year_of_first_marriage_1980_female |
Year of first marriage > 1980 > Female | decimal | 0% | - | - |
year_of_first_marriage_1981_subtotal |
Year of first marriage > 1981 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1981_male |
Year of first marriage > 1981 > Male | decimal | 0% | - | - |
year_of_first_marriage_1981_female |
Year of first marriage > 1981 > Female | decimal | 0% | - | - |
year_of_first_marriage_1982_subtotal |
Year of first marriage > 1982 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1982_male |
Year of first marriage > 1982 > Male | decimal | 0% | - | - |
year_of_first_marriage_1982_female |
Year of first marriage > 1982 > Female | decimal | 0% | - | - |
year_of_first_marriage_1983_subtotal |
Year of first marriage > 1983 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1983_male |
Year of first marriage > 1983 > Male | decimal | 0% | - | - |
year_of_first_marriage_1983_female |
Year of first marriage > 1983 > Female | decimal | 0% | - | - |
year_of_first_marriage_1984_subtotal |
Year of first marriage > 1984 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1984_male |
Year of first marriage > 1984 > Male | decimal | 0% | - | - |
year_of_first_marriage_1984_female |
Year of first marriage > 1984 > Female | decimal | 0% | - | - |
year_of_first_marriage_1985_subtotal |
Year of first marriage > 1985 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1985_male |
Year of first marriage > 1985 > Male | decimal | 0% | - | - |
year_of_first_marriage_1985_female |
Year of first marriage > 1985 > Female | decimal | 0% | - | - |
year_of_first_marriage_1986_subtotal |
Year of first marriage > 1986 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1986_male |
Year of first marriage > 1986 > Male | decimal | 0% | - | - |
year_of_first_marriage_1986_female |
Year of first marriage > 1986 > Female | decimal | 0% | - | - |
year_of_first_marriage_1987_subtotal |
Year of first marriage > 1987 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1987_male |
Year of first marriage > 1987 > Male | decimal | 0% | - | - |
year_of_first_marriage_1987_female |
Year of first marriage > 1987 > Female | decimal | 0% | - | - |
year_of_first_marriage_1988_subtotal |
Year of first marriage > 1988 > Subtotal | decimal | 0% | - | - |
| +98 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_at_first_marriage |
Age at first marriage | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
year_of_first_marriage_total_total |
Year of first marriage > Total > Total | decimal | 0% | - | - |
year_of_first_marriage_total_male |
Year of first marriage > Total > Male | decimal | 0% | - | - |
year_of_first_marriage_total_female |
Year of first marriage > Total > Female | decimal | 0% | - | - |
year_of_first_marriage_1980_subtotal |
Year of first marriage > 1980 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1980_male |
Year of first marriage > 1980 > Male | decimal | 0% | - | - |
year_of_first_marriage_1980_female |
Year of first marriage > 1980 > Female | decimal | 0% | - | - |
year_of_first_marriage_1981_subtotal |
Year of first marriage > 1981 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1981_male |
Year of first marriage > 1981 > Male | decimal | 0% | - | - |
year_of_first_marriage_1981_female |
Year of first marriage > 1981 > Female | decimal | 0% | - | - |
year_of_first_marriage_1982_subtotal |
Year of first marriage > 1982 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1982_male |
Year of first marriage > 1982 > Male | decimal | 0% | - | - |
year_of_first_marriage_1982_female |
Year of first marriage > 1982 > Female | decimal | 0% | - | - |
year_of_first_marriage_1983_subtotal |
Year of first marriage > 1983 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1983_male |
Year of first marriage > 1983 > Male | decimal | 0% | - | - |
year_of_first_marriage_1983_female |
Year of first marriage > 1983 > Female | decimal | 0% | - | - |
year_of_first_marriage_1984_subtotal |
Year of first marriage > 1984 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1984_male |
Year of first marriage > 1984 > Male | decimal | 0% | - | - |
year_of_first_marriage_1984_female |
Year of first marriage > 1984 > Female | decimal | 0% | - | - |
year_of_first_marriage_1985_subtotal |
Year of first marriage > 1985 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1985_male |
Year of first marriage > 1985 > Male | decimal | 0% | - | - |
year_of_first_marriage_1985_female |
Year of first marriage > 1985 > Female | decimal | 0% | - | - |
year_of_first_marriage_1986_subtotal |
Year of first marriage > 1986 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1986_male |
Year of first marriage > 1986 > Male | decimal | 0% | - | - |
year_of_first_marriage_1986_female |
Year of first marriage > 1986 > Female | decimal | 0% | - | - |
year_of_first_marriage_1987_subtotal |
Year of first marriage > 1987 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1987_male |
Year of first marriage > 1987 > Male | decimal | 0% | - | - |
year_of_first_marriage_1987_female |
Year of first marriage > 1987 > Female | decimal | 0% | - | - |
year_of_first_marriage_1988_subtotal |
Year of first marriage > 1988 > Subtotal | decimal | 0% | - | - |
| +98 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_at_first_marriage |
Age at first marriage | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
year_of_first_marriage_total_total |
Year of first marriage > Total > Total | decimal | 0% | - | - |
year_of_first_marriage_total_male |
Year of first marriage > Total > Male | decimal | 0% | - | - |
year_of_first_marriage_total_female |
Year of first marriage > Total > Female | decimal | 0% | - | - |
year_of_first_marriage_1980_subtotal |
Year of first marriage > 1980 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1980_male |
Year of first marriage > 1980 > Male | decimal | 0% | - | - |
year_of_first_marriage_1980_female |
Year of first marriage > 1980 > Female | decimal | 0% | - | - |
year_of_first_marriage_1981_subtotal |
Year of first marriage > 1981 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1981_male |
Year of first marriage > 1981 > Male | decimal | 0% | - | - |
year_of_first_marriage_1981_female |
Year of first marriage > 1981 > Female | decimal | 0% | - | - |
year_of_first_marriage_1982_subtotal |
Year of first marriage > 1982 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1982_male |
Year of first marriage > 1982 > Male | decimal | 0% | - | - |
year_of_first_marriage_1982_female |
Year of first marriage > 1982 > Female | decimal | 0% | - | - |
year_of_first_marriage_1983_subtotal |
Year of first marriage > 1983 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1983_male |
Year of first marriage > 1983 > Male | decimal | 0% | - | - |
year_of_first_marriage_1983_female |
Year of first marriage > 1983 > Female | decimal | 0% | - | - |
year_of_first_marriage_1984_subtotal |
Year of first marriage > 1984 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1984_male |
Year of first marriage > 1984 > Male | decimal | 0% | - | - |
year_of_first_marriage_1984_female |
Year of first marriage > 1984 > Female | decimal | 0% | - | - |
year_of_first_marriage_1985_subtotal |
Year of first marriage > 1985 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1985_male |
Year of first marriage > 1985 > Male | decimal | 0% | - | - |
year_of_first_marriage_1985_female |
Year of first marriage > 1985 > Female | decimal | 0% | - | - |
year_of_first_marriage_1986_subtotal |
Year of first marriage > 1986 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1986_male |
Year of first marriage > 1986 > Male | decimal | 0% | - | - |
year_of_first_marriage_1986_female |
Year of first marriage > 1986 > Female | decimal | 0% | - | - |
year_of_first_marriage_1987_subtotal |
Year of first marriage > 1987 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1987_male |
Year of first marriage > 1987 > Male | decimal | 0% | - | - |
year_of_first_marriage_1987_female |
Year of first marriage > 1987 > Female | decimal | 0% | - | - |
year_of_first_marriage_1988_subtotal |
Year of first marriage > 1988 > Subtotal | decimal | 0% | - | - |
| +98 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_at_first_marriage |
Age at first marriage | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
year_of_first_marriage_total_total |
Year of first marriage > Total > Total | decimal | 0% | - | - |
year_of_first_marriage_total_male |
Year of first marriage > Total > Male | decimal | 0% | - | - |
year_of_first_marriage_total_female |
Year of first marriage > Total > Female | decimal | 0% | - | - |
year_of_first_marriage_1980_subtotal |
Year of first marriage > 1980 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1980_male |
Year of first marriage > 1980 > Male | decimal | 0% | - | - |
year_of_first_marriage_1980_female |
Year of first marriage > 1980 > Female | decimal | 0% | - | - |
year_of_first_marriage_1981_subtotal |
Year of first marriage > 1981 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1981_male |
Year of first marriage > 1981 > Male | decimal | 0% | - | - |
year_of_first_marriage_1981_female |
Year of first marriage > 1981 > Female | decimal | 0% | - | - |
year_of_first_marriage_1982_subtotal |
Year of first marriage > 1982 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1982_male |
Year of first marriage > 1982 > Male | decimal | 0% | - | - |
year_of_first_marriage_1982_female |
Year of first marriage > 1982 > Female | decimal | 0% | - | - |
year_of_first_marriage_1983_subtotal |
Year of first marriage > 1983 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1983_male |
Year of first marriage > 1983 > Male | decimal | 0% | - | - |
year_of_first_marriage_1983_female |
Year of first marriage > 1983 > Female | decimal | 0% | - | - |
year_of_first_marriage_1984_subtotal |
Year of first marriage > 1984 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1984_male |
Year of first marriage > 1984 > Male | decimal | 0% | - | - |
year_of_first_marriage_1984_female |
Year of first marriage > 1984 > Female | decimal | 0% | - | - |
year_of_first_marriage_1985_subtotal |
Year of first marriage > 1985 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1985_male |
Year of first marriage > 1985 > Male | decimal | 0% | - | - |
year_of_first_marriage_1985_female |
Year of first marriage > 1985 > Female | decimal | 0% | - | - |
year_of_first_marriage_1986_subtotal |
Year of first marriage > 1986 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1986_male |
Year of first marriage > 1986 > Male | decimal | 0% | - | - |
year_of_first_marriage_1986_female |
Year of first marriage > 1986 > Female | decimal | 0% | - | - |
year_of_first_marriage_1987_subtotal |
Year of first marriage > 1987 > Subtotal | decimal | 0% | - | - |
year_of_first_marriage_1987_male |
Year of first marriage > 1987 > Male | decimal | 0% | - | - |
year_of_first_marriage_1987_female |
Year of first marriage > 1987 > Female | decimal | 0% | - | - |
year_of_first_marriage_1988_subtotal |
Year of first marriage > 1988 > Subtotal | decimal | 0% | - | - |
| +98 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
age_at_first_marriage_total_total |
Age at first marriage > Total > Total | decimal | 0% | - | - |
age_at_first_marriage_total_male |
Age at first marriage > Total > Male | decimal | 0% | - | - |
age_at_first_marriage_total_female |
Age at first marriage > Total > Female | decimal | 0% | - | - |
age_at_first_marriage_under_15_subtotal |
Age at first marriage > Under 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_under_15_male |
Age at first marriage > Under 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_under_15_female |
Age at first marriage > Under 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_15_subtotal |
Age at first marriage > Age 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_15_male |
Age at first marriage > Age 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_15_female |
Age at first marriage > Age 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_16_subtotal |
Age at first marriage > Age 16 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_16_male |
Age at first marriage > Age 16 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_16_female |
Age at first marriage > Age 16 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_17_subtotal |
Age at first marriage > Age 17 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_17_male |
Age at first marriage > Age 17 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_17_female |
Age at first marriage > Age 17 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_18_subtotal |
Age at first marriage > Age 18 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_18_male |
Age at first marriage > Age 18 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_18_female |
Age at first marriage > Age 18 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_19_subtotal |
Age at first marriage > Age 19 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_19_male |
Age at first marriage > Age 19 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_19_female |
Age at first marriage > Age 19 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_20_subtotal |
Age at first marriage > Age 20 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_20_male |
Age at first marriage > Age 20 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_20_female |
Age at first marriage > Age 20 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_21_subtotal |
Age at first marriage > Age 21 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_21_male |
Age at first marriage > Age 21 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_21_female |
Age at first marriage > Age 21 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_22_subtotal |
Age at first marriage > Age 22 > Subtotal | decimal | 0% | - | - |
| +56 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
age_at_first_marriage_total_total |
Age at first marriage > Total > Total | decimal | 0% | - | - |
age_at_first_marriage_total_male |
Age at first marriage > Total > Male | decimal | 0% | - | - |
age_at_first_marriage_total_female |
Age at first marriage > Total > Female | decimal | 0% | - | - |
age_at_first_marriage_under_15_subtotal |
Age at first marriage > Under 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_under_15_male |
Age at first marriage > Under 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_under_15_female |
Age at first marriage > Under 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_15_subtotal |
Age at first marriage > Age 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_15_male |
Age at first marriage > Age 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_15_female |
Age at first marriage > Age 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_16_subtotal |
Age at first marriage > Age 16 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_16_male |
Age at first marriage > Age 16 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_16_female |
Age at first marriage > Age 16 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_17_subtotal |
Age at first marriage > Age 17 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_17_male |
Age at first marriage > Age 17 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_17_female |
Age at first marriage > Age 17 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_18_subtotal |
Age at first marriage > Age 18 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_18_male |
Age at first marriage > Age 18 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_18_female |
Age at first marriage > Age 18 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_19_subtotal |
Age at first marriage > Age 19 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_19_male |
Age at first marriage > Age 19 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_19_female |
Age at first marriage > Age 19 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_20_subtotal |
Age at first marriage > Age 20 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_20_male |
Age at first marriage > Age 20 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_20_female |
Age at first marriage > Age 20 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_21_subtotal |
Age at first marriage > Age 21 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_21_male |
Age at first marriage > Age 21 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_21_female |
Age at first marriage > Age 21 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_22_subtotal |
Age at first marriage > Age 22 > Subtotal | decimal | 0% | - | - |
| +56 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
age_at_first_marriage_total_total |
Age at first marriage > Total > Total | decimal | 0% | - | - |
age_at_first_marriage_total_male |
Age at first marriage > Total > Male | decimal | 0% | - | - |
age_at_first_marriage_total_female |
Age at first marriage > Total > Female | decimal | 0% | - | - |
age_at_first_marriage_under_15_subtotal |
Age at first marriage > Under 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_under_15_male |
Age at first marriage > Under 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_under_15_female |
Age at first marriage > Under 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_15_subtotal |
Age at first marriage > Age 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_15_male |
Age at first marriage > Age 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_15_female |
Age at first marriage > Age 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_16_subtotal |
Age at first marriage > Age 16 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_16_male |
Age at first marriage > Age 16 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_16_female |
Age at first marriage > Age 16 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_17_subtotal |
Age at first marriage > Age 17 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_17_male |
Age at first marriage > Age 17 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_17_female |
Age at first marriage > Age 17 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_18_subtotal |
Age at first marriage > Age 18 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_18_male |
Age at first marriage > Age 18 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_18_female |
Age at first marriage > Age 18 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_19_subtotal |
Age at first marriage > Age 19 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_19_male |
Age at first marriage > Age 19 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_19_female |
Age at first marriage > Age 19 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_20_subtotal |
Age at first marriage > Age 20 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_20_male |
Age at first marriage > Age 20 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_20_female |
Age at first marriage > Age 20 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_21_subtotal |
Age at first marriage > Age 21 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_21_male |
Age at first marriage > Age 21 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_21_female |
Age at first marriage > Age 21 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_22_subtotal |
Age at first marriage > Age 22 > Subtotal | decimal | 0% | - | - |
| +56 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
age_at_first_marriage_total_total |
Age at first marriage > Total > Total | decimal | 0% | - | - |
age_at_first_marriage_total_male |
Age at first marriage > Total > Male | decimal | 0% | - | - |
age_at_first_marriage_total_female |
Age at first marriage > Total > Female | decimal | 0% | - | - |
age_at_first_marriage_under_15_subtotal |
Age at first marriage > Under 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_under_15_male |
Age at first marriage > Under 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_under_15_female |
Age at first marriage > Under 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_15_subtotal |
Age at first marriage > Age 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_15_male |
Age at first marriage > Age 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_15_female |
Age at first marriage > Age 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_16_subtotal |
Age at first marriage > Age 16 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_16_male |
Age at first marriage > Age 16 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_16_female |
Age at first marriage > Age 16 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_17_subtotal |
Age at first marriage > Age 17 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_17_male |
Age at first marriage > Age 17 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_17_female |
Age at first marriage > Age 17 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_18_subtotal |
Age at first marriage > Age 18 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_18_male |
Age at first marriage > Age 18 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_18_female |
Age at first marriage > Age 18 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_19_subtotal |
Age at first marriage > Age 19 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_19_male |
Age at first marriage > Age 19 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_19_female |
Age at first marriage > Age 19 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_20_subtotal |
Age at first marriage > Age 20 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_20_male |
Age at first marriage > Age 20 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_20_female |
Age at first marriage > Age 20 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_21_subtotal |
Age at first marriage > Age 21 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_21_male |
Age at first marriage > Age 21 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_21_female |
Age at first marriage > Age 21 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_22_subtotal |
Age at first marriage > Age 22 > Subtotal | decimal | 0% | - | - |
| +56 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
age_at_first_marriage_total_total |
Age at first marriage > Total > Total | decimal | 0% | - | - |
age_at_first_marriage_total_male |
Age at first marriage > Total > Male | decimal | 0% | - | - |
age_at_first_marriage_total_female |
Age at first marriage > Total > Female | decimal | 0% | - | - |
age_at_first_marriage_under_15_subtotal |
Age at first marriage > Under 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_under_15_male |
Age at first marriage > Under 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_under_15_female |
Age at first marriage > Under 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_15_subtotal |
Age at first marriage > Age 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_15_male |
Age at first marriage > Age 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_15_female |
Age at first marriage > Age 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_16_subtotal |
Age at first marriage > Age 16 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_16_male |
Age at first marriage > Age 16 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_16_female |
Age at first marriage > Age 16 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_17_subtotal |
Age at first marriage > Age 17 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_17_male |
Age at first marriage > Age 17 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_17_female |
Age at first marriage > Age 17 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_18_subtotal |
Age at first marriage > Age 18 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_18_male |
Age at first marriage > Age 18 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_18_female |
Age at first marriage > Age 18 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_19_subtotal |
Age at first marriage > Age 19 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_19_male |
Age at first marriage > Age 19 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_19_female |
Age at first marriage > Age 19 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_20_subtotal |
Age at first marriage > Age 20 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_20_male |
Age at first marriage > Age 20 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_20_female |
Age at first marriage > Age 20 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_21_subtotal |
Age at first marriage > Age 21 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_21_male |
Age at first marriage > Age 21 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_21_female |
Age at first marriage > Age 21 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_22_subtotal |
Age at first marriage > Age 22 > Subtotal | decimal | 0% | - | - |
| +56 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
age_at_first_marriage_total_total |
Age at first marriage > Total > Total | decimal | 0% | - | - |
age_at_first_marriage_total_male |
Age at first marriage > Total > Male | decimal | 0% | - | - |
age_at_first_marriage_total_female |
Age at first marriage > Total > Female | decimal | 0% | - | - |
age_at_first_marriage_under_15_subtotal |
Age at first marriage > Under 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_under_15_male |
Age at first marriage > Under 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_under_15_female |
Age at first marriage > Under 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_15_subtotal |
Age at first marriage > Age 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_15_male |
Age at first marriage > Age 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_15_female |
Age at first marriage > Age 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_16_subtotal |
Age at first marriage > Age 16 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_16_male |
Age at first marriage > Age 16 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_16_female |
Age at first marriage > Age 16 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_17_subtotal |
Age at first marriage > Age 17 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_17_male |
Age at first marriage > Age 17 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_17_female |
Age at first marriage > Age 17 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_18_subtotal |
Age at first marriage > Age 18 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_18_male |
Age at first marriage > Age 18 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_18_female |
Age at first marriage > Age 18 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_19_subtotal |
Age at first marriage > Age 19 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_19_male |
Age at first marriage > Age 19 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_19_female |
Age at first marriage > Age 19 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_20_subtotal |
Age at first marriage > Age 20 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_20_male |
Age at first marriage > Age 20 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_20_female |
Age at first marriage > Age 20 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_21_subtotal |
Age at first marriage > Age 21 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_21_male |
Age at first marriage > Age 21 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_21_female |
Age at first marriage > Age 21 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_22_subtotal |
Age at first marriage > Age 22 > Subtotal | decimal | 0% | - | - |
| +56 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
age_at_first_marriage_total_total |
Age at first marriage > Total > Total | decimal | 0% | - | - |
age_at_first_marriage_total_male |
Age at first marriage > Total > Male | decimal | 0% | - | - |
age_at_first_marriage_total_female |
Age at first marriage > Total > Female | decimal | 0% | - | - |
age_at_first_marriage_under_15_subtotal |
Age at first marriage > Under 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_under_15_male |
Age at first marriage > Under 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_under_15_female |
Age at first marriage > Under 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_15_subtotal |
Age at first marriage > Age 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_15_male |
Age at first marriage > Age 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_15_female |
Age at first marriage > Age 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_16_subtotal |
Age at first marriage > Age 16 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_16_male |
Age at first marriage > Age 16 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_16_female |
Age at first marriage > Age 16 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_17_subtotal |
Age at first marriage > Age 17 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_17_male |
Age at first marriage > Age 17 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_17_female |
Age at first marriage > Age 17 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_18_subtotal |
Age at first marriage > Age 18 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_18_male |
Age at first marriage > Age 18 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_18_female |
Age at first marriage > Age 18 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_19_subtotal |
Age at first marriage > Age 19 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_19_male |
Age at first marriage > Age 19 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_19_female |
Age at first marriage > Age 19 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_20_subtotal |
Age at first marriage > Age 20 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_20_male |
Age at first marriage > Age 20 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_20_female |
Age at first marriage > Age 20 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_21_subtotal |
Age at first marriage > Age 21 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_21_male |
Age at first marriage > Age 21 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_21_female |
Age at first marriage > Age 21 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_22_subtotal |
Age at first marriage > Age 22 > Subtotal | decimal | 0% | - | - |
| +56 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
age_at_first_marriage_total_total |
Age at first marriage > Total > Total | decimal | 0% | - | - |
age_at_first_marriage_total_male |
Age at first marriage > Total > Male | decimal | 0% | - | - |
age_at_first_marriage_total_female |
Age at first marriage > Total > Female | decimal | 0% | - | - |
age_at_first_marriage_under_15_subtotal |
Age at first marriage > Under 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_under_15_male |
Age at first marriage > Under 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_under_15_female |
Age at first marriage > Under 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_15_subtotal |
Age at first marriage > Age 15 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_15_male |
Age at first marriage > Age 15 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_15_female |
Age at first marriage > Age 15 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_16_subtotal |
Age at first marriage > Age 16 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_16_male |
Age at first marriage > Age 16 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_16_female |
Age at first marriage > Age 16 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_17_subtotal |
Age at first marriage > Age 17 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_17_male |
Age at first marriage > Age 17 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_17_female |
Age at first marriage > Age 17 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_18_subtotal |
Age at first marriage > Age 18 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_18_male |
Age at first marriage > Age 18 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_18_female |
Age at first marriage > Age 18 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_19_subtotal |
Age at first marriage > Age 19 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_19_male |
Age at first marriage > Age 19 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_19_female |
Age at first marriage > Age 19 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_20_subtotal |
Age at first marriage > Age 20 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_20_male |
Age at first marriage > Age 20 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_20_female |
Age at first marriage > Age 20 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_21_subtotal |
Age at first marriage > Age 21 > Subtotal | decimal | 0% | - | - |
age_at_first_marriage_age_21_male |
Age at first marriage > Age 21 > Male | decimal | 0% | - | - |
age_at_first_marriage_age_21_female |
Age at first marriage > Age 21 > Female | decimal | 0% | - | - |
age_at_first_marriage_age_22_subtotal |
Age at first marriage > Age 22 > Subtotal | decimal | 0% | - | - |
| +56 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
ⓘ 1-in-10 household sample. These tables come from the census long questionnaire, which about one household in ten answered. The National Bureau of Statistics publishes the sample's own counts without scaling them up, so counts here are about a tenth of the real figure: this sample counted 138,657,945 people, against 1,409,778,724 in the full count. Shares, rates and averages can be used as they are; for population totals use the full-count datasets.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_who_gave_birth_to_a_boy |
Number of women who gave birth to a boy | decimal | 0% | - | - |
number_of_women_who_gave_birth_to_a_girl |
Number of women who gave birth to a girl | decimal | 0% | - | - |
first_birth_subtotal |
First birth > Subtotal | decimal | 0% | - | - |
first_birth_male |
First birth > Male | decimal | 0% | - | - |
first_birth_female |
First birth > Female | decimal | 0% | - | - |
second_birth_subtotal |
Second birth > Subtotal | decimal | 0% | - | - |
second_birth_male |
Second birth > Male | decimal | 0% | - | - |
second_birth_female |
Second birth > Female | decimal | 0% | - | - |
third_birth_or_higher_subtotal |
Third birth or higher > Subtotal | decimal | 0% | - | - |
third_birth_or_higher_male |
Third birth or higher > Male | decimal | 0% | - | - |
third_birth_or_higher_female |
Third birth or higher > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_who_gave_birth_to_a_boy |
Number of women who gave birth to a boy | decimal | 0% | - | - |
number_of_women_who_gave_birth_to_a_girl |
Number of women who gave birth to a girl | decimal | 0% | - | - |
first_birth_subtotal |
First birth > Subtotal | decimal | 0% | - | - |
first_birth_male |
First birth > Male | decimal | 0% | - | - |
first_birth_female |
First birth > Female | decimal | 0% | - | - |
second_birth_subtotal |
Second birth > Subtotal | decimal | 0% | - | - |
second_birth_male |
Second birth > Male | decimal | 0% | - | - |
second_birth_female |
Second birth > Female | decimal | 0% | - | - |
third_birth_or_higher_subtotal |
Third birth or higher > Subtotal | decimal | 0% | - | - |
third_birth_or_higher_male |
Third birth or higher > Male | decimal | 0% | - | - |
third_birth_or_higher_female |
Third birth or higher > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_who_gave_birth_to_a_boy |
Number of women who gave birth to a boy | decimal | 0% | - | - |
number_of_women_who_gave_birth_to_a_girl |
Number of women who gave birth to a girl | decimal | 0% | - | - |
first_birth_subtotal |
First birth > Subtotal | decimal | 0% | - | - |
first_birth_male |
First birth > Male | decimal | 0% | - | - |
first_birth_female |
First birth > Female | decimal | 0% | - | - |
second_birth_subtotal |
Second birth > Subtotal | decimal | 0% | - | - |
second_birth_male |
Second birth > Male | decimal | 0% | - | - |
second_birth_female |
Second birth > Female | decimal | 0% | - | - |
third_birth_or_higher_subtotal |
Third birth or higher > Subtotal | decimal | 0% | - | - |
third_birth_or_higher_male |
Third birth or higher > Male | decimal | 0% | - | - |
third_birth_or_higher_female |
Third birth or higher > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_who_gave_birth_to_a_boy |
Number of women who gave birth to a boy | decimal | 0% | - | - |
number_of_women_who_gave_birth_to_a_girl |
Number of women who gave birth to a girl | decimal | 0% | - | - |
first_birth_subtotal |
First birth > Subtotal | decimal | 0% | - | - |
first_birth_male |
First birth > Male | decimal | 0% | - | - |
first_birth_female |
First birth > Female | decimal | 0% | - | - |
second_birth_subtotal |
Second birth > Subtotal | decimal | 0% | - | - |
second_birth_male |
Second birth > Male | decimal | 0% | - | - |
second_birth_female |
Second birth > Female | decimal | 0% | - | - |
third_birth_or_higher_subtotal |
Third birth or higher > Subtotal | decimal | 0% | - | - |
third_birth_or_higher_male |
Third birth or higher > Male | decimal | 0% | - | - |
third_birth_or_higher_female |
Third birth or higher > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
number_of_births |
Number of births | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
average_number_of_women_of_childbearing_age |
Average number of women of childbearing age | decimal | 0% | - | - |
fertility_rate |
Fertility rate | decimal | 0% | - | - |
first_birth_number_of_births |
First birth > Number of births | decimal | 0% | - | - |
first_birth_fertility_rate |
First birth > Fertility rate | decimal | 0% | - | - |
second_birth_number_of_births |
Second birth > Number of births | decimal | 0% | - | - |
second_birth_fertility_rate |
Second birth > Fertility rate | decimal | 0% | - | - |
third_birth_or_higher_number_of_births |
Third birth or higher > Number of births | decimal | 0% | - | - |
third_birth_or_higher_fertility_rate |
Third birth or higher > Fertility rate | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
number_of_births |
Number of births | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
average_number_of_women_of_childbearing_age |
Average number of women of childbearing age | decimal | 0% | - | - |
fertility_rate |
Fertility rate | decimal | 0% | - | - |
first_birth_number_of_births |
First birth > Number of births | decimal | 0% | - | - |
first_birth_fertility_rate |
First birth > Fertility rate | decimal | 0% | - | - |
second_birth_number_of_births |
Second birth > Number of births | decimal | 0% | - | - |
second_birth_fertility_rate |
Second birth > Fertility rate | decimal | 0% | - | - |
third_birth_or_higher_number_of_births |
Third birth or higher > Number of births | decimal | 0% | - | - |
third_birth_or_higher_fertility_rate |
Third birth or higher > Fertility rate | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
number_of_births |
Number of births | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
average_number_of_women_of_childbearing_age |
Average number of women of childbearing age | decimal | 0% | - | - |
fertility_rate |
Fertility rate | decimal | 0% | - | - |
first_birth_number_of_births |
First birth > Number of births | decimal | 0% | - | - |
first_birth_fertility_rate |
First birth > Fertility rate | decimal | 0% | - | - |
second_birth_number_of_births |
Second birth > Number of births | decimal | 0% | - | - |
second_birth_fertility_rate |
Second birth > Fertility rate | decimal | 0% | - | - |
third_birth_or_higher_number_of_births |
Third birth or higher > Number of births | decimal | 0% | - | - |
third_birth_or_higher_fertility_rate |
Third birth or higher > Fertility rate | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
number_of_births |
Number of births | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
average_number_of_women_of_childbearing_age |
Average number of women of childbearing age | decimal | 0% | - | - |
fertility_rate |
Fertility rate | decimal | 0% | - | - |
first_birth_number_of_births |
First birth > Number of births | decimal | 0% | - | - |
first_birth_fertility_rate |
First birth > Fertility rate | decimal | 0% | - | - |
second_birth_number_of_births |
Second birth > Number of births | decimal | 0% | - | - |
second_birth_fertility_rate |
Second birth > Fertility rate | decimal | 0% | - | - |
third_birth_or_higher_number_of_births |
Third birth or higher > Number of births | decimal | 0% | - | - |
third_birth_or_higher_fertility_rate |
Third birth or higher > Fertility rate | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_aged_15_64 |
Number of women aged 15-64 | decimal | 0% | - | - |
0_live_births |
0 live births | decimal | 0% | - | - |
1_live_birth |
1 live birth | decimal | 0% | - | - |
2_live_births |
2 live births | decimal | 0% | - | - |
3_live_births |
3 live births | decimal | 0% | - | - |
4_live_births |
4 live births | decimal | 0% | - | - |
5_or_more_live_births |
5 or more live births | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_aged_15_64 |
Number of women aged 15-64 | decimal | 0% | - | - |
0_live_births |
0 live births | decimal | 0% | - | - |
1_live_birth |
1 live birth | decimal | 0% | - | - |
2_live_births |
2 live births | decimal | 0% | - | - |
3_live_births |
3 live births | decimal | 0% | - | - |
4_live_births |
4 live births | decimal | 0% | - | - |
5_or_more_live_births |
5 or more live births | decimal | 0% | - | - |
average_live_births_per_woman |
Average live births per woman | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_aged_15_64 |
Number of women aged 15-64 | decimal | 0% | - | - |
0_surviving_children |
0 surviving children | decimal | 0% | - | - |
1_surviving_child |
1 surviving child | decimal | 0% | - | - |
2_surviving_children |
2 surviving children | decimal | 0% | - | - |
3_surviving_children |
3 surviving children | decimal | 0% | - | - |
4_surviving_children |
4 surviving children | decimal | 0% | - | - |
5_or_more_surviving_children |
5 or more surviving children | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_aged_15_64 |
Number of women aged 15-64 | decimal | 0% | - | - |
0_surviving_children |
0 surviving children | decimal | 0% | - | - |
1_surviving_child |
1 surviving child | decimal | 0% | - | - |
2_surviving_children |
2 surviving children | decimal | 0% | - | - |
3_surviving_children |
3 surviving children | decimal | 0% | - | - |
4_surviving_children |
4 surviving children | decimal | 0% | - | - |
5_or_more_surviving_children |
5 or more surviving children | decimal | 0% | - | - |
average_surviving_children_per_woman |
Average surviving children per woman | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_aged_15_64 |
Number of women aged 15-64 | decimal | 0% | - | - |
total_live_births_total |
Total live births > Total | decimal | 0% | - | - |
total_live_births_male |
Total live births > Male | decimal | 0% | - | - |
total_live_births_female |
Total live births > Female | decimal | 0% | - | - |
total_surviving_children_total |
Total surviving children > Total | decimal | 0% | - | - |
total_surviving_children_male |
Total surviving children > Male | decimal | 0% | - | - |
total_surviving_children_female |
Total surviving children > Female | decimal | 0% | - | - |
surviving_children_as_a_percentage_of_live_births |
Surviving children as a percentage of live births | decimal | 0% | - | - |
average_live_births_per_woman |
Average live births per woman | decimal | 0% | - | - |
average_surviving_children_per_woman |
Average surviving children per woman | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_aged_15_64 |
Number of women aged 15-64 | decimal | 0% | - | - |
total_live_births_total |
Total live births > Total | decimal | 0% | - | - |
total_live_births_male |
Total live births > Male | decimal | 0% | - | - |
total_live_births_female |
Total live births > Female | decimal | 0% | - | - |
total_surviving_children_total |
Total surviving children > Total | decimal | 0% | - | - |
total_surviving_children_male |
Total surviving children > Male | decimal | 0% | - | - |
total_surviving_children_female |
Total surviving children > Female | decimal | 0% | - | - |
surviving_children_as_a_percentage_of_live_births |
Surviving children as a percentage of live births | decimal | 0% | - | - |
average_live_births_per_woman |
Average live births per woman | decimal | 0% | - | - |
average_surviving_children_per_woman |
Average surviving children per woman | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_births_total |
Number of births > Total | decimal | 0% | - | - |
number_of_births_male |
Number of births > Male | decimal | 0% | - | - |
number_of_births_female |
Number of births > Female | decimal | 0% | - | - |
number_of_births_sex_ratio_female_100 |
Number of births > Sex ratio (female=100) | decimal | 0% | - | - |
first_birth_subtotal |
First birth > Subtotal | decimal | 0% | - | - |
first_birth_male |
First birth > Male | decimal | 0% | - | - |
first_birth_female |
First birth > Female | decimal | 0% | - | - |
first_birth_sex_ratio_female_100 |
First birth > Sex ratio (female=100) | decimal | 0% | - | - |
second_birth_subtotal |
Second birth > Subtotal | decimal | 0% | - | - |
second_birth_male |
Second birth > Male | decimal | 0% | - | - |
second_birth_female |
Second birth > Female | decimal | 0% | - | - |
second_birth_sex_ratio_female_100 |
Second birth > Sex ratio (female=100) | decimal | 0% | - | - |
third_birth_subtotal |
Third birth > Subtotal | decimal | 0% | - | - |
third_birth_male |
Third birth > Male | decimal | 0% | - | - |
third_birth_female |
Third birth > Female | decimal | 0% | - | - |
third_birth_sex_ratio_female_100 |
Third birth > Sex ratio (female=100) | decimal | 0% | - | - |
fourth_birth_subtotal |
Fourth birth > Subtotal | decimal | 0% | - | - |
fourth_birth_male |
Fourth birth > Male | decimal | 0% | - | - |
fourth_birth_female |
Fourth birth > Female | decimal | 0% | - | - |
fourth_birth_sex_ratio_female_100 |
Fourth birth > Sex ratio (female=100) | decimal | 0% | - | - |
fifth_birth_or_higher_subtotal |
Fifth birth or higher > Subtotal | decimal | 0% | - | - |
fifth_birth_or_higher_male |
Fifth birth or higher > Male | decimal | 0% | - | - |
fifth_birth_or_higher_female |
Fifth birth or higher > Female | decimal | 0% | - | - |
fifth_birth_or_higher_sex_ratio_female_100 |
Fifth birth or higher > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_births_total |
Number of births > Total | decimal | 0% | - | - |
number_of_births_male |
Number of births > Male | decimal | 0% | - | - |
number_of_births_female |
Number of births > Female | decimal | 0% | - | - |
number_of_births_sex_ratio_female_100 |
Number of births > Sex ratio (female=100) | decimal | 0% | - | - |
first_birth_subtotal |
First birth > Subtotal | decimal | 0% | - | - |
first_birth_male |
First birth > Male | decimal | 0% | - | - |
first_birth_female |
First birth > Female | decimal | 0% | - | - |
first_birth_sex_ratio_female_100 |
First birth > Sex ratio (female=100) | decimal | 0% | - | - |
second_birth_subtotal |
Second birth > Subtotal | decimal | 0% | - | - |
second_birth_male |
Second birth > Male | decimal | 0% | - | - |
second_birth_female |
Second birth > Female | decimal | 0% | - | - |
second_birth_sex_ratio_female_100 |
Second birth > Sex ratio (female=100) | decimal | 0% | - | - |
third_birth_subtotal |
Third birth > Subtotal | decimal | 0% | - | - |
third_birth_male |
Third birth > Male | decimal | 0% | - | - |
third_birth_female |
Third birth > Female | decimal | 0% | - | - |
third_birth_sex_ratio_female_100 |
Third birth > Sex ratio (female=100) | decimal | 0% | - | - |
fourth_birth_subtotal |
Fourth birth > Subtotal | decimal | 0% | - | - |
fourth_birth_male |
Fourth birth > Male | decimal | 0% | - | - |
fourth_birth_female |
Fourth birth > Female | decimal | 0% | - | - |
fourth_birth_sex_ratio_female_100 |
Fourth birth > Sex ratio (female=100) | decimal | 0% | - | - |
fifth_birth_or_higher_subtotal |
Fifth birth or higher > Subtotal | decimal | 0% | - | - |
fifth_birth_or_higher_male |
Fifth birth or higher > Male | decimal | 0% | - | - |
fifth_birth_or_higher_female |
Fifth birth or higher > Female | decimal | 0% | - | - |
fifth_birth_or_higher_sex_ratio_female_100 |
Fifth birth or higher > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_births_total |
Number of births > Total | decimal | 0% | - | - |
number_of_births_male |
Number of births > Male | decimal | 0% | - | - |
number_of_births_female |
Number of births > Female | decimal | 0% | - | - |
number_of_births_sex_ratio_female_100 |
Number of births > Sex ratio (female=100) | decimal | 0% | - | - |
first_birth_subtotal |
First birth > Subtotal | decimal | 0% | - | - |
first_birth_male |
First birth > Male | decimal | 0% | - | - |
first_birth_female |
First birth > Female | decimal | 0% | - | - |
first_birth_sex_ratio_female_100 |
First birth > Sex ratio (female=100) | decimal | 0% | - | - |
second_birth_subtotal |
Second birth > Subtotal | decimal | 0% | - | - |
second_birth_male |
Second birth > Male | decimal | 0% | - | - |
second_birth_female |
Second birth > Female | decimal | 0% | - | - |
second_birth_sex_ratio_female_100 |
Second birth > Sex ratio (female=100) | decimal | 0% | - | - |
third_birth_subtotal |
Third birth > Subtotal | decimal | 0% | - | - |
third_birth_male |
Third birth > Male | decimal | 0% | - | - |
third_birth_female |
Third birth > Female | decimal | 0% | - | - |
third_birth_sex_ratio_female_100 |
Third birth > Sex ratio (female=100) | decimal | 0% | - | - |
fourth_birth_subtotal |
Fourth birth > Subtotal | decimal | 0% | - | - |
fourth_birth_male |
Fourth birth > Male | decimal | 0% | - | - |
fourth_birth_female |
Fourth birth > Female | decimal | 0% | - | - |
fourth_birth_sex_ratio_female_100 |
Fourth birth > Sex ratio (female=100) | decimal | 0% | - | - |
fifth_birth_or_higher_subtotal |
Fifth birth or higher > Subtotal | decimal | 0% | - | - |
fifth_birth_or_higher_male |
Fifth birth or higher > Male | decimal | 0% | - | - |
fifth_birth_or_higher_female |
Fifth birth or higher > Female | decimal | 0% | - | - |
fifth_birth_or_higher_sex_ratio_female_100 |
Fifth birth or higher > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_births_total |
Number of births > Total | decimal | 0% | - | - |
number_of_births_male |
Number of births > Male | decimal | 0% | - | - |
number_of_births_female |
Number of births > Female | decimal | 0% | - | - |
number_of_births_sex_ratio_female_100 |
Number of births > Sex ratio (female=100) | decimal | 0% | - | - |
first_birth_subtotal |
First birth > Subtotal | decimal | 0% | - | - |
first_birth_male |
First birth > Male | decimal | 0% | - | - |
first_birth_female |
First birth > Female | decimal | 0% | - | - |
first_birth_sex_ratio_female_100 |
First birth > Sex ratio (female=100) | decimal | 0% | - | - |
second_birth_subtotal |
Second birth > Subtotal | decimal | 0% | - | - |
second_birth_male |
Second birth > Male | decimal | 0% | - | - |
second_birth_female |
Second birth > Female | decimal | 0% | - | - |
second_birth_sex_ratio_female_100 |
Second birth > Sex ratio (female=100) | decimal | 0% | - | - |
third_birth_subtotal |
Third birth > Subtotal | decimal | 0% | - | - |
third_birth_male |
Third birth > Male | decimal | 0% | - | - |
third_birth_female |
Third birth > Female | decimal | 0% | - | - |
third_birth_sex_ratio_female_100 |
Third birth > Sex ratio (female=100) | decimal | 0% | - | - |
fourth_birth_subtotal |
Fourth birth > Subtotal | decimal | 0% | - | - |
fourth_birth_male |
Fourth birth > Male | decimal | 0% | - | - |
fourth_birth_female |
Fourth birth > Female | decimal | 0% | - | - |
fourth_birth_sex_ratio_female_100 |
Fourth birth > Sex ratio (female=100) | decimal | 0% | - | - |
fifth_birth_or_higher_subtotal |
Fifth birth or higher > Subtotal | decimal | 0% | - | - |
fifth_birth_or_higher_male |
Fifth birth or higher > Male | decimal | 0% | - | - |
fifth_birth_or_higher_female |
Fifth birth or higher > Female | decimal | 0% | - | - |
fifth_birth_or_higher_sex_ratio_female_100 |
Fifth birth or higher > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total_fertility_rate |
Total fertility rate | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
ages_15_19 |
Ages 15-19 | decimal | 0% | - | - |
ages_20_24 |
Ages 20-24 | decimal | 0% | - | - |
ages_25_29 |
Ages 25-29 | decimal | 0% | - | - |
ages_30_34 |
Ages 30-34 | decimal | 0% | - | - |
ages_35_39 |
Ages 35-39 | decimal | 0% | - | - |
ages_40_44 |
Ages 40-44 | decimal | 0% | - | - |
ages_45_49 |
Ages 45-49 | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total_fertility_rate |
Total fertility rate | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
ages_15_19 |
Ages 15-19 | decimal | 0% | - | - |
ages_20_24 |
Ages 20-24 | decimal | 0% | - | - |
ages_25_29 |
Ages 25-29 | decimal | 0% | - | - |
ages_30_34 |
Ages 30-34 | decimal | 0% | - | - |
ages_35_39 |
Ages 35-39 | decimal | 0% | - | - |
ages_40_44 |
Ages 40-44 | decimal | 0% | - | - |
ages_45_49 |
Ages 45-49 | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total_fertility_rate |
Total fertility rate | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
ages_15_19 |
Ages 15-19 | decimal | 0% | - | - |
ages_20_24 |
Ages 20-24 | decimal | 0% | - | - |
ages_25_29 |
Ages 25-29 | decimal | 0% | - | - |
ages_30_34 |
Ages 30-34 | decimal | 0% | - | - |
ages_35_39 |
Ages 35-39 | decimal | 0% | - | - |
ages_40_44 |
Ages 40-44 | decimal | 0% | - | - |
ages_45_49 |
Ages 45-49 | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total_fertility_rate |
Total fertility rate | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
ages_15_19 |
Ages 15-19 | decimal | 0% | - | - |
ages_20_24 |
Ages 20-24 | decimal | 0% | - | - |
ages_25_29 |
Ages 25-29 | decimal | 0% | - | - |
ages_30_34 |
Ages 30-34 | decimal | 0% | - | - |
ages_35_39 |
Ages 35-39 | decimal | 0% | - | - |
ages_40_44 |
Ages 40-44 | decimal | 0% | - | - |
ages_45_49 |
Ages 45-49 | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_aged_15_64 |
Number of women aged 15-64 | decimal | 0% | - | - |
0_live_births |
0 live births | decimal | 0% | - | - |
1_live_birth |
1 live birth | decimal | 0% | - | - |
2_live_births |
2 live births | decimal | 0% | - | - |
3_live_births |
3 live births | decimal | 0% | - | - |
4_live_births |
4 live births | decimal | 0% | - | - |
5_or_more_live_births |
5 or more live births | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_aged_15_64 |
Number of women aged 15-64 | decimal | 0% | - | - |
0_surviving_children |
0 surviving children | decimal | 0% | - | - |
1_surviving_child |
1 surviving child | decimal | 0% | - | - |
2_surviving_children |
2 surviving children | decimal | 0% | - | - |
3_surviving_children |
3 surviving children | decimal | 0% | - | - |
4_surviving_children |
4 surviving children | decimal | 0% | - | - |
5_or_more_surviving_children |
5 or more surviving children | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_aged_15_64 |
Number of women aged 15-64 | decimal | 0% | - | - |
total_live_births_total |
Total live births > Total | decimal | 0% | - | - |
total_live_births_male |
Total live births > Male | decimal | 0% | - | - |
total_live_births_female |
Total live births > Female | decimal | 0% | - | - |
total_surviving_children_total |
Total surviving children > Total | decimal | 0% | - | - |
total_surviving_children_male |
Total surviving children > Male | decimal | 0% | - | - |
total_surviving_children_female |
Total surviving children > Female | decimal | 0% | - | - |
surviving_children_as_a_percentage_of_live_births |
Surviving children as a percentage of live births | decimal | 0% | - | - |
average_live_births_per_woman |
Average live births per woman | decimal | 0% | - | - |
average_surviving_children_per_woman |
Average surviving children per woman | decimal | 0% | - | - |
ⓘ 1-in-10 household sample. These tables come from the census long questionnaire, which about one household in ten answered. The National Bureau of Statistics publishes the sample's own counts without scaling them up, so counts here are about a tenth of the real figure: this sample counted 138,657,945 people, against 1,409,778,724 in the full count. Shares, rates and averages can be used as they are; for population totals use the full-count datasets.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
never_attended_school |
Never attended school | decimal | SEL | 0% | - | - |
primary_school |
Primary school | decimal | SEL | 0% | - | - |
senior_secondary_school |
Senior secondary school | decimal | SEL | 0% | - | - |
university_undergraduate |
University (undergraduate) | decimal | SEL | 0% | - | - |
postgraduate_master_s |
Postgraduate (Master's) | decimal | SEL | 0% | - | - |
postgraduate_doctoral |
Postgraduate (Doctoral) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
pre_school_education |
Pre-school education | decimal | 0% | - | - |
junior_secondary_school |
Junior secondary school | decimal | 0% | - | - |
junior_college |
Junior college | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
never_attended_school |
Never attended school | decimal | SEL | 0% | - | - |
primary_school |
Primary school | decimal | SEL | 0% | - | - |
senior_secondary_school |
Senior secondary school | decimal | SEL | 0% | - | - |
university_undergraduate |
University (undergraduate) | decimal | SEL | 0% | - | - |
postgraduate_master_s |
Postgraduate (Master's) | decimal | SEL | 0% | - | - |
postgraduate_doctoral |
Postgraduate (Doctoral) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
pre_school_education |
Pre-school education | decimal | 0% | - | - |
junior_secondary_school |
Junior secondary school | decimal | 0% | - | - |
junior_college |
Junior college | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
never_attended_school |
Never attended school | decimal | SEL | 0% | - | - |
primary_school |
Primary school | decimal | SEL | 0% | - | - |
senior_secondary_school |
Senior secondary school | decimal | SEL | 0% | - | - |
university_undergraduate |
University (undergraduate) | decimal | SEL | 0% | - | - |
postgraduate_master_s |
Postgraduate (Master's) | decimal | SEL | 0% | - | - |
postgraduate_doctoral |
Postgraduate (Doctoral) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
pre_school_education |
Pre-school education | decimal | 0% | - | - |
junior_secondary_school |
Junior secondary school | decimal | 0% | - | - |
junior_college |
Junior college | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
never_attended_school |
Never attended school | decimal | SEL | 0% | - | - |
primary_school |
Primary school | decimal | SEL | 0% | - | - |
senior_secondary_school |
Senior secondary school | decimal | SEL | 0% | - | - |
university_undergraduate |
University (undergraduate) | decimal | SEL | 0% | - | - |
postgraduate_master_s |
Postgraduate (Master's) | decimal | SEL | 0% | - | - |
postgraduate_doctoral |
Postgraduate (Doctoral) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
pre_school_education |
Pre-school education | decimal | 0% | - | - |
junior_secondary_school |
Junior secondary school | decimal | 0% | - | - |
junior_college |
Junior college | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_subtotal |
Agriculture, forestry, animal husbandry and fishery > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_farming |
Agriculture, forestry, animal husbandry and fishery > Farming | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_forestry |
Agriculture, forestry, animal husbandry and fishery > Forestry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_animal_h |
Agriculture, forestry, animal husbandry and fishery > Animal husbandry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_fishery |
Agriculture, forestry, animal husbandry and fishery > Fishery | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_professi |
Agriculture, forestry, animal husbandry and fishery > Professional and support activities for agriculture, forestry, animal husbandry and fishery | decimal | 0% | - | - |
mining_subtotal |
Mining > Subtotal | decimal | 0% | - | - |
mining_coal_mining_and_washing |
Mining > Coal mining and washing | decimal | 0% | - | - |
mining_oil_and_natural_gas_extraction |
Mining > Oil and natural gas extraction | decimal | 0% | - | - |
mining_ferrous_metal_mining_and_dressing |
Mining > Ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_ferrous_metal_mining_and_dressing |
Mining > Non-ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_metallic_mineral_mining_and_dressing |
Mining > Non-metallic mineral mining and dressing | decimal | 0% | - | - |
mining_professional_and_support_activities_for_mining |
Mining > Professional and support activities for mining | decimal | 0% | - | - |
mining_other_mining |
Mining > Other mining | decimal | 0% | - | - |
manufacturing_subtotal |
Manufacturing > Subtotal | decimal | 0% | - | - |
manufacturing_processing_of_food_from_agricultural_product |
Manufacturing > Processing of food from agricultural products | decimal | 0% | - | - |
manufacturing_food_manufacturing |
Manufacturing > Food manufacturing | decimal | 0% | - | - |
manufacturing_liquor_beverage_and_refined_tea_manufacturin |
Manufacturing > Liquor, beverage and refined tea manufacturing | decimal | 0% | - | - |
manufacturing_tobacco_products |
Manufacturing > Tobacco products | decimal | 0% | - | - |
manufacturing_textiles |
Manufacturing > Textiles | decimal | 0% | - | - |
manufacturing_manufacture_of_textile_wearing_apparel_and_a |
Manufacturing > Manufacture of textile wearing apparel and accessories | decimal | 0% | - | - |
manufacturing_leather_fur_feather_and_related_products_and |
Manufacturing > Leather, fur, feather and related products and footwear | decimal | 0% | - | - |
manufacturing_processing_of_wood_and_products_of_wood_bamb |
Manufacturing > Processing of wood and products of wood, bamboo, rattan, palm and straw | decimal | 0% | - | - |
manufacturing_furniture_manufacturing |
Manufacturing > Furniture manufacturing | decimal | 0% | - | - |
manufacturing_paper_and_paper_products |
Manufacturing > Paper and paper products | decimal | 0% | - | - |
manufacturing_printing_and_reproduction_of_recording_media |
Manufacturing > Printing and reproduction of recording media | decimal | 0% | - | - |
manufacturing_manufacture_of_culture_education_arts_and_cr |
Manufacturing > Manufacture of culture, education, arts and crafts, sports and entertainment goods | decimal | 0% | - | - |
manufacturing_processing_of_petroleum_coal_and_other_fuels |
Manufacturing > Processing of petroleum, coal and other fuels | decimal | 0% | - | - |
| +89 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_subtotal |
Agriculture, forestry, animal husbandry and fishery > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_farming |
Agriculture, forestry, animal husbandry and fishery > Farming | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_forestry |
Agriculture, forestry, animal husbandry and fishery > Forestry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_animal_h |
Agriculture, forestry, animal husbandry and fishery > Animal husbandry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_fishery |
Agriculture, forestry, animal husbandry and fishery > Fishery | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_professi |
Agriculture, forestry, animal husbandry and fishery > Professional and support activities for agriculture, forestry, animal husbandry and fishery | decimal | 0% | - | - |
mining_subtotal |
Mining > Subtotal | decimal | 0% | - | - |
mining_coal_mining_and_washing |
Mining > Coal mining and washing | decimal | 0% | - | - |
mining_oil_and_natural_gas_extraction |
Mining > Oil and natural gas extraction | decimal | 0% | - | - |
mining_ferrous_metal_mining_and_dressing |
Mining > Ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_ferrous_metal_mining_and_dressing |
Mining > Non-ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_metallic_mineral_mining_and_dressing |
Mining > Non-metallic mineral mining and dressing | decimal | 0% | - | - |
mining_professional_and_support_activities_for_mining |
Mining > Professional and support activities for mining | decimal | 0% | - | - |
mining_other_mining |
Mining > Other mining | decimal | 0% | - | - |
manufacturing_subtotal |
Manufacturing > Subtotal | decimal | 0% | - | - |
manufacturing_processing_of_food_from_agricultural_product |
Manufacturing > Processing of food from agricultural products | decimal | 0% | - | - |
manufacturing_food_manufacturing |
Manufacturing > Food manufacturing | decimal | 0% | - | - |
manufacturing_liquor_beverage_and_refined_tea_manufacturin |
Manufacturing > Liquor, beverage and refined tea manufacturing | decimal | 0% | - | - |
manufacturing_tobacco_products |
Manufacturing > Tobacco products | decimal | 0% | - | - |
manufacturing_textiles |
Manufacturing > Textiles | decimal | 0% | - | - |
manufacturing_manufacture_of_textile_wearing_apparel_and_a |
Manufacturing > Manufacture of textile wearing apparel and accessories | decimal | 0% | - | - |
manufacturing_leather_fur_feather_and_related_products_and |
Manufacturing > Leather, fur, feather and related products and footwear | decimal | 0% | - | - |
manufacturing_processing_of_wood_and_products_of_wood_bamb |
Manufacturing > Processing of wood and products of wood, bamboo, rattan, palm and straw | decimal | 0% | - | - |
manufacturing_furniture_manufacturing |
Manufacturing > Furniture manufacturing | decimal | 0% | - | - |
manufacturing_paper_and_paper_products |
Manufacturing > Paper and paper products | decimal | 0% | - | - |
manufacturing_printing_and_reproduction_of_recording_media |
Manufacturing > Printing and reproduction of recording media | decimal | 0% | - | - |
manufacturing_manufacture_of_culture_education_arts_and_cr |
Manufacturing > Manufacture of culture, education, arts and crafts, sports and entertainment goods | decimal | 0% | - | - |
manufacturing_processing_of_petroleum_coal_and_other_fuels |
Manufacturing > Processing of petroleum, coal and other fuels | decimal | 0% | - | - |
| +89 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_subtotal |
Agriculture, forestry, animal husbandry and fishery > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_farming |
Agriculture, forestry, animal husbandry and fishery > Farming | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_forestry |
Agriculture, forestry, animal husbandry and fishery > Forestry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_animal_h |
Agriculture, forestry, animal husbandry and fishery > Animal husbandry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_fishery |
Agriculture, forestry, animal husbandry and fishery > Fishery | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_professi |
Agriculture, forestry, animal husbandry and fishery > Professional and support activities for agriculture, forestry, animal husbandry and fishery | decimal | 0% | - | - |
mining_subtotal |
Mining > Subtotal | decimal | 0% | - | - |
mining_coal_mining_and_washing |
Mining > Coal mining and washing | decimal | 0% | - | - |
mining_oil_and_natural_gas_extraction |
Mining > Oil and natural gas extraction | decimal | 0% | - | - |
mining_ferrous_metal_mining_and_dressing |
Mining > Ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_ferrous_metal_mining_and_dressing |
Mining > Non-ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_metallic_mineral_mining_and_dressing |
Mining > Non-metallic mineral mining and dressing | decimal | 0% | - | - |
mining_professional_and_support_activities_for_mining |
Mining > Professional and support activities for mining | decimal | 0% | - | - |
mining_other_mining |
Mining > Other mining | decimal | 0% | - | - |
manufacturing_subtotal |
Manufacturing > Subtotal | decimal | 0% | - | - |
manufacturing_processing_of_food_from_agricultural_product |
Manufacturing > Processing of food from agricultural products | decimal | 0% | - | - |
manufacturing_food_manufacturing |
Manufacturing > Food manufacturing | decimal | 0% | - | - |
manufacturing_liquor_beverage_and_refined_tea_manufacturin |
Manufacturing > Liquor, beverage and refined tea manufacturing | decimal | 0% | - | - |
manufacturing_tobacco_products |
Manufacturing > Tobacco products | decimal | 0% | - | - |
manufacturing_textiles |
Manufacturing > Textiles | decimal | 0% | - | - |
manufacturing_manufacture_of_textile_wearing_apparel_and_a |
Manufacturing > Manufacture of textile wearing apparel and accessories | decimal | 0% | - | - |
manufacturing_leather_fur_feather_and_related_products_and |
Manufacturing > Leather, fur, feather and related products and footwear | decimal | 0% | - | - |
manufacturing_processing_of_wood_and_products_of_wood_bamb |
Manufacturing > Processing of wood and products of wood, bamboo, rattan, palm and straw | decimal | 0% | - | - |
manufacturing_furniture_manufacturing |
Manufacturing > Furniture manufacturing | decimal | 0% | - | - |
manufacturing_paper_and_paper_products |
Manufacturing > Paper and paper products | decimal | 0% | - | - |
manufacturing_printing_and_reproduction_of_recording_media |
Manufacturing > Printing and reproduction of recording media | decimal | 0% | - | - |
manufacturing_manufacture_of_culture_education_arts_and_cr |
Manufacturing > Manufacture of culture, education, arts and crafts, sports and entertainment goods | decimal | 0% | - | - |
manufacturing_processing_of_petroleum_coal_and_other_fuels |
Manufacturing > Processing of petroleum, coal and other fuels | decimal | 0% | - | - |
| +89 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_subtotal |
Agriculture, forestry, animal husbandry and fishery > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_farming |
Agriculture, forestry, animal husbandry and fishery > Farming | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_forestry |
Agriculture, forestry, animal husbandry and fishery > Forestry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_animal_h |
Agriculture, forestry, animal husbandry and fishery > Animal husbandry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_fishery |
Agriculture, forestry, animal husbandry and fishery > Fishery | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_professi |
Agriculture, forestry, animal husbandry and fishery > Professional and support activities for agriculture, forestry, animal husbandry and fishery | decimal | 0% | - | - |
mining_subtotal |
Mining > Subtotal | decimal | 0% | - | - |
mining_coal_mining_and_washing |
Mining > Coal mining and washing | decimal | 0% | - | - |
mining_oil_and_natural_gas_extraction |
Mining > Oil and natural gas extraction | decimal | 0% | - | - |
mining_ferrous_metal_mining_and_dressing |
Mining > Ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_ferrous_metal_mining_and_dressing |
Mining > Non-ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_metallic_mineral_mining_and_dressing |
Mining > Non-metallic mineral mining and dressing | decimal | 0% | - | - |
mining_professional_and_support_activities_for_mining |
Mining > Professional and support activities for mining | decimal | 0% | - | - |
mining_other_mining |
Mining > Other mining | decimal | 0% | - | - |
manufacturing_subtotal |
Manufacturing > Subtotal | decimal | 0% | - | - |
manufacturing_processing_of_food_from_agricultural_product |
Manufacturing > Processing of food from agricultural products | decimal | 0% | - | - |
manufacturing_food_manufacturing |
Manufacturing > Food manufacturing | decimal | 0% | - | - |
manufacturing_liquor_beverage_and_refined_tea_manufacturin |
Manufacturing > Liquor, beverage and refined tea manufacturing | decimal | 0% | - | - |
manufacturing_tobacco_products |
Manufacturing > Tobacco products | decimal | 0% | - | - |
manufacturing_textiles |
Manufacturing > Textiles | decimal | 0% | - | - |
manufacturing_manufacture_of_textile_wearing_apparel_and_a |
Manufacturing > Manufacture of textile wearing apparel and accessories | decimal | 0% | - | - |
manufacturing_leather_fur_feather_and_related_products_and |
Manufacturing > Leather, fur, feather and related products and footwear | decimal | 0% | - | - |
manufacturing_processing_of_wood_and_products_of_wood_bamb |
Manufacturing > Processing of wood and products of wood, bamboo, rattan, palm and straw | decimal | 0% | - | - |
manufacturing_furniture_manufacturing |
Manufacturing > Furniture manufacturing | decimal | 0% | - | - |
manufacturing_paper_and_paper_products |
Manufacturing > Paper and paper products | decimal | 0% | - | - |
manufacturing_printing_and_reproduction_of_recording_media |
Manufacturing > Printing and reproduction of recording media | decimal | 0% | - | - |
manufacturing_manufacture_of_culture_education_arts_and_cr |
Manufacturing > Manufacture of culture, education, arts and crafts, sports and entertainment goods | decimal | 0% | - | - |
manufacturing_processing_of_petroleum_coal_and_other_fuels |
Manufacturing > Processing of petroleum, coal and other fuels | decimal | 0% | - | - |
| +89 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of organs of the Communist Party of China | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of state organs | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_4 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of democratic parties and federations of industry and commerce | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_5 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of people's organizations, mass organizations, social organizations and other membership organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_6 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of community-level self-governing organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_7 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of enterprises and public institutions | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_scientific_research_p |
Professional and technical personnel > Scientific research personnel | decimal | 0% | - | - |
professional_and_technical_personnel_engineering_and_techn |
Professional and technical personnel > Engineering and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_agricultural_technica |
Professional and technical personnel > Agricultural technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_aircraft_and_ship_tec |
Professional and technical personnel > Aircraft and ship technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_health_professional_a |
Professional and technical personnel > Health professional and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_economic_and_financia |
Professional and technical personnel > Economic and financial professionals | decimal | 0% | - | - |
professional_and_technical_personnel_legal_social_and_reli |
Professional and technical personnel > Legal, social and religious professionals | decimal | 0% | - | - |
professional_and_technical_personnel_teaching_personnel |
Professional and technical personnel > Teaching personnel | decimal | 0% | - | - |
professional_and_technical_personnel_literature_art_and_sp |
Professional and technical personnel > Literature, art and sports professionals | decimal | 0% | - | - |
professional_and_technical_personnel_news_publishing_and_c |
Professional and technical personnel > News, publishing and cultural professionals | decimal | 0% | - | - |
professional_and_technical_personnel_other_professional_an |
Professional and technical personnel > Other professional and technical personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_clerical_staff |
Clerical staff and related personnel > Clerical staff | decimal | 0% | - | - |
clerical_staff_and_related_personnel_security_and_fire_fig |
Clerical staff and related personnel > Security and fire-fighting personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_other_clerical_staff_ |
Clerical staff and related personnel > Other clerical staff and related personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_wholesale_a |
Social production and living service personnel > Wholesale and retail service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_transport_s |
Social production and living service personnel > Transport, storage and postal service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_accommodati |
Social production and living service personnel > Accommodation and catering service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_information |
Social production and living service personnel > Information transmission, software and information technology service personnel | decimal | 0% | - | - |
| +52 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of organs of the Communist Party of China | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of state organs | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_4 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of democratic parties and federations of industry and commerce | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_5 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of people's organizations, mass organizations, social organizations and other membership organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_6 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of community-level self-governing organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_7 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of enterprises and public institutions | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_scientific_research_p |
Professional and technical personnel > Scientific research personnel | decimal | 0% | - | - |
professional_and_technical_personnel_engineering_and_techn |
Professional and technical personnel > Engineering and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_agricultural_technica |
Professional and technical personnel > Agricultural technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_aircraft_and_ship_tec |
Professional and technical personnel > Aircraft and ship technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_health_professional_a |
Professional and technical personnel > Health professional and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_economic_and_financia |
Professional and technical personnel > Economic and financial professionals | decimal | 0% | - | - |
professional_and_technical_personnel_legal_social_and_reli |
Professional and technical personnel > Legal, social and religious professionals | decimal | 0% | - | - |
professional_and_technical_personnel_teaching_personnel |
Professional and technical personnel > Teaching personnel | decimal | 0% | - | - |
professional_and_technical_personnel_literature_art_and_sp |
Professional and technical personnel > Literature, art and sports professionals | decimal | 0% | - | - |
professional_and_technical_personnel_news_publishing_and_c |
Professional and technical personnel > News, publishing and cultural professionals | decimal | 0% | - | - |
professional_and_technical_personnel_other_professional_an |
Professional and technical personnel > Other professional and technical personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_clerical_staff |
Clerical staff and related personnel > Clerical staff | decimal | 0% | - | - |
clerical_staff_and_related_personnel_security_and_fire_fig |
Clerical staff and related personnel > Security and fire-fighting personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_other_clerical_staff_ |
Clerical staff and related personnel > Other clerical staff and related personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_wholesale_a |
Social production and living service personnel > Wholesale and retail service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_transport_s |
Social production and living service personnel > Transport, storage and postal service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_accommodati |
Social production and living service personnel > Accommodation and catering service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_information |
Social production and living service personnel > Information transmission, software and information technology service personnel | decimal | 0% | - | - |
| +52 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of organs of the Communist Party of China | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of state organs | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_4 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of democratic parties and federations of industry and commerce | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_5 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of people's organizations, mass organizations, social organizations and other membership organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_6 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of community-level self-governing organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_7 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of enterprises and public institutions | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_scientific_research_p |
Professional and technical personnel > Scientific research personnel | decimal | 0% | - | - |
professional_and_technical_personnel_engineering_and_techn |
Professional and technical personnel > Engineering and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_agricultural_technica |
Professional and technical personnel > Agricultural technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_aircraft_and_ship_tec |
Professional and technical personnel > Aircraft and ship technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_health_professional_a |
Professional and technical personnel > Health professional and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_economic_and_financia |
Professional and technical personnel > Economic and financial professionals | decimal | 0% | - | - |
professional_and_technical_personnel_legal_social_and_reli |
Professional and technical personnel > Legal, social and religious professionals | decimal | 0% | - | - |
professional_and_technical_personnel_teaching_personnel |
Professional and technical personnel > Teaching personnel | decimal | 0% | - | - |
professional_and_technical_personnel_literature_art_and_sp |
Professional and technical personnel > Literature, art and sports professionals | decimal | 0% | - | - |
professional_and_technical_personnel_news_publishing_and_c |
Professional and technical personnel > News, publishing and cultural professionals | decimal | 0% | - | - |
professional_and_technical_personnel_other_professional_an |
Professional and technical personnel > Other professional and technical personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_clerical_staff |
Clerical staff and related personnel > Clerical staff | decimal | 0% | - | - |
clerical_staff_and_related_personnel_security_and_fire_fig |
Clerical staff and related personnel > Security and fire-fighting personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_other_clerical_staff_ |
Clerical staff and related personnel > Other clerical staff and related personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_wholesale_a |
Social production and living service personnel > Wholesale and retail service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_transport_s |
Social production and living service personnel > Transport, storage and postal service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_accommodati |
Social production and living service personnel > Accommodation and catering service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_information |
Social production and living service personnel > Information transmission, software and information technology service personnel | decimal | 0% | - | - |
| +52 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of organs of the Communist Party of China | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of state organs | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_4 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of democratic parties and federations of industry and commerce | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_5 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of people's organizations, mass organizations, social organizations and other membership organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_6 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of community-level self-governing organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_7 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of enterprises and public institutions | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_scientific_research_p |
Professional and technical personnel > Scientific research personnel | decimal | 0% | - | - |
professional_and_technical_personnel_engineering_and_techn |
Professional and technical personnel > Engineering and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_agricultural_technica |
Professional and technical personnel > Agricultural technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_aircraft_and_ship_tec |
Professional and technical personnel > Aircraft and ship technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_health_professional_a |
Professional and technical personnel > Health professional and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_economic_and_financia |
Professional and technical personnel > Economic and financial professionals | decimal | 0% | - | - |
professional_and_technical_personnel_legal_social_and_reli |
Professional and technical personnel > Legal, social and religious professionals | decimal | 0% | - | - |
professional_and_technical_personnel_teaching_personnel |
Professional and technical personnel > Teaching personnel | decimal | 0% | - | - |
professional_and_technical_personnel_literature_art_and_sp |
Professional and technical personnel > Literature, art and sports professionals | decimal | 0% | - | - |
professional_and_technical_personnel_news_publishing_and_c |
Professional and technical personnel > News, publishing and cultural professionals | decimal | 0% | - | - |
professional_and_technical_personnel_other_professional_an |
Professional and technical personnel > Other professional and technical personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_clerical_staff |
Clerical staff and related personnel > Clerical staff | decimal | 0% | - | - |
clerical_staff_and_related_personnel_security_and_fire_fig |
Clerical staff and related personnel > Security and fire-fighting personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_other_clerical_staff_ |
Clerical staff and related personnel > Other clerical staff and related personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_wholesale_a |
Social production and living service personnel > Wholesale and retail service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_transport_s |
Social production and living service personnel > Transport, storage and postal service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_accommodati |
Social production and living service personnel > Accommodation and catering service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_information |
Social production and living service personnel > Information transmission, software and information technology service personnel | decimal | 0% | - | - |
| +52 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
ages_16_19 |
Ages 16-19 | decimal | 0% | - | - |
ages_20_24 |
Ages 20-24 | decimal | 0% | - | - |
ages_25_29 |
Ages 25-29 | decimal | 0% | - | - |
ages_30_34 |
Ages 30-34 | decimal | 0% | - | - |
ages_35_39 |
Ages 35-39 | decimal | 0% | - | - |
ages_40_44 |
Ages 40-44 | decimal | 0% | - | - |
ages_45_49 |
Ages 45-49 | decimal | 0% | - | - |
ages_50_54 |
Ages 50-54 | decimal | 0% | - | - |
ages_55_59 |
Ages 55-59 | decimal | 0% | - | - |
ages_60_64 |
Ages 60-64 | decimal | 0% | - | - |
ages_65_69 |
Ages 65-69 | decimal | 0% | - | - |
ages_70_74 |
Ages 70-74 | decimal | 0% | - | - |
age_75_and_over |
Age 75 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
ages_16_19 |
Ages 16-19 | decimal | 0% | - | - |
ages_20_24 |
Ages 20-24 | decimal | 0% | - | - |
ages_25_29 |
Ages 25-29 | decimal | 0% | - | - |
ages_30_34 |
Ages 30-34 | decimal | 0% | - | - |
ages_35_39 |
Ages 35-39 | decimal | 0% | - | - |
ages_40_44 |
Ages 40-44 | decimal | 0% | - | - |
ages_45_49 |
Ages 45-49 | decimal | 0% | - | - |
ages_50_54 |
Ages 50-54 | decimal | 0% | - | - |
ages_55_59 |
Ages 55-59 | decimal | 0% | - | - |
ages_60_64 |
Ages 60-64 | decimal | 0% | - | - |
ages_65_69 |
Ages 65-69 | decimal | 0% | - | - |
ages_70_74 |
Ages 70-74 | decimal | 0% | - | - |
age_75_and_over |
Age 75 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
ages_16_19 |
Ages 16-19 | decimal | 0% | - | - |
ages_20_24 |
Ages 20-24 | decimal | 0% | - | - |
ages_25_29 |
Ages 25-29 | decimal | 0% | - | - |
ages_30_34 |
Ages 30-34 | decimal | 0% | - | - |
ages_35_39 |
Ages 35-39 | decimal | 0% | - | - |
ages_40_44 |
Ages 40-44 | decimal | 0% | - | - |
ages_45_49 |
Ages 45-49 | decimal | 0% | - | - |
ages_50_54 |
Ages 50-54 | decimal | 0% | - | - |
ages_55_59 |
Ages 55-59 | decimal | 0% | - | - |
ages_60_64 |
Ages 60-64 | decimal | 0% | - | - |
ages_65_69 |
Ages 65-69 | decimal | 0% | - | - |
ages_70_74 |
Ages 70-74 | decimal | 0% | - | - |
age_75_and_over |
Age 75 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
ages_16_19 |
Ages 16-19 | decimal | 0% | - | - |
ages_20_24 |
Ages 20-24 | decimal | 0% | - | - |
ages_25_29 |
Ages 25-29 | decimal | 0% | - | - |
ages_30_34 |
Ages 30-34 | decimal | 0% | - | - |
ages_35_39 |
Ages 35-39 | decimal | 0% | - | - |
ages_40_44 |
Ages 40-44 | decimal | 0% | - | - |
ages_45_49 |
Ages 45-49 | decimal | 0% | - | - |
ages_50_54 |
Ages 50-54 | decimal | 0% | - | - |
ages_55_59 |
Ages 55-59 | decimal | 0% | - | - |
ages_60_64 |
Ages 60-64 | decimal | 0% | - | - |
ages_65_69 |
Ages 65-69 | decimal | 0% | - | - |
ages_70_74 |
Ages 70-74 | decimal | 0% | - | - |
age_75_and_over |
Age 75 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
never_attended_school |
Never attended school | decimal | SEL | 0% | - | - |
primary_school |
Primary school | decimal | SEL | 0% | - | - |
senior_secondary_school |
Senior secondary school | decimal | SEL | 0% | - | - |
university_undergraduate |
University (undergraduate) | decimal | SEL | 0% | - | - |
postgraduate_master_s |
Postgraduate (Master's) | decimal | SEL | 0% | - | - |
postgraduate_doctoral |
Postgraduate (Doctoral) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
pre_school_education |
Pre-school education | decimal | 0% | - | - |
junior_secondary_school |
Junior secondary school | decimal | 0% | - | - |
junior_college |
Junior college | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
never_attended_school |
Never attended school | decimal | SEL | 0% | - | - |
primary_school |
Primary school | decimal | SEL | 0% | - | - |
senior_secondary_school |
Senior secondary school | decimal | SEL | 0% | - | - |
university_undergraduate |
University (undergraduate) | decimal | SEL | 0% | - | - |
postgraduate_master_s |
Postgraduate (Master's) | decimal | SEL | 0% | - | - |
postgraduate_doctoral |
Postgraduate (Doctoral) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
pre_school_education |
Pre-school education | decimal | 0% | - | - |
junior_secondary_school |
Junior secondary school | decimal | 0% | - | - |
junior_college |
Junior college | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
never_attended_school |
Never attended school | decimal | SEL | 0% | - | - |
primary_school |
Primary school | decimal | SEL | 0% | - | - |
senior_secondary_school |
Senior secondary school | decimal | SEL | 0% | - | - |
university_undergraduate |
University (undergraduate) | decimal | SEL | 0% | - | - |
postgraduate_master_s |
Postgraduate (Master's) | decimal | SEL | 0% | - | - |
postgraduate_doctoral |
Postgraduate (Doctoral) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
pre_school_education |
Pre-school education | decimal | 0% | - | - |
junior_secondary_school |
Junior secondary school | decimal | 0% | - | - |
junior_college |
Junior college | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
never_attended_school |
Never attended school | decimal | SEL | 0% | - | - |
primary_school |
Primary school | decimal | SEL | 0% | - | - |
senior_secondary_school |
Senior secondary school | decimal | SEL | 0% | - | - |
university_undergraduate |
University (undergraduate) | decimal | SEL | 0% | - | - |
postgraduate_master_s |
Postgraduate (Master's) | decimal | SEL | 0% | - | - |
postgraduate_doctoral |
Postgraduate (Doctoral) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
pre_school_education |
Pre-school education | decimal | 0% | - | - |
junior_secondary_school |
Junior secondary school | decimal | 0% | - | - |
junior_college |
Junior college | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_subtotal |
Agriculture, forestry, animal husbandry and fishery > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_farming |
Agriculture, forestry, animal husbandry and fishery > Farming | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_forestry |
Agriculture, forestry, animal husbandry and fishery > Forestry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_animal_h |
Agriculture, forestry, animal husbandry and fishery > Animal husbandry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_fishery |
Agriculture, forestry, animal husbandry and fishery > Fishery | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_professi |
Agriculture, forestry, animal husbandry and fishery > Professional and support activities for agriculture, forestry, animal husbandry and fishery | decimal | 0% | - | - |
mining_subtotal |
Mining > Subtotal | decimal | 0% | - | - |
mining_coal_mining_and_washing |
Mining > Coal mining and washing | decimal | 0% | - | - |
mining_oil_and_natural_gas_extraction |
Mining > Oil and natural gas extraction | decimal | 0% | - | - |
mining_ferrous_metal_mining_and_dressing |
Mining > Ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_ferrous_metal_mining_and_dressing |
Mining > Non-ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_metallic_mineral_mining_and_dressing |
Mining > Non-metallic mineral mining and dressing | decimal | 0% | - | - |
mining_professional_and_support_activities_for_mining |
Mining > Professional and support activities for mining | decimal | 0% | - | - |
mining_other_mining |
Mining > Other mining | decimal | 0% | - | - |
manufacturing_subtotal |
Manufacturing > Subtotal | decimal | 0% | - | - |
manufacturing_processing_of_food_from_agricultural_product |
Manufacturing > Processing of food from agricultural products | decimal | 0% | - | - |
manufacturing_food_manufacturing |
Manufacturing > Food manufacturing | decimal | 0% | - | - |
manufacturing_liquor_beverage_and_refined_tea_manufacturin |
Manufacturing > Liquor, beverage and refined tea manufacturing | decimal | 0% | - | - |
manufacturing_tobacco_products |
Manufacturing > Tobacco products | decimal | 0% | - | - |
manufacturing_textiles |
Manufacturing > Textiles | decimal | 0% | - | - |
manufacturing_manufacture_of_textile_wearing_apparel_and_a |
Manufacturing > Manufacture of textile wearing apparel and accessories | decimal | 0% | - | - |
manufacturing_leather_fur_feather_and_related_products_and |
Manufacturing > Leather, fur, feather and related products and footwear | decimal | 0% | - | - |
manufacturing_processing_of_wood_and_products_of_wood_bamb |
Manufacturing > Processing of wood and products of wood, bamboo, rattan, palm and straw | decimal | 0% | - | - |
manufacturing_furniture_manufacturing |
Manufacturing > Furniture manufacturing | decimal | 0% | - | - |
manufacturing_paper_and_paper_products |
Manufacturing > Paper and paper products | decimal | 0% | - | - |
manufacturing_printing_and_reproduction_of_recording_media |
Manufacturing > Printing and reproduction of recording media | decimal | 0% | - | - |
manufacturing_manufacture_of_culture_education_arts_and_cr |
Manufacturing > Manufacture of culture, education, arts and crafts, sports and entertainment goods | decimal | 0% | - | - |
manufacturing_processing_of_petroleum_coal_and_other_fuels |
Manufacturing > Processing of petroleum, coal and other fuels | decimal | 0% | - | - |
| +89 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_subtotal |
Agriculture, forestry, animal husbandry and fishery > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_farming |
Agriculture, forestry, animal husbandry and fishery > Farming | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_forestry |
Agriculture, forestry, animal husbandry and fishery > Forestry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_animal_h |
Agriculture, forestry, animal husbandry and fishery > Animal husbandry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_fishery |
Agriculture, forestry, animal husbandry and fishery > Fishery | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_professi |
Agriculture, forestry, animal husbandry and fishery > Professional and support activities for agriculture, forestry, animal husbandry and fishery | decimal | 0% | - | - |
mining_subtotal |
Mining > Subtotal | decimal | 0% | - | - |
mining_coal_mining_and_washing |
Mining > Coal mining and washing | decimal | 0% | - | - |
mining_oil_and_natural_gas_extraction |
Mining > Oil and natural gas extraction | decimal | 0% | - | - |
mining_ferrous_metal_mining_and_dressing |
Mining > Ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_ferrous_metal_mining_and_dressing |
Mining > Non-ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_metallic_mineral_mining_and_dressing |
Mining > Non-metallic mineral mining and dressing | decimal | 0% | - | - |
mining_professional_and_support_activities_for_mining |
Mining > Professional and support activities for mining | decimal | 0% | - | - |
mining_other_mining |
Mining > Other mining | decimal | 0% | - | - |
manufacturing_subtotal |
Manufacturing > Subtotal | decimal | 0% | - | - |
manufacturing_processing_of_food_from_agricultural_product |
Manufacturing > Processing of food from agricultural products | decimal | 0% | - | - |
manufacturing_food_manufacturing |
Manufacturing > Food manufacturing | decimal | 0% | - | - |
manufacturing_liquor_beverage_and_refined_tea_manufacturin |
Manufacturing > Liquor, beverage and refined tea manufacturing | decimal | 0% | - | - |
manufacturing_tobacco_products |
Manufacturing > Tobacco products | decimal | 0% | - | - |
manufacturing_textiles |
Manufacturing > Textiles | decimal | 0% | - | - |
manufacturing_manufacture_of_textile_wearing_apparel_and_a |
Manufacturing > Manufacture of textile wearing apparel and accessories | decimal | 0% | - | - |
manufacturing_leather_fur_feather_and_related_products_and |
Manufacturing > Leather, fur, feather and related products and footwear | decimal | 0% | - | - |
manufacturing_processing_of_wood_and_products_of_wood_bamb |
Manufacturing > Processing of wood and products of wood, bamboo, rattan, palm and straw | decimal | 0% | - | - |
manufacturing_furniture_manufacturing |
Manufacturing > Furniture manufacturing | decimal | 0% | - | - |
manufacturing_paper_and_paper_products |
Manufacturing > Paper and paper products | decimal | 0% | - | - |
manufacturing_printing_and_reproduction_of_recording_media |
Manufacturing > Printing and reproduction of recording media | decimal | 0% | - | - |
manufacturing_manufacture_of_culture_education_arts_and_cr |
Manufacturing > Manufacture of culture, education, arts and crafts, sports and entertainment goods | decimal | 0% | - | - |
manufacturing_processing_of_petroleum_coal_and_other_fuels |
Manufacturing > Processing of petroleum, coal and other fuels | decimal | 0% | - | - |
| +89 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_subtotal |
Agriculture, forestry, animal husbandry and fishery > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_farming |
Agriculture, forestry, animal husbandry and fishery > Farming | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_forestry |
Agriculture, forestry, animal husbandry and fishery > Forestry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_animal_h |
Agriculture, forestry, animal husbandry and fishery > Animal husbandry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_fishery |
Agriculture, forestry, animal husbandry and fishery > Fishery | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_professi |
Agriculture, forestry, animal husbandry and fishery > Professional and support activities for agriculture, forestry, animal husbandry and fishery | decimal | 0% | - | - |
mining_subtotal |
Mining > Subtotal | decimal | 0% | - | - |
mining_coal_mining_and_washing |
Mining > Coal mining and washing | decimal | 0% | - | - |
mining_oil_and_natural_gas_extraction |
Mining > Oil and natural gas extraction | decimal | 0% | - | - |
mining_ferrous_metal_mining_and_dressing |
Mining > Ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_ferrous_metal_mining_and_dressing |
Mining > Non-ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_metallic_mineral_mining_and_dressing |
Mining > Non-metallic mineral mining and dressing | decimal | 0% | - | - |
mining_professional_and_support_activities_for_mining |
Mining > Professional and support activities for mining | decimal | 0% | - | - |
mining_other_mining |
Mining > Other mining | decimal | 0% | - | - |
manufacturing_subtotal |
Manufacturing > Subtotal | decimal | 0% | - | - |
manufacturing_processing_of_food_from_agricultural_product |
Manufacturing > Processing of food from agricultural products | decimal | 0% | - | - |
manufacturing_food_manufacturing |
Manufacturing > Food manufacturing | decimal | 0% | - | - |
manufacturing_liquor_beverage_and_refined_tea_manufacturin |
Manufacturing > Liquor, beverage and refined tea manufacturing | decimal | 0% | - | - |
manufacturing_tobacco_products |
Manufacturing > Tobacco products | decimal | 0% | - | - |
manufacturing_textiles |
Manufacturing > Textiles | decimal | 0% | - | - |
manufacturing_manufacture_of_textile_wearing_apparel_and_a |
Manufacturing > Manufacture of textile wearing apparel and accessories | decimal | 0% | - | - |
manufacturing_leather_fur_feather_and_related_products_and |
Manufacturing > Leather, fur, feather and related products and footwear | decimal | 0% | - | - |
manufacturing_processing_of_wood_and_products_of_wood_bamb |
Manufacturing > Processing of wood and products of wood, bamboo, rattan, palm and straw | decimal | 0% | - | - |
manufacturing_furniture_manufacturing |
Manufacturing > Furniture manufacturing | decimal | 0% | - | - |
manufacturing_paper_and_paper_products |
Manufacturing > Paper and paper products | decimal | 0% | - | - |
manufacturing_printing_and_reproduction_of_recording_media |
Manufacturing > Printing and reproduction of recording media | decimal | 0% | - | - |
manufacturing_manufacture_of_culture_education_arts_and_cr |
Manufacturing > Manufacture of culture, education, arts and crafts, sports and entertainment goods | decimal | 0% | - | - |
manufacturing_processing_of_petroleum_coal_and_other_fuels |
Manufacturing > Processing of petroleum, coal and other fuels | decimal | 0% | - | - |
| +89 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_subtotal |
Agriculture, forestry, animal husbandry and fishery > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_farming |
Agriculture, forestry, animal husbandry and fishery > Farming | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_forestry |
Agriculture, forestry, animal husbandry and fishery > Forestry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_animal_h |
Agriculture, forestry, animal husbandry and fishery > Animal husbandry | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_fishery |
Agriculture, forestry, animal husbandry and fishery > Fishery | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_professi |
Agriculture, forestry, animal husbandry and fishery > Professional and support activities for agriculture, forestry, animal husbandry and fishery | decimal | 0% | - | - |
mining_subtotal |
Mining > Subtotal | decimal | 0% | - | - |
mining_coal_mining_and_washing |
Mining > Coal mining and washing | decimal | 0% | - | - |
mining_oil_and_natural_gas_extraction |
Mining > Oil and natural gas extraction | decimal | 0% | - | - |
mining_ferrous_metal_mining_and_dressing |
Mining > Ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_ferrous_metal_mining_and_dressing |
Mining > Non-ferrous metal mining and dressing | decimal | 0% | - | - |
mining_non_metallic_mineral_mining_and_dressing |
Mining > Non-metallic mineral mining and dressing | decimal | 0% | - | - |
mining_professional_and_support_activities_for_mining |
Mining > Professional and support activities for mining | decimal | 0% | - | - |
mining_other_mining |
Mining > Other mining | decimal | 0% | - | - |
manufacturing_subtotal |
Manufacturing > Subtotal | decimal | 0% | - | - |
manufacturing_processing_of_food_from_agricultural_product |
Manufacturing > Processing of food from agricultural products | decimal | 0% | - | - |
manufacturing_food_manufacturing |
Manufacturing > Food manufacturing | decimal | 0% | - | - |
manufacturing_liquor_beverage_and_refined_tea_manufacturin |
Manufacturing > Liquor, beverage and refined tea manufacturing | decimal | 0% | - | - |
manufacturing_tobacco_products |
Manufacturing > Tobacco products | decimal | 0% | - | - |
manufacturing_textiles |
Manufacturing > Textiles | decimal | 0% | - | - |
manufacturing_manufacture_of_textile_wearing_apparel_and_a |
Manufacturing > Manufacture of textile wearing apparel and accessories | decimal | 0% | - | - |
manufacturing_leather_fur_feather_and_related_products_and |
Manufacturing > Leather, fur, feather and related products and footwear | decimal | 0% | - | - |
manufacturing_processing_of_wood_and_products_of_wood_bamb |
Manufacturing > Processing of wood and products of wood, bamboo, rattan, palm and straw | decimal | 0% | - | - |
manufacturing_furniture_manufacturing |
Manufacturing > Furniture manufacturing | decimal | 0% | - | - |
manufacturing_paper_and_paper_products |
Manufacturing > Paper and paper products | decimal | 0% | - | - |
manufacturing_printing_and_reproduction_of_recording_media |
Manufacturing > Printing and reproduction of recording media | decimal | 0% | - | - |
manufacturing_manufacture_of_culture_education_arts_and_cr |
Manufacturing > Manufacture of culture, education, arts and crafts, sports and entertainment goods | decimal | 0% | - | - |
manufacturing_processing_of_petroleum_coal_and_other_fuels |
Manufacturing > Processing of petroleum, coal and other fuels | decimal | 0% | - | - |
| +89 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of organs of the Communist Party of China | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of state organs | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_4 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of democratic parties and federations of industry and commerce | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_5 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of people's organizations, mass organizations, social organizations and other membership organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_6 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of community-level self-governing organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_7 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of enterprises and public institutions | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_scientific_research_p |
Professional and technical personnel > Scientific research personnel | decimal | 0% | - | - |
professional_and_technical_personnel_engineering_and_techn |
Professional and technical personnel > Engineering and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_agricultural_technica |
Professional and technical personnel > Agricultural technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_aircraft_and_ship_tec |
Professional and technical personnel > Aircraft and ship technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_health_professional_a |
Professional and technical personnel > Health professional and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_economic_and_financia |
Professional and technical personnel > Economic and financial professionals | decimal | 0% | - | - |
professional_and_technical_personnel_legal_social_and_reli |
Professional and technical personnel > Legal, social and religious professionals | decimal | 0% | - | - |
professional_and_technical_personnel_teaching_personnel |
Professional and technical personnel > Teaching personnel | decimal | 0% | - | - |
professional_and_technical_personnel_literature_art_and_sp |
Professional and technical personnel > Literature, art and sports professionals | decimal | 0% | - | - |
professional_and_technical_personnel_news_publishing_and_c |
Professional and technical personnel > News, publishing and cultural professionals | decimal | 0% | - | - |
professional_and_technical_personnel_other_professional_an |
Professional and technical personnel > Other professional and technical personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_clerical_staff |
Clerical staff and related personnel > Clerical staff | decimal | 0% | - | - |
clerical_staff_and_related_personnel_security_and_fire_fig |
Clerical staff and related personnel > Security and fire-fighting personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_other_clerical_staff_ |
Clerical staff and related personnel > Other clerical staff and related personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_wholesale_a |
Social production and living service personnel > Wholesale and retail service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_transport_s |
Social production and living service personnel > Transport, storage and postal service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_accommodati |
Social production and living service personnel > Accommodation and catering service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_information |
Social production and living service personnel > Information transmission, software and information technology service personnel | decimal | 0% | - | - |
| +52 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of organs of the Communist Party of China | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of state organs | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_4 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of democratic parties and federations of industry and commerce | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_5 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of people's organizations, mass organizations, social organizations and other membership organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_6 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of community-level self-governing organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_7 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of enterprises and public institutions | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_scientific_research_p |
Professional and technical personnel > Scientific research personnel | decimal | 0% | - | - |
professional_and_technical_personnel_engineering_and_techn |
Professional and technical personnel > Engineering and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_agricultural_technica |
Professional and technical personnel > Agricultural technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_aircraft_and_ship_tec |
Professional and technical personnel > Aircraft and ship technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_health_professional_a |
Professional and technical personnel > Health professional and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_economic_and_financia |
Professional and technical personnel > Economic and financial professionals | decimal | 0% | - | - |
professional_and_technical_personnel_legal_social_and_reli |
Professional and technical personnel > Legal, social and religious professionals | decimal | 0% | - | - |
professional_and_technical_personnel_teaching_personnel |
Professional and technical personnel > Teaching personnel | decimal | 0% | - | - |
professional_and_technical_personnel_literature_art_and_sp |
Professional and technical personnel > Literature, art and sports professionals | decimal | 0% | - | - |
professional_and_technical_personnel_news_publishing_and_c |
Professional and technical personnel > News, publishing and cultural professionals | decimal | 0% | - | - |
professional_and_technical_personnel_other_professional_an |
Professional and technical personnel > Other professional and technical personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_clerical_staff |
Clerical staff and related personnel > Clerical staff | decimal | 0% | - | - |
clerical_staff_and_related_personnel_security_and_fire_fig |
Clerical staff and related personnel > Security and fire-fighting personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_other_clerical_staff_ |
Clerical staff and related personnel > Other clerical staff and related personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_wholesale_a |
Social production and living service personnel > Wholesale and retail service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_transport_s |
Social production and living service personnel > Transport, storage and postal service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_accommodati |
Social production and living service personnel > Accommodation and catering service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_information |
Social production and living service personnel > Information transmission, software and information technology service personnel | decimal | 0% | - | - |
| +52 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of organs of the Communist Party of China | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of state organs | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_4 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of democratic parties and federations of industry and commerce | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_5 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of people's organizations, mass organizations, social organizations and other membership organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_6 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of community-level self-governing organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_7 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of enterprises and public institutions | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_scientific_research_p |
Professional and technical personnel > Scientific research personnel | decimal | 0% | - | - |
professional_and_technical_personnel_engineering_and_techn |
Professional and technical personnel > Engineering and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_agricultural_technica |
Professional and technical personnel > Agricultural technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_aircraft_and_ship_tec |
Professional and technical personnel > Aircraft and ship technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_health_professional_a |
Professional and technical personnel > Health professional and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_economic_and_financia |
Professional and technical personnel > Economic and financial professionals | decimal | 0% | - | - |
professional_and_technical_personnel_legal_social_and_reli |
Professional and technical personnel > Legal, social and religious professionals | decimal | 0% | - | - |
professional_and_technical_personnel_teaching_personnel |
Professional and technical personnel > Teaching personnel | decimal | 0% | - | - |
professional_and_technical_personnel_literature_art_and_sp |
Professional and technical personnel > Literature, art and sports professionals | decimal | 0% | - | - |
professional_and_technical_personnel_news_publishing_and_c |
Professional and technical personnel > News, publishing and cultural professionals | decimal | 0% | - | - |
professional_and_technical_personnel_other_professional_an |
Professional and technical personnel > Other professional and technical personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_clerical_staff |
Clerical staff and related personnel > Clerical staff | decimal | 0% | - | - |
clerical_staff_and_related_personnel_security_and_fire_fig |
Clerical staff and related personnel > Security and fire-fighting personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_other_clerical_staff_ |
Clerical staff and related personnel > Other clerical staff and related personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_wholesale_a |
Social production and living service personnel > Wholesale and retail service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_transport_s |
Social production and living service personnel > Transport, storage and postal service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_accommodati |
Social production and living service personnel > Accommodation and catering service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_information |
Social production and living service personnel > Information transmission, software and information technology service personnel | decimal | 0% | - | - |
| +52 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
sex |
Sex | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of organs of the Communist Party of China | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of state organs | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_4 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of democratic parties and federations of industry and commerce | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_5 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of people's organizations, mass organizations, social organizations and other membership organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_6 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of community-level self-governing organizations | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_7 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Heads of enterprises and public institutions | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_scientific_research_p |
Professional and technical personnel > Scientific research personnel | decimal | 0% | - | - |
professional_and_technical_personnel_engineering_and_techn |
Professional and technical personnel > Engineering and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_agricultural_technica |
Professional and technical personnel > Agricultural technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_aircraft_and_ship_tec |
Professional and technical personnel > Aircraft and ship technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_health_professional_a |
Professional and technical personnel > Health professional and technical personnel | decimal | 0% | - | - |
professional_and_technical_personnel_economic_and_financia |
Professional and technical personnel > Economic and financial professionals | decimal | 0% | - | - |
professional_and_technical_personnel_legal_social_and_reli |
Professional and technical personnel > Legal, social and religious professionals | decimal | 0% | - | - |
professional_and_technical_personnel_teaching_personnel |
Professional and technical personnel > Teaching personnel | decimal | 0% | - | - |
professional_and_technical_personnel_literature_art_and_sp |
Professional and technical personnel > Literature, art and sports professionals | decimal | 0% | - | - |
professional_and_technical_personnel_news_publishing_and_c |
Professional and technical personnel > News, publishing and cultural professionals | decimal | 0% | - | - |
professional_and_technical_personnel_other_professional_an |
Professional and technical personnel > Other professional and technical personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_clerical_staff |
Clerical staff and related personnel > Clerical staff | decimal | 0% | - | - |
clerical_staff_and_related_personnel_security_and_fire_fig |
Clerical staff and related personnel > Security and fire-fighting personnel | decimal | 0% | - | - |
clerical_staff_and_related_personnel_other_clerical_staff_ |
Clerical staff and related personnel > Other clerical staff and related personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_wholesale_a |
Social production and living service personnel > Wholesale and retail service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_transport_s |
Social production and living service personnel > Transport, storage and postal service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_accommodati |
Social production and living service personnel > Accommodation and catering service personnel | decimal | 0% | - | - |
social_production_and_living_service_personnel_information |
Social production and living service personnel > Information transmission, software and information technology service personnel | decimal | 0% | - | - |
| +52 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_2 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_3 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_2 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_3 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_2 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_3 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_2 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_3 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
outside_the_province_subtotal |
Outside the province > Subtotal | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
within_the_province_subtotal |
Within the province > Subtotal | decimal | 0% | - | - |
within_the_province_male |
Within the province > Male | decimal | 0% | - | - |
within_the_province_female |
Within the province > Female | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat |
Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat_2 |
Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat_3 |
Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
outside_the_province_male |
Outside the province > Male | decimal | 0% | - | - |
outside_the_province_female |
Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
outside_the_province_subtotal |
Outside the province > Subtotal | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
within_the_province_subtotal |
Within the province > Subtotal | decimal | 0% | - | - |
within_the_province_male |
Within the province > Male | decimal | 0% | - | - |
within_the_province_female |
Within the province > Female | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat |
Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat_2 |
Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat_3 |
Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
outside_the_province_male |
Outside the province > Male | decimal | 0% | - | - |
outside_the_province_female |
Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
outside_the_province_subtotal |
Outside the province > Subtotal | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
within_the_province_subtotal |
Within the province > Subtotal | decimal | 0% | - | - |
within_the_province_male |
Within the province > Male | decimal | 0% | - | - |
within_the_province_female |
Within the province > Female | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat |
Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat_2 |
Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat_3 |
Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
outside_the_province_male |
Outside the province > Male | decimal | 0% | - | - |
outside_the_province_female |
Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
outside_the_province_subtotal |
Outside the province > Subtotal | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
within_the_province_subtotal |
Within the province > Subtotal | decimal | 0% | - | - |
within_the_province_male |
Within the province > Male | decimal | 0% | - | - |
within_the_province_female |
Within the province > Female | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat |
Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat_2 |
Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
within_the_province_of_which_residence_household_registrat_3 |
Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
outside_the_province_male |
Outside the province > Male | decimal | 0% | - | - |
outside_the_province_female |
Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
work_and_employment_subtotal |
Work and employment > Subtotal | decimal | 0% | - | - |
work_and_employment_male |
Work and employment > Male | decimal | 0% | - | - |
work_and_employment_female |
Work and employment > Female | decimal | 0% | - | - |
study_and_training_subtotal |
Study and training > Subtotal | decimal | 0% | - | - |
study_and_training_male |
Study and training > Male | decimal | 0% | - | - |
study_and_training_female |
Study and training > Female | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_subtotal |
Accompanying others / joining relatives or friends > Subtotal | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_male |
Accompanying others / joining relatives or friends > Male | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_female |
Accompanying others / joining relatives or friends > Female | decimal | 0% | - | - |
demolition_moving_house_subtotal |
Demolition / moving house > Subtotal | decimal | 0% | - | - |
demolition_moving_house_male |
Demolition / moving house > Male | decimal | 0% | - | - |
demolition_moving_house_female |
Demolition / moving house > Female | decimal | 0% | - | - |
nominal_household_registration_subtotal |
Nominal household registration > Subtotal | decimal | 0% | - | - |
nominal_household_registration_male |
Nominal household registration > Male | decimal | 0% | - | - |
nominal_household_registration_female |
Nominal household registration > Female | decimal | 0% | - | - |
marriage_subtotal |
Marriage > Subtotal | decimal | 0% | - | - |
marriage_male |
Marriage > Male | decimal | 0% | - | - |
marriage_female |
Marriage > Female | decimal | 0% | - | - |
caring_for_grandchildren_subtotal |
Caring for grandchildren > Subtotal | decimal | 0% | - | - |
caring_for_grandchildren_male |
Caring for grandchildren > Male | decimal | 0% | - | - |
caring_for_grandchildren_female |
Caring for grandchildren > Female | decimal | 0% | - | - |
for_children_s_schooling_subtotal |
For children's schooling > Subtotal | decimal | 0% | - | - |
for_children_s_schooling_male |
For children's schooling > Male | decimal | 0% | - | - |
for_children_s_schooling_female |
For children's schooling > Female | decimal | 0% | - | - |
old_age_care_health_and_wellness_subtotal |
Old-age care / health and wellness > Subtotal | decimal | 0% | - | - |
old_age_care_health_and_wellness_male |
Old-age care / health and wellness > Male | decimal | 0% | - | - |
| +4 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
work_and_employment_subtotal |
Work and employment > Subtotal | decimal | 0% | - | - |
work_and_employment_male |
Work and employment > Male | decimal | 0% | - | - |
work_and_employment_female |
Work and employment > Female | decimal | 0% | - | - |
study_and_training_subtotal |
Study and training > Subtotal | decimal | 0% | - | - |
study_and_training_male |
Study and training > Male | decimal | 0% | - | - |
study_and_training_female |
Study and training > Female | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_subtotal |
Accompanying others / joining relatives or friends > Subtotal | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_male |
Accompanying others / joining relatives or friends > Male | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_female |
Accompanying others / joining relatives or friends > Female | decimal | 0% | - | - |
demolition_moving_house_subtotal |
Demolition / moving house > Subtotal | decimal | 0% | - | - |
demolition_moving_house_male |
Demolition / moving house > Male | decimal | 0% | - | - |
demolition_moving_house_female |
Demolition / moving house > Female | decimal | 0% | - | - |
nominal_household_registration_subtotal |
Nominal household registration > Subtotal | decimal | 0% | - | - |
nominal_household_registration_male |
Nominal household registration > Male | decimal | 0% | - | - |
nominal_household_registration_female |
Nominal household registration > Female | decimal | 0% | - | - |
marriage_subtotal |
Marriage > Subtotal | decimal | 0% | - | - |
marriage_male |
Marriage > Male | decimal | 0% | - | - |
marriage_female |
Marriage > Female | decimal | 0% | - | - |
caring_for_grandchildren_subtotal |
Caring for grandchildren > Subtotal | decimal | 0% | - | - |
caring_for_grandchildren_male |
Caring for grandchildren > Male | decimal | 0% | - | - |
caring_for_grandchildren_female |
Caring for grandchildren > Female | decimal | 0% | - | - |
for_children_s_schooling_subtotal |
For children's schooling > Subtotal | decimal | 0% | - | - |
for_children_s_schooling_male |
For children's schooling > Male | decimal | 0% | - | - |
for_children_s_schooling_female |
For children's schooling > Female | decimal | 0% | - | - |
old_age_care_health_and_wellness_subtotal |
Old-age care / health and wellness > Subtotal | decimal | 0% | - | - |
old_age_care_health_and_wellness_male |
Old-age care / health and wellness > Male | decimal | 0% | - | - |
| +4 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
work_and_employment_subtotal |
Work and employment > Subtotal | decimal | 0% | - | - |
work_and_employment_male |
Work and employment > Male | decimal | 0% | - | - |
work_and_employment_female |
Work and employment > Female | decimal | 0% | - | - |
study_and_training_subtotal |
Study and training > Subtotal | decimal | 0% | - | - |
study_and_training_male |
Study and training > Male | decimal | 0% | - | - |
study_and_training_female |
Study and training > Female | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_subtotal |
Accompanying others / joining relatives or friends > Subtotal | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_male |
Accompanying others / joining relatives or friends > Male | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_female |
Accompanying others / joining relatives or friends > Female | decimal | 0% | - | - |
demolition_moving_house_subtotal |
Demolition / moving house > Subtotal | decimal | 0% | - | - |
demolition_moving_house_male |
Demolition / moving house > Male | decimal | 0% | - | - |
demolition_moving_house_female |
Demolition / moving house > Female | decimal | 0% | - | - |
nominal_household_registration_subtotal |
Nominal household registration > Subtotal | decimal | 0% | - | - |
nominal_household_registration_male |
Nominal household registration > Male | decimal | 0% | - | - |
nominal_household_registration_female |
Nominal household registration > Female | decimal | 0% | - | - |
marriage_subtotal |
Marriage > Subtotal | decimal | 0% | - | - |
marriage_male |
Marriage > Male | decimal | 0% | - | - |
marriage_female |
Marriage > Female | decimal | 0% | - | - |
caring_for_grandchildren_subtotal |
Caring for grandchildren > Subtotal | decimal | 0% | - | - |
caring_for_grandchildren_male |
Caring for grandchildren > Male | decimal | 0% | - | - |
caring_for_grandchildren_female |
Caring for grandchildren > Female | decimal | 0% | - | - |
for_children_s_schooling_subtotal |
For children's schooling > Subtotal | decimal | 0% | - | - |
for_children_s_schooling_male |
For children's schooling > Male | decimal | 0% | - | - |
for_children_s_schooling_female |
For children's schooling > Female | decimal | 0% | - | - |
old_age_care_health_and_wellness_subtotal |
Old-age care / health and wellness > Subtotal | decimal | 0% | - | - |
old_age_care_health_and_wellness_male |
Old-age care / health and wellness > Male | decimal | 0% | - | - |
| +4 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
work_and_employment_subtotal |
Work and employment > Subtotal | decimal | 0% | - | - |
work_and_employment_male |
Work and employment > Male | decimal | 0% | - | - |
work_and_employment_female |
Work and employment > Female | decimal | 0% | - | - |
study_and_training_subtotal |
Study and training > Subtotal | decimal | 0% | - | - |
study_and_training_male |
Study and training > Male | decimal | 0% | - | - |
study_and_training_female |
Study and training > Female | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_subtotal |
Accompanying others / joining relatives or friends > Subtotal | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_male |
Accompanying others / joining relatives or friends > Male | decimal | 0% | - | - |
accompanying_others_joining_relatives_or_friends_female |
Accompanying others / joining relatives or friends > Female | decimal | 0% | - | - |
demolition_moving_house_subtotal |
Demolition / moving house > Subtotal | decimal | 0% | - | - |
demolition_moving_house_male |
Demolition / moving house > Male | decimal | 0% | - | - |
demolition_moving_house_female |
Demolition / moving house > Female | decimal | 0% | - | - |
nominal_household_registration_subtotal |
Nominal household registration > Subtotal | decimal | 0% | - | - |
nominal_household_registration_male |
Nominal household registration > Male | decimal | 0% | - | - |
nominal_household_registration_female |
Nominal household registration > Female | decimal | 0% | - | - |
marriage_subtotal |
Marriage > Subtotal | decimal | 0% | - | - |
marriage_male |
Marriage > Male | decimal | 0% | - | - |
marriage_female |
Marriage > Female | decimal | 0% | - | - |
caring_for_grandchildren_subtotal |
Caring for grandchildren > Subtotal | decimal | 0% | - | - |
caring_for_grandchildren_male |
Caring for grandchildren > Male | decimal | 0% | - | - |
caring_for_grandchildren_female |
Caring for grandchildren > Female | decimal | 0% | - | - |
for_children_s_schooling_subtotal |
For children's schooling > Subtotal | decimal | 0% | - | - |
for_children_s_schooling_male |
For children's schooling > Male | decimal | 0% | - | - |
for_children_s_schooling_female |
For children's schooling > Female | decimal | 0% | - | - |
old_age_care_health_and_wellness_subtotal |
Old-age care / health and wellness > Subtotal | decimal | 0% | - | - |
old_age_care_health_and_wellness_male |
Old-age care / health and wellness > Male | decimal | 0% | - | - |
| +4 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside_2 |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside_3 |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within |
Place of household registration > Within the province > Within-province migrants > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within_2 |
Place of household registration > Within the province > Within-province migrants > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within_3 |
Place of household registration > Within the province > Within-province migrants > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside_2 |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside_3 |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within |
Place of household registration > Within the province > Within-province migrants > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within_2 |
Place of household registration > Within the province > Within-province migrants > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within_3 |
Place of household registration > Within the province > Within-province migrants > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside_2 |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside_3 |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within |
Place of household registration > Within the province > Within-province migrants > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within_2 |
Place of household registration > Within the province > Within-province migrants > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within_3 |
Place of household registration > Within the province > Within-province migrants > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside_2 |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_reside_3 |
Place of household registration > Within the province > Residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within |
Place of household registration > Within the province > Within-province migrants > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within_2 |
Place of household registration > Within the province > Within-province migrants > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_within_3 |
Place of household registration > Within the province > Within-province migrants > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_beijing_subtotal |
Place of household registration > Beijing > Subtotal | decimal | 0% | - | - |
place_of_household_registration_beijing_male |
Place of household registration > Beijing > Male | decimal | 0% | - | - |
place_of_household_registration_beijing_female |
Place of household registration > Beijing > Female | decimal | 0% | - | - |
place_of_household_registration_tianjin_subtotal |
Place of household registration > Tianjin > Subtotal | decimal | 0% | - | - |
place_of_household_registration_tianjin_male |
Place of household registration > Tianjin > Male | decimal | 0% | - | - |
place_of_household_registration_tianjin_female |
Place of household registration > Tianjin > Female | decimal | 0% | - | - |
place_of_household_registration_hebei_subtotal |
Place of household registration > Hebei > Subtotal | decimal | 0% | - | - |
place_of_household_registration_hebei_male |
Place of household registration > Hebei > Male | decimal | 0% | - | - |
place_of_household_registration_hebei_female |
Place of household registration > Hebei > Female | decimal | 0% | - | - |
place_of_household_registration_shanxi_subtotal |
Place of household registration > Shanxi > Subtotal | decimal | 0% | - | - |
place_of_household_registration_shanxi_male |
Place of household registration > Shanxi > Male | decimal | 0% | - | - |
place_of_household_registration_shanxi_female |
Place of household registration > Shanxi > Female | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_subtotal |
Place of household registration > Inner Mongolia > Subtotal | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_male |
Place of household registration > Inner Mongolia > Male | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_female |
Place of household registration > Inner Mongolia > Female | decimal | 0% | - | - |
place_of_household_registration_liaoning_subtotal |
Place of household registration > Liaoning > Subtotal | decimal | 0% | - | - |
place_of_household_registration_liaoning_male |
Place of household registration > Liaoning > Male | decimal | 0% | - | - |
place_of_household_registration_liaoning_female |
Place of household registration > Liaoning > Female | decimal | 0% | - | - |
place_of_household_registration_jilin_subtotal |
Place of household registration > Jilin > Subtotal | decimal | 0% | - | - |
place_of_household_registration_jilin_male |
Place of household registration > Jilin > Male | decimal | 0% | - | - |
place_of_household_registration_jilin_female |
Place of household registration > Jilin > Female | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_subtotal |
Place of household registration > Heilongjiang > Subtotal | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_male |
Place of household registration > Heilongjiang > Male | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_female |
Place of household registration > Heilongjiang > Female | decimal | 0% | - | - |
place_of_household_registration_shanghai_subtotal |
Place of household registration > Shanghai > Subtotal | decimal | 0% | - | - |
| +68 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_beijing_subtotal |
Place of household registration > Beijing > Subtotal | decimal | 0% | - | - |
place_of_household_registration_beijing_male |
Place of household registration > Beijing > Male | decimal | 0% | - | - |
place_of_household_registration_beijing_female |
Place of household registration > Beijing > Female | decimal | 0% | - | - |
place_of_household_registration_tianjin_subtotal |
Place of household registration > Tianjin > Subtotal | decimal | 0% | - | - |
place_of_household_registration_tianjin_male |
Place of household registration > Tianjin > Male | decimal | 0% | - | - |
place_of_household_registration_tianjin_female |
Place of household registration > Tianjin > Female | decimal | 0% | - | - |
place_of_household_registration_hebei_subtotal |
Place of household registration > Hebei > Subtotal | decimal | 0% | - | - |
place_of_household_registration_hebei_male |
Place of household registration > Hebei > Male | decimal | 0% | - | - |
place_of_household_registration_hebei_female |
Place of household registration > Hebei > Female | decimal | 0% | - | - |
place_of_household_registration_shanxi_subtotal |
Place of household registration > Shanxi > Subtotal | decimal | 0% | - | - |
place_of_household_registration_shanxi_male |
Place of household registration > Shanxi > Male | decimal | 0% | - | - |
place_of_household_registration_shanxi_female |
Place of household registration > Shanxi > Female | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_subtotal |
Place of household registration > Inner Mongolia > Subtotal | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_male |
Place of household registration > Inner Mongolia > Male | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_female |
Place of household registration > Inner Mongolia > Female | decimal | 0% | - | - |
place_of_household_registration_liaoning_subtotal |
Place of household registration > Liaoning > Subtotal | decimal | 0% | - | - |
place_of_household_registration_liaoning_male |
Place of household registration > Liaoning > Male | decimal | 0% | - | - |
place_of_household_registration_liaoning_female |
Place of household registration > Liaoning > Female | decimal | 0% | - | - |
place_of_household_registration_jilin_subtotal |
Place of household registration > Jilin > Subtotal | decimal | 0% | - | - |
place_of_household_registration_jilin_male |
Place of household registration > Jilin > Male | decimal | 0% | - | - |
place_of_household_registration_jilin_female |
Place of household registration > Jilin > Female | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_subtotal |
Place of household registration > Heilongjiang > Subtotal | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_male |
Place of household registration > Heilongjiang > Male | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_female |
Place of household registration > Heilongjiang > Female | decimal | 0% | - | - |
place_of_household_registration_shanghai_subtotal |
Place of household registration > Shanghai > Subtotal | decimal | 0% | - | - |
| +68 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_beijing_subtotal |
Place of household registration > Beijing > Subtotal | decimal | 0% | - | - |
place_of_household_registration_beijing_male |
Place of household registration > Beijing > Male | decimal | 0% | - | - |
place_of_household_registration_beijing_female |
Place of household registration > Beijing > Female | decimal | 0% | - | - |
place_of_household_registration_tianjin_subtotal |
Place of household registration > Tianjin > Subtotal | decimal | 0% | - | - |
place_of_household_registration_tianjin_male |
Place of household registration > Tianjin > Male | decimal | 0% | - | - |
place_of_household_registration_tianjin_female |
Place of household registration > Tianjin > Female | decimal | 0% | - | - |
place_of_household_registration_hebei_subtotal |
Place of household registration > Hebei > Subtotal | decimal | 0% | - | - |
place_of_household_registration_hebei_male |
Place of household registration > Hebei > Male | decimal | 0% | - | - |
place_of_household_registration_hebei_female |
Place of household registration > Hebei > Female | decimal | 0% | - | - |
place_of_household_registration_shanxi_subtotal |
Place of household registration > Shanxi > Subtotal | decimal | 0% | - | - |
place_of_household_registration_shanxi_male |
Place of household registration > Shanxi > Male | decimal | 0% | - | - |
place_of_household_registration_shanxi_female |
Place of household registration > Shanxi > Female | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_subtotal |
Place of household registration > Inner Mongolia > Subtotal | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_male |
Place of household registration > Inner Mongolia > Male | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_female |
Place of household registration > Inner Mongolia > Female | decimal | 0% | - | - |
place_of_household_registration_liaoning_subtotal |
Place of household registration > Liaoning > Subtotal | decimal | 0% | - | - |
place_of_household_registration_liaoning_male |
Place of household registration > Liaoning > Male | decimal | 0% | - | - |
place_of_household_registration_liaoning_female |
Place of household registration > Liaoning > Female | decimal | 0% | - | - |
place_of_household_registration_jilin_subtotal |
Place of household registration > Jilin > Subtotal | decimal | 0% | - | - |
place_of_household_registration_jilin_male |
Place of household registration > Jilin > Male | decimal | 0% | - | - |
place_of_household_registration_jilin_female |
Place of household registration > Jilin > Female | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_subtotal |
Place of household registration > Heilongjiang > Subtotal | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_male |
Place of household registration > Heilongjiang > Male | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_female |
Place of household registration > Heilongjiang > Female | decimal | 0% | - | - |
place_of_household_registration_shanghai_subtotal |
Place of household registration > Shanghai > Subtotal | decimal | 0% | - | - |
| +68 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_beijing_subtotal |
Place of household registration > Beijing > Subtotal | decimal | 0% | - | - |
place_of_household_registration_beijing_male |
Place of household registration > Beijing > Male | decimal | 0% | - | - |
place_of_household_registration_beijing_female |
Place of household registration > Beijing > Female | decimal | 0% | - | - |
place_of_household_registration_tianjin_subtotal |
Place of household registration > Tianjin > Subtotal | decimal | 0% | - | - |
place_of_household_registration_tianjin_male |
Place of household registration > Tianjin > Male | decimal | 0% | - | - |
place_of_household_registration_tianjin_female |
Place of household registration > Tianjin > Female | decimal | 0% | - | - |
place_of_household_registration_hebei_subtotal |
Place of household registration > Hebei > Subtotal | decimal | 0% | - | - |
place_of_household_registration_hebei_male |
Place of household registration > Hebei > Male | decimal | 0% | - | - |
place_of_household_registration_hebei_female |
Place of household registration > Hebei > Female | decimal | 0% | - | - |
place_of_household_registration_shanxi_subtotal |
Place of household registration > Shanxi > Subtotal | decimal | 0% | - | - |
place_of_household_registration_shanxi_male |
Place of household registration > Shanxi > Male | decimal | 0% | - | - |
place_of_household_registration_shanxi_female |
Place of household registration > Shanxi > Female | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_subtotal |
Place of household registration > Inner Mongolia > Subtotal | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_male |
Place of household registration > Inner Mongolia > Male | decimal | 0% | - | - |
place_of_household_registration_inner_mongolia_female |
Place of household registration > Inner Mongolia > Female | decimal | 0% | - | - |
place_of_household_registration_liaoning_subtotal |
Place of household registration > Liaoning > Subtotal | decimal | 0% | - | - |
place_of_household_registration_liaoning_male |
Place of household registration > Liaoning > Male | decimal | 0% | - | - |
place_of_household_registration_liaoning_female |
Place of household registration > Liaoning > Female | decimal | 0% | - | - |
place_of_household_registration_jilin_subtotal |
Place of household registration > Jilin > Subtotal | decimal | 0% | - | - |
place_of_household_registration_jilin_male |
Place of household registration > Jilin > Male | decimal | 0% | - | - |
place_of_household_registration_jilin_female |
Place of household registration > Jilin > Female | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_subtotal |
Place of household registration > Heilongjiang > Subtotal | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_male |
Place of household registration > Heilongjiang > Male | decimal | 0% | - | - |
place_of_household_registration_heilongjiang_female |
Place of household registration > Heilongjiang > Female | decimal | 0% | - | - |
place_of_household_registration_shanghai_subtotal |
Place of household registration > Shanghai > Subtotal | decimal | 0% | - | - |
| +68 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot |
Time since leaving the place of household registration > Total > Total | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_2 |
Time since leaving the place of household registration > Total > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_3 |
Time since leaving the place of household registration > Total > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_4 |
Time since leaving the place of household registration > Total > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_5 |
Time since leaving the place of household registration > Total > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_6 |
Time since leaving the place of household registration > Total > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_7 |
Time since leaving the place of household registration > Total > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_8 |
Time since leaving the place of household registration > Total > 10 years or more | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit |
Time since leaving the place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_2 |
Time since leaving the place of household registration > Within the province > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_3 |
Time since leaving the place of household registration > Within the province > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_4 |
Time since leaving the place of household registration > Within the province > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_5 |
Time since leaving the place of household registration > Within the province > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_6 |
Time since leaving the place of household registration > Within the province > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_7 |
Time since leaving the place of household registration > Within the province > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_8 |
Time since leaving the place of household registration > Within the province > 10 years or more | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out |
Time since leaving the place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_2 |
Time since leaving the place of household registration > Outside the province > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_3 |
Time since leaving the place of household registration > Outside the province > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_4 |
Time since leaving the place of household registration > Outside the province > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_5 |
Time since leaving the place of household registration > Outside the province > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_6 |
Time since leaving the place of household registration > Outside the province > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_7 |
Time since leaving the place of household registration > Outside the province > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_8 |
Time since leaving the place of household registration > Outside the province > 10 years or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot |
Time since leaving the place of household registration > Total > Total | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_2 |
Time since leaving the place of household registration > Total > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_3 |
Time since leaving the place of household registration > Total > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_4 |
Time since leaving the place of household registration > Total > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_5 |
Time since leaving the place of household registration > Total > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_6 |
Time since leaving the place of household registration > Total > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_7 |
Time since leaving the place of household registration > Total > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_8 |
Time since leaving the place of household registration > Total > 10 years or more | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit |
Time since leaving the place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_2 |
Time since leaving the place of household registration > Within the province > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_3 |
Time since leaving the place of household registration > Within the province > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_4 |
Time since leaving the place of household registration > Within the province > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_5 |
Time since leaving the place of household registration > Within the province > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_6 |
Time since leaving the place of household registration > Within the province > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_7 |
Time since leaving the place of household registration > Within the province > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_8 |
Time since leaving the place of household registration > Within the province > 10 years or more | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out |
Time since leaving the place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_2 |
Time since leaving the place of household registration > Outside the province > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_3 |
Time since leaving the place of household registration > Outside the province > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_4 |
Time since leaving the place of household registration > Outside the province > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_5 |
Time since leaving the place of household registration > Outside the province > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_6 |
Time since leaving the place of household registration > Outside the province > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_7 |
Time since leaving the place of household registration > Outside the province > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_8 |
Time since leaving the place of household registration > Outside the province > 10 years or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot |
Time since leaving the place of household registration > Total > Total | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_2 |
Time since leaving the place of household registration > Total > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_3 |
Time since leaving the place of household registration > Total > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_4 |
Time since leaving the place of household registration > Total > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_5 |
Time since leaving the place of household registration > Total > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_6 |
Time since leaving the place of household registration > Total > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_7 |
Time since leaving the place of household registration > Total > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_8 |
Time since leaving the place of household registration > Total > 10 years or more | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit |
Time since leaving the place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_2 |
Time since leaving the place of household registration > Within the province > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_3 |
Time since leaving the place of household registration > Within the province > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_4 |
Time since leaving the place of household registration > Within the province > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_5 |
Time since leaving the place of household registration > Within the province > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_6 |
Time since leaving the place of household registration > Within the province > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_7 |
Time since leaving the place of household registration > Within the province > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_8 |
Time since leaving the place of household registration > Within the province > 10 years or more | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out |
Time since leaving the place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_2 |
Time since leaving the place of household registration > Outside the province > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_3 |
Time since leaving the place of household registration > Outside the province > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_4 |
Time since leaving the place of household registration > Outside the province > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_5 |
Time since leaving the place of household registration > Outside the province > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_6 |
Time since leaving the place of household registration > Outside the province > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_7 |
Time since leaving the place of household registration > Outside the province > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_8 |
Time since leaving the place of household registration > Outside the province > 10 years or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot |
Time since leaving the place of household registration > Total > Total | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_2 |
Time since leaving the place of household registration > Total > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_3 |
Time since leaving the place of household registration > Total > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_4 |
Time since leaving the place of household registration > Total > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_5 |
Time since leaving the place of household registration > Total > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_6 |
Time since leaving the place of household registration > Total > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_7 |
Time since leaving the place of household registration > Total > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_tot_8 |
Time since leaving the place of household registration > Total > 10 years or more | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit |
Time since leaving the place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_2 |
Time since leaving the place of household registration > Within the province > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_3 |
Time since leaving the place of household registration > Within the province > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_4 |
Time since leaving the place of household registration > Within the province > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_5 |
Time since leaving the place of household registration > Within the province > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_6 |
Time since leaving the place of household registration > Within the province > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_7 |
Time since leaving the place of household registration > Within the province > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_wit_8 |
Time since leaving the place of household registration > Within the province > 10 years or more | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out |
Time since leaving the place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_2 |
Time since leaving the place of household registration > Outside the province > 6 months or more, under 1 year | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_3 |
Time since leaving the place of household registration > Outside the province > 1 year or more, under 2 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_4 |
Time since leaving the place of household registration > Outside the province > 2 years or more, under 3 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_5 |
Time since leaving the place of household registration > Outside the province > 3 years or more, under 4 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_6 |
Time since leaving the place of household registration > Outside the province > 4 years or more, under 5 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_7 |
Time since leaving the place of household registration > Outside the province > 5 years or more, under 10 years | decimal | 0% | - | - |
time_since_leaving_the_place_of_household_registration_out_8 |
Time since leaving the place of household registration > Outside the province > 10 years or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
| +1 more extension field — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
| +1 more extension field — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
| +1 more extension field — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
| +1 more extension field — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
| +1 more extension field — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
| +1 more extension field — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
| +1 more extension field — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
| +1 more extension field — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_households_total |
Number of households > Total | decimal | SEL | 0% | - | - |
population_total_total |
Population > Total > Total | decimal | SEL | 0% | - | - |
population_total_male |
Population > Total > Male | decimal | SEL | 0% | - | - |
population_total_female |
Population > Total > Female | decimal | SEL | 0% | - | - |
population_total_sex_ratio_female_100 |
Population > Total > Sex ratio (female=100) | decimal | SEL | 0% | - | - |
average_family_household_size_persons_household |
Average family household size (persons/household) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_family_households |
Number of households > Family households | decimal | 0% | - | - |
number_of_households_collective_households |
Number of households > Collective households | decimal | 0% | - | - |
population_family_households_subtotal |
Population > Family households > Subtotal | decimal | 0% | - | - |
population_family_households_male |
Population > Family households > Male | decimal | 0% | - | - |
population_family_households_female |
Population > Family households > Female | decimal | 0% | - | - |
population_family_households_sex_ratio_female_100 |
Population > Family households > Sex ratio (female=100) | decimal | 0% | - | - |
population_collective_households_subtotal |
Population > Collective households > Subtotal | decimal | 0% | - | - |
population_collective_households_male |
Population > Collective households > Male | decimal | 0% | - | - |
population_collective_households_female |
Population > Collective households > Female | decimal | 0% | - | - |
population_collective_households_sex_ratio_female_100 |
Population > Collective households > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_households_total |
Number of households > Total | decimal | SEL | 0% | - | - |
population_total_total |
Population > Total > Total | decimal | SEL | 0% | - | - |
population_total_male |
Population > Total > Male | decimal | SEL | 0% | - | - |
population_total_female |
Population > Total > Female | decimal | SEL | 0% | - | - |
population_total_sex_ratio_female_100 |
Population > Total > Sex ratio (female=100) | decimal | SEL | 0% | - | - |
average_family_household_size_persons_household |
Average family household size (persons/household) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_family_households |
Number of households > Family households | decimal | 0% | - | - |
number_of_households_collective_households |
Number of households > Collective households | decimal | 0% | - | - |
population_family_households_subtotal |
Population > Family households > Subtotal | decimal | 0% | - | - |
population_family_households_male |
Population > Family households > Male | decimal | 0% | - | - |
population_family_households_female |
Population > Family households > Female | decimal | 0% | - | - |
population_family_households_sex_ratio_female_100 |
Population > Family households > Sex ratio (female=100) | decimal | 0% | - | - |
population_collective_households_subtotal |
Population > Collective households > Subtotal | decimal | 0% | - | - |
population_collective_households_male |
Population > Collective households > Male | decimal | 0% | - | - |
population_collective_households_female |
Population > Collective households > Female | decimal | 0% | - | - |
population_collective_households_sex_ratio_female_100 |
Population > Collective households > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_households_total |
Number of households > Total | decimal | SEL | 0% | - | - |
population_total_total |
Population > Total > Total | decimal | SEL | 0% | - | - |
population_total_male |
Population > Total > Male | decimal | SEL | 0% | - | - |
population_total_female |
Population > Total > Female | decimal | SEL | 0% | - | - |
population_total_sex_ratio_female_100 |
Population > Total > Sex ratio (female=100) | decimal | SEL | 0% | - | - |
average_family_household_size_persons_household |
Average family household size (persons/household) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_family_households |
Number of households > Family households | decimal | 0% | - | - |
number_of_households_collective_households |
Number of households > Collective households | decimal | 0% | - | - |
population_family_households_subtotal |
Population > Family households > Subtotal | decimal | 0% | - | - |
population_family_households_male |
Population > Family households > Male | decimal | 0% | - | - |
population_family_households_female |
Population > Family households > Female | decimal | 0% | - | - |
population_family_households_sex_ratio_female_100 |
Population > Family households > Sex ratio (female=100) | decimal | 0% | - | - |
population_collective_households_subtotal |
Population > Collective households > Subtotal | decimal | 0% | - | - |
population_collective_households_male |
Population > Collective households > Male | decimal | 0% | - | - |
population_collective_households_female |
Population > Collective households > Female | decimal | 0% | - | - |
population_collective_households_sex_ratio_female_100 |
Population > Collective households > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_households_total |
Number of households > Total | decimal | SEL | 0% | - | - |
population_total_total |
Population > Total > Total | decimal | SEL | 0% | - | - |
population_total_male |
Population > Total > Male | decimal | SEL | 0% | - | - |
population_total_female |
Population > Total > Female | decimal | SEL | 0% | - | - |
population_total_sex_ratio_female_100 |
Population > Total > Sex ratio (female=100) | decimal | SEL | 0% | - | - |
average_family_household_size_persons_household |
Average family household size (persons/household) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_family_households |
Number of households > Family households | decimal | 0% | - | - |
number_of_households_collective_households |
Number of households > Collective households | decimal | 0% | - | - |
population_family_households_subtotal |
Population > Family households > Subtotal | decimal | 0% | - | - |
population_family_households_male |
Population > Family households > Male | decimal | 0% | - | - |
population_family_households_female |
Population > Family households > Female | decimal | 0% | - | - |
population_family_households_sex_ratio_female_100 |
Population > Family households > Sex ratio (female=100) | decimal | 0% | - | - |
population_collective_households_subtotal |
Population > Collective households > Subtotal | decimal | 0% | - | - |
population_collective_households_male |
Population > Collective households > Male | decimal | 0% | - | - |
population_collective_households_female |
Population > Collective households > Female | decimal | 0% | - | - |
population_collective_households_sex_ratio_female_100 |
Population > Collective households > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_2 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_3 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_4 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_5 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_6 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi |
Living in this township, town or subdistrict, household registration pending > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_2 |
Living in this township, town or subdistrict, household registration pending > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_3 |
Living in this township, town or subdistrict, household registration pending > Female | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Subtotal | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_2 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Male | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_3 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_2 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_3 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_4 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_5 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_6 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi |
Living in this township, town or subdistrict, household registration pending > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_2 |
Living in this township, town or subdistrict, household registration pending > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_3 |
Living in this township, town or subdistrict, household registration pending > Female | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Subtotal | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_2 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Male | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_3 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_2 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_3 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_4 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_5 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_6 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi |
Living in this township, town or subdistrict, household registration pending > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_2 |
Living in this township, town or subdistrict, household registration pending > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_3 |
Living in this township, town or subdistrict, household registration pending > Female | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Subtotal | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_2 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Male | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_3 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_2 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_3 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_4 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_5 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_6 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi |
Living in this township, town or subdistrict, household registration pending > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_2 |
Living in this township, town or subdistrict, household registration pending > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_3 |
Living in this township, town or subdistrict, household registration pending > Female | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Subtotal | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_2 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Male | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_3 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district_ |
Place of household registration > Same county (city, district) > Subtotal | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district__2 |
Place of household registration > Same county (city, district) > Male | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district__3 |
Place of household registration > Same county (city, district) > Female | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district |
Place of household registration > Other county (city, district) in the same province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district_2 |
Place of household registration > Other county (city, district) in the same province > Male | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district_3 |
Place of household registration > Other county (city, district) in the same province > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district_ |
Place of household registration > Same county (city, district) > Subtotal | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district__2 |
Place of household registration > Same county (city, district) > Male | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district__3 |
Place of household registration > Same county (city, district) > Female | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district |
Place of household registration > Other county (city, district) in the same province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district_2 |
Place of household registration > Other county (city, district) in the same province > Male | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district_3 |
Place of household registration > Other county (city, district) in the same province > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district_ |
Place of household registration > Same county (city, district) > Subtotal | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district__2 |
Place of household registration > Same county (city, district) > Male | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district__3 |
Place of household registration > Same county (city, district) > Female | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district |
Place of household registration > Other county (city, district) in the same province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district_2 |
Place of household registration > Other county (city, district) in the same province > Male | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district_3 |
Place of household registration > Other county (city, district) in the same province > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district_ |
Place of household registration > Same county (city, district) > Subtotal | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district__2 |
Place of household registration > Same county (city, district) > Male | decimal | 0% | - | - |
place_of_household_registration_same_county_city_district__3 |
Place of household registration > Same county (city, district) > Female | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district |
Place of household registration > Other county (city, district) in the same province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district_2 |
Place of household registration > Other county (city, district) in the same province > Male | decimal | 0% | - | - |
place_of_household_registration_other_county_city_district_3 |
Place of household registration > Other county (city, district) in the same province > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
han_subtotal |
Han > Subtotal | decimal | 0% | - | - |
han_male |
Han > Male | decimal | 0% | - | - |
han_female |
Han > Female | decimal | 0% | - | - |
mongol_subtotal |
Mongol > Subtotal | decimal | 0% | - | - |
mongol_male |
Mongol > Male | decimal | 0% | - | - |
mongol_female |
Mongol > Female | decimal | 0% | - | - |
hui_subtotal |
Hui > Subtotal | decimal | 0% | - | - |
hui_male |
Hui > Male | decimal | 0% | - | - |
hui_female |
Hui > Female | decimal | 0% | - | - |
tibetan_subtotal |
Tibetan > Subtotal | decimal | 0% | - | - |
tibetan_male |
Tibetan > Male | decimal | 0% | - | - |
tibetan_female |
Tibetan > Female | decimal | 0% | - | - |
uygur_subtotal |
Uygur > Subtotal | decimal | 0% | - | - |
uygur_male |
Uygur > Male | decimal | 0% | - | - |
uygur_female |
Uygur > Female | decimal | 0% | - | - |
miao_subtotal |
Miao > Subtotal | decimal | 0% | - | - |
miao_male |
Miao > Male | decimal | 0% | - | - |
miao_female |
Miao > Female | decimal | 0% | - | - |
yi_subtotal |
Yi > Subtotal | decimal | 0% | - | - |
yi_male |
Yi > Male | decimal | 0% | - | - |
yi_female |
Yi > Female | decimal | 0% | - | - |
zhuang_subtotal |
Zhuang > Subtotal | decimal | 0% | - | - |
zhuang_male |
Zhuang > Male | decimal | 0% | - | - |
zhuang_female |
Zhuang > Female | decimal | 0% | - | - |
bouyei_subtotal |
Bouyei > Subtotal | decimal | 0% | - | - |
| +149 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
han_subtotal |
Han > Subtotal | decimal | 0% | - | - |
han_male |
Han > Male | decimal | 0% | - | - |
han_female |
Han > Female | decimal | 0% | - | - |
mongol_subtotal |
Mongol > Subtotal | decimal | 0% | - | - |
mongol_male |
Mongol > Male | decimal | 0% | - | - |
mongol_female |
Mongol > Female | decimal | 0% | - | - |
hui_subtotal |
Hui > Subtotal | decimal | 0% | - | - |
hui_male |
Hui > Male | decimal | 0% | - | - |
hui_female |
Hui > Female | decimal | 0% | - | - |
tibetan_subtotal |
Tibetan > Subtotal | decimal | 0% | - | - |
tibetan_male |
Tibetan > Male | decimal | 0% | - | - |
tibetan_female |
Tibetan > Female | decimal | 0% | - | - |
uygur_subtotal |
Uygur > Subtotal | decimal | 0% | - | - |
uygur_male |
Uygur > Male | decimal | 0% | - | - |
uygur_female |
Uygur > Female | decimal | 0% | - | - |
miao_subtotal |
Miao > Subtotal | decimal | 0% | - | - |
miao_male |
Miao > Male | decimal | 0% | - | - |
miao_female |
Miao > Female | decimal | 0% | - | - |
yi_subtotal |
Yi > Subtotal | decimal | 0% | - | - |
yi_male |
Yi > Male | decimal | 0% | - | - |
yi_female |
Yi > Female | decimal | 0% | - | - |
zhuang_subtotal |
Zhuang > Subtotal | decimal | 0% | - | - |
zhuang_male |
Zhuang > Male | decimal | 0% | - | - |
zhuang_female |
Zhuang > Female | decimal | 0% | - | - |
bouyei_subtotal |
Bouyei > Subtotal | decimal | 0% | - | - |
| +149 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
han_subtotal |
Han > Subtotal | decimal | 0% | - | - |
han_male |
Han > Male | decimal | 0% | - | - |
han_female |
Han > Female | decimal | 0% | - | - |
mongol_subtotal |
Mongol > Subtotal | decimal | 0% | - | - |
mongol_male |
Mongol > Male | decimal | 0% | - | - |
mongol_female |
Mongol > Female | decimal | 0% | - | - |
hui_subtotal |
Hui > Subtotal | decimal | 0% | - | - |
hui_male |
Hui > Male | decimal | 0% | - | - |
hui_female |
Hui > Female | decimal | 0% | - | - |
tibetan_subtotal |
Tibetan > Subtotal | decimal | 0% | - | - |
tibetan_male |
Tibetan > Male | decimal | 0% | - | - |
tibetan_female |
Tibetan > Female | decimal | 0% | - | - |
uygur_subtotal |
Uygur > Subtotal | decimal | 0% | - | - |
uygur_male |
Uygur > Male | decimal | 0% | - | - |
uygur_female |
Uygur > Female | decimal | 0% | - | - |
miao_subtotal |
Miao > Subtotal | decimal | 0% | - | - |
miao_male |
Miao > Male | decimal | 0% | - | - |
miao_female |
Miao > Female | decimal | 0% | - | - |
yi_subtotal |
Yi > Subtotal | decimal | 0% | - | - |
yi_male |
Yi > Male | decimal | 0% | - | - |
yi_female |
Yi > Female | decimal | 0% | - | - |
zhuang_subtotal |
Zhuang > Subtotal | decimal | 0% | - | - |
zhuang_male |
Zhuang > Male | decimal | 0% | - | - |
zhuang_female |
Zhuang > Female | decimal | 0% | - | - |
bouyei_subtotal |
Bouyei > Subtotal | decimal | 0% | - | - |
| +149 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
han_subtotal |
Han > Subtotal | decimal | 0% | - | - |
han_male |
Han > Male | decimal | 0% | - | - |
han_female |
Han > Female | decimal | 0% | - | - |
mongol_subtotal |
Mongol > Subtotal | decimal | 0% | - | - |
mongol_male |
Mongol > Male | decimal | 0% | - | - |
mongol_female |
Mongol > Female | decimal | 0% | - | - |
hui_subtotal |
Hui > Subtotal | decimal | 0% | - | - |
hui_male |
Hui > Male | decimal | 0% | - | - |
hui_female |
Hui > Female | decimal | 0% | - | - |
tibetan_subtotal |
Tibetan > Subtotal | decimal | 0% | - | - |
tibetan_male |
Tibetan > Male | decimal | 0% | - | - |
tibetan_female |
Tibetan > Female | decimal | 0% | - | - |
uygur_subtotal |
Uygur > Subtotal | decimal | 0% | - | - |
uygur_male |
Uygur > Male | decimal | 0% | - | - |
uygur_female |
Uygur > Female | decimal | 0% | - | - |
miao_subtotal |
Miao > Subtotal | decimal | 0% | - | - |
miao_male |
Miao > Male | decimal | 0% | - | - |
miao_female |
Miao > Female | decimal | 0% | - | - |
yi_subtotal |
Yi > Subtotal | decimal | 0% | - | - |
yi_male |
Yi > Male | decimal | 0% | - | - |
yi_female |
Yi > Female | decimal | 0% | - | - |
zhuang_subtotal |
Zhuang > Subtotal | decimal | 0% | - | - |
zhuang_male |
Zhuang > Male | decimal | 0% | - | - |
zhuang_female |
Zhuang > Female | decimal | 0% | - | - |
bouyei_subtotal |
Bouyei > Subtotal | decimal | 0% | - | - |
| +149 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
ⓘ 1-in-10 household sample. These tables come from the census long questionnaire, which about one household in ten answered. The National Bureau of Statistics publishes the sample's own counts without scaling them up, so counts here are about a tenth of the real figure: this sample counted 138,657,945 people, against 1,409,778,724 in the full count. Shares, rates and averages can be used as they are; for population totals use the full-count datasets.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
marital_status |
Marital status | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
marital_status |
Marital status | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
marital_status |
Marital status | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
marital_status |
Marital status | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
main_source_of_living |
Main source of living | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
main_source_of_living |
Main source of living | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
main_source_of_living |
Main source of living | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
main_source_of_living |
Main source of living | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
living_arrangement |
Living arrangement | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
living_arrangement |
Living arrangement | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
living_arrangement |
Living arrangement | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
living_arrangement |
Living arrangement | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
income_from_work_subtotal |
Income from work > Subtotal | decimal | 0% | - | - |
income_from_work_male |
Income from work > Male | decimal | 0% | - | - |
income_from_work_female |
Income from work > Female | decimal | 0% | - | - |
retirement_pension_old_age_pension_subtotal |
Retirement pension / old-age pension > Subtotal | decimal | 0% | - | - |
retirement_pension_old_age_pension_male |
Retirement pension / old-age pension > Male | decimal | 0% | - | - |
retirement_pension_old_age_pension_female |
Retirement pension / old-age pension > Female | decimal | 0% | - | - |
minimum_living_allowance_subtotal |
Minimum living allowance > Subtotal | decimal | 0% | - | - |
minimum_living_allowance_male |
Minimum living allowance > Male | decimal | 0% | - | - |
minimum_living_allowance_female |
Minimum living allowance > Female | decimal | 0% | - | - |
unemployment_insurance_benefit_subtotal |
Unemployment insurance benefit > Subtotal | decimal | 0% | - | - |
unemployment_insurance_benefit_male |
Unemployment insurance benefit > Male | decimal | 0% | - | - |
unemployment_insurance_benefit_female |
Unemployment insurance benefit > Female | decimal | 0% | - | - |
property_income_subtotal |
Property income > Subtotal | decimal | 0% | - | - |
property_income_male |
Property income > Male | decimal | 0% | - | - |
property_income_female |
Property income > Female | decimal | 0% | - | - |
supported_by_other_household_members_subtotal |
Supported by other household members > Subtotal | decimal | 0% | - | - |
supported_by_other_household_members_male |
Supported by other household members > Male | decimal | 0% | - | - |
supported_by_other_household_members_female |
Supported by other household members > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
income_from_work_subtotal |
Income from work > Subtotal | decimal | 0% | - | - |
income_from_work_male |
Income from work > Male | decimal | 0% | - | - |
income_from_work_female |
Income from work > Female | decimal | 0% | - | - |
retirement_pension_old_age_pension_subtotal |
Retirement pension / old-age pension > Subtotal | decimal | 0% | - | - |
retirement_pension_old_age_pension_male |
Retirement pension / old-age pension > Male | decimal | 0% | - | - |
retirement_pension_old_age_pension_female |
Retirement pension / old-age pension > Female | decimal | 0% | - | - |
minimum_living_allowance_subtotal |
Minimum living allowance > Subtotal | decimal | 0% | - | - |
minimum_living_allowance_male |
Minimum living allowance > Male | decimal | 0% | - | - |
minimum_living_allowance_female |
Minimum living allowance > Female | decimal | 0% | - | - |
unemployment_insurance_benefit_subtotal |
Unemployment insurance benefit > Subtotal | decimal | 0% | - | - |
unemployment_insurance_benefit_male |
Unemployment insurance benefit > Male | decimal | 0% | - | - |
unemployment_insurance_benefit_female |
Unemployment insurance benefit > Female | decimal | 0% | - | - |
property_income_subtotal |
Property income > Subtotal | decimal | 0% | - | - |
property_income_male |
Property income > Male | decimal | 0% | - | - |
property_income_female |
Property income > Female | decimal | 0% | - | - |
supported_by_other_household_members_subtotal |
Supported by other household members > Subtotal | decimal | 0% | - | - |
supported_by_other_household_members_male |
Supported by other household members > Male | decimal | 0% | - | - |
supported_by_other_household_members_female |
Supported by other household members > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
income_from_work_subtotal |
Income from work > Subtotal | decimal | 0% | - | - |
income_from_work_male |
Income from work > Male | decimal | 0% | - | - |
income_from_work_female |
Income from work > Female | decimal | 0% | - | - |
retirement_pension_old_age_pension_subtotal |
Retirement pension / old-age pension > Subtotal | decimal | 0% | - | - |
retirement_pension_old_age_pension_male |
Retirement pension / old-age pension > Male | decimal | 0% | - | - |
retirement_pension_old_age_pension_female |
Retirement pension / old-age pension > Female | decimal | 0% | - | - |
minimum_living_allowance_subtotal |
Minimum living allowance > Subtotal | decimal | 0% | - | - |
minimum_living_allowance_male |
Minimum living allowance > Male | decimal | 0% | - | - |
minimum_living_allowance_female |
Minimum living allowance > Female | decimal | 0% | - | - |
unemployment_insurance_benefit_subtotal |
Unemployment insurance benefit > Subtotal | decimal | 0% | - | - |
unemployment_insurance_benefit_male |
Unemployment insurance benefit > Male | decimal | 0% | - | - |
unemployment_insurance_benefit_female |
Unemployment insurance benefit > Female | decimal | 0% | - | - |
property_income_subtotal |
Property income > Subtotal | decimal | 0% | - | - |
property_income_male |
Property income > Male | decimal | 0% | - | - |
property_income_female |
Property income > Female | decimal | 0% | - | - |
supported_by_other_household_members_subtotal |
Supported by other household members > Subtotal | decimal | 0% | - | - |
supported_by_other_household_members_male |
Supported by other household members > Male | decimal | 0% | - | - |
supported_by_other_household_members_female |
Supported by other household members > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
income_from_work_subtotal |
Income from work > Subtotal | decimal | 0% | - | - |
income_from_work_male |
Income from work > Male | decimal | 0% | - | - |
income_from_work_female |
Income from work > Female | decimal | 0% | - | - |
retirement_pension_old_age_pension_subtotal |
Retirement pension / old-age pension > Subtotal | decimal | 0% | - | - |
retirement_pension_old_age_pension_male |
Retirement pension / old-age pension > Male | decimal | 0% | - | - |
retirement_pension_old_age_pension_female |
Retirement pension / old-age pension > Female | decimal | 0% | - | - |
minimum_living_allowance_subtotal |
Minimum living allowance > Subtotal | decimal | 0% | - | - |
minimum_living_allowance_male |
Minimum living allowance > Male | decimal | 0% | - | - |
minimum_living_allowance_female |
Minimum living allowance > Female | decimal | 0% | - | - |
unemployment_insurance_benefit_subtotal |
Unemployment insurance benefit > Subtotal | decimal | 0% | - | - |
unemployment_insurance_benefit_male |
Unemployment insurance benefit > Male | decimal | 0% | - | - |
unemployment_insurance_benefit_female |
Unemployment insurance benefit > Female | decimal | 0% | - | - |
property_income_subtotal |
Property income > Subtotal | decimal | 0% | - | - |
property_income_male |
Property income > Male | decimal | 0% | - | - |
property_income_female |
Property income > Female | decimal | 0% | - | - |
supported_by_other_household_members_subtotal |
Supported by other household members > Subtotal | decimal | 0% | - | - |
supported_by_other_household_members_male |
Supported by other household members > Male | decimal | 0% | - | - |
supported_by_other_household_members_female |
Supported by other household members > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
healthy_subtotal |
Healthy > Subtotal | decimal | 0% | - | - |
healthy_male |
Healthy > Male | decimal | 0% | - | - |
healthy_female |
Healthy > Female | decimal | 0% | - | - |
basically_healthy_subtotal |
Basically healthy > Subtotal | decimal | 0% | - | - |
basically_healthy_male |
Basically healthy > Male | decimal | 0% | - | - |
basically_healthy_female |
Basically healthy > Female | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_subtotal |
In poor health but able to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_male |
In poor health but able to care for self > Male | decimal | 0% | - | - |
in_poor_health_but_able_to_care_for_self_female |
In poor health but able to care for self > Female | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_subtotal |
In poor health and unable to care for self > Subtotal | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_male |
In poor health and unable to care for self > Male | decimal | 0% | - | - |
in_poor_health_and_unable_to_care_for_self_female |
In poor health and unable to care for self > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
income_from_work_subtotal |
Income from work > Subtotal | decimal | 0% | - | - |
income_from_work_male |
Income from work > Male | decimal | 0% | - | - |
income_from_work_female |
Income from work > Female | decimal | 0% | - | - |
retirement_pension_old_age_pension_subtotal |
Retirement pension / old-age pension > Subtotal | decimal | 0% | - | - |
retirement_pension_old_age_pension_male |
Retirement pension / old-age pension > Male | decimal | 0% | - | - |
retirement_pension_old_age_pension_female |
Retirement pension / old-age pension > Female | decimal | 0% | - | - |
minimum_living_allowance_subtotal |
Minimum living allowance > Subtotal | decimal | 0% | - | - |
minimum_living_allowance_male |
Minimum living allowance > Male | decimal | 0% | - | - |
minimum_living_allowance_female |
Minimum living allowance > Female | decimal | 0% | - | - |
unemployment_insurance_benefit_subtotal |
Unemployment insurance benefit > Subtotal | decimal | 0% | - | - |
unemployment_insurance_benefit_male |
Unemployment insurance benefit > Male | decimal | 0% | - | - |
unemployment_insurance_benefit_female |
Unemployment insurance benefit > Female | decimal | 0% | - | - |
property_income_subtotal |
Property income > Subtotal | decimal | 0% | - | - |
property_income_male |
Property income > Male | decimal | 0% | - | - |
property_income_female |
Property income > Female | decimal | 0% | - | - |
supported_by_other_household_members_subtotal |
Supported by other household members > Subtotal | decimal | 0% | - | - |
supported_by_other_household_members_male |
Supported by other household members > Male | decimal | 0% | - | - |
supported_by_other_household_members_female |
Supported by other household members > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
income_from_work_subtotal |
Income from work > Subtotal | decimal | 0% | - | - |
income_from_work_male |
Income from work > Male | decimal | 0% | - | - |
income_from_work_female |
Income from work > Female | decimal | 0% | - | - |
retirement_pension_old_age_pension_subtotal |
Retirement pension / old-age pension > Subtotal | decimal | 0% | - | - |
retirement_pension_old_age_pension_male |
Retirement pension / old-age pension > Male | decimal | 0% | - | - |
retirement_pension_old_age_pension_female |
Retirement pension / old-age pension > Female | decimal | 0% | - | - |
minimum_living_allowance_subtotal |
Minimum living allowance > Subtotal | decimal | 0% | - | - |
minimum_living_allowance_male |
Minimum living allowance > Male | decimal | 0% | - | - |
minimum_living_allowance_female |
Minimum living allowance > Female | decimal | 0% | - | - |
unemployment_insurance_benefit_subtotal |
Unemployment insurance benefit > Subtotal | decimal | 0% | - | - |
unemployment_insurance_benefit_male |
Unemployment insurance benefit > Male | decimal | 0% | - | - |
unemployment_insurance_benefit_female |
Unemployment insurance benefit > Female | decimal | 0% | - | - |
property_income_subtotal |
Property income > Subtotal | decimal | 0% | - | - |
property_income_male |
Property income > Male | decimal | 0% | - | - |
property_income_female |
Property income > Female | decimal | 0% | - | - |
supported_by_other_household_members_subtotal |
Supported by other household members > Subtotal | decimal | 0% | - | - |
supported_by_other_household_members_male |
Supported by other household members > Male | decimal | 0% | - | - |
supported_by_other_household_members_female |
Supported by other household members > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
income_from_work_subtotal |
Income from work > Subtotal | decimal | 0% | - | - |
income_from_work_male |
Income from work > Male | decimal | 0% | - | - |
income_from_work_female |
Income from work > Female | decimal | 0% | - | - |
retirement_pension_old_age_pension_subtotal |
Retirement pension / old-age pension > Subtotal | decimal | 0% | - | - |
retirement_pension_old_age_pension_male |
Retirement pension / old-age pension > Male | decimal | 0% | - | - |
retirement_pension_old_age_pension_female |
Retirement pension / old-age pension > Female | decimal | 0% | - | - |
minimum_living_allowance_subtotal |
Minimum living allowance > Subtotal | decimal | 0% | - | - |
minimum_living_allowance_male |
Minimum living allowance > Male | decimal | 0% | - | - |
minimum_living_allowance_female |
Minimum living allowance > Female | decimal | 0% | - | - |
unemployment_insurance_benefit_subtotal |
Unemployment insurance benefit > Subtotal | decimal | 0% | - | - |
unemployment_insurance_benefit_male |
Unemployment insurance benefit > Male | decimal | 0% | - | - |
unemployment_insurance_benefit_female |
Unemployment insurance benefit > Female | decimal | 0% | - | - |
property_income_subtotal |
Property income > Subtotal | decimal | 0% | - | - |
property_income_male |
Property income > Male | decimal | 0% | - | - |
property_income_female |
Property income > Female | decimal | 0% | - | - |
supported_by_other_household_members_subtotal |
Supported by other household members > Subtotal | decimal | 0% | - | - |
supported_by_other_household_members_male |
Supported by other household members > Male | decimal | 0% | - | - |
supported_by_other_household_members_female |
Supported by other household members > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
income_from_work_subtotal |
Income from work > Subtotal | decimal | 0% | - | - |
income_from_work_male |
Income from work > Male | decimal | 0% | - | - |
income_from_work_female |
Income from work > Female | decimal | 0% | - | - |
retirement_pension_old_age_pension_subtotal |
Retirement pension / old-age pension > Subtotal | decimal | 0% | - | - |
retirement_pension_old_age_pension_male |
Retirement pension / old-age pension > Male | decimal | 0% | - | - |
retirement_pension_old_age_pension_female |
Retirement pension / old-age pension > Female | decimal | 0% | - | - |
minimum_living_allowance_subtotal |
Minimum living allowance > Subtotal | decimal | 0% | - | - |
minimum_living_allowance_male |
Minimum living allowance > Male | decimal | 0% | - | - |
minimum_living_allowance_female |
Minimum living allowance > Female | decimal | 0% | - | - |
unemployment_insurance_benefit_subtotal |
Unemployment insurance benefit > Subtotal | decimal | 0% | - | - |
unemployment_insurance_benefit_male |
Unemployment insurance benefit > Male | decimal | 0% | - | - |
unemployment_insurance_benefit_female |
Unemployment insurance benefit > Female | decimal | 0% | - | - |
property_income_subtotal |
Property income > Subtotal | decimal | 0% | - | - |
property_income_male |
Property income > Male | decimal | 0% | - | - |
property_income_female |
Property income > Female | decimal | 0% | - | - |
supported_by_other_household_members_subtotal |
Supported by other household members > Subtotal | decimal | 0% | - | - |
supported_by_other_household_members_male |
Supported by other household members > Male | decimal | 0% | - | - |
supported_by_other_household_members_female |
Supported by other household members > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
living_with_spouse_and_children_subtotal |
Living with spouse and children > Subtotal | decimal | 0% | - | - |
living_with_spouse_and_children_male |
Living with spouse and children > Male | decimal | 0% | - | - |
living_with_spouse_and_children_female |
Living with spouse and children > Female | decimal | 0% | - | - |
living_with_spouse_subtotal |
Living with spouse > Subtotal | decimal | 0% | - | - |
living_with_spouse_male |
Living with spouse > Male | decimal | 0% | - | - |
living_with_spouse_female |
Living with spouse > Female | decimal | 0% | - | - |
living_with_children_subtotal |
Living with children > Subtotal | decimal | 0% | - | - |
living_with_children_male |
Living with children > Male | decimal | 0% | - | - |
living_with_children_female |
Living with children > Female | decimal | 0% | - | - |
living_alone_with_domestic_helper_subtotal |
Living alone (with domestic helper) > Subtotal | decimal | 0% | - | - |
living_alone_with_domestic_helper_male |
Living alone (with domestic helper) > Male | decimal | 0% | - | - |
living_alone_with_domestic_helper_female |
Living alone (with domestic helper) > Female | decimal | 0% | - | - |
living_alone_without_domestic_helper_subtotal |
Living alone (without domestic helper) > Subtotal | decimal | 0% | - | - |
living_alone_without_domestic_helper_male |
Living alone (without domestic helper) > Male | decimal | 0% | - | - |
living_alone_without_domestic_helper_female |
Living alone (without domestic helper) > Female | decimal | 0% | - | - |
institution_for_the_elderly_subtotal |
Institution for the elderly > Subtotal | decimal | 0% | - | - |
institution_for_the_elderly_male |
Institution for the elderly > Male | decimal | 0% | - | - |
institution_for_the_elderly_female |
Institution for the elderly > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
living_with_spouse_and_children_subtotal |
Living with spouse and children > Subtotal | decimal | 0% | - | - |
living_with_spouse_and_children_male |
Living with spouse and children > Male | decimal | 0% | - | - |
living_with_spouse_and_children_female |
Living with spouse and children > Female | decimal | 0% | - | - |
living_with_spouse_subtotal |
Living with spouse > Subtotal | decimal | 0% | - | - |
living_with_spouse_male |
Living with spouse > Male | decimal | 0% | - | - |
living_with_spouse_female |
Living with spouse > Female | decimal | 0% | - | - |
living_with_children_subtotal |
Living with children > Subtotal | decimal | 0% | - | - |
living_with_children_male |
Living with children > Male | decimal | 0% | - | - |
living_with_children_female |
Living with children > Female | decimal | 0% | - | - |
living_alone_with_domestic_helper_subtotal |
Living alone (with domestic helper) > Subtotal | decimal | 0% | - | - |
living_alone_with_domestic_helper_male |
Living alone (with domestic helper) > Male | decimal | 0% | - | - |
living_alone_with_domestic_helper_female |
Living alone (with domestic helper) > Female | decimal | 0% | - | - |
living_alone_without_domestic_helper_subtotal |
Living alone (without domestic helper) > Subtotal | decimal | 0% | - | - |
living_alone_without_domestic_helper_male |
Living alone (without domestic helper) > Male | decimal | 0% | - | - |
living_alone_without_domestic_helper_female |
Living alone (without domestic helper) > Female | decimal | 0% | - | - |
institution_for_the_elderly_subtotal |
Institution for the elderly > Subtotal | decimal | 0% | - | - |
institution_for_the_elderly_male |
Institution for the elderly > Male | decimal | 0% | - | - |
institution_for_the_elderly_female |
Institution for the elderly > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
living_with_spouse_and_children_subtotal |
Living with spouse and children > Subtotal | decimal | 0% | - | - |
living_with_spouse_and_children_male |
Living with spouse and children > Male | decimal | 0% | - | - |
living_with_spouse_and_children_female |
Living with spouse and children > Female | decimal | 0% | - | - |
living_with_spouse_subtotal |
Living with spouse > Subtotal | decimal | 0% | - | - |
living_with_spouse_male |
Living with spouse > Male | decimal | 0% | - | - |
living_with_spouse_female |
Living with spouse > Female | decimal | 0% | - | - |
living_with_children_subtotal |
Living with children > Subtotal | decimal | 0% | - | - |
living_with_children_male |
Living with children > Male | decimal | 0% | - | - |
living_with_children_female |
Living with children > Female | decimal | 0% | - | - |
living_alone_with_domestic_helper_subtotal |
Living alone (with domestic helper) > Subtotal | decimal | 0% | - | - |
living_alone_with_domestic_helper_male |
Living alone (with domestic helper) > Male | decimal | 0% | - | - |
living_alone_with_domestic_helper_female |
Living alone (with domestic helper) > Female | decimal | 0% | - | - |
living_alone_without_domestic_helper_subtotal |
Living alone (without domestic helper) > Subtotal | decimal | 0% | - | - |
living_alone_without_domestic_helper_male |
Living alone (without domestic helper) > Male | decimal | 0% | - | - |
living_alone_without_domestic_helper_female |
Living alone (without domestic helper) > Female | decimal | 0% | - | - |
institution_for_the_elderly_subtotal |
Institution for the elderly > Subtotal | decimal | 0% | - | - |
institution_for_the_elderly_male |
Institution for the elderly > Male | decimal | 0% | - | - |
institution_for_the_elderly_female |
Institution for the elderly > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_60_and_over_total |
Population aged 60 and over > Total | decimal | 0% | - | - |
population_aged_60_and_over_male |
Population aged 60 and over > Male | decimal | 0% | - | - |
population_aged_60_and_over_female |
Population aged 60 and over > Female | decimal | 0% | - | - |
living_with_spouse_and_children_subtotal |
Living with spouse and children > Subtotal | decimal | 0% | - | - |
living_with_spouse_and_children_male |
Living with spouse and children > Male | decimal | 0% | - | - |
living_with_spouse_and_children_female |
Living with spouse and children > Female | decimal | 0% | - | - |
living_with_spouse_subtotal |
Living with spouse > Subtotal | decimal | 0% | - | - |
living_with_spouse_male |
Living with spouse > Male | decimal | 0% | - | - |
living_with_spouse_female |
Living with spouse > Female | decimal | 0% | - | - |
living_with_children_subtotal |
Living with children > Subtotal | decimal | 0% | - | - |
living_with_children_male |
Living with children > Male | decimal | 0% | - | - |
living_with_children_female |
Living with children > Female | decimal | 0% | - | - |
living_alone_with_domestic_helper_subtotal |
Living alone (with domestic helper) > Subtotal | decimal | 0% | - | - |
living_alone_with_domestic_helper_male |
Living alone (with domestic helper) > Male | decimal | 0% | - | - |
living_alone_with_domestic_helper_female |
Living alone (with domestic helper) > Female | decimal | 0% | - | - |
living_alone_without_domestic_helper_subtotal |
Living alone (without domestic helper) > Subtotal | decimal | 0% | - | - |
living_alone_without_domestic_helper_male |
Living alone (without domestic helper) > Male | decimal | 0% | - | - |
living_alone_without_domestic_helper_female |
Living alone (without domestic helper) > Female | decimal | 0% | - | - |
institution_for_the_elderly_subtotal |
Institution for the elderly > Subtotal | decimal | 0% | - | - |
institution_for_the_elderly_male |
Institution for the elderly > Male | decimal | 0% | - | - |
institution_for_the_elderly_female |
Institution for the elderly > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_3_and_over_total |
Population aged 3 and over > Total | decimal | 0% | - | - |
population_aged_3_and_over_male |
Population aged 3 and over > Male | decimal | 0% | - | - |
population_aged_3_and_over_female |
Population aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_3_and_over_total |
Population aged 3 and over > Total | decimal | 0% | - | - |
population_aged_3_and_over_male |
Population aged 3 and over > Male | decimal | 0% | - | - |
population_aged_3_and_over_female |
Population aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_3_and_over_total |
Population aged 3 and over > Total | decimal | 0% | - | - |
population_aged_3_and_over_male |
Population aged 3 and over > Male | decimal | 0% | - | - |
population_aged_3_and_over_female |
Population aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_3_and_over_total |
Population aged 3 and over > Total | decimal | 0% | - | - |
population_aged_3_and_over_male |
Population aged 3 and over > Male | decimal | 0% | - | - |
population_aged_3_and_over_female |
Population aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
illiterate_population_total |
Illiterate population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
illiterate_population_male |
Illiterate population > Male | decimal | 0% | - | - |
illiterate_population_female |
Illiterate population > Female | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and |
Illiterate population as a share of population aged 15 and over > Total | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and_2 |
Illiterate population as a share of population aged 15 and over > Male | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and_3 |
Illiterate population as a share of population aged 15 and over > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
illiterate_population_total |
Illiterate population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
illiterate_population_male |
Illiterate population > Male | decimal | 0% | - | - |
illiterate_population_female |
Illiterate population > Female | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and |
Illiterate population as a share of population aged 15 and over > Total | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and_2 |
Illiterate population as a share of population aged 15 and over > Male | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and_3 |
Illiterate population as a share of population aged 15 and over > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
illiterate_population_total |
Illiterate population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
illiterate_population_male |
Illiterate population > Male | decimal | 0% | - | - |
illiterate_population_female |
Illiterate population > Female | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and |
Illiterate population as a share of population aged 15 and over > Total | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and_2 |
Illiterate population as a share of population aged 15 and over > Male | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and_3 |
Illiterate population as a share of population aged 15 and over > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
illiterate_population_total |
Illiterate population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
illiterate_population_male |
Illiterate population > Male | decimal | 0% | - | - |
illiterate_population_female |
Illiterate population > Female | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and |
Illiterate population as a share of population aged 15 and over > Total | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and_2 |
Illiterate population as a share of population aged 15 and over > Male | decimal | 0% | - | - |
illiterate_population_as_a_share_of_population_aged_15_and_3 |
Illiterate population as a share of population aged 15 and over > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_16_59_total |
Population aged 16-59 > Total | decimal | 0% | - | - |
population_aged_16_59_male |
Population aged 16-59 > Male | decimal | 0% | - | - |
population_aged_16_59_female |
Population aged 16-59 > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_16_59_total |
Population aged 16-59 > Total | decimal | 0% | - | - |
population_aged_16_59_male |
Population aged 16-59 > Male | decimal | 0% | - | - |
population_aged_16_59_female |
Population aged 16-59 > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_16_59_total |
Population aged 16-59 > Total | decimal | 0% | - | - |
population_aged_16_59_male |
Population aged 16-59 > Male | decimal | 0% | - | - |
population_aged_16_59_female |
Population aged 16-59 > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_16_59_total |
Population aged 16-59 > Total | decimal | 0% | - | - |
population_aged_16_59_male |
Population aged 16-59 > Male | decimal | 0% | - | - |
population_aged_16_59_female |
Population aged 16-59 > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_25_and_over_total |
Population aged 25 and over > Total | decimal | 0% | - | - |
population_aged_25_and_over_male |
Population aged 25 and over > Male | decimal | 0% | - | - |
population_aged_25_and_over_female |
Population aged 25 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_25_and_over_total |
Population aged 25 and over > Total | decimal | 0% | - | - |
population_aged_25_and_over_male |
Population aged 25 and over > Male | decimal | 0% | - | - |
population_aged_25_and_over_female |
Population aged 25 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_25_and_over_total |
Population aged 25 and over > Total | decimal | 0% | - | - |
population_aged_25_and_over_male |
Population aged 25 and over > Male | decimal | 0% | - | - |
population_aged_25_and_over_female |
Population aged 25 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_25_and_over_total |
Population aged 25 and over > Total | decimal | 0% | - | - |
population_aged_25_and_over_male |
Population aged 25 and over > Male | decimal | 0% | - | - |
population_aged_25_and_over_female |
Population aged 25 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
ⓘ 1-in-10 household sample. These tables come from the census long questionnaire, which about one household in ten answered. The National Bureau of Statistics publishes the sample's own counts without scaling them up, so counts here are about a tenth of the real figure: this sample counted 138,657,945 people, against 1,409,778,724 in the full count. Shares, rates and averages can be used as they are; for population totals use the full-count datasets.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_households |
Number of households (households) | decimal | 0% | - | - |
number_of_persons_persons |
Number of persons (persons) | decimal | 0% | - | - |
average_rooms_per_household_rooms_household |
Average rooms per household (rooms/household) | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_person |
Per capita housing floor area (square metres/person) | decimal | 0% | - | - |
rooms_per_person_rooms_person |
Rooms per person (rooms/person) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_households |
Number of households (households) | decimal | 0% | - | - |
number_of_persons_persons |
Number of persons (persons) | decimal | 0% | - | - |
average_rooms_per_household_rooms_household |
Average rooms per household (rooms/household) | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_person |
Per capita housing floor area (square metres/person) | decimal | 0% | - | - |
rooms_per_person_rooms_person |
Rooms per person (rooms/person) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_households |
Number of households (households) | decimal | 0% | - | - |
number_of_persons_persons |
Number of persons (persons) | decimal | 0% | - | - |
average_rooms_per_household_rooms_household |
Average rooms per household (rooms/household) | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_person |
Per capita housing floor area (square metres/person) | decimal | 0% | - | - |
rooms_per_person_rooms_person |
Rooms per person (rooms/person) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
occupation_major_group |
Occupation major group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_households |
Number of households (households) | decimal | 0% | - | - |
number_of_persons_persons |
Number of persons (persons) | decimal | 0% | - | - |
average_rooms_per_household_rooms_household |
Average rooms per household (rooms/household) | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_person |
Per capita housing floor area (square metres/person) | decimal | 0% | - | - |
rooms_per_person_rooms_person |
Rooms per person (rooms/person) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_building_floors_single_storey_house |
Number of building floors > Single-storey house | decimal | 0% | - | - |
number_of_building_floors_multi_storey_7_floors_or_fewer |
Number of building floors > Multi-storey (7 floors or fewer) | decimal | 0% | - | - |
number_of_building_floors_high_rise_8_33_floors |
Number of building floors > High-rise (8-33 floors) | decimal | 0% | - | - |
number_of_building_floors_super_high_rise_34_floors_or_mor |
Number of building floors > Super high-rise (34 floors or more) | decimal | 0% | - | - |
load_bearing_structure_type_steel_and_reinforced_concrete_ |
Load-bearing structure type > Steel and reinforced concrete structure | decimal | 0% | - | - |
load_bearing_structure_type_mixed_structure |
Load-bearing structure type > Mixed structure | decimal | 0% | - | - |
load_bearing_structure_type_brick_and_wood_structure |
Load-bearing structure type > Brick and wood structure | decimal | 0% | - | - |
load_bearing_structure_type_bamboo_straw_and_adobe_structu |
Load-bearing structure type > Bamboo, straw and adobe structure | decimal | 0% | - | - |
load_bearing_structure_type_other_structure |
Load-bearing structure type > Other structure | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_building_floors_single_storey_house |
Number of building floors > Single-storey house | decimal | 0% | - | - |
number_of_building_floors_multi_storey_7_floors_or_fewer |
Number of building floors > Multi-storey (7 floors or fewer) | decimal | 0% | - | - |
number_of_building_floors_high_rise_8_33_floors |
Number of building floors > High-rise (8-33 floors) | decimal | 0% | - | - |
number_of_building_floors_super_high_rise_34_floors_or_mor |
Number of building floors > Super high-rise (34 floors or more) | decimal | 0% | - | - |
load_bearing_structure_type_steel_and_reinforced_concrete_ |
Load-bearing structure type > Steel and reinforced concrete structure | decimal | 0% | - | - |
load_bearing_structure_type_mixed_structure |
Load-bearing structure type > Mixed structure | decimal | 0% | - | - |
load_bearing_structure_type_brick_and_wood_structure |
Load-bearing structure type > Brick and wood structure | decimal | 0% | - | - |
load_bearing_structure_type_bamboo_straw_and_adobe_structu |
Load-bearing structure type > Bamboo, straw and adobe structure | decimal | 0% | - | - |
load_bearing_structure_type_other_structure |
Load-bearing structure type > Other structure | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_building_floors_single_storey_house |
Number of building floors > Single-storey house | decimal | 0% | - | - |
number_of_building_floors_multi_storey_7_floors_or_fewer |
Number of building floors > Multi-storey (7 floors or fewer) | decimal | 0% | - | - |
number_of_building_floors_high_rise_8_33_floors |
Number of building floors > High-rise (8-33 floors) | decimal | 0% | - | - |
number_of_building_floors_super_high_rise_34_floors_or_mor |
Number of building floors > Super high-rise (34 floors or more) | decimal | 0% | - | - |
load_bearing_structure_type_steel_and_reinforced_concrete_ |
Load-bearing structure type > Steel and reinforced concrete structure | decimal | 0% | - | - |
load_bearing_structure_type_mixed_structure |
Load-bearing structure type > Mixed structure | decimal | 0% | - | - |
load_bearing_structure_type_brick_and_wood_structure |
Load-bearing structure type > Brick and wood structure | decimal | 0% | - | - |
load_bearing_structure_type_bamboo_straw_and_adobe_structu |
Load-bearing structure type > Bamboo, straw and adobe structure | decimal | 0% | - | - |
load_bearing_structure_type_other_structure |
Load-bearing structure type > Other structure | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_building_floors_single_storey_house |
Number of building floors > Single-storey house | decimal | 0% | - | - |
number_of_building_floors_multi_storey_7_floors_or_fewer |
Number of building floors > Multi-storey (7 floors or fewer) | decimal | 0% | - | - |
number_of_building_floors_high_rise_8_33_floors |
Number of building floors > High-rise (8-33 floors) | decimal | 0% | - | - |
number_of_building_floors_super_high_rise_34_floors_or_mor |
Number of building floors > Super high-rise (34 floors or more) | decimal | 0% | - | - |
load_bearing_structure_type_steel_and_reinforced_concrete_ |
Load-bearing structure type > Steel and reinforced concrete structure | decimal | 0% | - | - |
load_bearing_structure_type_mixed_structure |
Load-bearing structure type > Mixed structure | decimal | 0% | - | - |
load_bearing_structure_type_brick_and_wood_structure |
Load-bearing structure type > Brick and wood structure | decimal | 0% | - | - |
load_bearing_structure_type_bamboo_straw_and_adobe_structu |
Load-bearing structure type > Bamboo, straw and adobe structure | decimal | 0% | - | - |
load_bearing_structure_type_other_structure |
Load-bearing structure type > Other structure | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_number_of_households |
Total > Number of households | decimal | 0% | - | - |
total_number_of_rooms |
Total > Number of rooms | decimal | 0% | - | - |
total_floor_area |
Total > Floor area | decimal | 0% | - | - |
before_1949_number_of_households |
Before 1949 > Number of households | decimal | 0% | - | - |
before_1949_number_of_rooms |
Before 1949 > Number of rooms | decimal | 0% | - | - |
before_1949_floor_area |
Before 1949 > Floor area | decimal | 0% | - | - |
1949_1959_number_of_households |
1949-1959 > Number of households | decimal | 0% | - | - |
1949_1959_number_of_rooms |
1949-1959 > Number of rooms | decimal | 0% | - | - |
1949_1959_floor_area |
1949-1959 > Floor area | decimal | 0% | - | - |
1960_1969_number_of_households |
1960-1969 > Number of households | decimal | 0% | - | - |
1960_1969_number_of_rooms |
1960-1969 > Number of rooms | decimal | 0% | - | - |
1960_1969_floor_area |
1960-1969 > Floor area | decimal | 0% | - | - |
1970_1979_number_of_households |
1970-1979 > Number of households | decimal | 0% | - | - |
1970_1979_number_of_rooms |
1970-1979 > Number of rooms | decimal | 0% | - | - |
1970_1979_floor_area |
1970-1979 > Floor area | decimal | 0% | - | - |
1980_1989_number_of_households |
1980-1989 > Number of households | decimal | 0% | - | - |
1980_1989_number_of_rooms |
1980-1989 > Number of rooms | decimal | 0% | - | - |
1980_1989_floor_area |
1980-1989 > Floor area | decimal | 0% | - | - |
1990_1999_number_of_households |
1990-1999 > Number of households | decimal | 0% | - | - |
1990_1999_number_of_rooms |
1990-1999 > Number of rooms | decimal | 0% | - | - |
1990_1999_floor_area |
1990-1999 > Floor area | decimal | 0% | - | - |
2000_2009_number_of_households |
2000-2009 > Number of households | decimal | 0% | - | - |
2000_2009_number_of_rooms |
2000-2009 > Number of rooms | decimal | 0% | - | - |
2000_2009_floor_area |
2000-2009 > Floor area | decimal | 0% | - | - |
2010_2014_number_of_households |
2010-2014 > Number of households | decimal | 0% | - | - |
2010_2014_number_of_rooms |
2010-2014 > Number of rooms | decimal | 0% | - | - |
2010_2014_floor_area |
2010-2014 > Floor area | decimal | 0% | - | - |
2015_and_later_number_of_households |
2015 and later > Number of households | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_number_of_households |
Total > Number of households | decimal | 0% | - | - |
total_number_of_rooms |
Total > Number of rooms | decimal | 0% | - | - |
total_floor_area |
Total > Floor area | decimal | 0% | - | - |
before_1949_number_of_households |
Before 1949 > Number of households | decimal | 0% | - | - |
before_1949_number_of_rooms |
Before 1949 > Number of rooms | decimal | 0% | - | - |
before_1949_floor_area |
Before 1949 > Floor area | decimal | 0% | - | - |
1949_1959_number_of_households |
1949-1959 > Number of households | decimal | 0% | - | - |
1949_1959_number_of_rooms |
1949-1959 > Number of rooms | decimal | 0% | - | - |
1949_1959_floor_area |
1949-1959 > Floor area | decimal | 0% | - | - |
1960_1969_number_of_households |
1960-1969 > Number of households | decimal | 0% | - | - |
1960_1969_number_of_rooms |
1960-1969 > Number of rooms | decimal | 0% | - | - |
1960_1969_floor_area |
1960-1969 > Floor area | decimal | 0% | - | - |
1970_1979_number_of_households |
1970-1979 > Number of households | decimal | 0% | - | - |
1970_1979_number_of_rooms |
1970-1979 > Number of rooms | decimal | 0% | - | - |
1970_1979_floor_area |
1970-1979 > Floor area | decimal | 0% | - | - |
1980_1989_number_of_households |
1980-1989 > Number of households | decimal | 0% | - | - |
1980_1989_number_of_rooms |
1980-1989 > Number of rooms | decimal | 0% | - | - |
1980_1989_floor_area |
1980-1989 > Floor area | decimal | 0% | - | - |
1990_1999_number_of_households |
1990-1999 > Number of households | decimal | 0% | - | - |
1990_1999_number_of_rooms |
1990-1999 > Number of rooms | decimal | 0% | - | - |
1990_1999_floor_area |
1990-1999 > Floor area | decimal | 0% | - | - |
2000_2009_number_of_households |
2000-2009 > Number of households | decimal | 0% | - | - |
2000_2009_number_of_rooms |
2000-2009 > Number of rooms | decimal | 0% | - | - |
2000_2009_floor_area |
2000-2009 > Floor area | decimal | 0% | - | - |
2010_2014_number_of_households |
2010-2014 > Number of households | decimal | 0% | - | - |
2010_2014_number_of_rooms |
2010-2014 > Number of rooms | decimal | 0% | - | - |
2010_2014_floor_area |
2010-2014 > Floor area | decimal | 0% | - | - |
2015_and_later_number_of_households |
2015 and later > Number of households | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_number_of_households |
Total > Number of households | decimal | 0% | - | - |
total_number_of_rooms |
Total > Number of rooms | decimal | 0% | - | - |
total_floor_area |
Total > Floor area | decimal | 0% | - | - |
before_1949_number_of_households |
Before 1949 > Number of households | decimal | 0% | - | - |
before_1949_number_of_rooms |
Before 1949 > Number of rooms | decimal | 0% | - | - |
before_1949_floor_area |
Before 1949 > Floor area | decimal | 0% | - | - |
1949_1959_number_of_households |
1949-1959 > Number of households | decimal | 0% | - | - |
1949_1959_number_of_rooms |
1949-1959 > Number of rooms | decimal | 0% | - | - |
1949_1959_floor_area |
1949-1959 > Floor area | decimal | 0% | - | - |
1960_1969_number_of_households |
1960-1969 > Number of households | decimal | 0% | - | - |
1960_1969_number_of_rooms |
1960-1969 > Number of rooms | decimal | 0% | - | - |
1960_1969_floor_area |
1960-1969 > Floor area | decimal | 0% | - | - |
1970_1979_number_of_households |
1970-1979 > Number of households | decimal | 0% | - | - |
1970_1979_number_of_rooms |
1970-1979 > Number of rooms | decimal | 0% | - | - |
1970_1979_floor_area |
1970-1979 > Floor area | decimal | 0% | - | - |
1980_1989_number_of_households |
1980-1989 > Number of households | decimal | 0% | - | - |
1980_1989_number_of_rooms |
1980-1989 > Number of rooms | decimal | 0% | - | - |
1980_1989_floor_area |
1980-1989 > Floor area | decimal | 0% | - | - |
1990_1999_number_of_households |
1990-1999 > Number of households | decimal | 0% | - | - |
1990_1999_number_of_rooms |
1990-1999 > Number of rooms | decimal | 0% | - | - |
1990_1999_floor_area |
1990-1999 > Floor area | decimal | 0% | - | - |
2000_2009_number_of_households |
2000-2009 > Number of households | decimal | 0% | - | - |
2000_2009_number_of_rooms |
2000-2009 > Number of rooms | decimal | 0% | - | - |
2000_2009_floor_area |
2000-2009 > Floor area | decimal | 0% | - | - |
2010_2014_number_of_households |
2010-2014 > Number of households | decimal | 0% | - | - |
2010_2014_number_of_rooms |
2010-2014 > Number of rooms | decimal | 0% | - | - |
2010_2014_floor_area |
2010-2014 > Floor area | decimal | 0% | - | - |
2015_and_later_number_of_households |
2015 and later > Number of households | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_number_of_households |
Total > Number of households | decimal | 0% | - | - |
total_number_of_rooms |
Total > Number of rooms | decimal | 0% | - | - |
total_floor_area |
Total > Floor area | decimal | 0% | - | - |
before_1949_number_of_households |
Before 1949 > Number of households | decimal | 0% | - | - |
before_1949_number_of_rooms |
Before 1949 > Number of rooms | decimal | 0% | - | - |
before_1949_floor_area |
Before 1949 > Floor area | decimal | 0% | - | - |
1949_1959_number_of_households |
1949-1959 > Number of households | decimal | 0% | - | - |
1949_1959_number_of_rooms |
1949-1959 > Number of rooms | decimal | 0% | - | - |
1949_1959_floor_area |
1949-1959 > Floor area | decimal | 0% | - | - |
1960_1969_number_of_households |
1960-1969 > Number of households | decimal | 0% | - | - |
1960_1969_number_of_rooms |
1960-1969 > Number of rooms | decimal | 0% | - | - |
1960_1969_floor_area |
1960-1969 > Floor area | decimal | 0% | - | - |
1970_1979_number_of_households |
1970-1979 > Number of households | decimal | 0% | - | - |
1970_1979_number_of_rooms |
1970-1979 > Number of rooms | decimal | 0% | - | - |
1970_1979_floor_area |
1970-1979 > Floor area | decimal | 0% | - | - |
1980_1989_number_of_households |
1980-1989 > Number of households | decimal | 0% | - | - |
1980_1989_number_of_rooms |
1980-1989 > Number of rooms | decimal | 0% | - | - |
1980_1989_floor_area |
1980-1989 > Floor area | decimal | 0% | - | - |
1990_1999_number_of_households |
1990-1999 > Number of households | decimal | 0% | - | - |
1990_1999_number_of_rooms |
1990-1999 > Number of rooms | decimal | 0% | - | - |
1990_1999_floor_area |
1990-1999 > Floor area | decimal | 0% | - | - |
2000_2009_number_of_households |
2000-2009 > Number of households | decimal | 0% | - | - |
2000_2009_number_of_rooms |
2000-2009 > Number of rooms | decimal | 0% | - | - |
2000_2009_floor_area |
2000-2009 > Floor area | decimal | 0% | - | - |
2010_2014_number_of_households |
2010-2014 > Number of households | decimal | 0% | - | - |
2010_2014_number_of_rooms |
2010-2014 > Number of rooms | decimal | 0% | - | - |
2010_2014_floor_area |
2010-2014 > Floor area | decimal | 0% | - | - |
2015_and_later_number_of_households |
2015 and later > Number of households | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
lift_in_the_building_have |
Lift in the building > Have | decimal | 0% | - | - |
lift_in_the_building_none |
Lift in the building > None | decimal | 0% | - | - |
main_cooking_fuel_gas |
Main cooking fuel > Gas | decimal | 0% | - | - |
main_cooking_fuel_electricity |
Main cooking fuel > Electricity | decimal | 0% | - | - |
main_cooking_fuel_coal |
Main cooking fuel > Coal | decimal | 0% | - | - |
main_cooking_fuel_firewood_and_straw |
Main cooking fuel > Firewood and straw | decimal | 0% | - | - |
main_cooking_fuel_other |
Main cooking fuel > Other | decimal | 0% | - | - |
piped_tap_water_in_the_dwelling_have |
Piped tap water in the dwelling > Have | decimal | 0% | - | - |
piped_tap_water_in_the_dwelling_none |
Piped tap water in the dwelling > None | decimal | 0% | - | - |
kitchen_in_the_dwelling_for_exclusive_use |
Kitchen in the dwelling > For exclusive use | decimal | 0% | - | - |
kitchen_in_the_dwelling_shared_with_other_households |
Kitchen in the dwelling > Shared with other households | decimal | 0% | - | - |
kitchen_in_the_dwelling_none |
Kitchen in the dwelling > None | decimal | 0% | - | - |
toilet_in_the_dwelling_flush_sanitary_toilet |
Toilet in the dwelling > Flush sanitary toilet | decimal | 0% | - | - |
toilet_in_the_dwelling_flush_non_sanitary_toilet |
Toilet in the dwelling > Flush non-sanitary toilet | decimal | 0% | - | - |
toilet_in_the_dwelling_sanitary_pit_latrine |
Toilet in the dwelling > Sanitary pit latrine | decimal | 0% | - | - |
toilet_in_the_dwelling_ordinary_pit_latrine |
Toilet in the dwelling > Ordinary pit latrine | decimal | 0% | - | - |
toilet_in_the_dwelling_none |
Toilet in the dwelling > None | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_centrally_supplied_hot_ |
Bathing facilities in the dwelling > Centrally supplied hot water | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_household_installed_wat |
Bathing facilities in the dwelling > Household-installed water heater | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_other |
Bathing facilities in the dwelling > Other | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_none |
Bathing facilities in the dwelling > None | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
lift_in_the_building_have |
Lift in the building > Have | decimal | 0% | - | - |
lift_in_the_building_none |
Lift in the building > None | decimal | 0% | - | - |
main_cooking_fuel_gas |
Main cooking fuel > Gas | decimal | 0% | - | - |
main_cooking_fuel_electricity |
Main cooking fuel > Electricity | decimal | 0% | - | - |
main_cooking_fuel_coal |
Main cooking fuel > Coal | decimal | 0% | - | - |
main_cooking_fuel_firewood_and_straw |
Main cooking fuel > Firewood and straw | decimal | 0% | - | - |
main_cooking_fuel_other |
Main cooking fuel > Other | decimal | 0% | - | - |
piped_tap_water_in_the_dwelling_have |
Piped tap water in the dwelling > Have | decimal | 0% | - | - |
piped_tap_water_in_the_dwelling_none |
Piped tap water in the dwelling > None | decimal | 0% | - | - |
kitchen_in_the_dwelling_for_exclusive_use |
Kitchen in the dwelling > For exclusive use | decimal | 0% | - | - |
kitchen_in_the_dwelling_shared_with_other_households |
Kitchen in the dwelling > Shared with other households | decimal | 0% | - | - |
kitchen_in_the_dwelling_none |
Kitchen in the dwelling > None | decimal | 0% | - | - |
toilet_in_the_dwelling_flush_sanitary_toilet |
Toilet in the dwelling > Flush sanitary toilet | decimal | 0% | - | - |
toilet_in_the_dwelling_flush_non_sanitary_toilet |
Toilet in the dwelling > Flush non-sanitary toilet | decimal | 0% | - | - |
toilet_in_the_dwelling_sanitary_pit_latrine |
Toilet in the dwelling > Sanitary pit latrine | decimal | 0% | - | - |
toilet_in_the_dwelling_ordinary_pit_latrine |
Toilet in the dwelling > Ordinary pit latrine | decimal | 0% | - | - |
toilet_in_the_dwelling_none |
Toilet in the dwelling > None | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_centrally_supplied_hot_ |
Bathing facilities in the dwelling > Centrally supplied hot water | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_household_installed_wat |
Bathing facilities in the dwelling > Household-installed water heater | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_other |
Bathing facilities in the dwelling > Other | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_none |
Bathing facilities in the dwelling > None | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
lift_in_the_building_have |
Lift in the building > Have | decimal | 0% | - | - |
lift_in_the_building_none |
Lift in the building > None | decimal | 0% | - | - |
main_cooking_fuel_gas |
Main cooking fuel > Gas | decimal | 0% | - | - |
main_cooking_fuel_electricity |
Main cooking fuel > Electricity | decimal | 0% | - | - |
main_cooking_fuel_coal |
Main cooking fuel > Coal | decimal | 0% | - | - |
main_cooking_fuel_firewood_and_straw |
Main cooking fuel > Firewood and straw | decimal | 0% | - | - |
main_cooking_fuel_other |
Main cooking fuel > Other | decimal | 0% | - | - |
piped_tap_water_in_the_dwelling_have |
Piped tap water in the dwelling > Have | decimal | 0% | - | - |
piped_tap_water_in_the_dwelling_none |
Piped tap water in the dwelling > None | decimal | 0% | - | - |
kitchen_in_the_dwelling_for_exclusive_use |
Kitchen in the dwelling > For exclusive use | decimal | 0% | - | - |
kitchen_in_the_dwelling_shared_with_other_households |
Kitchen in the dwelling > Shared with other households | decimal | 0% | - | - |
kitchen_in_the_dwelling_none |
Kitchen in the dwelling > None | decimal | 0% | - | - |
toilet_in_the_dwelling_flush_sanitary_toilet |
Toilet in the dwelling > Flush sanitary toilet | decimal | 0% | - | - |
toilet_in_the_dwelling_flush_non_sanitary_toilet |
Toilet in the dwelling > Flush non-sanitary toilet | decimal | 0% | - | - |
toilet_in_the_dwelling_sanitary_pit_latrine |
Toilet in the dwelling > Sanitary pit latrine | decimal | 0% | - | - |
toilet_in_the_dwelling_ordinary_pit_latrine |
Toilet in the dwelling > Ordinary pit latrine | decimal | 0% | - | - |
toilet_in_the_dwelling_none |
Toilet in the dwelling > None | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_centrally_supplied_hot_ |
Bathing facilities in the dwelling > Centrally supplied hot water | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_household_installed_wat |
Bathing facilities in the dwelling > Household-installed water heater | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_other |
Bathing facilities in the dwelling > Other | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_none |
Bathing facilities in the dwelling > None | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
lift_in_the_building_have |
Lift in the building > Have | decimal | 0% | - | - |
lift_in_the_building_none |
Lift in the building > None | decimal | 0% | - | - |
main_cooking_fuel_gas |
Main cooking fuel > Gas | decimal | 0% | - | - |
main_cooking_fuel_electricity |
Main cooking fuel > Electricity | decimal | 0% | - | - |
main_cooking_fuel_coal |
Main cooking fuel > Coal | decimal | 0% | - | - |
main_cooking_fuel_firewood_and_straw |
Main cooking fuel > Firewood and straw | decimal | 0% | - | - |
main_cooking_fuel_other |
Main cooking fuel > Other | decimal | 0% | - | - |
piped_tap_water_in_the_dwelling_have |
Piped tap water in the dwelling > Have | decimal | 0% | - | - |
piped_tap_water_in_the_dwelling_none |
Piped tap water in the dwelling > None | decimal | 0% | - | - |
kitchen_in_the_dwelling_for_exclusive_use |
Kitchen in the dwelling > For exclusive use | decimal | 0% | - | - |
kitchen_in_the_dwelling_shared_with_other_households |
Kitchen in the dwelling > Shared with other households | decimal | 0% | - | - |
kitchen_in_the_dwelling_none |
Kitchen in the dwelling > None | decimal | 0% | - | - |
toilet_in_the_dwelling_flush_sanitary_toilet |
Toilet in the dwelling > Flush sanitary toilet | decimal | 0% | - | - |
toilet_in_the_dwelling_flush_non_sanitary_toilet |
Toilet in the dwelling > Flush non-sanitary toilet | decimal | 0% | - | - |
toilet_in_the_dwelling_sanitary_pit_latrine |
Toilet in the dwelling > Sanitary pit latrine | decimal | 0% | - | - |
toilet_in_the_dwelling_ordinary_pit_latrine |
Toilet in the dwelling > Ordinary pit latrine | decimal | 0% | - | - |
toilet_in_the_dwelling_none |
Toilet in the dwelling > None | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_centrally_supplied_hot_ |
Bathing facilities in the dwelling > Centrally supplied hot water | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_household_installed_wat |
Bathing facilities in the dwelling > Household-installed water heater | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_other |
Bathing facilities in the dwelling > Other | decimal | 0% | - | - |
bathing_facilities_in_the_dwelling_none |
Bathing facilities in the dwelling > None | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
renting_low_rent_or_public_rental_housing |
Renting low-rent or public rental housing | decimal | 0% | - | - |
renting_other_housing |
Renting other housing | decimal | 0% | - | - |
purchased_newly_built_commercial_housing |
Purchased newly built commercial housing | decimal | 0% | - | - |
purchased_second_hand_housing |
Purchased second-hand housing | decimal | 0% | - | - |
purchased_former_public_housing |
Purchased former public housing | decimal | 0% | - | - |
purchased_economically_affordable_or_dual_limit_price_and_ |
Purchased economically affordable or dual-limit (price- and size-capped) housing | decimal | 0% | - | - |
self_built_housing |
Self-built housing | decimal | 0% | - | - |
inherited_or_gifted |
Inherited or gifted | decimal | 0% | - | - |
other |
Other | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
under_200_yuan |
Under 200 yuan | decimal | 0% | - | - |
200_499_yuan |
200-499 yuan | decimal | 0% | - | - |
500_999_yuan |
500-999 yuan | decimal | 0% | - | - |
1_000_1_999_yuan |
1,000-1,999 yuan | decimal | 0% | - | - |
2_000_2_999_yuan |
2,000-2,999 yuan | decimal | 0% | - | - |
3_000_3_999_yuan |
3,000-3,999 yuan | decimal | 0% | - | - |
4_000_5_999_yuan |
4,000-5,999 yuan | decimal | 0% | - | - |
6_000_7_999_yuan |
6,000-7,999 yuan | decimal | 0% | - | - |
8_000_9_999_yuan |
8,000-9,999 yuan | decimal | 0% | - | - |
10_000_yuan_and_over |
10,000 yuan and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
average_population_total |
Average population > Total | decimal | SEL | 0% | - | - |
death_rate_total |
Death rate > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
average_population_male |
Average population > Male | decimal | 0% | - | - |
average_population_female |
Average population > Female | decimal | 0% | - | - |
deaths_total |
Deaths > Total | decimal | 0% | - | - |
deaths_male |
Deaths > Male | decimal | 0% | - | - |
deaths_female |
Deaths > Female | decimal | 0% | - | - |
death_rate_male |
Death rate > Male | decimal | 0% | - | - |
death_rate_female |
Death rate > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
average_population_total |
Average population > Total | decimal | SEL | 0% | - | - |
death_rate_total |
Death rate > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
average_population_male |
Average population > Male | decimal | 0% | - | - |
average_population_female |
Average population > Female | decimal | 0% | - | - |
deaths_total |
Deaths > Total | decimal | 0% | - | - |
deaths_male |
Deaths > Male | decimal | 0% | - | - |
deaths_female |
Deaths > Female | decimal | 0% | - | - |
death_rate_male |
Death rate > Male | decimal | 0% | - | - |
death_rate_female |
Death rate > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
average_population_total |
Average population > Total | decimal | SEL | 0% | - | - |
death_rate_total |
Death rate > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
average_population_male |
Average population > Male | decimal | 0% | - | - |
average_population_female |
Average population > Female | decimal | 0% | - | - |
deaths_total |
Deaths > Total | decimal | 0% | - | - |
deaths_male |
Deaths > Male | decimal | 0% | - | - |
deaths_female |
Deaths > Female | decimal | 0% | - | - |
death_rate_male |
Death rate > Male | decimal | 0% | - | - |
death_rate_female |
Death rate > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
average_population_total |
Average population > Total | decimal | SEL | 0% | - | - |
death_rate_total |
Death rate > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
average_population_male |
Average population > Male | decimal | 0% | - | - |
average_population_female |
Average population > Female | decimal | 0% | - | - |
deaths_total |
Deaths > Total | decimal | 0% | - | - |
deaths_male |
Deaths > Male | decimal | 0% | - | - |
deaths_female |
Deaths > Female | decimal | 0% | - | - |
death_rate_male |
Death rate > Male | decimal | 0% | - | - |
death_rate_female |
Death rate > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_total |
Deaths > Total | decimal | 0% | - | - |
deaths_male |
Deaths > Male | decimal | 0% | - | - |
deaths_female |
Deaths > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_total |
Deaths > Total | decimal | 0% | - | - |
deaths_male |
Deaths > Male | decimal | 0% | - | - |
deaths_female |
Deaths > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_total |
Deaths > Total | decimal | 0% | - | - |
deaths_male |
Deaths > Male | decimal | 0% | - | - |
deaths_female |
Deaths > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_total |
Deaths > Total | decimal | 0% | - | - |
deaths_male |
Deaths > Male | decimal | 0% | - | - |
deaths_female |
Deaths > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_aged_3_and_over_total |
Deaths aged 3 and over > Total | decimal | 0% | - | - |
deaths_aged_3_and_over_male |
Deaths aged 3 and over > Male | decimal | 0% | - | - |
deaths_aged_3_and_over_female |
Deaths aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_aged_3_and_over_total |
Deaths aged 3 and over > Total | decimal | 0% | - | - |
deaths_aged_3_and_over_male |
Deaths aged 3 and over > Male | decimal | 0% | - | - |
deaths_aged_3_and_over_female |
Deaths aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_aged_3_and_over_total |
Deaths aged 3 and over > Total | decimal | 0% | - | - |
deaths_aged_3_and_over_male |
Deaths aged 3 and over > Male | decimal | 0% | - | - |
deaths_aged_3_and_over_female |
Deaths aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_aged_3_and_over_total |
Deaths aged 3 and over > Total | decimal | 0% | - | - |
deaths_aged_3_and_over_male |
Deaths aged 3 and over > Male | decimal | 0% | - | - |
deaths_aged_3_and_over_female |
Deaths aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_aged_15_and_over_total |
Deaths aged 15 and over > Total | decimal | 0% | - | - |
deaths_aged_15_and_over_male |
Deaths aged 15 and over > Male | decimal | 0% | - | - |
deaths_aged_15_and_over_female |
Deaths aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_aged_15_and_over_total |
Deaths aged 15 and over > Total | decimal | 0% | - | - |
deaths_aged_15_and_over_male |
Deaths aged 15 and over > Male | decimal | 0% | - | - |
deaths_aged_15_and_over_female |
Deaths aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_aged_15_and_over_total |
Deaths aged 15 and over > Total | decimal | 0% | - | - |
deaths_aged_15_and_over_male |
Deaths aged 15 and over > Male | decimal | 0% | - | - |
deaths_aged_15_and_over_female |
Deaths aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
deaths_aged_15_and_over_total |
Deaths aged 15 and over > Total | decimal | 0% | - | - |
deaths_aged_15_and_over_male |
Deaths aged 15 and over > Male | decimal | 0% | - | - |
deaths_aged_15_and_over_female |
Deaths aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
ⓘ 1-in-10 household sample. These tables come from the census long questionnaire, which about one household in ten answered. The National Bureau of Statistics publishes the sample's own counts without scaling them up, so counts here are about a tenth of the real figure: this sample counted 138,657,945 people, against 1,409,778,724 in the full count. Shares, rates and averages can be used as they are; for population totals use the full-count datasets.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
sex_ratio_female_100 |
Sex ratio (female=100) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
share_of_total_population_total |
Share of total population > Total | decimal | 0% | - | - |
share_of_total_population_male |
Share of total population > Male | decimal | 0% | - | - |
share_of_total_population_female |
Share of total population > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
sex_ratio_female_100 |
Sex ratio (female=100) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
share_of_total_population_total |
Share of total population > Total | decimal | 0% | - | - |
share_of_total_population_male |
Share of total population > Male | decimal | 0% | - | - |
share_of_total_population_female |
Share of total population > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
sex_ratio_female_100 |
Sex ratio (female=100) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
share_of_total_population_total |
Share of total population > Total | decimal | 0% | - | - |
share_of_total_population_male |
Share of total population > Male | decimal | 0% | - | - |
share_of_total_population_female |
Share of total population > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
sex_ratio_female_100 |
Sex ratio (female=100) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
share_of_total_population_total |
Share of total population > Total | decimal | 0% | - | - |
share_of_total_population_male |
Share of total population > Male | decimal | 0% | - | - |
share_of_total_population_female |
Share of total population > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_households_total |
Number of households > Total | decimal | SEL | 0% | - | - |
population_total_total |
Population > Total > Total | decimal | SEL | 0% | - | - |
population_total_male |
Population > Total > Male | decimal | SEL | 0% | - | - |
population_total_female |
Population > Total > Female | decimal | SEL | 0% | - | - |
population_total_sex_ratio_female_100 |
Population > Total > Sex ratio (female=100) | decimal | SEL | 0% | - | - |
average_family_household_size_persons_household |
Average family household size (persons/household) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_family_households |
Number of households > Family households | decimal | 0% | - | - |
number_of_households_collective_households |
Number of households > Collective households | decimal | 0% | - | - |
population_family_households_subtotal |
Population > Family households > Subtotal | decimal | 0% | - | - |
population_family_households_male |
Population > Family households > Male | decimal | 0% | - | - |
population_family_households_female |
Population > Family households > Female | decimal | 0% | - | - |
population_family_households_sex_ratio_female_100 |
Population > Family households > Sex ratio (female=100) | decimal | 0% | - | - |
population_collective_households_subtotal |
Population > Collective households > Subtotal | decimal | 0% | - | - |
population_collective_households_male |
Population > Collective households > Male | decimal | 0% | - | - |
population_collective_households_female |
Population > Collective households > Female | decimal | 0% | - | - |
population_collective_households_sex_ratio_female_100 |
Population > Collective households > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_households_total |
Number of households > Total | decimal | SEL | 0% | - | - |
population_total_total |
Population > Total > Total | decimal | SEL | 0% | - | - |
population_total_male |
Population > Total > Male | decimal | SEL | 0% | - | - |
population_total_female |
Population > Total > Female | decimal | SEL | 0% | - | - |
population_total_sex_ratio_female_100 |
Population > Total > Sex ratio (female=100) | decimal | SEL | 0% | - | - |
average_family_household_size_persons_household |
Average family household size (persons/household) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_family_households |
Number of households > Family households | decimal | 0% | - | - |
number_of_households_collective_households |
Number of households > Collective households | decimal | 0% | - | - |
population_family_households_subtotal |
Population > Family households > Subtotal | decimal | 0% | - | - |
population_family_households_male |
Population > Family households > Male | decimal | 0% | - | - |
population_family_households_female |
Population > Family households > Female | decimal | 0% | - | - |
population_family_households_sex_ratio_female_100 |
Population > Family households > Sex ratio (female=100) | decimal | 0% | - | - |
population_collective_households_subtotal |
Population > Collective households > Subtotal | decimal | 0% | - | - |
population_collective_households_male |
Population > Collective households > Male | decimal | 0% | - | - |
population_collective_households_female |
Population > Collective households > Female | decimal | 0% | - | - |
population_collective_households_sex_ratio_female_100 |
Population > Collective households > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_households_total |
Number of households > Total | decimal | SEL | 0% | - | - |
population_total_total |
Population > Total > Total | decimal | SEL | 0% | - | - |
population_total_male |
Population > Total > Male | decimal | SEL | 0% | - | - |
population_total_female |
Population > Total > Female | decimal | SEL | 0% | - | - |
population_total_sex_ratio_female_100 |
Population > Total > Sex ratio (female=100) | decimal | SEL | 0% | - | - |
average_family_household_size_persons_household |
Average family household size (persons/household) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_family_households |
Number of households > Family households | decimal | 0% | - | - |
number_of_households_collective_households |
Number of households > Collective households | decimal | 0% | - | - |
population_family_households_subtotal |
Population > Family households > Subtotal | decimal | 0% | - | - |
population_family_households_male |
Population > Family households > Male | decimal | 0% | - | - |
population_family_households_female |
Population > Family households > Female | decimal | 0% | - | - |
population_family_households_sex_ratio_female_100 |
Population > Family households > Sex ratio (female=100) | decimal | 0% | - | - |
population_collective_households_subtotal |
Population > Collective households > Subtotal | decimal | 0% | - | - |
population_collective_households_male |
Population > Collective households > Male | decimal | 0% | - | - |
population_collective_households_female |
Population > Collective households > Female | decimal | 0% | - | - |
population_collective_households_sex_ratio_female_100 |
Population > Collective households > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_households_total |
Number of households > Total | decimal | SEL | 0% | - | - |
population_total_total |
Population > Total > Total | decimal | SEL | 0% | - | - |
population_total_male |
Population > Total > Male | decimal | SEL | 0% | - | - |
population_total_female |
Population > Total > Female | decimal | SEL | 0% | - | - |
population_total_sex_ratio_female_100 |
Population > Total > Sex ratio (female=100) | decimal | SEL | 0% | - | - |
average_family_household_size_persons_household |
Average family household size (persons/household) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_family_households |
Number of households > Family households | decimal | 0% | - | - |
number_of_households_collective_households |
Number of households > Collective households | decimal | 0% | - | - |
population_family_households_subtotal |
Population > Family households > Subtotal | decimal | 0% | - | - |
population_family_households_male |
Population > Family households > Male | decimal | 0% | - | - |
population_family_households_female |
Population > Family households > Female | decimal | 0% | - | - |
population_family_households_sex_ratio_female_100 |
Population > Family households > Sex ratio (female=100) | decimal | 0% | - | - |
population_collective_households_subtotal |
Population > Collective households > Subtotal | decimal | 0% | - | - |
population_collective_households_male |
Population > Collective households > Male | decimal | 0% | - | - |
population_collective_households_female |
Population > Collective households > Female | decimal | 0% | - | - |
population_collective_households_sex_ratio_female_100 |
Population > Collective households > Sex ratio (female=100) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_2 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_3 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_4 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_5 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_6 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi |
Living in this township, town or subdistrict, household registration pending > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_2 |
Living in this township, town or subdistrict, household registration pending > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_3 |
Living in this township, town or subdistrict, household registration pending > Female | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Subtotal | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_2 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Male | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_3 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_2 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_3 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_4 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_5 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_6 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi |
Living in this township, town or subdistrict, household registration pending > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_2 |
Living in this township, town or subdistrict, household registration pending > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_3 |
Living in this township, town or subdistrict, household registration pending > Female | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Subtotal | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_2 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Male | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_3 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_2 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_3 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_4 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_5 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_6 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi |
Living in this township, town or subdistrict, household registration pending > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_2 |
Living in this township, town or subdistrict, household registration pending > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_3 |
Living in this township, town or subdistrict, household registration pending > Female | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Subtotal | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_2 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Male | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_3 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_2 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_3 |
Living in this township, town or subdistrict with household registration in this township, town or subdistrict > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_4 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_5 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_with_household_6 |
Living in this township, town or subdistrict with household registration in another township, town or subdistrict, having left the place of household registration for six months or more > Female | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi |
Living in this township, town or subdistrict, household registration pending > Subtotal | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_2 |
Living in this township, town or subdistrict, household registration pending > Male | decimal | 0% | - | - |
living_in_this_township_town_or_subdistrict_household_regi_3 |
Living in this township, town or subdistrict, household registration pending > Female | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Subtotal | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_2 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Male | decimal | 0% | - | - |
formerly_living_in_this_township_town_or_subdistrict_now_w_3 |
Formerly living in this township, town or subdistrict, now working or studying in Hong Kong, Macao, Taiwan or abroad > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_0_subtotal |
Age 0 > Subtotal | decimal | 0% | - | - |
age_0_male |
Age 0 > Male | decimal | 0% | - | - |
age_0_female |
Age 0 > Female | decimal | 0% | - | - |
ages_1_4_subtotal |
Ages 1-4 > Subtotal | decimal | 0% | - | - |
ages_1_4_male |
Ages 1-4 > Male | decimal | 0% | - | - |
ages_1_4_female |
Ages 1-4 > Female | decimal | 0% | - | - |
ages_5_9_subtotal |
Ages 5-9 > Subtotal | decimal | 0% | - | - |
ages_5_9_male |
Ages 5-9 > Male | decimal | 0% | - | - |
ages_5_9_female |
Ages 5-9 > Female | decimal | 0% | - | - |
ages_10_14_subtotal |
Ages 10-14 > Subtotal | decimal | 0% | - | - |
ages_10_14_male |
Ages 10-14 > Male | decimal | 0% | - | - |
ages_10_14_female |
Ages 10-14 > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
| +41 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
population |
Population | decimal | CCL | 0% | - | - |
share_of_each_ethnic_group_in_the_total_population |
Share of each ethnic group in the total population | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
male |
Male | decimal | 0% | - | - |
female |
Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
population |
Population | decimal | CCL | 0% | - | - |
share_of_each_ethnic_group_in_the_total_population |
Share of each ethnic group in the total population | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
male |
Male | decimal | 0% | - | - |
female |
Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
population |
Population | decimal | CCL | 0% | - | - |
share_of_each_ethnic_group_in_the_total_population |
Share of each ethnic group in the total population | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
male |
Male | decimal | 0% | - | - |
female |
Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
population |
Population | decimal | CCL | 0% | - | - |
share_of_each_ethnic_group_in_the_total_population |
Share of each ethnic group in the total population | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
male |
Male | decimal | 0% | - | - |
female |
Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
han_subtotal |
Han > Subtotal | decimal | 0% | - | - |
han_male |
Han > Male | decimal | 0% | - | - |
han_female |
Han > Female | decimal | 0% | - | - |
mongol_subtotal |
Mongol > Subtotal | decimal | 0% | - | - |
mongol_male |
Mongol > Male | decimal | 0% | - | - |
mongol_female |
Mongol > Female | decimal | 0% | - | - |
hui_subtotal |
Hui > Subtotal | decimal | 0% | - | - |
hui_male |
Hui > Male | decimal | 0% | - | - |
hui_female |
Hui > Female | decimal | 0% | - | - |
tibetan_subtotal |
Tibetan > Subtotal | decimal | 0% | - | - |
tibetan_male |
Tibetan > Male | decimal | 0% | - | - |
tibetan_female |
Tibetan > Female | decimal | 0% | - | - |
uygur_subtotal |
Uygur > Subtotal | decimal | 0% | - | - |
uygur_male |
Uygur > Male | decimal | 0% | - | - |
uygur_female |
Uygur > Female | decimal | 0% | - | - |
miao_subtotal |
Miao > Subtotal | decimal | 0% | - | - |
miao_male |
Miao > Male | decimal | 0% | - | - |
miao_female |
Miao > Female | decimal | 0% | - | - |
yi_subtotal |
Yi > Subtotal | decimal | 0% | - | - |
yi_male |
Yi > Male | decimal | 0% | - | - |
yi_female |
Yi > Female | decimal | 0% | - | - |
zhuang_subtotal |
Zhuang > Subtotal | decimal | 0% | - | - |
zhuang_male |
Zhuang > Male | decimal | 0% | - | - |
zhuang_female |
Zhuang > Female | decimal | 0% | - | - |
bouyei_subtotal |
Bouyei > Subtotal | decimal | 0% | - | - |
| +149 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
han_subtotal |
Han > Subtotal | decimal | 0% | - | - |
han_male |
Han > Male | decimal | 0% | - | - |
han_female |
Han > Female | decimal | 0% | - | - |
mongol_subtotal |
Mongol > Subtotal | decimal | 0% | - | - |
mongol_male |
Mongol > Male | decimal | 0% | - | - |
mongol_female |
Mongol > Female | decimal | 0% | - | - |
hui_subtotal |
Hui > Subtotal | decimal | 0% | - | - |
hui_male |
Hui > Male | decimal | 0% | - | - |
hui_female |
Hui > Female | decimal | 0% | - | - |
tibetan_subtotal |
Tibetan > Subtotal | decimal | 0% | - | - |
tibetan_male |
Tibetan > Male | decimal | 0% | - | - |
tibetan_female |
Tibetan > Female | decimal | 0% | - | - |
uygur_subtotal |
Uygur > Subtotal | decimal | 0% | - | - |
uygur_male |
Uygur > Male | decimal | 0% | - | - |
uygur_female |
Uygur > Female | decimal | 0% | - | - |
miao_subtotal |
Miao > Subtotal | decimal | 0% | - | - |
miao_male |
Miao > Male | decimal | 0% | - | - |
miao_female |
Miao > Female | decimal | 0% | - | - |
yi_subtotal |
Yi > Subtotal | decimal | 0% | - | - |
yi_male |
Yi > Male | decimal | 0% | - | - |
yi_female |
Yi > Female | decimal | 0% | - | - |
zhuang_subtotal |
Zhuang > Subtotal | decimal | 0% | - | - |
zhuang_male |
Zhuang > Male | decimal | 0% | - | - |
zhuang_female |
Zhuang > Female | decimal | 0% | - | - |
bouyei_subtotal |
Bouyei > Subtotal | decimal | 0% | - | - |
| +149 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
han_subtotal |
Han > Subtotal | decimal | 0% | - | - |
han_male |
Han > Male | decimal | 0% | - | - |
han_female |
Han > Female | decimal | 0% | - | - |
mongol_subtotal |
Mongol > Subtotal | decimal | 0% | - | - |
mongol_male |
Mongol > Male | decimal | 0% | - | - |
mongol_female |
Mongol > Female | decimal | 0% | - | - |
hui_subtotal |
Hui > Subtotal | decimal | 0% | - | - |
hui_male |
Hui > Male | decimal | 0% | - | - |
hui_female |
Hui > Female | decimal | 0% | - | - |
tibetan_subtotal |
Tibetan > Subtotal | decimal | 0% | - | - |
tibetan_male |
Tibetan > Male | decimal | 0% | - | - |
tibetan_female |
Tibetan > Female | decimal | 0% | - | - |
uygur_subtotal |
Uygur > Subtotal | decimal | 0% | - | - |
uygur_male |
Uygur > Male | decimal | 0% | - | - |
uygur_female |
Uygur > Female | decimal | 0% | - | - |
miao_subtotal |
Miao > Subtotal | decimal | 0% | - | - |
miao_male |
Miao > Male | decimal | 0% | - | - |
miao_female |
Miao > Female | decimal | 0% | - | - |
yi_subtotal |
Yi > Subtotal | decimal | 0% | - | - |
yi_male |
Yi > Male | decimal | 0% | - | - |
yi_female |
Yi > Female | decimal | 0% | - | - |
zhuang_subtotal |
Zhuang > Subtotal | decimal | 0% | - | - |
zhuang_male |
Zhuang > Male | decimal | 0% | - | - |
zhuang_female |
Zhuang > Female | decimal | 0% | - | - |
bouyei_subtotal |
Bouyei > Subtotal | decimal | 0% | - | - |
| +149 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age_group |
Age group | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
han_subtotal |
Han > Subtotal | decimal | 0% | - | - |
han_male |
Han > Male | decimal | 0% | - | - |
han_female |
Han > Female | decimal | 0% | - | - |
mongol_subtotal |
Mongol > Subtotal | decimal | 0% | - | - |
mongol_male |
Mongol > Male | decimal | 0% | - | - |
mongol_female |
Mongol > Female | decimal | 0% | - | - |
hui_subtotal |
Hui > Subtotal | decimal | 0% | - | - |
hui_male |
Hui > Male | decimal | 0% | - | - |
hui_female |
Hui > Female | decimal | 0% | - | - |
tibetan_subtotal |
Tibetan > Subtotal | decimal | 0% | - | - |
tibetan_male |
Tibetan > Male | decimal | 0% | - | - |
tibetan_female |
Tibetan > Female | decimal | 0% | - | - |
uygur_subtotal |
Uygur > Subtotal | decimal | 0% | - | - |
uygur_male |
Uygur > Male | decimal | 0% | - | - |
uygur_female |
Uygur > Female | decimal | 0% | - | - |
miao_subtotal |
Miao > Subtotal | decimal | 0% | - | - |
miao_male |
Miao > Male | decimal | 0% | - | - |
miao_female |
Miao > Female | decimal | 0% | - | - |
yi_subtotal |
Yi > Subtotal | decimal | 0% | - | - |
yi_male |
Yi > Male | decimal | 0% | - | - |
yi_female |
Yi > Female | decimal | 0% | - | - |
zhuang_subtotal |
Zhuang > Subtotal | decimal | 0% | - | - |
zhuang_male |
Zhuang > Male | decimal | 0% | - | - |
zhuang_female |
Zhuang > Female | decimal | 0% | - | - |
bouyei_subtotal |
Bouyei > Subtotal | decimal | 0% | - | - |
| +149 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_3_and_over_total |
Population aged 3 and over > Total | decimal | 0% | - | - |
population_aged_3_and_over_male |
Population aged 3 and over > Male | decimal | 0% | - | - |
population_aged_3_and_over_female |
Population aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_3_and_over_total |
Population aged 3 and over > Total | decimal | 0% | - | - |
population_aged_3_and_over_male |
Population aged 3 and over > Male | decimal | 0% | - | - |
population_aged_3_and_over_female |
Population aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_3_and_over_total |
Population aged 3 and over > Total | decimal | 0% | - | - |
population_aged_3_and_over_male |
Population aged 3 and over > Male | decimal | 0% | - | - |
population_aged_3_and_over_female |
Population aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_3_and_over_total |
Population aged 3 and over > Total | decimal | 0% | - | - |
population_aged_3_and_over_male |
Population aged 3 and over > Male | decimal | 0% | - | - |
population_aged_3_and_over_female |
Population aged 3 and over > Female | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_male |
Never attended school > Male | decimal | 0% | - | - |
never_attended_school_female |
Never attended school > Female | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_male |
Pre-school education > Male | decimal | 0% | - | - |
pre_school_education_female |
Pre-school education > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
| +2 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_2 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_3 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_2 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_3 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_2 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_3 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_household_registration_total_total |
Place of household registration > Total > Total | decimal | 0% | - | - |
place_of_household_registration_total_male |
Place of household registration > Total > Male | decimal | 0% | - | - |
place_of_household_registration_total_female |
Place of household registration > Total > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_subtot |
Place of household registration > Within the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_male |
Place of household registration > Within the province > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_female |
Place of household registration > Within the province > Female | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Subtotal | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_2 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Male | decimal | 0% | - | - |
place_of_household_registration_within_the_province_of_whi_3 |
Place of household registration > Within the province > Of which: residence-household-registration separation within the municipal district > Female | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_subto |
Place of household registration > Outside the province > Subtotal | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_male |
Place of household registration > Outside the province > Male | decimal | 0% | - | - |
place_of_household_registration_outside_the_province_femal |
Place of household registration > Outside the province > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
sex_ratio_female_100 |
Sex ratio (female=100) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
share_of_total_population_total |
Share of total population > Total | decimal | 0% | - | - |
share_of_total_population_male |
Share of total population > Male | decimal | 0% | - | - |
share_of_total_population_female |
Share of total population > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
sex_ratio_female_100 |
Sex ratio (female=100) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
share_of_total_population_total |
Share of total population > Total | decimal | 0% | - | - |
share_of_total_population_male |
Share of total population > Male | decimal | 0% | - | - |
share_of_total_population_female |
Share of total population > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
sex_ratio_female_100 |
Sex ratio (female=100) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
share_of_total_population_total |
Share of total population > Total | decimal | 0% | - | - |
share_of_total_population_male |
Share of total population > Male | decimal | 0% | - | - |
share_of_total_population_female |
Share of total population > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
sex_ratio_female_100 |
Sex ratio (female=100) | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
share_of_total_population_total |
Share of total population > Total | decimal | 0% | - | - |
share_of_total_population_male |
Share of total population > Male | decimal | 0% | - | - |
share_of_total_population_female |
Share of total population > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
population_ages_0_14 |
Population > Ages 0-14 | decimal | SEL | 0% | - | - |
population_ages_15_64 |
Population > Ages 15-64 | decimal | SEL | 0% | - | - |
population_age_65_and_over |
Population > Age 65 and over | decimal | SEL | 0% | - | - |
share_ages_0_14 |
Share > Ages 0-14 | decimal | SEL | 0% | - | - |
share_ages_15_64 |
Share > Ages 15-64 | decimal | SEL | 0% | - | - |
share_age_65_and_over |
Share > Age 65 and over | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
share_total |
Share > Total | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
population_ages_0_14 |
Population > Ages 0-14 | decimal | SEL | 0% | - | - |
population_ages_15_64 |
Population > Ages 15-64 | decimal | SEL | 0% | - | - |
population_age_65_and_over |
Population > Age 65 and over | decimal | SEL | 0% | - | - |
share_ages_0_14 |
Share > Ages 0-14 | decimal | SEL | 0% | - | - |
share_ages_15_64 |
Share > Ages 15-64 | decimal | SEL | 0% | - | - |
share_age_65_and_over |
Share > Age 65 and over | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
share_total |
Share > Total | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
population_ages_0_14 |
Population > Ages 0-14 | decimal | SEL | 0% | - | - |
population_ages_15_64 |
Population > Ages 15-64 | decimal | SEL | 0% | - | - |
population_age_65_and_over |
Population > Age 65 and over | decimal | SEL | 0% | - | - |
share_ages_0_14 |
Share > Ages 0-14 | decimal | SEL | 0% | - | - |
share_ages_15_64 |
Share > Ages 15-64 | decimal | SEL | 0% | - | - |
share_age_65_and_over |
Share > Age 65 and over | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
share_total |
Share > Total | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
population_ages_0_14 |
Population > Ages 0-14 | decimal | SEL | 0% | - | - |
population_ages_15_64 |
Population > Ages 15-64 | decimal | SEL | 0% | - | - |
population_age_65_and_over |
Population > Age 65 and over | decimal | SEL | 0% | - | - |
share_ages_0_14 |
Share > Ages 0-14 | decimal | SEL | 0% | - | - |
share_ages_15_64 |
Share > Ages 15-64 | decimal | SEL | 0% | - | - |
share_age_65_and_over |
Share > Age 65 and over | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
share_total |
Share > Total | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
population_age_60_and_over |
Population > Age 60 and over | decimal | SEL | 0% | - | - |
share_age_60_and_over |
Share > Age 60 and over | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_ages_0_15 |
Population > Ages 0-15 | decimal | 0% | - | - |
population_ages_16_59 |
Population > Ages 16-59 | decimal | 0% | - | - |
share_total |
Share > Total | decimal | 0% | - | - |
share_ages_0_15 |
Share > Ages 0-15 | decimal | 0% | - | - |
share_ages_16_59 |
Share > Ages 16-59 | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
population_age_60_and_over |
Population > Age 60 and over | decimal | SEL | 0% | - | - |
share_age_60_and_over |
Share > Age 60 and over | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_ages_0_15 |
Population > Ages 0-15 | decimal | 0% | - | - |
population_ages_16_59 |
Population > Ages 16-59 | decimal | 0% | - | - |
share_total |
Share > Total | decimal | 0% | - | - |
share_ages_0_15 |
Share > Ages 0-15 | decimal | 0% | - | - |
share_ages_16_59 |
Share > Ages 16-59 | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
population_age_60_and_over |
Population > Age 60 and over | decimal | SEL | 0% | - | - |
share_age_60_and_over |
Share > Age 60 and over | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_ages_0_15 |
Population > Ages 0-15 | decimal | 0% | - | - |
population_ages_16_59 |
Population > Ages 16-59 | decimal | 0% | - | - |
share_total |
Share > Total | decimal | 0% | - | - |
share_ages_0_15 |
Share > Ages 0-15 | decimal | 0% | - | - |
share_ages_16_59 |
Share > Ages 16-59 | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
population_age_60_and_over |
Population > Age 60 and over | decimal | SEL | 0% | - | - |
share_age_60_and_over |
Share > Age 60 and over | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_ages_0_15 |
Population > Ages 0-15 | decimal | 0% | - | - |
population_ages_16_59 |
Population > Ages 16-59 | decimal | 0% | - | - |
share_total |
Share > Total | decimal | 0% | - | - |
share_ages_0_15 |
Share > Ages 0-15 | decimal | 0% | - | - |
share_ages_16_59 |
Share > Ages 16-59 | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
family_household_size |
Family household size | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_family_households |
Number of family households | decimal | 0% | - | - |
one_generation_household |
One-generation household | decimal | 0% | - | - |
two_generation_household |
Two-generation household | decimal | 0% | - | - |
three_generation_household |
Three-generation household | decimal | 0% | - | - |
four_generation_household |
Four-generation household | decimal | 0% | - | - |
households_of_five_or_more_generations |
Households of five or more generations | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
family_household_size |
Family household size | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_family_households |
Number of family households | decimal | 0% | - | - |
one_generation_household |
One-generation household | decimal | 0% | - | - |
two_generation_household |
Two-generation household | decimal | 0% | - | - |
three_generation_household |
Three-generation household | decimal | 0% | - | - |
four_generation_household |
Four-generation household | decimal | 0% | - | - |
households_of_five_or_more_generations |
Households of five or more generations | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
family_household_size |
Family household size | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_family_households |
Number of family households | decimal | 0% | - | - |
one_generation_household |
One-generation household | decimal | 0% | - | - |
two_generation_household |
Two-generation household | decimal | 0% | - | - |
three_generation_household |
Three-generation household | decimal | 0% | - | - |
four_generation_household |
Four-generation household | decimal | 0% | - | - |
households_of_five_or_more_generations |
Households of five or more generations | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
family_household_size |
Family household size | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_family_households |
Number of family households | decimal | 0% | - | - |
one_generation_household |
One-generation household | decimal | 0% | - | - |
two_generation_household |
Two-generation household | decimal | 0% | - | - |
three_generation_household |
Three-generation household | decimal | 0% | - | - |
four_generation_household |
Four-generation household | decimal | 0% | - | - |
households_of_five_or_more_generations |
Households of five or more generations | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_14_and_under_subtotal |
Age 14 and under > Subtotal | decimal | 0% | - | - |
age_14_and_under_male |
Age 14 and under > Male | decimal | 0% | - | - |
age_14_and_under_female |
Age 14 and under > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
ages_35_39_male |
Ages 35-39 > Male | decimal | 0% | - | - |
ages_35_39_female |
Ages 35-39 > Female | decimal | 0% | - | - |
ages_40_44_subtotal |
Ages 40-44 > Subtotal | decimal | 0% | - | - |
ages_40_44_male |
Ages 40-44 > Male | decimal | 0% | - | - |
ages_40_44_female |
Ages 40-44 > Female | decimal | 0% | - | - |
ages_45_49_subtotal |
Ages 45-49 > Subtotal | decimal | 0% | - | - |
ages_45_49_male |
Ages 45-49 > Male | decimal | 0% | - | - |
ages_45_49_female |
Ages 45-49 > Female | decimal | 0% | - | - |
ages_50_54_subtotal |
Ages 50-54 > Subtotal | decimal | 0% | - | - |
| +11 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_14_and_under_subtotal |
Age 14 and under > Subtotal | decimal | 0% | - | - |
age_14_and_under_male |
Age 14 and under > Male | decimal | 0% | - | - |
age_14_and_under_female |
Age 14 and under > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
ages_35_39_male |
Ages 35-39 > Male | decimal | 0% | - | - |
ages_35_39_female |
Ages 35-39 > Female | decimal | 0% | - | - |
ages_40_44_subtotal |
Ages 40-44 > Subtotal | decimal | 0% | - | - |
ages_40_44_male |
Ages 40-44 > Male | decimal | 0% | - | - |
ages_40_44_female |
Ages 40-44 > Female | decimal | 0% | - | - |
ages_45_49_subtotal |
Ages 45-49 > Subtotal | decimal | 0% | - | - |
ages_45_49_male |
Ages 45-49 > Male | decimal | 0% | - | - |
ages_45_49_female |
Ages 45-49 > Female | decimal | 0% | - | - |
ages_50_54_subtotal |
Ages 50-54 > Subtotal | decimal | 0% | - | - |
| +11 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_14_and_under_subtotal |
Age 14 and under > Subtotal | decimal | 0% | - | - |
age_14_and_under_male |
Age 14 and under > Male | decimal | 0% | - | - |
age_14_and_under_female |
Age 14 and under > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
ages_35_39_male |
Ages 35-39 > Male | decimal | 0% | - | - |
ages_35_39_female |
Ages 35-39 > Female | decimal | 0% | - | - |
ages_40_44_subtotal |
Ages 40-44 > Subtotal | decimal | 0% | - | - |
ages_40_44_male |
Ages 40-44 > Male | decimal | 0% | - | - |
ages_40_44_female |
Ages 40-44 > Female | decimal | 0% | - | - |
ages_45_49_subtotal |
Ages 45-49 > Subtotal | decimal | 0% | - | - |
ages_45_49_male |
Ages 45-49 > Male | decimal | 0% | - | - |
ages_45_49_female |
Ages 45-49 > Female | decimal | 0% | - | - |
ages_50_54_subtotal |
Ages 50-54 > Subtotal | decimal | 0% | - | - |
| +11 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
age_14_and_under_subtotal |
Age 14 and under > Subtotal | decimal | 0% | - | - |
age_14_and_under_male |
Age 14 and under > Male | decimal | 0% | - | - |
age_14_and_under_female |
Age 14 and under > Female | decimal | 0% | - | - |
ages_15_19_subtotal |
Ages 15-19 > Subtotal | decimal | 0% | - | - |
ages_15_19_male |
Ages 15-19 > Male | decimal | 0% | - | - |
ages_15_19_female |
Ages 15-19 > Female | decimal | 0% | - | - |
ages_20_24_subtotal |
Ages 20-24 > Subtotal | decimal | 0% | - | - |
ages_20_24_male |
Ages 20-24 > Male | decimal | 0% | - | - |
ages_20_24_female |
Ages 20-24 > Female | decimal | 0% | - | - |
ages_25_29_subtotal |
Ages 25-29 > Subtotal | decimal | 0% | - | - |
ages_25_29_male |
Ages 25-29 > Male | decimal | 0% | - | - |
ages_25_29_female |
Ages 25-29 > Female | decimal | 0% | - | - |
ages_30_34_subtotal |
Ages 30-34 > Subtotal | decimal | 0% | - | - |
ages_30_34_male |
Ages 30-34 > Male | decimal | 0% | - | - |
ages_30_34_female |
Ages 30-34 > Female | decimal | 0% | - | - |
ages_35_39_subtotal |
Ages 35-39 > Subtotal | decimal | 0% | - | - |
ages_35_39_male |
Ages 35-39 > Male | decimal | 0% | - | - |
ages_35_39_female |
Ages 35-39 > Female | decimal | 0% | - | - |
ages_40_44_subtotal |
Ages 40-44 > Subtotal | decimal | 0% | - | - |
ages_40_44_male |
Ages 40-44 > Male | decimal | 0% | - | - |
ages_40_44_female |
Ages 40-44 > Female | decimal | 0% | - | - |
ages_45_49_subtotal |
Ages 45-49 > Subtotal | decimal | 0% | - | - |
ages_45_49_male |
Ages 45-49 > Male | decimal | 0% | - | - |
ages_45_49_female |
Ages 45-49 > Female | decimal | 0% | - | - |
ages_50_54_subtotal |
Ages 50-54 > Subtotal | decimal | 0% | - | - |
| +11 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
single_ethnic_group_households_number_of_households |
Single-ethnic-group households > Number of households | decimal | 0% | - | - |
single_ethnic_group_households_share_of_family_households |
Single-ethnic-group households > Share of family households | decimal | 0% | - | - |
households_of_two_ethnic_groups_number_of_households |
Households of two ethnic groups > Number of households | decimal | 0% | - | - |
households_of_two_ethnic_groups_share_of_family_households |
Households of two ethnic groups > Share of family households | decimal | 0% | - | - |
households_of_three_ethnic_groups_number_of_households |
Households of three ethnic groups > Number of households | decimal | 0% | - | - |
households_of_three_ethnic_groups_share_of_family_househol |
Households of three ethnic groups > Share of family households | decimal | 0% | - | - |
households_of_four_or_more_ethnic_groups_number_of_househo |
Households of four or more ethnic groups > Number of households | decimal | 0% | - | - |
households_of_four_or_more_ethnic_groups_share_of_family_h |
Households of four or more ethnic groups > Share of family households | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
single_ethnic_group_households_number_of_households |
Single-ethnic-group households > Number of households | decimal | 0% | - | - |
single_ethnic_group_households_share_of_family_households |
Single-ethnic-group households > Share of family households | decimal | 0% | - | - |
households_of_two_ethnic_groups_number_of_households |
Households of two ethnic groups > Number of households | decimal | 0% | - | - |
households_of_two_ethnic_groups_share_of_family_households |
Households of two ethnic groups > Share of family households | decimal | 0% | - | - |
households_of_three_ethnic_groups_number_of_households |
Households of three ethnic groups > Number of households | decimal | 0% | - | - |
households_of_three_ethnic_groups_share_of_family_househol |
Households of three ethnic groups > Share of family households | decimal | 0% | - | - |
households_of_four_or_more_ethnic_groups_number_of_househo |
Households of four or more ethnic groups > Number of households | decimal | 0% | - | - |
households_of_four_or_more_ethnic_groups_share_of_family_h |
Households of four or more ethnic groups > Share of family households | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
single_ethnic_group_households_number_of_households |
Single-ethnic-group households > Number of households | decimal | 0% | - | - |
single_ethnic_group_households_share_of_family_households |
Single-ethnic-group households > Share of family households | decimal | 0% | - | - |
households_of_two_ethnic_groups_number_of_households |
Households of two ethnic groups > Number of households | decimal | 0% | - | - |
households_of_two_ethnic_groups_share_of_family_households |
Households of two ethnic groups > Share of family households | decimal | 0% | - | - |
households_of_three_ethnic_groups_number_of_households |
Households of three ethnic groups > Number of households | decimal | 0% | - | - |
households_of_three_ethnic_groups_share_of_family_househol |
Households of three ethnic groups > Share of family households | decimal | 0% | - | - |
households_of_four_or_more_ethnic_groups_number_of_househo |
Households of four or more ethnic groups > Number of households | decimal | 0% | - | - |
households_of_four_or_more_ethnic_groups_share_of_family_h |
Households of four or more ethnic groups > Share of family households | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
single_ethnic_group_households_number_of_households |
Single-ethnic-group households > Number of households | decimal | 0% | - | - |
single_ethnic_group_households_share_of_family_households |
Single-ethnic-group households > Share of family households | decimal | 0% | - | - |
households_of_two_ethnic_groups_number_of_households |
Households of two ethnic groups > Number of households | decimal | 0% | - | - |
households_of_two_ethnic_groups_share_of_family_households |
Households of two ethnic groups > Share of family households | decimal | 0% | - | - |
households_of_three_ethnic_groups_number_of_households |
Households of three ethnic groups > Number of households | decimal | 0% | - | - |
households_of_three_ethnic_groups_share_of_family_househol |
Households of three ethnic groups > Share of family households | decimal | 0% | - | - |
households_of_four_or_more_ethnic_groups_number_of_househo |
Households of four or more ethnic groups > Number of households | decimal | 0% | - | - |
households_of_four_or_more_ethnic_groups_share_of_family_h |
Households of four or more ethnic groups > Share of family households | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_60_and_over_subtotal |
Households with one person aged 60 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_living_alone |
Households with one person aged 60 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_living_only_wi |
Households with one person aged 60 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_other |
Households with one person aged 60 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_subtotal |
Households with two persons aged 60 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_couple_both_a |
Households with two persons aged 60 and over > Couple both aged 60 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_couple_both_a_2 |
Households with two persons aged 60 and over > Couple both aged 60 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_other |
Households with two persons aged 60 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_60_and_over |
Households with three or more persons aged 60 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_60_and_over_subtotal |
Households with one person aged 60 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_living_alone |
Households with one person aged 60 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_living_only_wi |
Households with one person aged 60 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_other |
Households with one person aged 60 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_subtotal |
Households with two persons aged 60 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_couple_both_a |
Households with two persons aged 60 and over > Couple both aged 60 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_couple_both_a_2 |
Households with two persons aged 60 and over > Couple both aged 60 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_other |
Households with two persons aged 60 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_60_and_over |
Households with three or more persons aged 60 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_60_and_over_subtotal |
Households with one person aged 60 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_living_alone |
Households with one person aged 60 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_living_only_wi |
Households with one person aged 60 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_other |
Households with one person aged 60 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_subtotal |
Households with two persons aged 60 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_couple_both_a |
Households with two persons aged 60 and over > Couple both aged 60 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_couple_both_a_2 |
Households with two persons aged 60 and over > Couple both aged 60 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_other |
Households with two persons aged 60 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_60_and_over |
Households with three or more persons aged 60 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_60_and_over_subtotal |
Households with one person aged 60 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_living_alone |
Households with one person aged 60 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_living_only_wi |
Households with one person aged 60 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_60_and_over_other |
Households with one person aged 60 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_subtotal |
Households with two persons aged 60 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_couple_both_a |
Households with two persons aged 60 and over > Couple both aged 60 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_couple_both_a_2 |
Households with two persons aged 60 and over > Couple both aged 60 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_60_and_over_other |
Households with two persons aged 60 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_60_and_over |
Households with three or more persons aged 60 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_65_and_over_subtotal |
Households with one person aged 65 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_living_alone |
Households with one person aged 65 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_living_only_wi |
Households with one person aged 65 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_other |
Households with one person aged 65 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_subtotal |
Households with two persons aged 65 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_couple_both_a |
Households with two persons aged 65 and over > Couple both aged 65 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_couple_both_a_2 |
Households with two persons aged 65 and over > Couple both aged 65 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_other |
Households with two persons aged 65 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_65_and_over |
Households with three or more persons aged 65 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_65_and_over_subtotal |
Households with one person aged 65 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_living_alone |
Households with one person aged 65 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_living_only_wi |
Households with one person aged 65 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_other |
Households with one person aged 65 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_subtotal |
Households with two persons aged 65 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_couple_both_a |
Households with two persons aged 65 and over > Couple both aged 65 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_couple_both_a_2 |
Households with two persons aged 65 and over > Couple both aged 65 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_other |
Households with two persons aged 65 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_65_and_over |
Households with three or more persons aged 65 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_65_and_over_subtotal |
Households with one person aged 65 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_living_alone |
Households with one person aged 65 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_living_only_wi |
Households with one person aged 65 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_other |
Households with one person aged 65 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_subtotal |
Households with two persons aged 65 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_couple_both_a |
Households with two persons aged 65 and over > Couple both aged 65 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_couple_both_a_2 |
Households with two persons aged 65 and over > Couple both aged 65 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_other |
Households with two persons aged 65 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_65_and_over |
Households with three or more persons aged 65 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_65_and_over_subtotal |
Households with one person aged 65 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_living_alone |
Households with one person aged 65 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_living_only_wi |
Households with one person aged 65 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_65_and_over_other |
Households with one person aged 65 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_subtotal |
Households with two persons aged 65 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_couple_both_a |
Households with two persons aged 65 and over > Couple both aged 65 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_couple_both_a_2 |
Households with two persons aged 65 and over > Couple both aged 65 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_65_and_over_other |
Households with two persons aged 65 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_65_and_over |
Households with three or more persons aged 65 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_80_and_over_subtotal |
Households with one person aged 80 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_living_alone |
Households with one person aged 80 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_living_only_wi |
Households with one person aged 80 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_other |
Households with one person aged 80 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_subtotal |
Households with two persons aged 80 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_couple_both_a |
Households with two persons aged 80 and over > Couple both aged 80 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_couple_both_a_2 |
Households with two persons aged 80 and over > Couple both aged 80 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_other |
Households with two persons aged 80 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_80_and_over |
Households with three or more persons aged 80 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_80_and_over_subtotal |
Households with one person aged 80 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_living_alone |
Households with one person aged 80 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_living_only_wi |
Households with one person aged 80 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_other |
Households with one person aged 80 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_subtotal |
Households with two persons aged 80 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_couple_both_a |
Households with two persons aged 80 and over > Couple both aged 80 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_couple_both_a_2 |
Households with two persons aged 80 and over > Couple both aged 80 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_other |
Households with two persons aged 80 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_80_and_over |
Households with three or more persons aged 80 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_80_and_over_subtotal |
Households with one person aged 80 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_living_alone |
Households with one person aged 80 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_living_only_wi |
Households with one person aged 80 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_other |
Households with one person aged 80 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_subtotal |
Households with two persons aged 80 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_couple_both_a |
Households with two persons aged 80 and over > Couple both aged 80 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_couple_both_a_2 |
Households with two persons aged 80 and over > Couple both aged 80 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_other |
Households with two persons aged 80 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_80_and_over |
Households with three or more persons aged 80 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
households_with_one_person_aged_80_and_over_subtotal |
Households with one person aged 80 and over > Subtotal | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_living_alone |
Households with one person aged 80 and over > Living alone | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_living_only_wi |
Households with one person aged 80 and over > Living only with minors | decimal | 0% | - | - |
households_with_one_person_aged_80_and_over_other |
Households with one person aged 80 and over > Other | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_subtotal |
Households with two persons aged 80 and over > Subtotal | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_couple_both_a |
Households with two persons aged 80 and over > Couple both aged 80 and over living alone | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_couple_both_a_2 |
Households with two persons aged 80 and over > Couple both aged 80 and over living with minors | decimal | 0% | - | - |
households_with_two_persons_aged_80_and_over_other |
Households with two persons aged 80 and over > Other | decimal | 0% | - | - |
households_with_three_or_more_persons_aged_80_and_over |
Households with three or more persons aged 80 and over | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_households |
Number of households (households) | decimal | 0% | - | - |
number_of_persons_persons |
Number of persons (persons) | decimal | 0% | - | - |
average_rooms_per_household_rooms_household |
Average rooms per household (rooms/household) | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_person |
Per capita housing floor area (square metres/person) | decimal | 0% | - | - |
rooms_per_person_rooms_person |
Rooms per person (rooms/person) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_households |
Number of households (households) | decimal | 0% | - | - |
number_of_persons_persons |
Number of persons (persons) | decimal | 0% | - | - |
average_rooms_per_household_rooms_household |
Average rooms per household (rooms/household) | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_person |
Per capita housing floor area (square metres/person) | decimal | 0% | - | - |
rooms_per_person_rooms_person |
Rooms per person (rooms/person) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_households |
Number of households (households) | decimal | 0% | - | - |
number_of_persons_persons |
Number of persons (persons) | decimal | 0% | - | - |
average_rooms_per_household_rooms_household |
Average rooms per household (rooms/household) | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_person |
Per capita housing floor area (square metres/person) | decimal | 0% | - | - |
rooms_per_person_rooms_person |
Rooms per person (rooms/person) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households_households |
Number of households (households) | decimal | 0% | - | - |
number_of_persons_persons |
Number of persons (persons) | decimal | 0% | - | - |
average_rooms_per_household_rooms_household |
Average rooms per household (rooms/household) | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_person |
Per capita housing floor area (square metres/person) | decimal | 0% | - | - |
rooms_per_person_rooms_person |
Rooms per person (rooms/person) | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households |
Number of households | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_8_m_or_less |
Per capita housing floor area (square metres) > 8 m² or less | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_9_12_m |
Per capita housing floor area (square metres) > 9-12 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_13_16_m |
Per capita housing floor area (square metres) > 13-16 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_17_19_m |
Per capita housing floor area (square metres) > 17-19 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_20_29_m |
Per capita housing floor area (square metres) > 20-29 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_30_39_m |
Per capita housing floor area (square metres) > 30-39 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_40_49_m |
Per capita housing floor area (square metres) > 40-49 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_50_59_m |
Per capita housing floor area (square metres) > 50-59 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_60_m_or_more |
Per capita housing floor area (square metres) > 60 m² or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households |
Number of households | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_8_m_or_less |
Per capita housing floor area (square metres) > 8 m² or less | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_9_12_m |
Per capita housing floor area (square metres) > 9-12 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_13_16_m |
Per capita housing floor area (square metres) > 13-16 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_17_19_m |
Per capita housing floor area (square metres) > 17-19 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_20_29_m |
Per capita housing floor area (square metres) > 20-29 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_30_39_m |
Per capita housing floor area (square metres) > 30-39 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_40_49_m |
Per capita housing floor area (square metres) > 40-49 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_50_59_m |
Per capita housing floor area (square metres) > 50-59 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_60_m_or_more |
Per capita housing floor area (square metres) > 60 m² or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households |
Number of households | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_8_m_or_less |
Per capita housing floor area (square metres) > 8 m² or less | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_9_12_m |
Per capita housing floor area (square metres) > 9-12 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_13_16_m |
Per capita housing floor area (square metres) > 13-16 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_17_19_m |
Per capita housing floor area (square metres) > 17-19 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_20_29_m |
Per capita housing floor area (square metres) > 20-29 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_30_39_m |
Per capita housing floor area (square metres) > 30-39 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_40_49_m |
Per capita housing floor area (square metres) > 40-49 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_50_59_m |
Per capita housing floor area (square metres) > 50-59 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_60_m_or_more |
Per capita housing floor area (square metres) > 60 m² or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_households |
Number of households | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_8_m_or_less |
Per capita housing floor area (square metres) > 8 m² or less | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_9_12_m |
Per capita housing floor area (square metres) > 9-12 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_13_16_m |
Per capita housing floor area (square metres) > 13-16 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_17_19_m |
Per capita housing floor area (square metres) > 17-19 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_20_29_m |
Per capita housing floor area (square metres) > 20-29 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_30_39_m |
Per capita housing floor area (square metres) > 30-39 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_40_49_m |
Per capita housing floor area (square metres) > 40-49 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_50_59_m |
Per capita housing floor area (square metres) > 50-59 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_60_m_or_more |
Per capita housing floor area (square metres) > 60 m² or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_rooms_1_room |
Number of rooms > 1 room | decimal | 0% | - | - |
number_of_rooms_2_rooms |
Number of rooms > 2 rooms | decimal | 0% | - | - |
number_of_rooms_3_rooms |
Number of rooms > 3 rooms | decimal | 0% | - | - |
number_of_rooms_4_rooms |
Number of rooms > 4 rooms | decimal | 0% | - | - |
number_of_rooms_5_rooms |
Number of rooms > 5 rooms | decimal | 0% | - | - |
number_of_rooms_6_rooms |
Number of rooms > 6 rooms | decimal | 0% | - | - |
number_of_rooms_7_rooms |
Number of rooms > 7 rooms | decimal | 0% | - | - |
number_of_rooms_8_rooms |
Number of rooms > 8 rooms | decimal | 0% | - | - |
number_of_rooms_9_rooms |
Number of rooms > 9 rooms | decimal | 0% | - | - |
number_of_rooms_10_rooms_or_more |
Number of rooms > 10 rooms or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_rooms_1_room |
Number of rooms > 1 room | decimal | 0% | - | - |
number_of_rooms_2_rooms |
Number of rooms > 2 rooms | decimal | 0% | - | - |
number_of_rooms_3_rooms |
Number of rooms > 3 rooms | decimal | 0% | - | - |
number_of_rooms_4_rooms |
Number of rooms > 4 rooms | decimal | 0% | - | - |
number_of_rooms_5_rooms |
Number of rooms > 5 rooms | decimal | 0% | - | - |
number_of_rooms_6_rooms |
Number of rooms > 6 rooms | decimal | 0% | - | - |
number_of_rooms_7_rooms |
Number of rooms > 7 rooms | decimal | 0% | - | - |
number_of_rooms_8_rooms |
Number of rooms > 8 rooms | decimal | 0% | - | - |
number_of_rooms_9_rooms |
Number of rooms > 9 rooms | decimal | 0% | - | - |
number_of_rooms_10_rooms_or_more |
Number of rooms > 10 rooms or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_rooms_1_room |
Number of rooms > 1 room | decimal | 0% | - | - |
number_of_rooms_2_rooms |
Number of rooms > 2 rooms | decimal | 0% | - | - |
number_of_rooms_3_rooms |
Number of rooms > 3 rooms | decimal | 0% | - | - |
number_of_rooms_4_rooms |
Number of rooms > 4 rooms | decimal | 0% | - | - |
number_of_rooms_5_rooms |
Number of rooms > 5 rooms | decimal | 0% | - | - |
number_of_rooms_6_rooms |
Number of rooms > 6 rooms | decimal | 0% | - | - |
number_of_rooms_7_rooms |
Number of rooms > 7 rooms | decimal | 0% | - | - |
number_of_rooms_8_rooms |
Number of rooms > 8 rooms | decimal | 0% | - | - |
number_of_rooms_9_rooms |
Number of rooms > 9 rooms | decimal | 0% | - | - |
number_of_rooms_10_rooms_or_more |
Number of rooms > 10 rooms or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_rooms_1_room |
Number of rooms > 1 room | decimal | 0% | - | - |
number_of_rooms_2_rooms |
Number of rooms > 2 rooms | decimal | 0% | - | - |
number_of_rooms_3_rooms |
Number of rooms > 3 rooms | decimal | 0% | - | - |
number_of_rooms_4_rooms |
Number of rooms > 4 rooms | decimal | 0% | - | - |
number_of_rooms_5_rooms |
Number of rooms > 5 rooms | decimal | 0% | - | - |
number_of_rooms_6_rooms |
Number of rooms > 6 rooms | decimal | 0% | - | - |
number_of_rooms_7_rooms |
Number of rooms > 7 rooms | decimal | 0% | - | - |
number_of_rooms_8_rooms |
Number of rooms > 8 rooms | decimal | 0% | - | - |
number_of_rooms_9_rooms |
Number of rooms > 9 rooms | decimal | 0% | - | - |
number_of_rooms_10_rooms_or_more |
Number of rooms > 10 rooms or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
per_capita_housing_floor_area_square_metres_8_m_or_less |
Per capita housing floor area (square metres) > 8 m² or less | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_9_12_m |
Per capita housing floor area (square metres) > 9-12 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_13_16_m |
Per capita housing floor area (square metres) > 13-16 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_17_19_m |
Per capita housing floor area (square metres) > 17-19 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_20_29_m |
Per capita housing floor area (square metres) > 20-29 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_30_39_m |
Per capita housing floor area (square metres) > 30-39 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_40_49_m |
Per capita housing floor area (square metres) > 40-49 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_50_59_m |
Per capita housing floor area (square metres) > 50-59 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_60_69_m |
Per capita housing floor area (square metres) > 60-69 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_70_m_or_more |
Per capita housing floor area (square metres) > 70 m² or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
per_capita_housing_floor_area_square_metres_8_m_or_less |
Per capita housing floor area (square metres) > 8 m² or less | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_9_12_m |
Per capita housing floor area (square metres) > 9-12 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_13_16_m |
Per capita housing floor area (square metres) > 13-16 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_17_19_m |
Per capita housing floor area (square metres) > 17-19 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_20_29_m |
Per capita housing floor area (square metres) > 20-29 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_30_39_m |
Per capita housing floor area (square metres) > 30-39 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_40_49_m |
Per capita housing floor area (square metres) > 40-49 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_50_59_m |
Per capita housing floor area (square metres) > 50-59 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_60_69_m |
Per capita housing floor area (square metres) > 60-69 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_70_m_or_more |
Per capita housing floor area (square metres) > 70 m² or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
per_capita_housing_floor_area_square_metres_8_m_or_less |
Per capita housing floor area (square metres) > 8 m² or less | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_9_12_m |
Per capita housing floor area (square metres) > 9-12 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_13_16_m |
Per capita housing floor area (square metres) > 13-16 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_17_19_m |
Per capita housing floor area (square metres) > 17-19 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_20_29_m |
Per capita housing floor area (square metres) > 20-29 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_30_39_m |
Per capita housing floor area (square metres) > 30-39 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_40_49_m |
Per capita housing floor area (square metres) > 40-49 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_50_59_m |
Per capita housing floor area (square metres) > 50-59 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_60_69_m |
Per capita housing floor area (square metres) > 60-69 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_70_m_or_more |
Per capita housing floor area (square metres) > 70 m² or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
per_capita_housing_floor_area_square_metres_8_m_or_less |
Per capita housing floor area (square metres) > 8 m² or less | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_9_12_m |
Per capita housing floor area (square metres) > 9-12 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_13_16_m |
Per capita housing floor area (square metres) > 13-16 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_17_19_m |
Per capita housing floor area (square metres) > 17-19 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_20_29_m |
Per capita housing floor area (square metres) > 20-29 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_30_39_m |
Per capita housing floor area (square metres) > 30-39 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_40_49_m |
Per capita housing floor area (square metres) > 40-49 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_50_59_m |
Per capita housing floor area (square metres) > 50-59 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_60_69_m |
Per capita housing floor area (square metres) > 60-69 m² | decimal | 0% | - | - |
per_capita_housing_floor_area_square_metres_70_m_or_more |
Per capita housing floor area (square metres) > 70 m² or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
one_generation_household_1_room |
One-generation household > 1 room | decimal | 0% | - | - |
one_generation_household_2_rooms |
One-generation household > 2 rooms | decimal | 0% | - | - |
one_generation_household_3_rooms |
One-generation household > 3 rooms | decimal | 0% | - | - |
one_generation_household_4_rooms |
One-generation household > 4 rooms | decimal | 0% | - | - |
one_generation_household_5_rooms_or_more |
One-generation household > 5 rooms or more | decimal | 0% | - | - |
two_generation_household_1_room |
Two-generation household > 1 room | decimal | 0% | - | - |
two_generation_household_2_rooms |
Two-generation household > 2 rooms | decimal | 0% | - | - |
two_generation_household_3_rooms |
Two-generation household > 3 rooms | decimal | 0% | - | - |
two_generation_household_4_rooms |
Two-generation household > 4 rooms | decimal | 0% | - | - |
two_generation_household_5_rooms_or_more |
Two-generation household > 5 rooms or more | decimal | 0% | - | - |
three_generation_household_1_room |
Three-generation household > 1 room | decimal | 0% | - | - |
three_generation_household_2_rooms |
Three-generation household > 2 rooms | decimal | 0% | - | - |
three_generation_household_3_rooms |
Three-generation household > 3 rooms | decimal | 0% | - | - |
three_generation_household_4_rooms |
Three-generation household > 4 rooms | decimal | 0% | - | - |
three_generation_household_5_rooms_or_more |
Three-generation household > 5 rooms or more | decimal | 0% | - | - |
four_generation_household_1_room |
Four-generation household > 1 room | decimal | 0% | - | - |
four_generation_household_2_rooms |
Four-generation household > 2 rooms | decimal | 0% | - | - |
four_generation_household_3_rooms |
Four-generation household > 3 rooms | decimal | 0% | - | - |
four_generation_household_4_rooms |
Four-generation household > 4 rooms | decimal | 0% | - | - |
four_generation_household_5_rooms_or_more |
Four-generation household > 5 rooms or more | decimal | 0% | - | - |
households_of_five_or_more_generations_1_room |
Households of five or more generations > 1 room | decimal | 0% | - | - |
households_of_five_or_more_generations_2_rooms |
Households of five or more generations > 2 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_3_rooms |
Households of five or more generations > 3 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_4_rooms |
Households of five or more generations > 4 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_5_rooms_or_more |
Households of five or more generations > 5 rooms or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
one_generation_household_1_room |
One-generation household > 1 room | decimal | 0% | - | - |
one_generation_household_2_rooms |
One-generation household > 2 rooms | decimal | 0% | - | - |
one_generation_household_3_rooms |
One-generation household > 3 rooms | decimal | 0% | - | - |
one_generation_household_4_rooms |
One-generation household > 4 rooms | decimal | 0% | - | - |
one_generation_household_5_rooms_or_more |
One-generation household > 5 rooms or more | decimal | 0% | - | - |
two_generation_household_1_room |
Two-generation household > 1 room | decimal | 0% | - | - |
two_generation_household_2_rooms |
Two-generation household > 2 rooms | decimal | 0% | - | - |
two_generation_household_3_rooms |
Two-generation household > 3 rooms | decimal | 0% | - | - |
two_generation_household_4_rooms |
Two-generation household > 4 rooms | decimal | 0% | - | - |
two_generation_household_5_rooms_or_more |
Two-generation household > 5 rooms or more | decimal | 0% | - | - |
three_generation_household_1_room |
Three-generation household > 1 room | decimal | 0% | - | - |
three_generation_household_2_rooms |
Three-generation household > 2 rooms | decimal | 0% | - | - |
three_generation_household_3_rooms |
Three-generation household > 3 rooms | decimal | 0% | - | - |
three_generation_household_4_rooms |
Three-generation household > 4 rooms | decimal | 0% | - | - |
three_generation_household_5_rooms_or_more |
Three-generation household > 5 rooms or more | decimal | 0% | - | - |
four_generation_household_1_room |
Four-generation household > 1 room | decimal | 0% | - | - |
four_generation_household_2_rooms |
Four-generation household > 2 rooms | decimal | 0% | - | - |
four_generation_household_3_rooms |
Four-generation household > 3 rooms | decimal | 0% | - | - |
four_generation_household_4_rooms |
Four-generation household > 4 rooms | decimal | 0% | - | - |
four_generation_household_5_rooms_or_more |
Four-generation household > 5 rooms or more | decimal | 0% | - | - |
households_of_five_or_more_generations_1_room |
Households of five or more generations > 1 room | decimal | 0% | - | - |
households_of_five_or_more_generations_2_rooms |
Households of five or more generations > 2 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_3_rooms |
Households of five or more generations > 3 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_4_rooms |
Households of five or more generations > 4 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_5_rooms_or_more |
Households of five or more generations > 5 rooms or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
one_generation_household_1_room |
One-generation household > 1 room | decimal | 0% | - | - |
one_generation_household_2_rooms |
One-generation household > 2 rooms | decimal | 0% | - | - |
one_generation_household_3_rooms |
One-generation household > 3 rooms | decimal | 0% | - | - |
one_generation_household_4_rooms |
One-generation household > 4 rooms | decimal | 0% | - | - |
one_generation_household_5_rooms_or_more |
One-generation household > 5 rooms or more | decimal | 0% | - | - |
two_generation_household_1_room |
Two-generation household > 1 room | decimal | 0% | - | - |
two_generation_household_2_rooms |
Two-generation household > 2 rooms | decimal | 0% | - | - |
two_generation_household_3_rooms |
Two-generation household > 3 rooms | decimal | 0% | - | - |
two_generation_household_4_rooms |
Two-generation household > 4 rooms | decimal | 0% | - | - |
two_generation_household_5_rooms_or_more |
Two-generation household > 5 rooms or more | decimal | 0% | - | - |
three_generation_household_1_room |
Three-generation household > 1 room | decimal | 0% | - | - |
three_generation_household_2_rooms |
Three-generation household > 2 rooms | decimal | 0% | - | - |
three_generation_household_3_rooms |
Three-generation household > 3 rooms | decimal | 0% | - | - |
three_generation_household_4_rooms |
Three-generation household > 4 rooms | decimal | 0% | - | - |
three_generation_household_5_rooms_or_more |
Three-generation household > 5 rooms or more | decimal | 0% | - | - |
four_generation_household_1_room |
Four-generation household > 1 room | decimal | 0% | - | - |
four_generation_household_2_rooms |
Four-generation household > 2 rooms | decimal | 0% | - | - |
four_generation_household_3_rooms |
Four-generation household > 3 rooms | decimal | 0% | - | - |
four_generation_household_4_rooms |
Four-generation household > 4 rooms | decimal | 0% | - | - |
four_generation_household_5_rooms_or_more |
Four-generation household > 5 rooms or more | decimal | 0% | - | - |
households_of_five_or_more_generations_1_room |
Households of five or more generations > 1 room | decimal | 0% | - | - |
households_of_five_or_more_generations_2_rooms |
Households of five or more generations > 2 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_3_rooms |
Households of five or more generations > 3 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_4_rooms |
Households of five or more generations > 4 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_5_rooms_or_more |
Households of five or more generations > 5 rooms or more | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
number_of_family_households |
Number of family households | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
one_generation_household_1_room |
One-generation household > 1 room | decimal | 0% | - | - |
one_generation_household_2_rooms |
One-generation household > 2 rooms | decimal | 0% | - | - |
one_generation_household_3_rooms |
One-generation household > 3 rooms | decimal | 0% | - | - |
one_generation_household_4_rooms |
One-generation household > 4 rooms | decimal | 0% | - | - |
one_generation_household_5_rooms_or_more |
One-generation household > 5 rooms or more | decimal | 0% | - | - |
two_generation_household_1_room |
Two-generation household > 1 room | decimal | 0% | - | - |
two_generation_household_2_rooms |
Two-generation household > 2 rooms | decimal | 0% | - | - |
two_generation_household_3_rooms |
Two-generation household > 3 rooms | decimal | 0% | - | - |
two_generation_household_4_rooms |
Two-generation household > 4 rooms | decimal | 0% | - | - |
two_generation_household_5_rooms_or_more |
Two-generation household > 5 rooms or more | decimal | 0% | - | - |
three_generation_household_1_room |
Three-generation household > 1 room | decimal | 0% | - | - |
three_generation_household_2_rooms |
Three-generation household > 2 rooms | decimal | 0% | - | - |
three_generation_household_3_rooms |
Three-generation household > 3 rooms | decimal | 0% | - | - |
three_generation_household_4_rooms |
Three-generation household > 4 rooms | decimal | 0% | - | - |
three_generation_household_5_rooms_or_more |
Three-generation household > 5 rooms or more | decimal | 0% | - | - |
four_generation_household_1_room |
Four-generation household > 1 room | decimal | 0% | - | - |
four_generation_household_2_rooms |
Four-generation household > 2 rooms | decimal | 0% | - | - |
four_generation_household_3_rooms |
Four-generation household > 3 rooms | decimal | 0% | - | - |
four_generation_household_4_rooms |
Four-generation household > 4 rooms | decimal | 0% | - | - |
four_generation_household_5_rooms_or_more |
Four-generation household > 5 rooms or more | decimal | 0% | - | - |
households_of_five_or_more_generations_1_room |
Households of five or more generations > 1 room | decimal | 0% | - | - |
households_of_five_or_more_generations_2_rooms |
Households of five or more generations > 2 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_3_rooms |
Households of five or more generations > 3 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_4_rooms |
Households of five or more generations > 4 rooms | decimal | 0% | - | - |
households_of_five_or_more_generations_5_rooms_or_more |
Households of five or more generations > 5 rooms or more | decimal | 0% | - | - |
ⓘ 1-in-10 household sample. These tables come from the census long questionnaire, which about one household in ten answered. The National Bureau of Statistics publishes the sample's own counts without scaling them up, so counts here are about a tenth of the real figure: this sample counted 138,657,945 people, against 1,409,778,724 in the full count. Shares, rates and averages can be used as they are; for population totals use the full-count datasets.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_subtotal |
Agriculture, forestry, animal husbandry and fishery > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_male |
Agriculture, forestry, animal husbandry and fishery > Male | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_female |
Agriculture, forestry, animal husbandry and fishery > Female | decimal | 0% | - | - |
mining_subtotal |
Mining > Subtotal | decimal | 0% | - | - |
mining_male |
Mining > Male | decimal | 0% | - | - |
mining_female |
Mining > Female | decimal | 0% | - | - |
manufacturing_subtotal |
Manufacturing > Subtotal | decimal | 0% | - | - |
manufacturing_male |
Manufacturing > Male | decimal | 0% | - | - |
manufacturing_female |
Manufacturing > Female | decimal | 0% | - | - |
production_and_supply_of_electricity_heat_gas_and_water_su |
Production and supply of electricity, heat, gas and water > Subtotal | decimal | 0% | - | - |
production_and_supply_of_electricity_heat_gas_and_water_ma |
Production and supply of electricity, heat, gas and water > Male | decimal | 0% | - | - |
production_and_supply_of_electricity_heat_gas_and_water_fe |
Production and supply of electricity, heat, gas and water > Female | decimal | 0% | - | - |
construction_subtotal |
Construction > Subtotal | decimal | 0% | - | - |
construction_male |
Construction > Male | decimal | 0% | - | - |
construction_female |
Construction > Female | decimal | 0% | - | - |
wholesale_and_retail_trade_subtotal |
Wholesale and retail trade > Subtotal | decimal | 0% | - | - |
wholesale_and_retail_trade_male |
Wholesale and retail trade > Male | decimal | 0% | - | - |
wholesale_and_retail_trade_female |
Wholesale and retail trade > Female | decimal | 0% | - | - |
transport_storage_and_post_subtotal |
Transport, storage and post > Subtotal | decimal | 0% | - | - |
transport_storage_and_post_male |
Transport, storage and post > Male | decimal | 0% | - | - |
transport_storage_and_post_female |
Transport, storage and post > Female | decimal | 0% | - | - |
accommodation_and_catering_subtotal |
Accommodation and catering > Subtotal | decimal | 0% | - | - |
accommodation_and_catering_male |
Accommodation and catering > Male | decimal | 0% | - | - |
accommodation_and_catering_female |
Accommodation and catering > Female | decimal | 0% | - | - |
information_transmission_software_and_information_technolo |
Information transmission, software and information technology services > Subtotal | decimal | 0% | - | - |
information_transmission_software_and_information_technolo_2 |
Information transmission, software and information technology services > Male | decimal | 0% | - | - |
| +34 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
population_total |
Population > Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_male |
Population > Male | decimal | 0% | - | - |
population_female |
Population > Female | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Male | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Female | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_male |
Professional and technical personnel > Male | decimal | 0% | - | - |
professional_and_technical_personnel_female |
Professional and technical personnel > Female | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_male |
Clerical staff and related personnel > Male | decimal | 0% | - | - |
clerical_staff_and_related_personnel_female |
Clerical staff and related personnel > Female | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_male |
Social production and living service personnel > Male | decimal | 0% | - | - |
social_production_and_living_service_personnel_female |
Social production and living service personnel > Female | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_producti |
Agriculture, forestry, animal husbandry and fishery production and support workers > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_producti_2 |
Agriculture, forestry, animal husbandry and fishery production and support workers > Male | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_producti_3 |
Agriculture, forestry, animal husbandry and fishery production and support workers > Female | decimal | 0% | - | - |
production_manufacturing_and_related_workers_subtotal |
Production, manufacturing and related workers > Subtotal | decimal | 0% | - | - |
production_manufacturing_and_related_workers_male |
Production, manufacturing and related workers > Male | decimal | 0% | - | - |
production_manufacturing_and_related_workers_female |
Production, manufacturing and related workers > Female | decimal | 0% | - | - |
other_employed_persons_not_elsewhere_classified_subtotal |
Other employed persons not elsewhere classified > Subtotal | decimal | 0% | - | - |
other_employed_persons_not_elsewhere_classified_male |
Other employed persons not elsewhere classified > Male | decimal | 0% | - | - |
other_employed_persons_not_elsewhere_classified_female |
Other employed persons not elsewhere classified > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
income_from_work_subtotal |
Income from work > Subtotal | decimal | 0% | - | - |
income_from_work_male |
Income from work > Male | decimal | 0% | - | - |
income_from_work_female |
Income from work > Female | decimal | 0% | - | - |
retirement_pension_old_age_pension_subtotal |
Retirement pension / old-age pension > Subtotal | decimal | 0% | - | - |
retirement_pension_old_age_pension_male |
Retirement pension / old-age pension > Male | decimal | 0% | - | - |
retirement_pension_old_age_pension_female |
Retirement pension / old-age pension > Female | decimal | 0% | - | - |
minimum_living_allowance_subtotal |
Minimum living allowance > Subtotal | decimal | 0% | - | - |
minimum_living_allowance_male |
Minimum living allowance > Male | decimal | 0% | - | - |
minimum_living_allowance_female |
Minimum living allowance > Female | decimal | 0% | - | - |
unemployment_insurance_benefit_subtotal |
Unemployment insurance benefit > Subtotal | decimal | 0% | - | - |
unemployment_insurance_benefit_male |
Unemployment insurance benefit > Male | decimal | 0% | - | - |
unemployment_insurance_benefit_female |
Unemployment insurance benefit > Female | decimal | 0% | - | - |
property_income_subtotal |
Property income > Subtotal | decimal | 0% | - | - |
property_income_male |
Property income > Male | decimal | 0% | - | - |
property_income_female |
Property income > Female | decimal | 0% | - | - |
supported_by_other_household_members_subtotal |
Supported by other household members > Subtotal | decimal | 0% | - | - |
supported_by_other_household_members_male |
Supported by other household members > Male | decimal | 0% | - | - |
supported_by_other_household_members_female |
Supported by other household members > Female | decimal | 0% | - | - |
other_subtotal |
Other > Subtotal | decimal | 0% | - | - |
other_male |
Other > Male | decimal | 0% | - | - |
other_female |
Other > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
population_aged_15_and_over_total |
Population aged 15 and over > Total | decimal | 0% | - | - |
population_aged_15_and_over_male |
Population aged 15 and over > Male | decimal | 0% | - | - |
population_aged_15_and_over_female |
Population aged 15 and over > Female | decimal | 0% | - | - |
never_married_subtotal |
Never married > Subtotal | decimal | 0% | - | - |
never_married_male |
Never married > Male | decimal | 0% | - | - |
never_married_female |
Never married > Female | decimal | 0% | - | - |
married_subtotal |
Married > Subtotal | decimal | 0% | - | - |
married_male |
Married > Male | decimal | 0% | - | - |
married_female |
Married > Female | decimal | 0% | - | - |
divorced_subtotal |
Divorced > Subtotal | decimal | 0% | - | - |
divorced_male |
Divorced > Male | decimal | 0% | - | - |
divorced_female |
Divorced > Female | decimal | 0% | - | - |
widowed_subtotal |
Widowed > Subtotal | decimal | 0% | - | - |
widowed_male |
Widowed > Male | decimal | 0% | - | - |
widowed_female |
Widowed > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
under_15_subtotal |
Under 15 > Subtotal | decimal | 0% | - | - |
under_15_male |
Under 15 > Male | decimal | 0% | - | - |
under_15_female |
Under 15 > Female | decimal | 0% | - | - |
age_15_subtotal |
Age 15 > Subtotal | decimal | 0% | - | - |
age_15_male |
Age 15 > Male | decimal | 0% | - | - |
age_15_female |
Age 15 > Female | decimal | 0% | - | - |
age_16_subtotal |
Age 16 > Subtotal | decimal | 0% | - | - |
age_16_male |
Age 16 > Male | decimal | 0% | - | - |
age_16_female |
Age 16 > Female | decimal | 0% | - | - |
age_17_subtotal |
Age 17 > Subtotal | decimal | 0% | - | - |
age_17_male |
Age 17 > Male | decimal | 0% | - | - |
age_17_female |
Age 17 > Female | decimal | 0% | - | - |
age_18_subtotal |
Age 18 > Subtotal | decimal | 0% | - | - |
age_18_male |
Age 18 > Male | decimal | 0% | - | - |
age_18_female |
Age 18 > Female | decimal | 0% | - | - |
age_19_subtotal |
Age 19 > Subtotal | decimal | 0% | - | - |
age_19_male |
Age 19 > Male | decimal | 0% | - | - |
age_19_female |
Age 19 > Female | decimal | 0% | - | - |
age_20_subtotal |
Age 20 > Subtotal | decimal | 0% | - | - |
age_20_male |
Age 20 > Male | decimal | 0% | - | - |
age_20_female |
Age 20 > Female | decimal | 0% | - | - |
age_21_subtotal |
Age 21 > Subtotal | decimal | 0% | - | - |
age_21_male |
Age 21 > Male | decimal | 0% | - | - |
age_21_female |
Age 21 > Female | decimal | 0% | - | - |
age_22_subtotal |
Age 22 > Subtotal | decimal | 0% | - | - |
| +56 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_who_gave_birth_to_a_boy |
Number of women who gave birth to a boy | decimal | 0% | - | - |
number_of_women_who_gave_birth_to_a_girl |
Number of women who gave birth to a girl | decimal | 0% | - | - |
first_birth_subtotal |
First birth > Subtotal | decimal | 0% | - | - |
first_birth_male |
First birth > Male | decimal | 0% | - | - |
first_birth_female |
First birth > Female | decimal | 0% | - | - |
second_birth_subtotal |
Second birth > Subtotal | decimal | 0% | - | - |
second_birth_male |
Second birth > Male | decimal | 0% | - | - |
second_birth_female |
Second birth > Female | decimal | 0% | - | - |
third_birth_subtotal |
Third birth > Subtotal | decimal | 0% | - | - |
third_birth_male |
Third birth > Male | decimal | 0% | - | - |
third_birth_female |
Third birth > Female | decimal | 0% | - | - |
fourth_birth_subtotal |
Fourth birth > Subtotal | decimal | 0% | - | - |
fourth_birth_male |
Fourth birth > Male | decimal | 0% | - | - |
fourth_birth_female |
Fourth birth > Female | decimal | 0% | - | - |
fifth_birth_or_higher_subtotal |
Fifth birth or higher > Subtotal | decimal | 0% | - | - |
fifth_birth_or_higher_male |
Fifth birth or higher > Male | decimal | 0% | - | - |
fifth_birth_or_higher_female |
Fifth birth or higher > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
number_of_women_aged_15_64 |
Number of women aged 15-64 | decimal | 0% | - | - |
total_live_births_subtotal |
Total live births > Subtotal | decimal | 0% | - | - |
total_live_births_male |
Total live births > Male | decimal | 0% | - | - |
total_live_births_female |
Total live births > Female | decimal | 0% | - | - |
total_surviving_children_subtotal |
Total surviving children > Subtotal | decimal | 0% | - | - |
total_surviving_children_male |
Total surviving children > Male | decimal | 0% | - | - |
total_surviving_children_female |
Total surviving children > Female | decimal | 0% | - | - |
surviving_children_as_a_percentage_of_live_births |
Surviving children as a percentage of live births | decimal | 0% | - | - |
average_live_births_per_woman |
Average live births per woman | decimal | 0% | - | - |
average_surviving_children_per_woman |
Average surviving children per woman | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
male |
Male | decimal | 0% | - | - |
female |
Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
ethnic_group |
Ethnic group | string | CCL | 0% | - | - |
population |
Population | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
population |
Population | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
residents_of_the_hong_kong_sar_subtotal |
Residents of the Hong Kong SAR > Subtotal | decimal | 0% | - | - |
residents_of_the_hong_kong_sar_male |
Residents of the Hong Kong SAR > Male | decimal | 0% | - | - |
residents_of_the_hong_kong_sar_female |
Residents of the Hong Kong SAR > Female | decimal | 0% | - | - |
residents_of_the_macao_sar_subtotal |
Residents of the Macao SAR > Subtotal | decimal | 0% | - | - |
residents_of_the_macao_sar_male |
Residents of the Macao SAR > Male | decimal | 0% | - | - |
residents_of_the_macao_sar_female |
Residents of the Macao SAR > Female | decimal | 0% | - | - |
residents_of_the_taiwan_region_subtotal |
Residents of the Taiwan region > Subtotal | decimal | 0% | - | - |
residents_of_the_taiwan_region_male |
Residents of the Taiwan region > Male | decimal | 0% | - | - |
residents_of_the_taiwan_region_female |
Residents of the Taiwan region > Female | decimal | 0% | - | - |
foreign_nationals_subtotal |
Foreign nationals > Subtotal | decimal | 0% | - | - |
foreign_nationals_male |
Foreign nationals > Male | decimal | 0% | - | - |
foreign_nationals_female |
Foreign nationals > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
purpose_of_coming_to_the_mainland_or_to_china |
Purpose of coming to the mainland or to China | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
residents_of_the_hong_kong_sar |
Residents of the Hong Kong SAR | decimal | 0% | - | - |
residents_of_the_macao_sar |
Residents of the Macao SAR | decimal | 0% | - | - |
residents_of_the_taiwan_region |
Residents of the Taiwan region | decimal | 0% | - | - |
foreign_nationals |
Foreign nationals | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
duration_of_residence |
Duration of residence | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
residents_of_the_hong_kong_sar |
Residents of the Hong Kong SAR | decimal | 0% | - | - |
residents_of_the_macao_sar |
Residents of the Macao SAR | decimal | 0% | - | - |
residents_of_the_taiwan_region |
Residents of the Taiwan region | decimal | 0% | - | - |
foreign_nationals |
Foreign nationals | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
educational_attainment |
Educational attainment | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
residents_of_the_hong_kong_sar |
Residents of the Hong Kong SAR | decimal | 0% | - | - |
residents_of_the_macao_sar |
Residents of the Macao SAR | decimal | 0% | - | - |
residents_of_the_taiwan_region |
Residents of the Taiwan region | decimal | 0% | - | - |
foreign_nationals |
Foreign nationals | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
nationality |
Nationality | string | CCL | 0% | - | - |
population |
Population | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
region |
Region | string | SEL | 0% | - | - |
total |
Total | decimal | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
residents_of_the_hong_kong_sar |
Residents of the Hong Kong SAR | decimal | 0% | - | - |
residents_of_the_macao_sar |
Residents of the Macao SAR | decimal | 0% | - | - |
residents_of_the_taiwan_region |
Residents of the Taiwan region | decimal | 0% | - | - |
foreign_nationals |
Foreign nationals | decimal | 0% | - | - |
ⓘ 1-in-10 household sample. These tables come from the census long questionnaire, which about one household in ten answered. The National Bureau of Statistics publishes the sample's own counts without scaling them up, so counts here are about a tenth of the real figure: this sample counted 138,657,945 people, against 1,409,778,724 in the full count. Shares, rates and averages can be used as they are; for population totals use the full-count datasets.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_township |
Total > Township | decimal | 0% | - | - |
total_town_villagers_committee |
Total > Town - villagers' committee | decimal | 0% | - | - |
total_town_residents_committee |
Total > Town - residents' committee | decimal | 0% | - | - |
total_subdistrict |
Total > Subdistrict | decimal | 0% | - | - |
within_the_province_subtotal |
Within the province > Subtotal | decimal | 0% | - | - |
within_the_province_township |
Within the province > Township | decimal | 0% | - | - |
within_the_province_town_villagers_committee |
Within the province > Town - villagers' committee | decimal | 0% | - | - |
within_the_province_town_residents_committee |
Within the province > Town - residents' committee | decimal | 0% | - | - |
within_the_province_subdistrict |
Within the province > Subdistrict | decimal | 0% | - | - |
outside_the_province_subtotal_subtotal |
Outside the province > Subtotal > Subtotal | decimal | 0% | - | - |
outside_the_province_subtotal_township |
Outside the province > Subtotal > Township | decimal | 0% | - | - |
outside_the_province_subtotal_town_villagers_committee |
Outside the province > Subtotal > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_subtotal_town_residents_committee |
Outside the province > Subtotal > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_subtotal_subdistrict |
Outside the province > Subtotal > Subdistrict | decimal | 0% | - | - |
outside_the_province_beijing_subtotal |
Outside the province > Beijing > Subtotal | decimal | 0% | - | - |
outside_the_province_beijing_township |
Outside the province > Beijing > Township | decimal | 0% | - | - |
outside_the_province_beijing_town_villagers_committee |
Outside the province > Beijing > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_beijing_town_residents_committee |
Outside the province > Beijing > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_beijing_subdistrict |
Outside the province > Beijing > Subdistrict | decimal | 0% | - | - |
outside_the_province_tianjin_subtotal |
Outside the province > Tianjin > Subtotal | decimal | 0% | - | - |
outside_the_province_tianjin_township |
Outside the province > Tianjin > Township | decimal | 0% | - | - |
outside_the_province_tianjin_town_villagers_committee |
Outside the province > Tianjin > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_tianjin_town_residents_committee |
Outside the province > Tianjin > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_tianjin_subdistrict |
Outside the province > Tianjin > Subdistrict | decimal | 0% | - | - |
outside_the_province_hebei_subtotal |
Outside the province > Hebei > Subtotal | decimal | 0% | - | - |
outside_the_province_hebei_township |
Outside the province > Hebei > Township | decimal | 0% | - | - |
outside_the_province_hebei_town_villagers_committee |
Outside the province > Hebei > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_hebei_town_residents_committee |
Outside the province > Hebei > Town - residents' committee | decimal | 0% | - | - |
| +141 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_township |
Total > Township | decimal | 0% | - | - |
total_town_villagers_committee |
Total > Town - villagers' committee | decimal | 0% | - | - |
total_town_residents_committee |
Total > Town - residents' committee | decimal | 0% | - | - |
total_subdistrict |
Total > Subdistrict | decimal | 0% | - | - |
within_the_province_subtotal |
Within the province > Subtotal | decimal | 0% | - | - |
within_the_province_township |
Within the province > Township | decimal | 0% | - | - |
within_the_province_town_villagers_committee |
Within the province > Town - villagers' committee | decimal | 0% | - | - |
within_the_province_town_residents_committee |
Within the province > Town - residents' committee | decimal | 0% | - | - |
within_the_province_subdistrict |
Within the province > Subdistrict | decimal | 0% | - | - |
outside_the_province_subtotal_subtotal |
Outside the province > Subtotal > Subtotal | decimal | 0% | - | - |
outside_the_province_subtotal_township |
Outside the province > Subtotal > Township | decimal | 0% | - | - |
outside_the_province_subtotal_town_villagers_committee |
Outside the province > Subtotal > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_subtotal_town_residents_committee |
Outside the province > Subtotal > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_subtotal_subdistrict |
Outside the province > Subtotal > Subdistrict | decimal | 0% | - | - |
outside_the_province_beijing_subtotal |
Outside the province > Beijing > Subtotal | decimal | 0% | - | - |
outside_the_province_beijing_township |
Outside the province > Beijing > Township | decimal | 0% | - | - |
outside_the_province_beijing_town_villagers_committee |
Outside the province > Beijing > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_beijing_town_residents_committee |
Outside the province > Beijing > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_beijing_subdistrict |
Outside the province > Beijing > Subdistrict | decimal | 0% | - | - |
outside_the_province_tianjin_subtotal |
Outside the province > Tianjin > Subtotal | decimal | 0% | - | - |
outside_the_province_tianjin_township |
Outside the province > Tianjin > Township | decimal | 0% | - | - |
outside_the_province_tianjin_town_villagers_committee |
Outside the province > Tianjin > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_tianjin_town_residents_committee |
Outside the province > Tianjin > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_tianjin_subdistrict |
Outside the province > Tianjin > Subdistrict | decimal | 0% | - | - |
outside_the_province_hebei_subtotal |
Outside the province > Hebei > Subtotal | decimal | 0% | - | - |
outside_the_province_hebei_township |
Outside the province > Hebei > Township | decimal | 0% | - | - |
outside_the_province_hebei_town_villagers_committee |
Outside the province > Hebei > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_hebei_town_residents_committee |
Outside the province > Hebei > Town - residents' committee | decimal | 0% | - | - |
| +141 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_township |
Total > Township | decimal | 0% | - | - |
total_town_villagers_committee |
Total > Town - villagers' committee | decimal | 0% | - | - |
total_town_residents_committee |
Total > Town - residents' committee | decimal | 0% | - | - |
total_subdistrict |
Total > Subdistrict | decimal | 0% | - | - |
within_the_province_subtotal |
Within the province > Subtotal | decimal | 0% | - | - |
within_the_province_township |
Within the province > Township | decimal | 0% | - | - |
within_the_province_town_villagers_committee |
Within the province > Town - villagers' committee | decimal | 0% | - | - |
within_the_province_town_residents_committee |
Within the province > Town - residents' committee | decimal | 0% | - | - |
within_the_province_subdistrict |
Within the province > Subdistrict | decimal | 0% | - | - |
outside_the_province_subtotal_subtotal |
Outside the province > Subtotal > Subtotal | decimal | 0% | - | - |
outside_the_province_subtotal_township |
Outside the province > Subtotal > Township | decimal | 0% | - | - |
outside_the_province_subtotal_town_villagers_committee |
Outside the province > Subtotal > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_subtotal_town_residents_committee |
Outside the province > Subtotal > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_subtotal_subdistrict |
Outside the province > Subtotal > Subdistrict | decimal | 0% | - | - |
outside_the_province_beijing_subtotal |
Outside the province > Beijing > Subtotal | decimal | 0% | - | - |
outside_the_province_beijing_township |
Outside the province > Beijing > Township | decimal | 0% | - | - |
outside_the_province_beijing_town_villagers_committee |
Outside the province > Beijing > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_beijing_town_residents_committee |
Outside the province > Beijing > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_beijing_subdistrict |
Outside the province > Beijing > Subdistrict | decimal | 0% | - | - |
outside_the_province_tianjin_subtotal |
Outside the province > Tianjin > Subtotal | decimal | 0% | - | - |
outside_the_province_tianjin_township |
Outside the province > Tianjin > Township | decimal | 0% | - | - |
outside_the_province_tianjin_town_villagers_committee |
Outside the province > Tianjin > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_tianjin_town_residents_committee |
Outside the province > Tianjin > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_tianjin_subdistrict |
Outside the province > Tianjin > Subdistrict | decimal | 0% | - | - |
outside_the_province_hebei_subtotal |
Outside the province > Hebei > Subtotal | decimal | 0% | - | - |
outside_the_province_hebei_township |
Outside the province > Hebei > Township | decimal | 0% | - | - |
outside_the_province_hebei_town_villagers_committee |
Outside the province > Hebei > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_hebei_town_residents_committee |
Outside the province > Hebei > Town - residents' committee | decimal | 0% | - | - |
| +141 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_township |
Total > Township | decimal | 0% | - | - |
total_town_villagers_committee |
Total > Town - villagers' committee | decimal | 0% | - | - |
total_town_residents_committee |
Total > Town - residents' committee | decimal | 0% | - | - |
total_subdistrict |
Total > Subdistrict | decimal | 0% | - | - |
within_the_province_subtotal |
Within the province > Subtotal | decimal | 0% | - | - |
within_the_province_township |
Within the province > Township | decimal | 0% | - | - |
within_the_province_town_villagers_committee |
Within the province > Town - villagers' committee | decimal | 0% | - | - |
within_the_province_town_residents_committee |
Within the province > Town - residents' committee | decimal | 0% | - | - |
within_the_province_subdistrict |
Within the province > Subdistrict | decimal | 0% | - | - |
outside_the_province_subtotal_subtotal |
Outside the province > Subtotal > Subtotal | decimal | 0% | - | - |
outside_the_province_subtotal_township |
Outside the province > Subtotal > Township | decimal | 0% | - | - |
outside_the_province_subtotal_town_villagers_committee |
Outside the province > Subtotal > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_subtotal_town_residents_committee |
Outside the province > Subtotal > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_subtotal_subdistrict |
Outside the province > Subtotal > Subdistrict | decimal | 0% | - | - |
outside_the_province_beijing_subtotal |
Outside the province > Beijing > Subtotal | decimal | 0% | - | - |
outside_the_province_beijing_township |
Outside the province > Beijing > Township | decimal | 0% | - | - |
outside_the_province_beijing_town_villagers_committee |
Outside the province > Beijing > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_beijing_town_residents_committee |
Outside the province > Beijing > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_beijing_subdistrict |
Outside the province > Beijing > Subdistrict | decimal | 0% | - | - |
outside_the_province_tianjin_subtotal |
Outside the province > Tianjin > Subtotal | decimal | 0% | - | - |
outside_the_province_tianjin_township |
Outside the province > Tianjin > Township | decimal | 0% | - | - |
outside_the_province_tianjin_town_villagers_committee |
Outside the province > Tianjin > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_tianjin_town_residents_committee |
Outside the province > Tianjin > Town - residents' committee | decimal | 0% | - | - |
outside_the_province_tianjin_subdistrict |
Outside the province > Tianjin > Subdistrict | decimal | 0% | - | - |
outside_the_province_hebei_subtotal |
Outside the province > Hebei > Subtotal | decimal | 0% | - | - |
outside_the_province_hebei_township |
Outside the province > Hebei > Township | decimal | 0% | - | - |
outside_the_province_hebei_town_villagers_committee |
Outside the province > Hebei > Town - villagers' committee | decimal | 0% | - | - |
outside_the_province_hebei_town_residents_committee |
Outside the province > Hebei > Town - residents' committee | decimal | 0% | - | - |
| +141 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Male | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Female | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_male |
Professional and technical personnel > Male | decimal | 0% | - | - |
professional_and_technical_personnel_female |
Professional and technical personnel > Female | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_male |
Clerical staff and related personnel > Male | decimal | 0% | - | - |
clerical_staff_and_related_personnel_female |
Clerical staff and related personnel > Female | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_male |
Social production and living service personnel > Male | decimal | 0% | - | - |
social_production_and_living_service_personnel_female |
Social production and living service personnel > Female | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_producti |
Agriculture, forestry, animal husbandry and fishery production and support workers > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_producti_2 |
Agriculture, forestry, animal husbandry and fishery production and support workers > Male | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_producti_3 |
Agriculture, forestry, animal husbandry and fishery production and support workers > Female | decimal | 0% | - | - |
production_manufacturing_and_related_workers_subtotal |
Production, manufacturing and related workers > Subtotal | decimal | 0% | - | - |
production_manufacturing_and_related_workers_male |
Production, manufacturing and related workers > Male | decimal | 0% | - | - |
production_manufacturing_and_related_workers_female |
Production, manufacturing and related workers > Female | decimal | 0% | - | - |
other_employed_persons_not_elsewhere_classified_subtotal |
Other employed persons not elsewhere classified > Subtotal | decimal | 0% | - | - |
other_employed_persons_not_elsewhere_classified_male |
Other employed persons not elsewhere classified > Male | decimal | 0% | - | - |
other_employed_persons_not_elsewhere_classified_female |
Other employed persons not elsewhere classified > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Subtotal | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_2 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Male | decimal | 0% | - | - |
heads_of_party_organs_state_organs_mass_organizations_soci_3 |
Heads of Party organs, state organs, mass organizations, social organizations, enterprises and public institutions > Female | decimal | 0% | - | - |
professional_and_technical_personnel_subtotal |
Professional and technical personnel > Subtotal | decimal | 0% | - | - |
professional_and_technical_personnel_male |
Professional and technical personnel > Male | decimal | 0% | - | - |
professional_and_technical_personnel_female |
Professional and technical personnel > Female | decimal | 0% | - | - |
clerical_staff_and_related_personnel_subtotal |
Clerical staff and related personnel > Subtotal | decimal | 0% | - | - |
clerical_staff_and_related_personnel_male |
Clerical staff and related personnel > Male | decimal | 0% | - | - |
clerical_staff_and_related_personnel_female |
Clerical staff and related personnel > Female | decimal | 0% | - | - |
social_production_and_living_service_personnel_subtotal |
Social production and living service personnel > Subtotal | decimal | 0% | - | - |
social_production_and_living_service_personnel_male |
Social production and living service personnel > Male | decimal | 0% | - | - |
social_production_and_living_service_personnel_female |
Social production and living service personnel > Female | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_producti |
Agriculture, forestry, animal husbandry and fishery production and support workers > Subtotal | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_producti_2 |
Agriculture, forestry, animal husbandry and fishery production and support workers > Male | decimal | 0% | - | - |
agriculture_forestry_animal_husbandry_and_fishery_producti_3 |
Agriculture, forestry, animal husbandry and fishery production and support workers > Female | decimal | 0% | - | - |
production_manufacturing_and_related_workers_subtotal |
Production, manufacturing and related workers > Subtotal | decimal | 0% | - | - |
production_manufacturing_and_related_workers_male |
Production, manufacturing and related workers > Male | decimal | 0% | - | - |
production_manufacturing_and_related_workers_female |
Production, manufacturing and related workers > Female | decimal | 0% | - | - |
other_employed_persons_not_elsewhere_classified_subtotal |
Other employed persons not elsewhere classified > Subtotal | decimal | 0% | - | - |
other_employed_persons_not_elsewhere_classified_male |
Other employed persons not elsewhere classified > Male | decimal | 0% | - | - |
other_employed_persons_not_elsewhere_classified_female |
Other employed persons not elsewhere classified > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_township |
Total > Township | decimal | 0% | - | - |
total_town_villagers_committee |
Total > Town - villagers' committee | decimal | 0% | - | - |
total_town_residents_committee |
Total > Town - residents' committee | decimal | 0% | - | - |
total_subdistrict |
Total > Subdistrict | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_township |
Never attended school > Township | decimal | 0% | - | - |
never_attended_school_town_villagers_committee |
Never attended school > Town - villagers' committee | decimal | 0% | - | - |
never_attended_school_town_residents_committee |
Never attended school > Town - residents' committee | decimal | 0% | - | - |
never_attended_school_subdistrict |
Never attended school > Subdistrict | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_township |
Pre-school education > Township | decimal | 0% | - | - |
pre_school_education_town_villagers_committee |
Pre-school education > Town - villagers' committee | decimal | 0% | - | - |
pre_school_education_town_residents_committee |
Pre-school education > Town - residents' committee | decimal | 0% | - | - |
pre_school_education_subdistrict |
Pre-school education > Subdistrict | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_township |
Primary school > Township | decimal | 0% | - | - |
primary_school_town_villagers_committee |
Primary school > Town - villagers' committee | decimal | 0% | - | - |
primary_school_town_residents_committee |
Primary school > Town - residents' committee | decimal | 0% | - | - |
primary_school_subdistrict |
Primary school > Subdistrict | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_township |
Junior secondary school > Township | decimal | 0% | - | - |
junior_secondary_school_town_villagers_committee |
Junior secondary school > Town - villagers' committee | decimal | 0% | - | - |
junior_secondary_school_town_residents_committee |
Junior secondary school > Town - residents' committee | decimal | 0% | - | - |
junior_secondary_school_subdistrict |
Junior secondary school > Subdistrict | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_township |
Senior secondary school > Township | decimal | 0% | - | - |
senior_secondary_school_town_villagers_committee |
Senior secondary school > Town - villagers' committee | decimal | 0% | - | - |
senior_secondary_school_town_residents_committee |
Senior secondary school > Town - residents' committee | decimal | 0% | - | - |
| +21 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
total_total |
Total > Total | decimal | CCL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_township |
Total > Township | decimal | 0% | - | - |
total_town_villagers_committee |
Total > Town - villagers' committee | decimal | 0% | - | - |
total_town_residents_committee |
Total > Town - residents' committee | decimal | 0% | - | - |
total_subdistrict |
Total > Subdistrict | decimal | 0% | - | - |
never_attended_school_subtotal |
Never attended school > Subtotal | decimal | 0% | - | - |
never_attended_school_township |
Never attended school > Township | decimal | 0% | - | - |
never_attended_school_town_villagers_committee |
Never attended school > Town - villagers' committee | decimal | 0% | - | - |
never_attended_school_town_residents_committee |
Never attended school > Town - residents' committee | decimal | 0% | - | - |
never_attended_school_subdistrict |
Never attended school > Subdistrict | decimal | 0% | - | - |
pre_school_education_subtotal |
Pre-school education > Subtotal | decimal | 0% | - | - |
pre_school_education_township |
Pre-school education > Township | decimal | 0% | - | - |
pre_school_education_town_villagers_committee |
Pre-school education > Town - villagers' committee | decimal | 0% | - | - |
pre_school_education_town_residents_committee |
Pre-school education > Town - residents' committee | decimal | 0% | - | - |
pre_school_education_subdistrict |
Pre-school education > Subdistrict | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_township |
Primary school > Township | decimal | 0% | - | - |
primary_school_town_villagers_committee |
Primary school > Town - villagers' committee | decimal | 0% | - | - |
primary_school_town_residents_committee |
Primary school > Town - residents' committee | decimal | 0% | - | - |
primary_school_subdistrict |
Primary school > Subdistrict | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_township |
Junior secondary school > Township | decimal | 0% | - | - |
junior_secondary_school_town_villagers_committee |
Junior secondary school > Town - villagers' committee | decimal | 0% | - | - |
junior_secondary_school_town_residents_committee |
Junior secondary school > Town - residents' committee | decimal | 0% | - | - |
junior_secondary_school_subdistrict |
Junior secondary school > Subdistrict | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_township |
Senior secondary school > Township | decimal | 0% | - | - |
senior_secondary_school_town_villagers_committee |
Senior secondary school > Town - villagers' committee | decimal | 0% | - | - |
senior_secondary_school_town_residents_committee |
Senior secondary school > Town - residents' committee | decimal | 0% | - | - |
| +21 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_birth_total |
Place of birth > Total | decimal | 0% | - | - |
place_of_birth_within_the_province_same_county_city_distri |
Place of birth > Within the province > Same county (city, district) | decimal | 0% | - | - |
place_of_birth_within_the_province_other_county_city_distr |
Place of birth > Within the province > Other county (city, district) in the same province | decimal | 0% | - | - |
place_of_birth_outside_the_province_beijing |
Place of birth > Outside the province > Beijing | decimal | 0% | - | - |
place_of_birth_outside_the_province_tianjin |
Place of birth > Outside the province > Tianjin | decimal | 0% | - | - |
place_of_birth_outside_the_province_hebei |
Place of birth > Outside the province > Hebei | decimal | 0% | - | - |
place_of_birth_outside_the_province_shanxi |
Place of birth > Outside the province > Shanxi | decimal | 0% | - | - |
place_of_birth_outside_the_province_inner_mongolia |
Place of birth > Outside the province > Inner Mongolia | decimal | 0% | - | - |
place_of_birth_outside_the_province_liaoning |
Place of birth > Outside the province > Liaoning | decimal | 0% | - | - |
place_of_birth_outside_the_province_jilin |
Place of birth > Outside the province > Jilin | decimal | 0% | - | - |
place_of_birth_outside_the_province_heilongjiang |
Place of birth > Outside the province > Heilongjiang | decimal | 0% | - | - |
place_of_birth_outside_the_province_shanghai |
Place of birth > Outside the province > Shanghai | decimal | 0% | - | - |
place_of_birth_outside_the_province_jiangsu |
Place of birth > Outside the province > Jiangsu | decimal | 0% | - | - |
place_of_birth_outside_the_province_zhejiang |
Place of birth > Outside the province > Zhejiang | decimal | 0% | - | - |
place_of_birth_outside_the_province_anhui |
Place of birth > Outside the province > Anhui | decimal | 0% | - | - |
place_of_birth_outside_the_province_fujian |
Place of birth > Outside the province > Fujian | decimal | 0% | - | - |
place_of_birth_outside_the_province_jiangxi |
Place of birth > Outside the province > Jiangxi | decimal | 0% | - | - |
place_of_birth_outside_the_province_shandong |
Place of birth > Outside the province > Shandong | decimal | 0% | - | - |
place_of_birth_outside_the_province_henan |
Place of birth > Outside the province > Henan | decimal | 0% | - | - |
place_of_birth_outside_the_province_hubei |
Place of birth > Outside the province > Hubei | decimal | 0% | - | - |
place_of_birth_outside_the_province_hunan |
Place of birth > Outside the province > Hunan | decimal | 0% | - | - |
place_of_birth_outside_the_province_guangdong |
Place of birth > Outside the province > Guangdong | decimal | 0% | - | - |
place_of_birth_outside_the_province_guangxi |
Place of birth > Outside the province > Guangxi | decimal | 0% | - | - |
place_of_birth_outside_the_province_hainan |
Place of birth > Outside the province > Hainan | decimal | 0% | - | - |
place_of_birth_outside_the_province_chongqing |
Place of birth > Outside the province > Chongqing | decimal | 0% | - | - |
place_of_birth_outside_the_province_sichuan |
Place of birth > Outside the province > Sichuan | decimal | 0% | - | - |
place_of_birth_outside_the_province_guizhou |
Place of birth > Outside the province > Guizhou | decimal | 0% | - | - |
place_of_birth_outside_the_province_yunnan |
Place of birth > Outside the province > Yunnan | decimal | 0% | - | - |
| +7 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
place_of_current_residence |
Place of current residence | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 2 | 0, 1 |
admin_level_type |
Administrative level type | string | SEL | 0% | 2 | country, province |
admin_code |
Administrative unit code | string | SEL | 0% | 32 | 110000, 120000, 130000, 140000, 150000 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
place_of_usual_residence_five_years_ago_total |
Place of usual residence five years ago > Total | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_within_the_provinc |
Place of usual residence five years ago > Within the province > Same county (city, district) | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_within_the_provinc_2 |
Place of usual residence five years ago > Within the province > Other county (city, district) in the same province | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin |
Place of usual residence five years ago > Outside the province > Beijing | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_2 |
Place of usual residence five years ago > Outside the province > Tianjin | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_3 |
Place of usual residence five years ago > Outside the province > Hebei | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_4 |
Place of usual residence five years ago > Outside the province > Shanxi | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_5 |
Place of usual residence five years ago > Outside the province > Inner Mongolia | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_6 |
Place of usual residence five years ago > Outside the province > Liaoning | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_7 |
Place of usual residence five years ago > Outside the province > Jilin | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_8 |
Place of usual residence five years ago > Outside the province > Heilongjiang | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_9 |
Place of usual residence five years ago > Outside the province > Shanghai | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_10 |
Place of usual residence five years ago > Outside the province > Jiangsu | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_11 |
Place of usual residence five years ago > Outside the province > Zhejiang | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_12 |
Place of usual residence five years ago > Outside the province > Anhui | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_13 |
Place of usual residence five years ago > Outside the province > Fujian | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_14 |
Place of usual residence five years ago > Outside the province > Jiangxi | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_15 |
Place of usual residence five years ago > Outside the province > Shandong | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_16 |
Place of usual residence five years ago > Outside the province > Henan | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_17 |
Place of usual residence five years ago > Outside the province > Hubei | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_18 |
Place of usual residence five years ago > Outside the province > Hunan | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_19 |
Place of usual residence five years ago > Outside the province > Guangdong | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_20 |
Place of usual residence five years ago > Outside the province > Guangxi | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_21 |
Place of usual residence five years ago > Outside the province > Hainan | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_22 |
Place of usual residence five years ago > Outside the province > Chongqing | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_23 |
Place of usual residence five years ago > Outside the province > Sichuan | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_24 |
Place of usual residence five years ago > Outside the province > Guizhou | decimal | 0% | - | - |
place_of_usual_residence_five_years_ago_outside_the_provin_25 |
Place of usual residence five years ago > Outside the province > Yunnan | decimal | 0% | - | - |
| +7 more extension fields — download the CSV/Parquet to see them all. | |||||
ⓘ 1-in-10 household sample. These tables come from the census long questionnaire, which about one household in ten answered. The National Bureau of Statistics publishes the sample's own counts without scaling them up, so counts here are about a tenth of the real figure: this sample counted 138,657,945 people, against 1,409,778,724 in the full count. Shares, rates and averages can be used as they are; for population totals use the full-count datasets.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
school_attendance_and_completion_status |
School attendance and completion status | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
postgraduate_doctoral_female |
Postgraduate (Doctoral) > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
school_attendance_and_completion_status |
School attendance and completion status | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
postgraduate_doctoral_female |
Postgraduate (Doctoral) > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
school_attendance_and_completion_status |
School attendance and completion status | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
postgraduate_doctoral_female |
Postgraduate (Doctoral) > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
school_attendance_and_completion_status |
School attendance and completion status | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total |
Total > Total | decimal | 0% | - | - |
total_male |
Total > Male | decimal | 0% | - | - |
total_female |
Total > Female | decimal | 0% | - | - |
primary_school_subtotal |
Primary school > Subtotal | decimal | 0% | - | - |
primary_school_male |
Primary school > Male | decimal | 0% | - | - |
primary_school_female |
Primary school > Female | decimal | 0% | - | - |
junior_secondary_school_subtotal |
Junior secondary school > Subtotal | decimal | 0% | - | - |
junior_secondary_school_male |
Junior secondary school > Male | decimal | 0% | - | - |
junior_secondary_school_female |
Junior secondary school > Female | decimal | 0% | - | - |
senior_secondary_school_subtotal |
Senior secondary school > Subtotal | decimal | 0% | - | - |
senior_secondary_school_male |
Senior secondary school > Male | decimal | 0% | - | - |
senior_secondary_school_female |
Senior secondary school > Female | decimal | 0% | - | - |
junior_college_subtotal |
Junior college > Subtotal | decimal | 0% | - | - |
junior_college_male |
Junior college > Male | decimal | 0% | - | - |
junior_college_female |
Junior college > Female | decimal | 0% | - | - |
university_undergraduate_subtotal |
University (undergraduate) > Subtotal | decimal | 0% | - | - |
university_undergraduate_male |
University (undergraduate) > Male | decimal | 0% | - | - |
university_undergraduate_female |
University (undergraduate) > Female | decimal | 0% | - | - |
postgraduate_master_s_subtotal |
Postgraduate (Master's) > Subtotal | decimal | 0% | - | - |
postgraduate_master_s_male |
Postgraduate (Master's) > Male | decimal | 0% | - | - |
postgraduate_master_s_female |
Postgraduate (Master's) > Female | decimal | 0% | - | - |
postgraduate_doctoral_subtotal |
Postgraduate (Doctoral) > Subtotal | decimal | 0% | - | - |
postgraduate_doctoral_male |
Postgraduate (Doctoral) > Male | decimal | 0% | - | - |
postgraduate_doctoral_female |
Postgraduate (Doctoral) > Female | decimal | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total_total |
Total > Total > Total | decimal | 0% | - | - |
total_total_male |
Total > Total > Male | decimal | 0% | - | - |
total_total_female |
Total > Total > Female | decimal | 0% | - | - |
total_currently_enrolled_subtotal |
Total > Currently enrolled > Subtotal | decimal | 0% | - | - |
total_currently_enrolled_male |
Total > Currently enrolled > Male | decimal | 0% | - | - |
total_currently_enrolled_female |
Total > Currently enrolled > Female | decimal | 0% | - | - |
total_graduated_subtotal |
Total > Graduated > Subtotal | decimal | 0% | - | - |
total_graduated_male |
Total > Graduated > Male | decimal | 0% | - | - |
total_graduated_female |
Total > Graduated > Female | decimal | 0% | - | - |
total_left_without_graduating_subtotal |
Total > Left without graduating > Subtotal | decimal | 0% | - | - |
total_left_without_graduating_male |
Total > Left without graduating > Male | decimal | 0% | - | - |
total_left_without_graduating_female |
Total > Left without graduating > Female | decimal | 0% | - | - |
total_dropped_out_subtotal |
Total > Dropped out > Subtotal | decimal | 0% | - | - |
total_dropped_out_male |
Total > Dropped out > Male | decimal | 0% | - | - |
total_dropped_out_female |
Total > Dropped out > Female | decimal | 0% | - | - |
total_other_subtotal |
Total > Other > Subtotal | decimal | 0% | - | - |
total_other_male |
Total > Other > Male | decimal | 0% | - | - |
total_other_female |
Total > Other > Female | decimal | 0% | - | - |
primary_school_total_total |
Primary school > Total > Total | decimal | 0% | - | - |
primary_school_total_male |
Primary school > Total > Male | decimal | 0% | - | - |
primary_school_total_female |
Primary school > Total > Female | decimal | 0% | - | - |
primary_school_currently_enrolled_subtotal |
Primary school > Currently enrolled > Subtotal | decimal | 0% | - | - |
primary_school_currently_enrolled_male |
Primary school > Currently enrolled > Male | decimal | 0% | - | - |
primary_school_currently_enrolled_female |
Primary school > Currently enrolled > Female | decimal | 0% | - | - |
primary_school_graduated_subtotal |
Primary school > Graduated > Subtotal | decimal | 0% | - | - |
primary_school_graduated_male |
Primary school > Graduated > Male | decimal | 0% | - | - |
primary_school_graduated_female |
Primary school > Graduated > Female | decimal | 0% | - | - |
primary_school_left_without_graduating_subtotal |
Primary school > Left without graduating > Subtotal | decimal | 0% | - | - |
| +116 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total_total |
Total > Total > Total | decimal | 0% | - | - |
total_total_male |
Total > Total > Male | decimal | 0% | - | - |
total_total_female |
Total > Total > Female | decimal | 0% | - | - |
total_currently_enrolled_subtotal |
Total > Currently enrolled > Subtotal | decimal | 0% | - | - |
total_currently_enrolled_male |
Total > Currently enrolled > Male | decimal | 0% | - | - |
total_currently_enrolled_female |
Total > Currently enrolled > Female | decimal | 0% | - | - |
total_graduated_subtotal |
Total > Graduated > Subtotal | decimal | 0% | - | - |
total_graduated_male |
Total > Graduated > Male | decimal | 0% | - | - |
total_graduated_female |
Total > Graduated > Female | decimal | 0% | - | - |
total_left_without_graduating_subtotal |
Total > Left without graduating > Subtotal | decimal | 0% | - | - |
total_left_without_graduating_male |
Total > Left without graduating > Male | decimal | 0% | - | - |
total_left_without_graduating_female |
Total > Left without graduating > Female | decimal | 0% | - | - |
total_dropped_out_subtotal |
Total > Dropped out > Subtotal | decimal | 0% | - | - |
total_dropped_out_male |
Total > Dropped out > Male | decimal | 0% | - | - |
total_dropped_out_female |
Total > Dropped out > Female | decimal | 0% | - | - |
total_other_subtotal |
Total > Other > Subtotal | decimal | 0% | - | - |
total_other_male |
Total > Other > Male | decimal | 0% | - | - |
total_other_female |
Total > Other > Female | decimal | 0% | - | - |
primary_school_total_total |
Primary school > Total > Total | decimal | 0% | - | - |
primary_school_total_male |
Primary school > Total > Male | decimal | 0% | - | - |
primary_school_total_female |
Primary school > Total > Female | decimal | 0% | - | - |
primary_school_currently_enrolled_subtotal |
Primary school > Currently enrolled > Subtotal | decimal | 0% | - | - |
primary_school_currently_enrolled_male |
Primary school > Currently enrolled > Male | decimal | 0% | - | - |
primary_school_currently_enrolled_female |
Primary school > Currently enrolled > Female | decimal | 0% | - | - |
primary_school_graduated_subtotal |
Primary school > Graduated > Subtotal | decimal | 0% | - | - |
primary_school_graduated_male |
Primary school > Graduated > Male | decimal | 0% | - | - |
primary_school_graduated_female |
Primary school > Graduated > Female | decimal | 0% | - | - |
primary_school_left_without_graduating_subtotal |
Primary school > Left without graduating > Subtotal | decimal | 0% | - | - |
| +116 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total_total |
Total > Total > Total | decimal | 0% | - | - |
total_total_male |
Total > Total > Male | decimal | 0% | - | - |
total_total_female |
Total > Total > Female | decimal | 0% | - | - |
total_currently_enrolled_subtotal |
Total > Currently enrolled > Subtotal | decimal | 0% | - | - |
total_currently_enrolled_male |
Total > Currently enrolled > Male | decimal | 0% | - | - |
total_currently_enrolled_female |
Total > Currently enrolled > Female | decimal | 0% | - | - |
total_graduated_subtotal |
Total > Graduated > Subtotal | decimal | 0% | - | - |
total_graduated_male |
Total > Graduated > Male | decimal | 0% | - | - |
total_graduated_female |
Total > Graduated > Female | decimal | 0% | - | - |
total_left_without_graduating_subtotal |
Total > Left without graduating > Subtotal | decimal | 0% | - | - |
total_left_without_graduating_male |
Total > Left without graduating > Male | decimal | 0% | - | - |
total_left_without_graduating_female |
Total > Left without graduating > Female | decimal | 0% | - | - |
total_dropped_out_subtotal |
Total > Dropped out > Subtotal | decimal | 0% | - | - |
total_dropped_out_male |
Total > Dropped out > Male | decimal | 0% | - | - |
total_dropped_out_female |
Total > Dropped out > Female | decimal | 0% | - | - |
total_other_subtotal |
Total > Other > Subtotal | decimal | 0% | - | - |
total_other_male |
Total > Other > Male | decimal | 0% | - | - |
total_other_female |
Total > Other > Female | decimal | 0% | - | - |
primary_school_total_total |
Primary school > Total > Total | decimal | 0% | - | - |
primary_school_total_male |
Primary school > Total > Male | decimal | 0% | - | - |
primary_school_total_female |
Primary school > Total > Female | decimal | 0% | - | - |
primary_school_currently_enrolled_subtotal |
Primary school > Currently enrolled > Subtotal | decimal | 0% | - | - |
primary_school_currently_enrolled_male |
Primary school > Currently enrolled > Male | decimal | 0% | - | - |
primary_school_currently_enrolled_female |
Primary school > Currently enrolled > Female | decimal | 0% | - | - |
primary_school_graduated_subtotal |
Primary school > Graduated > Subtotal | decimal | 0% | - | - |
primary_school_graduated_male |
Primary school > Graduated > Male | decimal | 0% | - | - |
primary_school_graduated_female |
Primary school > Graduated > Female | decimal | 0% | - | - |
primary_school_left_without_graduating_subtotal |
Primary school > Left without graduating > Subtotal | decimal | 0% | - | - |
| +116 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
age |
Age | string | SEL | 0% | - | - |
admin_level |
Administrative level | integer | SEL | 0% | 1 | 0 |
admin_level_type |
Administrative level type | string | SEL | 0% | 1 | country |
admin_code |
Administrative unit code | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
section |
Section | string | 0% | - | - |
row_type |
Row type | string | 0% | - | - |
total_total_total |
Total > Total > Total | decimal | 0% | - | - |
total_total_male |
Total > Total > Male | decimal | 0% | - | - |
total_total_female |
Total > Total > Female | decimal | 0% | - | - |
total_currently_enrolled_subtotal |
Total > Currently enrolled > Subtotal | decimal | 0% | - | - |
total_currently_enrolled_male |
Total > Currently enrolled > Male | decimal | 0% | - | - |
total_currently_enrolled_female |
Total > Currently enrolled > Female | decimal | 0% | - | - |
total_graduated_subtotal |
Total > Graduated > Subtotal | decimal | 0% | - | - |
total_graduated_male |
Total > Graduated > Male | decimal | 0% | - | - |
total_graduated_female |
Total > Graduated > Female | decimal | 0% | - | - |
total_left_without_graduating_subtotal |
Total > Left without graduating > Subtotal | decimal | 0% | - | - |
total_left_without_graduating_male |
Total > Left without graduating > Male | decimal | 0% | - | - |
total_left_without_graduating_female |
Total > Left without graduating > Female | decimal | 0% | - | - |
total_dropped_out_subtotal |
Total > Dropped out > Subtotal | decimal | 0% | - | - |
total_dropped_out_male |
Total > Dropped out > Male | decimal | 0% | - | - |
total_dropped_out_female |
Total > Dropped out > Female | decimal | 0% | - | - |
total_other_subtotal |
Total > Other > Subtotal | decimal | 0% | - | - |
total_other_male |
Total > Other > Male | decimal | 0% | - | - |
total_other_female |
Total > Other > Female | decimal | 0% | - | - |
primary_school_total_total |
Primary school > Total > Total | decimal | 0% | - | - |
primary_school_total_male |
Primary school > Total > Male | decimal | 0% | - | - |
primary_school_total_female |
Primary school > Total > Female | decimal | 0% | - | - |
primary_school_currently_enrolled_subtotal |
Primary school > Currently enrolled > Subtotal | decimal | 0% | - | - |
primary_school_currently_enrolled_male |
Primary school > Currently enrolled > Male | decimal | 0% | - | - |
primary_school_currently_enrolled_female |
Primary school > Currently enrolled > Female | decimal | 0% | - | - |
primary_school_graduated_subtotal |
Primary school > Graduated > Subtotal | decimal | 0% | - | - |
primary_school_graduated_male |
Primary school > Graduated > Male | decimal | 0% | - | - |
primary_school_graduated_female |
Primary school > Graduated > Female | decimal | 0% | - | - |
primary_school_left_without_graduating_subtotal |
Primary school > Left without graduating > Subtotal | decimal | 0% | - | - |
| +116 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
Fertilizer_consumption_pct_of_fertilizer_production |
Fertilizer_consumption_pct_of_fertilizer_production | float | 0% | 1 | 92.0312777126008 |
Fertilizer_consumption_kilograms_per_hectare_of_arable_land |
Fertilizer_consumption_kilograms_per_hectare_of_arable_land | float | 0% | 1 | 394.019742296898 |
Agricultural_land_sq._km |
Agricultural_land_sq._km | float | 0% | 1 | 5204130.0 |
Agricultural_land_pct_of_land_area |
Agricultural_land_pct_of_land_area | float | 0% | 1 | 55.4326117545304 |
Arable_land_hectares |
Arable_land_hectares | float | 0% | 1 | 108427100.0 |
Arable_land_hectares_per_person |
Arable_land_hectares_per_person | float | 0% | 1 | 0.0768599499542783 |
Arable_land_pct_of_land_area |
Arable_land_pct_of_land_area | float | 0% | 1 | 11.5492836227566 |
Land_under_cereal_production_hectares |
Land_under_cereal_production_hectares | float | 0% | 1 | 99987255.0 |
Permanent_cropland_pct_of_land_area |
Permanent_cropland_pct_of_land_area | float | 0% | 1 | 2.04010136117535 |
Rural_land_area_where_elevation_is_below_5_meters_sq._km |
Rural_land_area_where_elevation_is_below_5_meters_sq._km | float | 0% | 1 | 42639.9398719 |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area | float | 0% | 1 | 0.461168344660781 |
Forest_area_sq._km |
Forest_area_sq._km | float | 0% | 1 | 2256168.9 |
Forest_area_pct_of_land_area |
Forest_area_pct_of_land_area | float | 0% | 1 | 24.0319389958256 |
Average_precipitation_in_depth_mm_per_year |
Average_precipitation_in_depth_mm_per_year | float | 0% | 1 | 645.0 |
Land_area_sq._km |
Land_area_sq._km | float | 0% | 1 | 9388210.0 |
Rural_land_area_sq._km |
Rural_land_area_sq._km | float | 0% | 1 | 8723723.0597445 |
Cereal_production_metric_tons |
Cereal_production_metric_tons | float | 0% | 1 | 641731705.88 |
Crop_production_index_2014-2016_=_100 |
Crop_production_index_2014-2016_=_100 | float | 0% | 1 | 111.85 |
Food_production_index_2014-2016_=_100 |
Food_production_index_2014-2016_=_100 | float | 0% | 1 | 111.75 |
Livestock_production_index_2014-2016_=_100 |
Livestock_production_index_2014-2016_=_100 | float | 0% | 1 | 109.5 |
Surface_area_sq._km |
Surface_area_sq._km | float | 0% | 1 | 9562910.0 |
Cereal_yield_kg_per_hectare |
Cereal_yield_kg_per_hectare | float | 0% | 1 | 6418.1 |
Access_to_electricity_rural_pct_of_rural_population |
Access_to_electricity_rural_pct_of_rural_population | float | 0% | 1 | 100.0 |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ | float | 0% | 1 | 0.525493494671787 |
Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal |
Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal | float | 0% | 1 | 62.14454059 |
Agriculture_forestry_and_fishing_value_added_current_USusd |
Agriculture_forestry_and_fishing_value_added_current_USusd | float | 0% | 1 | 1270079880349.97 |
Agriculture_forestry_and_fishing_value_added_pct_of_GDP |
Agriculture_forestry_and_fishing_value_added_pct_of_GDP | float | 0% | 1 | 6.77599881291286 |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 18.6826526976472 |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate | float | 0% | 1 | 24.1934332847983 |
| +2703 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
Fertilizer_consumption_kilograms_per_hectare_of_arable_land |
Fertilizer_consumption_kilograms_per_hectare_of_arable_land | float | 0% | 1 | 484.0 |
Agricultural_land_sq._km |
Agricultural_land_sq._km | float | 0% | 1 | 40.0 |
Agricultural_land_pct_of_land_area |
Agricultural_land_pct_of_land_area | float | 0% | 1 | 3.80952380952381 |
Arable_land_hectares |
Arable_land_hectares | float | 0% | 1 | 2000.0 |
Arable_land_hectares_per_person |
Arable_land_hectares_per_person | float | 0% | 1 | 0.00026538925969666 |
Arable_land_pct_of_land_area |
Arable_land_pct_of_land_area | float | 0% | 1 | 1.9047619047619 |
Land_under_cereal_production_hectares |
Land_under_cereal_production_hectares | float | 0% | 1 | 0.0 |
Permanent_cropland_pct_of_land_area |
Permanent_cropland_pct_of_land_area | float | 0% | 1 | 0.952380952380952 |
Rural_land_area_where_elevation_is_below_5_meters_sq._km |
Rural_land_area_where_elevation_is_below_5_meters_sq._km | float | 0% | 1 | 74.9537466205 |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area | float | 0% | 1 | 6.76533067761933 |
Land_area_sq._km |
Land_area_sq._km | float | 0% | 1 | 1050.0 |
Rural_land_area_sq._km |
Rural_land_area_sq._km | float | 0% | 1 | 591.19585189281 |
Cereal_production_metric_tons |
Cereal_production_metric_tons | float | 0% | 1 | 0.06 |
Crop_production_index_2014-2016_=_100 |
Crop_production_index_2014-2016_=_100 | float | 0% | 1 | 101.49 |
Food_production_index_2014-2016_=_100 |
Food_production_index_2014-2016_=_100 | float | 0% | 1 | 141.66 |
Livestock_production_index_2014-2016_=_100 |
Livestock_production_index_2014-2016_=_100 | float | 0% | 1 | 149.97 |
Surface_area_sq._km |
Surface_area_sq._km | float | 0% | 1 | 1110.0 |
Cereal_yield_kg_per_hectare |
Cereal_yield_kg_per_hectare | float | 0% | 1 | 2059.0 |
Access_to_electricity_rural_pct_of_rural_population |
Access_to_electricity_rural_pct_of_rural_population | float | 0% | 1 | 100.0 |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ | float | 0% | 1 | 0.555621452880751 |
Agriculture_forestry_and_fishing_value_added_current_USusd |
Agriculture_forestry_and_fishing_value_added_current_USusd | float | 0% | 1 | 152361025.665208 |
Agriculture_forestry_and_fishing_value_added_pct_of_GDP |
Agriculture_forestry_and_fishing_value_added_pct_of_GDP | float | 0% | 1 | 0.0374477102095245 |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 0.104659514309261 |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate | float | 0% | 1 | 0.264712552443588 |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate | float | 0% | 1 | 0.182377495822408 |
Rural_population |
Rural_population | float | 0% | 1 | 0.0 |
Rural_population_growth_annual_pct |
Rural_population_growth_annual_pct | float | 0% | 1 | -172.328531479259 |
Rural_population_pct_of_total_population |
Rural_population_pct_of_total_population | float | 0% | 1 | 0.0 |
Agricultural_raw_materials_imports_pct_of_merchandise_imports |
Agricultural_raw_materials_imports_pct_of_merchandise_imports | float | 0% | 1 | 0.0913335982064106 |
| +1709 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
Rural_land_area_where_elevation_is_below_5_meters_sq._km |
Rural_land_area_where_elevation_is_below_5_meters_sq._km | float | 0% | 1 | 3.57163106359 |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area | float | 0% | 1 | 14.095617461755 |
Land_area_sq._km |
Land_area_sq._km | float | 0% | 1 | 33.0 |
Rural_land_area_sq._km |
Rural_land_area_sq._km | float | 0% | 1 | 7.5741654768354 |
Crop_production_index_2014-2016_=_100 |
Crop_production_index_2014-2016_=_100 | float | 0% | 1 | 103.18 |
Food_production_index_2014-2016_=_100 |
Food_production_index_2014-2016_=_100 | float | 0% | 1 | 81.34 |
Livestock_production_index_2014-2016_=_100 |
Livestock_production_index_2014-2016_=_100 | float | 0% | 1 | 73.39 |
Surface_area_sq._km |
Surface_area_sq._km | float | 0% | 1 | 33.0 |
Access_to_electricity_rural_pct_of_rural_population |
Access_to_electricity_rural_pct_of_rural_population | float | 0% | 1 | 100.0 |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ | float | 0% | 1 | 0.772778435373717 |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 0.33160896670646 |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate | float | 0% | 1 | 0.417951590992474 |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate | float | 0% | 1 | 0.373797814869546 |
Rural_population |
Rural_population | float | 0% | 1 | 0.0 |
Rural_population_growth_annual_pct |
Rural_population_growth_annual_pct | float | 0% | 1 | -120.397280432594 |
Rural_population_pct_of_total_population |
Rural_population_pct_of_total_population | float | 0% | 1 | 0.0 |
Agricultural_raw_materials_imports_pct_of_merchandise_imports |
Agricultural_raw_materials_imports_pct_of_merchandise_imports | float | 0% | 1 | 0.142749528079388 |
Agricultural_raw_materials_exports_pct_of_merchandise_exports |
Agricultural_raw_materials_exports_pct_of_merchandise_exports | float | 0% | 1 | 0.408785558205904 |
Grants_excluding_technical_cooperation_BoP_current_USusd |
Grants_excluding_technical_cooperation_BoP_current_USusd | float | 0% | 1 | 0.0 |
Technical_cooperation_grants_BoP_current_USusd |
Technical_cooperation_grants_BoP_current_USusd | float | 0% | 1 | 320000.0 |
Net_bilateral_aid_flows_from_DAC_donors_Australia_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Australia_current_USusd | float | 0% | 1 | 9999.99977648258 |
Net_bilateral_aid_flows_from_DAC_donors_European_Union_institutions_current_USus |
Net_bilateral_aid_flows_from_DAC_donors_European_Union_institutions_current_USus | float | 0% | 1 | 360000.014305115 |
Net_bilateral_aid_flows_from_DAC_donors_Switzerland_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Switzerland_current_USusd | float | 0% | 1 | 9999.99977648258 |
Net_bilateral_aid_flows_from_DAC_donors_Germany_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Germany_current_USusd | float | 0% | 1 | 19999.9995529652 |
Net_bilateral_aid_flows_from_DAC_donors_France_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_France_current_USusd | float | 0% | 1 | 9999.99977648258 |
Net_bilateral_aid_flows_from_DAC_donors_Japan_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Japan_current_USusd | float | 0% | 1 | 209999.993443489 |
Net_bilateral_aid_flows_from_DAC_donors_Netherlands_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Netherlands_current_USusd | float | 0% | 1 | 70000.0002980232 |
Net_bilateral_aid_flows_from_DAC_donors_Norway_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Norway_current_USusd | float | 0% | 1 | 50000.0007450581 |
Net_bilateral_aid_flows_from_DAC_donors_Portugal_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Portugal_current_USusd | float | 0% | 1 | 70000.0002980232 |
| +1588 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
GHO (CODE) |
GHO (CODE) | string | 0% | 67 | AIR_35, AIR_90, MORT_100,... |
GHO (DISPLAY) |
GHO (DISPLAY) | string | 0% | 67 | Joint effects of air pollution attributable deaths,... |
GHO (URL) |
GHO (URL) | string | 0% | 67 | https://www.who.int/data/gho/data/indicators/indicator-de... |
YEAR (DISPLAY) |
YEAR (DISPLAY) | string | 0% | 36 | 2018, 2016, 2005, 2002, 1988 |
STARTYEAR |
STARTYEAR | string | 0% | 36 | 2018, 2016, 2005, 2002, 1988 |
ENDYEAR |
ENDYEAR | string | 0% | 36 | 2018, 2016, 2005, 2002, 1988 |
REGION (CODE) |
REGION (CODE) | string | 0% | 1 | WPR, WPR, WPR, WPR, WPR |
REGION (DISPLAY) |
REGION (DISPLAY) | string | 0% | 1 | Western Pacific, Western Pacific, Western Pacific,... |
COUNTRY (CODE) |
COUNTRY (CODE) | string | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
COUNTRY (DISPLAY) |
COUNTRY (DISPLAY) | string | 0% | 1 | China, China, China, China, China |
DIMENSION (TYPE) |
DIMENSION (TYPE) | string | 16% | 12 | SEX, SEX, SEX, RESIDENCEAREATYPE, SEX |
DIMENSION (CODE) |
DIMENSION (CODE) | string | 16% | 29 | SEX_MLE, SEX_FMLE, SEX_BTSX, RESIDENCEAREATYPE_TOTL, SEX_MLE |
DIMENSION (NAME) |
DIMENSION (NAME) | string | 16% | 27 | Male, Female, Both sexes, Total, Male |
Numeric |
Numeric | string | 14% | 77 | 44691.668, 348.371, 1267.40388, 57.2, 45.36125162 |
Value |
Value | string | 0% | 85 | 44 692 [34 228-56 945], 348 [243-439], 1267.4, 57.2 [43... |
Low |
Low | float | 51% | 44 | 34228.413, 243.092, 43.0, 40.960643219, 0.0 |
High |
High | float | 51% | 49 | 56944.818, 438.831, 71.5, 50.232530613, 5.8 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education | float | 0% | 1 | 0.0 |
Barro-Lee:_Percentage_of_population_age_15-19_with_no_education |
Barro-Lee:_Percentage_of_population_age_15-19_with_no_education | float | 0% | 1 | 0.0 |
Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education | float | 0% | 1 | 7.54 |
Barro-Lee:_Percentage_of_population_age_15+_with_no_education |
Barro-Lee:_Percentage_of_population_age_15+_with_no_education | float | 0% | 1 | 5.38 |
Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education | float | 0% | 1 | 0.0 |
Barro-Lee:_Percentage_of_population_age_20-24_with_no_education |
Barro-Lee:_Percentage_of_population_age_20-24_with_no_education | float | 0% | 1 | 0.0 |
Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education | float | 0% | 1 | 0.0 |
Barro-Lee:_Percentage_of_population_age_25-29_with_no_education |
Barro-Lee:_Percentage_of_population_age_25-29_with_no_education | float | 0% | 1 | 0.11 |
Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education | float | 0% | 1 | 8.71 |
Barro-Lee:_Percentage_of_population_age_25+_with_no_education |
Barro-Lee:_Percentage_of_population_age_25+_with_no_education | float | 0% | 1 | 6.28 |
Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education | float | 0% | 1 | 0.31 |
Barro-Lee:_Percentage_of_population_age_30-34_with_no_education |
Barro-Lee:_Percentage_of_population_age_30-34_with_no_education | float | 0% | 1 | 0.22 |
Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education | float | 0% | 1 | 0.59 |
Barro-Lee:_Percentage_of_population_age_35-39_with_no_education |
Barro-Lee:_Percentage_of_population_age_35-39_with_no_education | float | 0% | 1 | 0.45 |
Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education | float | 0% | 1 | 0.59 |
Barro-Lee:_Percentage_of_population_age_40-44_with_no_education |
Barro-Lee:_Percentage_of_population_age_40-44_with_no_education | float | 0% | 1 | 0.45 |
Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education | float | 0% | 1 | 2.25 |
Barro-Lee:_Percentage_of_population_age_45-49_with_no_education |
Barro-Lee:_Percentage_of_population_age_45-49_with_no_education | float | 0% | 1 | 1.49 |
Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education | float | 0% | 1 | 2.25 |
Barro-Lee:_Percentage_of_population_age_50-54_with_no_education |
Barro-Lee:_Percentage_of_population_age_50-54_with_no_education | float | 0% | 1 | 1.49 |
Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education | float | 0% | 1 | 8.06 |
Barro-Lee:_Percentage_of_population_age_55-59_with_no_education |
Barro-Lee:_Percentage_of_population_age_55-59_with_no_education | float | 0% | 1 | 5.39 |
Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education | float | 0% | 1 | 8.06 |
Barro-Lee:_Percentage_of_population_age_60-64_with_no_education |
Barro-Lee:_Percentage_of_population_age_60-64_with_no_education | float | 0% | 1 | 5.39 |
Barro-Lee:_Population_in_thousands_age_15-19_total |
Barro-Lee:_Population_in_thousands_age_15-19_total | float | 0% | 1 | 401.0 |
Barro-Lee:_Population_in_thousands_age_15-19_female |
Barro-Lee:_Population_in_thousands_age_15-19_female | float | 0% | 1 | 200.0 |
Barro-Lee:_Population_in_thousands_age_15+_total |
Barro-Lee:_Population_in_thousands_age_15+_total | float | 0% | 1 | 6429.0 |
Barro-Lee:_Population_in_thousands_age_15+_female |
Barro-Lee:_Population_in_thousands_age_15+_female | float | 0% | 1 | 3451.0 |
Barro-Lee:_Population_in_thousands_age_20-24_total |
Barro-Lee:_Population_in_thousands_age_20-24_total | float | 0% | 1 | 450.0 |
| +807 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education | float | 0% | 1 | 0.14 |
Barro-Lee:_Percentage_of_population_age_15-19_with_no_education |
Barro-Lee:_Percentage_of_population_age_15-19_with_no_education | float | 0% | 1 | 0.12 |
Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education | float | 0% | 1 | 4.43 |
Barro-Lee:_Percentage_of_population_age_15+_with_no_education |
Barro-Lee:_Percentage_of_population_age_15+_with_no_education | float | 0% | 1 | 3.46 |
Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education | float | 0% | 1 | 2.98 |
Barro-Lee:_Percentage_of_population_age_20-24_with_no_education |
Barro-Lee:_Percentage_of_population_age_20-24_with_no_education | float | 0% | 1 | 4.44 |
Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education | float | 0% | 1 | 0.18 |
Barro-Lee:_Percentage_of_population_age_25-29_with_no_education |
Barro-Lee:_Percentage_of_population_age_25-29_with_no_education | float | 0% | 1 | 0.11 |
Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education | float | 0% | 1 | 5.13 |
Barro-Lee:_Percentage_of_population_age_25+_with_no_education |
Barro-Lee:_Percentage_of_population_age_25+_with_no_education | float | 0% | 1 | 3.75 |
Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education | float | 0% | 1 | 0.13 |
Barro-Lee:_Percentage_of_population_age_30-34_with_no_education |
Barro-Lee:_Percentage_of_population_age_30-34_with_no_education | float | 0% | 1 | 0.15 |
Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education | float | 0% | 1 | 0.57 |
Barro-Lee:_Percentage_of_population_age_35-39_with_no_education |
Barro-Lee:_Percentage_of_population_age_35-39_with_no_education | float | 0% | 1 | 0.58 |
Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education | float | 0% | 1 | 0.93 |
Barro-Lee:_Percentage_of_population_age_40-44_with_no_education |
Barro-Lee:_Percentage_of_population_age_40-44_with_no_education | float | 0% | 1 | 0.75 |
Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education | float | 0% | 1 | 1.31 |
Barro-Lee:_Percentage_of_population_age_45-49_with_no_education |
Barro-Lee:_Percentage_of_population_age_45-49_with_no_education | float | 0% | 1 | 1.04 |
Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education | float | 0% | 1 | 4.32 |
Barro-Lee:_Percentage_of_population_age_50-54_with_no_education |
Barro-Lee:_Percentage_of_population_age_50-54_with_no_education | float | 0% | 1 | 2.87 |
Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education | float | 0% | 1 | 5.45 |
Barro-Lee:_Percentage_of_population_age_55-59_with_no_education |
Barro-Lee:_Percentage_of_population_age_55-59_with_no_education | float | 0% | 1 | 3.7 |
Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education | float | 0% | 1 | 10.04 |
Barro-Lee:_Percentage_of_population_age_60-64_with_no_education |
Barro-Lee:_Percentage_of_population_age_60-64_with_no_education | float | 0% | 1 | 6.61 |
Barro-Lee:_Population_in_thousands_age_15-19_total |
Barro-Lee:_Population_in_thousands_age_15-19_total | float | 0% | 1 | 35.0 |
Barro-Lee:_Population_in_thousands_age_15-19_female |
Barro-Lee:_Population_in_thousands_age_15-19_female | float | 0% | 1 | 17.0 |
Barro-Lee:_Population_in_thousands_age_15+_total |
Barro-Lee:_Population_in_thousands_age_15+_total | float | 0% | 1 | 416.0 |
Barro-Lee:_Population_in_thousands_age_15+_female |
Barro-Lee:_Population_in_thousands_age_15+_female | float | 0% | 1 | 218.0 |
Barro-Lee:_Population_in_thousands_age_20-24_total |
Barro-Lee:_Population_in_thousands_age_20-24_total | float | 0% | 1 | 43.0 |
| +797 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
Firms_with_female_top_manager_pct_of_firms |
Firms_with_female_top_manager_pct_of_firms | float | 0% | 1 | 43.64096451 |
Firms_with_female_participation_in_ownership_pct_of_firms |
Firms_with_female_participation_in_ownership_pct_of_firms | float | 0% | 1 | 37.14170837 |
School_enrollment_primary_gross_gender_parity_index_GPI |
School_enrollment_primary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.042799949646 |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.01925003528595 |
School_enrollment_secondary_gross_gender_parity_index_GPI |
School_enrollment_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.994069993495941 |
School_enrollment_tertiary_gross_gender_parity_index_GPI |
School_enrollment_tertiary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.09234325401374 |
School_enrollment_preprimary_female_pct_gross |
School_enrollment_preprimary_female_pct_gross | float | 0% | 1 | 96.0097808837891 |
School_enrollment_preprimary_male_pct_gross |
School_enrollment_preprimary_male_pct_gross | float | 0% | 1 | 91.5473098754883 |
Primary_completion_rate_female_pct_of_relevant_age_group |
Primary_completion_rate_female_pct_of_relevant_age_group | float | 0% | 1 | 90.7207792207792 |
Primary_completion_rate_male_pct_of_relevant_age_group |
Primary_completion_rate_male_pct_of_relevant_age_group | float | 0% | 1 | 92.5840978593272 |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc | float | 0% | 1 | 100.0 |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ | float | 0% | 1 | 100.0 |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct | float | 0% | 1 | 100.0 |
Primary_education_pupils_pct_female |
Primary_education_pupils_pct_female | float | 0% | 1 | 47.79839 |
School_enrollment_primary_female_pct_gross |
School_enrollment_primary_female_pct_gross | float | 0% | 1 | 101.573264781491 |
School_enrollment_primary_male_pct_gross |
School_enrollment_primary_male_pct_gross | float | 0% | 1 | 104.650822669104 |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag | float | 0% | 1 | 117.2294 |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ | float | 0% | 1 | 110.50432 |
School_enrollment_primary_female_pct_net |
School_enrollment_primary_female_pct_net | float | 0% | 1 | 94.16782 |
School_enrollment_primary_male_pct_net |
School_enrollment_primary_male_pct_net | float | 0% | 1 | 93.46964 |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population | float | 0% | 1 | 89.06373 |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population | float | 0% | 1 | 81.05459 |
Persistence_to_grade_5_female_pct_of_cohort |
Persistence_to_grade_5_female_pct_of_cohort | float | 0% | 1 | 96.778450012207 |
Persistence_to_grade_5_male_pct_of_cohort |
Persistence_to_grade_5_male_pct_of_cohort | float | 0% | 1 | 98.3544082641602 |
Persistence_to_last_grade_of_primary_female_pct_of_cohort |
Persistence_to_last_grade_of_primary_female_pct_of_cohort | float | 0% | 1 | 94.8337097167969 |
Persistence_to_last_grade_of_primary_male_pct_of_cohort |
Persistence_to_last_grade_of_primary_male_pct_of_cohort | float | 0% | 1 | 96.2746887207031 |
Repeaters_primary_female_pct_of_female_enrollment |
Repeaters_primary_female_pct_of_female_enrollment | float | 0% | 1 | 0.36839 |
Repeaters_primary_male_pct_of_male_enrollment |
Repeaters_primary_male_pct_of_male_enrollment | float | 0% | 1 | 0.43317 |
Trained_teachers_in_primary_education_female_pct_of_female_teachers |
Trained_teachers_in_primary_education_female_pct_of_female_teachers | float | 0% | 1 | 94.0331799804824 |
| +106 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
Firms_with_female_top_manager_pct_of_firms |
Firms_with_female_top_manager_pct_of_firms | float | 0% | 1 | 19.59796906 |
Firms_with_female_participation_in_ownership_pct_of_firms |
Firms_with_female_participation_in_ownership_pct_of_firms | float | 0% | 1 | 43.99720764 |
Literacy_rate_youth_female_pct_of_females_ages_15-24 |
Literacy_rate_youth_female_pct_of_females_ages_15-24 | float | 0% | 1 | 99.7600021362305 |
Literacy_rate_youth_ages_15-24_gender_parity_index_GPI |
Literacy_rate_youth_ages_15-24_gender_parity_index_GPI | float | 0% | 1 | 1.0 |
Literacy_rate_youth_male_pct_of_males_ages_15-24 |
Literacy_rate_youth_male_pct_of_males_ages_15-24 | float | 0% | 1 | 99.75 |
Literacy_rate_adult_female_pct_of_females_ages_15_and_above |
Literacy_rate_adult_female_pct_of_females_ages_15_and_above | float | 0% | 1 | 95.0500030517578 |
Literacy_rate_adult_male_pct_of_males_ages_15_and_above |
Literacy_rate_adult_male_pct_of_males_ages_15_and_above | float | 0% | 1 | 98.379997253418 |
School_enrollment_primary_gross_gender_parity_index_GPI |
School_enrollment_primary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.00856995582581 |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.01161003112793 |
School_enrollment_secondary_gross_gender_parity_index_GPI |
School_enrollment_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.996550023555756 |
School_enrollment_tertiary_gross_gender_parity_index_GPI |
School_enrollment_tertiary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.13814000492912 |
School_enrollment_preprimary_female_pct_gross |
School_enrollment_preprimary_female_pct_gross | float | 0% | 1 | 93.5752716064453 |
School_enrollment_preprimary_male_pct_gross |
School_enrollment_preprimary_male_pct_gross | float | 0% | 1 | 92.6212310791016 |
Primary_completion_rate_female_pct_of_relevant_age_group |
Primary_completion_rate_female_pct_of_relevant_age_group | float | 0% | 1 | 103.93893921564 |
Primary_completion_rate_male_pct_of_relevant_age_group |
Primary_completion_rate_male_pct_of_relevant_age_group | float | 0% | 1 | 103.038399540957 |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc | float | 0% | 1 | 93.7399978637695 |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ | float | 0% | 1 | 97.9000015258789 |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct | float | 0% | 1 | 95.8399963378906 |
Primary_education_pupils_pct_female |
Primary_education_pupils_pct_female | float | 0% | 1 | 46.47985 |
School_enrollment_primary_female_pct_gross |
School_enrollment_primary_female_pct_gross | float | 0% | 1 | 100.682731254959 |
School_enrollment_primary_male_pct_gross |
School_enrollment_primary_male_pct_gross | float | 0% | 1 | 98.7425594135002 |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag | float | 0% | 1 | 103.25703 |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ | float | 0% | 1 | 101.9667 |
School_enrollment_primary_female_pct_net |
School_enrollment_primary_female_pct_net | float | 0% | 1 | 88.3706 |
School_enrollment_primary_male_pct_net |
School_enrollment_primary_male_pct_net | float | 0% | 1 | 90.26422 |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population | float | 0% | 1 | 82.97871 |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population | float | 0% | 1 | 81.86279 |
Persistence_to_grade_5_female_pct_of_cohort |
Persistence_to_grade_5_female_pct_of_cohort | float | 0% | 1 | 99.7389678955078 |
Persistence_to_grade_5_male_pct_of_cohort |
Persistence_to_grade_5_male_pct_of_cohort | float | 0% | 1 | 99.8268203735352 |
| +128 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
Literacy_rate_youth_female_pct_of_females_ages_15-24 |
Literacy_rate_youth_female_pct_of_females_ages_15-24 | float | 0% | 1 | 99.870002746582 |
Literacy_rate_youth_ages_15-24_gender_parity_index_GPI |
Literacy_rate_youth_ages_15-24_gender_parity_index_GPI | float | 0% | 1 | 1.0 |
Literacy_rate_youth_male_pct_of_males_ages_15-24 |
Literacy_rate_youth_male_pct_of_males_ages_15-24 | float | 0% | 1 | 99.7300033569336 |
Literacy_rate_adult_female_pct_of_females_ages_15_and_above |
Literacy_rate_adult_female_pct_of_females_ages_15_and_above | float | 0% | 1 | 95.0299987792969 |
Literacy_rate_adult_male_pct_of_males_ages_15_and_above |
Literacy_rate_adult_male_pct_of_males_ages_15_and_above | float | 0% | 1 | 98.1900024414062 |
School_enrollment_primary_gross_gender_parity_index_GPI |
School_enrollment_primary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.978659987449646 |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.98633998632431 |
School_enrollment_secondary_gross_gender_parity_index_GPI |
School_enrollment_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.996479988098145 |
School_enrollment_tertiary_gross_gender_parity_index_GPI |
School_enrollment_tertiary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.10614641930701 |
School_enrollment_preprimary_female_pct_gross |
School_enrollment_preprimary_female_pct_gross | float | 0% | 1 | 84.9695281982422 |
School_enrollment_preprimary_male_pct_gross |
School_enrollment_preprimary_male_pct_gross | float | 0% | 1 | 87.769660949707 |
Primary_completion_rate_female_pct_of_relevant_age_group |
Primary_completion_rate_female_pct_of_relevant_age_group | float | 0% | 1 | 93.9090909090909 |
Primary_completion_rate_male_pct_of_relevant_age_group |
Primary_completion_rate_male_pct_of_relevant_age_group | float | 0% | 1 | 94.3243243243243 |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc | float | 0% | 1 | 87.8000030517578 |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ | float | 0% | 1 | 92.0599975585938 |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct | float | 0% | 1 | 89.8300018310547 |
Primary_education_pupils_pct_female |
Primary_education_pupils_pct_female | float | 0% | 1 | 48.17859 |
School_enrollment_primary_female_pct_gross |
School_enrollment_primary_female_pct_gross | float | 0% | 1 | 89.8774509803922 |
School_enrollment_primary_male_pct_gross |
School_enrollment_primary_male_pct_gross | float | 0% | 1 | 89.7488789237668 |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag | float | 0% | 1 | 95.57895 |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ | float | 0% | 1 | 93.60158 |
School_enrollment_primary_female_pct_net |
School_enrollment_primary_female_pct_net | float | 0% | 1 | 96.39243 |
School_enrollment_primary_male_pct_net |
School_enrollment_primary_male_pct_net | float | 0% | 1 | 96.39843 |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population | float | 0% | 1 | 91.15789 |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population | float | 0% | 1 | 88.29156 |
Persistence_to_grade_5_female_pct_of_cohort |
Persistence_to_grade_5_female_pct_of_cohort | float | 0% | 1 | 99.2282485961914 |
Persistence_to_grade_5_male_pct_of_cohort |
Persistence_to_grade_5_male_pct_of_cohort | float | 0% | 1 | 99.8556213378906 |
Persistence_to_last_grade_of_primary_female_pct_of_cohort |
Persistence_to_last_grade_of_primary_female_pct_of_cohort | float | 0% | 1 | 99.1962509155273 |
Persistence_to_last_grade_of_primary_male_pct_of_cohort |
Persistence_to_last_grade_of_primary_male_pct_of_cohort | float | 0% | 1 | 99.4566497802734 |
| +102 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
gns_language_code |
gns_language_code | string | CCL | 0% | 15 | zho, bod, eng, rus, uig |
gns_language_name |
gns_language_name | string | CCL | 0% | 15 | Chinese, Tibetan, English, Russian, Uighur |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 13 | 557974, 6149, 638, 136, 120 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 13 | 98.7346, 1.0881, 0.1129, 0.0241, 0.0212 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 7 | 275717, 0, 0, 56, 54 |
gns_dominant_script_code |
gns_dominant_script_code | string | CCL | 0% | 5 | Hans, , , Cyrl, Arab |
gns_dominant_script_name |
gns_dominant_script_name | string | CCL | 0% | 5 | Han (Simplified variant), , , Cyrillic, Arabic |
gns_script_count |
gns_script_count | integer | CCL | 0% | 3 | 4, 0, 0, 1, 1 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | CHN |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | China |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 15 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 6 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 99.9978 |
gns_non_roman_name_count |
gns_non_roman_name_count | integer | CCL | 0% | 1 | 290501 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
gns_name_count |
gns_name_count | integer | 0% | 1 | 597798 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 283208 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 597785 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 13 |
gns_source_build_date |
gns_source_build_date | string | 0% | 1 | Mon, 21 Sep 2026 |
gns_source_change_date |
gns_source_change_date | string | 0% | 1 | 2026-09-21 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 16108 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 3694 |
gns_name_count_populated_places |
gns_name_count_populated_places | integer | 0% | 1 | 564188 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 272006 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 5126 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 1956 |
gns_name_count_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 6979 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 2975 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 2345 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 1321 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 3026 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 1245 |
gns_name_count_transportation_networks |
gns_name_count_transportation_networks | integer | 0% | 1 | 8 |
gns_feature_count_transportation_networks |
gns_feature_count_transportation_networks | integer | 0% | 1 | 4 |
gns_name_count_vegetation |
gns_name_count_vegetation | integer | 0% | 1 | 18 |
gns_feature_count_vegetation |
gns_feature_count_vegetation | integer | 0% | 1 | 7 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
gns_ufi |
gns_ufi | integer | 0% | 100 | 11234817, 11234850, 11231628, 11234858, 11234834 |
admin_designation |
admin_designation | string | 0% | 3 | ADM2, ADM2, ADM2, ADM2, ADM2 |
gns_bgn_name |
gns_bgn_name | string | 0% | 92 | Chongzuo, Fangchenggang, Guigang, Hezhou, Laibin |
gns_local_name |
gns_local_name | string | 1% | 94 | 崇左市, 防城港, 贵港市, 贺州, 来宾市 |
iso_3166_2 |
iso_3166_2 | string | 0% | 16 | CN-GX, CN-GX, CN-GX, CN-GX, CN-GX |
parent_code |
parent_code | string | 0% | 16 | CN-GX, CN-GX, CN-GX, CN-GX, CN-GX |
gns_prominence_band |
gns_prominence_band | integer | 0% | 5 | 6, 7, 7, 7, 7 |
latitude |
latitude | float | 0% | 100 | 22.571647, 21.935796, 23.256286, 24.402443, 23.766667 |
longitude |
longitude | float | 0% | 100 | 107.369211, 107.959321, 109.981462, 111.435165, 109.633333 |
gns_mgrs |
gns_mgrs | string | 0% | 100 | 48QYK4360998037, 48QZK0570028672, 49QCF9581372257,... |
name_variant_count |
name_variant_count | integer | 0% | 4 | 4, 4, 4, 4, 4 |
ⓘ Compiled from local governments' 2020 census bulletins by Lei Dong et al., Peking University (MIT License, (c) 2022 Lei Dong). Units are adjusted so 2010 and 2020 cover the same areas: 91 county rows merge several counties, and some figures differ from NBS's own county tabulation (development zones counted inside their host county, territory moved between neighbours). Xinjiang published no county bulletins, so its 106 counties carry no 2020 values.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
admin_level |
Administrative level | string | SEL | 0% | 1 | admin_2, admin_2, admin_2, admin_2, admin_2 |
unit_tier |
Administrative tier (prefecture / county-level division) | string | SEL | 0% | 1 | prefecture, prefecture, prefecture, prefecture, prefecture |
admin_code |
GB/T 2260 code; merged units join their component codes with '+' | integer | SEL | 0% | 100 | 110100, 120100, 130100, 130200, 130300 |
admin_name |
Unit name (English; NGA GNS BGN where available) | string | SEL | 0% | 99 | Beijing, Tianjin, Shijiazhuang City, Tangshan City,... |
admin_parent_name |
Parent unit name (English) | string | SEL | 0% | 12 | Beijing, Tianjin, Hebei, Hebei, Hebei |
population_2020 |
Resident population, 2020 (local census bulletin) | integer | SEL | 0% | 100 | 21893095, 13866009, 11235086, 7717983, 3136879 |
urban_population_2020 |
Urban population, 2020 | integer | SEL | 1% | 99 | 19166433, 11744440, 7884379, 4963907, 2006711 |
rural_population_2020 |
Rural population, 2020 | integer | SEL | 1% | 99 | 2726662, 2121569, 3350707, 2754076, 1130168 |
avg_household_size_2020 |
Average family household size, 2020 (persons) | float | SEL | 2% | 58 | 2.31, 2.4, 2.82, 2.55, 2.44 |
sex_ratio_2020 |
Sex ratio, 2020 (males per 100 females) | float | SEL | 1% | 99 | 104.7, 106.31, 100.59, 103.29, 101.76 |
share_age_0_14_2020_pct |
Share aged 0-14, 2020 (%) | float | SEL | 1% | 97 | 11.9, 13.47, 19.3, 16.56, 15.17 |
share_age_60_plus_2020_pct |
Share aged 60+, 2020 (%) | float | SEL | 1% | 95 | 19.6, 21.66, 18.47, 22.81, 23.36 |
share_age_65_plus_2020_pct |
Share aged 65+, 2020 (%) | float | SEL | 1% | 91 | 13.3, 14.75, 12.86, 15.98, 16.23 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_name_pinyin |
Unit name in plain Hanyu Pinyin | string | 0% | 99 | Beijing, Tianjin, Shijiazhuang City, Tangshan City,... |
admin_name_local |
Unit name (Chinese, as published) | string | 0% | 100 | 北京市, 天津市, 石家庄市, 唐山市, 秦皇岛市 |
admin_name_source |
Source of the English name (nga_gns / pypinyin / crosswalk) | string | 0% | 3 | crosswalk, crosswalk, nga_gns, nga_gns, nga_gns |
admin_parent_code |
Parent unit code | integer | 0% | 12 | 110000, 120000, 130000, 130000, 130000 |
province_code |
Province GB/T 2260 code | integer | 0% | 12 | 110000, 120000, 130000, 130000, 130000 |
is_merged_unit |
True when the row merges several units so 2010 and 2020 compare | boolean | 0% | 1 | False, False, False, False, False |
component_codes |
GB/T 2260 codes of the units the row covers | integer | 0% | 100 | 110100, 120100, 130100, 130200, 130300 |
dispute_id |
config/disputes/registry.yaml id when the unit lies in a contested area | string | 100% | - | - |
bulletin_published |
False when no 2020 bulletin figures were published (all of Xinjiang's counties) | boolean | 0% | 1 | True, True, True, True, True |
share_age_15_59_2020_pct |
Share aged 15-59, 2020 (%) | float | 1% | 94 | 68.5, 64.87, 62.23, 60.62, 61.47 |
population_2010 |
Resident population, 2010, on 2020-comparable units | integer | 0% | 100 | 19612368, 12938224, 10163788, 7577289, 2987605 |
urban_population_2010 |
Urban population, 2010 | integer | 0% | 100 | 16858692, 10277893, 5145133, 3850975, 1419487 |
rural_population_2010 |
Rural population, 2010 | integer | 0% | 100 | 2753676, 2660331, 5018655, 3726314, 1568118 |
avg_household_size_2010 |
Average family household size, 2010 (persons) | float | 1% | 64 | 2.45, 2.8, 3.47, 3.04, 2.94 |
sex_ratio_2010 |
Sex ratio, 2010 (males per 100 females) | float | 1% | 94 | 106.8, 114.52, 100.24, 104.46, 103.04 |
share_age_0_14_2010_pct |
Share aged 0-14, 2010 (%) | float | 0% | 93 | 8.6, 9.8, 15.23, 14.62, 14.25 |
share_age_15_59_2010_pct |
Share aged 15-59, 2010 (%) | float | 0% | 98 | 78.9, 77.18, 72.13, 70.99, 71.26 |
share_age_60_plus_2010_pct |
Share aged 60+, 2010 (%) | float | 0% | 97 | 12.5, 13.02, 12.63, 14.38, 14.49 |
share_age_65_plus_2010_pct |
Share aged 65+, 2010 (%) | float | 0% | 93 | 8.7, 8.52, 8.13, 9.19, 9.46 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
admin_level |
Administrative level | string | SEL | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
unit_tier |
Administrative tier (prefecture / county-level division) | string | SEL | 0% | 1 | county-level division, county-level division,... |
admin_code |
GB/T 2260 code; merged units join their component codes with '+' | string | SEL | 0% | 100 | 110101, 110102, 110105, 110106, 110107 |
admin_name |
Unit name (English; NGA GNS BGN where available) | string | SEL | 0% | 99 | Dongcheng District, Xicheng District, Chaoyang District,... |
admin_parent_name |
Parent unit name (English) | string | SEL | 0% | 7 | Beijing, Beijing, Beijing, Beijing, Beijing |
population_2020 |
Resident population, 2020 (local census bulletin) | integer | SEL | 0% | 100 | 708829, 1106214, 3452460, 2019764, 567851 |
avg_household_size_2020 |
Average family household size, 2020 (persons) | float | SEL | 25% | 55 | 2.33, 2.37, 2.16, 2.28, 2.35 |
sex_ratio_2020 |
Sex ratio, 2020 (males per 100 females) | float | SEL | 5% | 92 | 94.2, 94.2, 97.7, 97.9, 98.5 |
share_age_0_14_2020_pct |
Share aged 0-14, 2020 (%) | float | SEL | 4% | 89 | 13.9, 14.3, 11.4, 10.9, 11.4 |
share_age_60_plus_2020_pct |
Share aged 60+, 2020 (%) | float | SEL | 4% | 93 | 26.4, 26.0, 20.5, 23.7, 24.3 |
share_age_65_plus_2020_pct |
Share aged 65+, 2020 (%) | float | SEL | 4% | 91 | 18.2, 18.2, 14.3, 15.8, 16.4 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_name_pinyin |
Unit name in plain Hanyu Pinyin | string | 0% | 99 | Dongcheng District, Xicheng District, Chaoyang District,... |
admin_name_local |
Unit name (Chinese, as published) | string | 0% | 100 | 东城区, 西城区, 朝阳区, 丰台区, 石景山区 |
admin_name_source |
Source of the English name (nga_gns / pypinyin / crosswalk) | string | 0% | 3 | nga_gns, nga_gns, nga_gns, nga_gns, nga_gns |
admin_parent_code |
Parent unit code | integer | 0% | 7 | 110100, 110100, 110100, 110100, 110100 |
province_code |
Province GB/T 2260 code | integer | 0% | 3 | 110000, 110000, 110000, 110000, 110000 |
is_merged_unit |
True when the row merges several units so 2010 and 2020 compare | boolean | 0% | 2 | False, False, False, False, False |
dispute_id |
config/disputes/registry.yaml id when the unit lies in a contested area | string | 100% | - | - |
component_codes |
GB/T 2260 codes of the units the row covers | string | 0% | 100 | 110101, 110102, 110105, 110106, 110107 |
bulletin_published |
False when no 2020 bulletin figures were published (all of Xinjiang's counties) | boolean | 0% | 1 | True, True, True, True, True |
share_age_15_59_2020_pct |
Share aged 15-59, 2020 (%) | float | 4% | 90 | 59.7, 59.7, 68.0, 65.4, 64.4 |
population_2010 |
Resident population, 2010, on 2020-comparable units | float | 0% | 100 | 919253, 1243315, 3545137, 2112162, 616083 |
avg_household_size_2010 |
Average family household size, 2010 (persons) | float | 7% | 78 | 2.55, 2.46, 2.26, 2.4, 2.48 |
sex_ratio_2010 |
Sex ratio, 2010 (males per 100 females) | float | 7% | 88 | 97.8, 100.3, 106.1, 104.3, 105.5 |
share_age_0_14_2010_pct |
Share aged 0-14, 2010 (%) | float | 7% | 90 | 7.5, 7.6, 7.6, 8.7, 8.9 |
share_age_15_59_2010_pct |
Share aged 15-59, 2010 (%) | float | 7% | 88 | 75.8, 75.4, 80.2, 78.5, 77.6 |
share_age_60_plus_2010_pct |
Share aged 60+, 2010 (%) | float | 7% | 86 | 16.7, 17.0, 12.2, 12.8, 13.5 |
share_age_65_plus_2010_pct |
Share aged 65+, 2010 (%) | float | 7% | 85 | 12.3, 12.7, 8.6, 8.9, 9.7 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
geoBoundaries admin unit ID | string | SEL | 0% | 31 | 43563684B38891657012300, 43563684B96917371447908,... |
admin_name |
Admin unit name | string | SEL | 0% | 31 | Guangdong Province, Henan Province, Shandong Province,... |
T_TL |
Total population (2020 census, modeled) | integer | SEL | 0% | 31 | 116117501, 103504941, 94910451, 85426917, 83540956 |
pop_0_14 |
Population aged 0-14 (2020 census, modeled) | integer | SEL | 0% | 31 | 22195625, 23945096, 17772329, 13756686, 12739232 |
pop_15_64 |
Population aged 15-64 (2020 census, modeled) | integer | SEL | 0% | 31 | 83617671, 65590942, 62758831, 57214625, 57366005 |
pop_65_plus |
Population aged 65+ (2020 census, modeled) | integer | SEL | 0% | 31 | 10304205, 13968903, 14379291, 14455606, 13435719 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
aspect_15_59 |
Population aged 15-59 (2020 census, modeled) | integer | 0% | 31 | 79134470, 60856285, 57282437, 53137575, 52652897 |
aspect_60_64 |
Population aged 60-64 (2020 census, modeled) | integer | 0% | 31 | 4483202, 4734657, 5476394, 4077051, 4713108 |
admin_level |
Administrative level | string | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
geoBoundaries admin unit ID | string | SEL | 0% | 100 | 17275852B82708605205805, 17275852B40522342172572,... |
admin_name |
Admin unit name | string | SEL | 0% | 100 | Shanghaishi, Beijingshi, Shenzhenxian, Guangzhoushi, Wuhanshi |
T_TL |
Total population (2020 census, modeled) | integer | SEL | 0% | 100 | 13796984, 12609921, 12396715, 11859115, 10323698 |
pop_0_14 |
Population aged 0-14 (2020 census, modeled) | integer | SEL | 0% | 100 | 1352799, 1505059, 1799260, 1469217, 1300697 |
pop_15_64 |
Population aged 15-64 (2020 census, modeled) | integer | SEL | 0% | 100 | 10033043, 9250994, 10298314, 9393169, 7863187 |
pop_65_plus |
Population aged 65+ (2020 census, modeled) | integer | SEL | 0% | 100 | 2411142, 1853868, 299141, 996729, 1159814 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
aspect_15_59 |
Population aged 15-59 (2020 census, modeled) | integer | 0% | 100 | 8963688, 8407349, 10072835, 8938553, 7301975 |
aspect_60_64 |
Population aged 60-64 (2020 census, modeled) | integer | 0% | 100 | 1069355, 843645, 225478, 454616, 561212 |
admin_level |
Administrative level | string | 0% | 1 | admin_2, admin_2, admin_2, admin_2, admin_2 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | China |
admin_code |
Admin code | string | SEL | 0% | 1 | 351020B83567386155957 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 9481443.6475 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 1416619720 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 149.41 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
admin_name |
Admin name | string | SEL | 0% | 34 | Henan Province, Guangzhou Province, Shandong Province,... |
admin_code |
Admin code | string | SEL | 0% | 34 | 43563684B96917371447908, 43563684B38891657012300,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 34 | 166238.359, 180002.4365, 151156.5736, 483501.9625, 97814.4381 |
pop_2024 |
Population count | integer | SEL | 0% | 34 | 104172436, 103921764, 95111552, 85954603, 81803578 |
pop_density_2024 |
Population density | float | SEL | 0% | 34 | 626.64, 577.34, 629.23, 177.78, 836.31 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality, locality, locality, locality |
admin_name |
Admin name | string | SEL | 0% | 100 | Guangzhou, Shanghai, Beijing, Shantou, Suzhou |
admin_code |
Admin code | integer | SEL | 0% | 100 | 10933, 11345, 8745, 11407, 11199 |
area_sqkm |
Area sqkm | float | SEL | 0% | 100 | 6423.8035, 3118.2531, 2176.4202, 1951.9985, 1796.4524 |
pop_2024 |
Population count | integer | SEL | 0% | 100 | 36895550, 20917787, 14784609, 8816799, 7439805 |
pop_density_2024 |
Population density | float | SEL | 0% | 100 | 5743.57, 6708.17, 6793.09, 4516.81, 4141.39 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 100 | 42987704, 30678616, 18150576, 10579303, 11540430 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 92 | 0.858, 0.682, 0.815, 0.833, 0.645 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 98 | Guangzhou, Shanghai, Beijing, Suzhou, Shantou |
country_code |
Country code | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
population |
Population count | integer | SEL | 0% | 100 | 42987704, 30678616, 18150576, 11540430, 10579303 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 100 | 10933, 11345, 8745, 11199, 11407 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | China, China, China, China, China |
population_year |
population_year | integer | 0% | 1 | 2025, 2025, 2025, 2025, 2025 |
latitude |
latitude | string | 100% | - | - |
longitude |
longitude | string | 100% | - | - |
region |
region | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
urban_centre_id |
GHS-UCDB urban-centre ID | integer | SEL | 0% | 100 | 10933, 11345, 8745, 11199, 11407 |
urban_centre_name |
Urban centre name | string | SEL | 0% | 98 | Guangzhou, Shanghai, Beijing, Suzhou, Shantou |
country_code |
ISO 3166-1 alpha-3 country code | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
population_2025 |
Resident population (2025, modeled) | float | SEL | 0% | 100 | 42987704.0, 30678616.2, 18150575.8, 11540429.5, 10579302.5 |
area_sqkm |
Urban centre area (sq km) | float | SEL | 0% | 87 | 6454.0, 3128.0, 2179.0, 1802.0, 1961.0 |
population_density_2025 |
Population density (persons per sq km, 2025) | float | SEL | 0% | 100 | 6660.6, 9807.7, 8329.8, 6404.2, 5394.9 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
name_local |
Urban centre name (native script) | string | 100% | - | - |
country_name |
Country name | string | 0% | 1 | China, China, China, China, China |
built_up_total_sqm_2025 |
Built-up surface, total (sq m, 2025) | integer | 0% | 100 | 1395959307, 718029348, 556610117, 402633886, 332661794 |
built_up_residential_sqm_2025 |
Built-up surface, residential (sq m, 2025) | integer | 0% | 100 | 1173246596, 601977146, 485129765, 324018046, 321243981 |
income_group |
World Bank income group | string | 0% | 1 | Upper Middle, Upper Middle, Upper Middle, Upper Middle,... |
un_subregion |
UN geographic sub-region | string | 0% | 1 | Eastern and South-Eastern Asia, Eastern and... |
first_built_year |
Year first built-up area detected | integer | 0% | 4 | 1975, 1975, 1975, 1975, 1975 |
is_capital |
National capital (1 = capital city) | integer | 0% | 2 | 0, 0, 1, 0, 0 |
admin_level |
Spatial entity level | string | 0% | 1 | locality, locality, locality, locality, locality |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
category |
category | string | 0% | 7 | City prosperity, City prosperity, Streets, Crime, Crime |
indicator |
indicator | string | 0% | 27 | cpi_4_dimensions, cpi_4_dimensions,... |
indicator_friendly |
indicator_friendly | string | 0% | 27 | City Prosperity Index with 4 dimensions, City Prosperity... |
type_data |
type_data | string | 0% | 5 | p, p, n, 000 population, 000 population |
latitude |
latitude | string | 0% | 8 | 39.928892, 31.216452, 35, n, n |
longitude |
longitude | string | 0% | 8 | 116.388286, 121.436505, 105, 35, 35 |
region_id |
region_id | string | 0% | 2 | 789, 789, 789, 105, 105 |
country_id |
country_id | string | 0% | 2 | CN, CN, CN, 789, 789 |
name |
name | string | 0% | 8 | Beijing, Shanghai, China, CN, CN |
year |
year | string | 0% | 23 | 2012, 2012, 2009, China, China |
value |
value | string | 0% | 88 | 0.762, 0.832, 40, 2000, 1999 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
abr |
abr | float | 0% | 1 | 5.227 |
assets |
assets | float | 0% | 1 | 2.977 |
child_mortality |
child_mortality | float | 0% | 1 | 0.371 |
co2_prod |
co2_prod | float | 0% | 1 | 8.349 |
coef_ineq |
coef_ineq | float | 0% | 1 | 15.243 |
cooking_fuel |
cooking_fuel | float | 0% | 1 | 11.496 |
diff_hdi_phdi |
diff_hdi_phdi | float | 0% | 1 | 19.197 |
drinking_water |
drinking_water | float | 0% | 1 | 7.363 |
electricity |
electricity | float | 0% | 1 | 0.13 |
eys |
eys | float | 0% | 1 | 15.479 |
eys_f |
eys_f | float | 0% | 1 | 15.952 |
eys_m |
eys_m | float | 0% | 1 | 15.068 |
gdi_group |
gdi_group | float | 0% | 1 | 1.0 |
gii_rank |
gii_rank | float | 0% | 1 | 41.0 |
gni_pc_f |
gni_pc_f | float | 0% | 1 | 16257.194 |
gni_pc_m |
gni_pc_m | float | 0% | 1 | 27579.501 |
gnipc |
gnipc | float | 0% | 1 | 22029.223 |
hdi_f |
hdi_f | float | 0% | 1 | 0.786 |
hdi_m |
hdi_m | float | 0% | 1 | 0.806 |
hdi_rank |
hdi_rank | float | 0% | 1 | 78.0 |
ineq_edu |
ineq_edu | float | 0% | 1 | 10.293 |
ineq_inc |
ineq_inc | float | 0% | 1 | 30.288 |
ineq_le |
ineq_le | float | 0% | 1 | 5.147 |
le |
le | float | 0% | 1 | 77.953 |
le_f |
le_f | float | 0% | 1 | 80.926 |
le_m |
le_m | float | 0% | 1 | 75.201 |
lfpr_f |
lfpr_f | float | 0% | 1 | 54.6 |
lfpr_m |
lfpr_m | float | 0% | 1 | 75.57 |
loss |
loss | float | 0% | 1 | 15.935 |
| +17 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
GHO (CODE) |
GHO (CODE) | string | 0% | 28 | WHS3_56, TB_c_newinc, WHS3_46, WHS3_57, WHS3_56 |
GHO (DISPLAY) |
GHO (DISPLAY) | string | 0% | 28 | Neonatal tetanus - number of reported cases,... |
GHO (URL) |
GHO (URL) | string | 0% | 28 | https://www.who.int/data/gho/data/indicators/indicator-de... |
YEAR (DISPLAY) |
YEAR (DISPLAY) | string | 0% | 36 | 2015, 2001, 1980, 1999, 1995 |
STARTYEAR |
STARTYEAR | string | 0% | 36 | 2015, 2001, 1980, 1999, 1995 |
ENDYEAR |
ENDYEAR | string | 0% | 36 | 2015, 2001, 1980, 1999, 1995 |
REGION (CODE) |
REGION (CODE) | string | 100% | - | - |
REGION (DISPLAY) |
REGION (DISPLAY) | string | 100% | - | - |
COUNTRY (CODE) |
COUNTRY (CODE) | string | 0% | 1 | HKG, HKG, HKG, HKG, HKG |
COUNTRY (DISPLAY) |
COUNTRY (DISPLAY) | string | 0% | 1 | China, Hong Kong Special Administrative Region, China,... |
DIMENSION (TYPE) |
DIMENSION (TYPE) | string | 91% | 1 | SEX, SEX, SEX, SEX, SEX |
DIMENSION (CODE) |
DIMENSION (CODE) | string | 91% | 1 | SEX_FMLE, SEX_FMLE, SEX_FMLE, SEX_FMLE, SEX_FMLE |
DIMENSION (NAME) |
DIMENSION (NAME) | string | 91% | 1 | Female, Female, Female, Female, Female |
Numeric |
Numeric | float | 0% | 64 | 0.0, 6788.0, 15.0, 53.0, 0.0 |
Value |
Value | string | 0% | 67 | 0, 6788, 15, 53, 0 |
Low |
Low | float | 81% | 18 | 4000.0, 0.41, 0.29, 90.0, 12000.0 |
High |
High | float | 81% | 16 | 5900.0, 0.67, 0.67, 180.0, 17000.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
GHO (CODE) |
GHO (CODE) | string | 0% | 29 | TB_c_dst_rlt_ret_pct, WHS3_50, TB_c_xdr_tsr,... |
GHO (DISPLAY) |
GHO (DISPLAY) | string | 0% | 29 | Previously treated cases tested for RR-/MDR-TB (%),... |
GHO (URL) |
GHO (URL) | string | 0% | 29 | https://www.who.int/data/gho/data/indicators/indicator-de... |
YEAR (DISPLAY) |
YEAR (DISPLAY) | string | 0% | 36 | 2014, 2009, 2015, 2020, 2021 |
STARTYEAR |
STARTYEAR | string | 0% | 36 | 2014, 2009, 2015, 2020, 2021 |
ENDYEAR |
ENDYEAR | string | 0% | 36 | 2014, 2009, 2015, 2020, 2021 |
REGION (CODE) |
REGION (CODE) | string | 100% | - | - |
REGION (DISPLAY) |
REGION (DISPLAY) | string | 100% | - | - |
COUNTRY (CODE) |
COUNTRY (CODE) | string | 0% | 1 | MAC, MAC, MAC, MAC, MAC |
COUNTRY (DISPLAY) |
COUNTRY (DISPLAY) | string | 0% | 1 | China, Macao Special Administrative Region, China, Macao... |
DIMENSION (TYPE) |
DIMENSION (TYPE) | string | 98% | 1 | SEX, SEX |
DIMENSION (CODE) |
DIMENSION (CODE) | string | 98% | 1 | SEX_FMLE, SEX_FMLE |
DIMENSION (NAME) |
DIMENSION (NAME) | string | 98% | 1 | Female, Female |
Numeric |
Numeric | float | 0% | 49 | 79.0, 0.0, 0.0, 92.0, 0.0 |
Value |
Value | string | 0% | 55 | 79, 0, 0, 92, 0 |
Low |
Low | float | 78% | 17 | 0.0, 42.0, 0.0, 124.0, 480.0 |
High |
High | float | 78% | 21 | 8.0, 62.0, 11.0, 184.0, 720.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
Urban_land_area_where_elevation_is_below_5_meters_sq._km |
Urban_land_area_where_elevation_is_below_5_meters_sq._km | float | 0% | 1 | 32989.8003106 |
Urban_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area |
Urban_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area | float | 0% | 1 | 0.3567981485348 |
Urban_land_area_sq._km |
Urban_land_area_sq._km | float | 0% | 1 | 522345.1853048 |
Access_to_electricity_urban_pct_of_urban_population |
Access_to_electricity_urban_pct_of_urban_population | float | 0% | 1 | 100.0 |
PM2.5_air_pollution_mean_annual_exposure_micrograms_per_cubic_meter |
PM2.5_air_pollution_mean_annual_exposure_micrograms_per_cubic_meter | float | 0% | 1 | 34.8105237153218 |
PM2.5_air_pollution_population_exposed_to_levels_exceeding_WHO_guideline_value_p |
PM2.5_air_pollution_population_exposed_to_levels_exceeding_WHO_guideline_value_p | float | 0% | 1 | 99.9982944622564 |
Population_density_people_per_sq._km_of_land_area |
Population_density_people_per_sq._km_of_land_area | float | 0% | 1 | 150.264001337848 |
Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ |
Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ | float | 0% | 1 | 4.35330882386637 |
Population_living_in_slums_pct_of_urban_population |
Population_living_in_slums_pct_of_urban_population | float | 0% | 1 | 26.32091 |
Population_in_largest_city |
Population_in_largest_city | float | 0% | 1 | 30482140.0 |
Population_in_the_largest_city_pct_of_urban_population |
Population_in_the_largest_city_pct_of_urban_population | float | 0% | 1 | 3.26840706087884 |
Population_in_urban_agglomerations_of_more_than_1_million |
Population_in_urban_agglomerations_of_more_than_1_million | float | 0% | 1 | 460164024.0 |
Population_in_urban_agglomerations_of_more_than_1_million_pct_of_total_populatio |
Population_in_urban_agglomerations_of_more_than_1_million_pct_of_total_populatio | float | 0% | 1 | 32.7339486002285 |
Mortality_caused_by_road_traffic_injury_per_100000_population |
Mortality_caused_by_road_traffic_injury_per_100000_population | float | 0% | 1 | 17.4 |
Urban_population_growth_annual_pct |
Urban_population_growth_annual_pct | float | 0% | 1 | 0.431708792065523 |
Urban_population |
Urban_population | float | 0% | 1 | 928439823.0 |
Urban_population_pct_of_total_population |
Urban_population_pct_of_total_population | float | 0% | 1 | 65.8946980998325 |
year |
Reference year | integer | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
glottocode |
Glottocode | string | CCL | 0% | 100 | acha1249, ache1244, aich1238, ainu1251, akeu1235 |
name |
Name | string | CCL | 0% | 100 | Longchuan Achang, Ache, Ai-Cham, Ainu (China), Akeu |
iso639_3 |
Iso639 3 | string | CCL | 12% | 88 | acn, yif, aih, aib, aeu |
level |
Level | string | CCL | 0% | 1 | language, language, language, language, language |
family_name |
Family name | string | CCL | 100% | - | - |
family_glottocode |
Family glottocode | string | CCL | 0% | 11 | sino1245, sino1245, taik1256, turk1311, sino1245 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 0% | 86 | acha1252, uncl1517, maka1300, uigh1243, akeu1236 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
child_family_count |
Child family count | integer | CCL | 0% | 1 | 0, 0, 0, 0, 0 |
child_language_count |
Child language count | integer | CCL | 0% | 1 | 0, 0, 0, 0, 0 |
child_dialect_count |
Child dialect count | integer | CCL | 0% | 12 | 3, 0, 2, 2, 0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 1% | 98 | 24.3479, 24.152, 25.4908, 39.2714, 22.1959 |
longitude |
longitude | float | 1% | 98 | 97.7438, 102.446, 107.844, 76.4209, 101.0823 |
country_codes |
Country codes | string | 0% | 18 | ['CN', 'MM'], ['CN'], ['CN'], ['CN'], ['CN', 'LA', 'MM', 'TH'] |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN |
Urban_land_area_where_elevation_is_below_5_meters_sq._km |
Urban_land_area_where_elevation_is_below_5_meters_sq._km | float | 0% | 1 | 8.30704187323 |
Urban_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area |
Urban_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area | float | 0% | 1 | 32.7841488661865 |
Urban_land_area_sq._km |
Urban_land_area_sq._km | float | 0% | 1 | 17.764426984834 |
Access_to_electricity_urban_pct_of_urban_population |
Access_to_electricity_urban_pct_of_urban_population | float | 0% | 1 | 100.0 |
Population_density_people_per_sq._km_of_land_area |
Population_density_people_per_sq._km_of_land_area | float | 0% | 1 | 20569.696969697 |
Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ |
Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ | float | 0% | 1 | 16.4565015811634 |
Population_in_largest_city |
Population_in_largest_city | float | 0% | 1 | 701381.0 |
Population_in_the_largest_city_pct_of_urban_population |
Population_in_the_largest_city_pct_of_urban_population | float | 0% | 1 | 100.0 |
Urban_population_growth_annual_pct |
Urban_population_growth_annual_pct | float | 0% | 1 | 1.2007758862278 |
Urban_population |
Urban_population | float | 0% | 1 | 687000.0 |
Urban_population_pct_of_total_population |
Urban_population_pct_of_total_population | float | 0% | 1 | 100.0 |
year |
Reference year | integer | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_name |
Administrative unit name | string | 0% | 1 | China |
year |
Year | float | 0% | 1 | 2022 |
population_count |
Population (persons) | integer | 0% | 1 | 1411750000 |
urban_population |
Urban population | integer | 0% | 1 | 920710000 |
rural_population |
Rural population | integer | 0% | 1 | 491040000 |
population_male |
Male population | integer | 0% | 1 | 722060000 |
population_female |
Female population | integer | 0% | 1 | 689690000 |
population_0_14 |
Population aged 0–14 | integer | 0% | 1 | 256150000 |
population_15_64 |
Population aged 15–64 | integer | 0% | 1 | 875560000 |
population_60_plus |
Population aged 60 and over | integer | 0% | 1 | 280040000 |
population_65_plus |
Population aged 65 and over | integer | 0% | 1 | 209780000 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
commodity_name |
Commodity name | string | 0% | 14 | Steel products, Textile yarn, fabrics & products,... |
unit |
Unit of measure | string | 0% | 7 | 10,000 tonnes, —, —, 10,000 pairs, — |
quantity |
Quantity | float | 0% | 9 | 6732, —, —, 929318, — |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 14 | 22.3, 4.9, 6.7, 24.4, -2.5 |
amount_100m_yuan |
Amount (¥100M) | float | 0% | 14 | 6427, 9836, 11713, 3844, 4639 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
industry |
Industry | string | 0% | 10 | Total, of which: Agriculture, forestry, livestock &... |
enterprise_count |
Enterprise count | float | 0% | 10 | 38497, 420, 3570, 523, 602 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 10 | 6.3, 44.6, 46.1, 10.8, -1.1 |
actual_fdi_100m_yuan |
Actual foreign direct investment (¥100M) | float | 0% | 10 | 12327, 80, 3237, 276, 347 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
indicator |
Indicator | string | 0% | 7 | Total deposits, of which: Domestic household deposits,... |
yearend_100m_yuan |
Year-end stock (¥100M) | float | 0% | 7 | 2644472, 1212110, 1203387, 779398, 2191029 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 7 | 10.8, 17.3, 17.4, 6.8, 10.4 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
industry |
Industry | string | 0% | 10 | Finance, Real estate, Leasing & business services,... |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 10 | 10.5, -8.4, 14.5, 21.0, 10.3 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
commodity_name |
Commodity name | string | 0% | 13 | Soybeans, Edible vegetable oil, Iron ore & concentrates,... |
unit |
Unit of measure | string | 0% | 3 | 10,000 tonnes, 10,000 tonnes, 10,000 tonnes, 10,000... |
quantity |
Quantity | float | 0% | 13 | 9108, 648, 110686, 29320, 50828 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 13 | 18.1, -14.1, -27.9, 22.2, 45.9 |
amount_100m_yuan |
Amount (¥100M) | float | 0% | 13 | 4085, 606, 8498, 2855, 24350 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
indicator |
Indicator | string | 0% | 9 | New 220kV+ substation capacity added, New railway line... |
unit |
Unit of measure | string | 0% | 5 | 10,000 kVA, km, km, km, km |
value |
Value | float | 0% | 9 | 25839, 4100, 2082, 2658, 3452 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
industry |
Industry | string | 0% | 11 | Total, of which: Agriculture, forestry, livestock &... |
amount_100m_usd |
Amount (US$100M) | float | 0% | 11 | 1168.5, 8.3, 50.1, 216.0, 35.2 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 11 | 2.8, -26.5, 0.6, 17.4, -28.0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
indicator |
Indicator | string | 0% | 8 | Patents granted, of which: Domestic patents granted, of... |
patents_10k |
Patents (10,000) | float | 0% | 8 | 432.3, 418.7, 79.8, 68.9, 1787.9 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 8 | -6.0, -5.9, 14.7, 19.2, 15.9 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
indicator |
Indicator | string | 0% | 9 | Total population, Urban, Rural, Male, Female |
yearend_10k_persons |
Year-end stock (10,000 persons) | float | 0% | 9 | 141175, 92071, 49104, 72206, 68969 |
share_pct |
Share (%) | float | 0% | 9 | 100.0, 65.2, 34.8, 51.1, 48.9 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
单位:% |
Unit (%) | string | 0% | 11 | Indicator, Urban, CPI, of which: Food, tobacco &... |
col_1 |
Generic column 1 (table-specific) | string | 0% | 11 | National, Rural, 2.0, 2.4, 0.5 |
col_2 |
Generic column 2 (table-specific) | string | 9% | 9 | , 2.0, 2.6, 0.6, 0.5 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
product_name |
Product name | string | 0% | 39 | Yarn, Cloth, Chemical fibre, Refined sugar, Cigarettes |
unit |
Unit of measure | string | 0% | 14 | 10,000 tonnes, 100 million metres, 10,000 tonnes, 10,000... |
output |
Output (value or volume — see unit column) | float | 0% | 39 | 2719.1, 467.5, 6697.8, 1486.8, 24321.5 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 38 | -5.4, -6.9, -0.2, 2.6, 0.6 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
indicator |
Indicator | string | 0% | 9 | Investment, of which: Residential, Floor space under... |
unit |
Unit of measure | string | 0% | 2 | ¥100 million, ¥100 million, 10,000 sq m, 10,000 sq m, 10,000 sq m |
value |
Value | float | 0% | 13 | 132895, 100646, 904999, 639696, 120587 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 13 | -10.0, -9.5, -7.2, -7.3, -39.4 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
country_region |
Country / region (trade-partner dimension) | string | 0% | 11 | ASEAN, EU, United States, South Korea, Japan |
exports_100m_yuan |
Exports (¥100M) | float | 0% | 11 | 37907, 37434, 38706, 10843, 11537 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 11 | 6.8, -4.9, 1.9, -3.7, -7.5 |
export_share_pct |
Export share (%) | float | 0% | 11 | 15.8, 15.6, 16.2, 4.5, 4.8 |
imports_100m_yuan |
Imports (¥100M) | float | 0% | 11 | 27247, 19034, 11834, 13278, 12295 |
import_share_pct |
Import share (%) | float | 0% | 11 | 15.1, 10.5, 6.5, 7.3, 6.8 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
indicator |
Indicator | string | 0% | 8 | Total trade, Total exports, of which: General trade,... |
amount_100m_yuan |
Amount (¥100M) | float | 0% | 12 | 420678, 239654, 152468, 53952, 136973 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 12 | 7.7, 10.5, 15.4, 1.1, 7.0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
indicator |
Indicator | string | 0% | 7 | Total freight, Railway, Highway, Waterway, Civil aviation |
unit |
Unit of measure | string | 0% | 3 | 100 million tonnes, 100 million tonnes, 100 million... |
value |
Value | float | 0% | 12 | 514.7, 49.3, 371.2, 85.5, 607.6 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 12 | -3.0, 4.5, -5.5, 3.8, -17.0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
indicator |
Indicator | string | 0% | 6 | Total passengers, Railway, Highway, Waterway, Civil aviation |
unit |
Unit of measure | string | 0% | 2 | 100 million trips, 100 million trips, 100 million trips,... |
value |
Value | float | 0% | 10 | 55.9, 16.7, 35.5, 1.2, 2.5 |
yoy_growth_pct |
Year-over-year growth (%) | float | 0% | 10 | -32.7, -35.9, -30.3, -28.8, -42.9 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CN, CN, CN, CN, CN |
population_count |
Population count | float | SEL | 2% | 65 | 667070000.0, 660330000.0, 665770000.0, 682335000.0, 698355000.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 33.419, 40.158, 50.959, 51.67, 52.343 |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 2% | 65 | 89.7150749167731, 75.9655011127574, 71.0616845971262,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 92% | 5 | 65.5100021362305, 77.7900009155273, 90.9199981689453,... |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 17% | 53 | 119.1, 113.1, 107.3, 101.7, 96.1 |
poverty_headcount_pct |
Poverty headcount percent | float | SEL | 80% | 13 | 49.8, 30.2, 17.2, 12.7, 10.2 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | China, China, China, China, China |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CN, CN, CN, CN, CN |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 33.419, 40.158, 50.959, 51.67, 52.343 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 47% | 34 | 29.7, 29.7, 29.5, 29.1, 28.5 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 17% | 53 | 119.1, 113.1, 107.3, 101.7, 96.1 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 37 | 125.0, 120.0, 114.0, 108.0, 104.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 61 | 4.451, 3.863, 6.085, 7.513, 6.672 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 64 | 20.86, 18.02, 37.01, 43.37, 39.14 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 55 | 25.43, 14.24, 10.02, 10.04, 11.5 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 23% | 48 | 1.07, 0.96, 0.94, 0.91, 0.88 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 11% | 56 | 1.44000005722046, 1.51999998092651, 1.5,... |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 36% | 18 | 58.0, 73.0, 78.0, 78.0, 75.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 4.4535861, 4.19752026, 4.32156181, 4.35460472, 4.22949076 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | China, China, China, China, China |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
country_name |
country_name | string | 0% | 1 | China, China, China, China, China |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
intl_migrant_stock |
intl_migrant_stock | float | 88% | 8 | 518395.0, 610608.0, 720915.0, 853360.0, 1010008.0 |
intl_migrant_stock_pct |
intl_migrant_stock_pct | float | 88% | 2 | 0.0, 0.1, 0.1, 0.1, 0.1 |
net_migration |
net_migration | float | 0% | 66 | -16927.0, -25578.0, -31305.0, -31383.0, -1250441.0 |
remittances_received_usd |
remittances_received_usd | float | 33% | 44 | 617320000.0, 542000000.0, 403000000.0, 271000000.0, 445280000.0 |
remittances_received_pct_gdp |
remittances_received_pct_gdp | float | 33% | 44 | 0.300426926220373, 0.234499792789059, 0.154736437935385,... |
remittances_paid_usd |
remittances_paid_usd | float | 33% | 38 | 3000000.0, 2000000.0, 2000000.0, 3000000.0, 3000000.0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
society_id |
Society id | string | CCL | 0% | 17 | Eb2, Eb4, Eb7, Ec9, Ed10 |
society_name |
Society name | string | CCL | 0% | 17 | Tu, Dagur, Chahar, Nanai, Shantung |
language_glottocode |
Language glottocode | string | CCL | 0% | 17 | tuuu1240, daur1238, peri1253, nana1257, mand1415 |
language_name |
Language name | string | CCL | 0% | 1 | , , , , |
kinship_system |
Kinship system | string | CCL | 0% | 13 | EA017:4; EA018:4; EA019:1; EA020:1; EA021:9; EA022:9;... |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 16 | EA006:1; EA007:8; EA008:7; EA009:2; EA023:1; EA025:15,... |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 14 | EA001:0; EA002:0; EA003:1; EA004:3; EA005:6; EA028:5;... |
political_complexity |
Political complexity | string | CCL | 0% | 8 | EA032:3; EA033:2, EA032:NA; EA033:NA, EA032:3; EA033:3,... |
religion_importance |
Religion importance | string | CCL | 0% | 13 | EA034:NA; EA112:3, EA034:NA; EA112:6, EA034:1; EA112:NA,... |
residence_pattern |
Residence pattern | string | CCL | 0% | 3 | EA010:8; EA011:1; EA012:8; EA013:9; EA014:11, EA010:8;... |
settlement_pattern |
settlement_pattern | string | CCL | 0% | 12 | EA030:6; EA031:NA, EA030:NA; EA031:NA, EA030:3; EA031:3,... |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | China, China, China, China, China |
dataset |
dataset | string | 0% | 1 | EA, EA, EA, EA, EA |
region |
region | string | 0% | 1 | , , , , |
latitude |
latitude | float | 0% | 14 | 39.0, 49.0, 41.0, 47.0, 37.0 |
longitude |
longitude | float | 0% | 15 | 100.0, 125.0, 115.0, 132.0, 118.0 |
assignment_method |
assignment_method | string | 0% | 1 | point_in_polygon, point_in_polygon, point_in_polygon,... |
assignment_confidence |
assignment_confidence | string | 0% | 1 | approximate, approximate, approximate, approximate, approximate |
source |
source | string | 0% | 1 | D-PLACE: Database of Places, Language, Culture, and... |
source_url |
source_url | string | 0% | 1 | https://d-place.org, https://d-place.org,... |
license |
license | string | 0% | 1 | CC BY 4.0, CC BY 4.0, CC BY 4.0, CC BY 4.0, CC BY 4.0 |
data_vintage |
data_vintage | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | CHN, CHN, CHN, CHN, CHN |
society_id |
society_id | string | CCL | 0% | 17 | Eb2, Eb4, Eb7, Ec9, Ed10 |
society_name |
society_name | string | CCL | 0% | 17 | Tu, Dagur, Chahar, Nanai, Shantung |
language_glottocode |
language_glottocode | string | CCL | 0% | 17 | tuuu1240, daur1238, peri1253, nana1257, mand1415 |
language_name |
language_name | string | CCL | 0% | 1 | , , , , |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | China, China, China, China, China |
dataset |
dataset | string | 0% | 1 | EA, EA, EA, EA, EA |
region |
region | string | 0% | 1 | , , , , |
latitude |
latitude | float | 0% | 14 | 39.0, 49.0, 41.0, 47.0, 37.0 |
longitude |
longitude | float | 0% | 15 | 100.0, 125.0, 115.0, 132.0, 118.0 |
assignment_method |
assignment_method | string | 0% | 1 | point_in_polygon, point_in_polygon, point_in_polygon,... |
assignment_confidence |
assignment_confidence | string | 0% | 1 | approximate, approximate, approximate, approximate, approximate |
source |
source | string | 0% | 1 | D-PLACE: Database of Places, Language, Culture, and... |
source_url |
source_url | string | 0% | 1 | https://d-place.org, https://d-place.org,... |
license |
license | string | 0% | 1 | CC BY 4.0, CC BY 4.0, CC BY 4.0, CC BY 4.0, CC BY 4.0 |
data_vintage |
data_vintage | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
jurisdictional_hierarchy_of_local_community |
jurisdictional_hierarchy_of_local_community | integer | 12% | 2 | 3, 3, 3, 4, 3 |
jurisdictional_hierarchy_beyond_local_community |
jurisdictional_hierarchy_beyond_local_community | integer | 18% | 4 | 2, 3, 2, 5, 5 |
religion_high_gods |
religion_high_gods | integer | 47% | 3 | 1, 1, 1, 1, 1 |
trance_states |
trance_states | integer | 29% | 5 | 3, 6, 6, 2, 6 |
settlement_patterns |
settlement_patterns | integer | 12% | 4 | 6, 3, 7, 7, 7 |
mean_size_of_local_communities |
mean_size_of_local_communities | integer | 29% | 5 | 3, 8, 8, 3, 3 |
marital_residence_first_years |
marital_residence_first_years | integer | 0% | 3 | 8, 8, 8, 8, 8 |
residence_transfer_prevailing_pattern |
residence_transfer_prevailing_pattern | integer | 0% | 2 | 1, 1, 1, 1, 1 |
marital_residence_prevailing_pattern |
marital_residence_prevailing_pattern | integer | 0% | 2 | 8, 8, 8, 8, 8 |
residence_transfer_alternate |
residence_transfer_alternate | integer | 0% | 2 | 9, 9, 9, 9, 9 |
marital_residence_alternate |
marital_residence_alternate | integer | 0% | 2 | 11, 11, 11, 11, 11 |
largest_patrilineal_kin_group |
largest_patrilineal_kin_group | integer | 0% | 3 | 4, 5, 4, 4, 4 |
largest_patrilineal_exogamous_group |
largest_patrilineal_exogamous_group | integer | 0% | 4 | 4, 5, 3, 4, 4 |
largest_matrilineal_kin_group |
largest_matrilineal_kin_group | integer | 0% | 1 | 1, 1, 1, 1, 1 |
largest_matrilineal_exogamous_group |
largest_matrilineal_exogamous_group | integer | 0% | 1 | 1, 1, 1, 1, 1 |
cognatic_kin_groups |
cognatic_kin_groups | integer | 0% | 2 | 9, 9, 9, 9, 9 |
secondary_cognatic_kin_group |
secondary_cognatic_kin_group | integer | 0% | 1 | 9, 9, 9, 9, 9 |
kin_terms_for_cousins |
kin_terms_for_cousins | integer | 18% | 5 | 5, 6, 2, 4, 4 |
descent_major_type |
descent_major_type | integer | 0% | 2 | 1, 1, 1, 1, 1 |
| +14 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
telephones_fixed_lines_subscriptions_per_100_inhabitants_numeric |
Fixed line subscriptions per 100 | float | SEL | 0% | 1 | 12.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 132.0 |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 78.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric |
Broadband subscriptions per 100 | float | SEL | 0% | 1 | 45.0 |
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
telephones_fixed_lines_total_subscriptions_text |
telephones_fixed_lines_total_subscriptions_text | string | 0% | 1 | 167 million (2024 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 167.0 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 12 (2024 est.) |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 1.87 billion (2024 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 1.87 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 132 (2024 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | all broadcast media are owned by, or affiliated with,... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 2000.0 |
internet_country_code_text |
Internet country code text | string | 0% | 1 | .cn |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 78% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 636 million (2023 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 636.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 45 (2023 est.) |
source_section |
source_section | string | 0% | 1 | Communications |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ch.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
real_gdp_per_capita_real_gdp_per_capita_2024_numeric |
Real gdp per capita 2024 (numeric) | float | SEL | 0% | 1 | 23800.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 18.744 |
population_below_poverty_line_numeric |
Poverty headcount percent | float | SEL | 0% | 1 | 0.0 |
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
economic_overview_text |
economic_overview_text | string | 0% | 1 | world’s second-largest economy by nominal GDP; global... |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $33.598 trillion (2024 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_numeric |
Real gdp purchasing power parity 2024 (numeric) | float | 0% | 1 | 33.598 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $32.005 trillion (2023 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_numeric |
Real gdp purchasing power parity 2023 (numeric) | float | 0% | 1 | 32.005 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $30.361 trillion (2022 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_numeric |
Real gdp purchasing power parity 2022 (numeric) | float | 0% | 1 | 30.361 |
real_gdp_purchasing_power_parity_note |
real_gdp_purchasing_power_parity_note | string | 0% | 1 | note: data in 2021 dollars |
real_gdp_growth_rate_real_gdp_growth_rate_2024_text |
Real gdp growth rate 2024 (text) | string | 0% | 1 | 5% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | 5.0 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 5.4% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 5.4 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 3.1% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 3.1 |
real_gdp_growth_rate_note |
real_gdp_growth_rate_note | string | 0% | 1 | note: annual GDP % growth based on constant local currency |
real_gdp_per_capita_real_gdp_per_capita_2024_text |
Real gdp per capita 2024 (text) | string | 0% | 1 | $23,800 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $22,700 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 22700.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $21,500 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 21500.0 |
real_gdp_per_capita_note |
real_gdp_per_capita_note | string | 0% | 1 | note: data in 2021 dollars |
gdp_official_exchange_rate_text |
gdp_official_exchange_rate_text | string | 0% | 1 | $18.744 trillion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 0.2% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 0.2 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text |
Inflation rate consumer prices 2023 (text) | string | 0% | 1 | 0.2% (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric |
Inflation rate consumer prices 2023 (numeric) | float | 0% | 1 | 0.2 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 2% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 2.0 |
inflation_rate_consumer_prices_note |
inflation_rate_consumer_prices_note | string | 0% | 1 | note: annual % change based on consumer prices |
gdp_composition_by_sector_of_origin_agriculture_text |
gdp_composition_by_sector_of_origin_agriculture_text | string | 0% | 1 | 6.8% (2024 est.) |
| +121 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
electricity_access_electrification_total_population_numeric |
Electricity access percent | float | SEL | 0% | 1 | 100.0 |
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
electricity_access_electrification_total_population_text |
electricity_access_electrification_total_population_text | string | 0% | 1 | 100% (2022 est.) |
electricity_installed_generating_capacity_text |
electricity_installed_generating_capacity_text | string | 0% | 1 | 2.949 billion kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 2.949 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 8.894 trillion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 8.894 |
electricity_exports_text |
electricity_exports_text | string | 0% | 1 | 20.577 billion kWh (2023 est.) |
electricity_exports_numeric |
electricity_exports_numeric | float | 0% | 1 | 20.577 |
electricity_imports_text |
electricity_imports_text | string | 0% | 1 | 7.195 billion kWh (2023 est.) |
electricity_imports_numeric |
electricity_imports_numeric | float | 0% | 1 | 7.195 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 325.352 billion kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 325.352 |
electricity_generation_sources_fossil_fuels_text |
electricity_generation_sources_fossil_fuels_text | string | 0% | 1 | 64.2% of total installed capacity (2023 est.) |
electricity_generation_sources_fossil_fuels_numeric |
electricity_generation_sources_fossil_fuels_numeric | float | 0% | 1 | 64.2 |
electricity_generation_sources_nuclear_text |
electricity_generation_sources_nuclear_text | string | 0% | 1 | 4.7% of total installed capacity (2023 est.) |
electricity_generation_sources_nuclear_numeric |
electricity_generation_sources_nuclear_numeric | float | 0% | 1 | 4.7 |
electricity_generation_sources_solar_text |
electricity_generation_sources_solar_text | string | 0% | 1 | 6.3% of total installed capacity (2023 est.) |
electricity_generation_sources_solar_numeric |
electricity_generation_sources_solar_numeric | float | 0% | 1 | 6.3 |
electricity_generation_sources_wind_text |
electricity_generation_sources_wind_text | string | 0% | 1 | 9.6% of total installed capacity (2023 est.) |
electricity_generation_sources_wind_numeric |
electricity_generation_sources_wind_numeric | float | 0% | 1 | 9.6 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 13.3% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 13.3 |
electricity_generation_sources_biomass_and_waste_text |
electricity_generation_sources_biomass_and_waste_text | string | 0% | 1 | 1.9% of total installed capacity (2023 est.) |
electricity_generation_sources_biomass_and_waste_numeric |
electricity_generation_sources_biomass_and_waste_numeric | float | 0% | 1 | 1.9 |
nuclear_energy_number_of_operational_nuclear_reactors_text |
nuclear_energy_number_of_operational_nuclear_reactors_text | string | 0% | 1 | 57 (2025) |
nuclear_energy_number_of_operational_nuclear_reactors_numeric |
nuclear_energy_number_of_operational_nuclear_reactors_numeric | float | 0% | 1 | 57.0 |
nuclear_energy_number_of_nuclear_reactors_under_construction_text |
nuclear_energy_number_of_nuclear_reactors_under_construction_text | string | 0% | 1 | 28 (2025) |
nuclear_energy_number_of_nuclear_reactors_under_construction_numeric |
nuclear_energy_number_of_nuclear_reactors_under_construction_numeric | float | 0% | 1 | 28.0 |
nuclear_energy_net_capacity_of_operational_nuclear_reactors_text |
nuclear_energy_net_capacity_of_operational_nuclear_reactors_text | string | 0% | 1 | 55.32GW (2025 est.) |
nuclear_energy_net_capacity_of_operational_nuclear_reactors_numeric |
nuclear_energy_net_capacity_of_operational_nuclear_reactors_numeric | float | 0% | 1 | 55.32 |
nuclear_energy_percent_of_total_electricity_production_text |
nuclear_energy_percent_of_total_electricity_production_text | string | 0% | 1 | 4.9% (2023 est.) |
| +31 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 55.3 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 23.8 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 64.6 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 1.78 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 395.081 |
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
environmental_issues_text |
environmental_issues_text | string | 0% | 1 | air pollution and acid rain from reliance on coal;... |
international_environmental_agreements_party_to_text |
international_environmental_agreements_party_to_text | string | 0% | 1 | Antarctic-Environmental Protection, Antarctic-Marine... |
international_environmental_agreements_party_to_numeric |
international_environmental_agreements_party_to_numeric | float | 0% | 1 | 2006.0 |
international_environmental_agreements_signed_but_not_ratified_text |
international_environmental_agreements_signed_but_not_ratified_text | string | 0% | 1 | Comprehensive Nuclear Test Ban |
climate_text |
climate_text | string | 0% | 1 | extremely diverse; tropical in south to subarctic in north |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 55.3% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 11.6% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 11.6 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 2.1% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 2.1 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 41.7% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 41.7 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 23.8% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 20.6% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 20.6 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 64.6% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 1.78% annual rate of change (2020-25 est.) |
urbanization_note |
urbanization_note | string | 0% | 1 | note: data do not include Hong Kong and Macau |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 12.196 billion metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 12.196 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 9.575 billion metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_numeric |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_numeric | float | 0% | 1 | 9.575 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 1.847 billion metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_numeric |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_numeric | float | 0% | 1 | 1.847 |
carbon_dioxide_emissions_from_consumed_natural_gas_text |
carbon_dioxide_emissions_from_consumed_natural_gas_text | string | 0% | 1 | 774.076 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_from_consumed_natural_gas_numeric |
carbon_dioxide_emissions_from_consumed_natural_gas_numeric | float | 0% | 1 | 774.076 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 41.4 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 41.4 |
methane_emissions_energy_text |
methane_emissions_energy_text | string | 0% | 1 | 27,832.7 kt (2022-2024 est.) |
methane_emissions_energy_numeric |
methane_emissions_energy_numeric | float | 0% | 1 | 27832.7 |
| +23 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
nationality_noun_text |
nationality_noun_text | string | 0% | 1 | Chinese (singular and plural) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Chinese |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | Han Chinese 91.1%, ethnic minorities 8.9% (includes... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 91.1 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ch.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 9596960.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 9326410.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 270550.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 22457.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 14500.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 8849.0 |
elevation_lowest_point_numeric |
Elevation min m | float | SEL | 0% | 1 | -154.0 |
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 55.3 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 23.8 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 690070.0 |
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
location_text |
location_text | string | 0% | 1 | Eastern Asia, bordering the East China Sea, Korea Bay,... |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 35 00 N, 105 00 E |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 35.0 |
map_references_text |
map_references_text | string | 0% | 1 | Asia |
area_total_text |
area_total_text | string | 0% | 1 | 9,596,960 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 9,326,410 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 270,550 sq km |
area_comparative_text |
area_comparative_text | string | 0% | 1 | slightly smaller than the US |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 22,457 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | Afghanistan 91 km; Bhutan 477 km; Burma 2,129 km; India... |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 91.0 |
coastline_text |
coastline_text | string | 0% | 1 | 14,500 km |
maritime_claims_territorial_sea_text |
maritime_claims_territorial_sea_text | string | 0% | 1 | 12 nm |
maritime_claims_territorial_sea_numeric |
maritime_claims_territorial_sea_numeric | float | 0% | 1 | 12.0 |
maritime_claims_contiguous_zone_text |
maritime_claims_contiguous_zone_text | string | 0% | 1 | 24 nm |
maritime_claims_contiguous_zone_numeric |
maritime_claims_contiguous_zone_numeric | float | 0% | 1 | 24.0 |
maritime_claims_exclusive_economic_zone_text |
maritime_claims_exclusive_economic_zone_text | string | 0% | 1 | 200 nm |
maritime_claims_exclusive_economic_zone_numeric |
maritime_claims_exclusive_economic_zone_numeric | float | 0% | 1 | 200.0 |
maritime_claims_continental_shelf_text |
maritime_claims_continental_shelf_text | string | 0% | 1 | 200 nm or to the edge of the continental margin |
maritime_claims_continental_shelf_numeric |
maritime_claims_continental_shelf_numeric | float | 0% | 1 | 200.0 |
climate_text |
climate_text | string | 0% | 1 | extremely diverse; tropical in south to subarctic in north |
terrain_text |
terrain_text | string | 0% | 1 | mostly mountains, high plateaus, deserts in west;... |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Mount Everest (highest peak in Asia and highest point on... |
elevation_lowest_point_text |
elevation_lowest_point_text | string | 0% | 1 | Turpan Pendi (Turfan Depression) -154 m |
elevation_mean_elevation_text |
elevation_mean_elevation_text | string | 0% | 1 | 1,840 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 1840.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | coal, iron ore, helium, petroleum, natural gas, arsenic,... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 55.3% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 11.6% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 11.6 |
| +29 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name_conventional_long_form_text |
country_name_conventional_long_form_text | string | 0% | 1 | People's Republic of China |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | China |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | Zhonghua Renmin Gongheguo |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Zhongguo |
country_name_abbreviation_text |
country_name_abbreviation_text | string | 0% | 1 | PRC |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | English name could be derived from the Qin (Chin, Ts'in)... |
country_name_etymology_numeric |
country_name_etymology_numeric | float | 0% | 1 | 3.0 |
government_type_text |
government_type_text | string | 0% | 1 | communist party-led state |
capital_name_text |
capital_name_text | string | 0% | 1 | Beijing |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 39 55 N, 116 23 E |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 39.0 |
capital_time_difference_text |
capital_time_difference_text | string | 0% | 1 | UTC+8 (13 hours ahead of Washington, DC, during Standard Time) |
capital_time_difference_numeric |
capital_time_difference_numeric | float | 0% | 1 | 8.0 |
capital_time_zone_note_text |
capital_time_zone_note_text | string | 0% | 1 | China is the largest country (in terms of area) with... |
capital_time_zone_note_numeric |
capital_time_zone_note_numeric | float | 0% | 1 | 1949.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | the name comes from the Chinese words bei (north) and... |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 23 provinces (sheng, singular and plural), 5 autonomous... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 23.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | civil law influenced by Soviet and continental European... |
constitution_history_text |
constitution_history_text | string | 0% | 1 | several previous; latest promulgated 4 December 1982 |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 4.0 |
constitution_amendment_process_text |
constitution_amendment_process_text | string | 0% | 1 | proposed by the Standing Committee of the National... |
international_law_organization_participation_text |
international_law_organization_participation_text | string | 0% | 1 | has not submitted an ICJ jurisdiction declaration;... |
citizenship_citizenship_by_birth_text |
Citizenship by birth (text) | string | 0% | 1 | no |
citizenship_citizenship_by_descent_only_text |
Citizenship by descent only (text) | string | 0% | 1 | least one parent must be a citizen of China |
citizenship_dual_citizenship_recognized_text |
citizenship_dual_citizenship_recognized_text | string | 0% | 1 | no |
citizenship_residency_requirement_for_naturalization_text |
citizenship_residency_requirement_for_naturalization_text | string | 0% | 1 | while naturalization is theoretically possible, in... |
suffrage_text |
suffrage_text | string | 0% | 1 | 18 years of age; universal |
suffrage_numeric |
suffrage_numeric | float | 0% | 1 | 18.0 |
executive_branch_chief_of_state_text |
executive_branch_chief_of_state_text | string | 0% | 1 | President XI Jinping (since 14 March 2013) |
| +74 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | China's historical civilization dates to at least the... |
background_numeric |
background_numeric | float | 0% | 1 | 13.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ch.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_languages_text |
Languages (text) | string | 0% | 1 | Standard Chinese or Mandarin (official; Putonghua, based... |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | 世界概況 – 不可缺少的基本消息來源 (Standard Chinese)The World... |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ch.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
refugees_and_internally_displaced_persons_refugees_text |
refugees_and_internally_displaced_persons_refugees_text | string | 0% | 1 | 814 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 814.0 |
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 198,400 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 198400.0 |
trafficking_in_persons_tier_rating_text |
trafficking_in_persons_tier_rating_text | string | 0% | 1 | Tier 3 — China does not fully meet the minimum standards... |
trafficking_in_persons_tier_rating_numeric |
trafficking_in_persons_tier_rating_numeric | float | 0% | 1 | 3.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ch.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
military_and_security_forces_text |
military_and_security_forces_text | string | 0% | 1 | People's Liberation Army (PLA): Ground Forces or... |
military_and_security_forces_numeric |
military_and_security_forces_numeric | float | 0% | 1 | 2025.0 |
military_expenditures_military_expenditures_2024_text |
Military expenditures 2024 (text) | string | 0% | 1 | 1.5% of GDP (2024 est.) |
military_expenditures_military_expenditures_2024_numeric |
Military expenditures 2024 (numeric) | float | 0% | 1 | 1.5 |
military_expenditures_military_expenditures_2023_text |
Military expenditures 2023 (text) | string | 0% | 1 | 1.5% of GDP (2023 est.) |
military_expenditures_military_expenditures_2023_numeric |
Military expenditures 2023 (numeric) | float | 0% | 1 | 1.5 |
military_expenditures_military_expenditures_2022_text |
Military expenditures 2022 (text) | string | 0% | 1 | 1.5% of GDP (2022 est.) |
military_expenditures_military_expenditures_2022_numeric |
Military expenditures 2022 (numeric) | float | 0% | 1 | 1.5 |
military_expenditures_military_expenditures_2021_text |
Military expenditures 2021 (text) | string | 0% | 1 | 1.5% of GDP (2021 est.) |
military_expenditures_military_expenditures_2021_numeric |
Military expenditures 2021 (numeric) | float | 0% | 1 | 1.5 |
military_expenditures_military_expenditures_2020_text |
Military expenditures 2020 (text) | string | 0% | 1 | 1.7% of GDP (2020 est.) |
military_expenditures_military_expenditures_2020_numeric |
Military expenditures 2020 (numeric) | float | 0% | 1 | 1.7 |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | approximately 2 million active-duty PLA (950,000-1... |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 2.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the PLA is mostly equipped with domestically produced... |
military_equipment_inventories_and_acquisitions_numeric |
military_equipment_inventories_and_acquisitions_numeric | float | 0% | 1 | 2025.0 |
military_service_age_and_obligation_text |
military_service_age_and_obligation_text | string | 0% | 1 | 18-26 years of age depending on education level for men... |
military_service_age_and_obligation_numeric |
military_service_age_and_obligation_numeric | float | 0% | 1 | 18.0 |
military_deployments_text |
military_deployments_text | string | 0% | 1 | 475 Lebanon (UNIFIL); 1,050 South Sudan (UNMISS); 280... |
military_deployments_numeric |
military_deployments_numeric | float | 0% | 1 | 475.0 |
military_note_text |
military_note_text | string | 0% | 1 | the People's Liberation Army (PLA) is the world’s... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 2025.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ch.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 1407181209.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 716908592.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 690272617.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 16.3 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 69.3 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 14.4 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 43.4 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 22.4 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 21.0 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 40.8 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | -0.08 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 7.28 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 7.97 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | -0.11 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 64.6 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 1.78 |
sex_ratio_at_birth_numeric |
Sex ratio at birth | float | SEL | 0% | 1 | 1.09 |
sex_ratio_total_population_numeric |
Sex ratio overall | float | SEL | 0% | 1 | 1.04 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 16.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 6.0 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 78.7 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 1.2 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 0.57 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 3.11 |
hospital_bed_density_numeric |
Hospital beds per 1000 | float | SEL | 0% | 1 | 5.0 |
literacy_total_population_numeric |
Literacy rate percent | float | SEL | 0% | 1 | 96.7 |
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
population_total_text |
population_total_text | string | 0% | 1 | 1,407,181,209 (2025 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 716,908,592 |
population_female_text |
population_female_text | string | 0% | 1 | 690,272,617 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 16.3% (male 122,644,111/female 107,926,176) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 69.3% (male 505,412,555/female 476,599,793) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 14.4% (2024 est.) (male 94,144,838/female 109,315,797) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 43.4 (2025 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 22.4 (2025 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 21 (2025 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 4.8 (2025 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 4.8 |
dependency_ratios_note |
dependency_ratios_note | string | 0% | 1 | note: data do not include Hong Kong, Macau, and Taiwan |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 40.8 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 39 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 39.0 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 41.5 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 41.5 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | -0.08% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 7.28 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 7.97 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | -0.11 migrant(s)/1,000 population (2025 est.) |
population_distribution_text |
population_distribution_text | string | 0% | 1 | overwhelming majority of the population is found in the... |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 64.6% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 1.78% annual rate of change (2020-25 est.) |
urbanization_note |
urbanization_note | string | 0% | 1 | note: data do not include Hong Kong and Macau |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 29.211 million Shanghai, 21.766 million BEIJING... |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 29.211 |
sex_ratio_at_birth_text |
sex_ratio_at_birth_text | string | 0% | 1 | 1.09 male(s)/female |
sex_ratio_0_14_years_text |
sex_ratio_0_14_years_text | string | 0% | 1 | 1.14 male(s)/female |
sex_ratio_0_14_years_numeric |
sex_ratio_0_14_years_numeric | float | 0% | 1 | 1.14 |
| +89 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_religion_buddhist_pct_synth |
Buddhist | numeric | CCL | 0% | - | 18.2 |
composition_religion_christian_pct_synth |
Christian | numeric | CCL | 0% | - | 5.1 |
composition_religion_muslim_pct_synth |
Muslim | numeric | CCL | 0% | - | 1.8 |
composition_religion_hindu_pct_synth |
Hindu | numeric | CCL | 0% | - | 0.05 |
composition_religion_other_pct_synth |
other | numeric | CCL | 0% | - | 0.7 |
composition_ethnicity_primary_label_synth |
Han Chinese | string | CCL | 0% | - | Han Chinese |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | folk religion 21.9%, Buddhist 18.2%, Christian 5.1%,... |
religions_numeric |
religions_numeric | float | 0% | 1 | 21.9 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ch.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_folk_religion_pct_synth |
folk religion | numeric | 0% | - | 21.9 |
composition_religion_jewish_pct_synth |
Jewish | numeric | 0% | - | 0.05 |
composition_religion_unaffiliated_pct_synth |
unaffiliated | numeric | 0% | - | 52.1 |
composition_ethnicity_han_chinese_pct_synth |
Han Chinese | numeric | 0% | - | 91.1 |
composition_ethnicity_ethnic_minorities_pct_synth |
ethnic minorities | numeric | 0% | - | 8.9 |
composition_ethnicity_primary_share_pct_synth |
Han Chinese | numeric | 0% | - | 91.1 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
space_agency_agencies_text |
space_agency_agencies_text | string | 0% | 1 | China National Space Administration (CNSA; established... |
space_agency_agencies_numeric |
space_agency_agencies_numeric | float | 0% | 1 | 1993.0 |
space_launch_site_s_text |
space_launch_site_s_text | string | 0% | 1 | Jiuquan Launch Center (Inner Mongolia); Xichang Launch... |
space_launch_site_s_numeric |
space_launch_site_s_numeric | float | 0% | 1 | 2024.0 |
space_program_overview_text |
space_program_overview_text | string | 0% | 1 | considered one of the world’s leading space powers, with... |
space_program_overview_numeric |
space_program_overview_numeric | float | 0% | 1 | 45.0 |
key_space_program_milestones_text |
key_space_program_milestones_text | string | 0% | 1 | 1960s - began launching rockets and initiated satellite... |
key_space_program_milestones_numeric |
key_space_program_milestones_numeric | float | 0% | 1 | 1960.0 |
source_section |
source_section | string | 0% | 1 | Space |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ch.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
illicit_drugs_usg_identification_text |
illicit_drugs_usg_identification_text | string | 0% | 1 | major illicit drug-producing and/or drug-transit... |
illicit_drugs_usg_identification_numeric |
illicit_drugs_usg_identification_numeric | float | 0% | 1 | 2025.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ch.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
airports_numeric |
Airports count | float | SEL | 0% | 1 | 552.0 |
country_code |
Country code | string | SEL | 0% | 1 | CHN |
country_name |
Country name | string | SEL | 0% | 1 | China |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
civil_aircraft_registration_country_code_prefix_text |
Civil aircraft registration country code prefix text | string | 0% | 1 | B |
airports_text |
airports_text | string | 0% | 1 | 552 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 120 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 120.0 |
railways_total_text |
railways_total_text | string | 0% | 1 | 150,000 km (2021) 1.435-m gauge (100,000 km... |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 150000.0 |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 8,314 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 8314.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | bulk carrier 1,831, container ship 419, general cargo... |
merchant_marine_by_type_numeric |
merchant_marine_by_type_numeric | float | 0% | 1 | 1831.0 |
ports_total_ports_text |
ports_total_ports_text | string | 0% | 1 | 66 (2024) |
ports_total_ports_numeric |
ports_total_ports_numeric | float | 0% | 1 | 66.0 |
ports_large_text |
ports_large_text | float | 0% | 1 | 5 |
ports_large_numeric |
ports_large_numeric | float | 0% | 1 | 5.0 |
ports_medium_text |
ports_medium_text | float | 0% | 1 | 9 |
ports_medium_numeric |
ports_medium_numeric | float | 0% | 1 | 9.0 |
ports_small_text |
ports_small_text | float | 0% | 1 | 25 |
ports_small_numeric |
ports_small_numeric | float | 0% | 1 | 25.0 |
ports_very_small_text |
ports_very_small_text | float | 0% | 1 | 27 |
ports_very_small_numeric |
ports_very_small_numeric | float | 0% | 1 | 27.0 |
ports_ports_with_oil_terminals_text |
Ports with oil terminals (text) | float | 0% | 1 | 48 |
ports_ports_with_oil_terminals_numeric |
Ports with oil terminals (numeric) | float | 0% | 1 | 48.0 |
ports_key_ports_text |
ports_key_ports_text | string | 0% | 1 | Chaozhou, Dalian, Fang-Cheng, Guangzhou, Hankow, Lon... |
source_section |
source_section | string | 0% | 1 | Transportation |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ch.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
Agricultural_land_pct_of_land_area |
Agricultural land percent | float | SEL | 0% | 1 | 55.4326117545304 |
Forest_area_sq._km |
Forest area sqkm | float | SEL | 0% | 1 | 2256168.9 |
Forest_area_pct_of_land_area |
Forest area percent | float | SEL | 0% | 1 | 24.0319389958256 |
Land_area_sq._km |
Area land sqkm | float | SEL | 0% | 1 | 9388210.0 |
Surface_area_sq._km |
Area sqkm | float | SEL | 0% | 1 | 9562910.0 |
Cereal_yield_kg_per_hectare |
Cereal yield kg per hectare | float | SEL | 0% | 1 | 6418.1 |
Rural_population |
Rural population | float | SEL | 0% | 1 | 480535177.0 |
Mortality_rate_under-5_per_1000_live_births |
Under5 mortality per 1000 | float | SEL | 0% | 1 | 6.2 |
Pregnant_women_receiving_prenatal_care_pct |
Prenatal care percent | float | SEL | 0% | 1 | 99.6 |
Maternal_mortality_ratio_modeled_estimate_per_100000_live_births |
Maternal mortality per 100k | float | SEL | 0% | 1 | 16.0 |
GDP_current_USusd |
Gdp total usd | float | SEL | 0% | 1 | 18743803170827.2 |
GDP_per_capita_current_USusd |
Gdp per capita usd | float | SEL | 0% | 1 | 13303.1481543868 |
Literacy_rate_adult_total_pct_of_people_ages_15_and_above |
Literacy rate percent | float | SEL | 0% | 1 | 96.7399978637695 |
School_enrollment_primary_pct_gross |
Primary enrollment rate percent | float | SEL | 0% | 1 | 99.644962886981 |
School_enrollment_secondary_pct_gross |
Secondary enrollment rate percent | float | SEL | 0% | 1 | 92.2603063015232 |
School_enrollment_tertiary_pct_gross |
Tertiary enrollment rate percent | float | SEL | 0% | 1 | 76.8757843123403 |
Government_expenditure_on_education_total_pct_of_GDP |
Education expenditure percent gdp | float | SEL | 0% | 1 | 4.00127983093262 |
Unemployment_total_pct_of_total_labor_force_modeled_ILO_estimate |
Unemployment rate percent | float | SEL | 0% | 1 | 4.615 |
Population_ages_0-14_pct_of_total_population |
Population 0 14 percent | float | SEL | 0% | 1 | 16.0078123326803 |
Population_ages_15-64_pct_of_total_population |
Population 15 64 percent | float | SEL | 0% | 1 | 69.3269188307508 |
Access_to_electricity_pct_of_population |
Electricity access percent | float | SEL | 0% | 1 | 100.0 |
Population_living_in_slums_pct_of_urban_population |
Slum population percent | float | SEL | 0% | 1 | 26.32091 |
People_using_at_least_basic_sanitation_services_pct_of_population |
Basic sanitation percent | float | SEL | 0% | 1 | 97.2718787578263 |
People_with_basic_handwashing_facilities_including_soap_and_water_pct_of_populat |
Handwashing facility percent | float | SEL | 0% | 1 | 97.2663184969228 |
People_practicing_open_defecation_pct_of_population |
Open defecation percent | float | SEL | 0% | 1 | 0.0 |
Hospital_beds_per_1000_people |
Hospital beds per 1000 | float | SEL | 0% | 1 | 5.63 |
Physicians_per_1000_people |
Physicians per 1000 | float | SEL | 0% | 1 | 3.112 |
Current_health_expenditure_pct_of_GDP |
Health expenditure percent gdp | float | SEL | 0% | 1 | 5.94388866 |
Prevalence_of_undernourishment_pct_of_population |
Undernourishment percent | float | SEL | 0% | 1 | 2.5 |
| +26 more standards-aligned fields — download the CSV/Parquet to see them all. | ||||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Fertilizer_consumption_pct_of_fertilizer_production |
Fertilizer_consumption_pct_of_fertilizer_production | float | 0% | 1 | 92.0312777126008 |
Fertilizer_consumption_kilograms_per_hectare_of_arable_land |
Fertilizer_consumption_kilograms_per_hectare_of_arable_land | float | 0% | 1 | 394.019742296898 |
Agricultural_land_sq._km |
Agricultural_land_sq._km | float | 0% | 1 | 5204130.0 |
Arable_land_hectares |
Arable_land_hectares | float | 0% | 1 | 108427100.0 |
Arable_land_hectares_per_person |
Arable_land_hectares_per_person | float | 0% | 1 | 0.0768599499542783 |
Arable_land_pct_of_land_area |
Arable_land_pct_of_land_area | float | 0% | 1 | 11.5492836227566 |
Land_under_cereal_production_hectares |
Land_under_cereal_production_hectares | float | 0% | 1 | 99987255.0 |
Permanent_cropland_pct_of_land_area |
Permanent_cropland_pct_of_land_area | float | 0% | 1 | 2.04010136117535 |
Rural_land_area_where_elevation_is_below_5_meters_sq._km |
Rural_land_area_where_elevation_is_below_5_meters_sq._km | float | 0% | 1 | 42639.9398719 |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area | float | 0% | 1 | 0.461168344660781 |
Average_precipitation_in_depth_mm_per_year |
Average_precipitation_in_depth_mm_per_year | float | 0% | 1 | 645.0 |
Rural_land_area_sq._km |
Rural_land_area_sq._km | float | 0% | 1 | 8723723.0597445 |
Cereal_production_metric_tons |
Cereal_production_metric_tons | float | 0% | 1 | 641731705.88 |
Crop_production_index_2014-2016_=_100 |
Crop_production_index_2014-2016_=_100 | float | 0% | 1 | 111.85 |
Food_production_index_2014-2016_=_100 |
Food_production_index_2014-2016_=_100 | float | 0% | 1 | 111.75 |
Livestock_production_index_2014-2016_=_100 |
Livestock_production_index_2014-2016_=_100 | float | 0% | 1 | 109.5 |
Access_to_electricity_rural_pct_of_rural_population |
Access_to_electricity_rural_pct_of_rural_population | float | 0% | 1 | 100.0 |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ | float | 0% | 1 | 0.525493494671787 |
Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal |
Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal | float | 0% | 1 | 62.14454059 |
Agriculture_forestry_and_fishing_value_added_current_USusd |
Agriculture_forestry_and_fishing_value_added_current_USusd | float | 0% | 1 | 1270079880349.97 |
Agriculture_forestry_and_fishing_value_added_pct_of_GDP |
Agriculture_forestry_and_fishing_value_added_pct_of_GDP | float | 0% | 1 | 6.77599881291286 |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 18.6826526976472 |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate | float | 0% | 1 | 24.1934332847983 |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate | float | 0% | 1 | 21.6768623336956 |
Rural_population_growth_annual_pct |
Rural_population_growth_annual_pct | float | 0% | 1 | -1.18629610241506 |
Rural_population_pct_of_total_population |
Rural_population_pct_of_total_population | float | 0% | 1 | 34.1053019001675 |
Agricultural_raw_materials_imports_pct_of_merchandise_imports |
Agricultural_raw_materials_imports_pct_of_merchandise_imports | float | 0% | 1 | 2.65554162830592 |
Agricultural_raw_materials_exports_pct_of_merchandise_exports |
Agricultural_raw_materials_exports_pct_of_merchandise_exports | float | 0% | 1 | 0.344746971362811 |
Grants_excluding_technical_cooperation_BoP_current_USusd |
Grants_excluding_technical_cooperation_BoP_current_USusd | float | 0% | 1 | 103417845.0 |
Technical_cooperation_grants_BoP_current_USusd |
Technical_cooperation_grants_BoP_current_USusd | float | 0% | 1 | 398944950.0 |
| +2647 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
Pregnant_women_receiving_prenatal_care_pct |
Prenatal care percent | float | SEL | 0% | 1 | 99.6 |
Maternal_mortality_ratio_modeled_estimate_per_100000_live_births |
Maternal mortality per 100k | float | SEL | 0% | 1 | 16.0 |
Contraceptive_prevalence_any_method_pct_of_married_women_ages_15-49 |
Contraception any percent | float | SEL | 0% | 1 | 84.5 |
Fertility_rate_total_births_per_woman |
Fertility rate | float | SEL | 0% | 1 | 0.999 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Firms_with_female_top_manager_pct_of_firms |
Firms_with_female_top_manager_pct_of_firms | float | 0% | 1 | 19.59796906 |
Firms_with_female_participation_in_ownership_pct_of_firms |
Firms_with_female_participation_in_ownership_pct_of_firms | float | 0% | 1 | 43.99720764 |
Literacy_rate_youth_female_pct_of_females_ages_15-24 |
Literacy_rate_youth_female_pct_of_females_ages_15-24 | float | 0% | 1 | 99.7600021362305 |
Literacy_rate_youth_ages_15-24_gender_parity_index_GPI |
Literacy_rate_youth_ages_15-24_gender_parity_index_GPI | float | 0% | 1 | 1.0 |
Literacy_rate_youth_male_pct_of_males_ages_15-24 |
Literacy_rate_youth_male_pct_of_males_ages_15-24 | float | 0% | 1 | 99.75 |
Literacy_rate_adult_female_pct_of_females_ages_15_and_above |
Literacy_rate_adult_female_pct_of_females_ages_15_and_above | float | 0% | 1 | 95.0500030517578 |
Literacy_rate_adult_male_pct_of_males_ages_15_and_above |
Literacy_rate_adult_male_pct_of_males_ages_15_and_above | float | 0% | 1 | 98.379997253418 |
School_enrollment_primary_gross_gender_parity_index_GPI |
School_enrollment_primary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.00856995582581 |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.01161003112793 |
School_enrollment_secondary_gross_gender_parity_index_GPI |
School_enrollment_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.996550023555756 |
School_enrollment_tertiary_gross_gender_parity_index_GPI |
School_enrollment_tertiary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.13814000492912 |
School_enrollment_preprimary_female_pct_gross |
School_enrollment_preprimary_female_pct_gross | float | 0% | 1 | 93.5752716064453 |
School_enrollment_preprimary_male_pct_gross |
School_enrollment_preprimary_male_pct_gross | float | 0% | 1 | 92.6212310791016 |
Primary_completion_rate_female_pct_of_relevant_age_group |
Primary_completion_rate_female_pct_of_relevant_age_group | float | 0% | 1 | 103.93893921564 |
Primary_completion_rate_male_pct_of_relevant_age_group |
Primary_completion_rate_male_pct_of_relevant_age_group | float | 0% | 1 | 103.038399540957 |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc | float | 0% | 1 | 93.7399978637695 |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ | float | 0% | 1 | 97.9000015258789 |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct | float | 0% | 1 | 95.8399963378906 |
Primary_education_pupils_pct_female |
Primary_education_pupils_pct_female | float | 0% | 1 | 46.47985 |
School_enrollment_primary_female_pct_gross |
School_enrollment_primary_female_pct_gross | float | 0% | 1 | 100.682731254959 |
School_enrollment_primary_male_pct_gross |
School_enrollment_primary_male_pct_gross | float | 0% | 1 | 98.7425594135002 |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag | float | 0% | 1 | 103.25703 |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ | float | 0% | 1 | 101.9667 |
School_enrollment_primary_female_pct_net |
School_enrollment_primary_female_pct_net | float | 0% | 1 | 88.3706 |
School_enrollment_primary_male_pct_net |
School_enrollment_primary_male_pct_net | float | 0% | 1 | 90.26422 |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population | float | 0% | 1 | 82.97871 |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population | float | 0% | 1 | 81.86279 |
Persistence_to_grade_5_female_pct_of_cohort |
Persistence_to_grade_5_female_pct_of_cohort | float | 0% | 1 | 99.7389678955078 |
Persistence_to_grade_5_male_pct_of_cohort |
Persistence_to_grade_5_male_pct_of_cohort | float | 0% | 1 | 99.8268203735352 |
Persistence_to_last_grade_of_primary_female_pct_of_cohort |
Persistence_to_last_grade_of_primary_female_pct_of_cohort | float | 0% | 1 | 96.711051940918 |
| +122 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
le |
Life expectancy | float | SEL | 0% | 1 | 77.953 |
mys |
Mean years schooling | float | SEL | 0% | 1 | 8.036 |
years_of_schooling |
Mean years schooling | float | SEL | 0% | 1 | 20.663 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
abr |
abr | float | 0% | 1 | 5.227 |
assets |
assets | float | 0% | 1 | 2.977 |
child_mortality |
child_mortality | float | 0% | 1 | 0.371 |
co2_prod |
co2_prod | float | 0% | 1 | 8.349 |
coef_ineq |
coef_ineq | float | 0% | 1 | 15.243 |
cooking_fuel |
cooking_fuel | float | 0% | 1 | 11.496 |
diff_hdi_phdi |
diff_hdi_phdi | float | 0% | 1 | 19.197 |
drinking_water |
drinking_water | float | 0% | 1 | 7.363 |
electricity |
electricity | float | 0% | 1 | 0.13 |
eys |
eys | float | 0% | 1 | 15.479 |
eys_f |
eys_f | float | 0% | 1 | 15.952 |
eys_m |
eys_m | float | 0% | 1 | 15.068 |
gdi_group |
gdi_group | float | 0% | 1 | 1.0 |
gii_rank |
gii_rank | float | 0% | 1 | 41.0 |
gni_pc_f |
gni_pc_f | float | 0% | 1 | 16257.194 |
gni_pc_m |
gni_pc_m | float | 0% | 1 | 27579.501 |
gnipc |
gnipc | float | 0% | 1 | 22029.223 |
hdi_f |
hdi_f | float | 0% | 1 | 0.786 |
hdi_m |
hdi_m | float | 0% | 1 | 0.806 |
hdi_rank |
hdi_rank | float | 0% | 1 | 78.0 |
ineq_edu |
ineq_edu | float | 0% | 1 | 10.293 |
ineq_inc |
ineq_inc | float | 0% | 1 | 30.288 |
ineq_le |
ineq_le | float | 0% | 1 | 5.147 |
le_f |
le_f | float | 0% | 1 | 80.926 |
le_m |
le_m | float | 0% | 1 | 75.201 |
lfpr_f |
lfpr_f | float | 0% | 1 | 54.6 |
lfpr_m |
lfpr_m | float | 0% | 1 | 75.57 |
loss |
loss | float | 0% | 1 | 15.935 |
mf |
mf | float | 0% | 1 | 24.906 |
mmr |
mmr | float | 0% | 1 | 23.048 |
| +12 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
Population_density_people_per_sq._km_of_land_area |
Population density | float | SEL | 0% | 1 | 150.264001337848 |
Population_living_in_slums_pct_of_urban_population |
Slum population percent | float | SEL | 0% | 1 | 26.32091 |
Urban_population_growth_annual_pct |
Urban growth rate percent | float | SEL | 0% | 1 | 0.431708792065523 |
Urban_population |
Urban population | float | SEL | 0% | 1 | 928439823.0 |
Urban_population_pct_of_total_population |
Urban population percent | float | SEL | 0% | 1 | 65.8946980998325 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Urban_land_area_where_elevation_is_below_5_meters_sq._km |
Urban_land_area_where_elevation_is_below_5_meters_sq._km | float | 0% | 1 | 32989.8003106 |
Urban_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area |
Urban_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area | float | 0% | 1 | 0.3567981485348 |
Urban_land_area_sq._km |
Urban_land_area_sq._km | float | 0% | 1 | 522345.1853048 |
Access_to_electricity_urban_pct_of_urban_population |
Access_to_electricity_urban_pct_of_urban_population | float | 0% | 1 | 100.0 |
PM2.5_air_pollution_mean_annual_exposure_micrograms_per_cubic_meter |
PM2.5_air_pollution_mean_annual_exposure_micrograms_per_cubic_meter | float | 0% | 1 | 34.8105237153218 |
PM2.5_air_pollution_population_exposed_to_levels_exceeding_WHO_guideline_value_p |
PM2.5_air_pollution_population_exposed_to_levels_exceeding_WHO_guideline_value_p | float | 0% | 1 | 99.9982944622564 |
Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ |
Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ | float | 0% | 1 | 4.35330882386637 |
Population_in_largest_city |
Population_in_largest_city | float | 0% | 1 | 30482140.0 |
Population_in_the_largest_city_pct_of_urban_population |
Population_in_the_largest_city_pct_of_urban_population | float | 0% | 1 | 3.26840706087884 |
Population_in_urban_agglomerations_of_more_than_1_million |
Population_in_urban_agglomerations_of_more_than_1_million | float | 0% | 1 | 460164024.0 |
Population_in_urban_agglomerations_of_more_than_1_million_pct_of_total_populatio |
Population_in_urban_agglomerations_of_more_than_1_million_pct_of_total_populatio | float | 0% | 1 | 32.7339486002285 |
Mortality_caused_by_road_traffic_injury_per_100000_population |
Mortality_caused_by_road_traffic_injury_per_100000_population | float | 0% | 1 | 17.4 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
Agricultural_land_pct_of_land_area |
Agricultural land percent | float | SEL | 0% | 1 | 3.80952380952381 |
Land_area_sq._km |
Area land sqkm | float | SEL | 0% | 1 | 1050.0 |
Surface_area_sq._km |
Area sqkm | float | SEL | 0% | 1 | 1110.0 |
Cereal_yield_kg_per_hectare |
Cereal yield kg per hectare | float | SEL | 0% | 1 | 2059.0 |
Rural_population |
Rural population | float | SEL | 0% | 1 | 0.0 |
GDP_current_USusd |
Gdp total usd | float | SEL | 0% | 1 | 406863396487.342 |
GDP_per_capita_current_USusd |
Gdp per capita usd | float | SEL | 0% | 1 | 54074.6928519479 |
School_enrollment_primary_pct_gross |
Primary enrollment rate percent | float | SEL | 0% | 1 | 103.152955896153 |
School_enrollment_secondary_pct_gross |
Secondary enrollment rate percent | float | SEL | 0% | 1 | 107.160326941213 |
School_enrollment_tertiary_pct_gross |
Tertiary enrollment rate percent | float | SEL | 0% | 1 | 120.08978583196 |
Government_expenditure_on_education_total_pct_of_GDP |
Education expenditure percent gdp | float | SEL | 0% | 1 | 3.80804991722107 |
Unemployment_total_pct_of_total_labor_force_modeled_ILO_estimate |
Unemployment rate percent | float | SEL | 0% | 1 | 2.799 |
Population_ages_0-14_pct_of_total_population |
Population 0 14 percent | float | SEL | 0% | 1 | 10.5078221116522 |
Population_ages_15-64_pct_of_total_population |
Population 15 64 percent | float | SEL | 0% | 1 | 66.8250300290246 |
Access_to_electricity_pct_of_population |
Electricity access percent | float | SEL | 0% | 1 | 100.0 |
People_using_safely_managed_drinking_water_services_pct_of_population |
Safe drinking water percent | float | SEL | 0% | 1 | 100.0 |
People_using_at_least_basic_sanitation_services_pct_of_population |
Basic sanitation percent | float | SEL | 0% | 1 | 94.834373461349 |
People_practicing_open_defecation_pct_of_population |
Open defecation percent | float | SEL | 0% | 1 | 0.0 |
Hospital_beds_per_1000_people |
Hospital beds per 1000 | float | SEL | 0% | 1 | 4.89090013504028 |
Physicians_per_1000_people |
Physicians per 1000 | float | SEL | 0% | 1 | 1.319 |
Prevalence_of_undernourishment_pct_of_population |
Undernourishment percent | float | SEL | 0% | 1 | 3.1 |
Birth_rate_crude_per_1000_people |
Birth rate per 1000 | float | SEL | 0% | 1 | 4.4 |
Death_rate_crude_per_1000_people |
Death rate per 1000 | float | SEL | 0% | 1 | 7.3 |
Contraceptive_prevalence_any_method_pct_of_married_women_ages_15-49 |
Contraception any percent | float | SEL | 0% | 1 | 66.7 |
Life_expectancy_at_birth_total_years |
Life expectancy | float | SEL | 0% | 1 | 85.2473170731707 |
Fertility_rate_total_births_per_woman |
Fertility rate | float | SEL | 0% | 1 | 0.751 |
Population_ages_0-14_total |
Population 0 14 | float | SEL | 0% | 1 | 790619.0 |
Population_ages_15-64_total |
Population 15 64 | float | SEL | 0% | 1 | 5027982.0 |
Population_ages_65_and_above_total |
Population 65 plus | float | SEL | 0% | 1 | 1705499.0 |
| +15 more standards-aligned fields — download the CSV/Parquet to see them all. | ||||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Fertilizer_consumption_kilograms_per_hectare_of_arable_land |
Fertilizer_consumption_kilograms_per_hectare_of_arable_land | float | 0% | 1 | 484.0 |
Agricultural_land_sq._km |
Agricultural_land_sq._km | float | 0% | 1 | 40.0 |
Arable_land_hectares |
Arable_land_hectares | float | 0% | 1 | 2000.0 |
Arable_land_hectares_per_person |
Arable_land_hectares_per_person | float | 0% | 1 | 0.00026538925969666 |
Arable_land_pct_of_land_area |
Arable_land_pct_of_land_area | float | 0% | 1 | 1.9047619047619 |
Land_under_cereal_production_hectares |
Land_under_cereal_production_hectares | float | 0% | 1 | 0.0 |
Permanent_cropland_pct_of_land_area |
Permanent_cropland_pct_of_land_area | float | 0% | 1 | 0.952380952380952 |
Rural_land_area_where_elevation_is_below_5_meters_sq._km |
Rural_land_area_where_elevation_is_below_5_meters_sq._km | float | 0% | 1 | 74.9537466205 |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area | float | 0% | 1 | 6.76533067761933 |
Rural_land_area_sq._km |
Rural_land_area_sq._km | float | 0% | 1 | 591.19585189281 |
Cereal_production_metric_tons |
Cereal_production_metric_tons | float | 0% | 1 | 0.06 |
Crop_production_index_2014-2016_=_100 |
Crop_production_index_2014-2016_=_100 | float | 0% | 1 | 101.49 |
Food_production_index_2014-2016_=_100 |
Food_production_index_2014-2016_=_100 | float | 0% | 1 | 141.66 |
Livestock_production_index_2014-2016_=_100 |
Livestock_production_index_2014-2016_=_100 | float | 0% | 1 | 149.97 |
Access_to_electricity_rural_pct_of_rural_population |
Access_to_electricity_rural_pct_of_rural_population | float | 0% | 1 | 100.0 |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ | float | 0% | 1 | 0.555621452880751 |
Agriculture_forestry_and_fishing_value_added_current_USusd |
Agriculture_forestry_and_fishing_value_added_current_USusd | float | 0% | 1 | 152361025.665208 |
Agriculture_forestry_and_fishing_value_added_pct_of_GDP |
Agriculture_forestry_and_fishing_value_added_pct_of_GDP | float | 0% | 1 | 0.0374477102095245 |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 0.104659514309261 |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate | float | 0% | 1 | 0.264712552443588 |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate | float | 0% | 1 | 0.182377495822408 |
Rural_population_growth_annual_pct |
Rural_population_growth_annual_pct | float | 0% | 1 | -172.328531479259 |
Rural_population_pct_of_total_population |
Rural_population_pct_of_total_population | float | 0% | 1 | 0.0 |
Agricultural_raw_materials_imports_pct_of_merchandise_imports |
Agricultural_raw_materials_imports_pct_of_merchandise_imports | float | 0% | 1 | 0.0913335982064106 |
Agricultural_raw_materials_exports_pct_of_merchandise_exports |
Agricultural_raw_materials_exports_pct_of_merchandise_exports | float | 0% | 1 | 0.0307288054098069 |
Grants_excluding_technical_cooperation_BoP_current_USusd |
Grants_excluding_technical_cooperation_BoP_current_USusd | float | 0% | 1 | 3270000.0 |
Technical_cooperation_grants_BoP_current_USusd |
Technical_cooperation_grants_BoP_current_USusd | float | 0% | 1 | 10250000.0 |
Net_bilateral_aid_flows_from_DAC_donors_Australia_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Australia_current_USusd | float | 0% | 1 | 119999.997317791 |
Net_bilateral_aid_flows_from_DAC_donors_Austria_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Austria_current_USusd | float | 0% | 1 | 70000.0002980232 |
Net_bilateral_aid_flows_from_DAC_donors_Belgium_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Belgium_current_USusd | float | 0% | 1 | 50000.0007450581 |
| +1663 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
School_enrollment_primary_pct_gross |
Primary enrollment rate percent | float | SEL | 0% | 1 | 103.152955896153 |
School_enrollment_secondary_pct_gross |
Secondary enrollment rate percent | float | SEL | 0% | 1 | 107.160326941213 |
School_enrollment_tertiary_pct_gross |
Tertiary enrollment rate percent | float | SEL | 0% | 1 | 120.08978583196 |
Government_expenditure_on_education_total_pct_of_GDP |
Education expenditure percent gdp | float | SEL | 0% | 1 | 3.80804991722107 |
Unemployment_total_pct_of_total_labor_force_modeled_ILO_estimate |
Unemployment rate percent | float | SEL | 0% | 1 | 2.799 |
Population_ages_0-14_pct_of_total_population |
Population 0 14 percent | float | SEL | 0% | 1 | 10.5078221116522 |
Population_ages_15-64_pct_of_total_population |
Population 15 64 percent | float | SEL | 0% | 1 | 66.8250300290246 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education | float | 0% | 1 | 0.0 |
Barro-Lee:_Percentage_of_population_age_15-19_with_no_education |
Barro-Lee:_Percentage_of_population_age_15-19_with_no_education | float | 0% | 1 | 0.0 |
Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education | float | 0% | 1 | 7.54 |
Barro-Lee:_Percentage_of_population_age_15+_with_no_education |
Barro-Lee:_Percentage_of_population_age_15+_with_no_education | float | 0% | 1 | 5.38 |
Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education | float | 0% | 1 | 0.0 |
Barro-Lee:_Percentage_of_population_age_20-24_with_no_education |
Barro-Lee:_Percentage_of_population_age_20-24_with_no_education | float | 0% | 1 | 0.0 |
Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education | float | 0% | 1 | 0.0 |
Barro-Lee:_Percentage_of_population_age_25-29_with_no_education |
Barro-Lee:_Percentage_of_population_age_25-29_with_no_education | float | 0% | 1 | 0.11 |
Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education | float | 0% | 1 | 8.71 |
Barro-Lee:_Percentage_of_population_age_25+_with_no_education |
Barro-Lee:_Percentage_of_population_age_25+_with_no_education | float | 0% | 1 | 6.28 |
Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education | float | 0% | 1 | 0.31 |
Barro-Lee:_Percentage_of_population_age_30-34_with_no_education |
Barro-Lee:_Percentage_of_population_age_30-34_with_no_education | float | 0% | 1 | 0.22 |
Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education | float | 0% | 1 | 0.59 |
Barro-Lee:_Percentage_of_population_age_35-39_with_no_education |
Barro-Lee:_Percentage_of_population_age_35-39_with_no_education | float | 0% | 1 | 0.45 |
Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education | float | 0% | 1 | 0.59 |
Barro-Lee:_Percentage_of_population_age_40-44_with_no_education |
Barro-Lee:_Percentage_of_population_age_40-44_with_no_education | float | 0% | 1 | 0.45 |
Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education | float | 0% | 1 | 2.25 |
Barro-Lee:_Percentage_of_population_age_45-49_with_no_education |
Barro-Lee:_Percentage_of_population_age_45-49_with_no_education | float | 0% | 1 | 1.49 |
Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education | float | 0% | 1 | 2.25 |
Barro-Lee:_Percentage_of_population_age_50-54_with_no_education |
Barro-Lee:_Percentage_of_population_age_50-54_with_no_education | float | 0% | 1 | 1.49 |
Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education | float | 0% | 1 | 8.06 |
Barro-Lee:_Percentage_of_population_age_55-59_with_no_education |
Barro-Lee:_Percentage_of_population_age_55-59_with_no_education | float | 0% | 1 | 5.39 |
Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education | float | 0% | 1 | 8.06 |
Barro-Lee:_Percentage_of_population_age_60-64_with_no_education |
Barro-Lee:_Percentage_of_population_age_60-64_with_no_education | float | 0% | 1 | 5.39 |
Barro-Lee:_Population_in_thousands_age_15-19_total |
Barro-Lee:_Population_in_thousands_age_15-19_total | float | 0% | 1 | 401.0 |
Barro-Lee:_Population_in_thousands_age_15-19_female |
Barro-Lee:_Population_in_thousands_age_15-19_female | float | 0% | 1 | 200.0 |
Barro-Lee:_Population_in_thousands_age_15+_total |
Barro-Lee:_Population_in_thousands_age_15+_total | float | 0% | 1 | 6429.0 |
Barro-Lee:_Population_in_thousands_age_15+_female |
Barro-Lee:_Population_in_thousands_age_15+_female | float | 0% | 1 | 3451.0 |
Barro-Lee:_Population_in_thousands_age_20-24_total |
Barro-Lee:_Population_in_thousands_age_20-24_total | float | 0% | 1 | 450.0 |
Barro-Lee:_Population_in_thousands_age_20-24_female |
Barro-Lee:_Population_in_thousands_age_20-24_female | float | 0% | 1 | 228.0 |
| +798 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
Contraceptive_prevalence_any_method_pct_of_married_women_ages_15-49 |
Contraception any percent | float | SEL | 0% | 1 | 66.7 |
Fertility_rate_total_births_per_woman |
Fertility rate | float | SEL | 0% | 1 | 0.751 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Firms_with_female_top_manager_pct_of_firms |
Firms_with_female_top_manager_pct_of_firms | float | 0% | 1 | 43.64096451 |
Firms_with_female_participation_in_ownership_pct_of_firms |
Firms_with_female_participation_in_ownership_pct_of_firms | float | 0% | 1 | 37.14170837 |
School_enrollment_primary_gross_gender_parity_index_GPI |
School_enrollment_primary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.042799949646 |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.01925003528595 |
School_enrollment_secondary_gross_gender_parity_index_GPI |
School_enrollment_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.994069993495941 |
School_enrollment_tertiary_gross_gender_parity_index_GPI |
School_enrollment_tertiary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.09234325401374 |
School_enrollment_preprimary_female_pct_gross |
School_enrollment_preprimary_female_pct_gross | float | 0% | 1 | 96.0097808837891 |
School_enrollment_preprimary_male_pct_gross |
School_enrollment_preprimary_male_pct_gross | float | 0% | 1 | 91.5473098754883 |
Primary_completion_rate_female_pct_of_relevant_age_group |
Primary_completion_rate_female_pct_of_relevant_age_group | float | 0% | 1 | 90.7207792207792 |
Primary_completion_rate_male_pct_of_relevant_age_group |
Primary_completion_rate_male_pct_of_relevant_age_group | float | 0% | 1 | 92.5840978593272 |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc | float | 0% | 1 | 100.0 |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ | float | 0% | 1 | 100.0 |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct | float | 0% | 1 | 100.0 |
Primary_education_pupils_pct_female |
Primary_education_pupils_pct_female | float | 0% | 1 | 47.79839 |
School_enrollment_primary_female_pct_gross |
School_enrollment_primary_female_pct_gross | float | 0% | 1 | 101.573264781491 |
School_enrollment_primary_male_pct_gross |
School_enrollment_primary_male_pct_gross | float | 0% | 1 | 104.650822669104 |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag | float | 0% | 1 | 117.2294 |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ | float | 0% | 1 | 110.50432 |
School_enrollment_primary_female_pct_net |
School_enrollment_primary_female_pct_net | float | 0% | 1 | 94.16782 |
School_enrollment_primary_male_pct_net |
School_enrollment_primary_male_pct_net | float | 0% | 1 | 93.46964 |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population | float | 0% | 1 | 89.06373 |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population | float | 0% | 1 | 81.05459 |
Persistence_to_grade_5_female_pct_of_cohort |
Persistence_to_grade_5_female_pct_of_cohort | float | 0% | 1 | 96.778450012207 |
Persistence_to_grade_5_male_pct_of_cohort |
Persistence_to_grade_5_male_pct_of_cohort | float | 0% | 1 | 98.3544082641602 |
Persistence_to_last_grade_of_primary_female_pct_of_cohort |
Persistence_to_last_grade_of_primary_female_pct_of_cohort | float | 0% | 1 | 94.8337097167969 |
Persistence_to_last_grade_of_primary_male_pct_of_cohort |
Persistence_to_last_grade_of_primary_male_pct_of_cohort | float | 0% | 1 | 96.2746887207031 |
Repeaters_primary_female_pct_of_female_enrollment |
Repeaters_primary_female_pct_of_female_enrollment | float | 0% | 1 | 0.36839 |
Repeaters_primary_male_pct_of_male_enrollment |
Repeaters_primary_male_pct_of_male_enrollment | float | 0% | 1 | 0.43317 |
Trained_teachers_in_primary_education_female_pct_of_female_teachers |
Trained_teachers_in_primary_education_female_pct_of_female_teachers | float | 0% | 1 | 94.0331799804824 |
Trained_teachers_in_primary_education_male_pct_of_male_teachers |
Trained_teachers_in_primary_education_male_pct_of_male_teachers | float | 0% | 1 | 92.0325203252033 |
| +102 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
Land_area_sq._km |
Area land sqkm | float | SEL | 0% | 1 | 33.0 |
Surface_area_sq._km |
Area sqkm | float | SEL | 0% | 1 | 33.0 |
Rural_population |
Rural population | float | SEL | 0% | 1 | 0.0 |
GDP_current_USusd |
Gdp total usd | float | SEL | 0% | 1 | 49467258923.3244 |
GDP_per_capita_current_USusd |
Gdp per capita usd | float | SEL | 0% | 1 | 72004.7437020733 |
Literacy_rate_adult_total_pct_of_people_ages_15_and_above |
Literacy rate percent | float | SEL | 0% | 1 | 96.5400009155273 |
School_enrollment_primary_pct_gross |
Primary enrollment rate percent | float | SEL | 0% | 1 | 89.8103044496487 |
School_enrollment_secondary_pct_gross |
Secondary enrollment rate percent | float | SEL | 0% | 1 | 94.6616766467066 |
School_enrollment_tertiary_pct_gross |
Tertiary enrollment rate percent | float | SEL | 0% | 1 | 141.864795918367 |
Government_expenditure_on_education_total_pct_of_GDP |
Education expenditure percent gdp | float | SEL | 0% | 1 | 3.50183010101318 |
Unemployment_total_pct_of_total_labor_force_modeled_ILO_estimate |
Unemployment rate percent | float | SEL | 0% | 1 | 2.347 |
Population_ages_0-14_pct_of_total_population |
Population 0 14 percent | float | SEL | 0% | 1 | 13.910146585548 |
Population_ages_15-64_pct_of_total_population |
Population 15 64 percent | float | SEL | 0% | 1 | 71.8214344224741 |
Access_to_electricity_pct_of_population |
Electricity access percent | float | SEL | 0% | 1 | 100.0 |
People_using_safely_managed_drinking_water_services_pct_of_population |
Safe drinking water percent | float | SEL | 0% | 1 | 100.0 |
People_using_at_least_basic_sanitation_services_pct_of_population |
Basic sanitation percent | float | SEL | 0% | 1 | 100.0 |
People_practicing_open_defecation_pct_of_population |
Open defecation percent | float | SEL | 0% | 1 | 0.0 |
Hospital_beds_per_1000_people |
Hospital beds per 1000 | float | SEL | 0% | 1 | 5.29530000686646 |
Physicians_per_1000_people |
Physicians per 1000 | float | SEL | 0% | 1 | 1.562 |
Prevalence_of_undernourishment_pct_of_population |
Undernourishment percent | float | SEL | 0% | 1 | 11.2 |
Birth_rate_crude_per_1000_people |
Birth rate per 1000 | float | SEL | 0% | 1 | 5.5 |
Death_rate_crude_per_1000_people |
Death rate per 1000 | float | SEL | 0% | 1 | 4.4 |
Life_expectancy_at_birth_total_years |
Life expectancy | float | SEL | 0% | 1 | 83.1804878048781 |
Fertility_rate_total_births_per_woman |
Fertility rate | float | SEL | 0% | 1 | 0.586 |
Population_ages_0-14_total |
Population 0 14 | float | SEL | 0% | 1 | 95563.0 |
Population_ages_15-64_total |
Population 15 64 | float | SEL | 0% | 1 | 493413.0 |
Population_ages_65_and_above_total |
Population 65 plus | float | SEL | 0% | 1 | 98024.0 |
Population_ages_65_and_above_pct_of_total_population |
Population 65 plus percent | float | SEL | 0% | 1 | 14.2684189919779 |
Population_growth_annual_pct |
Population growth rate percent | float | SEL | 0% | 1 | 1.20077588622782 |
| +13 more standards-aligned fields — download the CSV/Parquet to see them all. | ||||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Rural_land_area_where_elevation_is_below_5_meters_sq._km |
Rural_land_area_where_elevation_is_below_5_meters_sq._km | float | 0% | 1 | 3.57163106359 |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area |
Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area | float | 0% | 1 | 14.095617461755 |
Rural_land_area_sq._km |
Rural_land_area_sq._km | float | 0% | 1 | 7.5741654768354 |
Crop_production_index_2014-2016_=_100 |
Crop_production_index_2014-2016_=_100 | float | 0% | 1 | 103.18 |
Food_production_index_2014-2016_=_100 |
Food_production_index_2014-2016_=_100 | float | 0% | 1 | 81.34 |
Livestock_production_index_2014-2016_=_100 |
Livestock_production_index_2014-2016_=_100 | float | 0% | 1 | 73.39 |
Access_to_electricity_rural_pct_of_rural_population |
Access_to_electricity_rural_pct_of_rural_population | float | 0% | 1 | 100.0 |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ |
Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ | float | 0% | 1 | 0.772778435373717 |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate |
Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 0.33160896670646 |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate |
Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate | float | 0% | 1 | 0.417951590992474 |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate | float | 0% | 1 | 0.373797814869546 |
Rural_population_growth_annual_pct |
Rural_population_growth_annual_pct | float | 0% | 1 | -120.397280432594 |
Rural_population_pct_of_total_population |
Rural_population_pct_of_total_population | float | 0% | 1 | 0.0 |
Agricultural_raw_materials_imports_pct_of_merchandise_imports |
Agricultural_raw_materials_imports_pct_of_merchandise_imports | float | 0% | 1 | 0.142749528079388 |
Agricultural_raw_materials_exports_pct_of_merchandise_exports |
Agricultural_raw_materials_exports_pct_of_merchandise_exports | float | 0% | 1 | 0.408785558205904 |
Grants_excluding_technical_cooperation_BoP_current_USusd |
Grants_excluding_technical_cooperation_BoP_current_USusd | float | 0% | 1 | 0.0 |
Technical_cooperation_grants_BoP_current_USusd |
Technical_cooperation_grants_BoP_current_USusd | float | 0% | 1 | 320000.0 |
Net_bilateral_aid_flows_from_DAC_donors_Australia_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Australia_current_USusd | float | 0% | 1 | 9999.99977648258 |
Net_bilateral_aid_flows_from_DAC_donors_European_Union_institutions_current_USus |
Net_bilateral_aid_flows_from_DAC_donors_European_Union_institutions_current_USus | float | 0% | 1 | 360000.014305115 |
Net_bilateral_aid_flows_from_DAC_donors_Switzerland_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Switzerland_current_USusd | float | 0% | 1 | 9999.99977648258 |
Net_bilateral_aid_flows_from_DAC_donors_Germany_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Germany_current_USusd | float | 0% | 1 | 19999.9995529652 |
Net_bilateral_aid_flows_from_DAC_donors_France_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_France_current_USusd | float | 0% | 1 | 9999.99977648258 |
Net_bilateral_aid_flows_from_DAC_donors_Japan_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Japan_current_USusd | float | 0% | 1 | 209999.993443489 |
Net_bilateral_aid_flows_from_DAC_donors_Netherlands_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Netherlands_current_USusd | float | 0% | 1 | 70000.0002980232 |
Net_bilateral_aid_flows_from_DAC_donors_Norway_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Norway_current_USusd | float | 0% | 1 | 50000.0007450581 |
Net_bilateral_aid_flows_from_DAC_donors_Portugal_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Portugal_current_USusd | float | 0% | 1 | 70000.0002980232 |
Net_bilateral_aid_flows_from_DAC_donors_Sweden_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Sweden_current_USusd | float | 0% | 1 | 9999.99977648258 |
Net_bilateral_aid_flows_from_DAC_donors_Total_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_Total_current_USusd | float | 0% | 1 | 9999.99977648258 |
Net_bilateral_aid_flows_from_DAC_donors_United_States_current_USusd |
Net_bilateral_aid_flows_from_DAC_donors_United_States_current_USusd | float | 0% | 1 | 19999.9995529652 |
Net_official_flows_from_UN_agencies_IFAD_current_USusd |
Net_official_flows_from_UN_agencies_IFAD_current_USusd | float | 0% | 1 | -4219999.79019165 |
| +1544 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
Literacy_rate_adult_total_pct_of_people_ages_15_and_above |
Literacy rate percent | float | SEL | 0% | 1 | 96.5400009155273 |
School_enrollment_primary_pct_gross |
Primary enrollment rate percent | float | SEL | 0% | 1 | 89.8103044496487 |
School_enrollment_secondary_pct_gross |
Secondary enrollment rate percent | float | SEL | 0% | 1 | 94.6616766467066 |
School_enrollment_tertiary_pct_gross |
Tertiary enrollment rate percent | float | SEL | 0% | 1 | 141.864795918367 |
Government_expenditure_on_education_total_pct_of_GDP |
Education expenditure percent gdp | float | SEL | 0% | 1 | 3.50183010101318 |
Unemployment_total_pct_of_total_labor_force_modeled_ILO_estimate |
Unemployment rate percent | float | SEL | 0% | 1 | 2.347 |
Population_ages_0-14_pct_of_total_population |
Population 0 14 percent | float | SEL | 0% | 1 | 13.910146585548 |
Population_ages_15-64_pct_of_total_population |
Population 15 64 percent | float | SEL | 0% | 1 | 71.8214344224741 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education | float | 0% | 1 | 0.14 |
Barro-Lee:_Percentage_of_population_age_15-19_with_no_education |
Barro-Lee:_Percentage_of_population_age_15-19_with_no_education | float | 0% | 1 | 0.12 |
Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education | float | 0% | 1 | 4.43 |
Barro-Lee:_Percentage_of_population_age_15+_with_no_education |
Barro-Lee:_Percentage_of_population_age_15+_with_no_education | float | 0% | 1 | 3.46 |
Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education | float | 0% | 1 | 2.98 |
Barro-Lee:_Percentage_of_population_age_20-24_with_no_education |
Barro-Lee:_Percentage_of_population_age_20-24_with_no_education | float | 0% | 1 | 4.44 |
Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education | float | 0% | 1 | 0.18 |
Barro-Lee:_Percentage_of_population_age_25-29_with_no_education |
Barro-Lee:_Percentage_of_population_age_25-29_with_no_education | float | 0% | 1 | 0.11 |
Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education | float | 0% | 1 | 5.13 |
Barro-Lee:_Percentage_of_population_age_25+_with_no_education |
Barro-Lee:_Percentage_of_population_age_25+_with_no_education | float | 0% | 1 | 3.75 |
Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education | float | 0% | 1 | 0.13 |
Barro-Lee:_Percentage_of_population_age_30-34_with_no_education |
Barro-Lee:_Percentage_of_population_age_30-34_with_no_education | float | 0% | 1 | 0.15 |
Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education | float | 0% | 1 | 0.57 |
Barro-Lee:_Percentage_of_population_age_35-39_with_no_education |
Barro-Lee:_Percentage_of_population_age_35-39_with_no_education | float | 0% | 1 | 0.58 |
Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education | float | 0% | 1 | 0.93 |
Barro-Lee:_Percentage_of_population_age_40-44_with_no_education |
Barro-Lee:_Percentage_of_population_age_40-44_with_no_education | float | 0% | 1 | 0.75 |
Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education | float | 0% | 1 | 1.31 |
Barro-Lee:_Percentage_of_population_age_45-49_with_no_education |
Barro-Lee:_Percentage_of_population_age_45-49_with_no_education | float | 0% | 1 | 1.04 |
Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education | float | 0% | 1 | 4.32 |
Barro-Lee:_Percentage_of_population_age_50-54_with_no_education |
Barro-Lee:_Percentage_of_population_age_50-54_with_no_education | float | 0% | 1 | 2.87 |
Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education | float | 0% | 1 | 5.45 |
Barro-Lee:_Percentage_of_population_age_55-59_with_no_education |
Barro-Lee:_Percentage_of_population_age_55-59_with_no_education | float | 0% | 1 | 3.7 |
Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education |
Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education | float | 0% | 1 | 10.04 |
Barro-Lee:_Percentage_of_population_age_60-64_with_no_education |
Barro-Lee:_Percentage_of_population_age_60-64_with_no_education | float | 0% | 1 | 6.61 |
Barro-Lee:_Population_in_thousands_age_15-19_total |
Barro-Lee:_Population_in_thousands_age_15-19_total | float | 0% | 1 | 35.0 |
Barro-Lee:_Population_in_thousands_age_15-19_female |
Barro-Lee:_Population_in_thousands_age_15-19_female | float | 0% | 1 | 17.0 |
Barro-Lee:_Population_in_thousands_age_15+_total |
Barro-Lee:_Population_in_thousands_age_15+_total | float | 0% | 1 | 416.0 |
Barro-Lee:_Population_in_thousands_age_15+_female |
Barro-Lee:_Population_in_thousands_age_15+_female | float | 0% | 1 | 218.0 |
Barro-Lee:_Population_in_thousands_age_20-24_total |
Barro-Lee:_Population_in_thousands_age_20-24_total | float | 0% | 1 | 43.0 |
Barro-Lee:_Population_in_thousands_age_20-24_female |
Barro-Lee:_Population_in_thousands_age_20-24_female | float | 0% | 1 | 21.0 |
| +787 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
Fertility_rate_total_births_per_woman |
Fertility rate | float | SEL | 0% | 1 | 0.586 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Literacy_rate_youth_female_pct_of_females_ages_15-24 |
Literacy_rate_youth_female_pct_of_females_ages_15-24 | float | 0% | 1 | 99.870002746582 |
Literacy_rate_youth_ages_15-24_gender_parity_index_GPI |
Literacy_rate_youth_ages_15-24_gender_parity_index_GPI | float | 0% | 1 | 1.0 |
Literacy_rate_youth_male_pct_of_males_ages_15-24 |
Literacy_rate_youth_male_pct_of_males_ages_15-24 | float | 0% | 1 | 99.7300033569336 |
Literacy_rate_adult_female_pct_of_females_ages_15_and_above |
Literacy_rate_adult_female_pct_of_females_ages_15_and_above | float | 0% | 1 | 95.0299987792969 |
Literacy_rate_adult_male_pct_of_males_ages_15_and_above |
Literacy_rate_adult_male_pct_of_males_ages_15_and_above | float | 0% | 1 | 98.1900024414062 |
School_enrollment_primary_gross_gender_parity_index_GPI |
School_enrollment_primary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.978659987449646 |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.98633998632431 |
School_enrollment_secondary_gross_gender_parity_index_GPI |
School_enrollment_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.996479988098145 |
School_enrollment_tertiary_gross_gender_parity_index_GPI |
School_enrollment_tertiary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.10614641930701 |
School_enrollment_preprimary_female_pct_gross |
School_enrollment_preprimary_female_pct_gross | float | 0% | 1 | 84.9695281982422 |
School_enrollment_preprimary_male_pct_gross |
School_enrollment_preprimary_male_pct_gross | float | 0% | 1 | 87.769660949707 |
Primary_completion_rate_female_pct_of_relevant_age_group |
Primary_completion_rate_female_pct_of_relevant_age_group | float | 0% | 1 | 93.9090909090909 |
Primary_completion_rate_male_pct_of_relevant_age_group |
Primary_completion_rate_male_pct_of_relevant_age_group | float | 0% | 1 | 94.3243243243243 |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc |
Educational_attainment_at_least_completed_primary_population_25+_years_female_pc | float | 0% | 1 | 87.8000030517578 |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ |
Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_ | float | 0% | 1 | 92.0599975585938 |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct |
Educational_attainment_at_least_completed_primary_population_25+_years_total_pct | float | 0% | 1 | 89.8300018310547 |
Primary_education_pupils_pct_female |
Primary_education_pupils_pct_female | float | 0% | 1 | 48.17859 |
School_enrollment_primary_female_pct_gross |
School_enrollment_primary_female_pct_gross | float | 0% | 1 | 89.8774509803922 |
School_enrollment_primary_male_pct_gross |
School_enrollment_primary_male_pct_gross | float | 0% | 1 | 89.7488789237668 |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag |
Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag | float | 0% | 1 | 95.57895 |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ |
Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_ | float | 0% | 1 | 93.60158 |
School_enrollment_primary_female_pct_net |
School_enrollment_primary_female_pct_net | float | 0% | 1 | 96.39243 |
School_enrollment_primary_male_pct_net |
School_enrollment_primary_male_pct_net | float | 0% | 1 | 96.39843 |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population | float | 0% | 1 | 91.15789 |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population |
Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population | float | 0% | 1 | 88.29156 |
Persistence_to_grade_5_female_pct_of_cohort |
Persistence_to_grade_5_female_pct_of_cohort | float | 0% | 1 | 99.2282485961914 |
Persistence_to_grade_5_male_pct_of_cohort |
Persistence_to_grade_5_male_pct_of_cohort | float | 0% | 1 | 99.8556213378906 |
Persistence_to_last_grade_of_primary_female_pct_of_cohort |
Persistence_to_last_grade_of_primary_female_pct_of_cohort | float | 0% | 1 | 99.1962509155273 |
Persistence_to_last_grade_of_primary_male_pct_of_cohort |
Persistence_to_last_grade_of_primary_male_pct_of_cohort | float | 0% | 1 | 99.4566497802734 |
Repeaters_primary_female_pct_of_female_enrollment |
Repeaters_primary_female_pct_of_female_enrollment | float | 0% | 1 | 1.29343 |
| +99 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHN |
Population_density_people_per_sq._km_of_land_area |
Population density | float | SEL | 0% | 1 | 20569.696969697 |
Urban_population_growth_annual_pct |
Urban growth rate percent | float | SEL | 0% | 1 | 1.2007758862278 |
Urban_population |
Urban population | float | SEL | 0% | 1 | 687000.0 |
Urban_population_pct_of_total_population |
Urban population percent | float | SEL | 0% | 1 | 100.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Urban_land_area_where_elevation_is_below_5_meters_sq._km |
Urban_land_area_where_elevation_is_below_5_meters_sq._km | float | 0% | 1 | 8.30704187323 |
Urban_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area |
Urban_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area | float | 0% | 1 | 32.7841488661865 |
Urban_land_area_sq._km |
Urban_land_area_sq._km | float | 0% | 1 | 17.764426984834 |
Access_to_electricity_urban_pct_of_urban_population |
Access_to_electricity_urban_pct_of_urban_population | float | 0% | 1 | 100.0 |
Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ |
Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_ | float | 0% | 1 | 16.4565015811634 |
Population_in_largest_city |
Population_in_largest_city | float | 0% | 1 | 701381.0 |
Population_in_the_largest_city_pct_of_urban_population |
Population_in_the_largest_city_pct_of_urban_population | float | 0% | 1 | 100.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | 0% | 1 | CHN |
inform_aff_dr |
People affected by drought (absolute) - raw | float | 0% | 1 | 13174285.7142857 |
inform_aff_dr_freq |
Frequency of Droughts events | float | 0% | 1 | 0.685714285714286 |
inform_aff_dr_rel |
People affected by droughts (relative) - raw | float | 0% | 1 | 0.924912447448729 |
inform_ag_lnd_totl_k2 |
Land area (sq. km) | float | 0% | 1 | 9327489.9 |
inform_asi |
Agriculture Stress Index Probability | float | 0% | 1 | 0.0 |
inform_bx_trf_pwkr_dt_gd_zs_inst |
Remittences Instability | float | 0% | 1 | 0.00741865777961795 |
inform_bx_trf_pwkr_dt_gd_zs_inst_norm |
ODA % GNI Normalized [BX.TRF.PWKR.DT.GD.ZS.INST.NORM] | float | 0% | 1 | 1.2 |
inform_bx_trf_pwkr |
Personal remittances, received (% of GDP) | float | 0% | 1 | 0.153874754905701 |
inform_lack_of_coping_capacity |
Lack of Coping Capacity Index | float | 0% | 1 | 3.0 |
inform_infrastructure_capacity |
Infrastructure | float | 0% | 1 | 2.2 |
inform_cc_inf_ahc |
Access to Health Care | float | 0% | 1 | 2.0 |
inform_cc_inf_ahc_health_exp |
Health expenditure per capita [CC.INF.AHC.HEALTH-EXP] | float | 0% | 1 | 5.1 |
inform_cc_inf_ahc_imm |
Immunization coverage | float | 0% | 1 | 0.5 |
inform_cc_inf_ahc_imm_dtp3 |
Diphtheria-Tetanus-Pertussis | float | 0% | 1 | 0.3 |
inform_cc_inf_ahc_imm_mcv2 |
Measles | float | 0% | 1 | 0.7 |
inform_cc_inf_ahc_mmr |
Maternal Mortality Ratio [CC.INF.AHC.MMR] | float | 0% | 1 | 0.2 |
inform_cc_inf_ahc_phys |
Physicians density [CC.INF.AHC.PHYS] | float | 0% | 1 | 2.2 |
inform_cc_inf_com |
Communication | float | 0% | 1 | 1.3 |
inform_cc_inf_com_cel |
Mobile cellular subscriptions [CC.INF.COM.CEL] | float | 0% | 1 | 3.5 |
inform_cc_inf_com_elaccs |
Access to electricity [CC.INF.COM.ELACCS] | float | 0% | 1 | 0.0 |
inform_cc_inf_com_litr |
Adult literacy rate | float | 0% | 1 | 0.7 |
inform_cc_inf_com_netus |
Internet users [CC.INF.COM.NETUS] | float | 0% | 1 | 0.8 |
inform_cc_inf_phy |
Physical Infrastructure | float | 0% | 1 | 3.4 |
inform_cc_inf_phy_h2o |
Access to improved water source | float | 0% | 1 | 0.8 |
inform_cc_inf_phy_rod |
Road density [CC.INF.PHY.ROD] | float | 0% | 1 | 9.0 |
inform_cc_inf_phy_sta |
Access to improved sanitation facilities | float | 0% | 1 | 0.3 |
inform_institutional_capacity |
Institutional | float | 0% | 1 | 3.8 |
inform_cc_ins_drr |
Disaster Risk Reduction | float | 0% | 1 | 3.0 |
inform_cc_ins_drr_sg_dsr_lgrgsr |
Disaster Risk Reduction SG_DSR_LGRGSR [CC.INS.DRR.SG_DSR_LGRGSR] | float | 0% | 1 | 0.0 |
| +237 more pending fields — download the CSV/Parquet to see them all. | |||||
Which languages name the landscape here, and in which writing systems. A language's toponymic footprint and its speaker population are different measures and often diverge. Counts include variant and foreign-language renderings of the same place, so a language can rank high because outside sources record names in it rather than because it is spoken locally — and a widely spoken language can be almost absent where official naming is in another language.
| Language | Place names | Share* | Script |
|---|---|---|---|
| Chinese (zho) | 557,974 | 98.7% | Han (Simplified variant) +3 |
| Tibetan (bod) | 6,149 | 1.1% | — |
| English (eng) | 638 | 0.1% | — |
| + 12 further languages (364 names, each under 0.05%) | |||
283,208 distinct features ·
15 languages ·
6 scripts ·
290,501 names in non-Roman script ·
13 conventional English names
Source: NGA GEOnet Names Server
(public domain) · rebuilt Mon, 21 Sep 2026.
* Shares are of the
565,125 names that carry a language
code; the remaining 32,673 of
597,798 are unattributed, so these
percentages do not divide into the headline count.
Names follow the US/BGN convention.
The data providers this country's datasets are sourced from — each links out to the provider.
Pick datasets and admin level(s). You'll get a .zip with one CSV per dataset, each filtered to the levels you choose.