Japan
JPN
Mount Fuji · Photo: Midori /
CC BY 3.0
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610,279
Records
23
Datasets
74
Tables
16
Sources
272
SEL Fields
66
CCL Fields
📋
Most recent national census: 2025.
HERA carries the
2020 round — the 2025 census is not yet
ingested (results may still be in staged release, or the source isn't published in a
machine-readable form yet). The figures below are 2020.
Loading overview…
Datasets (23)
SEL — DGIWG Statistical Extent Location
SEL+ — Platform extension (not in DGIWG core spec)
CCL — DGIWG Cultural Context Location
Extension — Preserved in extension tables (not in core SEL/CCL schema)
Pending — Awaiting mapping
JPN e-Stat (Japan Statistics Portal)
JPN-ESTAT
Census
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 13 table(s)
JPN e-Stat - Demographics Wide (admin_0)
— 1 rows, 98 columns
Loading data…
Field details — 98 fields (type, nulls, unique, samples)
Standards-Aligned Fields (2)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 1 | 00000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN |
Extension Fields (96)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
#D0110101_Financial_power_index_Prefecture |
Financial power index Prefecture | float | 0% | 1 | 0.494 |
#D0110101_Financial_power_index_Prefecture_time |
Financial power index Prefecture (survey year) | float | 0% | 1 | 2022 |
#D01102_Real_term_balance_of_revenue_to_expenditure_Prefectu |
Real term balance of revenue to expenditure Prefectu | float | 0% | 1 | 3.1 |
#D01102_Real_term_balance_of_revenue_to_expenditure_Prefectu_time |
Real term balance of revenue to expenditure Prefectu (survey year) | float | 0% | 1 | 2022 |
#D0120101_Percentage_of_self-financial_resources_Prefecture |
Percentage of self-financial resources Prefecture | float | 0% | 1 | 55.9 |
#D0120101_Percentage_of_self-financial_resources_Prefecture_time |
Percentage of self-financial resources Prefecture (survey year) | float | 0% | 1 | 2022 |
#D0130201_Percentage_of_outstanding_amount_of_local_bonds_to |
Percentage of outstanding amount of local bonds to | float | 0% | 1 | 139.4 |
#D0130201_Percentage_of_outstanding_amount_of_local_bonds_to_time |
Percentage of outstanding amount of local bonds to (survey year) | float | 0% | 1 | 2022 |
#D01401_Real_term_of_current_balance_Prefecture |
Real term of current balance Prefecture | float | 0% | 1 | 93.3 |
#D01401_Real_term_of_current_balance_Prefecture_time |
Real term of current balance Prefecture (survey year) | float | 0% | 1 | 2022 |
#D0140201_Percentage_of_investment_expenditure_Prefecture |
Percentage of investment expenditure Prefecture | float | 0% | 1 | 13.1 |
#D0140201_Percentage_of_investment_expenditure_Prefecture_time |
Percentage of investment expenditure Prefecture (survey year) | float | 0% | 1 | 2022 |
#D0140301_Percentage_of_revenues_from_local_taxes_and_grants |
Percentage of revenues from local taxes and grants | float | 0% | 1 | 56.8 |
#D0140301_Percentage_of_revenues_from_local_taxes_and_grants_time |
Percentage of revenues from local taxes and grants (survey year) | float | 0% | 1 | 2022 |
#D0210101_Percentage_of_local_taxes_Prefecture |
Percentage of local taxes Prefecture | float | 0% | 1 | 36.29 |
#D0210101_Percentage_of_local_taxes_Prefecture_time |
Percentage of local taxes Prefecture (survey year) | float | 0% | 1 | 2022 |
#D0210201_Percentage_of_grants_to_local_governments_Prefectu |
Percentage of grants to local governments Prefectu | float | 0% | 1 | 14.95 |
#D0210201_Percentage_of_grants_to_local_governments_Prefectu_time |
Percentage of grants to local governments Prefectu (survey year) | float | 0% | 1 | 2022 |
#D0210301_Percentage_of_national_disbursements_Prefecture |
Percentage of national disbursements Prefecture | float | 0% | 1 | 19.88 |
#D0210301_Percentage_of_national_disbursements_Prefecture_time |
Percentage of national disbursements Prefecture (survey year) | float | 0% | 1 | 2022 |
#D0220103_Resident_tax_per_capita_Prefecture_+_Municipality |
Resident tax per capita Prefecture + Municipality | float | 0% | 1 | 129.5 |
#D0220103_Resident_tax_per_capita_Prefecture_+_Municipality_time |
Resident tax per capita Prefecture + Municipality (survey year) | float | 0% | 1 | 2022 |
#D02202_Fixed_assets_tax_per_capita_Prefecture_+_Municipalit |
Fixed assets tax per capita Prefecture + Municipalit | float | 0% | 1 | 77.4 |
#D02202_Fixed_assets_tax_per_capita_Prefecture_+_Municipalit_time |
Fixed assets tax per capita Prefecture + Municipalit (survey year) | float | 0% | 1 | 2022 |
#D02204_Amount_of_national_tax_per_capita |
Amount of national tax per capita | float | 0% | 1 | 704.7 |
#D02204_Amount_of_national_tax_per_capita_time |
Amount of national tax per capita (survey year) | float | 0% | 1 | 2023 |
#D02206_Taxable_income_per_tax_debtor |
Taxable income per tax debtor | float | 0% | 1 | 3933.7 |
#D02206_Taxable_income_per_tax_debtor_time |
Taxable income per tax debtor (survey year) | float | 0% | 1 | 2024 |
#D02207_Ratio_of_taxpayer_per_capita |
Ratio of taxpayer per capita | float | 0% | 1 | 46.2 |
#D02207_Ratio_of_taxpayer_per_capita_time |
Ratio of taxpayer per capita (survey year) | float | 0% | 1 | 2024 |
| +66 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Education Wide (admin_0)
— 1 rows, 120 columns
Loading data…
Field details — 120 fields (type, nulls, unique, samples)
Standards-Aligned Fields (2)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 1 | 00000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN |
Extension Fields (118)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
D110101_Number_of_cities,_towns_and_villages |
Number of cities, towns and villages | float | 0% | 1 | 1741.0 |
D110101_Number_of_cities,_towns_and_villages_time |
Number of cities, towns and villages (survey year) | float | 0% | 1 | 2024 |
D110102_Number_of_cities_and_wards |
Number of cities and wards | float | 0% | 1 | 986.0 |
D110102_Number_of_cities_and_wards_time |
Number of cities and wards (survey year) | float | 0% | 1 | 2024 |
D110103_Number_of_towns_and_villages |
Number of towns and villages | float | 0% | 1 | 926.0 |
D110103_Number_of_towns_and_villages_time |
Number of towns and villages (survey year) | float | 0% | 1 | 2024 |
D1201_Number_of_general_personnel_Prefecture |
Number of general personnel Prefecture | float | 0% | 1 | 238199.0 |
D1201_Number_of_general_personnel_Prefecture_time |
Number of general personnel Prefecture (survey year) | float | 0% | 1 | 2024 |
D1202_Number_of_general_personnel_Municipality |
Number of general personnel Municipality | float | 0% | 1 | 709421.0 |
D1202_Number_of_general_personnel_Municipality_time |
Number of general personnel Municipality (survey year) | float | 0% | 1 | 2024 |
D1203_Number_of_fire_service_personnel |
Number of fire service personnel | float | 0% | 1 | 165343.0 |
D1203_Number_of_fire_service_personnel_time |
Number of fire service personnel (survey year) | float | 0% | 1 | 2024 |
D1204_Number_of_educational_service_personnel |
Number of educational service personnel | float | 0% | 1 | 1069060.0 |
D1204_Number_of_educational_service_personnel_time |
Number of educational service personnel (survey year) | float | 0% | 1 | 2024 |
D1205_Number_of_police_personnel |
Number of police personnel | float | 0% | 1 | 287631.0 |
D1205_Number_of_police_personnel_time |
Number of police personnel (survey year) | float | 0% | 1 | 2024 |
D1206_Number_of_public_businesses_account_personnel |
Number of public businesses account personnel | float | 0% | 1 | 342095.0 |
D1206_Number_of_public_businesses_account_personnel_time |
Number of public businesses account personnel (survey year) | float | 0% | 1 | 2024 |
D1210_Number_of_prefectural_assembly_members |
Number of prefectural assembly members | float | 0% | 1 | 2614.0 |
D1210_Number_of_prefectural_assembly_members_time |
Number of prefectural assembly members (survey year) | float | 0% | 1 | 2024 |
D1211_Number_of_municipal_assembly_members |
Number of municipal assembly members | float | 0% | 1 | 18389.0 |
D1211_Number_of_municipal_assembly_members_time |
Number of municipal assembly members (survey year) | float | 0% | 1 | 2024 |
D1212_Number_of_electoral_roll_subscribers |
Number of electoral roll subscribers | float | 0% | 1 | 104074483.0 |
D1212_Number_of_electoral_roll_subscribers_time |
Number of electoral roll subscribers (survey year) | float | 0% | 1 | 2024 |
D2101_Financial_power_index_Prefecture |
Financial power index Prefecture | float | 0% | 1 | 0.49378 |
D2101_Financial_power_index_Prefecture_time |
Financial power index Prefecture (survey year) | float | 0% | 1 | 2022 |
D2102_Real_term_balance_of_revenue_to_expenditure_Prefecture |
Real term balance of revenue to expenditure Prefecture | float | 0% | 1 | 3.1 |
D2102_Real_term_balance_of_revenue_to_expenditure_Prefecture_time |
Real term balance of revenue to expenditure Prefecture (survey year) | float | 0% | 1 | 2022 |
D2103_Real_term_of_current_balance_Prefecture |
Real term of current balance Prefecture | float | 0% | 1 | 93.3 |
D2103_Real_term_of_current_balance_Prefecture_time |
Real term of current balance Prefecture (survey year) | float | 0% | 1 | 2022 |
| +88 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Employment Wide (admin_0)
— 1 rows, 684 columns
Loading data…
Field details — 684 fields (type, nulls, unique, samples)
Standards-Aligned Fields (4)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 1 | 00000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN |
F1101_Population_census_Population_in_labour_force |
Population census Population in labour force | float | SEL | 0% | 1 | 59949767.0 |
F1107_Population_census_Number_of_unemployed_persons |
Population census Number of unemployed persons | float | SEL | 0% | 1 | 2306542.0 |
Extension Fields (680)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
F1101_Population_census_Population_in_labour_force_time |
Population census Population in labour force (survey year) | float | 0% | 1 | 2020 |
F110101_Population_census_Population_in_labour_force_Male |
Population census Population in labour force Male | float | 0% | 1 | 32925925.0 |
F110101_Population_census_Population_in_labour_force_Male_time |
Population census Population in labour force Male (survey year) | float | 0% | 1 | 2020 |
F110102_Population_census_Population_in_labour_force_Female |
Population census Population in labour force Female | float | 0% | 1 | 27023842.0 |
F110102_Population_census_Population_in_labour_force_Female_time |
Population census Population in labour force Female (survey year) | float | 0% | 1 | 2020 |
F1102_Population_census_Number_of_employed_persons |
Population census Number of employed persons | float | 0% | 1 | 57643225.0 |
F1102_Population_census_Number_of_employed_persons_time |
Population census Number of employed persons (survey year) | float | 0% | 1 | 2020 |
F110201_Population_census_Number_of_employed_persons_Male |
Population census Number of employed persons Male | float | 0% | 1 | 31501307.0 |
F110201_Population_census_Number_of_employed_persons_Male_time |
Population census Number of employed persons Male (survey year) | float | 0% | 1 | 2020 |
F110202_Population_census_Number_of_employed_persons_Female |
Population census Number of employed persons Female | float | 0% | 1 | 26141918.0 |
F110202_Population_census_Number_of_employed_persons_Female_time |
Population census Number of employed persons Female (survey year) | float | 0% | 1 | 2020 |
F1103_Population_census_Number_of_employed_persons,_mainly_w |
Population census Number of employed persons, mainly w | float | 0% | 1 | 47954511.0 |
F1103_Population_census_Number_of_employed_persons,_mainly_w_time |
Population census Number of employed persons, mainly w (survey year) | float | 0% | 1 | 2020 |
F110301_Population_census_Number_of_employed_persons,_mainly |
Population census Number of employed persons, mainly | float | 0% | 1 | 34087161.0 |
F110301_Population_census_Number_of_employed_persons,_mainly_time |
Population census Number of employed persons, mainly (survey year) | float | 0% | 1 | 2005 |
F110302_Population_census_Number_of_employed_persons,_mainly |
Population census Number of employed persons, mainly | float | 0% | 1 | 16868133.0 |
F110302_Population_census_Number_of_employed_persons,_mainly_time |
Population census Number of employed persons, mainly (survey year) | float | 0% | 1 | 2005 |
F1104_Population_census_Number_of_employed_persons,_working_ |
Population census Number of employed persons, working | float | 0% | 1 | 7107404.0 |
F1104_Population_census_Number_of_employed_persons,_working__time |
Population census Number of employed persons, working (survey year) | float | 0% | 1 | 2020 |
F110401_Population_census_Number_of_employed_persons,_workin |
Population census Number of employed persons, workin | float | 0% | 1 | 544471.0 |
F110401_Population_census_Number_of_employed_persons,_workin_time |
Population census Number of employed persons, workin (survey year) | float | 0% | 1 | 2005 |
F110402_Population_census_Number_of_employed_persons,_workin |
Population census Number of employed persons, workin | float | 0% | 1 | 7953939.0 |
F110402_Population_census_Number_of_employed_persons,_workin_time |
Population census Number of employed persons, workin (survey year) | float | 0% | 1 | 2005 |
F1105_Population_census_Number_of_employed_persons,_working_ |
Population census Number of employed persons, working | float | 0% | 1 | 1105592.0 |
F1105_Population_census_Number_of_employed_persons,_working__time |
Population census Number of employed persons, working (survey year) | float | 0% | 1 | 2020 |
F110501_Population_census_Number_of_employed_persons,_workin |
Population census Number of employed persons, workin | float | 0% | 1 | 560697.0 |
F110501_Population_census_Number_of_employed_persons,_workin_time |
Population census Number of employed persons, workin (survey year) | float | 0% | 1 | 2005 |
F110502_Population_census_Number_of_employed_persons,_workin |
Population census Number of employed persons, workin | float | 0% | 1 | 507130.0 |
F110502_Population_census_Number_of_employed_persons,_workin_time |
Population census Number of employed persons, workin (survey year) | float | 0% | 1 | 2005 |
F1106_Population_census_Number_of_employed_persons,_being_ab |
Population census Number of employed persons, being ab | float | 0% | 1 | 1475718.0 |
| +650 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Health Wide (admin_0)
— 1 rows, 120 columns
Loading data…
Field details — 120 fields (type, nulls, unique, samples)
Standards-Aligned Fields (2)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 1 | 00000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN |
Extension Fields (118)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
D110101_Number_of_cities,_towns_and_villages |
Number of cities, towns and villages | float | 0% | 1 | 1741.0 |
D110101_Number_of_cities,_towns_and_villages_time |
Number of cities, towns and villages (survey year) | float | 0% | 1 | 2024 |
D110102_Number_of_cities_and_wards |
Number of cities and wards | float | 0% | 1 | 986.0 |
D110102_Number_of_cities_and_wards_time |
Number of cities and wards (survey year) | float | 0% | 1 | 2024 |
D110103_Number_of_towns_and_villages |
Number of towns and villages | float | 0% | 1 | 926.0 |
D110103_Number_of_towns_and_villages_time |
Number of towns and villages (survey year) | float | 0% | 1 | 2024 |
D1201_Number_of_general_personnel_Prefecture |
Number of general personnel Prefecture | float | 0% | 1 | 238199.0 |
D1201_Number_of_general_personnel_Prefecture_time |
Number of general personnel Prefecture (survey year) | float | 0% | 1 | 2024 |
D1202_Number_of_general_personnel_Municipality |
Number of general personnel Municipality | float | 0% | 1 | 709421.0 |
D1202_Number_of_general_personnel_Municipality_time |
Number of general personnel Municipality (survey year) | float | 0% | 1 | 2024 |
D1203_Number_of_fire_service_personnel |
Number of fire service personnel | float | 0% | 1 | 165343.0 |
D1203_Number_of_fire_service_personnel_time |
Number of fire service personnel (survey year) | float | 0% | 1 | 2024 |
D1204_Number_of_educational_service_personnel |
Number of educational service personnel | float | 0% | 1 | 1069060.0 |
D1204_Number_of_educational_service_personnel_time |
Number of educational service personnel (survey year) | float | 0% | 1 | 2024 |
D1205_Number_of_police_personnel |
Number of police personnel | float | 0% | 1 | 287631.0 |
D1205_Number_of_police_personnel_time |
Number of police personnel (survey year) | float | 0% | 1 | 2024 |
D1206_Number_of_public_businesses_account_personnel |
Number of public businesses account personnel | float | 0% | 1 | 342095.0 |
D1206_Number_of_public_businesses_account_personnel_time |
Number of public businesses account personnel (survey year) | float | 0% | 1 | 2024 |
D1210_Number_of_prefectural_assembly_members |
Number of prefectural assembly members | float | 0% | 1 | 2614.0 |
D1210_Number_of_prefectural_assembly_members_time |
Number of prefectural assembly members (survey year) | float | 0% | 1 | 2024 |
D1211_Number_of_municipal_assembly_members |
Number of municipal assembly members | float | 0% | 1 | 18389.0 |
D1211_Number_of_municipal_assembly_members_time |
Number of municipal assembly members (survey year) | float | 0% | 1 | 2024 |
D1212_Number_of_electoral_roll_subscribers |
Number of electoral roll subscribers | float | 0% | 1 | 104074483.0 |
D1212_Number_of_electoral_roll_subscribers_time |
Number of electoral roll subscribers (survey year) | float | 0% | 1 | 2024 |
D2101_Financial_power_index_Prefecture |
Financial power index Prefecture | float | 0% | 1 | 0.49378 |
D2101_Financial_power_index_Prefecture_time |
Financial power index Prefecture (survey year) | float | 0% | 1 | 2022 |
D2102_Real_term_balance_of_revenue_to_expenditure_Prefecture |
Real term balance of revenue to expenditure Prefecture | float | 0% | 1 | 3.1 |
D2102_Real_term_balance_of_revenue_to_expenditure_Prefecture_time |
Real term balance of revenue to expenditure Prefecture (survey year) | float | 0% | 1 | 2022 |
D2103_Real_term_of_current_balance_Prefecture |
Real term of current balance Prefecture | float | 0% | 1 | 93.3 |
D2103_Real_term_of_current_balance_Prefecture_time |
Real term of current balance Prefecture (survey year) | float | 0% | 1 | 2022 |
| +88 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Housing Wide (admin_0)
— 1 rows, 448 columns
Loading data…
Field details — 448 fields (type, nulls, unique, samples)
Standards-Aligned Fields (6)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 1 | 00000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN |
H1100_Number_of_dwellings |
Number of dwellings | float | SEL | 0% | 1 | 65046700.0 |
H1101_Number_of_dwellings_with_occupying_households |
Number of dwellings with occupying households | float | SEL | 0% | 1 | 55665000.0 |
H1102_Number_of_unoccupied_dwellings |
Number of unoccupied dwellings | float | SEL | 0% | 1 | 9381700.0 |
H3100_Number_of_total_households |
Number of total households | float | SEL | 0% | 1 | 56215300.0 |
Extension Fields (442)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
H1100_Number_of_dwellings_time |
Number of dwellings (survey year) | float | 0% | 1 | 2023 |
H1101_Number_of_dwellings_with_occupying_households_time |
Number of dwellings with occupying households (survey year) | float | 0% | 1 | 2023 |
H1102_Number_of_unoccupied_dwellings_time |
Number of unoccupied dwellings (survey year) | float | 0% | 1 | 2023 |
H110201_Number_of_houses_with_temporary_sojourners |
Number of houses with temporary sojourners | float | 0% | 1 | 285500.0 |
H110201_Number_of_houses_with_temporary_sojourners_time |
Number of houses with temporary sojourners (survey year) | float | 0% | 1 | 2023 |
H110202_Number_of_vacant_houses |
Number of vacant houses | float | 0% | 1 | 9001600.0 |
H110202_Number_of_vacant_houses_time |
Number of vacant houses (survey year) | float | 0% | 1 | 2023 |
H110203_Number_of_dwellings_under_construction |
Number of dwellings under construction | float | 0% | 1 | 94700.0 |
H110203_Number_of_dwellings_under_construction_time |
Number of dwellings under construction (survey year) | float | 0% | 1 | 2023 |
H1201_Number_of_dwellings_used_exclusively_for_living |
Number of dwellings used exclusively for living | float | 0% | 1 | 54893100.0 |
H1201_Number_of_dwellings_used_exclusively_for_living_time |
Number of dwellings used exclusively for living (survey year) | float | 0% | 1 | 2023 |
H1203_Number_of_dwellings_used_also_for_commerce_or_other_pu |
Number of dwellings used also for commerce or other pu | float | 0% | 1 | 772000.0 |
H1203_Number_of_dwellings_used_also_for_commerce_or_other_pu_time |
Number of dwellings used also for commerce or other pu (survey year) | float | 0% | 1 | 2023 |
H1310_Number_of_owned_houses |
Number of owned houses | float | 0% | 1 | 33875500.0 |
H1310_Number_of_owned_houses_time |
Number of owned houses (survey year) | float | 0% | 1 | 2023 |
H1320_Number_of_rented_houses |
Number of rented houses | float | 0% | 1 | 19461700.0 |
H1320_Number_of_rented_houses_time |
Number of rented houses (survey year) | float | 0% | 1 | 2023 |
H1321_Number_of_rented_houses_owned_by_local_government_and_ |
Number of rented houses owned by local government and | float | 0% | 1 | 2476200.0 |
H1321_Number_of_rented_houses_owned_by_local_government_and__time |
Number of rented houses owned by local government and (survey year) | float | 0% | 1 | 2023 |
H132101_Number_of_rented_houses_owned_by_local_government |
Number of rented houses owned by local government | float | 0% | 1 | 1760200.0 |
H132101_Number_of_rented_houses_owned_by_local_government_time |
Number of rented houses owned by local government (survey year) | float | 0% | 1 | 2023 |
H132102_Number_of_rented_houses_owned_by_Urban_Renaissance_A |
Number of rented houses owned by Urban Renaissance A | float | 0% | 1 | 716000.0 |
H132102_Number_of_rented_houses_owned_by_Urban_Renaissance_A_time |
Number of rented houses owned by Urban Renaissance A (survey year) | float | 0% | 1 | 2023 |
H1322_Number_of_rented_houses_owned_privately |
Number of rented houses owned privately | float | 0% | 1 | 15683500.0 |
H1322_Number_of_rented_houses_owned_privately_time |
Number of rented houses owned privately (survey year) | float | 0% | 1 | 2023 |
H1323_Number_of_issued_houses |
Number of issued houses | float | 0% | 1 | 1302100.0 |
H1323_Number_of_issued_houses_time |
Number of issued houses (survey year) | float | 0% | 1 | 2023 |
H1401_Number_of_detached_houses_Total |
Number of detached houses Total | float | 0% | 1 | 29319400.0 |
H1401_Number_of_detached_houses_Total_time |
Number of detached houses Total (survey year) | float | 0% | 1 | 2023 |
H140101_Number_of_detached_houses_Wooden |
Number of detached houses Wooden | float | 0% | 1 | 25780500.0 |
| +412 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Municipality Pop Wide (admin_0)
— 1 rows, 448 columns
Loading data…
Field details — 448 fields (type, nulls, unique, samples)
Standards-Aligned Fields (6)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 1 | 00000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN |
H1100_Number_of_dwellings |
Number of dwellings | float | SEL | 0% | 1 | 65046700.0 |
H1101_Number_of_dwellings_with_occupying_households |
Number of dwellings with occupying households | float | SEL | 0% | 1 | 55665000.0 |
H1102_Number_of_unoccupied_dwellings |
Number of unoccupied dwellings | float | SEL | 0% | 1 | 9381700.0 |
H3100_Number_of_total_households |
Number of total households | float | SEL | 0% | 1 | 56215300.0 |
Extension Fields (442)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
H1100_Number_of_dwellings_time |
Number of dwellings (survey year) | float | 0% | 1 | 2023 |
H1101_Number_of_dwellings_with_occupying_households_time |
Number of dwellings with occupying households (survey year) | float | 0% | 1 | 2023 |
H1102_Number_of_unoccupied_dwellings_time |
Number of unoccupied dwellings (survey year) | float | 0% | 1 | 2023 |
H110201_Number_of_houses_with_temporary_sojourners |
Number of houses with temporary sojourners | float | 0% | 1 | 285500.0 |
H110201_Number_of_houses_with_temporary_sojourners_time |
Number of houses with temporary sojourners (survey year) | float | 0% | 1 | 2023 |
H110202_Number_of_vacant_houses |
Number of vacant houses | float | 0% | 1 | 9001600.0 |
H110202_Number_of_vacant_houses_time |
Number of vacant houses (survey year) | float | 0% | 1 | 2023 |
H110203_Number_of_dwellings_under_construction |
Number of dwellings under construction | float | 0% | 1 | 94700.0 |
H110203_Number_of_dwellings_under_construction_time |
Number of dwellings under construction (survey year) | float | 0% | 1 | 2023 |
H1201_Number_of_dwellings_used_exclusively_for_living |
Number of dwellings used exclusively for living | float | 0% | 1 | 54893100.0 |
H1201_Number_of_dwellings_used_exclusively_for_living_time |
Number of dwellings used exclusively for living (survey year) | float | 0% | 1 | 2023 |
H1203_Number_of_dwellings_used_also_for_commerce_or_other_pu |
Number of dwellings used also for commerce or other pu | float | 0% | 1 | 772000.0 |
H1203_Number_of_dwellings_used_also_for_commerce_or_other_pu_time |
Number of dwellings used also for commerce or other pu (survey year) | float | 0% | 1 | 2023 |
H1310_Number_of_owned_houses |
Number of owned houses | float | 0% | 1 | 33875500.0 |
H1310_Number_of_owned_houses_time |
Number of owned houses (survey year) | float | 0% | 1 | 2023 |
H1320_Number_of_rented_houses |
Number of rented houses | float | 0% | 1 | 19461700.0 |
H1320_Number_of_rented_houses_time |
Number of rented houses (survey year) | float | 0% | 1 | 2023 |
H1321_Number_of_rented_houses_owned_by_local_government_and_ |
Number of rented houses owned by local government and | float | 0% | 1 | 2476200.0 |
H1321_Number_of_rented_houses_owned_by_local_government_and__time |
Number of rented houses owned by local government and (survey year) | float | 0% | 1 | 2023 |
H132101_Number_of_rented_houses_owned_by_local_government |
Number of rented houses owned by local government | float | 0% | 1 | 1760200.0 |
H132101_Number_of_rented_houses_owned_by_local_government_time |
Number of rented houses owned by local government (survey year) | float | 0% | 1 | 2023 |
H132102_Number_of_rented_houses_owned_by_Urban_Renaissance_A |
Number of rented houses owned by Urban Renaissance A | float | 0% | 1 | 716000.0 |
H132102_Number_of_rented_houses_owned_by_Urban_Renaissance_A_time |
Number of rented houses owned by Urban Renaissance A (survey year) | float | 0% | 1 | 2023 |
H1322_Number_of_rented_houses_owned_privately |
Number of rented houses owned privately | float | 0% | 1 | 15683500.0 |
H1322_Number_of_rented_houses_owned_privately_time |
Number of rented houses owned privately (survey year) | float | 0% | 1 | 2023 |
H1323_Number_of_issued_houses |
Number of issued houses | float | 0% | 1 | 1302100.0 |
H1323_Number_of_issued_houses_time |
Number of issued houses (survey year) | float | 0% | 1 | 2023 |
H1401_Number_of_detached_houses_Total |
Number of detached houses Total | float | 0% | 1 | 29319400.0 |
H1401_Number_of_detached_houses_Total_time |
Number of detached houses Total (survey year) | float | 0% | 1 | 2023 |
H140101_Number_of_detached_houses_Wooden |
Number of detached houses Wooden | float | 0% | 1 | 25780500.0 |
| +412 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Population Wide (admin_0)
— 1 rows, 88 columns
Loading data…
Field details — 88 fields (type, nulls, unique, samples)
Standards-Aligned Fields (7)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 1 | 00000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN |
A1101_Total_population_Both_sexes |
Total population Both sexes | float | SEL | 0% | 1 | 123802000.0 |
A110101_Total_population_Male |
Total population Male | float | SEL | 0% | 1 | 60233000.0 |
A110102_Total_population_Female |
Total population Female | float | SEL | 0% | 1 | 63569000.0 |
population_0_14 |
Population aged 0-14 (derived) | integer | SEL | 0% | - | - |
population_60_plus |
Population aged 60 and over (derived) | integer | SEL | 0% | - | - |
Extension Fields (81)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
A1101_Total_population_Both_sexes_time |
Total population Both sexes (survey year) | float | 0% | 1 | 2024 |
A110101_Total_population_Male_time |
Total population Male (survey year) | float | 0% | 1 | 2024 |
A110102_Total_population_Female_time |
Total population Female (survey year) | float | 0% | 1 | 2024 |
A1102_Japanese_population_Both_sexes |
Japanese population Both sexes | float | 0% | 1 | 120296000.0 |
A1102_Japanese_population_Both_sexes_time |
Japanese population Both sexes (survey year) | float | 0% | 1 | 2024 |
A110201_Japanese_population_Male |
Japanese population Male | float | 0% | 1 | 58450000.0 |
A110201_Japanese_population_Male_time |
Japanese population Male (survey year) | float | 0% | 1 | 2024 |
A110202_Japanese_population_Female |
Japanese population Female | float | 0% | 1 | 61846000.0 |
A110202_Japanese_population_Female_time |
Japanese population Female (survey year) | float | 0% | 1 | 2024 |
A1201_Population_0-4,_Total |
Population 0-4, Total | float | 0% | 1 | 3934000.0 |
A1201_Population_0-4,_Total_time |
Population 0-4, Total (survey year) | float | 0% | 1 | 2024 |
A120101_Population_0-4,_Male |
Population 0-4, Male | float | 0% | 1 | 2015000.0 |
A120101_Population_0-4,_Male_time |
Population 0-4, Male (survey year) | float | 0% | 1 | 2024 |
A120102_Population_0-4,_Female |
Population 0-4, Female | float | 0% | 1 | 1920000.0 |
A120102_Population_0-4,_Female_time |
Population 0-4, Female (survey year) | float | 0% | 1 | 2024 |
A1202_Population_5-9,_Total |
Population 5-9, Total | float | 0% | 1 | 4710000.0 |
A1202_Population_5-9,_Total_time |
Population 5-9, Total (survey year) | float | 0% | 1 | 2024 |
A120201_Population_5-9,_Male |
Population 5-9, Male | float | 0% | 1 | 2412000.0 |
A120201_Population_5-9,_Male_time |
Population 5-9, Male (survey year) | float | 0% | 1 | 2024 |
A120202_Population_5-9,_Female |
Population 5-9, Female | float | 0% | 1 | 2298000.0 |
A120202_Population_5-9,_Female_time |
Population 5-9, Female (survey year) | float | 0% | 1 | 2024 |
A1203_Population_10-14,_Total |
Population 10-14, Total | float | 0% | 1 | 5185000.0 |
A1203_Population_10-14,_Total_time |
Population 10-14, Total (survey year) | float | 0% | 1 | 2024 |
A120301_Population_10-14,_Male |
Population 10-14, Male | float | 0% | 1 | 2657000.0 |
A120301_Population_10-14,_Male_time |
Population 10-14, Male (survey year) | float | 0% | 1 | 2024 |
A120302_Population_10-14,_Female |
Population 10-14, Female | float | 0% | 1 | 2528000.0 |
A120302_Population_10-14,_Female_time |
Population 10-14, Female (survey year) | float | 0% | 1 | 2024 |
A1204_Population_15-19,_Total |
Population 15-19, Total | float | 0% | 1 | 5457000.0 |
A1204_Population_15-19,_Total_time |
Population 15-19, Total (survey year) | float | 0% | 1 | 2024 |
A120401_Population_15-19,_Male |
Population 15-19, Male | float | 0% | 1 | 2799000.0 |
| +51 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Relative Poverty
— 14 rows, 12 columns
Loading data…
Field details — 12 fields (type, nulls, unique, samples)
Standards-Aligned Fields (3)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
relative_poverty_rate_pct |
relative poverty rate pct | float | SEL | 0% | 11 | 12.0, 13.2, 13.5, 13.8, 14.6 |
child_poverty_rate_pct |
child poverty rate pct | float | SEL | 0% | 14 | 10.9, 12.9, 12.8, 12.2, 13.4 |
Extension Fields (9)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 13 | 1985, 1988, 1991, 1994, 1997 |
income_basis |
income basis | string | 0% | 3 | , , , , |
poverty_rate__working_hh_with_children |
poverty rate working hh with children | float | 0% | 13 | 10.3, 11.9, 11.6, 11.3, 12.2 |
poverty_rate__working_hh_single_adult |
poverty rate working hh single adult | float | 0% | 13 | 54.5, 51.4, 50.1, 53.5, 63.1 |
poverty_rate__working_hh_two_plus_adults |
poverty rate working hh two plus adults | float | 0% | 11 | 9.6, 11.1, 10.7, 10.2, 10.8 |
median_income_man_yen_nominal |
median income man yen nominal | float | 0% | 12 | 216.0, 227.0, 270.0, 289.0, 297.0 |
poverty_line_man_yen_nominal |
poverty line man yen nominal | float | 0% | 11 | 108.0, 114.0, 135.0, 144.0, 149.0 |
median_income_man_yen_real |
median income man yen real | float | 0% | 13 | 216.0, 226.0, 246.0, 255.0, 259.0 |
poverty_line_man_yen_real |
poverty line man yen real | float | 0% | 12 | 108.0, 113.0, 123.0, 127.0, 130.0 |
JPN e-Stat - Municipal Economic Census (admin_0)
— 1 rows, 24 columns
Loading data…
Field details — 24 fields (type, nulls, unique, samples)
Standards-Aligned Fields (6)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | SEL | 0% | 1 | 00000 |
area_name |
Geographic-area English name as returned by e-Stat | string | SEL | 0% | 1 | Japan |
admin_level |
Administrative level (admin_0..admin_4) | string | SEL | 0% | 1 | admin_0 |
Number_of_establishments_Total |
Number of establishments Total | float | SEL | 0% | 1 | 5211445.0 |
Number_of_persons_engaged_Male_and_Female_Total |
Number of persons engaged Male and Female Total | float | SEL | 0% | 1 | 61935849.0 |
Extension Fields (8)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total |
Number of establishments Including establishments not reported their industry et Total | float | 0% | 1 | 5995257.0 |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned |
Number of establishments Including establishments not reported their industry et Privately owned | float | 0% | 1 | 5862429.0 |
Number_of_establishments_Privately_owned |
Number of establishments Privately owned | float | 0% | 1 | 5078617.0 |
Number_of_persons_engaged_Male_and_Female_Privately_owned |
Number of persons engaged Male and Female Privately owned | float | 0% | 1 | 57457856.0 |
Number_of_persons_engaged_Male_Total |
Number of persons engaged Male Total | float | 0% | 1 | 34131304.0 |
Number_of_persons_engaged_Male_Privately_owned |
Number of persons engaged Male Privately owned | float | 0% | 1 | 31704141.0 |
Number_of_persons_engaged_Female_Total |
Number of persons engaged Female Total | float | 0% | 1 | 27416743.0 |
Number_of_persons_engaged_Female_Privately_owned |
Number of persons engaged Female Privately owned | float | 0% | 1 | 25365913.0 |
Pending (10) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total_time |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total_time | integer | 0% | 1 | 2021 |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned_time |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned_time | integer | 0% | 1 | 2021 |
Number_of_establishments_Total_time |
Number_of_establishments_Total_time | integer | 0% | 1 | 2021 |
Number_of_establishments_Privately_owned_time |
Number_of_establishments_Privately_owned_time | integer | 0% | 1 | 2021 |
Number_of_persons_engaged_Male_and_Female_Total_time |
Number_of_persons_engaged_Male_and_Female_Total_time | integer | 0% | 1 | 2021 |
Number_of_persons_engaged_Male_and_Female_Privately_owned_time |
Number_of_persons_engaged_Male_and_Female_Privately_owned_time | integer | 0% | 1 | 2021 |
Number_of_persons_engaged_Male_Total_time |
Number_of_persons_engaged_Male_Total_time | integer | 0% | 1 | 2021 |
Number_of_persons_engaged_Male_Privately_owned_time |
Number_of_persons_engaged_Male_Privately_owned_time | integer | 0% | 1 | 2021 |
Number_of_persons_engaged_Female_Total_time |
Number_of_persons_engaged_Female_Total_time | integer | 0% | 1 | 2021 |
Number_of_persons_engaged_Female_Privately_owned_time |
Number_of_persons_engaged_Female_Privately_owned_time | integer | 0% | 1 | 2021 |
JPN e-Stat - Municipal Pop Age Marital (admin_0)
— 1 rows, 1,732 columns
Loading data…
Field details — 1732 fields (type, nulls, unique, samples)
Standards-Aligned Fields (4)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | SEL | 0% | 1 | 00000 |
area_name |
Geographic-area English name as returned by e-Stat | string | SEL | 0% | 1 | Japan |
admin_level |
Administrative level (admin_0..admin_4) | string | SEL | 0% | 1 | admin_0 |
Extension Fields (864)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Population_Total_Total_Total_Total |
Population Total Total Total Total | float | 0% | 1 | 75069522.0 |
Population_Total_Total_Total_15_19_years_old |
Population Total Total Total 15 19 years old | float | 0% | 1 | 3973139.0 |
Population_Total_Total_Total_20_24_years_old |
Population Total Total Total 20 24 years old | float | 0% | 1 | 4542266.0 |
Population_Total_Total_Total_25_29_years_old |
Population Total Total Total 25 29 years old | float | 0% | 1 | 4637686.0 |
Population_Total_Total_Total_30_34_years_old |
Population Total Total Total 30 34 years old | float | 0% | 1 | 4861469.0 |
Population_Total_Total_Total_35_39_years_old |
Population Total Total Total 35 39 years old | float | 0% | 1 | 5365617.0 |
Population_Total_Total_Total_40_44_years_old |
Population Total Total Total 40 44 years old | float | 0% | 1 | 6024226.0 |
Population_Total_Total_Total_45_49_years_old |
Population Total Total Total 45 49 years old | float | 0% | 1 | 7056057.0 |
Population_Total_Total_Total_50_54_years_old |
Population Total Total Total 50 54 years old | float | 0% | 1 | 6229185.0 |
Population_Total_Total_Total_55_59_years_old |
Population Total Total Total 55 59 years old | float | 0% | 1 | 5422520.0 |
Population_Total_Total_Total_60_64_years_old |
Population Total Total Total 60 64 years old | float | 0% | 1 | 4724151.0 |
Population_Total_Total_Total_65_69_years_old |
Population Total Total Total 65 69 years old | float | 0% | 1 | 5046796.0 |
Population_Total_Total_Total_70_74_years_old |
Population Total Total Total 70 74 years old | float | 0% | 1 | 5786980.0 |
Population_Total_Total_Total_75_79_years_old |
Population Total Total Total 75 79 years old | float | 0% | 1 | 4549961.0 |
Population_Total_Total_Total_80_84_years_old |
Population Total Total Total 80 84 years old | float | 0% | 1 | 3370406.0 |
Population_Total_Total_Total_85_89_years_old |
Population Total Total Total 85 89 years old | float | 0% | 1 | 2202466.0 |
Population_Total_Total_Total_90_94_years_old |
Population Total Total Total 90 94 years old | float | 0% | 1 | 983383.0 |
Population_Total_Total_Total_95_99_years_old |
Population Total Total Total 95 99 years old | float | 0% | 1 | 253476.0 |
Population_Total_Total_Total_100_years_old_and_over |
Population Total Total Total 100 years old and over | float | 0% | 1 | 39738.0 |
Population_Total_Total_Total_Recount_15_64_years_old |
Population Total Total Total Recount 15 64 years old | float | 0% | 1 | 52836316.0 |
Population_Total_Total_Total_Recount_65_years_old_and_over |
Population Total Total Total Recount 65 years old and over | float | 0% | 1 | 22233206.0 |
Population_Total_Total_Total_Recount_75_years_old_and_over |
Population Total Total Total Recount 75 years old and over | float | 0% | 1 | 11399430.0 |
Population_Total_Total_Total_Recount_85_years_old_and_over |
Population Total Total Total Recount 85 years old and over | float | 0% | 1 | 3479063.0 |
Population_Total_Total_Total_Recount_20_69_years_old |
Population Total Total Total Recount 20 69 years old | float | 0% | 1 | 53909973.0 |
Population_Total_Total_Never_married_Total |
Population Total Total Never married Total | float | 0% | 1 | 20616956.0 |
Population_Total_Total_Never_married_15_19_years_old |
Population Total Total Never married 15 19 years old | float | 0% | 1 | 3932592.0 |
Population_Total_Total_Never_married_20_24_years_old |
Population Total Total Never married 20 24 years old | float | 0% | 1 | 3943793.0 |
Population_Total_Total_Never_married_25_29_years_old |
Population Total Total Never married 25 29 years old | float | 0% | 1 | 2806702.0 |
Population_Total_Total_Never_married_30_34_years_old |
Population Total Total Never married 30 34 years old | float | 0% | 1 | 1824428.0 |
Population_Total_Total_Never_married_35_39_years_old |
Population Total Total Never married 35 39 years old | float | 0% | 1 | 1434356.0 |
| +834 more extension fields — download the CSV/Parquet to see them all. | |||||
Pending (864) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Population_Total_Total_Total_Total_time |
Population_Total_Total_Total_Total_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_15_19_years_old_time |
Population_Total_Total_Total_15_19_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_20_24_years_old_time |
Population_Total_Total_Total_20_24_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_25_29_years_old_time |
Population_Total_Total_Total_25_29_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_30_34_years_old_time |
Population_Total_Total_Total_30_34_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_35_39_years_old_time |
Population_Total_Total_Total_35_39_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_40_44_years_old_time |
Population_Total_Total_Total_40_44_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_45_49_years_old_time |
Population_Total_Total_Total_45_49_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_50_54_years_old_time |
Population_Total_Total_Total_50_54_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_55_59_years_old_time |
Population_Total_Total_Total_55_59_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_60_64_years_old_time |
Population_Total_Total_Total_60_64_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_65_69_years_old_time |
Population_Total_Total_Total_65_69_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_70_74_years_old_time |
Population_Total_Total_Total_70_74_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_75_79_years_old_time |
Population_Total_Total_Total_75_79_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_80_84_years_old_time |
Population_Total_Total_Total_80_84_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_85_89_years_old_time |
Population_Total_Total_Total_85_89_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_90_94_years_old_time |
Population_Total_Total_Total_90_94_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_95_99_years_old_time |
Population_Total_Total_Total_95_99_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_100_years_old_and_over_time |
Population_Total_Total_Total_100_years_old_and_over_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_Recount_15_64_years_old_time |
Population_Total_Total_Total_Recount_15_64_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_Recount_65_years_old_and_over_time |
Population_Total_Total_Total_Recount_65_years_old_and_over_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_Recount_75_years_old_and_over_time |
Population_Total_Total_Total_Recount_75_years_old_and_over_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_Recount_85_years_old_and_over_time |
Population_Total_Total_Total_Recount_85_years_old_and_over_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Total_Recount_20_69_years_old_time |
Population_Total_Total_Total_Recount_20_69_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Never_married_Total_time |
Population_Total_Total_Never_married_Total_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Never_married_15_19_years_old_time |
Population_Total_Total_Never_married_15_19_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Never_married_20_24_years_old_time |
Population_Total_Total_Never_married_20_24_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Never_married_25_29_years_old_time |
Population_Total_Total_Never_married_25_29_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Never_married_30_34_years_old_time |
Population_Total_Total_Never_married_30_34_years_old_time | integer | 0% | 1 | 2020 |
Population_Total_Total_Never_married_35_39_years_old_time |
Population_Total_Total_Never_married_35_39_years_old_time | integer | 0% | 1 | 2020 |
| +834 more pending fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Municipal Population By Sex (admin_0)
— 1 rows, 10 columns
Loading data…
Field details — 10 fields (type, nulls, unique, samples)
Standards-Aligned Fields (7)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | SEL | 0% | 1 | 00000 |
area_name |
Geographic-area English name as returned by e-Stat | string | SEL | 0% | 1 | Japan |
admin_level |
Administrative level (admin_0..admin_4) | string | SEL | 0% | 1 | admin_0 |
Population_Total |
Population Total | float | SEL | 0% | 1 | 126146099.0 |
Population_Male |
Population Male | float | SEL | 0% | 1 | 61349581.0 |
Population_Female |
Population Female | float | SEL | 0% | 1 | 64796518.0 |
Pending (3) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Population_Total_time |
Population_Total_time | integer | 0% | 1 | 2020 |
Population_Male_time |
Population_Male_time | integer | 0% | 1 | 2020 |
Population_Female_time |
Population_Female_time | integer | 0% | 1 | 2020 |
JPN e-Stat - Ssds E Education (admin_0)
— 1 rows, 984 columns
Loading data…
Field details — 984 fields (type, nulls, unique, samples)
Pending (984) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | 0% | 1 | JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | 0% | 1 | 00000 |
area_name |
Geographic-area English name as returned by e-Stat | string | 0% | 1 | All Japan |
admin_level |
Administrative level (admin_0..admin_4) | string | 0% | 1 | admin_0 |
Observation_value_E1101_Number_of_kindergartens |
Observation_value_E1101_Number_of_kindergartens | float | 0% | 1 | 8530.0 |
Observation_value_E1101_Number_of_kindergartens_time |
Observation_value_E1101_Number_of_kindergartens_time | integer | 0% | 1 | 2024 |
Observation_value_E110102_Number_of_kindergartens_Public |
Observation_value_E110102_Number_of_kindergartens_Public | float | 0% | 1 | 2534.0 |
Observation_value_E110102_Number_of_kindergartens_Public_time |
Observation_value_E110102_Number_of_kindergartens_Public_time | integer | 0% | 1 | 2024 |
Observation_value_E1201_Number_of_kindergarten_classes |
Observation_value_E1201_Number_of_kindergarten_classes | float | 0% | 1 | 42329.0 |
Observation_value_E1201_Number_of_kindergarten_classes_time |
Observation_value_E1201_Number_of_kindergarten_classes_time | integer | 0% | 1 | 2024 |
Observation_value_E120101_Number_of_kindergarten_classes_National |
Observation_value_E120101_Number_of_kindergarten_classes_National | float | 0% | 1 | 229.0 |
Observation_value_E120101_Number_of_kindergarten_classes_National_time |
Observation_value_E120101_Number_of_kindergarten_classes_National_time | integer | 0% | 1 | 2008 |
Observation_value_E120102_Number_of_kindergarten_classes_Public |
Observation_value_E120102_Number_of_kindergarten_classes_Public | float | 0% | 1 | 15809.0 |
Observation_value_E120102_Number_of_kindergarten_classes_Public_time |
Observation_value_E120102_Number_of_kindergarten_classes_Public_time | integer | 0% | 1 | 2008 |
Observation_value_E120103_Number_of_kindergarten_classes_Private |
Observation_value_E120103_Number_of_kindergarten_classes_Private | float | 0% | 1 | 56358.0 |
Observation_value_E120103_Number_of_kindergarten_classes_Private_time |
Observation_value_E120103_Number_of_kindergarten_classes_Private_time | integer | 0% | 1 | 2008 |
Observation_value_E1301_Number_of_kindergarten_teachers |
Observation_value_E1301_Number_of_kindergarten_teachers | float | 0% | 1 | 86775.0 |
Observation_value_E1301_Number_of_kindergarten_teachers_time |
Observation_value_E1301_Number_of_kindergarten_teachers_time | integer | 0% | 1 | 2024 |
Observation_value_E130101_Number_of_kindergarten_teachers_Male |
Observation_value_E130101_Number_of_kindergarten_teachers_Male | float | 0% | 1 | 5789.0 |
Observation_value_E130101_Number_of_kindergarten_teachers_Male_time |
Observation_value_E130101_Number_of_kindergarten_teachers_Male_time | integer | 0% | 1 | 2024 |
Observation_value_E130102_Number_of_kindergarten_teachers_Female |
Observation_value_E130102_Number_of_kindergarten_teachers_Female | float | 0% | 1 | 80986.0 |
Observation_value_E130102_Number_of_kindergarten_teachers_Female_time |
Observation_value_E130102_Number_of_kindergarten_teachers_Female_time | integer | 0% | 1 | 2024 |
Observation_value_E1302_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_tea |
Observation_value_E1302_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_tea | float | 0% | 1 | 369.0 |
Observation_value_E1302_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_tea_time |
Observation_value_E1302_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_tea_time | integer | 0% | 1 | 2024 |
Observation_value_E130201_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t |
Observation_value_E130201_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t | float | 0% | 1 | 2.0 |
Observation_value_E130201_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t_time |
Observation_value_E130201_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t_time | integer | 0% | 1 | 2024 |
Observation_value_E130202_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t |
Observation_value_E130202_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t | float | 0% | 1 | 367.0 |
Observation_value_E130202_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t_time |
Observation_value_E130202_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t_time | integer | 0% | 1 | 2024 |
Observation_value_E1303_Number_of_kindergarten_teachers_Academic_assistant |
Observation_value_E1303_Number_of_kindergarten_teachers_Academic_assistant | float | 0% | 1 | 3966.0 |
Observation_value_E1303_Number_of_kindergarten_teachers_Academic_assistant_time |
Observation_value_E1303_Number_of_kindergarten_teachers_Academic_assistant_time | integer | 0% | 1 | 2024 |
| +954 more pending fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Ssds I Health (admin_0)
— 1 rows, 814 columns
Loading data…
Field details — 814 fields (type, nulls, unique, samples)
Pending (814) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | 0% | 1 | JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | 0% | 1 | 00000 |
area_name |
Geographic-area English name as returned by e-Stat | string | 0% | 1 | All Japan |
admin_level |
Administrative level (admin_0..admin_4) | string | 0% | 1 | admin_0 |
Observation_value_I1101_Life_expectancy_0_years_old_Male |
Observation_value_I1101_Life_expectancy_0_years_old_Male | float | 0% | 1 | 81.56 |
Observation_value_I1101_Life_expectancy_0_years_old_Male_time |
Observation_value_I1101_Life_expectancy_0_years_old_Male_time | integer | 0% | 1 | 2020 |
Observation_value_I1102_Life_expectancy_0_years_old_Female |
Observation_value_I1102_Life_expectancy_0_years_old_Female | float | 0% | 1 | 87.71 |
Observation_value_I1102_Life_expectancy_0_years_old_Female_time |
Observation_value_I1102_Life_expectancy_0_years_old_Female_time | integer | 0% | 1 | 2020 |
Observation_value_I1201_Life_expectancy_20_years_old_Male |
Observation_value_I1201_Life_expectancy_20_years_old_Male | float | 0% | 1 | 61.9 |
Observation_value_I1201_Life_expectancy_20_years_old_Male_time |
Observation_value_I1201_Life_expectancy_20_years_old_Male_time | integer | 0% | 1 | 2020 |
Observation_value_I1202_Life_expectancy_20_years_old_Female |
Observation_value_I1202_Life_expectancy_20_years_old_Female | float | 0% | 1 | 68.01 |
Observation_value_I1202_Life_expectancy_20_years_old_Female_time |
Observation_value_I1202_Life_expectancy_20_years_old_Female_time | integer | 0% | 1 | 2020 |
Observation_value_I1301_Life_expectancy_40_years_old_Male |
Observation_value_I1301_Life_expectancy_40_years_old_Male | float | 0% | 1 | 42.5 |
Observation_value_I1301_Life_expectancy_40_years_old_Male_time |
Observation_value_I1301_Life_expectancy_40_years_old_Male_time | integer | 0% | 1 | 2020 |
Observation_value_I1302_Life_expectancy_40_years_old_Female |
Observation_value_I1302_Life_expectancy_40_years_old_Female | float | 0% | 1 | 48.37 |
Observation_value_I1302_Life_expectancy_40_years_old_Female_time |
Observation_value_I1302_Life_expectancy_40_years_old_Female_time | integer | 0% | 1 | 2020 |
Observation_value_I1401_Life_expectancy_60_years_old_Male |
Observation_value_I1401_Life_expectancy_60_years_old_Male | float | 0% | 1 | 24.12 |
Observation_value_I1401_Life_expectancy_60_years_old_Male_time |
Observation_value_I1401_Life_expectancy_60_years_old_Male_time | integer | 0% | 1 | 2020 |
Observation_value_I1402_Life_expectancy_60_years_old_Female |
Observation_value_I1402_Life_expectancy_60_years_old_Female | float | 0% | 1 | 29.42 |
Observation_value_I1402_Life_expectancy_60_years_old_Female_time |
Observation_value_I1402_Life_expectancy_60_years_old_Female_time | integer | 0% | 1 | 2020 |
Observation_value_I1501_Life_expectancy_65_years_old_Male |
Observation_value_I1501_Life_expectancy_65_years_old_Male | float | 0% | 1 | 19.97 |
Observation_value_I1501_Life_expectancy_65_years_old_Male_time |
Observation_value_I1501_Life_expectancy_65_years_old_Male_time | integer | 0% | 1 | 2020 |
Observation_value_I1502_Life_expectancy_65_years_old_Female |
Observation_value_I1502_Life_expectancy_65_years_old_Female | float | 0% | 1 | 24.88 |
Observation_value_I1502_Life_expectancy_65_years_old_Female_time |
Observation_value_I1502_Life_expectancy_65_years_old_Female_time | integer | 0% | 1 | 2020 |
Observation_value_I1601_Healthy_life_expectancy_Male |
Observation_value_I1601_Healthy_life_expectancy_Male | float | 0% | 1 | 72.68 |
Observation_value_I1601_Healthy_life_expectancy_Male_time |
Observation_value_I1601_Healthy_life_expectancy_Male_time | integer | 0% | 1 | 2019 |
Observation_value_I1602_Healthy_life_expectancy_Female |
Observation_value_I1602_Healthy_life_expectancy_Female | float | 0% | 1 | 75.38 |
Observation_value_I1602_Healthy_life_expectancy_Female_time |
Observation_value_I1602_Healthy_life_expectancy_Female_time | integer | 0% | 1 | 2019 |
Observation_value_I210101_Number_of_persons_undergoing_medical_inspections_at_health_care_centers_ |
Observation_value_I210101_Number_of_persons_undergoing_medical_inspections_at_health_care_centers_ | float | 0% | 1 | 7188137.0 |
Observation_value_I210101_Number_of_persons_undergoing_medical_inspections_at_health_care_centers__time |
Observation_value_I210101_Number_of_persons_undergoing_medical_inspections_at_health_care_centers__time | integer | 0% | 1 | 2023 |
| +784 more pending fields — download the CSV/Parquet to see them all. | |||||
1
Admin 1
— 12 table(s)
JPN e-Stat - Demographics Wide (admin_1)
— 47 rows, 98 columns
Loading data…
Field details — 98 fields (type, nulls, unique, samples)
Standards-Aligned Fields (2)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
Extension Fields (96)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
#D0110101_Financial_power_index_Prefecture |
Financial power index Prefecture | float | 0% | 44 | 0.444, 0.342, 0.354, 0.591, 0.309 |
#D0110101_Financial_power_index_Prefecture_time |
Financial power index Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D01102_Real_term_balance_of_revenue_to_expenditure_Prefectu |
Real term balance of revenue to expenditure Prefectu | float | 0% | 34 | 2.0, 2.1, 5.1, 2.8, 4.5 |
#D01102_Real_term_balance_of_revenue_to_expenditure_Prefectu_time |
Real term balance of revenue to expenditure Prefectu (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D0120101_Percentage_of_self-financial_resources_Prefecture |
Percentage of self-financial resources Prefecture | float | 0% | 44 | 42.4, 40.2, 47.3, 55.5, 35.8 |
#D0120101_Percentage_of_self-financial_resources_Prefecture_time |
Percentage of self-financial resources Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D0130201_Percentage_of_outstanding_amount_of_local_bonds_to |
Percentage of outstanding amount of local bonds to | float | 0% | 45 | 188.9, 120.8, 158.2, 135.1, 193.7 |
#D0130201_Percentage_of_outstanding_amount_of_local_bonds_to_time |
Percentage of outstanding amount of local bonds to (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D01401_Real_term_of_current_balance_Prefecture |
Real term of current balance Prefecture | float | 0% | 41 | 98.1, 94.5, 94.2, 96.4, 90.4 |
#D01401_Real_term_of_current_balance_Prefecture_time |
Real term of current balance Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D0140201_Percentage_of_investment_expenditure_Prefecture |
Percentage of investment expenditure Prefecture | float | 0% | 40 | 15.8, 19.2, 16.5, 15.6, 22.2 |
#D0140201_Percentage_of_investment_expenditure_Prefecture_time |
Percentage of investment expenditure Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D0140301_Percentage_of_revenues_from_local_taxes_and_grants |
Percentage of revenues from local taxes and grants | float | 0% | 37 | 49.9, 56.7, 51.7, 50.7, 55.8 |
#D0140301_Percentage_of_revenues_from_local_taxes_and_grants_time |
Percentage of revenues from local taxes and grants (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D0210101_Percentage_of_local_taxes_Prefecture |
Percentage of local taxes Prefecture | float | 0% | 47 | 24.49, 22.8, 19.21, 30.96, 19.55 |
#D0210101_Percentage_of_local_taxes_Prefecture_time |
Percentage of local taxes Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D0210201_Percentage_of_grants_to_local_governments_Prefectu |
Percentage of grants to local governments Prefectu | float | 0% | 47 | 21.2, 28.61, 26.2, 13.89, 31.37 |
#D0210201_Percentage_of_grants_to_local_governments_Prefectu_time |
Percentage of grants to local governments Prefectu (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D0210301_Percentage_of_national_disbursements_Prefecture |
Percentage of national disbursements Prefecture | float | 0% | 46 | 24.41, 23.03, 19.34, 21.22, 19.59 |
#D0210301_Percentage_of_national_disbursements_Prefecture_time |
Percentage of national disbursements Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D0220103_Resident_tax_per_capita_Prefecture_+_Municipality |
Resident tax per capita Prefecture + Municipality | float | 0% | 45 | 100.0, 81.3, 89.6, 109.5, 81.8 |
#D0220103_Resident_tax_per_capita_Prefecture_+_Municipality_time |
Resident tax per capita Prefecture + Municipality (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D02202_Fixed_assets_tax_per_capita_Prefecture_+_Municipalit |
Fixed assets tax per capita Prefecture + Municipalit | float | 0% | 43 | 60.1, 63.0, 66.9, 68.2, 59.1 |
#D02202_Fixed_assets_tax_per_capita_Prefecture_+_Municipalit_time |
Fixed assets tax per capita Prefecture + Municipalit (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
#D02204_Amount_of_national_tax_per_capita |
Amount of national tax per capita | float | 0% | 46 | 378.8, 256.6, 242.2, 415.4, 251.3 |
#D02204_Amount_of_national_tax_per_capita_time |
Amount of national tax per capita (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
#D02206_Taxable_income_per_tax_debtor |
Taxable income per tax debtor | float | 0% | 47 | 3446.5, 3048.6, 3087.4, 3499.5, 3044.2 |
#D02206_Taxable_income_per_tax_debtor_time |
Taxable income per tax debtor (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
#D02207_Ratio_of_taxpayer_per_capita |
Ratio of taxpayer per capita | float | 0% | 37 | 43.6, 42.1, 43.8, 44.8, 41.8 |
#D02207_Ratio_of_taxpayer_per_capita_time |
Ratio of taxpayer per capita (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
| +66 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Education Wide (admin_1)
— 47 rows, 120 columns
Loading data…
Field details — 120 fields (type, nulls, unique, samples)
Standards-Aligned Fields (2)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
Extension Fields (118)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
D110101_Number_of_cities,_towns_and_villages |
Number of cities, towns and villages | float | 0% | 30 | 179.0, 40.0, 33.0, 35.0, 25.0 |
D110101_Number_of_cities,_towns_and_villages_time |
Number of cities, towns and villages (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D110102_Number_of_cities_and_wards |
Number of cities and wards | float | 0% | 23 | 45.0, 10.0, 14.0, 19.0, 13.0 |
D110102_Number_of_cities_and_wards_time |
Number of cities and wards (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D110103_Number_of_towns_and_villages |
Number of towns and villages | float | 0% | 24 | 144.0, 30.0, 19.0, 21.0, 12.0 |
D110103_Number_of_towns_and_villages_time |
Number of towns and villages (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1201_Number_of_general_personnel_Prefecture |
Number of general personnel Prefecture | float | 0% | 47 | 12674.0, 3854.0, 4232.0, 4831.0, 3513.0 |
D1201_Number_of_general_personnel_Prefecture_time |
Number of general personnel Prefecture (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1202_Number_of_general_personnel_Municipality |
Number of general personnel Municipality | float | 0% | 47 | 34176.0, 7897.0, 8454.0, 13687.0, 6905.0 |
D1202_Number_of_general_personnel_Municipality_time |
Number of general personnel Municipality (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1203_Number_of_fire_service_personnel |
Number of fire service personnel | float | 0% | 47 | 9161.0, 2607.0, 2020.0, 3130.0, 2048.0 |
D1203_Number_of_fire_service_personnel_time |
Number of fire service personnel (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1204_Number_of_educational_service_personnel |
Number of educational service personnel | float | 0% | 47 | 51418.0, 11750.0, 13016.0, 21542.0, 9762.0 |
D1204_Number_of_educational_service_personnel_time |
Number of educational service personnel (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1205_Number_of_police_personnel |
Number of police personnel | float | 0% | 46 | 11726.0, 2661.0, 2429.0, 4354.0, 2362.0 |
D1205_Number_of_police_personnel_time |
Number of police personnel (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1206_Number_of_public_businesses_account_personnel |
Number of public businesses account personnel | float | 0% | 47 | 20821.0, 7896.0, 7575.0, 8436.0, 2945.0 |
D1206_Number_of_public_businesses_account_personnel_time |
Number of public businesses account personnel (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1210_Number_of_prefectural_assembly_members |
Number of prefectural assembly members | float | 0% | 30 | 99.0, 48.0, 48.0, 59.0, 40.0 |
D1210_Number_of_prefectural_assembly_members_time |
Number of prefectural assembly members (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1211_Number_of_municipal_assembly_members |
Number of municipal assembly members | float | 0% | 46 | 692.0, 221.0, 309.0, 323.0, 266.0 |
D1211_Number_of_municipal_assembly_members_time |
Number of municipal assembly members (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1212_Number_of_electoral_roll_subscribers |
Number of electoral roll subscribers | float | 0% | 47 | 4378810.0, 1037676.0, 1002566.0, 1901034.0, 805450.0 |
D1212_Number_of_electoral_roll_subscribers_time |
Number of electoral roll subscribers (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D2101_Financial_power_index_Prefecture |
Financial power index Prefecture | float | 0% | 47 | 0.44422, 0.34201, 0.35368, 0.59081, 0.3094 |
D2101_Financial_power_index_Prefecture_time |
Financial power index Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
D2102_Real_term_balance_of_revenue_to_expenditure_Prefecture |
Real term balance of revenue to expenditure Prefecture | float | 0% | 34 | 2.0, 2.1, 5.1, 2.8, 4.5 |
D2102_Real_term_balance_of_revenue_to_expenditure_Prefecture_time |
Real term balance of revenue to expenditure Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
D2103_Real_term_of_current_balance_Prefecture |
Real term of current balance Prefecture | float | 0% | 41 | 98.1, 94.5, 94.2, 96.4, 90.4 |
D2103_Real_term_of_current_balance_Prefecture_time |
Real term of current balance Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
| +88 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Employment Wide (admin_1)
— 47 rows, 684 columns
Loading data…
Field details — 684 fields (type, nulls, unique, samples)
Standards-Aligned Fields (4)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
F1101_Population_census_Population_in_labour_force |
Population census Population in labour force | float | SEL | 0% | 47 | 2449395.0, 631696.0, 628881.0, 1130271.0, 483500.0 |
F1107_Population_census_Number_of_unemployed_persons |
Population census Number of unemployed persons | float | SEL | 0% | 47 | 102125.0, 29305.0, 23788.0, 48923.0, 19606.0 |
Extension Fields (680)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
F1101_Population_census_Population_in_labour_force_time |
Population census Population in labour force (survey year) | float | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
F110101_Population_census_Population_in_labour_force_Male |
Population census Population in labour force Male | float | 0% | 47 | 1330807.0, 340826.0, 345726.0, 629922.0, 264047.0 |
F110101_Population_census_Population_in_labour_force_Male_time |
Population census Population in labour force Male (survey year) | float | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
F110102_Population_census_Population_in_labour_force_Female |
Population census Population in labour force Female | float | 0% | 47 | 1118588.0, 290870.0, 283155.0, 500349.0, 219453.0 |
F110102_Population_census_Population_in_labour_force_Female_time |
Population census Population in labour force Female (survey year) | float | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
F1102_Population_census_Number_of_employed_persons |
Population census Number of employed persons | float | 0% | 47 | 2347270.0, 602391.0, 605093.0, 1081348.0, 463894.0 |
F1102_Population_census_Number_of_employed_persons_time |
Population census Number of employed persons (survey year) | float | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
F110201_Population_census_Number_of_employed_persons_Male |
Population census Number of employed persons Male | float | 0% | 47 | 1269990.0, 322282.0, 330246.0, 599389.0, 251051.0 |
F110201_Population_census_Number_of_employed_persons_Male_time |
Population census Number of employed persons Male (survey year) | float | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
F110202_Population_census_Number_of_employed_persons_Female |
Population census Number of employed persons Female | float | 0% | 47 | 1077280.0, 280109.0, 274847.0, 481959.0, 212843.0 |
F110202_Population_census_Number_of_employed_persons_Female_time |
Population census Number of employed persons Female (survey year) | float | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
F1103_Population_census_Number_of_employed_persons,_mainly_w |
Population census Number of employed persons, mainly w | float | 0% | 47 | 1970647.0, 528372.0, 527062.0, 918675.0, 403705.0 |
F1103_Population_census_Number_of_employed_persons,_mainly_w_time |
Population census Number of employed persons, mainly w (survey year) | float | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
F110301_Population_census_Number_of_employed_persons,_mainly |
Population census Number of employed persons, mainly | float | 0% | 47 | 1436470.0, 367711.0, 369980.0, 615692.0, 298878.0 |
F110301_Population_census_Number_of_employed_persons,_mainly_time |
Population census Number of employed persons, mainly (survey year) | float | 0% | 1 | 2005, 2005, 2005, 2005, 2005 |
F110302_Population_census_Number_of_employed_persons,_mainly |
Population census Number of employed persons, mainly | float | 0% | 47 | 734330.0, 219329.0, 213361.0, 316360.0, 168195.0 |
F110302_Population_census_Number_of_employed_persons,_mainly_time |
Population census Number of employed persons, mainly (survey year) | float | 0% | 1 | 2005, 2005, 2005, 2005, 2005 |
F1104_Population_census_Number_of_employed_persons,_working_ |
Population census Number of employed persons, working | float | 0% | 47 | 284760.0, 55268.0, 60650.0, 117158.0, 47345.0 |
F1104_Population_census_Number_of_employed_persons,_working__time |
Population census Number of employed persons, working (survey year) | float | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
F110401_Population_census_Number_of_employed_persons,_workin |
Population census Number of employed persons, workin | float | 0% | 47 | 16240.0, 5162.0, 7753.0, 10366.0, 6205.0 |
F110401_Population_census_Number_of_employed_persons,_workin_time |
Population census Number of employed persons, workin (survey year) | float | 0% | 1 | 2005, 2005, 2005, 2005, 2005 |
F110402_Population_census_Number_of_employed_persons,_workin |
Population census Number of employed persons, workin | float | 0% | 47 | 342466.0, 77984.0, 82677.0, 131852.0, 66540.0 |
F110402_Population_census_Number_of_employed_persons,_workin_time |
Population census Number of employed persons, workin (survey year) | float | 0% | 1 | 2005, 2005, 2005, 2005, 2005 |
F1105_Population_census_Number_of_employed_persons,_working_ |
Population census Number of employed persons, working | float | 0% | 47 | 38293.0, 4949.0, 4644.0, 19141.0, 2921.0 |
F1105_Population_census_Number_of_employed_persons,_working__time |
Population census Number of employed persons, working (survey year) | float | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
F110501_Population_census_Number_of_employed_persons,_workin |
Population census Number of employed persons, workin | float | 0% | 47 | 20553.0, 2030.0, 2124.0, 9521.0, 1477.0 |
F110501_Population_census_Number_of_employed_persons,_workin_time |
Population census Number of employed persons, workin (survey year) | float | 0% | 1 | 2005, 2005, 2005, 2005, 2005 |
F110502_Population_census_Number_of_employed_persons,_workin |
Population census Number of employed persons, workin | float | 0% | 47 | 18596.0, 2218.0, 2353.0, 8233.0, 1320.0 |
F110502_Population_census_Number_of_employed_persons,_workin_time |
Population census Number of employed persons, workin (survey year) | float | 0% | 1 | 2005, 2005, 2005, 2005, 2005 |
F1106_Population_census_Number_of_employed_persons,_being_ab |
Population census Number of employed persons, being ab | float | 0% | 47 | 53570.0, 13802.0, 12737.0, 26374.0, 9923.0 |
| +650 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Health Wide (admin_1)
— 47 rows, 120 columns
Loading data…
Field details — 120 fields (type, nulls, unique, samples)
Standards-Aligned Fields (2)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
Extension Fields (118)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
D110101_Number_of_cities,_towns_and_villages |
Number of cities, towns and villages | float | 0% | 30 | 179.0, 40.0, 33.0, 35.0, 25.0 |
D110101_Number_of_cities,_towns_and_villages_time |
Number of cities, towns and villages (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D110102_Number_of_cities_and_wards |
Number of cities and wards | float | 0% | 23 | 45.0, 10.0, 14.0, 19.0, 13.0 |
D110102_Number_of_cities_and_wards_time |
Number of cities and wards (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D110103_Number_of_towns_and_villages |
Number of towns and villages | float | 0% | 24 | 144.0, 30.0, 19.0, 21.0, 12.0 |
D110103_Number_of_towns_and_villages_time |
Number of towns and villages (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1201_Number_of_general_personnel_Prefecture |
Number of general personnel Prefecture | float | 0% | 47 | 12674.0, 3854.0, 4232.0, 4831.0, 3513.0 |
D1201_Number_of_general_personnel_Prefecture_time |
Number of general personnel Prefecture (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1202_Number_of_general_personnel_Municipality |
Number of general personnel Municipality | float | 0% | 47 | 34176.0, 7897.0, 8454.0, 13687.0, 6905.0 |
D1202_Number_of_general_personnel_Municipality_time |
Number of general personnel Municipality (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1203_Number_of_fire_service_personnel |
Number of fire service personnel | float | 0% | 47 | 9161.0, 2607.0, 2020.0, 3130.0, 2048.0 |
D1203_Number_of_fire_service_personnel_time |
Number of fire service personnel (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1204_Number_of_educational_service_personnel |
Number of educational service personnel | float | 0% | 47 | 51418.0, 11750.0, 13016.0, 21542.0, 9762.0 |
D1204_Number_of_educational_service_personnel_time |
Number of educational service personnel (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1205_Number_of_police_personnel |
Number of police personnel | float | 0% | 46 | 11726.0, 2661.0, 2429.0, 4354.0, 2362.0 |
D1205_Number_of_police_personnel_time |
Number of police personnel (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1206_Number_of_public_businesses_account_personnel |
Number of public businesses account personnel | float | 0% | 47 | 20821.0, 7896.0, 7575.0, 8436.0, 2945.0 |
D1206_Number_of_public_businesses_account_personnel_time |
Number of public businesses account personnel (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1210_Number_of_prefectural_assembly_members |
Number of prefectural assembly members | float | 0% | 30 | 99.0, 48.0, 48.0, 59.0, 40.0 |
D1210_Number_of_prefectural_assembly_members_time |
Number of prefectural assembly members (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1211_Number_of_municipal_assembly_members |
Number of municipal assembly members | float | 0% | 46 | 692.0, 221.0, 309.0, 323.0, 266.0 |
D1211_Number_of_municipal_assembly_members_time |
Number of municipal assembly members (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D1212_Number_of_electoral_roll_subscribers |
Number of electoral roll subscribers | float | 0% | 47 | 4378810.0, 1037676.0, 1002566.0, 1901034.0, 805450.0 |
D1212_Number_of_electoral_roll_subscribers_time |
Number of electoral roll subscribers (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
D2101_Financial_power_index_Prefecture |
Financial power index Prefecture | float | 0% | 47 | 0.44422, 0.34201, 0.35368, 0.59081, 0.3094 |
D2101_Financial_power_index_Prefecture_time |
Financial power index Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
D2102_Real_term_balance_of_revenue_to_expenditure_Prefecture |
Real term balance of revenue to expenditure Prefecture | float | 0% | 34 | 2.0, 2.1, 5.1, 2.8, 4.5 |
D2102_Real_term_balance_of_revenue_to_expenditure_Prefecture_time |
Real term balance of revenue to expenditure Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
D2103_Real_term_of_current_balance_Prefecture |
Real term of current balance Prefecture | float | 0% | 41 | 98.1, 94.5, 94.2, 96.4, 90.4 |
D2103_Real_term_of_current_balance_Prefecture_time |
Real term of current balance Prefecture (survey year) | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
| +88 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Housing Wide (admin_1)
— 47 rows, 448 columns
Loading data…
Field details — 448 fields (type, nulls, unique, samples)
Standards-Aligned Fields (6)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
H1100_Number_of_dwellings |
Number of dwellings | float | SEL | 0% | 47 | 2888500.0, 590300.0, 579400.0, 1129200.0, 440600.0 |
H1101_Number_of_dwellings_with_occupying_households |
Number of dwellings with occupying households | float | SEL | 0% | 47 | 2423200.0, 488700.0, 476700.0, 983900.0, 369400.0 |
H1102_Number_of_unoccupied_dwellings |
Number of unoccupied dwellings | float | SEL | 0% | 47 | 465300.0, 101600.0, 102800.0, 145300.0, 71200.0 |
H3100_Number_of_total_households |
Number of total households | float | SEL | 0% | 47 | 2455900.0, 496300.0, 482000.0, 992800.0, 373700.0 |
Extension Fields (442)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
H1100_Number_of_dwellings_time |
Number of dwellings (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1101_Number_of_dwellings_with_occupying_households_time |
Number of dwellings with occupying households (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1102_Number_of_unoccupied_dwellings_time |
Number of unoccupied dwellings (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H110201_Number_of_houses_with_temporary_sojourners |
Number of houses with temporary sojourners | float | 0% | 33 | 10000.0, 1900.0, 1700.0, 3300.0, 1100.0 |
H110201_Number_of_houses_with_temporary_sojourners_time |
Number of houses with temporary sojourners (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H110202_Number_of_vacant_houses |
Number of vacant houses | float | 0% | 47 | 451900.0, 98800.0, 100400.0, 140300.0, 69500.0 |
H110202_Number_of_vacant_houses_time |
Number of vacant houses (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H110203_Number_of_dwellings_under_construction |
Number of dwellings under construction | float | 0% | 29 | 3300.0, 900.0, 600.0, 1700.0, 600.0 |
H110203_Number_of_dwellings_under_construction_time |
Number of dwellings under construction (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1201_Number_of_dwellings_used_exclusively_for_living |
Number of dwellings used exclusively for living | float | 0% | 47 | 2384100.0, 478600.0, 467300.0, 974000.0, 360000.0 |
H1201_Number_of_dwellings_used_exclusively_for_living_time |
Number of dwellings used exclusively for living (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1203_Number_of_dwellings_used_also_for_commerce_or_other_pu |
Number of dwellings used also for commerce or other pu | float | 0% | 43 | 39100.0, 10100.0, 9400.0, 9800.0, 9400.0 |
H1203_Number_of_dwellings_used_also_for_commerce_or_other_pu_time |
Number of dwellings used also for commerce or other pu (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1310_Number_of_owned_houses |
Number of owned houses | float | 0% | 47 | 1381200.0, 349100.0, 334900.0, 590100.0, 284800.0 |
H1310_Number_of_owned_houses_time |
Number of owned houses (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1320_Number_of_rented_houses |
Number of rented houses | float | 0% | 47 | 961400.0, 126000.0, 131800.0, 357400.0, 77200.0 |
H1320_Number_of_rented_houses_time |
Number of rented houses (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1321_Number_of_rented_houses_owned_by_local_government_and_ |
Number of rented houses owned by local government and | float | 0% | 47 | 138100.0, 16400.0, 16100.0, 38000.0, 8700.0 |
H1321_Number_of_rented_houses_owned_by_local_government_and__time |
Number of rented houses owned by local government and (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H132101_Number_of_rented_houses_owned_by_local_government |
Number of rented houses owned by local government | float | 0% | 45 | 131900.0, 16400.0, 16100.0, 35900.0, 8700.0 |
H132101_Number_of_rented_houses_owned_by_local_government_time |
Number of rented houses owned by local government (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H132102_Number_of_rented_houses_owned_by_Urban_Renaissance_A |
Number of rented houses owned by Urban Renaissance A | float | 0% | 24 | 6200.0, 0.0, 200.0, 2100.0, 0.0 |
H132102_Number_of_rented_houses_owned_by_Urban_Renaissance_A_time |
Number of rented houses owned by Urban Renaissance A (survey year) | float | 0% | 4 | 2023, 2013, 2018, 2023, 2018 |
H1322_Number_of_rented_houses_owned_privately |
Number of rented houses owned privately | float | 0% | 47 | 758100.0, 99300.0, 103500.0, 294600.0, 61600.0 |
H1322_Number_of_rented_houses_owned_privately_time |
Number of rented houses owned privately (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1323_Number_of_issued_houses |
Number of issued houses | float | 0% | 45 | 65200.0, 10300.0, 12200.0, 24800.0, 6900.0 |
H1323_Number_of_issued_houses_time |
Number of issued houses (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1401_Number_of_detached_houses_Total |
Number of detached houses Total | float | 0% | 47 | 1258400.0, 368000.0, 344000.0, 543200.0, 293200.0 |
H1401_Number_of_detached_houses_Total_time |
Number of detached houses Total (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H140101_Number_of_detached_houses_Wooden |
Number of detached houses Wooden | float | 0% | 47 | 1183800.0, 356700.0, 328200.0, 500400.0, 284200.0 |
| +412 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Municipality Pop Wide (admin_1)
— 47 rows, 448 columns
Loading data…
Field details — 448 fields (type, nulls, unique, samples)
Standards-Aligned Fields (6)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
H1100_Number_of_dwellings |
Number of dwellings | float | SEL | 0% | 47 | 2888500.0, 590300.0, 579400.0, 1129200.0, 440600.0 |
H1101_Number_of_dwellings_with_occupying_households |
Number of dwellings with occupying households | float | SEL | 0% | 47 | 2423200.0, 488700.0, 476700.0, 983900.0, 369400.0 |
H1102_Number_of_unoccupied_dwellings |
Number of unoccupied dwellings | float | SEL | 0% | 47 | 465300.0, 101600.0, 102800.0, 145300.0, 71200.0 |
H3100_Number_of_total_households |
Number of total households | float | SEL | 0% | 47 | 2455900.0, 496300.0, 482000.0, 992800.0, 373700.0 |
Extension Fields (442)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
H1100_Number_of_dwellings_time |
Number of dwellings (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1101_Number_of_dwellings_with_occupying_households_time |
Number of dwellings with occupying households (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1102_Number_of_unoccupied_dwellings_time |
Number of unoccupied dwellings (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H110201_Number_of_houses_with_temporary_sojourners |
Number of houses with temporary sojourners | float | 0% | 33 | 10000.0, 1900.0, 1700.0, 3300.0, 1100.0 |
H110201_Number_of_houses_with_temporary_sojourners_time |
Number of houses with temporary sojourners (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H110202_Number_of_vacant_houses |
Number of vacant houses | float | 0% | 47 | 451900.0, 98800.0, 100400.0, 140300.0, 69500.0 |
H110202_Number_of_vacant_houses_time |
Number of vacant houses (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H110203_Number_of_dwellings_under_construction |
Number of dwellings under construction | float | 0% | 29 | 3300.0, 900.0, 600.0, 1700.0, 600.0 |
H110203_Number_of_dwellings_under_construction_time |
Number of dwellings under construction (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1201_Number_of_dwellings_used_exclusively_for_living |
Number of dwellings used exclusively for living | float | 0% | 47 | 2384100.0, 478600.0, 467300.0, 974000.0, 360000.0 |
H1201_Number_of_dwellings_used_exclusively_for_living_time |
Number of dwellings used exclusively for living (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1203_Number_of_dwellings_used_also_for_commerce_or_other_pu |
Number of dwellings used also for commerce or other pu | float | 0% | 43 | 39100.0, 10100.0, 9400.0, 9800.0, 9400.0 |
H1203_Number_of_dwellings_used_also_for_commerce_or_other_pu_time |
Number of dwellings used also for commerce or other pu (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1310_Number_of_owned_houses |
Number of owned houses | float | 0% | 47 | 1381200.0, 349100.0, 334900.0, 590100.0, 284800.0 |
H1310_Number_of_owned_houses_time |
Number of owned houses (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1320_Number_of_rented_houses |
Number of rented houses | float | 0% | 47 | 961400.0, 126000.0, 131800.0, 357400.0, 77200.0 |
H1320_Number_of_rented_houses_time |
Number of rented houses (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1321_Number_of_rented_houses_owned_by_local_government_and_ |
Number of rented houses owned by local government and | float | 0% | 47 | 138100.0, 16400.0, 16100.0, 38000.0, 8700.0 |
H1321_Number_of_rented_houses_owned_by_local_government_and__time |
Number of rented houses owned by local government and (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H132101_Number_of_rented_houses_owned_by_local_government |
Number of rented houses owned by local government | float | 0% | 45 | 131900.0, 16400.0, 16100.0, 35900.0, 8700.0 |
H132101_Number_of_rented_houses_owned_by_local_government_time |
Number of rented houses owned by local government (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H132102_Number_of_rented_houses_owned_by_Urban_Renaissance_A |
Number of rented houses owned by Urban Renaissance A | float | 0% | 24 | 6200.0, 0.0, 200.0, 2100.0, 0.0 |
H132102_Number_of_rented_houses_owned_by_Urban_Renaissance_A_time |
Number of rented houses owned by Urban Renaissance A (survey year) | float | 0% | 4 | 2023, 2013, 2018, 2023, 2018 |
H1322_Number_of_rented_houses_owned_privately |
Number of rented houses owned privately | float | 0% | 47 | 758100.0, 99300.0, 103500.0, 294600.0, 61600.0 |
H1322_Number_of_rented_houses_owned_privately_time |
Number of rented houses owned privately (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1323_Number_of_issued_houses |
Number of issued houses | float | 0% | 45 | 65200.0, 10300.0, 12200.0, 24800.0, 6900.0 |
H1323_Number_of_issued_houses_time |
Number of issued houses (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H1401_Number_of_detached_houses_Total |
Number of detached houses Total | float | 0% | 47 | 1258400.0, 368000.0, 344000.0, 543200.0, 293200.0 |
H1401_Number_of_detached_houses_Total_time |
Number of detached houses Total (survey year) | float | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
H140101_Number_of_detached_houses_Wooden |
Number of detached houses Wooden | float | 0% | 47 | 1183800.0, 356700.0, 328200.0, 500400.0, 284200.0 |
| +412 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Population Wide (admin_1)
— 47 rows, 88 columns
Loading data…
Field details — 88 fields (type, nulls, unique, samples)
Standards-Aligned Fields (7)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | float | SEL | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
A1101_Total_population_Both_sexes |
Total population Both sexes | float | SEL | 0% | 47 | 5043000.0, 1165000.0, 1145000.0, 2248000.0, 897000.0 |
A110101_Total_population_Male |
Total population Male | float | SEL | 0% | 46 | 2382000.0, 549000.0, 553000.0, 1096000.0, 424000.0 |
A110102_Total_population_Female |
Total population Female | float | SEL | 0% | 46 | 2661000.0, 615000.0, 592000.0, 1152000.0, 473000.0 |
population_0_14 |
Population aged 0-14 (derived) | integer | SEL | 0% | - | - |
population_60_plus |
Population aged 60 and over (derived) | integer | SEL | 0% | - | - |
Extension Fields (81)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
A1101_Total_population_Both_sexes_time |
Total population Both sexes (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A110101_Total_population_Male_time |
Total population Male (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A110102_Total_population_Female_time |
Total population Female (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A1102_Japanese_population_Both_sexes |
Japanese population Both sexes | float | 0% | 47 | 4980000.0, 1157000.0, 1134000.0, 2219000.0, 891000.0 |
A1102_Japanese_population_Both_sexes_time |
Japanese population Both sexes (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A110201_Japanese_population_Male |
Japanese population Male | float | 0% | 47 | 2351000.0, 546000.0, 548000.0, 1082000.0, 422000.0 |
A110201_Japanese_population_Male_time |
Japanese population Male (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A110202_Japanese_population_Female |
Japanese population Female | float | 0% | 46 | 2629000.0, 611000.0, 586000.0, 1137000.0, 469000.0 |
A110202_Japanese_population_Female_time |
Japanese population Female (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A1201_Population_0-4,_Total |
Population 0-4, Total | float | 0% | 38 | 134000.0, 30000.0, 30000.0, 66000.0, 20000.0 |
A1201_Population_0-4,_Total_time |
Population 0-4, Total (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A120101_Population_0-4,_Male |
Population 0-4, Male | float | 0% | 34 | 69000.0, 16000.0, 15000.0, 34000.0, 10000.0 |
A120101_Population_0-4,_Male_time |
Population 0-4, Male (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A120102_Population_0-4,_Female |
Population 0-4, Female | float | 0% | 32 | 66000.0, 15000.0, 14000.0, 32000.0, 10000.0 |
A120102_Population_0-4,_Female_time |
Population 0-4, Female (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A1202_Population_5-9,_Total |
Population 5-9, Total | float | 0% | 39 | 170000.0, 39000.0, 39000.0, 84000.0, 27000.0 |
A1202_Population_5-9,_Total_time |
Population 5-9, Total (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A120201_Population_5-9,_Male |
Population 5-9, Male | float | 0% | 36 | 87000.0, 20000.0, 20000.0, 43000.0, 14000.0 |
A120201_Population_5-9,_Male_time |
Population 5-9, Male (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A120202_Population_5-9,_Female |
Population 5-9, Female | float | 0% | 32 | 83000.0, 19000.0, 19000.0, 41000.0, 13000.0 |
A120202_Population_5-9,_Female_time |
Population 5-9, Female (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A1203_Population_10-14,_Total |
Population 10-14, Total | float | 0% | 40 | 193000.0, 45000.0, 46000.0, 94000.0, 32000.0 |
A1203_Population_10-14,_Total_time |
Population 10-14, Total (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A120301_Population_10-14,_Male |
Population 10-14, Male | float | 0% | 35 | 99000.0, 23000.0, 24000.0, 48000.0, 17000.0 |
A120301_Population_10-14,_Male_time |
Population 10-14, Male (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A120302_Population_10-14,_Female |
Population 10-14, Female | float | 0% | 34 | 94000.0, 22000.0, 23000.0, 46000.0, 16000.0 |
A120302_Population_10-14,_Female_time |
Population 10-14, Female (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A1204_Population_15-19,_Total |
Population 15-19, Total | float | 0% | 38 | 206000.0, 47000.0, 48000.0, 100000.0, 35000.0 |
A1204_Population_15-19,_Total_time |
Population 15-19, Total (survey year) | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
A120401_Population_15-19,_Male |
Population 15-19, Male | float | 0% | 34 | 106000.0, 24000.0, 25000.0, 51000.0, 18000.0 |
| +51 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Municipal Economic Census (admin_1)
— 47 rows, 24 columns
Loading data…
Field details — 24 fields (type, nulls, unique, samples)
Standards-Aligned Fields (6)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | SEL | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
area_name |
Geographic-area English name as returned by e-Stat | string | SEL | 0% | 47 | Hokkaido, Aomori-ken, Iwate-ken, Miyagi-ken, Akita-ken |
admin_level |
Administrative level (admin_0..admin_4) | string | SEL | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
Number_of_establishments_Total |
Number of establishments Total | float | SEL | 0% | 47 | 221456.0, 56336.0, 56168.0, 96563.0, 46483.0 |
Number_of_persons_engaged_Male_and_Female_Total |
Number of persons engaged Male and Female Total | float | SEL | 0% | 47 | 2396587.0, 562624.0, 572412.0, 1115600.0, 442272.0 |
Extension Fields (8)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total |
Number of establishments Including establishments not reported their industry et Total | float | 0% | 47 | 249011.0, 60013.0, 59231.0, 107148.0, 48959.0 |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned |
Number of establishments Including establishments not reported their industry et Privately owned | float | 0% | 47 | 240581.0, 58200.0, 57007.0, 104496.0, 46993.0 |
Number_of_establishments_Privately_owned |
Number of establishments Privately owned | float | 0% | 47 | 213026.0, 54523.0, 53944.0, 93911.0, 44517.0 |
Number_of_persons_engaged_Male_and_Female_Privately_owned |
Number of persons engaged Male and Female Privately owned | float | 0% | 47 | 2153312.0, 498573.0, 515967.0, 1022384.0, 399204.0 |
Number_of_persons_engaged_Male_Total |
Number of persons engaged Male Total | float | 0% | 47 | 1306545.0, 299815.0, 311964.0, 623145.0, 237972.0 |
Number_of_persons_engaged_Male_Privately_owned |
Number of persons engaged Male Privately owned | float | 0% | 47 | 1152711.0, 261314.0, 282752.0, 571389.0, 213681.0 |
Number_of_persons_engaged_Female_Total |
Number of persons engaged Female Total | float | 0% | 47 | 1070725.0, 261063.0, 258002.0, 486966.0, 202871.0 |
Number_of_persons_engaged_Female_Privately_owned |
Number of persons engaged Female Privately owned | float | 0% | 47 | 981284.0, 235513.0, 230769.0, 445506.0, 184094.0 |
Pending (10) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total_time |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned_time |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_establishments_Total_time |
Number_of_establishments_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_establishments_Privately_owned_time |
Number_of_establishments_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_and_Female_Total_time |
Number_of_persons_engaged_Male_and_Female_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_and_Female_Privately_owned_time |
Number_of_persons_engaged_Male_and_Female_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_Total_time |
Number_of_persons_engaged_Male_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_Privately_owned_time |
Number_of_persons_engaged_Male_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Female_Total_time |
Number_of_persons_engaged_Female_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Female_Privately_owned_time |
Number_of_persons_engaged_Female_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
JPN e-Stat - Municipal Pop Age Marital (admin_1)
— 47 rows, 1,732 columns
Loading data…
Field details — 1732 fields (type, nulls, unique, samples)
Standards-Aligned Fields (4)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | SEL | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
area_name |
Geographic-area English name as returned by e-Stat | string | SEL | 0% | 47 | Hokkaido, Aomori-ken, Iwate-ken, Miyagi-ken, Akita-ken |
admin_level |
Administrative level (admin_0..admin_4) | string | SEL | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
Extension Fields (864)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Population_Total_Total_Total_Total |
Population Total Total Total Total | float | 0% | 47 | 3487579.0, 506339.0, 340858.0, 1282296.0, 298218.0 |
Population_Total_Total_Total_15_19_years_old |
Population Total Total Total 15 19 years old | float | 0% | 47 | 173047.0, 26183.0, 19424.0, 74503.0, 14055.0 |
Population_Total_Total_Total_20_24_years_old |
Population Total Total Total 20 24 years old | float | 0% | 47 | 180908.0, 23715.0, 18381.0, 83807.0, 13589.0 |
Population_Total_Total_Total_25_29_years_old |
Population Total Total Total 25 29 years old | float | 0% | 47 | 182187.0, 23927.0, 18581.0, 78919.0, 14202.0 |
Population_Total_Total_Total_30_34_years_old |
Population Total Total Total 30 34 years old | float | 0% | 47 | 198082.0, 27292.0, 20485.0, 86428.0, 15944.0 |
Population_Total_Total_Total_35_39_years_old |
Population Total Total Total 35 39 years old | float | 0% | 47 | 228194.0, 32329.0, 23529.0, 96435.0, 18751.0 |
Population_Total_Total_Total_40_44_years_old |
Population Total Total Total 40 44 years old | float | 0% | 47 | 265397.0, 38084.0, 27477.0, 106765.0, 22662.0 |
Population_Total_Total_Total_45_49_years_old |
Population Total Total Total 45 49 years old | float | 0% | 47 | 304584.0, 43007.0, 30225.0, 117962.0, 24881.0 |
Population_Total_Total_Total_50_54_years_old |
Population Total Total Total 50 54 years old | float | 0% | 47 | 267107.0, 39712.0, 26804.0, 101298.0, 22225.0 |
Population_Total_Total_Total_55_59_years_old |
Population Total Total Total 55 59 years old | float | 0% | 47 | 256113.0, 39377.0, 25526.0, 91102.0, 22374.0 |
Population_Total_Total_Total_60_64_years_old |
Population Total Total Total 60 64 years old | float | 0% | 47 | 248338.0, 39570.0, 24411.0, 85248.0, 22790.0 |
Population_Total_Total_Total_65_69_years_old |
Population Total Total Total 65 69 years old | float | 0% | 47 | 288858.0, 42634.0, 25248.0, 90755.0, 25106.0 |
Population_Total_Total_Total_70_74_years_old |
Population Total Total Total 70 74 years old | float | 0% | 47 | 307483.0, 45062.0, 25813.0, 92108.0, 26728.0 |
Population_Total_Total_Total_75_79_years_old |
Population Total Total Total 75 79 years old | float | 0% | 47 | 220920.0, 32776.0, 19885.0, 68428.0, 19411.0 |
Population_Total_Total_Total_80_84_years_old |
Population Total Total Total 80 84 years old | float | 0% | 47 | 171751.0, 25764.0, 16107.0, 52095.0, 16584.0 |
Population_Total_Total_Total_85_89_years_old |
Population Total Total Total 85 89 years old | float | 0% | 47 | 120011.0, 17660.0, 11841.0, 35514.0, 11776.0 |
Population_Total_Total_Total_90_94_years_old |
Population Total Total Total 90 94 years old | float | 0% | 47 | 57245.0, 7338.0, 5487.0, 16124.0, 5644.0 |
Population_Total_Total_Total_95_99_years_old |
Population Total Total Total 95 99 years old | float | 0% | 47 | 15091.0, 1702.0, 1432.0, 4200.0, 1343.0 |
Population_Total_Total_Total_100_years_old_and_over |
Population Total Total Total 100 years old and over | float | 0% | 46 | 2263.0, 207.0, 202.0, 605.0, 153.0 |
Population_Total_Total_Total_Recount_15_64_years_old |
Population Total Total Total Recount 15 64 years old | float | 0% | 47 | 2303957.0, 333196.0, 234843.0, 922467.0, 191473.0 |
Population_Total_Total_Total_Recount_65_years_old_and_over |
Population Total Total Total Recount 65 years old and over | float | 0% | 47 | 1183622.0, 173143.0, 106015.0, 359829.0, 106745.0 |
Population_Total_Total_Total_Recount_75_years_old_and_over |
Population Total Total Total Recount 75 years old and over | float | 0% | 47 | 587281.0, 85447.0, 54954.0, 176966.0, 54911.0 |
Population_Total_Total_Total_Recount_85_years_old_and_over |
Population Total Total Total Recount 85 years old and over | float | 0% | 47 | 194610.0, 26907.0, 18962.0, 56443.0, 18916.0 |
Population_Total_Total_Total_Recount_20_69_years_old |
Population Total Total Total Recount 20 69 years old | float | 0% | 47 | 2419768.0, 349647.0, 240667.0, 938719.0, 202524.0 |
Population_Total_Total_Never_married_Total |
Population Total Total Never married Total | float | 0% | 47 | 890769.0, 133075.0, 95336.0, 362962.0, 73871.0 |
Population_Total_Total_Never_married_15_19_years_old |
Population Total Total Never married 15 19 years old | float | 0% | 47 | 170682.0, 25973.0, 19300.0, 73609.0, 13981.0 |
Population_Total_Total_Never_married_20_24_years_old |
Population Total Total Never married 20 24 years old | float | 0% | 47 | 154116.0, 21348.0, 16726.0, 73243.0, 12199.0 |
Population_Total_Total_Never_married_25_29_years_old |
Population Total Total Never married 25 29 years old | float | 0% | 47 | 108090.0, 15079.0, 11449.0, 47637.0, 8694.0 |
Population_Total_Total_Never_married_30_34_years_old |
Population Total Total Never married 30 34 years old | float | 0% | 47 | 76356.0, 11337.0, 7958.0, 32946.0, 6438.0 |
Population_Total_Total_Never_married_35_39_years_old |
Population Total Total Never married 35 39 years old | float | 0% | 47 | 64683.0, 9992.0, 6673.0, 26251.0, 5567.0 |
| +834 more extension fields — download the CSV/Parquet to see them all. | |||||
Pending (864) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Population_Total_Total_Total_Total_time |
Population_Total_Total_Total_Total_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_15_19_years_old_time |
Population_Total_Total_Total_15_19_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_20_24_years_old_time |
Population_Total_Total_Total_20_24_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_25_29_years_old_time |
Population_Total_Total_Total_25_29_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_30_34_years_old_time |
Population_Total_Total_Total_30_34_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_35_39_years_old_time |
Population_Total_Total_Total_35_39_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_40_44_years_old_time |
Population_Total_Total_Total_40_44_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_45_49_years_old_time |
Population_Total_Total_Total_45_49_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_50_54_years_old_time |
Population_Total_Total_Total_50_54_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_55_59_years_old_time |
Population_Total_Total_Total_55_59_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_60_64_years_old_time |
Population_Total_Total_Total_60_64_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_65_69_years_old_time |
Population_Total_Total_Total_65_69_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_70_74_years_old_time |
Population_Total_Total_Total_70_74_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_75_79_years_old_time |
Population_Total_Total_Total_75_79_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_80_84_years_old_time |
Population_Total_Total_Total_80_84_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_85_89_years_old_time |
Population_Total_Total_Total_85_89_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_90_94_years_old_time |
Population_Total_Total_Total_90_94_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_95_99_years_old_time |
Population_Total_Total_Total_95_99_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_100_years_old_and_over_time |
Population_Total_Total_Total_100_years_old_and_over_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_Recount_15_64_years_old_time |
Population_Total_Total_Total_Recount_15_64_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_Recount_65_years_old_and_over_time |
Population_Total_Total_Total_Recount_65_years_old_and_over_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_Recount_75_years_old_and_over_time |
Population_Total_Total_Total_Recount_75_years_old_and_over_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_Recount_85_years_old_and_over_time |
Population_Total_Total_Total_Recount_85_years_old_and_over_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_Recount_20_69_years_old_time |
Population_Total_Total_Total_Recount_20_69_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_Total_time |
Population_Total_Total_Never_married_Total_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_15_19_years_old_time |
Population_Total_Total_Never_married_15_19_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_20_24_years_old_time |
Population_Total_Total_Never_married_20_24_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_25_29_years_old_time |
Population_Total_Total_Never_married_25_29_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_30_34_years_old_time |
Population_Total_Total_Never_married_30_34_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_35_39_years_old_time |
Population_Total_Total_Never_married_35_39_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
| +834 more pending fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Municipal Population By Sex (admin_1)
— 47 rows, 10 columns
Loading data…
Field details — 10 fields (type, nulls, unique, samples)
Standards-Aligned Fields (7)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | SEL | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
area_name |
Geographic-area English name as returned by e-Stat | string | SEL | 0% | 47 | Hokkaido, Aomori-ken, Iwate-ken, Miyagi-ken, Akita-ken |
admin_level |
Administrative level (admin_0..admin_4) | string | SEL | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
Population_Total |
Population Total | float | SEL | 0% | 47 | 5224614.0, 1237984.0, 1210534.0, 2301996.0, 959502.0 |
Population_Male |
Population Male | float | SEL | 0% | 47 | 2465088.0, 583402.0, 582952.0, 1122598.0, 452439.0 |
Population_Female |
Population Female | float | SEL | 0% | 47 | 2759526.0, 654582.0, 627582.0, 1179398.0, 507063.0 |
Pending (3) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Population_Total_time |
Population_Total_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Male_time |
Population_Male_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Female_time |
Population_Female_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
JPN e-Stat - Ssds E Education (admin_1)
— 47 rows, 992 columns
Loading data…
Field details — 992 fields (type, nulls, unique, samples)
Pending (992) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
area_name |
Geographic-area English name as returned by e-Stat | string | 0% | 47 | Hokkaido, Aomori-ken, Iwate-ken, Miyagi-ken, Akita-ken |
admin_level |
Administrative level (admin_0..admin_4) | string | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
Observation_value_E1101_Number_of_kindergartens |
Observation_value_E1101_Number_of_kindergartens | float | 0% | 46 | 322.0, 81.0, 56.0, 201.0, 31.0 |
Observation_value_E1101_Number_of_kindergartens_time |
Observation_value_E1101_Number_of_kindergartens_time | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
Observation_value_E110102_Number_of_kindergartens_Public |
Observation_value_E110102_Number_of_kindergartens_Public | float | 0% | 38 | 34.0, 2.0, 18.0, 57.0, 1.0 |
Observation_value_E110102_Number_of_kindergartens_Public_time |
Observation_value_E110102_Number_of_kindergartens_Public_time | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
Observation_value_E1201_Number_of_kindergarten_classes |
Observation_value_E1201_Number_of_kindergarten_classes | float | 0% | 46 | 1595.0, 306.0, 231.0, 932.0, 119.0 |
Observation_value_E1201_Number_of_kindergarten_classes_time |
Observation_value_E1201_Number_of_kindergarten_classes_time | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
Observation_value_E120101_Number_of_kindergarten_classes_National |
Observation_value_E120101_Number_of_kindergarten_classes_National | float | 0% | 8 | 6.0, 5.0, 5.0, 5.0, 5.0 |
Observation_value_E120101_Number_of_kindergarten_classes_National_time |
Observation_value_E120101_Number_of_kindergarten_classes_National_time | integer | 0% | 1 | 2008, 2008, 2008, 2008, 2008 |
Observation_value_E120102_Number_of_kindergarten_classes_Public |
Observation_value_E120102_Number_of_kindergarten_classes_Public | float | 0% | 44 | 270.0, 36.0, 198.0, 322.0, 92.0 |
Observation_value_E120102_Number_of_kindergarten_classes_Public_time |
Observation_value_E120102_Number_of_kindergarten_classes_Public_time | integer | 0% | 1 | 2008, 2008, 2008, 2008, 2008 |
Observation_value_E120103_Number_of_kindergarten_classes_Private |
Observation_value_E120103_Number_of_kindergarten_classes_Private | float | 0% | 47 | 2710.0, 523.0, 480.0, 1167.0, 377.0 |
Observation_value_E120103_Number_of_kindergarten_classes_Private_time |
Observation_value_E120103_Number_of_kindergarten_classes_Private_time | integer | 0% | 1 | 2008, 2008, 2008, 2008, 2008 |
Observation_value_E1301_Number_of_kindergarten_teachers |
Observation_value_E1301_Number_of_kindergarten_teachers | float | 0% | 45 | 4031.0, 652.0, 431.0, 2058.0, 326.0 |
Observation_value_E1301_Number_of_kindergarten_teachers_time |
Observation_value_E1301_Number_of_kindergarten_teachers_time | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
Observation_value_E130101_Number_of_kindergarten_teachers_Male |
Observation_value_E130101_Number_of_kindergarten_teachers_Male | float | 0% | 38 | 281.0, 31.0, 20.0, 165.0, 33.0 |
Observation_value_E130101_Number_of_kindergarten_teachers_Male_time |
Observation_value_E130101_Number_of_kindergarten_teachers_Male_time | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
Observation_value_E130102_Number_of_kindergarten_teachers_Female |
Observation_value_E130102_Number_of_kindergarten_teachers_Female | float | 0% | 46 | 3750.0, 621.0, 411.0, 1893.0, 293.0 |
Observation_value_E130102_Number_of_kindergarten_teachers_Female_time |
Observation_value_E130102_Number_of_kindergarten_teachers_Female_time | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
Observation_value_E1302_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_tea |
Observation_value_E1302_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_tea | float | 0% | 17 | 16.0, 1.0, 1.0, 4.0, 1.0 |
Observation_value_E1302_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_tea_time |
Observation_value_E1302_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_tea_time | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
Observation_value_E130201_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t |
Observation_value_E130201_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t | float | 0% | 2 | 0.0, 0.0, 0.0, 0.0, 0.0 |
Observation_value_E130201_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t_time |
Observation_value_E130201_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t_time | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
Observation_value_E130202_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t |
Observation_value_E130202_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t | float | 0% | 17 | 16.0, 1.0, 1.0, 4.0, 1.0 |
Observation_value_E130202_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t_time |
Observation_value_E130202_Number_of_kindergarten_teachers_Nursing_teachers_and_assistant_nursing_t_time | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
Observation_value_E1303_Number_of_kindergarten_teachers_Academic_assistant |
Observation_value_E1303_Number_of_kindergarten_teachers_Academic_assistant | float | 0% | 43 | 299.0, 40.0, 18.0, 145.0, 33.0 |
Observation_value_E1303_Number_of_kindergarten_teachers_Academic_assistant_time |
Observation_value_E1303_Number_of_kindergarten_teachers_Academic_assistant_time | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
| +962 more pending fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Ssds I Health (admin_1)
— 47 rows, 814 columns
Loading data…
Field details — 814 fields (type, nulls, unique, samples)
Pending (814) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | 0% | 47 | 01000, 02000, 03000, 04000, 05000 |
area_name |
Geographic-area English name as returned by e-Stat | string | 0% | 47 | Hokkaido, Aomori-ken, Iwate-ken, Miyagi-ken, Akita-ken |
admin_level |
Administrative level (admin_0..admin_4) | string | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
Observation_value_I1101_Life_expectancy_0_years_old_Male |
Observation_value_I1101_Life_expectancy_0_years_old_Male | float | 0% | 44 | 80.92, 79.27, 80.64, 81.7, 80.48 |
Observation_value_I1101_Life_expectancy_0_years_old_Male_time |
Observation_value_I1101_Life_expectancy_0_years_old_Male_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Observation_value_I1102_Life_expectancy_0_years_old_Female |
Observation_value_I1102_Life_expectancy_0_years_old_Female | float | 0% | 45 | 87.08, 86.33, 87.05, 87.51, 87.1 |
Observation_value_I1102_Life_expectancy_0_years_old_Female_time |
Observation_value_I1102_Life_expectancy_0_years_old_Female_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Observation_value_I1201_Life_expectancy_20_years_old_Male |
Observation_value_I1201_Life_expectancy_20_years_old_Male | float | 0% | 41 | 61.3, 59.66, 61.0, 62.02, 60.8 |
Observation_value_I1201_Life_expectancy_20_years_old_Male_time |
Observation_value_I1201_Life_expectancy_20_years_old_Male_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Observation_value_I1202_Life_expectancy_20_years_old_Female |
Observation_value_I1202_Life_expectancy_20_years_old_Female | float | 0% | 38 | 67.41, 66.69, 67.33, 67.82, 67.41 |
Observation_value_I1202_Life_expectancy_20_years_old_Female_time |
Observation_value_I1202_Life_expectancy_20_years_old_Female_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Observation_value_I1301_Life_expectancy_40_years_old_Male |
Observation_value_I1301_Life_expectancy_40_years_old_Male | float | 0% | 41 | 42.02, 40.46, 41.64, 42.7, 41.52 |
Observation_value_I1301_Life_expectancy_40_years_old_Male_time |
Observation_value_I1301_Life_expectancy_40_years_old_Male_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Observation_value_I1302_Life_expectancy_40_years_old_Female |
Observation_value_I1302_Life_expectancy_40_years_old_Female | float | 0% | 41 | 47.82, 47.1, 47.73, 48.23, 47.84 |
Observation_value_I1302_Life_expectancy_40_years_old_Female_time |
Observation_value_I1302_Life_expectancy_40_years_old_Female_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Observation_value_I1401_Life_expectancy_60_years_old_Male |
Observation_value_I1401_Life_expectancy_60_years_old_Male | float | 0% | 45 | 23.78, 22.45, 23.51, 24.31, 23.28 |
Observation_value_I1401_Life_expectancy_60_years_old_Male_time |
Observation_value_I1401_Life_expectancy_60_years_old_Male_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Observation_value_I1402_Life_expectancy_60_years_old_Female |
Observation_value_I1402_Life_expectancy_60_years_old_Female | float | 0% | 41 | 29.01, 28.38, 28.95, 29.26, 29.03 |
Observation_value_I1402_Life_expectancy_60_years_old_Female_time |
Observation_value_I1402_Life_expectancy_60_years_old_Female_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Observation_value_I1501_Life_expectancy_65_years_old_Male |
Observation_value_I1501_Life_expectancy_65_years_old_Male | float | 0% | 40 | 19.67, 18.51, 19.42, 20.12, 19.23 |
Observation_value_I1501_Life_expectancy_65_years_old_Male_time |
Observation_value_I1501_Life_expectancy_65_years_old_Male_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Observation_value_I1502_Life_expectancy_65_years_old_Female |
Observation_value_I1502_Life_expectancy_65_years_old_Female | float | 0% | 37 | 24.54, 23.92, 24.44, 24.71, 24.51 |
Observation_value_I1502_Life_expectancy_65_years_old_Female_time |
Observation_value_I1502_Life_expectancy_65_years_old_Female_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Observation_value_I1601_Healthy_life_expectancy_Male |
Observation_value_I1601_Healthy_life_expectancy_Male | float | 0% | 38 | 71.6, 71.73, 71.39, 72.9, 72.61 |
Observation_value_I1601_Healthy_life_expectancy_Male_time |
Observation_value_I1601_Healthy_life_expectancy_Male_time | integer | 0% | 1 | 2019, 2019, 2019, 2019, 2019 |
Observation_value_I1602_Healthy_life_expectancy_Female |
Observation_value_I1602_Healthy_life_expectancy_Female | float | 0% | 42 | 75.03, 76.05, 74.69, 75.1, 76.0 |
Observation_value_I1602_Healthy_life_expectancy_Female_time |
Observation_value_I1602_Healthy_life_expectancy_Female_time | integer | 0% | 1 | 2019, 2019, 2019, 2019, 2019 |
Observation_value_I210101_Number_of_persons_undergoing_medical_inspections_at_health_care_centers_ |
Observation_value_I210101_Number_of_persons_undergoing_medical_inspections_at_health_care_centers_ | float | 0% | 47 | 117384.0, 77086.0, 66332.0, 334144.0, 85684.0 |
Observation_value_I210101_Number_of_persons_undergoing_medical_inspections_at_health_care_centers__time |
Observation_value_I210101_Number_of_persons_undergoing_medical_inspections_at_health_care_centers__time | integer | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
| +784 more pending fields — download the CSV/Parquet to see them all. | |||||
2
Admin 2
— 3 table(s)
JPN e-Stat - Municipal Economic Census (admin_2)
— 1,742 rows, 24 columns
Loading data…
Field details — 24 fields (type, nulls, unique, samples)
Standards-Aligned Fields (6)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | SEL | 0% | 100 | 01100, 01101, 01102, 01103, 01104 |
area_name |
Geographic-area English name as returned by e-Stat | string | SEL | 0% | 100 | Sapporo-shi, Sapporo-shi Chuo-ku, Sapporo-shi Kita-ku,... |
admin_level |
Administrative level (admin_0..admin_4) | string | SEL | 0% | 1 | admin_2, admin_2, admin_2, admin_2, admin_2 |
Number_of_establishments_Total |
Number of establishments Total | float | SEL | 0% | 98 | 71870.0, 21576.0, 8746.0, 8511.0, 8139.0 |
Number_of_persons_engaged_Male_and_Female_Total |
Number of persons engaged Male and Female Total | float | SEL | 0% | 99 | 920986.0, 317349.0, 114199.0, 107135.0, 99187.0 |
Extension Fields (8)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total |
Number of establishments Including establishments not reported their industry et Total | float | 0% | 96 | 87752.0, 28222.0, 10638.0, 9888.0, 9619.0 |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned |
Number of establishments Including establishments not reported their industry et Privately owned | float | 0% | 95 | 86906.0, 28044.0, 10520.0, 9799.0, 9547.0 |
Number_of_establishments_Privately_owned |
Number of establishments Privately owned | float | 0% | 98 | 71024.0, 21398.0, 8628.0, 8422.0, 8067.0 |
Number_of_persons_engaged_Male_and_Female_Privately_owned |
Number of persons engaged Male and Female Privately owned | float | 0% | 99 | 863439.0, 294720.0, 106840.0, 102405.0, 96517.0 |
Number_of_persons_engaged_Male_Total |
Number of persons engaged Male Total | float | 0% | 97 | 489881.0, 169985.0, 59098.0, 60169.0, 57655.0 |
Number_of_persons_engaged_Male_Privately_owned |
Number of persons engaged Male Privately owned | float | 0% | 99 | 451719.0, 154375.0, 54423.0, 56985.0, 56027.0 |
Number_of_persons_engaged_Female_Total |
Number of persons engaged Female Total | float | 0% | 99 | 422574.0, 145031.0, 53951.0, 46561.0, 40970.0 |
Number_of_persons_engaged_Female_Privately_owned |
Number of persons engaged Female Privately owned | float | 0% | 100 | 403189.0, 138012.0, 51267.0, 45015.0, 39928.0 |
Pending (10) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total_time |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned_time |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_establishments_Total_time |
Number_of_establishments_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_establishments_Privately_owned_time |
Number_of_establishments_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_and_Female_Total_time |
Number_of_persons_engaged_Male_and_Female_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_and_Female_Privately_owned_time |
Number_of_persons_engaged_Male_and_Female_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_Total_time |
Number_of_persons_engaged_Male_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_Privately_owned_time |
Number_of_persons_engaged_Male_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Female_Total_time |
Number_of_persons_engaged_Female_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Female_Privately_owned_time |
Number_of_persons_engaged_Female_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
JPN e-Stat - Municipal Pop Age Marital (admin_2)
— 815 rows, 1,732 columns
Loading data…
Field details — 1732 fields (type, nulls, unique, samples)
Standards-Aligned Fields (4)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | SEL | 0% | 100 | 01100, 01101, 01102, 01103, 01104 |
area_name |
Geographic-area English name as returned by e-Stat | string | SEL | 0% | 100 | Sapporo-shi, Sapporo-shi Chuo-ku, Sapporo-shi Kita-ku,... |
admin_level |
Administrative level (admin_0..admin_4) | string | SEL | 0% | 1 | admin_2, admin_2, admin_2, admin_2, admin_2 |
Extension Fields (864)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Population_Total_Total_Total_Total |
Population Total Total Total Total | float | 0% | 100 | 1676267.0, 213342.0, 243312.0, 220026.0, 185399.0 |
Population_Total_Total_Total_15_19_years_old |
Population Total Total Total 15 19 years old | float | 0% | 100 | 82217.0, 9572.0, 13698.0, 10908.0, 8032.0 |
Population_Total_Total_Total_20_24_years_old |
Population Total Total Total 20 24 years old | float | 0% | 99 | 94945.0, 13006.0, 17675.0, 12718.0, 10492.0 |
Population_Total_Total_Total_25_29_years_old |
Population Total Total Total 25 29 years old | float | 0% | 99 | 97276.0, 15231.0, 13510.0, 13851.0, 13072.0 |
Population_Total_Total_Total_30_34_years_old |
Population Total Total Total 30 34 years old | float | 0% | 97 | 105388.0, 15344.0, 14655.0, 14844.0, 13417.0 |
Population_Total_Total_Total_35_39_years_old |
Population Total Total Total 35 39 years old | float | 0% | 99 | 117760.0, 16324.0, 16737.0, 16372.0, 14067.0 |
Population_Total_Total_Total_40_44_years_old |
Population Total Total Total 40 44 years old | float | 0% | 99 | 133516.0, 17730.0, 19226.0, 18424.0, 15562.0 |
Population_Total_Total_Total_45_49_years_old |
Population Total Total Total 45 49 years old | float | 0% | 99 | 151467.0, 20324.0, 21948.0, 20719.0, 17573.0 |
Population_Total_Total_Total_50_54_years_old |
Population Total Total Total 50 54 years old | float | 0% | 100 | 133072.0, 18439.0, 18713.0, 17629.0, 15433.0 |
Population_Total_Total_Total_55_59_years_old |
Population Total Total Total 55 59 years old | float | 0% | 97 | 124536.0, 16765.0, 17165.0, 15554.0, 13857.0 |
Population_Total_Total_Total_60_64_years_old |
Population Total Total Total 60 64 years old | float | 0% | 100 | 116800.0, 14210.0, 16113.0, 14411.0, 12176.0 |
Population_Total_Total_Total_65_69_years_old |
Population Total Total Total 65 69 years old | float | 0% | 100 | 130488.0, 14042.0, 19014.0, 16392.0, 12862.0 |
Population_Total_Total_Total_70_74_years_old |
Population Total Total Total 70 74 years old | float | 0% | 100 | 136731.0, 14479.0, 19666.0, 17275.0, 13265.0 |
Population_Total_Total_Total_75_79_years_old |
Population Total Total Total 75 79 years old | float | 0% | 99 | 95202.0, 9839.0, 13646.0, 11932.0, 9551.0 |
Population_Total_Total_Total_80_84_years_old |
Population Total Total Total 80 84 years old | float | 0% | 100 | 72006.0, 7728.0, 10233.0, 8855.0, 7398.0 |
Population_Total_Total_Total_85_89_years_old |
Population Total Total Total 85 89 years old | float | 0% | 97 | 51837.0, 6220.0, 6940.0, 6261.0, 5388.0 |
Population_Total_Total_Total_90_94_years_old |
Population Total Total Total 90 94 years old | float | 0% | 95 | 25388.0, 3176.0, 3394.0, 2977.0, 2504.0 |
Population_Total_Total_Total_95_99_years_old |
Population Total Total Total 95 99 years old | float | 0% | 86 | 6645.0, 800.0, 846.0, 779.0, 672.0 |
Population_Total_Total_Total_100_years_old_and_over |
Population Total Total Total 100 years old and over | float | 2% | 51 | 993.0, 113.0, 133.0, 125.0, 78.0 |
Population_Total_Total_Total_Recount_15_64_years_old |
Population Total Total Total Recount 15 64 years old | float | 0% | 100 | 1156977.0, 156945.0, 169440.0, 155430.0, 133681.0 |
Population_Total_Total_Total_Recount_65_years_old_and_over |
Population Total Total Total Recount 65 years old and over | float | 0% | 100 | 519290.0, 56397.0, 73872.0, 64596.0, 51718.0 |
Population_Total_Total_Total_Recount_75_years_old_and_over |
Population Total Total Total Recount 75 years old and over | float | 0% | 100 | 252071.0, 27876.0, 35192.0, 30929.0, 25591.0 |
Population_Total_Total_Total_Recount_85_years_old_and_over |
Population Total Total Total Recount 85 years old and over | float | 0% | 99 | 84863.0, 10309.0, 11313.0, 10142.0, 8642.0 |
Population_Total_Total_Total_Recount_20_69_years_old |
Population Total Total Total Recount 20 69 years old | float | 0% | 100 | 1205248.0, 161415.0, 174756.0, 160914.0, 138511.0 |
Population_Total_Total_Never_married_Total |
Population Total Total Never married Total | float | 0% | 100 | 450159.0, 62379.0, 68796.0, 60663.0, 52594.0 |
Population_Total_Total_Never_married_15_19_years_old |
Population Total Total Never married 15 19 years old | float | 0% | 97 | 81010.0, 9309.0, 13496.0, 10759.0, 7902.0 |
Population_Total_Total_Never_married_20_24_years_old |
Population Total Total Never married 20 24 years old | float | 0% | 96 | 79766.0, 10000.0, 15449.0, 10601.0, 8294.0 |
Population_Total_Total_Never_married_25_29_years_old |
Population Total Total Never married 25 29 years old | float | 0% | 99 | 57878.0, 8713.0, 8305.0, 8028.0, 7283.0 |
Population_Total_Total_Never_married_30_34_years_old |
Population Total Total Never married 30 34 years old | float | 0% | 98 | 41178.0, 6032.0, 5579.0, 5585.0, 5156.0 |
Population_Total_Total_Never_married_35_39_years_old |
Population Total Total Never married 35 39 years old | float | 0% | 94 | 33664.0, 4787.0, 4649.0, 4534.0, 4222.0 |
| +834 more extension fields — download the CSV/Parquet to see them all. | |||||
Pending (864) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Population_Total_Total_Total_Total_time |
Population_Total_Total_Total_Total_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_15_19_years_old_time |
Population_Total_Total_Total_15_19_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_20_24_years_old_time |
Population_Total_Total_Total_20_24_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_25_29_years_old_time |
Population_Total_Total_Total_25_29_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_30_34_years_old_time |
Population_Total_Total_Total_30_34_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_35_39_years_old_time |
Population_Total_Total_Total_35_39_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_40_44_years_old_time |
Population_Total_Total_Total_40_44_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_45_49_years_old_time |
Population_Total_Total_Total_45_49_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_50_54_years_old_time |
Population_Total_Total_Total_50_54_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_55_59_years_old_time |
Population_Total_Total_Total_55_59_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_60_64_years_old_time |
Population_Total_Total_Total_60_64_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_65_69_years_old_time |
Population_Total_Total_Total_65_69_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_70_74_years_old_time |
Population_Total_Total_Total_70_74_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_75_79_years_old_time |
Population_Total_Total_Total_75_79_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_80_84_years_old_time |
Population_Total_Total_Total_80_84_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_85_89_years_old_time |
Population_Total_Total_Total_85_89_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_90_94_years_old_time |
Population_Total_Total_Total_90_94_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_95_99_years_old_time |
Population_Total_Total_Total_95_99_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_100_years_old_and_over_time |
Population_Total_Total_Total_100_years_old_and_over_time | integer | 2% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_Recount_15_64_years_old_time |
Population_Total_Total_Total_Recount_15_64_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_Recount_65_years_old_and_over_time |
Population_Total_Total_Total_Recount_65_years_old_and_over_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_Recount_75_years_old_and_over_time |
Population_Total_Total_Total_Recount_75_years_old_and_over_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_Recount_85_years_old_and_over_time |
Population_Total_Total_Total_Recount_85_years_old_and_over_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_Recount_20_69_years_old_time |
Population_Total_Total_Total_Recount_20_69_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_Total_time |
Population_Total_Total_Never_married_Total_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_15_19_years_old_time |
Population_Total_Total_Never_married_15_19_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_20_24_years_old_time |
Population_Total_Total_Never_married_20_24_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_25_29_years_old_time |
Population_Total_Total_Never_married_25_29_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_30_34_years_old_time |
Population_Total_Total_Never_married_30_34_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Never_married_35_39_years_old_time |
Population_Total_Total_Never_married_35_39_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
| +834 more pending fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Municipal Population By Sex (admin_2)
— 1,740 rows, 10 columns
Loading data…
Field details — 10 fields (type, nulls, unique, samples)
Standards-Aligned Fields (7)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | string | SEL | 0% | 100 | 01100, 01101, 01102, 01103, 01104 |
area_name |
Geographic-area English name as returned by e-Stat | string | SEL | 0% | 100 | Sapporo-shi, Sapporo-shi Chuo-ku, Sapporo-shi Kita-ku,... |
admin_level |
Administrative level (admin_0..admin_4) | string | SEL | 0% | 1 | admin_2, admin_2, admin_2, admin_2, admin_2 |
Population_Total |
Population Total | float | SEL | 0% | 100 | 1973395.0, 248680.0, 289323.0, 265379.0, 211835.0 |
Population_Male |
Population Male | float | SEL | 0% | 100 | 918682.0, 112853.0, 136596.0, 126023.0, 100062.0 |
Population_Female |
Population Female | float | SEL | 0% | 100 | 1054713.0, 135827.0, 152727.0, 139356.0, 111773.0 |
Pending (3) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
Population_Total_time |
Population_Total_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Male_time |
Population_Male_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Female_time |
Population_Female_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
3
Admin 3
— 3 table(s)
JPN e-Stat - Municipal Economic Census (admin_3)
— 175 rows, 24 columns
Loading data…
Field details — 24 fields (type, nulls, unique, samples)
Pending (24) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | 0% | 100 | 01101, 01102, 01103, 01104, 01105 |
area_name |
Geographic-area English name as returned by e-Stat | string | 0% | 100 | Sapporo-shi Chuo-ku, Sapporo-shi Kita-ku, Sapporo-shi... |
admin_level |
Administrative level (admin_0..admin_4) | string | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total | float | 0% | 99 | 28222.0, 10638.0, 9888.0, 9619.0, 6989.0 |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total_time |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned | float | 0% | 100 | 28044.0, 10520.0, 9799.0, 9547.0, 6913.0 |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned_time |
Number_of_establishments_Including_establishments_not_reported_their_industry_et_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_establishments_Total |
Number_of_establishments_Total | float | 0% | 99 | 21576.0, 8746.0, 8511.0, 8139.0, 5853.0 |
Number_of_establishments_Total_time |
Number_of_establishments_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_establishments_Privately_owned |
Number_of_establishments_Privately_owned | float | 0% | 99 | 21398.0, 8628.0, 8422.0, 8067.0, 5777.0 |
Number_of_establishments_Privately_owned_time |
Number_of_establishments_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_and_Female_Total |
Number_of_persons_engaged_Male_and_Female_Total | float | 0% | 100 | 317349.0, 114199.0, 107135.0, 99187.0, 63552.0 |
Number_of_persons_engaged_Male_and_Female_Total_time |
Number_of_persons_engaged_Male_and_Female_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_and_Female_Privately_owned |
Number_of_persons_engaged_Male_and_Female_Privately_owned | float | 0% | 100 | 294720.0, 106840.0, 102405.0, 96517.0, 60114.0 |
Number_of_persons_engaged_Male_and_Female_Privately_owned_time |
Number_of_persons_engaged_Male_and_Female_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_Total |
Number_of_persons_engaged_Male_Total | float | 0% | 99 | 169985.0, 59098.0, 60169.0, 57655.0, 32358.0 |
Number_of_persons_engaged_Male_Total_time |
Number_of_persons_engaged_Male_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Male_Privately_owned |
Number_of_persons_engaged_Male_Privately_owned | float | 0% | 100 | 154375.0, 54423.0, 56985.0, 56027.0, 30304.0 |
Number_of_persons_engaged_Male_Privately_owned_time |
Number_of_persons_engaged_Male_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Female_Total |
Number_of_persons_engaged_Female_Total | float | 0% | 100 | 145031.0, 53951.0, 46561.0, 40970.0, 30185.0 |
Number_of_persons_engaged_Female_Total_time |
Number_of_persons_engaged_Female_Total_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
Number_of_persons_engaged_Female_Privately_owned |
Number_of_persons_engaged_Female_Privately_owned | float | 0% | 100 | 138012.0, 51267.0, 45015.0, 39928.0, 28801.0 |
Number_of_persons_engaged_Female_Privately_owned_time |
Number_of_persons_engaged_Female_Privately_owned_time | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
JPN e-Stat - Municipal Pop Age Marital (admin_3)
— 174 rows, 1,720 columns
Loading data…
Field details — 1720 fields (type, nulls, unique, samples)
Pending (1720) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | 0% | 100 | 01101, 01102, 01103, 01104, 01105 |
area_name |
Geographic-area English name as returned by e-Stat | string | 0% | 100 | Sapporo-shi Chuo-ku, Sapporo-shi Kita-ku, Sapporo-shi... |
admin_level |
Administrative level (admin_0..admin_4) | string | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
Population_Total_Total_Total_Total |
Population_Total_Total_Total_Total | float | 0% | 100 | 213342.0, 243312.0, 220026.0, 185399.0, 198468.0 |
Population_Total_Total_Total_Total_time |
Population_Total_Total_Total_Total_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_15_19_years_old |
Population_Total_Total_Total_15_19_years_old | float | 0% | 100 | 9572.0, 13698.0, 10908.0, 8032.0, 9138.0 |
Population_Total_Total_Total_15_19_years_old_time |
Population_Total_Total_Total_15_19_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_20_24_years_old |
Population_Total_Total_Total_20_24_years_old | float | 0% | 100 | 13006.0, 17675.0, 12718.0, 10492.0, 12340.0 |
Population_Total_Total_Total_20_24_years_old_time |
Population_Total_Total_Total_20_24_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_25_29_years_old |
Population_Total_Total_Total_25_29_years_old | float | 0% | 100 | 15231.0, 13510.0, 13851.0, 13072.0, 14148.0 |
Population_Total_Total_Total_25_29_years_old_time |
Population_Total_Total_Total_25_29_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_30_34_years_old |
Population_Total_Total_Total_30_34_years_old | float | 0% | 99 | 15344.0, 14655.0, 14844.0, 13417.0, 14626.0 |
Population_Total_Total_Total_30_34_years_old_time |
Population_Total_Total_Total_30_34_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_35_39_years_old |
Population_Total_Total_Total_35_39_years_old | float | 0% | 100 | 16324.0, 16737.0, 16372.0, 14067.0, 14876.0 |
Population_Total_Total_Total_35_39_years_old_time |
Population_Total_Total_Total_35_39_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_40_44_years_old |
Population_Total_Total_Total_40_44_years_old | float | 0% | 99 | 17730.0, 19226.0, 18424.0, 15562.0, 16085.0 |
Population_Total_Total_Total_40_44_years_old_time |
Population_Total_Total_Total_40_44_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_45_49_years_old |
Population_Total_Total_Total_45_49_years_old | float | 0% | 99 | 20324.0, 21948.0, 20719.0, 17573.0, 17915.0 |
Population_Total_Total_Total_45_49_years_old_time |
Population_Total_Total_Total_45_49_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_50_54_years_old |
Population_Total_Total_Total_50_54_years_old | float | 0% | 100 | 18439.0, 18713.0, 17629.0, 15433.0, 15730.0 |
Population_Total_Total_Total_50_54_years_old_time |
Population_Total_Total_Total_50_54_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_55_59_years_old |
Population_Total_Total_Total_55_59_years_old | float | 0% | 99 | 16765.0, 17165.0, 15554.0, 13857.0, 14348.0 |
Population_Total_Total_Total_55_59_years_old_time |
Population_Total_Total_Total_55_59_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_60_64_years_old |
Population_Total_Total_Total_60_64_years_old | float | 0% | 100 | 14210.0, 16113.0, 14411.0, 12176.0, 12618.0 |
Population_Total_Total_Total_60_64_years_old_time |
Population_Total_Total_Total_60_64_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_65_69_years_old |
Population_Total_Total_Total_65_69_years_old | float | 0% | 100 | 14042.0, 19014.0, 16392.0, 12862.0, 13529.0 |
Population_Total_Total_Total_65_69_years_old_time |
Population_Total_Total_Total_65_69_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Total_Total_Total_70_74_years_old |
Population_Total_Total_Total_70_74_years_old | float | 0% | 99 | 14479.0, 19666.0, 17275.0, 13265.0, 14312.0 |
Population_Total_Total_Total_70_74_years_old_time |
Population_Total_Total_Total_70_74_years_old_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
| +1690 more pending fields — download the CSV/Parquet to see them all. | |||||
JPN e-Stat - Municipal Population By Sex (admin_3)
— 175 rows, 10 columns
Loading data…
Field details — 10 fields (type, nulls, unique, samples)
Pending (10) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
area_code |
e-Stat area code (JIS X 0401 prefecture + JIS X 0402 municipality) | integer | 0% | 100 | 01101, 01102, 01103, 01104, 01105 |
area_name |
Geographic-area English name as returned by e-Stat | string | 0% | 100 | Sapporo-shi Chuo-ku, Sapporo-shi Kita-ku, Sapporo-shi... |
admin_level |
Administrative level (admin_0..admin_4) | string | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
Population_Total |
Population_Total | float | 0% | 100 | 248680.0, 289323.0, 265379.0, 211835.0, 225298.0 |
Population_Total_time |
Population_Total_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Male |
Population_Male | float | 0% | 100 | 112853.0, 136596.0, 126023.0, 100062.0, 104154.0 |
Population_Male_time |
Population_Male_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
Population_Female |
Population_Female | float | 0% | 100 | 135827.0, 152727.0, 139356.0, 111773.0, 121144.0 |
Population_Female_time |
Population_Female_time | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
JPN OCHA HDX (NDVI subnational)
JPN-HDX_NDVI
Environmental
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
1
Admin 1
— 1 table(s)
JPN Hdx Ndvi - Jpn Ndvi Subnational 5Ytd (admin_1)
— 7,614 rows, 10 columns
Loading data…
Field details — 10 fields (type, nulls, unique, samples)
Extension Fields (10)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
admin_level |
admin_level | string | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
date |
date | string | 0% | 100 | 2022-01-01, 2022-01-11, 2022-01-21, 2022-02-01, 2022-02-11 |
adm_level |
adm_level | integer | 0% | 1 | 1, 1, 1, 1, 1 |
adm_id |
adm_id | integer | 0% | 1 | 1651, 1651, 1651, 1651, 1651 |
PCODE |
PCODE | string | 0% | 1 | , , , , |
n_pixels |
n_pixels | float | 0% | 1 | 200.0, 200.0, 200.0, 200.0, 200.0 |
vim |
vim | float | 0% | 100 | 0.5371355, 0.529764, 0.525109, 0.52178997, 0.520157 |
vim_avg |
vim_avg | float | 0% | 36 | 0.5185484, 0.51041394, 0.50447243, 0.49977553, 0.49700418 |
viq |
viq | float | 0% | 100 | 103.26921, 103.45281, 103.72183, 104.004265, 104.23266 |
2
Admin 2
— 1 table(s)
JPN Hdx Ndvi - Jpn Ndvi Subnational 5Ytd (admin_2)
— 488,268 rows, 10 columns
Loading data…
Field details — 10 fields (type, nulls, unique, samples)
Extension Fields (10)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
admin_level |
admin_level | string | 0% | 1 | admin_2, admin_2, admin_2, admin_2, admin_2 |
date |
date | string | 0% | 100 | 2022-01-01, 2022-01-11, 2022-01-21, 2022-02-01, 2022-02-11 |
adm_level |
adm_level | integer | 0% | 1 | 2, 2, 2, 2, 2 |
adm_id |
adm_id | integer | 0% | 1 | 34457, 34457, 34457, 34457, 34457 |
PCODE |
PCODE | string | 0% | 1 | , , , , |
n_pixels |
n_pixels | float | 0% | 1 | 1.0, 1.0, 1.0, 1.0, 1.0 |
vim |
vim | float | 0% | 97 | 0.7187, 0.7161, 0.71419996, 0.71239996, 0.7122 |
vim_avg |
vim_avg | float | 0% | 36 | 0.7009125, 0.6940187, 0.6901625, 0.68803126, 0.68768126 |
viq |
viq | float | 0% | 100 | 102.36878, 102.967834, 103.2476, 103.30186, 103.32376 |
JPN Japan - Economic, Social, Environmental, Health, E
JPN-HDX-Japan_-_Economic,_Social,_Environme
Indicators
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN Japan - Economic, Social, Environmental, Health, E
— 67,790 rows, 1,810 columns
Loading data…
Field details — 1810 fields (type, nulls, unique, samples)
Extension Fields (1810)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | JPN |
Fertilizer_consumption_pct_of_fertilizer_production |
Fertilizer_consumption_pct_of_fertilizer_production | float | 0% | 1 | 143.793572800672 |
Fertilizer_consumption_kilograms_per_hectare_of_arable_land |
Fertilizer_consumption_kilograms_per_hectare_of_arable_land | float | 0% | 1 | 202.84371909001 |
Agricultural_land_sq._km |
Agricultural_land_sq._km | float | 0% | 1 | 46070.0 |
Agricultural_land_pct_of_land_area |
Agricultural_land_pct_of_land_area | float | 0% | 1 | 12.6368303066246 |
Arable_land_hectares |
Arable_land_hectares | float | 0% | 1 | 4044000.0 |
Arable_land_hectares_per_person |
Arable_land_hectares_per_person | float | 0% | 1 | 0.0324775843230604 |
Arable_land_pct_of_land_area |
Arable_land_pct_of_land_area | float | 0% | 1 | 11.0925421662665 |
Land_under_cereal_production_hectares |
Land_under_cereal_production_hectares | float | 0% | 1 | 1841210.0 |
Permanent_cropland_pct_of_land_area |
Permanent_cropland_pct_of_land_area | float | 0% | 1 | 0.696712589078065 |
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 | 5490.8246975 |
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 | 1.48325195697308 |
Forest_area_sq._km |
Forest_area_sq._km | float | 0% | 1 | 249350.0 |
Forest_area_pct_of_land_area |
Forest_area_pct_of_land_area | float | 0% | 1 | 68.3957811364628 |
Agricultural_irrigated_land_pct_of_total_agricultural_land |
Agricultural_irrigated_land_pct_of_total_agricultural_land | float | 0% | 1 | 32.299794661191 |
Average_precipitation_in_depth_mm_per_year |
Average_precipitation_in_depth_mm_per_year | float | 0% | 1 | 1668.0 |
Land_area_sq._km |
Land_area_sq._km | float | 0% | 1 | 364569.27 |
Rural_land_area_sq._km |
Rural_land_area_sq._km | float | 0% | 1 | 316736.20486046 |
Cereal_production_metric_tons |
Cereal_production_metric_tons | float | 0% | 1 | 11498533.52 |
Crop_production_index_2014-2016_=_100 |
Crop_production_index_2014-2016_=_100 | float | 0% | 1 | 94.6 |
Food_production_index_2014-2016_=_100 |
Food_production_index_2014-2016_=_100 | float | 0% | 1 | 100.27 |
Livestock_production_index_2014-2016_=_100 |
Livestock_production_index_2014-2016_=_100 | float | 0% | 1 | 104.84 |
Surface_area_sq._km |
Surface_area_sq._km | float | 0% | 1 | 377969.27 |
Cereal_yield_kg_per_hectare |
Cereal_yield_kg_per_hectare | float | 0% | 1 | 6245.1 |
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 | 0.867822136159523 |
Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal |
Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal | float | 0% | 1 | 66.66666667 |
Agriculture_forestry_and_fishing_value_added_current_USusd |
Agriculture_forestry_and_fishing_value_added_current_USusd | float | 0% | 1 | 39496452070.8984 |
Agriculture_forestry_and_fishing_value_added_pct_of_GDP |
Agriculture_forestry_and_fishing_value_added_pct_of_GDP | float | 0% | 1 | 0.937452748505902 |
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 | 2.29336010524804 |
| +1780 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN Japan - Health Indicators
JPN-HDX-Japan_-_Health_Indicators
Indicators
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN Japan - Health Indicators
— 18,175 rows, 17 columns
Loading data…
Field details — 17 fields (type, nulls, unique, samples)
Extension Fields (17)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
GHO (CODE) |
GHO (CODE) | string | 0% | 69 | MORT_100, MORT_100, MORT_200, GHED_CHE_pc_US_SHA2011, NCD_PAA |
GHO (DISPLAY) |
GHO (DISPLAY) | string | 0% | 69 | Number of deaths in children aged <5 years, by cause,... |
GHO (URL) |
GHO (URL) | string | 0% | 67 | https://www.who.int/data/gho/data/indicators/indicator-de... |
YEAR (DISPLAY) |
YEAR (DISPLAY) | string | 0% | 32 | 2019, 2001, 2017, 2014, 2006 |
STARTYEAR |
STARTYEAR | string | 0% | 32 | 2019, 2001, 2017, 2014, 2006 |
ENDYEAR |
ENDYEAR | string | 0% | 32 | 2019, 2001, 2017, 2014, 2006 |
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 | JPN, JPN, JPN, JPN, JPN |
COUNTRY (DISPLAY) |
COUNTRY (DISPLAY) | string | 0% | 1 | Japan, Japan, Japan, Japan, Japan |
DIMENSION (TYPE) |
DIMENSION (TYPE) | string | 14% | 12 | SEX, SEX, AGEGROUP, SEX, TOBACCO_INDICATOR |
DIMENSION (CODE) |
DIMENSION (CODE) | string | 14% | 25 | SEX_BTSX, SEX_BTSX, AGEGROUP_DAYS0-27, SEX_MLE,... |
DIMENSION (NAME) |
DIMENSION (NAME) | string | 14% | 22 | Both sexes, Both sexes, 0-27 days, Male, Other smoked... |
Numeric |
Numeric | float | 20% | 67 | 0.0, 1142.07217, 0.0, 4121.21142578, 29.484329 |
Value |
Value | string | 0% | 73 | 0.0, 1142.1, 0, 4121.21, 29.5 [13.7-50.6] |
Low |
Low | float | 47% | 50 | 13.722679, 0.0, -0.051302813, 4.9, 14.01898 |
High |
High | float | 47% | 51 | 50.564968, 0.0, 0.058384208, 5.1, 15.135565 |
JPN Japan - Education
JPN-HDX-Japan_-_Education
Indicators
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN Japan - Education
— 13,311 rows, 761 columns
Loading data…
Field details — 761 fields (type, nulls, unique, samples)
Extension Fields (761)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | JPN |
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 | 0.93 |
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 | 0.87 |
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 | 0.15 |
Barro-Lee:_Percentage_of_population_age_15+_with_no_education |
Barro-Lee:_Percentage_of_population_age_15+_with_no_education | float | 0% | 1 | 0.13 |
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 | 0.09 |
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 | 0.1 |
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 | 0.06 |
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 | 0.06 |
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 | 0.15 |
Barro-Lee:_Percentage_of_population_age_25+_with_no_education |
Barro-Lee:_Percentage_of_population_age_25+_with_no_education | float | 0% | 1 | 0.12 |
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 | 0.06 |
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 | 0.06 |
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 | 0.06 |
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 | 0.06 |
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 | 0.06 |
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 | 0.06 |
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 | 0.09 |
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 | 0.09 |
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 | 0.09 |
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 | 0.09 |
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 | 0.1 |
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 | 0.09 |
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 | 0.1 |
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 | 0.09 |
Barro-Lee:_Population_in_thousands_age_15-19_total |
Barro-Lee:_Population_in_thousands_age_15-19_total | float | 0% | 1 | 6026.0 |
Barro-Lee:_Population_in_thousands_age_15-19_female |
Barro-Lee:_Population_in_thousands_age_15-19_female | float | 0% | 1 | 2942.0 |
Barro-Lee:_Population_in_thousands_age_15+_total |
Barro-Lee:_Population_in_thousands_age_15+_total | float | 0% | 1 | 110797.0 |
Barro-Lee:_Population_in_thousands_age_15+_female |
Barro-Lee:_Population_in_thousands_age_15+_female | float | 0% | 1 | 57243.0 |
Barro-Lee:_Population_in_thousands_age_20-24_total |
Barro-Lee:_Population_in_thousands_age_20-24_total | float | 0% | 1 | 6611.0 |
| +731 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN Japan - Gender
JPN-HDX-Japan_-_Gender
Indicators
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN Japan - Gender
— 3,514 rows, 132 columns
Loading data…
Field details — 132 fields (type, nulls, unique, samples)
Extension Fields (132)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | JPN |
School_enrollment_primary_gross_gender_parity_index_GPI |
School_enrollment_primary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.00253999233246 |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI |
School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.0034099817276 |
School_enrollment_secondary_gross_gender_parity_index_GPI |
School_enrollment_secondary_gross_gender_parity_index_GPI | float | 0% | 1 | 1.00423002243042 |
School_enrollment_tertiary_gross_gender_parity_index_GPI |
School_enrollment_tertiary_gross_gender_parity_index_GPI | float | 0% | 1 | 0.980690002441406 |
School_enrollment_preprimary_female_pct_gross |
School_enrollment_preprimary_female_pct_gross | float | 0% | 1 | 82.7969207763672 |
School_enrollment_preprimary_male_pct_gross |
School_enrollment_preprimary_male_pct_gross | float | 0% | 1 | 80.7868194580078 |
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 | 99.6100006103516 |
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 | 99.5699996948242 |
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 | 99.5899963378906 |
Primary_education_pupils_pct_female |
Primary_education_pupils_pct_female | float | 0% | 1 | 48.75264 |
School_enrollment_primary_female_pct_gross |
School_enrollment_primary_female_pct_gross | float | 0% | 1 | 102.426200866699 |
School_enrollment_primary_male_pct_gross |
School_enrollment_primary_male_pct_gross | float | 0% | 1 | 102.563247680664 |
Persistence_to_grade_5_female_pct_of_cohort |
Persistence_to_grade_5_female_pct_of_cohort | float | 0% | 1 | 99.9914398193359 |
Persistence_to_grade_5_male_pct_of_cohort |
Persistence_to_grade_5_male_pct_of_cohort | float | 0% | 1 | 99.9708099365234 |
Persistence_to_last_grade_of_primary_female_pct_of_cohort |
Persistence_to_last_grade_of_primary_female_pct_of_cohort | float | 0% | 1 | 99.9914398193359 |
Persistence_to_last_grade_of_primary_male_pct_of_cohort |
Persistence_to_last_grade_of_primary_male_pct_of_cohort | float | 0% | 1 | 99.9592590332031 |
Repeaters_primary_female_pct_of_female_enrollment |
Repeaters_primary_female_pct_of_female_enrollment | float | 0% | 1 | 0.0 |
Repeaters_primary_male_pct_of_male_enrollment |
Repeaters_primary_male_pct_of_male_enrollment | float | 0% | 1 | 0.0 |
Primary_education_teachers_pct_female |
Primary_education_teachers_pct_female | float | 0% | 1 | 70.3694229125977 |
Educational_attainment_at_least_completed_lower_secondary_population_25+_female_ |
Educational_attainment_at_least_completed_lower_secondary_population_25+_female_ | float | 0% | 1 | 98.2099990844727 |
Educational_attainment_at_least_completed_lower_secondary_population_25+_male_pc |
Educational_attainment_at_least_completed_lower_secondary_population_25+_male_pc | float | 0% | 1 | 99.0599975585938 |
Educational_attainment_at_least_completed_lower_secondary_population_25+_total_p |
Educational_attainment_at_least_completed_lower_secondary_population_25+_total_p | float | 0% | 1 | 98.620002746582 |
Educational_attainment_at_least_completed_post-secondary_population_25+_female_p |
Educational_attainment_at_least_completed_post-secondary_population_25+_female_p | float | 0% | 1 | 39.4500007629395 |
Educational_attainment_at_least_completed_post-secondary_population_25+_male_pct |
Educational_attainment_at_least_completed_post-secondary_population_25+_male_pct | float | 0% | 1 | 44.0400009155273 |
Educational_attainment_at_least_completed_post-secondary_population_25+_total_pc |
Educational_attainment_at_least_completed_post-secondary_population_25+_total_pc | float | 0% | 1 | 41.6300010681152 |
Educational_attainment_at_least_completed_upper_secondary_population_25+_female_ |
Educational_attainment_at_least_completed_upper_secondary_population_25+_female_ | float | 0% | 1 | 84.3499984741211 |
Educational_attainment_at_least_completed_upper_secondary_population_25+_male_pc |
Educational_attainment_at_least_completed_upper_secondary_population_25+_male_pc | float | 0% | 1 | 86.0899963378906 |
Educational_attainment_at_least_completed_upper_secondary_population_25+_total_p |
Educational_attainment_at_least_completed_upper_secondary_population_25+_total_p | float | 0% | 1 | 85.1800003051758 |
Secondary_education_pupils_pct_female |
Secondary_education_pupils_pct_female | float | 0% | 1 | 48.80558 |
| +102 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN Japan - Social Protection and Labor
JPN-HDX-Japan_-_Social_Protection_and_Labor
Indicators
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN Japan - Social Protection And Labor
— 3,131 rows, 85 columns
Loading data…
Field details — 85 fields (type, nulls, unique, samples)
Extension Fields (85)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | JPN |
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 | 2.29336010524804 |
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 | 3.24821287797992 |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate |
Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate | float | 0% | 1 | 2.81371149789044 |
Employment_to_population_ratio_ages_15-24_female_pct_national_estimate |
Employment_to_population_ratio_ages_15-24_female_pct_national_estimate | float | 0% | 1 | 50.191 |
Employment_to_population_ratio_ages_15-24_female_pct_modeled_ILO_estimate |
Employment_to_population_ratio_ages_15-24_female_pct_modeled_ILO_estimate | float | 0% | 1 | 50.517 |
Employment_to_population_ratio_ages_15-24_male_pct_national_estimate |
Employment_to_population_ratio_ages_15-24_male_pct_national_estimate | float | 0% | 1 | 47.593 |
Employment_to_population_ratio_ages_15-24_male_pct_modeled_ILO_estimate |
Employment_to_population_ratio_ages_15-24_male_pct_modeled_ILO_estimate | float | 0% | 1 | 47.876 |
Employment_to_population_ratio_ages_15-24_total_pct_national_estimate |
Employment_to_population_ratio_ages_15-24_total_pct_national_estimate | float | 0% | 1 | 48.818 |
Employment_to_population_ratio_ages_15-24_total_pct_modeled_ILO_estimate |
Employment_to_population_ratio_ages_15-24_total_pct_modeled_ILO_estimate | float | 0% | 1 | 49.163 |
Employers_female_pct_of_female_employment_modeled_ILO_estimate |
Employers_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 0.640938926818693 |
Employers_male_pct_of_male_employment_modeled_ILO_estimate |
Employers_male_pct_of_male_employment_modeled_ILO_estimate | float | 0% | 1 | 2.33380682774014 |
Employers_total_pct_of_total_employment_modeled_ILO_estimate |
Employers_total_pct_of_total_employment_modeled_ILO_estimate | float | 0% | 1 | 1.56347509536615 |
Self-employed_female_pct_of_female_employment_modeled_ILO_estimate |
Self-employed_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 7.51877387992717 |
Self-employed_male_pct_of_male_employment_modeled_ILO_estimate |
Self-employed_male_pct_of_male_employment_modeled_ILO_estimate | float | 0% | 1 | 10.3301000915369 |
Self-employed_total_pct_of_total_employment_modeled_ILO_estimate |
Self-employed_total_pct_of_total_employment_modeled_ILO_estimate | float | 0% | 1 | 9.05081758353661 |
Female_share_of_employment_in_senior_and_middle_management_pct |
Female_share_of_employment_in_senior_and_middle_management_pct | float | 0% | 1 | 13.269 |
Employment_to_population_ratio_15+_female_pct_national_estimate |
Employment_to_population_ratio_15+_female_pct_national_estimate | float | 0% | 1 | 54.271 |
Employment_to_population_ratio_15+_female_pct_modeled_ILO_estimate |
Employment_to_population_ratio_15+_female_pct_modeled_ILO_estimate | float | 0% | 1 | 54.621 |
Employment_to_population_ratio_15+_male_pct_national_estimate |
Employment_to_population_ratio_15+_male_pct_national_estimate | float | 0% | 1 | 69.662 |
Employment_to_population_ratio_15+_male_pct_modeled_ILO_estimate |
Employment_to_population_ratio_15+_male_pct_modeled_ILO_estimate | float | 0% | 1 | 69.634 |
Employment_to_population_ratio_15+_total_pct_national_estimate |
Employment_to_population_ratio_15+_total_pct_national_estimate | float | 0% | 1 | 61.709 |
Employment_to_population_ratio_15+_total_pct_modeled_ILO_estimate |
Employment_to_population_ratio_15+_total_pct_modeled_ILO_estimate | float | 0% | 1 | 61.893 |
Vulnerable_employment_female_pct_of_female_employment_modeled_ILO_estimate |
Vulnerable_employment_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 6.87783495310848 |
Vulnerable_employment_male_pct_of_male_employment_modeled_ILO_estimate |
Vulnerable_employment_male_pct_of_male_employment_modeled_ILO_estimate | float | 0% | 1 | 7.9962932637968 |
Vulnerable_employment_total_pct_of_total_employment_modeled_ILO_estimate |
Vulnerable_employment_total_pct_of_total_employment_modeled_ILO_estimate | float | 0% | 1 | 7.48734248817046 |
Wage_and_salaried_workers_female_pct_of_female_employment_modeled_ILO_estimate |
Wage_and_salaried_workers_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 92.4812228706334 |
Wage_and_salaried_workers_male_pct_of_male_employment_modeled_ILO_estimate |
Wage_and_salaried_workers_male_pct_of_male_employment_modeled_ILO_estimate | float | 0% | 1 | 89.6698999084631 |
Wage_and_salaried_workers_total_pct_of_total_employment_modeled_ILO_estimate |
Wage_and_salaried_workers_total_pct_of_total_employment_modeled_ILO_estimate | float | 0% | 1 | 90.949180937821 |
Contributing_family_workers_female_pct_of_female_employment_modeled_ILO_estimate |
Contributing_family_workers_female_pct_of_female_employment_modeled_ILO_estimate | float | 0% | 1 | 2.97839067548664 |
| +55 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN Japan - Human Development Indicators
JPN-HDX-Japan_-_Human_Development_Indicator
Indicators
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN Japan - Human Development Indicators
— 958 rows, 36 columns
Loading data…
Field details — 36 fields (type, nulls, unique, samples)
Extension Fields (36)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | JPN |
abr |
abr | float | 0% | 1 | 1.737 |
co2_prod |
co2_prod | float | 0% | 1 | 8.02 |
coef_ineq |
coef_ineq | float | 0% | 1 | 8.474 |
diff_hdi_phdi |
diff_hdi_phdi | float | 0% | 1 | 15.135 |
eys |
eys | float | 0% | 1 | 15.512 |
eys_f |
eys_f | float | 0% | 1 | 15.476 |
eys_m |
eys_m | float | 0% | 1 | 15.546 |
gdi_group |
gdi_group | float | 0% | 1 | 2.0 |
gii_rank |
gii_rank | float | 0% | 1 | 22.0 |
gni_pc_f |
gni_pc_f | float | 0% | 1 | 37016.985 |
gni_pc_m |
gni_pc_m | float | 0% | 1 | 59058.772 |
gnipc |
gnipc | float | 0% | 1 | 47774.61 |
hdi_f |
hdi_f | float | 0% | 1 | 0.909 |
hdi_m |
hdi_m | float | 0% | 1 | 0.938 |
hdi_rank |
hdi_rank | float | 0% | 1 | 23.0 |
ineq_edu |
ineq_edu | float | 0% | 1 | 5.752 |
ineq_inc |
ineq_inc | float | 0% | 1 | 17.123 |
ineq_le |
ineq_le | float | 0% | 1 | 2.546 |
le |
le | float | 0% | 1 | 84.712 |
le_f |
le_f | float | 0% | 1 | 87.741 |
le_m |
le_m | float | 0% | 1 | 81.688 |
lfpr_f |
lfpr_f | float | 0% | 1 | 54.8 |
lfpr_m |
lfpr_m | float | 0% | 1 | 71.4 |
loss |
loss | float | 0% | 1 | 8.649 |
mf |
mf | float | 0% | 1 | 17.895 |
mmr |
mmr | float | 0% | 1 | 4.315 |
mys |
mys | float | 0% | 1 | 12.684 |
mys_f |
mys_f | float | 0% | 1 | 12.364 |
mys_m |
mys_m | float | 0% | 1 | 13.033 |
| +6 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN Japan - Urban Development
JPN-HDX-Japan_-_Urban_Development
Indicators
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN Japan - Urban Development
— 631 rows, 18 columns
Loading data…
Field details — 18 fields (type, nulls, unique, samples)
Extension Fields (18)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_code |
country_code | string | 0% | 1 | JPN |
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 | 6558.79841573 |
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 | 1.77174670864157 |
Urban_land_area_sq._km |
Urban_land_area_sq._km | float | 0% | 1 | 53452.06097573 |
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 | 12.835201662985 |
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 | 76.7615082281987 |
Population_density_people_per_sq._km_of_land_area |
Population_density_people_per_sq._km_of_land_area | float | 0% | 1 | 341.54455749932 |
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 | 11.5747621193697 |
Population_living_in_slums_pct_of_urban_population |
Population_living_in_slums_pct_of_urban_population | float | 0% | 1 | 2.0 |
Population_in_largest_city |
Population_in_largest_city | float | 0% | 1 | 37036204.0 |
Population_in_the_largest_city_pct_of_urban_population |
Population_in_the_largest_city_pct_of_urban_population | float | 0% | 1 | 32.5680112680688 |
Population_in_urban_agglomerations_of_more_than_1_million |
Population_in_urban_agglomerations_of_more_than_1_million | float | 0% | 1 | 80938069.0 |
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 | 65.6931359343046 |
Mortality_caused_by_road_traffic_injury_per_100000_population |
Mortality_caused_by_road_traffic_injury_per_100000_population | float | 0% | 1 | 3.6 |
Urban_population_growth_annual_pct |
Urban_population_growth_annual_pct | float | 0% | 1 | -0.318996369716406 |
Urban_population |
Urban_population | float | 0% | 1 | 114293108.0 |
Urban_population_pct_of_total_population |
Urban_population_pct_of_total_population | float | 0% | 1 | 92.1901718034531 |
JPN Japan - Demographic, Health, Education and Transpo
JPN-HDX-Japan_-_Demographic,_Health,_Educat
Indicators
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN Japan - Demographic, Health, Education And Transpo
— 471 rows, 11 columns
Loading data…
Field details — 11 fields (type, nulls, unique, samples)
Extension Fields (11)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
category |
category | string | 0% | 6 | City prosperity, Streets, Crime, Crime, Transport |
indicator |
indicator | string | 0% | 22 | cpi_4_dimensions, road_density_national_roads,... |
indicator_friendly |
indicator_friendly | string | 0% | 22 | City Prosperity Index with 4 dimensions, Road density... |
type_data |
type_data | string | 0% | 5 | p, n, 000 population, 000 population, n |
latitude |
latitude | string | 0% | 9 | 35.685017, 36, n, n, 36 |
longitude |
longitude | string | 0% | 9 | 139.751407, 138, 36, 36, 138 |
region_id |
region_id | string | 0% | 2 | 789, 789, 138, 138, 789 |
country_id |
country_id | string | 0% | 2 | JP, JP, 789, 789, JP |
name |
name | string | 0% | 9 | Tokyo, Japan, JP, JP, Japan |
year |
year | string | 0% | 23 | 2012, 2009, Japan, Japan, 2000 |
value |
value | string | 0% | 69 | 0.925, 320, 2001, 2002, 327632 |
JPN Global Data Lab
JPN-GDL
Development Indices
ⓘ Global Data Lab publishes its own subnational regions, which match national admin units in some countries and group several together in others. The level shown is the nearest administrative tier, not a claim that these are that tier.
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
1
Admin 1
— 1 table(s)
JPN GDL - Subnational Indices
— 374 rows, 11 columns
Loading data…
Field details — 11 fields (type, nulls, unique, samples)
Standards-Aligned Fields (9)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 11 | Japan, Chugoku (Tottori, Shimane, Okayama, Hiroshima,... |
human_development_index |
Human development index | float | SEL | 0% | 65 | 0.847, 0.841, 0.826, 0.829, 0.85 |
health_index |
Health index | float | SEL | 0% | 31 | 0.908, 0.909, 0.908, 0.914, 0.903 |
education_index |
Education index | float | SEL | 0% | 80 | 0.744, 0.739, 0.708, 0.696, 0.76 |
income_index |
Income index | float | SEL | 0% | 48 | 0.898, 0.885, 0.879, 0.896, 0.895 |
life_expectancy |
Life expectancy | float | SEL | 0% | 53 | 78.99, 79.09, 78.99, 79.38, 78.7 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 81 | 11.17, 11.08, 10.62, 10.44, 11.4 |
Extension Fields (2)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 10 | 1990, 1990, 1990, 1990, 1990 |
level |
level | string | 0% | 1 | subnational, subnational, subnational, subnational, subnational |
JPN LandScan Global (ORNL)
JPN-LANDSCAN
Modeled Population
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN LandScan - Population Admin0 (admin_0)
— 1 rows, 7 columns
Loading data…
Field details — 7 fields (type, nulls, unique, samples)
Standards-Aligned Fields (7)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | Japan |
admin_code |
Admin code | string | SEL | 0% | 1 | 22093344B50624940221487 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 378051.8643 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 122334443 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 323.59 |
1
Admin 1
— 1 table(s)
JPN LandScan - Population Admin1 (admin_1)
— 47 rows, 7 columns
Loading data…
Field details — 7 fields (type, nulls, unique, samples)
Standards-Aligned Fields (7)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
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% | 47 | Tokyo, Kanagawa, Osaka Prefecture, Aichi Prefecture, Saitama |
admin_code |
Admin code | string | SEL | 0% | 47 | 47310658B199342310790, 47310658B16920518838967,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 47 | 2189.319, 2419.9969, 1911.9163, 5171.0362, 3797.7298 |
pop_2024 |
Population count | integer | SEL | 0% | 47 | 13698993, 8950051, 8619124, 7341273, 7182858 |
pop_density_2024 |
Population density | float | SEL | 0% | 47 | 6257.19, 3698.37, 4508.11, 1419.69, 1891.36 |
Locality
Locality
— 1 table(s)
JPN LandScan - Cities (locality)
— 135 rows, 9 columns
Loading data…
Field details — 9 fields (type, nulls, unique, samples)
Standards-Aligned Fields (7)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality, locality, locality, locality |
admin_name |
Admin name | string | SEL | 0% | 100 | Tokyo, Osaka, Nagoya, Fukuoka, Sapporo |
admin_code |
Admin code | integer | SEL | 0% | 100 | 5929, 4399, 5213, 907, 351 |
area_sqkm |
Area sqkm | float | SEL | 0% | 100 | 5153.8738, 2206.7643, 2386.561, 448.8311, 352.8406 |
pop_2024 |
Population count | integer | SEL | 0% | 100 | 33244670, 13767320, 7482025, 2340208, 1980880 |
pop_density_2024 |
Population density | float | SEL | 0% | 100 | 6450.42, 6238.69, 3135.07, 5214.01, 5614.09 |
Extension Fields (2)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 100 | 33155907, 12653994, 7721742, 2213305, 1931424 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 90 | 1.003, 1.088, 0.969, 1.057, 1.026 |
JPN GHS Urban Centre Database (EU JRC)
JPN-GHSL_UCDB
Modeled Population
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
Locality
Locality
— 1 table(s)
JPN GHS-UCDB - Cities (locality)
— 135 rows, 10 columns
Loading data…
Field details — 10 fields (type, nulls, unique, samples)
Standards-Aligned Fields (3)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 100 | Tokyo, Osaka, Nagoya, Fukuoka, Sapporo |
country_code |
Country code | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
population |
Population count | integer | SEL | 0% | 100 | 33155907, 12653994, 7721742, 2213305, 1931424 |
Extension Fields (7)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 100 | 5929, 4399, 5213, 907, 351 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Japan, Japan, Japan, Japan, Japan |
population_year |
population_year | integer | 0% | 1 | 2025, 2025, 2025, 2025, 2025 |
latitude |
latitude | string | 100% | - | - |
longitude |
longitude | string | 100% | - | - |
region |
region | string | 100% | - | - |
JPN World Bank Open Data
JPN-WORLD_BANK
Development Indicators
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 2 table(s)
JPN World Bank - Development Indicators
— 66 rows, 9 columns
Loading data…
Field details — 9 fields (type, nulls, unique, samples)
Standards-Aligned Fields (7)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JP, JP, JP, JP, JP |
population_count |
Population count | float | SEL | 2% | 64 | 93216000.0, 94055000.0, 94933000.0, 95900000.0, 96903000.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 67.6956097560976, 68.3519512195122, 68.6348780487805,... |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 2% | 65 | 508.702779291773, 608.864581144951, 684.565509797705,... |
literacy_rate_pct |
Literacy rate percent | string | SEL | 100% | - | - |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 58 | 39.7, 36.2, 32.9, 29.8, 27.0 |
poverty_headcount_pct |
Poverty headcount percent | string | SEL | 100% | - | - |
Extension Fields (2)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Japan, Japan, Japan, Japan, Japan |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
JPN World Bank - Health Indicators
— 66 rows, 14 columns
Loading data…
Field details — 14 fields (type, nulls, unique, samples)
Standards-Aligned Fields (12)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JP, JP, JP, JP, JP |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 67.6956097560976, 68.3519512195122, 68.6348780487805,... |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 15% | 40 | 9.7, 9.1, 8.7, 8.2, 7.8 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 58 | 39.7, 36.2, 32.9, 29.8, 27.0 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 17 | 19.0, 18.0, 17.0, 16.0, 15.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 42 | 2.0, 1.96, 1.98, 2.0, 2.05 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 53 | 17.2, 16.9, 17.0, 17.3, 17.7 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 37 | 7.6, 7.4, 7.5, 7.0, 6.9 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 41% | 22 | 1.0, 1.0, 1.0, 1.0, 1.0 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 49% | 34 | 9.0, 12.5, 13.6999998092651, 14.6999998092651, 15.6000003815 |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 32% | 19 | 60.0, 75.0, 81.0, 80.0, 82.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 7.03456163, 7.23947906, 7.35235405, 7.48654842, 7.53518438 |
Extension Fields (2)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Japan, Japan, Japan, Japan, Japan |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
JPN UNHCR Refugee Data Finder
JPN-UNHCR
Migration
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 2 table(s)
JPN UNHCR - Hosted Populations
— 49 rows, 24 columns
Loading data…
Field details — 24 fields (type, nulls, unique, samples)
Standards-Aligned Fields (6)
| 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% | - | - |
Extension Fields (18)
— supplemental data preserved outside core SEL/CCL schema
| 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% | - | - |
JPN UNHCR - Origin Populations
— 28 rows, 24 columns
Loading data…
Field details — 24 fields (type, nulls, unique, samples)
Standards-Aligned Fields (6)
| 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% | - | - |
Extension Fields (18)
— supplemental data preserved outside core SEL/CCL schema
| 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% | - | - |
JPN Google Community Mobility (2020-2022)
JPN-GOOGLE-MOBILITY
Mobility
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
1
Admin 1
— 1 table(s)
JPN Mobility by Region
— 47 rows, 11 columns
Loading data…
Field details — 11 fields (type, nulls, unique, samples)
Standards-Aligned Fields (3)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JP, JP, JP, JP, JP |
admin_level |
Admin level | integer | SEL | 0% | 1 | 1, 1, 1, 1, 1 |
iso3 |
Country code | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
Extension Fields (8)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
retail |
retail | float | 0% | 47 | -10.86, 0.96, -0.83, -9.63, -8.56 |
grocery |
grocery | float | 0% | 45 | 2.11, 7.62, 3.28, 3.08, 2.34 |
parks |
parks | float | 0% | 47 | -8.74, 49.86, 18.64, -6.6, 3.66 |
transit |
transit | float | 0% | 47 | -23.86, -11.07, -11.82, -26.28, -18.49 |
workplaces |
workplaces | float | 0% | 46 | -12.16, -8.74, -9.2, -15.45, -9.08 |
residential |
residential | float | 0% | 43 | 6.38, 3.64, 3.27, 8.29, 4.93 |
region |
region | string | 0% | 47 | Aichi, Akita, Aomori, Chiba, Ehime |
observation_count |
observation_count | integer | 0% | 1 | 974, 974, 974, 974, 974 |
JPN Glottolog Language Catalog
JPN-GLOTTOLOG
Language
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN Glottolog - Languages
— 25 rows, 16 columns
Loading data…
Field details — 16 fields (type, nulls, unique, samples)
Standards-Aligned Fields (13)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
glottocode |
Glottocode | string | CCL | 0% | 25 | ainu1240, amam1247, boni1239, cent2126, hach1239 |
name |
Name | string | CCL | 0% | 25 | Hokkaido Ainu, Amami O Shima Sign Language, Bonin... |
iso639_3 |
Iso639 3 | string | CCL | 28% | 18 | ain, jks, ryu, jsl, kzg |
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% | 5 | ainu1252, sign1238, pidg1258, japo1237, japo1237 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 0% | 16 | hokk1250, deaf1237, engl1287, okin1244, japo1237 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 2 | ['JP'], ['JP'], ['JP'], ['JP'], ['JP'] |
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% | 8 | 2, 0, 0, 4, 0 |
Extension Fields (3)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 4% | 24 | 43.633654, 28.268372, 27.07, 26.14854, 33.109444 |
longitude |
longitude | float | 4% | 24 | 142.46167, 129.358991, 142.21, 127.7816, 139.791389 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
JPN OpenFactBook
JPN-OPENFACTBOOK
Country Profile
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 16 table(s)
JPN OpenFactBook - Communications
— 1 rows, 21 columns
Loading data…
Field details — 22 fields (type, nulls, unique, samples)
Standards-Aligned Fields (8)
| 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 | 48.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 168.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .jp |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 87.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric |
Broadband subscriptions per 100 | float | SEL | 0% | 1 | 39.0 |
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (14)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
telephones_fixed_lines_total_subscriptions_text |
telephones_fixed_lines_total_subscriptions_text | string | 0% | 1 | 59.758 million (2023 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 59.758 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 48 (2023 est.) |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 219 million (2023 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 219.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 168 (2022 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | a mix of public and commercial TV and radio stations; 5... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 5.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 87% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 47.9 million (2023 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 47.9 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 39 (2023 est.) |
source_section |
source_section | string | 0% | 1 | Communications |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ja.json |
JPN OpenFactBook - Economy
— 1 rows, 146 columns
Loading data…
Field details — 151 fields (type, nulls, unique, samples)
Standards-Aligned Fields (5)
| 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 | 46100.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 4.026 |
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (146)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
economic_overview_text |
economic_overview_text | string | 0% | 1 | second-largest East Asian economy; trade-oriented and... |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $5.715 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 | 5.715 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $5.71 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 | 5.71 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $5.627 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 | 5.627 |
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 | 0.1% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | 0.1 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 1.5% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 1.5 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 0.9% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 0.9 |
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 | $46,100 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $45,900 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 45900.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $45,000 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 45000.0 |
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 | $4.026 trillion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 2.7% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 2.7 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text |
Inflation rate consumer prices 2023 (text) | string | 0% | 1 | 3.3% (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric |
Inflation rate consumer prices 2023 (numeric) | float | 0% | 1 | 3.3 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 2.5% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 2.5 |
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 | 0.9% (2023 est.) |
| +116 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN OpenFactBook - Energy
— 1 rows, 65 columns
Loading data…
Field details — 65 fields (type, nulls, unique, samples)
Standards-Aligned Fields (4)
| 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 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (61)
— supplemental data preserved outside core SEL/CCL schema
| 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 | 361.617 million kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 361.617 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 902.769 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 902.769 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 41.79 billion kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 41.79 |
electricity_generation_sources_fossil_fuels_text |
electricity_generation_sources_fossil_fuels_text | string | 0% | 1 | 65.8% of total installed capacity (2023 est.) |
electricity_generation_sources_fossil_fuels_numeric |
electricity_generation_sources_fossil_fuels_numeric | float | 0% | 1 | 65.8 |
electricity_generation_sources_nuclear_text |
electricity_generation_sources_nuclear_text | string | 0% | 1 | 8.9% of total installed capacity (2023 est.) |
electricity_generation_sources_nuclear_numeric |
electricity_generation_sources_nuclear_numeric | float | 0% | 1 | 8.9 |
electricity_generation_sources_solar_text |
electricity_generation_sources_solar_text | string | 0% | 1 | 10.3% of total installed capacity (2023 est.) |
electricity_generation_sources_solar_numeric |
electricity_generation_sources_solar_numeric | float | 0% | 1 | 10.3 |
electricity_generation_sources_wind_text |
electricity_generation_sources_wind_text | string | 0% | 1 | 1.1% of total installed capacity (2023 est.) |
electricity_generation_sources_wind_numeric |
electricity_generation_sources_wind_numeric | float | 0% | 1 | 1.1 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 7.1% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 7.1 |
electricity_generation_sources_geothermal_text |
electricity_generation_sources_geothermal_text | string | 0% | 1 | 0.3% of total installed capacity (2023 est.) |
electricity_generation_sources_geothermal_numeric |
electricity_generation_sources_geothermal_numeric | float | 0% | 1 | 0.3 |
electricity_generation_sources_biomass_and_waste_text |
electricity_generation_sources_biomass_and_waste_text | string | 0% | 1 | 6.5% of total installed capacity (2023 est.) |
electricity_generation_sources_biomass_and_waste_numeric |
electricity_generation_sources_biomass_and_waste_numeric | float | 0% | 1 | 6.5 |
nuclear_energy_number_of_operational_nuclear_reactors_text |
nuclear_energy_number_of_operational_nuclear_reactors_text | string | 0% | 1 | 14 (2025) |
nuclear_energy_number_of_operational_nuclear_reactors_numeric |
nuclear_energy_number_of_operational_nuclear_reactors_numeric | float | 0% | 1 | 14.0 |
nuclear_energy_number_of_nuclear_reactors_under_construction_text |
nuclear_energy_number_of_nuclear_reactors_under_construction_text | string | 0% | 1 | 2 (2025) |
nuclear_energy_number_of_nuclear_reactors_under_construction_numeric |
nuclear_energy_number_of_nuclear_reactors_under_construction_numeric | float | 0% | 1 | 2.0 |
nuclear_energy_net_capacity_of_operational_nuclear_reactors_text |
nuclear_energy_net_capacity_of_operational_nuclear_reactors_text | string | 0% | 1 | 12.63GW (2025 est.) |
nuclear_energy_net_capacity_of_operational_nuclear_reactors_numeric |
nuclear_energy_net_capacity_of_operational_nuclear_reactors_numeric | float | 0% | 1 | 12.63 |
nuclear_energy_percent_of_total_electricity_production_text |
nuclear_energy_percent_of_total_electricity_production_text | string | 0% | 1 | 5.5% (2023 est.) |
nuclear_energy_percent_of_total_electricity_production_numeric |
nuclear_energy_percent_of_total_electricity_production_numeric | float | 0% | 1 | 5.5 |
nuclear_energy_number_of_nuclear_reactors_permanently_shut_down_text |
nuclear_energy_number_of_nuclear_reactors_permanently_shut_down_text | string | 0% | 1 | 27 (2025) |
| +31 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN OpenFactBook - Environment
— 1 rows, 54 columns
Loading data…
Field details — 61 fields (type, nulls, unique, samples)
Standards-Aligned Fields (8)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 12.6 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 68.3 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 92.0 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | -0.25 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 42.72 |
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (53)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
environmental_issues_text |
environmental_issues_text | string | 0% | 1 | air pollution from power plants results in acid rain;... |
environmental_issues_numeric |
environmental_issues_numeric | float | 0% | 1 | 2011.0 |
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 | none of the selected agreements |
climate_text |
climate_text | string | 0% | 1 | varies from tropical in south to cool temperate in north |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 12.6% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 11.1% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 11.1 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.7% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.7 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 0.9% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 0.9 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 68.3% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 19% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 19.0 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 92% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | -0.25% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 960.23 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 960.23 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 367.144 million 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 | 367.144 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 403.042 million 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 | 403.042 |
carbon_dioxide_emissions_from_consumed_natural_gas_text |
carbon_dioxide_emissions_from_consumed_natural_gas_text | string | 0% | 1 | 190.043 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 | 190.043 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 10.5 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 10.5 |
methane_emissions_energy_text |
methane_emissions_energy_text | string | 0% | 1 | 214.7 kt (2022-2024 est.) |
methane_emissions_energy_numeric |
methane_emissions_energy_numeric | float | 0% | 1 | 214.7 |
| +23 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN OpenFactBook - Ethnic Groups
— 1 rows, 8 columns
Loading data…
Field details — 9 fields (type, nulls, unique, samples)
Standards-Aligned Fields (3)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (6)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
nationality_noun_text |
nationality_noun_text | string | 0% | 1 | Japanese (singular and plural) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Japanese |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | Japanese 97.5%, Chinese 0.6%, Vietnam 0.4%, South Korean... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 97.5 |
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/ja.json |
JPN OpenFactBook - Geography
— 1 rows, 53 columns
Loading data…
Field details — 57 fields (type, nulls, unique, samples)
Standards-Aligned Fields (13)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 377915.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 364485.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 13430.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 0.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 29751.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 3776.0 |
elevation_lowest_point_numeric |
Elevation min m | float | SEL | 0% | 1 | -4.0 |
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 12.6 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 68.3 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 15730.0 |
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (44)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
location_text |
location_text | string | 0% | 1 | Eastern Asia, island chain between the North Pacific... |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 36 00 N, 138 00 E |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 36.0 |
map_references_text |
map_references_text | string | 0% | 1 | Asia |
area_total_text |
area_total_text | string | 0% | 1 | 377,915 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 364,485 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 13,430 sq km |
area_note |
area_note | string | 0% | 1 | note: includes Bonin Islands (Ogasawara-gunto),... |
area_comparative_text |
area_comparative_text | string | 0% | 1 | slightly smaller than California |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 0 km |
coastline_text |
coastline_text | string | 0% | 1 | 29,751 km |
maritime_claims_territorial_sea_text |
maritime_claims_territorial_sea_text | string | 0% | 1 | 12 nm; between 3 nm and 12 nm in the international... |
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 |
climate_text |
climate_text | string | 0% | 1 | varies from tropical in south to cool temperate in north |
terrain_text |
terrain_text | string | 0% | 1 | mostly rugged and mountainous |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Mount Fuji 3,776 m |
elevation_lowest_point_text |
elevation_lowest_point_text | string | 0% | 1 | Hachiro-gata -4 m |
elevation_mean_elevation_text |
elevation_mean_elevation_text | string | 0% | 1 | 438 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 438.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | negligible mineral resources, fish |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 12.6% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 11.1% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 11.1 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.7% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.7 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 0.9% (2023 est.) |
| +14 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN OpenFactBook - Government
— 1 rows, 94 columns
Loading data…
Field details — 124 fields (type, nulls, unique, samples)
Standards-Aligned Fields (2)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (122)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name_conventional_long_form_text |
country_name_conventional_long_form_text | string | 0% | 1 | none |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Japan |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | Nihon-koku/Nippon-koku |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Nihon/Nippon |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | the English word for Japan comes from the Chinese name... |
government_type_text |
government_type_text | string | 0% | 1 | parliamentary constitutional monarchy |
capital_name_text |
capital_name_text | string | 0% | 1 | Tokyo |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 35 41 N, 139 45 E |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 35.0 |
capital_time_difference_text |
capital_time_difference_text | string | 0% | 1 | UTC+9 (14 hours ahead of Washington, DC, during Standard Time) |
capital_time_difference_numeric |
capital_time_difference_numeric | float | 0% | 1 | 9.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | originally known as Edo, meaning "estuary" because of... |
capital_etymology_numeric |
capital_etymology_numeric | float | 0% | 1 | 1868.0 |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 47 prefectures; Aichi, Akita, Aomori, Chiba, Ehime,... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 47.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | civil law system based on German model; also reflects... |
constitution_history_text |
constitution_history_text | string | 0% | 1 | previous 1890; latest approved 6 October 1946, adopted 3... |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 1890.0 |
constitution_amendment_process_text |
constitution_amendment_process_text | string | 0% | 1 | proposed by the Diet; passage requires approval by at... |
international_law_organization_participation_text |
international_law_organization_participation_text | string | 0% | 1 | accepts compulsory ICJ jurisdiction with reservations;... |
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 | at least one parent must be a citizen of Japan |
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 | 5 years |
citizenship_residency_requirement_for_naturalization_numeric |
citizenship_residency_requirement_for_naturalization_numeric | float | 0% | 1 | 5.0 |
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 | Emperor NARUHITO (since 1 May 2019) |
executive_branch_chief_of_state_numeric |
executive_branch_chief_of_state_numeric | float | 0% | 1 | 1.0 |
executive_branch_head_of_government_text |
executive_branch_head_of_government_text | string | 0% | 1 | Prime Minister Sanae TAKAICHI (since 21 October 2025) |
| +92 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN OpenFactBook - Introduction
— 1 rows, 6 columns
Loading data…
Field details — 7 fields (type, nulls, unique, samples)
Standards-Aligned Fields (3)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (4)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | In 1603, after decades of civil warfare, the Tokugawa... |
background_numeric |
background_numeric | float | 0% | 1 | 1603.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ja.json |
JPN OpenFactBook - Languages
— 1 rows, 7 columns
Loading data…
Field details — 7 fields (type, nulls, unique, samples)
Standards-Aligned Fields (3)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (4)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_languages_text |
Languages (text) | string | 0% | 1 | Japanese |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | 必要不可欠な基本情報の源、ワールド・ファクトブック(Japanese)The World Factbook,... |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ja.json |
JPN OpenFactBook - Migration
— 1 rows, 11 columns
Loading data…
Field details — 11 fields (type, nulls, unique, samples)
Standards-Aligned Fields (3)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (8)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
refugees_and_internally_displaced_persons_refugees_text |
refugees_and_internally_displaced_persons_refugees_text | string | 0% | 1 | 60,361 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 60361.0 |
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 29,244 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 29244.0 |
refugees_and_internally_displaced_persons_stateless_persons_text |
refugees_and_internally_displaced_persons_stateless_persons_text | string | 0% | 1 | 505 (2024 est.) |
refugees_and_internally_displaced_persons_stateless_persons_numeric |
refugees_and_internally_displaced_persons_stateless_persons_numeric | float | 0% | 1 | 505.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ja.json |
JPN OpenFactBook - Military And Security
— 1 rows, 21 columns
Loading data…
Field details — 27 fields (type, nulls, unique, samples)
Standards-Aligned Fields (3)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (24)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
military_and_security_forces_text |
military_and_security_forces_text | string | 0% | 1 | Japan Self-Defense Force (JSDF): Ground Self-Defense... |
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 | 1.4% of GDP (2024 est.) |
military_expenditures_military_expenditures_2024_numeric |
Military expenditures 2024 (numeric) | float | 0% | 1 | 1.4 |
military_expenditures_military_expenditures_2023_text |
Military expenditures 2023 (text) | string | 0% | 1 | 1.2% of GDP (2023 est.) |
military_expenditures_military_expenditures_2023_numeric |
Military expenditures 2023 (numeric) | float | 0% | 1 | 1.2 |
military_expenditures_military_expenditures_2022_text |
Military expenditures 2022 (text) | string | 0% | 1 | 1.1% of GDP (2022 est.) |
military_expenditures_military_expenditures_2022_numeric |
Military expenditures 2022 (numeric) | float | 0% | 1 | 1.1 |
military_expenditures_military_expenditures_2021_text |
Military expenditures 2021 (text) | string | 0% | 1 | 1% of GDP (2021 est.) |
military_expenditures_military_expenditures_2021_numeric |
Military expenditures 2021 (numeric) | float | 0% | 1 | 1.0 |
military_expenditures_military_expenditures_2020_text |
Military expenditures 2020 (text) | string | 0% | 1 | 1% of GDP (2020 est.) |
military_expenditures_military_expenditures_2020_numeric |
Military expenditures 2020 (numeric) | float | 0% | 1 | 1.0 |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | approximately 230-240,000 active Self Defense Forces (2025) |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 230.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the JSDF is equipped largely 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 | 18-32 years of age for voluntary military service for... |
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 | maintains a presence of about 400 military personnel at... |
military_deployments_numeric |
military_deployments_numeric | float | 0% | 1 | 400.0 |
military_note_text |
military_note_text | string | 0% | 1 | the Japan Self-Defense Force (JSDF) has a range of... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 3.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ja.json |
JPN OpenFactBook - People And Society
— 1 rows, 109 columns
Loading data…
Field details — 122 fields (type, nulls, unique, samples)
Standards-Aligned Fields (28)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 123201945.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 59875269.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 63326676.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 12.1 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 58.4 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 29.5 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 71.2 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 20.8 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 50.4 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 50.2 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | -0.45 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 6.84 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 12.04 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | 0.73 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 92.0 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | -0.25 |
sex_ratio_at_birth_numeric |
Sex ratio at birth | float | SEL | 0% | 1 | 1.06 |
sex_ratio_total_population_numeric |
Sex ratio overall | float | SEL | 0% | 1 | 0.95 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 3.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 1.8 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 85.2 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 1.41 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 0.68 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 2.65 |
hospital_bed_density_numeric |
Hospital beds per 1000 | float | SEL | 0% | 1 | 12.7 |
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (94)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
population_total_text |
population_total_text | string | 0% | 1 | 123,201,945 (2024 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 59,875,269 |
population_female_text |
population_female_text | string | 0% | 1 | 63,326,676 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 12.1% (male 7,701,196/female 7,239,389) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 58.4% (male 36,197,840/female 35,777,966) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 29.5% (2024 est.) (male 15,976,233/female 20,309,321) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 71.2 (2024 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 20.8 (2024 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 50.4 (2024 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 2 (2024 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 2.0 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 50.2 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 48.3 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 48.3 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 51.3 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 51.3 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | -0.45% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 6.84 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 12.04 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | 0.73 migrant(s)/1,000 population (2025 est.) |
population_distribution_text |
population_distribution_text | string | 0% | 1 | all primary and secondary regions of high population... |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 92% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | -0.25% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 37.194 million TOKYO (capital), 19.013 million Osaka,... |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 37.194 |
sex_ratio_at_birth_text |
sex_ratio_at_birth_text | string | 0% | 1 | 1.06 male(s)/female |
sex_ratio_0_14_years_text |
sex_ratio_0_14_years_text | string | 0% | 1 | 1.06 male(s)/female |
sex_ratio_0_14_years_numeric |
sex_ratio_0_14_years_numeric | float | 0% | 1 | 1.06 |
sex_ratio_15_64_years_text |
sex_ratio_15_64_years_text | string | 0% | 1 | 1.01 male(s)/female |
sex_ratio_15_64_years_numeric |
sex_ratio_15_64_years_numeric | float | 0% | 1 | 1.01 |
| +64 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN OpenFactBook - Religions
— 1 rows, 6 columns
Loading data…
Field details — 18 fields (type, nulls, unique, samples)
Standards-Aligned Fields (5)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_religion_other_pct_synth |
other | numeric | CCL | 0% | - | 4.0 |
composition_ethnicity_primary_label_synth |
Japanese | string | CCL | 0% | - | Japanese |
Extension Fields (4)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Shintoism 48.6%, Buddhism 46.4%, Christianity 1.1%,... |
religions_numeric |
religions_numeric | float | 0% | 1 | 48.6 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ja.json |
Pending (9) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_shintoism_pct_synth |
Shintoism | numeric | 0% | - | 48.6 |
composition_religion_buddhism_pct_synth |
Buddhism | numeric | 0% | - | 46.4 |
composition_religion_christianity_pct_synth |
Christianity | numeric | 0% | - | 1.1 |
composition_ethnicity_japanese_pct_synth |
Japanese | numeric | 0% | - | 97.5 |
composition_ethnicity_chinese_pct_synth |
Chinese | numeric | 0% | - | 0.6 |
composition_ethnicity_vietnam_pct_synth |
Vietnam | numeric | 0% | - | 0.4 |
composition_ethnicity_south_korean_pct_synth |
South Korean | numeric | 0% | - | 0.3 |
composition_ethnicity_other_pct_synth |
other | numeric | 0% | - | 1.2 |
composition_ethnicity_primary_share_pct_synth |
Japanese | numeric | 0% | - | 97.5 |
JPN OpenFactBook - Space
— 1 rows, 9 columns
Loading data…
Field details — 13 fields (type, nulls, unique, samples)
Standards-Aligned Fields (3)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (10)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
space_agency_agencies_text |
space_agency_agencies_text | string | 0% | 1 | Japan Aerospace Exploration Agency (JAXA; established in... |
space_agency_agencies_numeric |
space_agency_agencies_numeric | float | 0% | 1 | 2003.0 |
space_launch_site_s_text |
space_launch_site_s_text | string | 0% | 1 | Tanegashima Space Center/Yoshinobu Launch Complex... |
space_launch_site_s_numeric |
space_launch_site_s_numeric | float | 0% | 1 | 2025.0 |
space_program_overview_text |
space_program_overview_text | string | 0% | 1 | has one of the world’s largest and most advanced space... |
space_program_overview_numeric |
space_program_overview_numeric | float | 0% | 1 | 2025.0 |
key_space_program_milestones_text |
key_space_program_milestones_text | string | 0% | 1 | 1966-1970 - initiated satellite launch vehicle (SLV)... |
key_space_program_milestones_numeric |
key_space_program_milestones_numeric | float | 0% | 1 | 1966.0 |
source_section |
source_section | string | 0% | 1 | Space |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ja.json |
JPN OpenFactBook - Terrorism
— 1 rows, 5 columns
Loading data…
Field details — 5 fields (type, nulls, unique, samples)
Standards-Aligned Fields (3)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (2)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
source_section |
source_section | string | 0% | 1 | Terrorism |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/ja.json |
JPN OpenFactBook - Transportation
— 1 rows, 34 columns
Loading data…
Field details — 38 fields (type, nulls, unique, samples)
Standards-Aligned Fields (5)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
civil_aircraft_registration_country_code_prefix_text |
Civil aircraft registration country code prefix text | string | SEL+ | 0% | 1 | JA |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 280.0 |
country_code |
Country code | string | SEL | 0% | 1 | JPN |
country_name |
Country name | string | SEL | 0% | 1 | Japan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
Extension Fields (33)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
airports_text |
airports_text | string | 0% | 1 | 280 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 3,036 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 3036.0 |
railways_total_text |
railways_total_text | string | 0% | 1 | 27,311 km (2015) |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 27311.0 |
railways_standard_gauge_text |
railways_standard_gauge_text | string | 0% | 1 | 4,800 km (2015) 1.435-m gauge (4,800 km electrified) |
railways_standard_gauge_numeric |
railways_standard_gauge_numeric | float | 0% | 1 | 4800.0 |
railways_narrow_gauge_text |
railways_narrow_gauge_text | string | 0% | 1 | 124 km (2015) 1.372-m gauge (124 km electrified) |
railways_narrow_gauge_numeric |
railways_narrow_gauge_numeric | float | 0% | 1 | 124.0 |
railways_dual_gauge_text |
railways_dual_gauge_text | string | 0% | 1 | 132 km (2015) 1.435-1.067-m gauge (132 km electrified) |
railways_dual_gauge_numeric |
railways_dual_gauge_numeric | float | 0% | 1 | 132.0 |
railways_note |
railways_note | string | 0% | 1 | 22,207 km 1.067-mm gauge (15,430 km electrified)48 km... |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 5,229 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 5229.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | bulk carrier 166, container ship 49, general cargo... |
merchant_marine_by_type_numeric |
merchant_marine_by_type_numeric | float | 0% | 1 | 166.0 |
ports_total_ports_text |
ports_total_ports_text | string | 0% | 1 | 163 (2024) |
ports_total_ports_numeric |
ports_total_ports_numeric | float | 0% | 1 | 163.0 |
ports_large_text |
ports_large_text | float | 0% | 1 | 11 |
ports_large_numeric |
ports_large_numeric | float | 0% | 1 | 11.0 |
ports_medium_text |
ports_medium_text | float | 0% | 1 | 26 |
ports_medium_numeric |
ports_medium_numeric | float | 0% | 1 | 26.0 |
ports_small_text |
ports_small_text | float | 0% | 1 | 54 |
ports_small_numeric |
ports_small_numeric | float | 0% | 1 | 54.0 |
ports_very_small_text |
ports_very_small_text | float | 0% | 1 | 71 |
ports_very_small_numeric |
ports_very_small_numeric | float | 0% | 1 | 71.0 |
ports_size_unknown_text |
ports_size_unknown_text | float | 0% | 1 | 1 |
ports_size_unknown_numeric |
ports_size_unknown_numeric | float | 0% | 1 | 1.0 |
ports_ports_with_oil_terminals_text |
Ports with oil terminals (text) | float | 0% | 1 | 99 |
ports_ports_with_oil_terminals_numeric |
Ports with oil terminals (numeric) | float | 0% | 1 | 99.0 |
| +3 more extension fields — download the CSV/Parquet to see them all. | |||||
JPN Ethnic Power Relations Dataset
JPN-EPR
Political Ethnicity
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN EPR - Groups
— 5 rows, 8 columns
Loading data…
Field details — 8 fields (type, nulls, unique, samples)
Standards-Aligned Fields (6)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN, JPN |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 5 | Japanese, Okinawans, Burakumin, Koreans, Ainu |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 3 | MONOPOLY, POWERLESS, IRRELEVANT, POWERLESS, POWERLESS |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 5 | 0.979, 0.01, 0.007, 0.002, 0.0002 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 5 | 74003000, 74005000, 74002000, 74006000, 74001000 |
regional_autonomy |
Regional autonomy | string | CCL | 0% | 2 | , false, , false, false |
Extension Fields (2)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
group_relevance |
group_relevance | string | 0% | 1 | , , , , |
JPN NGA GEOnet Names Server (GNS)
JPN-NGA_GNS
Language
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 2 table(s)
JPN Nga Gns - Language
— 4 rows, 9 columns
Loading data…
Field details — 9 fields (type, nulls, unique, samples)
Standards-Aligned Fields (9)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN |
gns_language_code |
gns_language_code | string | CCL | 0% | 4 | jpn, rus, eng, ace |
gns_language_name |
gns_language_name | string | CCL | 0% | 4 | Japanese, Russian, English, Achinese |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 4 | 290574, 1972, 626, 1 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 4 | 99.1135, 0.6726, 0.2135, 0.0003 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 3 | 166756, 863, 0, 0 |
gns_dominant_script_code |
gns_dominant_script_code | string | CCL | 0% | 4 | Hani, Cyrl, Latn, |
gns_dominant_script_name |
gns_dominant_script_name | string | CCL | 0% | 4 | Han (Hanzi, Kanji, Hanja), Cyrillic, Latin, |
gns_script_count |
gns_script_count | integer | CCL | 0% | 3 | 8, 1, 1, 0 |
JPN Nga Gns - Summary
— 1 rows, 31 columns
Loading data…
Field details — 31 fields (type, nulls, unique, samples)
Standards-Aligned Fields (7)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | JPN |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Japan |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 4 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 9 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 99.994 |
gns_non_roman_name_count |
gns_non_roman_name_count | integer | CCL | 0% | 1 | 167624 |
Extension Fields (24)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
gns_name_count |
gns_name_count | integer | 0% | 1 | 301477 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 93713 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 301459 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 18 |
gns_source_build_date |
gns_source_build_date | string | 0% | 1 | Wed, 05 Aug 2026 |
gns_source_change_date |
gns_source_change_date | string | 0% | 1 | 2026-08-05 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 63316 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 19161 |
gns_name_count_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 34660 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 9929 |
gns_name_count_populated_places |
gns_name_count_populated_places | integer | 0% | 1 | 137448 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 45977 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 2805 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 1003 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 43166 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 12497 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 18470 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 4655 |
gns_name_count_vegetation |
gns_name_count_vegetation | integer | 0% | 1 | 238 |
gns_feature_count_vegetation |
gns_feature_count_vegetation | integer | 0% | 1 | 65 |
gns_name_count_transportation_networks |
gns_name_count_transportation_networks | integer | 0% | 1 | 1366 |
gns_feature_count_transportation_networks |
gns_feature_count_transportation_networks | integer | 0% | 1 | 422 |
gns_name_count_undersea |
gns_name_count_undersea | integer | 0% | 1 | 8 |
gns_feature_count_undersea |
gns_feature_count_undersea | integer | 0% | 1 | 4 |
JPN D-PLACE
JPN-DPLACE
Ethnographic Societies
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN D-PLACE - Dplace Ea Societies
— 4 rows, 18 columns
Loading data…
Field details — 18 fields (type, nulls, unique, samples)
Standards-Aligned Fields (11)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN, JPN, JPN, JPN |
society_id |
Society id | string | CCL | 0% | 4 | Ec7, Ed15a, Ed5, Ed7 |
society_name |
Society name | string | CCL | 0% | 4 | Ainu, Miyakans, Japanese, Okinawans |
language_glottocode |
Language glottocode | string | CCL | 0% | 4 | ainu1240, miya1259, nucl1643, cent2126 |
language_name |
Language name | string | CCL | 0% | 1 | , , , |
kinship_system |
Kinship system | string | CCL | 0% | 4 | EA001:2; EA002:3; EA003:4; EA004:0; EA005:1, EA001:0;... |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 4 | EA006:6; EA007:8; EA008:2; EA009:2; EA010:12, EA006:6;... |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 4 | EA028:3; EA029:6; EA030:3; EA031:1; EA032:3, EA028:NA;... |
political_complexity |
Political complexity | string | CCL | 0% | 4 | EA033:2; EA034:1; EA035:2, EA033:NA; EA034:NA; EA035:NA,... |
religion_importance |
Religion importance | string | CCL | 0% | 4 | EA034:1; EA112:6, EA034:NA; EA112:NA, EA034:2; EA112:6,... |
residence_pattern |
Residence pattern | string | CCL | 0% | 3 | EA011:2; EA012:12; EA013:3, EA011:1; EA012:8; EA013:2,... |
Extension Fields (7)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Japan, Japan, Japan, Japan |
dataset |
dataset | string | 0% | 1 | EA, EA, EA, EA |
region |
region | string | 0% | 1 | , , , |
latitude |
latitude | float | 0% | 4 | 44.0, 24.79, 35.0, 26.16 |
longitude |
longitude | float | 0% | 4 | 144.0, 125.32, 136.0, 127.8 |
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 |
JPN Global Organized Crime Index
JPN-OCINDEX
Crime Index
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN Organized Crime Scores 2025
— 1 rows, 35 columns
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Field details — 139 fields (type, nulls, unique, samples)
Standards-Aligned Fields (13)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
oc_anti_money_laundering |
oc_anti_money_laundering | numeric | CCL | 0% | 1 | - |
oc_arms_trafficking |
oc_arms_trafficking | numeric | CCL | 0% | 1 | - |
oc_criminal_actors |
oc_criminal_actors | numeric | CCL | 0% | 1 | - |
oc_criminal_markets |
oc_criminal_markets | numeric | CCL | 0% | 1 | - |
oc_criminality |
oc_criminality | numeric | CCL | 0% | 1 | - |
oc_cyber_dependent_crimes |
oc_cyber_dependent_crimes | numeric | CCL | 0% | 1 | - |
oc_financial_crimes |
oc_financial_crimes | numeric | CCL | 0% | 1 | - |
oc_human_smuggling |
oc_human_smuggling | numeric | CCL | 0% | 1 | - |
oc_human_trafficking |
oc_human_trafficking | numeric | CCL | 0% | 1 | - |
oc_judicial_system_and_detention |
oc_judicial_system_and_detention | numeric | CCL | 0% | 1 | - |
oc_law_enforcement |
oc_law_enforcement | numeric | CCL | 0% | 1 | - |
oc_political_leadership_and_governance |
oc_political_leadership_and_governance | numeric | CCL | 0% | 1 | - |
oc_resilience |
oc_resilience | numeric | CCL | 0% | 1 | - |
Extension Fields (22)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
oc_cannabis_trade |
oc_cannabis_trade | numeric | 0% | 1 | - |
oc_cocaine_trade |
oc_cocaine_trade | numeric | 0% | 1 | - |
oc_criminal_networks |
oc_criminal_networks | numeric | 0% | 1 | - |
oc_economic_regulatory_capacity |
oc_economic_regulatory_capacity | numeric | 0% | 1 | - |
oc_extortion_and_protection_racketeering |
oc_extortion_and_protection_racketeering | numeric | 0% | 1 | - |
oc_fauna_crimes |
oc_fauna_crimes | numeric | 0% | 1 | - |
oc_flora_crimes |
oc_flora_crimes | numeric | 0% | 1 | - |
oc_foreign_actors |
oc_foreign_actors | numeric | 0% | 1 | - |
oc_government_transparency_and_accountability |
oc_government_transparency_and_accountability | numeric | 0% | 1 | - |
oc_heroin_trade |
oc_heroin_trade | numeric | 0% | 1 | - |
oc_illicit_trade_in_excisable_goods |
oc_illicit_trade_in_excisable_goods | numeric | 0% | 1 | - |
oc_international_cooperation |
oc_international_cooperation | numeric | 0% | 1 | - |
oc_mafia_style_groups |
oc_mafia_style_groups | numeric | 0% | 1 | - |
oc_national_policies_and_laws |
oc_national_policies_and_laws | numeric | 0% | 1 | - |
oc_non_renewable_resource_crimes |
oc_non_renewable_resource_crimes | numeric | 0% | 1 | - |
oc_non_state_actors |
oc_non_state_actors | numeric | 0% | 1 | - |
oc_prevention |
oc_prevention | numeric | 0% | 1 | - |
oc_private_sector_actors |
oc_private_sector_actors | numeric | 0% | 1 | - |
oc_state_embedded_actors |
oc_state_embedded_actors | numeric | 0% | 1 | - |
oc_synthetic_drug_trade |
oc_synthetic_drug_trade | numeric | 0% | 1 | - |
oc_territorial_integrity |
oc_territorial_integrity | numeric | 0% | 1 | - |
oc_trade_in_counterfeit_goods |
oc_trade_in_counterfeit_goods | numeric | 0% | 1 | - |
Pending (104) — awaiting mapping
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
iso3 |
iso3 | string | 0% | 1 | JPN |
source |
source | string | 0% | 1 | Global Organized Crime Index |
source_url |
source_url | string | 0% | 1 | https://ocindex.net/ |
year |
year | integer | 0% | 1 | 2025 |
license |
license | string | 0% | 1 | Creative Commons (GI-TOC / ENACT) |
oc_anti_money_laundering_rank |
oc_anti_money_laundering_rank | integer | 0% | 1 | 7 |
oc_anti_money_laundering_2023 |
oc_anti_money_laundering_2023 | float | 0% | 1 | 7.5 |
oc_anti_money_laundering_2021 |
oc_anti_money_laundering_2021 | integer | 0% | 1 | 8 |
oc_arms_trafficking_rank |
oc_arms_trafficking_rank | integer | 0% | 1 | 171 |
oc_arms_trafficking_2023 |
oc_arms_trafficking_2023 | float | 0% | 1 | 2.5 |
oc_arms_trafficking_2021 |
oc_arms_trafficking_2021 | integer | 0% | 1 | 3 |
oc_cannabis_trade_rank |
oc_cannabis_trade_rank | integer | 0% | 1 | 114 |
oc_cannabis_trade_2023 |
oc_cannabis_trade_2023 | float | 0% | 1 | 4.5 |
oc_cannabis_trade_2021 |
oc_cannabis_trade_2021 | float | 0% | 1 | 4.5 |
oc_cocaine_trade_rank |
oc_cocaine_trade_rank | integer | 0% | 1 | 137 |
oc_cocaine_trade_2023 |
oc_cocaine_trade_2023 | integer | 0% | 1 | 3 |
oc_cocaine_trade_2021 |
oc_cocaine_trade_2021 | integer | 0% | 1 | 3 |
oc_criminal_actors_rank |
oc_criminal_actors_rank | integer | 0% | 1 | 126 |
oc_criminal_actors_2023 |
oc_criminal_actors_2023 | float | 0% | 1 | 4.7 |
oc_criminal_actors_2021 |
oc_criminal_actors_2021 | integer | 0% | 1 | 5 |
oc_criminal_markets_rank |
oc_criminal_markets_rank | integer | 0% | 1 | 150 |
oc_criminal_markets_2023 |
oc_criminal_markets_2023 | float | 0% | 1 | 3.87 |
oc_criminal_markets_2021 |
oc_criminal_markets_2021 | float | 0% | 1 | 4.05 |
oc_criminal_networks_rank |
oc_criminal_networks_rank | integer | 0% | 1 | 74 |
oc_criminal_networks_2023 |
oc_criminal_networks_2023 | float | 0% | 1 | 5.5 |
oc_criminal_networks_2021 |
oc_criminal_networks_2021 | float | 0% | 1 | 5.5 |
oc_criminality_rank |
oc_criminality_rank | integer | 0% | 1 | 141 |
oc_criminality_2023 |
oc_criminality_2023 | float | 0% | 1 | 4.28 |
oc_criminality_2021 |
oc_criminality_2021 | float | 0% | 1 | 4.53 |
oc_cyber_dependent_crimes_rank |
oc_cyber_dependent_crimes_rank | integer | 0% | 1 | 95 |
| +74 more pending fields — download the CSV/Parquet to see them all. | |||||
JPN World Values Survey
JPN-WVS
Attitudes Values
or use the per-admin-level buttons below. Free downloads return a 10-row sample.
Contact us for the full pack.
0
Admin 0
— 1 table(s)
JPN WVS - Country Aggregates
— 1 rows, 26 columns
Loading data…
Field details — 26 fields (type, nulls, unique, samples)
Standards-Aligned Fields (1)
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | JPN |
Extension Fields (25)
— supplemental data preserved outside core SEL/CCL schema
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
wave |
wave | integer | 0% | 1 | 7 |
wave_years |
wave_years | string | 0% | 1 | 2017-2022 |
source |
source | string | 0% | 1 | World Values Survey |
importance_religion |
importance_religion | integer | 0% | 1 | 1 |
importance_family |
importance_family | integer | 0% | 1 | 1 |
importance_friends |
importance_friends | integer | 0% | 1 | 1 |
trust_people |
trust_people | integer | 0% | 1 | 1 |
trust_family |
trust_family | integer | 0% | 1 | 1 |
life_satisfaction |
life_satisfaction | integer | 0% | 1 | 1 |
happiness |
happiness | integer | 0% | 1 | 1 |
freedom_choice |
freedom_choice | integer | 0% | 1 | 1 |
gender_jobs_scarce |
gender_jobs_scarce | integer | 0% | 1 | 1 |
gender_political_leaders |
gender_political_leaders | integer | 0% | 1 | 1 |
gender_university |
gender_university | integer | 0% | 1 | 1 |
justifiable_divorce |
justifiable_divorce | integer | 0% | 1 | 1 |
justifiable_homosexuality |
justifiable_homosexuality | integer | 0% | 1 | 1 |
immigration_policy |
immigration_policy | integer | 0% | 1 | 1 |
immigrants_jobs |
immigrants_jobs | integer | 0% | 1 | 1 |
immigrants_culture |
immigrants_culture | integer | 0% | 1 | 1 |
confidence_government |
confidence_government | integer | 0% | 1 | 1 |
confidence_parliament |
confidence_parliament | integer | 0% | 1 | 1 |
confidence_police |
confidence_police | integer | 0% | 1 | 1 |
confidence_courts |
confidence_courts | integer | 0% | 1 | 1 |
confidence_press |
confidence_press | integer | 0% | 1 | 1 |
democracy_importance |
democracy_importance | integer | 0% | 1 | 1 |