| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 100 | PK7, PK5, PK2, PK6, PK8 |
region_name |
Admin name | string | SEL | 0% | 1 | Pakistan, Pakistan, Pakistan, Pakistan, Pakistan |
T_TL |
Population count | integer | SEL | 0% | 99 | 12344408, 2006572, 35525047, 110012442, 47886051 |
M_TL |
Population male | integer | SEL | 0% | 99 | 6483653, 1055712, 18023937, 55958974, 24927046 |
F_TL |
Population female | integer | SEL | 0% | 99 | 5860646, 950727, 17500170, 54046759, 22956478 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
admin_level | string | 0% | 2 | admin_1, admin_1, admin_1, admin_1, admin_1 |
year |
year | string | 100% | - | - |
admin1Name_en |
admin1Name_en | string | 95% | 5 | Balochistan, Federal Capital Territory, Khyber... |
U_TL |
U_TL | integer | 0% | 88 | 3400876, 1014825, 5871532, 40387298, 24910458 |
R_TL |
R_TL | integer | 0% | 99 | 8943532, 991747, 29653515, 69625144, 22975593 |
TG_TL |
TG_TL | integer | 0% | 63 | 109, 133, 940, 6709, 2527 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 100 | PK20101, PK60305, PK61201, PK20301, PK62301 |
region_name |
Admin name | string | SEL | 0% | 1 | Pakistan, Pakistan, Pakistan, Pakistan, Pakistan |
T_TL |
Population count | float | SEL | 0% | 100 | 1332912, 1078683, 433517, 180414, 639748 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
admin_level | string | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
year |
year | string | 100% | - | - |
admin3Name_en |
admin3Name_en | string | 0% | 100 | Abbottabad, Ahmadupr East, Ahmedpur Sial, Alai, Alipur |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | Pakistan |
admin_code |
Admin code | string | SEL | 0% | 1 | 80972501B79610057257386 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 866216.7016 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 252130899 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 291.07 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK, PAK, PAK, PAK, PAK |
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% | 7 | Punjab, Sindh, Khyber Pakhtunkhwa, Balochistan, Azad Kashmir |
admin_code |
Admin code | string | SEL | 0% | 7 | 70912109B12169979015230, 70912109B8393927546319,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 7 | 201923.7021, 137721.8058, 101528.7775, 352516.3032, 12391.7161 |
pop_2024 |
Population count | integer | SEL | 0% | 7 | 128287461, 57469878, 41894280, 12118073, 5984379 |
pop_density_2024 |
Population density | float | SEL | 0% | 7 | 635.33, 417.29, 412.63, 34.38, 482.93 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK, PAK, PAK, PAK, PAK |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality, locality, locality, locality |
admin_name |
Admin name | string | SEL | 0% | 100 | Karachi, Lahore, Islamabad, Peshawar, Faisalabad |
admin_code |
Admin code | integer | SEL | 0% | 100 | 2457, 7794, 6766, 4277, 7428 |
area_sqkm |
Area sqkm | float | SEL | 0% | 100 | 830.3868, 895.2583, 548.5684, 506.7228, 324.9983 |
pop_2024 |
Population count | integer | SEL | 0% | 100 | 28496825, 9986203, 5020856, 3733166, 3124369 |
pop_density_2024 |
Population density | float | SEL | 0% | 100 | 34317.53, 11154.55, 9152.65, 7367.27, 9613.49 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 100 | 21031703, 14305060, 4913528, 3497359, 5676793 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 95 | 1.355, 0.698, 1.022, 1.067, 0.55 |
ⓘ 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.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK, PAK, PAK, PAK, PAK |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 9 | Total, AJK, Balochistan, FATA, Gilgit Baltistan |
human_development_index |
Human development index | float | SEL | 0% | 77 | 0.422, 0.503, 0.385, 0.382, 0.43 |
health_index |
Health index | float | SEL | 0% | 65 | 0.611, 0.591, 0.61, 0.702, 0.591 |
education_index |
Education index | float | SEL | 0% | 83 | 0.235, 0.377, 0.194, 0.177, 0.261 |
income_index |
Income index | float | SEL | 0% | 65 | 0.521, 0.571, 0.482, 0.448, 0.515 |
life_expectancy |
Life expectancy | float | SEL | 0% | 84 | 59.73, 58.4, 59.63, 65.6, 58.4 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 100 | 3.532, 5.85, 2.732, 2.198, 3.109 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 12 | 1990, 1990, 1990, 1990, 1990 |
level |
level | string | 0% | 2 | national, subnational, subnational, subnational, subnational |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 100 | Karachi, Lahore, Faisalabad, Islamabad, Peshawar |
country_code |
Country code | string | SEL | 0% | 1 | PAK, PAK, PAK, PAK, PAK |
population |
Population count | integer | SEL | 0% | 100 | 21031703, 14305060, 5676793, 4913528, 3497359 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 100 | 2457, 7794, 7428, 6766, 4277 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Pakistan, Pakistan, Pakistan, Pakistan, Pakistan |
population_year |
population_year | integer | 0% | 1 | 2025, 2025, 2025, 2025, 2025 |
latitude |
latitude | string | 100% | - | - |
longitude |
longitude | string | 100% | - | - |
region |
region | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PK, PK, PK, PK, PK |
population_count |
Population count | float | SEL | 2% | 65 | 45709310.0, 46921277.0, 48156128.0, 49447776.0, 50799999.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 44.101, 44.956, 45.85, 46.761, 47.831 |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 2% | 65 | 82.0241000071912, 87.7778246966181, 89.5039525753413,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 76% | 16 | 25.7299995422363, 42.7000007629395, 49.8699989318848,... |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 250.1, 241.2, 232.9, 225.2, 218.1 |
poverty_headcount_pct |
Poverty headcount percent | float | SEL | 86% | 9 | 64.3, 51.7, 50.4, 44.1, 36.8 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Pakistan, Pakistan, Pakistan, Pakistan, Pakistan |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PK, PK, PK, PK, PK |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 44.101, 44.956, 45.85, 46.761, 47.831 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 3% | 64 | 86.9, 85.2, 83.6, 82.2, 80.8 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 250.1, 241.2, 232.9, 225.2, 218.1 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 37 | 432.0, 436.0, 442.0, 441.0, 439.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 54 | 6.8, 6.8, 6.8, 6.8, 6.8 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 64 | 46.693, 46.63, 46.448, 46.242, 45.998 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 64 | 20.065, 19.483, 18.857, 18.234, 17.506 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 47% | 35 | 0.185, 0.232, 0.233, 0.285, 0.344 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 52% | 21 | 0.55726158618927, 0.520799994468689, 0.526300013065338,... |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 32% | 36 | 2.0, 3.0, 5.0, 15.0, 23.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 2.48079324, 2.33959723, 2.42219901, 2.10399199, 2.03666282 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Pakistan, Pakistan, Pakistan, Pakistan, Pakistan |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
glottocode |
Glottocode | string | CCL | 0% | 86 | aerr1238, bade1240, bagr1243, balt1258, bate1261 |
name |
Name | string | CCL | 0% | 86 | Aer, Badeshi, Bagri, Balti, Bateri |
iso639_3 |
Iso639 3 | string | CCL | 0% | 86 | aeq, bdz, bgq, bft, btv |
level |
Level | string | CCL | 0% | 1 | language, language, language, language, language |
family_name |
Family name | string | CCL | 100% | - | - |
family_glottocode |
Family glottocode | string | CCL | 1% | 7 | indo1319, unat1236, indo1319, sino1245, indo1319 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 1% | 56 | west2830, indo1329, bagr1245, sham1282, bate1269 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 18 | ['PK'], ['PK'], ['IN', 'PK'], ['IN', 'PK'], ['IN', 'PK'] |
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% | 13 | 2, 0, 3, 0, 0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 1% | 84 | 25.254, 35.2655, 31.4, 34.4491, 34.9582 |
longitude |
longitude | float | 1% | 84 | 69.029, 72.6823, 75.06, 77.2859, 72.92674 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 100% | - | - |
women_who_are_literate |
Women who are literate | float | CCL | 0% | 18 | 63.8, 15.4, 15.8, 15.9, 9.0 |
men_who_are_literate |
Men who are literate | float | CCL | 22% | 14 | 83.6, 52.8, 54.6, 64.7, 71.5 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Pakistan, Pakistan, Pakistan, Pakistan, Pakistan |
survey_year |
survey_year | integer | 0% | 3 | 2017, 2006, 2012, 2017, 2017 |
region |
region | string | 0% | 9 | Azad, Jammu and Kashmir, Balochistan, Balochistan,... |
survey_id |
survey_id | string | 0% | 3 | PK2017DHS, PK2006DHS, PK2012DHS, PK2017DHS, PK2017DHS |
survey_type |
survey_type | string | 0% | 1 | DHS, DHS, DHS, DHS, DHS |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 100% | - | - |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 0% | 19 | 47.0, 72.0, 49.0, 97.0, 66.0 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 0% | 21 | 53.0, 101.0, 59.0, 111.0, 78.0 |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 0% | 22 | 75.2, 17.8, 35.2, 16.4, 28.8 |
children_underweight |
Children underweight | float | CCL | 18% | 16 | 17.6, 51.0, 37.3, 39.0, 22.9 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Pakistan, Pakistan, Pakistan, Pakistan, Pakistan |
survey_year |
survey_year | integer | 0% | 4 | 2017, 1991, 2006, 2012, 2017 |
region |
region | string | 0% | 9 | Azad, Jammu and Kashmir, Balochistan, Balochistan,... |
survey_id |
survey_id | string | 0% | 4 | PK2017DHS, PK1991DHS, PK2006DHS, PK2012DHS, PK2017DHS |
survey_type |
survey_type | string | 0% | 1 | DHS, DHS, DHS, DHS, DHS |
| 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 | 1.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 77.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .pk |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 27.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric |
Broadband subscriptions per 100 | float | SEL | 0% | 1 | 1.0 |
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
telephones_fixed_lines_total_subscriptions_text |
telephones_fixed_lines_total_subscriptions_text | string | 0% | 1 | 2.573 million (2023 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 2.573 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 1 (2023 est.) |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 193 million (2024 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 193.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 77 (2024 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | 120 satellite TV stations; 42 media companies/channels;... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 120.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 27% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 3.36 million (2023 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 3.36 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 1 (2023 est.) |
source_section |
source_section | string | 0% | 1 | Communications |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
real_gdp_per_capita_real_gdp_per_capita_2024_numeric |
Real gdp per capita 2024 (numeric) | float | SEL | 0% | 1 | 5500.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 373.072 |
population_below_poverty_line_numeric |
Poverty headcount percent | float | SEL | 0% | 1 | 21.9 |
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
economic_overview_text |
economic_overview_text | string | 0% | 1 | lower middle-income South Asian economy; extremely high... |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $1.39 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 | 1.39 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $1.346 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 | 1.346 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $1.347 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 | 1.347 |
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 | 3.2% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | 3.2 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 0% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 0.0 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 4.8% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 4.8 |
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 | $5,500 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $5,400 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 5400.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $5,500 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 5500.0 |
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 | $373.072 billion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 12.6% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 12.6 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text |
Inflation rate consumer prices 2023 (text) | string | 0% | 1 | 30.8% (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric |
Inflation rate consumer prices 2023 (numeric) | float | 0% | 1 | 30.8 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 19.9% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 19.9 |
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 | 23.5% (2024 est.) |
| +119 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
electricity_access_electrification_total_population_numeric |
Electricity access percent | float | SEL | 0% | 1 | 95.0 |
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
electricity_access_electrification_total_population_text |
electricity_access_electrification_total_population_text | string | 0% | 1 | 95% (2022 est.) |
electricity_access_electrification_urban_areas_text |
electricity_access_electrification_urban_areas_text | string | 0% | 1 | 100% |
electricity_access_electrification_urban_areas_numeric |
electricity_access_electrification_urban_areas_numeric | float | 0% | 1 | 100.0 |
electricity_access_electrification_rural_areas_text |
electricity_access_electrification_rural_areas_text | string | 0% | 1 | 93% |
electricity_access_electrification_rural_areas_numeric |
electricity_access_electrification_rural_areas_numeric | float | 0% | 1 | 93.0 |
electricity_installed_generating_capacity_text |
electricity_installed_generating_capacity_text | string | 0% | 1 | 43.512 million kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 43.512 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 145.357 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 145.357 |
electricity_imports_text |
electricity_imports_text | string | 0% | 1 | 481.25 million kWh (2023 est.) |
electricity_imports_numeric |
electricity_imports_numeric | float | 0% | 1 | 481.25 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 25.811 billion kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 25.811 |
electricity_generation_sources_fossil_fuels_text |
electricity_generation_sources_fossil_fuels_text | string | 0% | 1 | 60.4% of total installed capacity (2023 est.) |
electricity_generation_sources_fossil_fuels_numeric |
electricity_generation_sources_fossil_fuels_numeric | float | 0% | 1 | 60.4 |
electricity_generation_sources_nuclear_text |
electricity_generation_sources_nuclear_text | string | 0% | 1 | 14.1% of total installed capacity (2023 est.) |
electricity_generation_sources_nuclear_numeric |
electricity_generation_sources_nuclear_numeric | float | 0% | 1 | 14.1 |
electricity_generation_sources_solar_text |
electricity_generation_sources_solar_text | string | 0% | 1 | 0.7% of total installed capacity (2023 est.) |
electricity_generation_sources_solar_numeric |
electricity_generation_sources_solar_numeric | float | 0% | 1 | 0.7 |
electricity_generation_sources_wind_text |
electricity_generation_sources_wind_text | string | 0% | 1 | 3.7% of total installed capacity (2023 est.) |
electricity_generation_sources_wind_numeric |
electricity_generation_sources_wind_numeric | float | 0% | 1 | 3.7 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 19.9% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 19.9 |
electricity_generation_sources_biomass_and_waste_text |
electricity_generation_sources_biomass_and_waste_text | string | 0% | 1 | 1.1% of total installed capacity (2023 est.) |
electricity_generation_sources_biomass_and_waste_numeric |
electricity_generation_sources_biomass_and_waste_numeric | float | 0% | 1 | 1.1 |
nuclear_energy_number_of_operational_nuclear_reactors_text |
nuclear_energy_number_of_operational_nuclear_reactors_text | string | 0% | 1 | 6 (2025) |
nuclear_energy_number_of_operational_nuclear_reactors_numeric |
nuclear_energy_number_of_operational_nuclear_reactors_numeric | float | 0% | 1 | 6.0 |
nuclear_energy_number_of_nuclear_reactors_under_construction_text |
nuclear_energy_number_of_nuclear_reactors_under_construction_text | string | 0% | 1 | 1 (2025) |
nuclear_energy_number_of_nuclear_reactors_under_construction_numeric |
nuclear_energy_number_of_nuclear_reactors_under_construction_numeric | float | 0% | 1 | 1.0 |
nuclear_energy_net_capacity_of_operational_nuclear_reactors_text |
nuclear_energy_net_capacity_of_operational_nuclear_reactors_text | string | 0% | 1 | 3.26GW (2025 est.) |
| +33 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 46.7 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 4.1 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 38.0 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 2.1 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 30.76 |
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
environmental_issues_text |
environmental_issues_text | string | 0% | 1 | water pollution from raw sewage, industrial wastes, and... |
international_environmental_agreements_party_to_text |
international_environmental_agreements_party_to_text | string | 0% | 1 | Antarctic-Environmental Protection, Antarctic-Marine... |
international_environmental_agreements_signed_but_not_ratified_text |
international_environmental_agreements_signed_but_not_ratified_text | string | 0% | 1 | Marine Life Conservation |
climate_text |
climate_text | string | 0% | 1 | mostly hot, dry desert; temperate in northwest; arctic in north |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 46.7% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 39.3% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 39.3 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 1% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 1.0 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 6.5% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 6.5 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 4.1% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 49.2% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 49.2 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 38% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 2.1% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 212.655 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 212.655 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 59.937 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 | 59.937 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 93.713 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 | 93.713 |
carbon_dioxide_emissions_from_consumed_natural_gas_text |
carbon_dioxide_emissions_from_consumed_natural_gas_text | string | 0% | 1 | 59.006 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 | 59.006 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 50.1 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 50.1 |
methane_emissions_energy_text |
methane_emissions_energy_text | string | 0% | 1 | 1,625.2 kt (2022-2024 est.) |
methane_emissions_energy_numeric |
methane_emissions_energy_numeric | float | 0% | 1 | 1625.2 |
methane_emissions_agriculture_text |
methane_emissions_agriculture_text | string | 0% | 1 | 5,381.3 kt (2019-2021 est.) |
methane_emissions_agriculture_numeric |
methane_emissions_agriculture_numeric | float | 0% | 1 | 5381.3 |
| +17 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
nationality_noun_text |
nationality_noun_text | string | 0% | 1 | Pakistani(s) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Pakistani |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | Punjabi 44.7%, Pashtun (Pathan) 15.4%, Sindhi 14.1%,... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 44.7 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 796095.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 770875.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 25220.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 7257.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 1046.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 2.0 |
elevation_lowest_point_numeric |
Elevation min m | float | SEL | 0% | 1 | 0.0 |
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 46.7 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 4.1 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 194200.0 |
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
location_text |
location_text | string | 0% | 1 | Southern Asia, bordering the Arabian Sea, between India... |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 30 00 N, 70 00 E |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 30.0 |
map_references_text |
map_references_text | string | 0% | 1 | Asia |
area_total_text |
area_total_text | string | 0% | 1 | 796,095 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 770,875 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 25,220 sq km |
area_comparative_text |
area_comparative_text | string | 0% | 1 | slightly more than five times the size of Georgia;... |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 7,257 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | Afghanistan 2,670 km; China 438 km; India 3,190 km; Iran 959 km |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 2670.0 |
coastline_text |
coastline_text | string | 0% | 1 | 1,046 km |
maritime_claims_territorial_sea_text |
maritime_claims_territorial_sea_text | string | 0% | 1 | 12 nm |
maritime_claims_territorial_sea_numeric |
maritime_claims_territorial_sea_numeric | float | 0% | 1 | 12.0 |
maritime_claims_contiguous_zone_text |
maritime_claims_contiguous_zone_text | string | 0% | 1 | 24 nm |
maritime_claims_contiguous_zone_numeric |
maritime_claims_contiguous_zone_numeric | float | 0% | 1 | 24.0 |
maritime_claims_exclusive_economic_zone_text |
maritime_claims_exclusive_economic_zone_text | string | 0% | 1 | 200 nm |
maritime_claims_exclusive_economic_zone_numeric |
maritime_claims_exclusive_economic_zone_numeric | float | 0% | 1 | 200.0 |
maritime_claims_continental_shelf_text |
maritime_claims_continental_shelf_text | string | 0% | 1 | 200 nm or to the edge of the continental margin |
maritime_claims_continental_shelf_numeric |
maritime_claims_continental_shelf_numeric | float | 0% | 1 | 200.0 |
climate_text |
climate_text | string | 0% | 1 | mostly hot, dry desert; temperate in northwest; arctic in north |
terrain_text |
terrain_text | string | 0% | 1 | divided into three major geographic areas: the northern... |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | K2 (Mt. Godwin-Austen) 8,611 m |
elevation_lowest_point_text |
elevation_lowest_point_text | string | 0% | 1 | Arabian Sea 0 m |
elevation_mean_elevation_text |
elevation_mean_elevation_text | string | 0% | 1 | 900 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 900.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | arable land, extensive natural gas reserves, limited... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 46.7% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 39.3% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 39.3 |
| +20 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name_conventional_long_form_text |
country_name_conventional_long_form_text | string | 0% | 1 | Islamic Republic of Pakistan |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Pakistan |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | Jamhuryat Islami Pakistan |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Pakistan |
country_name_former_text |
country_name_former_text | string | 0% | 1 | West Pakistan |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | the name is said to have been proposed in the early... |
country_name_etymology_numeric |
country_name_etymology_numeric | float | 0% | 1 | 1930.0 |
government_type_text |
government_type_text | string | 0% | 1 | federal parliamentary republic |
capital_name_text |
capital_name_text | string | 0% | 1 | Islamabad |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 33 41 N, 73 03 E |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 33.0 |
capital_time_difference_text |
capital_time_difference_text | string | 0% | 1 | UTC+5 (10 hours ahead of Washington, DC, during Standard Time) |
capital_time_difference_numeric |
capital_time_difference_numeric | float | 0% | 1 | 5.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | the name means "city of Islam" and derives from the... |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 4 provinces, 2 Pakistan-administered areas*, and 1... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 4.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | common law system with Islamic law influence |
constitution_history_text |
constitution_history_text | string | 0% | 1 | several previous; latest endorsed 12 April 1973, passed... |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 12.0 |
constitution_amendment_process_text |
constitution_amendment_process_text | string | 0% | 1 | proposed by the Senate or by the National Assembly;... |
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 | yes |
citizenship_citizenship_by_descent_only_text |
Citizenship by descent only (text) | string | 0% | 1 | at least one parent must be a citizen of Pakistan |
citizenship_dual_citizenship_recognized_text |
citizenship_dual_citizenship_recognized_text | string | 0% | 1 | yes, but limited to select countries |
citizenship_residency_requirement_for_naturalization_text |
citizenship_residency_requirement_for_naturalization_text | string | 0% | 1 | 4 out of the previous 7 years and including the 12... |
citizenship_residency_requirement_for_naturalization_numeric |
citizenship_residency_requirement_for_naturalization_numeric | float | 0% | 1 | 4.0 |
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 | President Asif Ali ZARDARI (since 10 March 2024) |
executive_branch_chief_of_state_numeric |
executive_branch_chief_of_state_numeric | float | 0% | 1 | 10.0 |
| +88 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | The Indus Valley civilization, one of the oldest in the... |
background_numeric |
background_numeric | float | 0% | 1 | 5000.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_languages_text |
Languages (text) | string | 0% | 1 | Punjabi 38.8%, Pashto (alternate name, Pashtu) 18.2%,... |
languages_languages_numeric |
Languages (numeric) | float | 0% | 1 | 38.8 |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | دنیا کا قاموس، ایک لازمی زریہ بنیادی معلومات کا... |
languages_note |
languages_note | string | 0% | 1 | note: data represent population by mother tongue;... |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
refugees_and_internally_displaced_persons_refugees_text |
refugees_and_internally_displaced_persons_refugees_text | string | 0% | 1 | 1,759,332 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 1759332.0 |
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 224,813 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 224813.0 |
refugees_and_internally_displaced_persons_stateless_persons_text |
refugees_and_internally_displaced_persons_stateless_persons_text | string | 0% | 1 | 60 (2024 est.) |
refugees_and_internally_displaced_persons_stateless_persons_numeric |
refugees_and_internally_displaced_persons_stateless_persons_numeric | float | 0% | 1 | 60.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
military_and_security_forces_text |
military_and_security_forces_text | string | 0% | 1 | Pakistan Armed Forces: Pakistan Army (includes National... |
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 | 2.5% of GDP (2024 est.) |
military_expenditures_military_expenditures_2024_numeric |
Military expenditures 2024 (numeric) | float | 0% | 1 | 2.5 |
military_expenditures_military_expenditures_2023_text |
Military expenditures 2023 (text) | string | 0% | 1 | 3% of GDP (2023 est.) |
military_expenditures_military_expenditures_2023_numeric |
Military expenditures 2023 (numeric) | float | 0% | 1 | 3.0 |
military_expenditures_military_expenditures_2022_text |
Military expenditures 2022 (text) | string | 0% | 1 | 4% of GDP (2022 est.) |
military_expenditures_military_expenditures_2022_numeric |
Military expenditures 2022 (numeric) | float | 0% | 1 | 4.0 |
military_expenditures_military_expenditures_2021_text |
Military expenditures 2021 (text) | string | 0% | 1 | 4% of GDP (2021 est.) |
military_expenditures_military_expenditures_2021_numeric |
Military expenditures 2021 (numeric) | float | 0% | 1 | 4.0 |
military_expenditures_military_expenditures_2020_text |
Military expenditures 2020 (text) | string | 0% | 1 | 4% of GDP (2020 est.) |
military_expenditures_military_expenditures_2020_numeric |
Military expenditures 2020 (numeric) | float | 0% | 1 | 4.0 |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | approximately 650,000 active Armed Forces (2025) |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 650000.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the military's inventory is a mix of mostly imported and... |
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 | 16-28 years of age for voluntary military service for... |
military_service_age_and_obligation_numeric |
military_service_age_and_obligation_numeric | float | 0% | 1 | 16.0 |
military_deployments_text |
military_deployments_text | string | 0% | 1 | 1,400 Central African Republic (MINUSCA); 300 MONUSCO;... |
military_deployments_numeric |
military_deployments_numeric | float | 0% | 1 | 1400.0 |
military_note_text |
military_note_text | string | 0% | 1 | the Pakistan military is responsible for external... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 30.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 257047044.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 130727015.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 126320029.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 34.4 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 60.7 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 4.9 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 64.0 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 55.8 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 8.2 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 23.2 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | 1.82 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 25.05 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 5.79 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | -1.1 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 38.0 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 2.1 |
sex_ratio_at_birth_numeric |
Sex ratio at birth | float | SEL | 0% | 1 | 1.05 |
sex_ratio_total_population_numeric |
Sex ratio overall | float | SEL | 0% | 1 | 1.04 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 155.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 50.3 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 70.3 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 3.25 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 1.59 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 1.16 |
hospital_bed_density_numeric |
Hospital beds per 1000 | float | SEL | 0% | 1 | 0.5 |
literacy_total_population_numeric |
Literacy rate percent | float | SEL | 0% | 1 | 58.9 |
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
population_total_text |
population_total_text | string | 0% | 1 | 257,047,044 (2025 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 130,727,015 |
population_female_text |
population_female_text | string | 0% | 1 | 126,320,029 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 34.4% (male 44,330,669/female 42,529,007) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 60.7% (male 78,321,834/female 74,833,003) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 4.9% (2024 est.) (male 5,735,294/female 6,613,764) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 64 (2025 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 55.8 (2025 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 8.2 (2025 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 12.1 (2025 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 12.1 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 23.2 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 22.8 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 22.8 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 23 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 23.0 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | 1.82% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 25.05 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 5.79 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | -1.1 migrant(s)/1,000 population (2025 est.) |
population_distribution_text |
population_distribution_text | string | 0% | 1 | the Indus River and its tributaries attract most of the... |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 38% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 2.1% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 17.236 million Karachi, 13.979 million Lahore, 3.711... |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 17.236 |
sex_ratio_at_birth_text |
sex_ratio_at_birth_text | string | 0% | 1 | 1.05 male(s)/female |
sex_ratio_0_14_years_text |
sex_ratio_0_14_years_text | string | 0% | 1 | 1.04 male(s)/female |
sex_ratio_0_14_years_numeric |
sex_ratio_0_14_years_numeric | float | 0% | 1 | 1.04 |
sex_ratio_15_64_years_text |
sex_ratio_15_64_years_text | string | 0% | 1 | 1.05 male(s)/female |
sex_ratio_15_64_years_numeric |
sex_ratio_15_64_years_numeric | float | 0% | 1 | 1.05 |
| +93 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_religion_muslim_pct_synth |
Muslim | numeric | CCL | 0% | - | 96.4 |
composition_religion_hindu_pct_synth |
Hindu | numeric | CCL | 0% | - | 1.6 |
composition_religion_other_pct_synth |
other | numeric | CCL | 0% | - | - |
composition_ethnicity_primary_label_synth |
Punjabi | string | CCL | 0% | - | Punjabi |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Muslim 96.4%, Hindu 1.6%, Christian 1.4%; less than 1%:... |
religions_numeric |
religions_numeric | float | 0% | 1 | 96.4 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_christian_1_4_scheduled_castes_pct_synth |
Christian 1.4%; : scheduled castes | numeric | 0% | - | 0.5 |
composition_religion_qadiani_ahmadi_pct_synth |
Qadiani/Ahmadi | numeric | 0% | - | - |
composition_religion_sikh_pct_synth |
Sikh | numeric | 0% | - | - |
composition_ethnicity_punjabi_pct_synth |
Punjabi | numeric | 0% | - | 44.7 |
composition_ethnicity_pashtun_pathan_pct_synth |
Pashtun (Pathan) | numeric | 0% | - | 15.4 |
composition_ethnicity_sindhi_pct_synth |
Sindhi | numeric | 0% | - | 14.1 |
composition_ethnicity_saraiki_pct_synth |
Saraiki | numeric | 0% | - | 8.4 |
composition_ethnicity_muhajirs_pct_synth |
Muhajirs | numeric | 0% | - | 7.6 |
composition_ethnicity_baloch_pct_synth |
Baloch | numeric | 0% | - | 3.6 |
composition_ethnicity_other_pct_synth |
other | numeric | 0% | - | 6.3 |
composition_ethnicity_primary_share_pct_synth |
Punjabi | numeric | 0% | - | 44.7 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
space_agency_agencies_text |
space_agency_agencies_text | string | 0% | 1 | Pakistan Space & Upper Atmosphere Research Commission... |
space_agency_agencies_numeric |
space_agency_agencies_numeric | float | 0% | 1 | 1961.0 |
space_launch_site_s_text |
space_launch_site_s_text | string | 0% | 1 | none; missile test sites at Somiani (Balochistan) and... |
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 | space program dates back to the early 1960s, but funding... |
space_program_overview_numeric |
space_program_overview_numeric | float | 0% | 1 | 1960.0 |
key_space_program_milestones_text |
key_space_program_milestones_text | string | 0% | 1 | 1962-1972 - launched about 200 sounding rockets with... |
key_space_program_milestones_numeric |
key_space_program_milestones_numeric | float | 0% | 1 | 1962.0 |
source_section |
source_section | string | 0% | 1 | Space |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
terrorist_group_s_text |
terrorist_group_s_text | string | 0% | 1 | al-Qa’ida; al-Qa’ida in the Indian Subcontinent (AQIS);... |
source_section |
source_section | string | 0% | 1 | Terrorism |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
illicit_drugs_usg_identification_text |
illicit_drugs_usg_identification_text | string | 0% | 1 | major illicit drug-producing and/or drug-transit... |
illicit_drugs_usg_identification_numeric |
illicit_drugs_usg_identification_numeric | float | 0% | 1 | 2025.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| 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 | AP |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 117.0 |
country_code |
Country code | string | SEL | 0% | 1 | PAK |
country_name |
Country name | string | SEL | 0% | 1 | Pakistan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
airports_text |
airports_text | string | 0% | 1 | 117 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 48 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 48.0 |
railways_total_text |
railways_total_text | string | 0% | 1 | 11,881 km (2021) |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 11881.0 |
railways_narrow_gauge_text |
railways_narrow_gauge_text | string | 0% | 1 | 389 km (2021) 1.000-m gauge |
railways_narrow_gauge_numeric |
railways_narrow_gauge_numeric | float | 0% | 1 | 389.0 |
railways_broad_gauge_text |
railways_broad_gauge_text | string | 0% | 1 | 11,492 km (2021) 1.676-m gauge (286 km electrified) |
railways_broad_gauge_numeric |
railways_broad_gauge_numeric | float | 0% | 1 | 11492.0 |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 60 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 60.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | bulk carrier 5, oil tanker 9, other 46 |
merchant_marine_by_type_numeric |
merchant_marine_by_type_numeric | float | 0% | 1 | 5.0 |
ports_total_ports_text |
ports_total_ports_text | string | 0% | 1 | 3 (2024) |
ports_total_ports_numeric |
ports_total_ports_numeric | float | 0% | 1 | 3.0 |
ports_large_text |
ports_large_text | float | 0% | 1 | 0 |
ports_large_numeric |
ports_large_numeric | float | 0% | 1 | 0.0 |
ports_medium_text |
ports_medium_text | float | 0% | 1 | 2 |
ports_medium_numeric |
ports_medium_numeric | float | 0% | 1 | 2.0 |
ports_small_text |
ports_small_text | float | 0% | 1 | 1 |
ports_small_numeric |
ports_small_numeric | float | 0% | 1 | 1.0 |
ports_very_small_text |
ports_very_small_text | float | 0% | 1 | 0 |
ports_very_small_numeric |
ports_very_small_numeric | float | 0% | 1 | 0.0 |
ports_ports_with_oil_terminals_text |
Ports with oil terminals (text) | float | 0% | 1 | 2 |
ports_ports_with_oil_terminals_numeric |
Ports with oil terminals (numeric) | float | 0% | 1 | 2.0 |
ports_key_ports_text |
ports_key_ports_text | string | 0% | 1 | Gwadar, Karachi, Muhamamad Bin Qasim |
source_section |
source_section | string | 0% | 1 | Transportation |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/pk.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | PAK, PAK, PAK, PAK, PAK |
gns_language_code |
gns_language_code | string | CCL | 0% | 10 | eng, rus, urd, fas, zho |
gns_language_name |
gns_language_name | string | CCL | 0% | 10 | English, Russian, Urdu, Persian, Chinese |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 8 | 17646, 734, 502, 193, 17 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 8 | 92.3294, 3.8405, 2.6266, 1.0098, 0.0889 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 8 | 0, 77, 102, 130, 7 |
gns_dominant_script_code |
gns_dominant_script_code | string | CCL | 0% | 3 | , , Arab, , Hans |
gns_dominant_script_name |
gns_dominant_script_name | string | CCL | 0% | 3 | , , Arabic, , Han (Simplified variant) |
gns_script_count |
gns_script_count | integer | CCL | 0% | 3 | 0, 0, 2, 0, 1 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | PAK |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Pakistan |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 10 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 3 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 99.9975 |
gns_non_roman_name_count |
gns_non_roman_name_count | integer | CCL | 0% | 1 | 560 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
gns_name_count |
gns_name_count | integer | 0% | 1 | 322100 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 228135 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 322092 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 8 |
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_populated_places |
gns_name_count_populated_places | integer | 0% | 1 | 214795 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 148990 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 15365 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 12304 |
gns_name_count_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 54366 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 38233 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 21753 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 16653 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 12835 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 9930 |
gns_name_count_vegetation |
gns_name_count_vegetation | integer | 0% | 1 | 1200 |
gns_feature_count_vegetation |
gns_feature_count_vegetation | integer | 0% | 1 | 914 |
gns_name_count_transportation_networks |
gns_name_count_transportation_networks | integer | 0% | 1 | 1216 |
gns_feature_count_transportation_networks |
gns_feature_count_transportation_networks | integer | 0% | 1 | 905 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 570 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 206 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK, PAK, PAK, PAK, PAK |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 8 | Punjabi, Pashtuns, Sindhi, Mohajirs, Baluchis |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 4 | SENIOR PARTNER, JUNIOR PARTNER, JUNIOR PARTNER,... |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 8 | 0.56, 0.15, 0.14, 0.08, 0.03 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 8 | 77005000, 77004000, 77006000, 77003000, 77001000 |
regional_autonomy |
Regional autonomy | string | CCL | 0% | 1 | false, false, false, false, false |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
group_relevance |
group_relevance | string | 0% | 1 | , , , , |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PK, PK, PK, PK, PK |
admin_level |
Admin level | integer | SEL | 0% | 1 | 1, 1, 1, 1, 1 |
iso3 |
Country code | string | SEL | 0% | 1 | PAK, PAK, PAK, PAK, PAK |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
retail |
retail | float | 0% | 7 | 30.35, 36.71, 0.0, 0.0, 5.28 |
grocery |
grocery | float | 0% | 7 | -0.37, 45.26, 0.0, 0.0, 14.47 |
parks |
parks | float | 0% | 8 | 71.24, 34.91, 64.11, 108.01, 25.35 |
transit |
transit | float | 0% | 7 | 31.66, 29.39, 0.0, 0.0, 7.71 |
workplaces |
workplaces | float | 0% | 8 | 0.01, 11.6, 43.79, 40.49, 2.21 |
residential |
residential | float | 0% | 7 | 2.44, 2.75, 0.0, 0.0, 5.58 |
region |
region | string | 0% | 8 | Azad Jammu and Kashmir, Balochistan, Federally... |
observation_count |
observation_count | integer | 0% | 2 | 974, 974, 949, 949, 974 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK, PAK, PAK, PAK, PAK |
society_id |
Society id | string | CCL | 0% | 6 | Ea1, Ea10, Ea13, Ea2, Ea4 |
society_name |
Society name | string | CCL | 0% | 6 | Sindhi, Marri, Punjabi, Yusufzai, Kohistani |
language_glottocode |
Language glottocode | string | CCL | 0% | 6 | sind1272, east2304, west2386, yusu1238, indu1241 |
language_name |
Language name | string | CCL | 0% | 1 | , , , , |
kinship_system |
Kinship system | string | CCL | 0% | 6 | EA001:0; EA002:0; EA003:2; EA004:3; EA005:5, EA001:1;... |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 5 | EA006:1; EA007:7; EA008:7; EA009:2; EA010:8, EA006:1;... |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 6 | EA028:6; EA029:6; EA030:7; EA031:8; EA032:3, EA028:5;... |
political_complexity |
Political complexity | string | CCL | 0% | 5 | EA033:4; EA034:4; EA035:NA, EA033:3; EA034:4; EA035:NA,... |
religion_importance |
Religion importance | string | CCL | 0% | 3 | EA034:4; EA112:NA, EA034:4; EA112:NA, EA034:4; EA112:NA,... |
residence_pattern |
Residence pattern | string | CCL | 0% | 1 | EA011:1; EA012:8; EA013:9, EA011:1; EA012:8; EA013:9,... |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Pakistan, Pakistan, Pakistan, Pakistan, Pakistan |
dataset |
dataset | string | 0% | 1 | EA, EA, EA, EA, EA |
region |
region | string | 0% | 1 | , , , , |
latitude |
latitude | float | 0% | 4 | 25.0, 30.0, 32.0, 35.0, 35.0 |
longitude |
longitude | float | 0% | 4 | 68.0, 69.0, 73.0, 72.0, 73.0 |
assignment_method |
assignment_method | string | 0% | 1 | point_in_polygon, point_in_polygon, point_in_polygon,... |
assignment_confidence |
assignment_confidence | string | 0% | 1 | approximate, approximate, approximate, approximate, approximate |
| 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 | - |
| 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 | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
iso3 |
iso3 | string | 0% | 1 | PAK |
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 | 122 |
oc_anti_money_laundering_2023 |
oc_anti_money_laundering_2023 | integer | 0% | 1 | 4 |
oc_anti_money_laundering_2021 |
oc_anti_money_laundering_2021 | integer | 0% | 1 | 4 |
oc_arms_trafficking_rank |
oc_arms_trafficking_rank | integer | 0% | 1 | 19 |
oc_arms_trafficking_2023 |
oc_arms_trafficking_2023 | float | 0% | 1 | 8.5 |
oc_arms_trafficking_2021 |
oc_arms_trafficking_2021 | integer | 0% | 1 | 8 |
oc_cannabis_trade_rank |
oc_cannabis_trade_rank | integer | 0% | 1 | 13 |
oc_cannabis_trade_2023 |
oc_cannabis_trade_2023 | integer | 0% | 1 | 7 |
oc_cannabis_trade_2021 |
oc_cannabis_trade_2021 | integer | 0% | 1 | 7 |
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 | 55 |
oc_criminal_actors_2023 |
oc_criminal_actors_2023 | float | 0% | 1 | 5.8 |
oc_criminal_actors_2021 |
oc_criminal_actors_2021 | float | 0% | 1 | 6.25 |
oc_criminal_markets_rank |
oc_criminal_markets_rank | integer | 0% | 1 | 26 |
oc_criminal_markets_2023 |
oc_criminal_markets_2023 | float | 0% | 1 | 6.27 |
oc_criminal_markets_2021 |
oc_criminal_markets_2021 | float | 0% | 1 | 6.3 |
oc_criminal_networks_rank |
oc_criminal_networks_rank | integer | 0% | 1 | 34 |
oc_criminal_networks_2023 |
oc_criminal_networks_2023 | integer | 0% | 1 | 7 |
oc_criminal_networks_2021 |
oc_criminal_networks_2021 | float | 0% | 1 | 7.5 |
oc_criminality_rank |
oc_criminality_rank | integer | 0% | 1 | 45 |
oc_criminality_2023 |
oc_criminality_2023 | float | 0% | 1 | 6.03 |
oc_criminality_2021 |
oc_criminality_2021 | float | 0% | 1 | 6.28 |
oc_cyber_dependent_crimes_rank |
oc_cyber_dependent_crimes_rank | integer | 0% | 1 | 79 |
| +74 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PAK |
| 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 |
Which languages name the landscape here, and in which writing systems. A language's toponymic footprint and its speaker population are different measures and often diverge. Counts include variant and foreign-language renderings of the same place, so a language can rank high because outside sources record names in it rather than because it is spoken locally — and a widely spoken language can be almost absent where official naming is in another language.
| Language | Place names | Share | Script |
|---|---|---|---|
| English (eng) | 17,646 | 92.3% | — |
| Russian (rus) | 734 | 3.8% | — |
| Urdu (urd) | 502 | 2.6% | Arabic +1 |
| Persian (fas) | 193 | 1.0% | — |
| Chinese (zho) | 17 | 0.1% | Han (Simplified variant) |
| Pushto (pus) | 13 | 0.1% | — |
228,135 distinct features ·
10 languages ·
3 scripts ·
560 names in non-Roman script ·
8 conventional English names
Source: NGA GEOnet Names Server
(public domain) · rebuilt Wed, 05 Aug 2026.
Names follow the US/BGN convention.
The data providers this country's datasets are sourced from — each links out to the provider.
Pick datasets and admin level(s). You'll get a .zip with one CSV per dataset, each filtered to the levels you choose.