ⓘ 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 | BTN, BTN, BTN, BTN, BTN |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 21 | Total, Bumthang, Chukha, Dagana, Gasa |
human_development_index |
Human development index | float | SEL | 0% | 77 | 0.448, 0.451, 0.481, 0.402, 0.36 |
health_index |
Health index | float | SEL | 0% | 73 | 0.551, 0.54, 0.511, 0.576, 0.464 |
education_index |
Education index | float | SEL | 0% | 79 | 0.307, 0.31, 0.389, 0.247, 0.222 |
income_index |
Income index | float | SEL | 0% | 76 | 0.531, 0.548, 0.559, 0.455, 0.452 |
life_expectancy |
Life expectancy | float | SEL | 0% | 91 | 55.81, 55.09, 53.25, 57.43, 50.15 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 100 | 4.609, 4.569, 6.884, 3.013, 3.233 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 5 | 1990, 1990, 1990, 1990, 1990 |
level |
level | string | 0% | 2 | national, subnational, subnational, subnational, subnational |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BT, BT, BT, BT, BT |
population_count |
Population count | float | SEL | 2% | 65 | 224084.0, 230602.0, 237636.0, 245156.0, 252987.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 36.367, 36.654, 36.992, 37.37, 37.796 |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 18% | 54 | 200.345229822469, 207.666560128876, 212.375150813633,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 94% | 4 | 52.810001373291, 55.3199996948242, 66.5599975585938,... |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 15% | 56 | 273.9, 267.4, 261.6, 255.2, 248.9 |
poverty_headcount_pct |
Poverty headcount percent | float | SEL | 92% | 5 | 31.7, 23.2, 12.0, 8.2, 12.4 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Bhutan, Bhutan, Bhutan, Bhutan, Bhutan |
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 | BT, BT, BT, BT, BT |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 36.367, 36.654, 36.992, 37.37, 37.796 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 47% | 35 | 43.2, 42.4, 41.5, 40.5, 39.5 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 15% | 56 | 273.9, 267.4, 261.6, 255.2, 248.9 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 39 | 969.0, 911.0, 857.0, 798.0, 747.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 64 | 6.704, 6.698, 6.692, 6.687, 6.682 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 64 | 48.763, 48.697, 48.599, 48.597, 48.559 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 64 | 26.952, 26.662, 26.305, 25.953, 25.559 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 70% | 19 | 0.125, 0.102, 0.333, 0.17, 0.16 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 58% | 20 | 1.70589995384216, 0.8467000127, 1.6147999763, 1.6000000238, 1.71 |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 32% | 24 | 6.0, 13.0, 15.0, 16.0, 28.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 4.13867903, 4.60037947, 3.95161104, 3.83481455, 4.26397753 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Bhutan, Bhutan, Bhutan, Bhutan, Bhutan |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
| 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 |
|---|---|---|---|---|---|---|
glottocode |
Glottocode | string | CCL | 0% | 33 | adap1234, assa1263, bhut1234, bori1243, brok1248 |
name |
Name | string | CCL | 0% | 33 | Adap, Assamese, Bhutanese Sign Language, Bori-Karko, Brokpake |
iso639_3 |
Iso639 3 | string | CCL | 6% | 31 | adp, asm, adi, sgt, bro |
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 | book1242, indo1319, sign1238, sino1245, sino1245 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 0% | 21 | book1242, assa1262, deaf1237, east2361, sout3217 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 8 | ['BT'], ['BD', 'BT', 'IN'], ['BT'], ['BT', 'CN', 'IN'],... |
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% | 9 | 0, 5, 0, 5, 0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 0% | 33 | 27.141, 26.0876, 27.48405, 27.62812, 27.3438 |
longitude |
longitude | float | 0% | 33 | 90.3369, 91.2932, 89.33058, 94.3538, 91.9972 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BTN |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | Bhutan |
admin_code |
Admin code | string | SEL | 0% | 1 | 95260433B17918647431984 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 40330.6562 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 912301 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 22.62 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BTN, BTN, BTN, BTN, BTN |
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% | 20 | Thimpu, Chukha, Samtse, Sarpang, Paro |
admin_code |
Admin code | string | SEL | 0% | 20 | 66845921B82067974050695, 66845921B66499017593499,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 20 | 1740.7634, 1782.3791, 1421.8671, 1593.0118, 1678.5201 |
pop_2024 |
Population count | integer | SEL | 0% | 20 | 180882, 114479, 85789, 66868, 59258 |
pop_density_2024 |
Population density | float | SEL | 0% | 20 | 103.91, 64.23, 60.34, 41.98, 35.3 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BTN |
admin_level |
Admin level | string | SEL | 0% | 1 | locality |
admin_name |
Admin name | string | SEL | 0% | 1 | Phuntsholing |
admin_code |
Admin code | integer | SEL | 0% | 1 | 170 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 2.988 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 19364 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 6480.59 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 1 | 76648 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 1 | 0.253 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 1 | BT |
region_name |
Region name | string | SEL | 0% | 1 | Bhutan |
F_TL |
Female population | integer | SEL | 0% | 1 | 372812 |
M_TL |
Male population | integer | SEL | 0% | 1 | 404410 |
T_TL |
Total population | integer | SEL | 0% | 1 | 777224 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_0 |
year |
Reference year | integer | 0% | 1 | 2024 |
year |
year | integer | 0% | 1 | 2024 |
F_00_04 |
Female population age 0-4 | integer | 0% | 1 | 29320 |
F_05_09 |
Female population age 5-9 | integer | 0% | 1 | 28068 |
F_10_14 |
Female population age 10-14 | integer | 0% | 1 | 29603 |
F_15_19 |
Female population age 15-19 | integer | 0% | 1 | 33088 |
F_20_24 |
Female population age 20-24 | integer | 0% | 1 | 33782 |
F_25_29 |
Female population age 25-29 | integer | 0% | 1 | 33358 |
F_30_34 |
Female population age 30-34 | integer | 0% | 1 | 35875 |
F_35_39 |
Female population age 35-39 | integer | 0% | 1 | 32443 |
F_40_44 |
Female population age 40-44 | integer | 0% | 1 | 26967 |
F_45_49 |
Female population age 45-49 | integer | 0% | 1 | 21060 |
F_50_54 |
Female population age 50-54 | integer | 0% | 1 | 16784 |
F_55_59 |
Female population age 55-59 | integer | 0% | 1 | 14156 |
F_60_64 |
Female population age 60-64 | integer | 0% | 1 | 11412 |
F_65_69 |
Female population age 65-69 | integer | 0% | 1 | 9857 |
F_70_74 |
Female population age 70-74 | integer | 0% | 1 | 7064 |
F_75Plus |
F_75Plus | integer | 0% | 1 | 9980 |
M_00_04 |
Male population age 0-4 | integer | 0% | 1 | 30223 |
M_05_09 |
Male population age 5-9 | integer | 0% | 1 | 28709 |
M_10_14 |
Male population age 10-14 | integer | 0% | 1 | 30883 |
M_15_19 |
Male population age 15-19 | integer | 0% | 1 | 33674 |
M_20_24 |
Male population age 20-24 | integer | 0% | 1 | 33884 |
M_25_29 |
Male population age 25-29 | integer | 0% | 1 | 37838 |
M_30_34 |
Male population age 30-34 | integer | 0% | 1 | 42550 |
M_35_39 |
Male population age 35-39 | integer | 0% | 1 | 37511 |
M_40_44 |
Male population age 40-44 | integer | 0% | 1 | 30779 |
M_45_49 |
Male population age 45-49 | integer | 0% | 1 | 24103 |
M_50_54 |
Male population age 50-54 | integer | 0% | 1 | 19009 |
| +21 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 20 | BT001, BT002, BT003, BT004, BT005 |
region_name |
Region name | string | SEL | 0% | 20 | Bumthang, Chhukha, Dagana, Gasa, Haa |
F_TL |
Female population | integer | SEL | 0% | 20 | 8993, 34107, 12430, 2071, 6307 |
M_TL |
Male population | integer | SEL | 0% | 20 | 9506, 36098, 13637, 2365, 7578 |
T_TL |
Total population | integer | SEL | 0% | 20 | 18499, 70205, 26067, 4435, 13884 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
year |
Reference year | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
year |
year | integer | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
F_00_04 |
Female population age 0-4 | integer | 0% | 20 | 751, 2553, 920, 165, 503 |
F_05_09 |
Female population age 5-9 | integer | 0% | 20 | 715, 2396, 946, 160, 473 |
F_10_14 |
Female population age 10-14 | integer | 0% | 20 | 725, 2659, 1140, 196, 582 |
F_15_19 |
Female population age 15-19 | integer | 0% | 19 | 741, 2995, 1093, 199, 641 |
F_20_24 |
Female population age 20-24 | integer | 0% | 20 | 710, 3811, 803, 147, 459 |
F_25_29 |
Female population age 25-29 | integer | 0% | 20 | 753, 3291, 898, 155, 514 |
F_30_34 |
Female population age 30-34 | integer | 0% | 20 | 858, 3516, 1124, 184, 604 |
F_35_39 |
Female population age 35-39 | integer | 0% | 20 | 790, 3237, 1066, 180, 565 |
F_40_44 |
Female population age 40-44 | integer | 0% | 20 | 599, 2551, 972, 147, 420 |
F_45_49 |
Female population age 45-49 | integer | 0% | 19 | 486, 1958, 807, 106, 348 |
F_50_54 |
Female population age 50-54 | integer | 0% | 20 | 407, 1468, 672, 91, 268 |
F_55_59 |
Female population age 55-59 | integer | 0% | 20 | 337, 1035, 583, 76, 253 |
F_60_64 |
Female population age 60-64 | integer | 0% | 19 | 293, 823, 467, 84, 204 |
F_65_69 |
Female population age 65-69 | integer | 0% | 19 | 264, 718, 389, 59, 187 |
F_70_74 |
Female population age 70-74 | integer | 0% | 20 | 226, 469, 244, 52, 121 |
F_75Plus |
F_75Plus | integer | 0% | 20 | 339, 627, 307, 72, 163 |
M_00_04 |
Male population age 0-4 | integer | 0% | 20 | 781, 2607, 1009, 175, 555 |
M_05_09 |
Male population age 5-9 | integer | 0% | 20 | 759, 2447, 1033, 173, 486 |
M_10_14 |
Male population age 10-14 | integer | 0% | 20 | 775, 2682, 1313, 202, 596 |
M_15_19 |
Male population age 15-19 | integer | 0% | 19 | 782, 2981, 1267, 234, 774 |
M_20_24 |
Male population age 20-24 | integer | 0% | 20 | 720, 3362, 863, 196, 554 |
M_25_29 |
Male population age 25-29 | integer | 0% | 20 | 882, 3367, 969, 220, 643 |
M_30_34 |
Male population age 30-34 | integer | 0% | 20 | 1010, 3820, 1246, 254, 922 |
M_35_39 |
Male population age 35-39 | integer | 0% | 20 | 871, 3591, 1132, 234, 806 |
M_40_44 |
Male population age 40-44 | integer | 0% | 20 | 707, 2866, 1009, 160, 590 |
M_45_49 |
Male population age 45-49 | integer | 0% | 20 | 500, 2308, 852, 131, 465 |
M_50_54 |
Male population age 50-54 | integer | 0% | 20 | 384, 1921, 660, 106, 304 |
| +21 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
telephones_fixed_lines_subscriptions_per_100_inhabitants_numeric |
Fixed line subscriptions per 100 | float | SEL | 0% | 1 | 0.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 100.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .bt |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 88.0 |
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 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
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 | 0 (2024 est.) no service |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 0.0 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 0 (2024 est.) no service |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 790,000 (2024 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 790000.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 100 (2024 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | state-owned TV station established in 1999; cable TV... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 1999.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 88% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 10,000 (2023 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 10000.0 |
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/bt.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 3.019 |
population_below_poverty_line_numeric |
Poverty headcount percent | float | SEL | 0% | 1 | 12.4 |
country_code |
Country code | string | SEL | 0% | 1 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
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 | hydropower investments spurring economic development;... |
economic_overview_numeric |
economic_overview_numeric | float | 0% | 1 | -19.0 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $11.517 billion (2023 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_numeric |
Real gdp purchasing power parity 2023 (numeric) | float | 0% | 1 | 11.517 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $10.981 billion (2022 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_numeric |
Real gdp purchasing power parity 2022 (numeric) | float | 0% | 1 | 10.981 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2021_text |
Real gdp purchasing power parity 2021 (text) | string | 0% | 1 | $10.437 billion (2021 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2021_numeric |
Real gdp purchasing power parity 2021 (numeric) | float | 0% | 1 | 10.437 |
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_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 4.9% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 4.9 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 5.2% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 5.2 |
real_gdp_growth_rate_real_gdp_growth_rate_2021_text |
Real gdp growth rate 2021 (text) | string | 0% | 1 | 4.4% (2021 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2021_numeric |
Real gdp growth rate 2021 (numeric) | float | 0% | 1 | 4.4 |
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_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $14,600 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 14600.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $14,100 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 14100.0 |
real_gdp_per_capita_real_gdp_per_capita_2021_text |
Real gdp per capita 2021 (text) | string | 0% | 1 | $13,500 (2021 est.) |
real_gdp_per_capita_real_gdp_per_capita_2021_numeric |
Real gdp per capita 2021 (numeric) | float | 0% | 1 | 13500.0 |
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 | $3.019 billion (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 2.8% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 2.8 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text |
Inflation rate consumer prices 2023 (text) | string | 0% | 1 | 4.2% (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric |
Inflation rate consumer prices 2023 (numeric) | float | 0% | 1 | 4.2 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 5.6% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 5.6 |
| +120 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
electricity_access_electrification_total_population_numeric |
Electricity access percent | float | SEL | 0% | 1 | 100.0 |
country_code |
Country code | string | SEL | 0% | 1 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
electricity_access_electrification_total_population_text |
electricity_access_electrification_total_population_text | string | 0% | 1 | 100% (2022 est.) |
electricity_installed_generating_capacity_text |
electricity_installed_generating_capacity_text | string | 0% | 1 | 2.344 million kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 2.344 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 11.914 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 11.914 |
electricity_exports_text |
electricity_exports_text | string | 0% | 1 | 6 billion kWh (2020 est.) |
electricity_exports_numeric |
electricity_exports_numeric | float | 0% | 1 | 6.0 |
electricity_imports_text |
electricity_imports_text | string | 0% | 1 | 834.7 million kWh (2023 est.) |
electricity_imports_numeric |
electricity_imports_numeric | float | 0% | 1 | 834.7 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 86.681 million kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 86.681 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 100% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 100.0 |
coal_production_text |
coal_production_text | string | 0% | 1 | 4,000 metric tons (2023 est.) |
coal_production_numeric |
coal_production_numeric | float | 0% | 1 | 4000.0 |
coal_consumption_text |
coal_consumption_text | string | 0% | 1 | 105,000 metric tons (2023 est.) |
coal_consumption_numeric |
coal_consumption_numeric | float | 0% | 1 | 105000.0 |
coal_exports_text |
coal_exports_text | string | 0% | 1 | 54 metric tons (2023 est.) |
coal_exports_numeric |
coal_exports_numeric | float | 0% | 1 | 54.0 |
coal_imports_text |
coal_imports_text | string | 0% | 1 | 122,000 metric tons (2023 est.) |
coal_imports_numeric |
coal_imports_numeric | float | 0% | 1 | 122000.0 |
petroleum_refined_petroleum_consumption_text |
petroleum_refined_petroleum_consumption_text | string | 0% | 1 | 4,000 bbl/day (2023 est.) |
petroleum_refined_petroleum_consumption_numeric |
petroleum_refined_petroleum_consumption_numeric | float | 0% | 1 | 4000.0 |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_text |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_text | string | 0% | 1 | 64.082 million Btu/person (2023 est.) |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_numeric |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_numeric | float | 0% | 1 | 64.082 |
source_section |
source_section | string | 0% | 1 | Energy |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/bt.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 13.8 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 70.6 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 44.4 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 2.52 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 111300.0 |
country_code |
Country code | string | SEL | 0% | 1 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
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 | soil erosion; limited access to potable water; wildlife... |
international_environmental_agreements_party_to_text |
international_environmental_agreements_party_to_text | string | 0% | 1 | Biodiversity, Climate Change, Climate Change-Kyoto... |
international_environmental_agreements_signed_but_not_ratified_text |
international_environmental_agreements_signed_but_not_ratified_text | string | 0% | 1 | Law of the Sea |
climate_text |
climate_text | string | 0% | 1 | varies; tropical in southern plains; cool winters and... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 13.8% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 2.6% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 2.6 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.4% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.4 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 10.8% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 10.8 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 70.6% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 15.6% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 15.6 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 44.4% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 2.52% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 733,000 metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 733000.0 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 241,000 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 | 241000.0 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 492,000 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 | 492000.0 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 26.4 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 26.4 |
waste_and_recycling_municipal_solid_waste_generated_annually_text |
waste_and_recycling_municipal_solid_waste_generated_annually_text | string | 0% | 1 | 111,300 tons (2024 est.) |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_text |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_text | string | 0% | 1 | 1.7% (2022 est.) |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_numeric |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_numeric | float | 0% | 1 | 1.7 |
total_water_withdrawal_municipal_text |
total_water_withdrawal_municipal_text | string | 0% | 1 | 17 million cubic meters (2022 est.) |
total_water_withdrawal_municipal_numeric |
total_water_withdrawal_municipal_numeric | float | 0% | 1 | 17.0 |
total_water_withdrawal_industrial_text |
total_water_withdrawal_industrial_text | string | 0% | 1 | 3 million cubic meters (2022 est.) |
| +7 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 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
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 | Bhutanese (singular and plural) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Bhutanese |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | Ngalop (also known as Bhote) 50%, ethnic Nepali 35%... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 50.0 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/bt.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 38394.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 38394.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 0.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 1136.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 0.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 7570.0 |
elevation_lowest_point_numeric |
Elevation min m | float | SEL | 0% | 1 | 97.0 |
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 13.8 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 70.6 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 320.0 |
country_code |
Country code | string | SEL | 0% | 1 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
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, between China and India |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 27 30 N, 90 30 E |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 27.0 |
map_references_text |
map_references_text | string | 0% | 1 | Asia |
area_total_text |
area_total_text | string | 0% | 1 | 38,394 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 38,394 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 0 sq km |
area_comparative_text |
area_comparative_text | string | 0% | 1 | slightly larger than Maryland; about one-half the size of Indiana |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 1,136 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | China 477 km; India 659 km |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 477.0 |
coastline_text |
coastline_text | string | 0% | 1 | 0 km (landlocked) |
maritime_claims_text |
maritime_claims_text | string | 0% | 1 | none (landlocked) |
climate_text |
climate_text | string | 0% | 1 | varies; tropical in southern plains; cool winters and... |
terrain_text |
terrain_text | string | 0% | 1 | mostly mountainous with some fertile valleys and savanna |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Gangkar Puensum 7,570 m |
elevation_lowest_point_text |
elevation_lowest_point_text | string | 0% | 1 | Drangeme Chhu 97 m |
elevation_mean_elevation_text |
elevation_mean_elevation_text | string | 0% | 1 | 2,220 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 2220.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | timber, hydropower, gypsum, calcium carbonate |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 13.8% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 2.6% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 2.6 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.4% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.4 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 10.8% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 10.8 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 70.6% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 15.6% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 15.6 |
| +5 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 | BTN |
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 | Kingdom of Bhutan |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Bhutan |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | Druk Gyalkhap |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Druk Yul |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | name may derive from the Sanskrit words bhoṭa, the name... |
government_type_text |
government_type_text | string | 0% | 1 | constitutional monarchy |
capital_name_text |
capital_name_text | string | 0% | 1 | Thimphu |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 27 28 N, 89 38 E |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 27.0 |
capital_time_difference_text |
capital_time_difference_text | string | 0% | 1 | UTC+6 (11 hours ahead of Washington, DC, during Standard Time) |
capital_time_difference_numeric |
capital_time_difference_numeric | float | 0% | 1 | 6.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | the origins of the name are unclear; the traditional... |
capital_etymology_numeric |
capital_etymology_numeric | float | 0% | 1 | 14.0 |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 20 districts (dzongkhag, singular and plural); Bumthang,... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 20.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | civil law based on Buddhist religious law |
constitution_history_text |
constitution_history_text | string | 0% | 1 | previous governing documents were various royal decrees;... |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 2001.0 |
constitution_amendment_process_text |
constitution_amendment_process_text | string | 0% | 1 | proposed as a motion by simple majority vote in a joint... |
international_law_organization_participation_text |
international_law_organization_participation_text | string | 0% | 1 | has not submitted an ICJ jurisdiction declaration;... |
citizenship_citizenship_by_birth_text |
Citizenship by birth (text) | string | 0% | 1 | no |
citizenship_citizenship_by_descent_only_text |
Citizenship by descent only (text) | string | 0% | 1 | the father must be a citizen of Bhutan |
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 | 10 years |
citizenship_residency_requirement_for_naturalization_numeric |
citizenship_residency_requirement_for_naturalization_numeric | float | 0% | 1 | 10.0 |
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 | King Jigme Khesar Namgyel WANGCHUCK (since 14 December 2006) |
executive_branch_chief_of_state_numeric |
executive_branch_chief_of_state_numeric | float | 0% | 1 | 14.0 |
executive_branch_head_of_government_text |
executive_branch_head_of_government_text | string | 0% | 1 | Prime Minister Tshering TOBGAY (since 28 January 2024) |
| +62 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 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | After Britain’s victory in the 1865 Duar War, Britain... |
background_numeric |
background_numeric | float | 0% | 1 | 1865.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/bt.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_text |
languages_text | string | 0% | 1 | Sharchopkha 28%, Dzongkha (official) 24%, Lhotshamkha... |
languages_numeric |
languages_numeric | float | 0% | 1 | 28.0 |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/bt.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 138 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 138.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/bt.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
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 | Royal Bhutan Army (RBA; includes Royal Bodyguard of... |
military_and_security_forces_numeric |
military_and_security_forces_numeric | float | 0% | 1 | 2025.0 |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | estimated 7-8,000 active Royal Bhutan Army (2025) |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 7.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the Royal Bhutan Army is lightly armed; it has a small... |
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 years of age for voluntary military service for men... |
military_service_age_and_obligation_numeric |
military_service_age_and_obligation_numeric | float | 0% | 1 | 18.0 |
military_deployments_text |
military_deployments_text | string | 0% | 1 | 180 Central African Republic (MINUSCA) (2025) |
military_deployments_numeric |
military_deployments_numeric | float | 0% | 1 | 180.0 |
military_note_text |
military_note_text | string | 0% | 1 | the Army is responsible for external threats but also... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 2007.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/bt.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 892877.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 461679.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 431198.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 23.1 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 70.2 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 6.7 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 42.1 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 32.4 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 9.7 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 31.2 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | 0.93 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 15.05 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 5.75 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | 0.0 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 44.4 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 2.52 |
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 | 1.07 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 47.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 23.0 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 73.7 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 1.75 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 0.85 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 0.55 |
hospital_bed_density_numeric |
Hospital beds per 1000 | float | SEL | 0% | 1 | 2.2 |
literacy_total_population_numeric |
Literacy rate percent | float | SEL | 0% | 1 | 64.9 |
country_code |
Country code | string | SEL | 0% | 1 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
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 | 892,877 (2025 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 461,679 |
population_female_text |
population_female_text | string | 0% | 1 | 431,198 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 23.1% (male 104,771/female 99,981) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 70.2% (male 322,497/female 298,324) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 6.7% (2024 est.) (male 30,397/female 28,576) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 42.1 (2025 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 32.4 (2025 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 9.7 (2025 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 10.3 (2025 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 10.3 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 31.2 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 31.1 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 31.1 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 30.3 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 30.3 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | 0.93% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 15.05 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 5.75 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | 0 migrant(s)/1,000 population (2025 est.) |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 44.4% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 2.52% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 203,000 THIMPHU (capital) (2018) |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 203000.0 |
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 | 1.05 male(s)/female |
sex_ratio_0_14_years_numeric |
sex_ratio_0_14_years_numeric | float | 0% | 1 | 1.05 |
sex_ratio_15_64_years_text |
sex_ratio_15_64_years_text | string | 0% | 1 | 1.08 male(s)/female |
sex_ratio_15_64_years_numeric |
sex_ratio_15_64_years_numeric | float | 0% | 1 | 1.08 |
sex_ratio_65_years_and_over_text |
sex_ratio_65_years_and_over_text | string | 0% | 1 | 1.06 male(s)/female |
| +84 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 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_religion_other_pct_synth |
other | numeric | CCL | 0% | - | 2.6 |
composition_ethnicity_primary_label_synth |
Ngalop (also known as Bhote) | string | CCL | 0% | - | Ngalop (also known as Bhote) |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Lamaistic Buddhist 75.3%, Indian- and Nepali-influenced... |
religions_numeric |
religions_numeric | float | 0% | 1 | 75.3 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/bt.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_lamaistic_buddhist_pct_synth |
Lamaistic Buddhist | numeric | 0% | - | 75.3 |
composition_religion_indian_and_nepali_influenced_hinduism_pct_synth |
Indian- and Nepali-influenced Hinduism | numeric | 0% | - | 22.1 |
composition_ethnicity_ngalop_also_known_as_bhote_pct_synth |
Ngalop (also known as Bhote) | numeric | 0% | - | 50.0 |
composition_ethnicity_ethnic_nepali_pct_synth |
ethnic Nepali | numeric | 0% | - | 35.0 |
composition_ethnicity_indigenous_or_migrant_tribes_pct_synth |
indigenous or migrant tribes | numeric | 0% | - | 15.0 |
composition_ethnicity_primary_share_pct_synth |
Ngalop (also known as Bhote) | numeric | 0% | - | 50.0 |
| 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 | A5 |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 4.0 |
country_code |
Country code | string | SEL | 0% | 1 | BTN |
country_name |
Country name | string | SEL | 0% | 1 | Bhutan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
civil_aircraft_registration_country_code_prefix_numeric |
civil_aircraft_registration_country_code_prefix_numeric | float | 0% | 1 | 5.0 |
airports_text |
airports_text | string | 0% | 1 | 4 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 8 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 8.0 |
source_section |
source_section | string | 0% | 1 | Transportation |
source_profile_path |
source_profile_path | string | 0% | 1 | south-asia/bt.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | BTN, BTN, BTN, BTN |
gns_language_code |
gns_language_code | string | CCL | 0% | 4 | zho, eng, nep, dzo |
gns_language_name |
gns_language_name | string | CCL | 0% | 4 | Chinese, English, Nepali, Dzongkha |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 2 | 2, 2, 2, 1 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 2 | 28.5714, 28.5714, 28.5714, 14.2857 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 2 | 1, 0, 0, 0 |
gns_dominant_script_code |
gns_dominant_script_code | string | CCL | 0% | 1 | , , , |
gns_dominant_script_name |
gns_dominant_script_name | string | CCL | 0% | 1 | , , , |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 0, 0, 0, 0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | BTN |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Bhutan |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 4 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 0 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 100.0 |
gns_non_roman_name_count |
gns_non_roman_name_count | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
gns_name_count |
gns_name_count | integer | 0% | 1 | 624 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 340 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 624 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 0 |
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 | 330 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 226 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 118 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 49 |
gns_name_count_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 79 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 26 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 21 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 16 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 72 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 22 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 4 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 1 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BTN, BTN, BTN |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 3 | Sharchops, Ngalops (Drupka), Lhotsampa (Hindu Nepalese) |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 3 | POWERLESS, MONOPOLY, DISCRIMINATED |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 2 | 0.4, 0.2, 0.2 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 3 | 76001020, 76001010, 76002000 |
regional_autonomy |
Regional autonomy | string | CCL | 0% | 2 | false, , false |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 1 | 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 | BTN |
society_id |
Society id | string | CCL | 0% | 1 | Ee7 |
society_name |
Society name | string | CCL | 0% | 1 | Kachari |
language_glottocode |
Language glottocode | string | CCL | 0% | 1 | kach1279 |
language_name |
Language name | string | CCL | 0% | 1 | |
kinship_system |
Kinship system | string | CCL | 0% | 1 | EA001:0; EA002:1; EA003:1; EA004:1; EA005:7 |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 1 | EA006:1; EA007:8; EA008:7; EA009:2; EA010:8 |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 1 | EA028:NA; EA029:NA; EA030:NA; EA031:NA; EA032:NA |
political_complexity |
Political complexity | string | CCL | 0% | 1 | EA033:NA; EA034:NA; EA035:NA |
religion_importance |
Religion importance | string | CCL | 0% | 1 | EA034:NA; EA112:NA |
residence_pattern |
Residence pattern | string | CCL | 0% | 1 | EA011:1; EA012:8; EA013:2 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Bhutan |
dataset |
dataset | string | 0% | 1 | EA |
region |
region | string | 0% | 1 | |
latitude |
latitude | float | 0% | 1 | 27.0 |
longitude |
longitude | float | 0% | 1 | 90.0 |
assignment_method |
assignment_method | string | 0% | 1 | point_in_polygon |
assignment_confidence |
assignment_confidence | string | 0% | 1 | approximate |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 1 | Phuntsholing |
country_code |
Country code | string | SEL | 0% | 1 | BTN |
population |
Population count | integer | SEL | 0% | 1 | 76648 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 1 | 170 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Bhutan |
population_year |
population_year | integer | 0% | 1 | 2025 |
latitude |
latitude | string | 100% | - | - |
longitude |
longitude | string | 100% | - | - |
region |
region | string | 100% | - | - |
| 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 | BTN |
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 | 98 |
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 | 161 |
oc_arms_trafficking_2023 |
oc_arms_trafficking_2023 | float | 0% | 1 | 2.5 |
oc_arms_trafficking_2021 |
oc_arms_trafficking_2021 | integer | 0% | 1 | 2 |
oc_cannabis_trade_rank |
oc_cannabis_trade_rank | integer | 0% | 1 | 114 |
oc_cannabis_trade_2023 |
oc_cannabis_trade_2023 | integer | 0% | 1 | 5 |
oc_cannabis_trade_2021 |
oc_cannabis_trade_2021 | integer | 0% | 1 | 4 |
oc_cocaine_trade_rank |
oc_cocaine_trade_rank | integer | 0% | 1 | 178 |
oc_cocaine_trade_2023 |
oc_cocaine_trade_2023 | float | 0% | 1 | 1.5 |
oc_cocaine_trade_2021 |
oc_cocaine_trade_2021 | float | 0% | 1 | 1.5 |
oc_criminal_actors_rank |
oc_criminal_actors_rank | integer | 0% | 1 | 176 |
oc_criminal_actors_2023 |
oc_criminal_actors_2023 | float | 0% | 1 | 3.9 |
oc_criminal_actors_2021 |
oc_criminal_actors_2021 | float | 0% | 1 | 3.63 |
oc_criminal_markets_rank |
oc_criminal_markets_rank | integer | 0% | 1 | 150 |
oc_criminal_markets_2023 |
oc_criminal_markets_2023 | float | 0% | 1 | 3.9 |
oc_criminal_markets_2021 |
oc_criminal_markets_2021 | float | 0% | 1 | 3.75 |
oc_criminal_networks_rank |
oc_criminal_networks_rank | integer | 0% | 1 | 143 |
oc_criminal_networks_2023 |
oc_criminal_networks_2023 | float | 0% | 1 | 4.5 |
oc_criminal_networks_2021 |
oc_criminal_networks_2021 | float | 0% | 1 | 3.5 |
oc_criminality_rank |
oc_criminality_rank | integer | 0% | 1 | 166 |
oc_criminality_2023 |
oc_criminality_2023 | float | 0% | 1 | 3.9 |
oc_criminality_2021 |
oc_criminality_2021 | float | 0% | 1 | 3.69 |
oc_cyber_dependent_crimes_rank |
oc_cyber_dependent_crimes_rank | integer | 0% | 1 | 134 |
| +74 more pending fields — download the CSV/Parquet to see them all. | |||||
Which languages name the landscape here, and in which writing systems. A language's toponymic footprint and its speaker population are different measures and often diverge. Counts include variant and foreign-language renderings of the same place, so a language can rank high because outside sources record names in it rather than because it is spoken locally — and a widely spoken language can be almost absent where official naming is in another language.
| Language | Place names | Share | Script |
|---|---|---|---|
| Chinese (zho) | 2 | 28.6% | — |
| English (eng) | 2 | 28.6% | — |
| Nepali (nep) | 2 | 28.6% | — |
| Dzongkha (dzo) | 1 | 14.3% | — |
340 distinct features ·
4 languages ·
0 scripts ·
1 names in non-Roman script
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.
| Source | Type | Access |
|---|---|---|
| HDX COD — Population Statistics (OCHA/UNFPA) | international_organization | bulk_download |
| Global Data Lab | academic | api |
| World Bank Open Data | international_organization | api |
| GI-TOC / ENACT (Global Initiative Against Transnational Organized Crime · ENACT) | academic | bulk_download |
| Ethnic Power Relations Dataset | academic | bulk_download |
| D-PLACE (Database of Places, Language, Culture & Environment) | academic | bulk_download |
| NGA GEOnet Names Server (GNS) | official_government | bulk_download |
| UNHCR Refugee Data Finder (UN High Commissioner for Refugees) | international_organization | api |
| Glottolog Language Catalog | academic | bulk_download |
| GHS Urban Centre Database (Global Human Settlement · EU Joint Research Centre) | international_organization | bulk_download |
| LandScan Global (ORNL — Oak Ridge National Laboratory) | research_institution | earth_engine |
| OpenFactBook | community_compilation | bulk_download |
Pick datasets and admin level(s). You'll get a .zip with one CSV per dataset, each filtered to the levels you choose.