ⓘ 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 | CMR, CMR, CMR, CMR, CMR |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 11 | Total, Adamaoua, Centre (incl Yaounde), Est, Extreme Nord |
human_development_index |
Human development index | float | SEL | 0% | 94 | 0.516, 0.43, 0.585, 0.483, 0.328 |
health_index |
Health index | float | SEL | 0% | 87 | 0.528, 0.487, 0.556, 0.518, 0.466 |
education_index |
Education index | float | SEL | 0% | 97 | 0.456, 0.288, 0.603, 0.431, 0.151 |
income_index |
Income index | float | SEL | 0% | 63 | 0.569, 0.569, 0.597, 0.506, 0.501 |
life_expectancy |
Life expectancy | float | SEL | 0% | 97 | 54.35, 51.66, 56.13, 53.66, 50.32 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 100 | 6.843, 3.033, 9.717, 6.129, 1.445 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 10 | 1990, 1990, 1990, 1990, 1990 |
level |
level | string | 0% | 2 | national, subnational, subnational, subnational, subnational |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
glottocode |
Glottocode | string | CCL | 0% | 100 | abar1238, abon1238, adam1253, afad1236, aghe1239 |
name |
Name | string | CCL | 0% | 100 | Mungbam, Abon, Adamawa Fulfulde, Afade, Aghem |
iso639_3 |
Iso639 3 | string | CCL | 5% | 95 | mij, abo, fub, aal, agq |
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% | 8 | atla1278, atla1278, atla1278, afro1255, atla1278 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 0% | 76 | yemn1234, nort3192, adam1260, koto1268, aghe1241 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 11 | ['CM'], ['CM', 'NG'], ['CM', 'ER', 'ET', 'NG', 'SD',... |
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% | 14 | 6, 0, 6, 0, 0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 1% | 99 | 6.5805, 6.90621, 8.140326, 12.0551, 6.38956 |
longitude |
longitude | float | 1% | 99 | 10.2267, 10.8769, 13.077338, 14.6343, 10.0807 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CM, CM, CM, CM, CM |
population_count |
Population count | float | SEL | 2% | 65 | 5159057.0, 5239273.0, 5338620.0, 5456623.0, 5578257.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 34.667, 35.186, 42.599, 43.074, 43.596 |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 2% | 65 | 119.05394115577, 124.593165563331, 130.042569873656,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 92% | 5 | 41.2200012207031, 68.4100036621094, 70.6800003051758,... |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 280.3, 274.1, 268.9, 264.3, 259.5 |
poverty_headcount_pct |
Poverty headcount percent | float | SEL | 92% | 5 | 53.3, 40.2, 39.9, 37.5, 37.7 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Cameroon, Cameroon, Cameroon, Cameroon, Cameroon |
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 | CM, CM, CM, CM, CM |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 34.667, 35.186, 42.599, 43.074, 43.596 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 3% | 64 | 72.8, 71.3, 70.1, 69.2, 68.2 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 280.3, 274.1, 268.9, 264.3, 259.5 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 37 | 572.0, 579.0, 557.0, 559.0, 564.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 63 | 5.725, 5.732, 5.729, 5.731, 5.739 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 64 | 43.806, 43.948, 43.853, 43.659, 43.427 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 64 | 28.697, 28.207, 22.081, 21.707, 21.293 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 70% | 17 | 0.034, 0.037, 0.034, 0.072, 0.071 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 91% | 6 | 2.00226593017578, 1.75150001049042, 2.46589994430542,... |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 33% | 32 | 5.0, 15.0, 25.0, 27.0, 33.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 4.29573393, 4.16830397, 4.02669907, 3.90227985, 3.72798991 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Cameroon, Cameroon, Cameroon, Cameroon, Cameroon |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
| 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% | 61 | 39.4, 51.2, 42.5, 47.5, 85.8 |
men_who_are_literate |
Men who are literate | float | CCL | 25% | 50 | 63.9, 76.5, 72.2, 90.1, 91.9 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Cameroon, Cameroon, Cameroon, Cameroon, Cameroon |
survey_year |
survey_year | integer | 0% | 4 | 2004, 2011, 2018, 2022, 2004 |
region |
region | string | 0% | 17 | ..Adamaoua, ..Adamaoua, ..Adamaoua, ..Adamaoua, ..Centre |
survey_id |
survey_id | string | 0% | 4 | CM2004DHS, CM2011DHS, CM2018DHS, CM2022MIS, CM2004DHS |
survey_type |
survey_type | string | 0% | 2 | DHS, DHS, DHS, MIS, DHS |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 100% | - | - |
contraception_modern_pct |
Contraception modern percent | float | SEL | 0% | 53 | 8.4, 10.5, 5.7, 17.1, 22.9 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 0% | 42 | 79.0, 74.0, 56.0, 77.0, 65.0 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 2% | 53 | 136.0, 129.0, 96.0, 120.0, 121.0 |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 2% | 57 | 47.2, 53.7, 38.0, 47.4, 51.6 |
children_underweight |
Children underweight | float | CCL | 0% | 50 | 11.9, 20.8, 17.0, 4.3, 8.3 |
hiv_prevalence_pct |
Hiv prevalence percent | float | SEL | 16% | 33 | 7.0, 5.1, 4.1, 4.7, 6.1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Cameroon, Cameroon, Cameroon, Cameroon, Cameroon |
survey_year |
survey_year | integer | 0% | 5 | 2004, 2011, 2018, 2004, 2011 |
region |
region | string | 0% | 17 | ..Adamaoua, ..Adamaoua, ..Adamaoua, ..Centre, ..Centre |
survey_id |
survey_id | string | 0% | 5 | CM2004DHS, CM2011DHS, CM2018DHS, CM2004DHS, CM2011DHS |
survey_type |
survey_type | string | 0% | 1 | DHS, DHS, DHS, DHS, DHS |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | the Republic of Cameroon |
admin_code |
Admin code | string | SEL | 0% | 1 | 59405334B15220060264401 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 465741.0306 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 30991782 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 66.54 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR, CMR, CMR, CMR, CMR |
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% | 10 | Centre, Far North, Littoral, North, North-West |
admin_code |
Admin code | string | SEL | 0% | 10 | 27767025B11866847137657, 27767025B65184844379073,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 10 | 68681.71, 34875.1508, 20250.3077, 67441.3319, 17121.4773 |
pop_2024 |
Population count | integer | SEL | 0% | 10 | 5800893, 5713547, 4620267, 3417105, 2725389 |
pop_density_2024 |
Population density | float | SEL | 0% | 10 | 84.46, 163.83, 228.16, 50.67, 159.18 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR, CMR, CMR, CMR, CMR |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality, locality, locality, locality |
admin_name |
Admin name | string | SEL | 0% | 44 | Yaoundé, Douala, Garoua, Maroua, Bamenda |
admin_code |
Admin code | integer | SEL | 0% | 44 | 2276, 832, 2695, 3238, 1400 |
area_sqkm |
Area sqkm | float | SEL | 0% | 44 | 310.9236, 278.1444, 66.5748, 65.5879, 81.4629 |
pop_2024 |
Population count | integer | SEL | 0% | 44 | 3550733, 3531133, 721599, 447951, 394714 |
pop_density_2024 |
Population density | float | SEL | 0% | 44 | 11419.95, 12695.32, 10838.92, 6829.78, 4845.32 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 44 | 5479204, 4457862, 699541, 512801, 399784 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 44 | 0.648, 0.792, 1.032, 0.874, 0.987 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 44 | Yaoundé, Douala, Garoua, Maroua, Bamenda |
country_code |
Country code | string | SEL | 0% | 1 | CMR, CMR, CMR, CMR, CMR |
population |
Population count | integer | SEL | 0% | 44 | 5479204, 4457862, 699541, 512801, 399784 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 44 | 2276, 832, 2695, 3238, 1400 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Cameroon, Cameroon, Cameroon, Cameroon, Cameroon |
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 | CMR, CMR, CMR, CMR, CMR |
society_id |
Society id | string | CCL | 0% | 33 | Ae12, Ae2, Ae40, Ae42, Ae43 |
society_name |
Society name | string | CCL | 0% | 33 | Duala, Kpe, Dzem, Ngumba, Sanga |
language_glottocode |
Language glottocode | string | CCL | 0% | 33 | dual1243, mokp1239, njye1238, kwas1243, bomw1238 |
language_name |
Language name | string | CCL | 0% | 1 | , , , , |
kinship_system |
Kinship system | string | CCL | 0% | 19 | EA001:0; EA002:0; EA003:3; EA004:1; EA005:6, EA001:0;... |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 13 | EA006:1; EA007:8; EA008:5; EA009:5; EA010:8, EA006:1;... |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 22 | EA028:3; EA029:5; EA030:7; EA031:NA; EA032:3, EA028:3;... |
political_complexity |
Political complexity | string | CCL | 0% | 13 | EA033:3; EA034:2; EA035:2, EA033:1; EA034:2; EA035:NA,... |
religion_importance |
Religion importance | string | CCL | 0% | 10 | EA034:2; EA112:2, EA034:2; EA112:1, EA034:NA; EA112:NA,... |
residence_pattern |
Residence pattern | string | CCL | 0% | 5 | 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 | Cameroon, Cameroon, Cameroon, Cameroon, Cameroon |
dataset |
dataset | string | 0% | 1 | EA, EA, EA, EA, EA |
region |
region | string | 0% | 1 | , , , , |
latitude |
latitude | float | 0% | 12 | 4.0, 4.22, 3.0, 3.0, 2.0 |
longitude |
longitude | float | 0% | 8 | 10.0, 9.27, 14.0, 11.0, 16.0 |
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 |
|---|---|---|---|---|---|---|
telephones_fixed_lines_subscriptions_per_100_inhabitants_numeric |
Fixed line subscriptions per 100 | float | SEL | 0% | 1 | 2024.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 108.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .cm |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 42.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric |
Broadband subscriptions per 100 | float | SEL | 0% | 1 | 2.0 |
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
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 | 67,500 (2024 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 67500.0 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | (2024 est.) less than 1 |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 31.5 million (2024 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 31.5 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 108 (2024 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | government maintains tight control over broadcast media;... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 2007.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 42% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 603,000 (2022 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 603000.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 2 (2022 est.) |
source_section |
source_section | string | 0% | 1 | Communications |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/cm.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 | 4900.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 51.327 |
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
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 | largest CEMAC economy with many natural resources;... |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $143.264 billion (2024 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_numeric |
Real gdp purchasing power parity 2024 (numeric) | float | 0% | 1 | 143.264 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $138.191 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 | 138.191 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $133.843 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 | 133.843 |
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 | 3.7% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | 3.7 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 3.2% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 3.2 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 3.7% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 3.7 |
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 | $4,900 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $4,900 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 4900.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $4,800 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 4800.0 |
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 | $51.327 billion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 4.5% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 4.5 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text |
Inflation rate consumer prices 2023 (text) | string | 0% | 1 | 7.4% (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric |
Inflation rate consumer prices 2023 (numeric) | float | 0% | 1 | 7.4 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 6.2% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 6.2 |
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 | 17.4% (2024 est.) |
| +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 | 71.0 |
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
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 | 71% (2022 est.) |
electricity_access_electrification_urban_areas_text |
electricity_access_electrification_urban_areas_text | string | 0% | 1 | 94% |
electricity_access_electrification_urban_areas_numeric |
electricity_access_electrification_urban_areas_numeric | float | 0% | 1 | 94.0 |
electricity_access_electrification_rural_areas_text |
electricity_access_electrification_rural_areas_text | string | 0% | 1 | 25% |
electricity_access_electrification_rural_areas_numeric |
electricity_access_electrification_rural_areas_numeric | float | 0% | 1 | 25.0 |
electricity_installed_generating_capacity_text |
electricity_installed_generating_capacity_text | string | 0% | 1 | 1.798 million kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 1.798 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 6.161 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 6.161 |
electricity_imports_text |
electricity_imports_text | string | 0% | 1 | 60 million kWh (2023 est.) |
electricity_imports_numeric |
electricity_imports_numeric | float | 0% | 1 | 60.0 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 2.238 billion kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 2.238 |
electricity_generation_sources_fossil_fuels_text |
electricity_generation_sources_fossil_fuels_text | string | 0% | 1 | 36.1% of total installed capacity (2023 est.) |
electricity_generation_sources_fossil_fuels_numeric |
electricity_generation_sources_fossil_fuels_numeric | float | 0% | 1 | 36.1 |
electricity_generation_sources_solar_text |
electricity_generation_sources_solar_text | string | 0% | 1 | 0.3% of total installed capacity (2023 est.) |
electricity_generation_sources_solar_numeric |
electricity_generation_sources_solar_numeric | float | 0% | 1 | 0.3 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 63.1% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 63.1 |
electricity_generation_sources_biomass_and_waste_text |
electricity_generation_sources_biomass_and_waste_text | string | 0% | 1 | 0.5% of total installed capacity (2023 est.) |
electricity_generation_sources_biomass_and_waste_numeric |
electricity_generation_sources_biomass_and_waste_numeric | float | 0% | 1 | 0.5 |
coal_imports_text |
coal_imports_text | string | 0% | 1 | 300 metric tons (2023 est.) |
coal_imports_numeric |
coal_imports_numeric | float | 0% | 1 | 300.0 |
petroleum_total_petroleum_production_text |
petroleum_total_petroleum_production_text | string | 0% | 1 | 64,000 bbl/day (2023 est.) |
petroleum_total_petroleum_production_numeric |
petroleum_total_petroleum_production_numeric | float | 0% | 1 | 64000.0 |
petroleum_refined_petroleum_consumption_text |
petroleum_refined_petroleum_consumption_text | string | 0% | 1 | 41,000 bbl/day (2023 est.) |
petroleum_refined_petroleum_consumption_numeric |
petroleum_refined_petroleum_consumption_numeric | float | 0% | 1 | 41000.0 |
petroleum_crude_oil_estimated_reserves_text |
petroleum_crude_oil_estimated_reserves_text | string | 0% | 1 | 200 million barrels (2021 est.) |
petroleum_crude_oil_estimated_reserves_numeric |
petroleum_crude_oil_estimated_reserves_numeric | float | 0% | 1 | 200.0 |
natural_gas_production_text |
natural_gas_production_text | string | 0% | 1 | 2.356 billion cubic meters (2023 est.) |
| +11 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 | 20.9 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 41.0 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 59.3 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 3.43 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 3.271 |
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
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 | deforestation; overgrazing; soil erosion;... |
international_environmental_agreements_party_to_text |
international_environmental_agreements_party_to_text | string | 0% | 1 | Biodiversity, Climate Change, Climate Change-Kyoto... |
international_environmental_agreements_party_to_numeric |
international_environmental_agreements_party_to_numeric | float | 0% | 1 | 2006.0 |
international_environmental_agreements_signed_but_not_ratified_text |
international_environmental_agreements_signed_but_not_ratified_text | string | 0% | 1 | Nuclear Test Ban |
climate_text |
climate_text | string | 0% | 1 | varies with terrain, from tropical along coast to... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 20.9% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 13.1% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 13.1 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 3.6% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 3.6 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 4.2% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 4.2 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 41% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 38.1% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 38.1 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 59.3% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 3.43% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 6.707 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 6.707 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 200 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 | 200.0 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 5.658 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 | 5.658 |
carbon_dioxide_emissions_from_consumed_natural_gas_text |
carbon_dioxide_emissions_from_consumed_natural_gas_text | string | 0% | 1 | 1.049 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 | 1.049 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 62 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 62.0 |
methane_emissions_energy_text |
methane_emissions_energy_text | string | 0% | 1 | 293.3 kt (2022-2024 est.) |
methane_emissions_energy_numeric |
methane_emissions_energy_numeric | float | 0% | 1 | 293.3 |
methane_emissions_agriculture_text |
methane_emissions_agriculture_text | string | 0% | 1 | 278.2 kt (2019-2021 est.) |
| +18 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 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
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 | Cameroonian(s) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Cameroonian |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | Bamileke-Bamu 22.2%, Biu-Mandara 16.4%,... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 22.2 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/cm.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 475440.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 472710.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 2730.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 5018.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 402.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 4045.0 |
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 | 20.9 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 41.0 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 290.0 |
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
location_text |
location_text | string | 0% | 1 | Central Africa, bordering the Bight of Biafra, between... |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 6 00 N, 12 00 E |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 6.0 |
map_references_text |
map_references_text | string | 0% | 1 | Africa |
area_total_text |
area_total_text | string | 0% | 1 | 475,440 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 472,710 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 2,730 sq km |
area_comparative_text |
area_comparative_text | string | 0% | 1 | slightly larger than California; about four times the... |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 5,018 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | Central African Republic 901 km; Chad 1,116 km; Republic... |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 901.0 |
coastline_text |
coastline_text | string | 0% | 1 | 402 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 |
climate_text |
climate_text | string | 0% | 1 | varies with terrain, from tropical along coast to... |
terrain_text |
terrain_text | string | 0% | 1 | diverse, with coastal plain in southwest, dissected... |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Fako on Mont Cameroun 4,045 m |
elevation_lowest_point_text |
elevation_lowest_point_text | string | 0% | 1 | Atlantic Ocean 0 m |
elevation_mean_elevation_text |
elevation_mean_elevation_text | string | 0% | 1 | 667 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 667.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | petroleum, bauxite, iron ore, timber, hydropower |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 20.9% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 13.1% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 13.1 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 3.6% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 3.6 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 4.2% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 4.2 |
| +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 | CMR |
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 | Republic of Cameroon |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Cameroon |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | République du Cameroun (French)/Republic of Cameroon (English) |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Cameroun/Cameroon |
country_name_former_text |
country_name_former_text | string | 0% | 1 | Kamerun, French Cameroon, British Cameroon, Federal... |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | in the 16th century, Portuguese explorers named an... |
country_name_etymology_numeric |
country_name_etymology_numeric | float | 0% | 1 | 16.0 |
government_type_text |
government_type_text | string | 0% | 1 | presidential republic |
capital_name_text |
capital_name_text | string | 0% | 1 | Yaounde |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 3 52 N, 11 31 E |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 3.0 |
capital_time_difference_text |
capital_time_difference_text | string | 0% | 1 | UTC+1 (6 hours ahead of Washington, DC, during Standard Time) |
capital_time_difference_numeric |
capital_time_difference_numeric | float | 0% | 1 | 1.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | Germans founded the city in 1888, but the name comes... |
capital_etymology_numeric |
capital_etymology_numeric | float | 0% | 1 | 1888.0 |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 10 regions (régions, singular - région); Adamaoua,... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 10.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | mixed system of English common law, French civil law,... |
constitution_history_text |
constitution_history_text | string | 0% | 1 | several previous; latest effective 18 January 1996 |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 18.0 |
constitution_amendment_process_text |
constitution_amendment_process_text | string | 0% | 1 | proposed by the president of the republic or by... |
international_law_organization_participation_text |
international_law_organization_participation_text | string | 0% | 1 | accepts compulsory ICJ jurisdiction; non-party state to the ICCt |
citizenship_citizenship_by_birth_text |
Citizenship by birth (text) | string | 0% | 1 | no |
citizenship_citizenship_by_descent_only_text |
Citizenship by descent only (text) | string | 0% | 1 | at least one parent must be a citizen of Cameroon |
citizenship_dual_citizenship_recognized_text |
citizenship_dual_citizenship_recognized_text | string | 0% | 1 | no |
citizenship_residency_requirement_for_naturalization_text |
citizenship_residency_requirement_for_naturalization_text | string | 0% | 1 | 5 years |
citizenship_residency_requirement_for_naturalization_numeric |
citizenship_residency_requirement_for_naturalization_numeric | float | 0% | 1 | 5.0 |
suffrage_text |
suffrage_text | string | 0% | 1 | 20 years of age; universal |
suffrage_numeric |
suffrage_numeric | float | 0% | 1 | 20.0 |
executive_branch_chief_of_state_text |
executive_branch_chief_of_state_text | string | 0% | 1 | President Paul BIYA (since 6 November 1982) |
| +86 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 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | Powerful chiefdoms ruled much of the area of present-day... |
background_numeric |
background_numeric | float | 0% | 1 | 1884.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/cm.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_languages_text |
Languages (text) | string | 0% | 1 | 24 major African language groups, English (official),... |
languages_languages_numeric |
Languages (numeric) | float | 0% | 1 | 24.0 |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | The World Factbook, the indispensable source for basic... |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/cm.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
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 | 443,740 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 443740.0 |
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 1,058,405 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 1058405.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/cm.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
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 | Cameroon Armed Forces (Forces Armees Camerounaises,... |
military_and_security_forces_numeric |
military_and_security_forces_numeric | float | 0% | 1 | 2025.0 |
military_expenditures_military_expenditures_2024_text |
Military expenditures 2024 (text) | string | 0% | 1 | 1% of GDP (2024 est.) |
military_expenditures_military_expenditures_2024_numeric |
Military expenditures 2024 (numeric) | float | 0% | 1 | 1.0 |
military_expenditures_military_expenditures_2023_text |
Military expenditures 2023 (text) | string | 0% | 1 | 1% of GDP (2023 est.) |
military_expenditures_military_expenditures_2023_numeric |
Military expenditures 2023 (numeric) | float | 0% | 1 | 1.0 |
military_expenditures_military_expenditures_2022_text |
Military expenditures 2022 (text) | string | 0% | 1 | 1% of GDP (2022 est.) |
military_expenditures_military_expenditures_2022_numeric |
Military expenditures 2022 (numeric) | float | 0% | 1 | 1.0 |
military_expenditures_military_expenditures_2021_text |
Military expenditures 2021 (text) | string | 0% | 1 | 1% of GDP (2021 est.) |
military_expenditures_military_expenditures_2021_numeric |
Military expenditures 2021 (numeric) | float | 0% | 1 | 1.0 |
military_expenditures_military_expenditures_2020_text |
Military expenditures 2020 (text) | string | 0% | 1 | 1% of GDP (2020 est.) |
military_expenditures_military_expenditures_2020_numeric |
Military expenditures 2020 (numeric) | float | 0% | 1 | 1.0 |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | estimated 40-50,000 active FAC, including the Gendarmerie (2025) |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 40.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the FAC inventory is comprised of armaments from a... |
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 | 18-23 years of age for voluntary military service for... |
military_service_age_and_obligation_numeric |
military_service_age_and_obligation_numeric | float | 0% | 1 | 18.0 |
military_deployments_text |
military_deployments_text | string | 0% | 1 | 750 (plus about 400 police) Central African Republic... |
military_deployments_numeric |
military_deployments_numeric | float | 0% | 1 | 750.0 |
military_note_text |
military_note_text | string | 0% | 1 | the Cameroon Armed Forces (FAC) are responsible for... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 2016.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/cm.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 31518954.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 15683611.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 15835343.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 41.5 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 55.3 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 3.2 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 77.6 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 71.8 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 5.8 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 19.4 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | 2.37 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 30.79 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 6.73 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | -0.32 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 59.3 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 3.43 |
sex_ratio_at_birth_numeric |
Sex ratio at birth | float | SEL | 0% | 1 | 1.03 |
sex_ratio_total_population_numeric |
Sex ratio overall | float | SEL | 0% | 1 | 0.99 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 258.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 44.6 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 64.2 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 3.87 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 1.91 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 0.14 |
hospital_bed_density_numeric |
Hospital beds per 1000 | float | SEL | 0% | 1 | 2.6 |
literacy_total_population_numeric |
Literacy rate percent | float | SEL | 0% | 1 | 72.6 |
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
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 | 31,518,954 (2025 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 15,683,611 |
population_female_text |
population_female_text | string | 0% | 1 | 15,835,343 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 41.5% (male 6,477,438/female 6,364,987) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 55.3% (male 8,488,522/female 8,638,519) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 3.2% (2024 est.) (male 463,628/female 533,011) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 77.6 (2025 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 71.8 (2025 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 5.8 (2025 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 17.3 (2025 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 17.3 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 19.4 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 18.6 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 18.6 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 19.2 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 19.2 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | 2.37% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 30.79 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 6.73 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | -0.32 migrant(s)/1,000 population (2025 est.) |
population_distribution_text |
population_distribution_text | string | 0% | 1 | population concentrated in the west and north, with the... |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 59.3% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 3.43% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 4.509 million YAOUNDE (capital), 4.063 million Douala (2023) |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 4.509 |
sex_ratio_at_birth_text |
sex_ratio_at_birth_text | string | 0% | 1 | 1.03 male(s)/female |
sex_ratio_0_14_years_text |
sex_ratio_0_14_years_text | string | 0% | 1 | 1.02 male(s)/female |
sex_ratio_0_14_years_numeric |
sex_ratio_0_14_years_numeric | float | 0% | 1 | 1.02 |
sex_ratio_15_64_years_text |
sex_ratio_15_64_years_text | string | 0% | 1 | 0.98 male(s)/female |
sex_ratio_15_64_years_numeric |
sex_ratio_15_64_years_numeric | float | 0% | 1 | 0.98 |
| +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 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_religion_muslim_pct_synth |
Muslim | numeric | CCL | 0% | - | 30.6 |
composition_religion_other_pct_synth |
other | numeric | CCL | 0% | - | 0.7 |
composition_ethnicity_primary_label_synth |
Bamileke-Bamu | string | CCL | 0% | - | Bamileke-Bamu |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Roman Catholic 33.1%, Muslim 30.6%, Protestant 27.1%... |
religions_numeric |
religions_numeric | float | 0% | 1 | 33.1 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/cm.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_roman_catholic_pct_synth |
Roman Catholic | numeric | 0% | - | 33.1 |
composition_religion_protestant_other_christian_6_1_pct_synth |
Protestant other Christian 6.1% | numeric | 0% | - | 27.1 |
composition_religion_animist_pct_synth |
animist | numeric | 0% | - | 1.3 |
composition_religion_none_pct_synth |
none | numeric | 0% | - | 1.2 |
composition_ethnicity_bamileke_bamu_pct_synth |
Bamileke-Bamu | numeric | 0% | - | 22.2 |
composition_ethnicity_biu_mandara_pct_synth |
Biu-Mandara | numeric | 0% | - | 16.4 |
composition_ethnicity_arab_choa_hausa_kanuri_pct_synth |
Arab-Choa/Hausa/Kanuri | numeric | 0% | - | 13.5 |
composition_ethnicity_beti_bassa_pct_synth |
Beti/Bassa | numeric | 0% | - | - |
composition_ethnicity_mbam_pct_synth |
Mbam | numeric | 0% | - | 13.1 |
composition_ethnicity_grassfields_pct_synth |
Grassfields | numeric | 0% | - | 9.9 |
composition_ethnicity_adamawa_ubangi_pct_synth |
Adamawa-Ubangi | numeric | 0% | - | - |
composition_ethnicity_cotier_ngoe_oroko_pct_synth |
Cotier/Ngoe/Oroko | numeric | 0% | - | 4.6 |
composition_ethnicity_southwestern_bantu_pct_synth |
Southwestern Bantu | numeric | 0% | - | 4.3 |
composition_ethnicity_kako_meka_pct_synth |
Kako/Meka | numeric | 0% | - | 2.3 |
composition_ethnicity_foreign_other_ethnic_group_pct_synth |
foreign/other ethnic group | numeric | 0% | - | 3.8 |
composition_ethnicity_primary_share_pct_synth |
Bamileke-Bamu | numeric | 0% | - | 22.2 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
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 | Boko Haram; Islamic State of Iraq and ash-Sham – West Africa |
source_section |
source_section | string | 0% | 1 | Terrorism |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/cm.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 | TJ |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 37.0 |
country_code |
Country code | string | SEL | 0% | 1 | CMR |
country_name |
Country name | string | SEL | 0% | 1 | Cameroon |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
airports_text |
airports_text | string | 0% | 1 | 37 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 1 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 1.0 |
railways_total_text |
railways_total_text | string | 0% | 1 | 987 km (2014) |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 987.0 |
railways_narrow_gauge_text |
railways_narrow_gauge_text | string | 0% | 1 | 987 km (2014) 1.000-m gauge |
railways_narrow_gauge_numeric |
railways_narrow_gauge_numeric | float | 0% | 1 | 987.0 |
railways_note |
railways_note | string | 0% | 1 | note: railway connections generally efficient but... |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 198 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 198.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | bulk carrier 2, general cargo 91, oil tanker 42, other 63 |
merchant_marine_by_type_numeric |
merchant_marine_by_type_numeric | float | 0% | 1 | 2.0 |
ports_total_ports_text |
ports_total_ports_text | string | 0% | 1 | 7 (2024) |
ports_total_ports_numeric |
ports_total_ports_numeric | float | 0% | 1 | 7.0 |
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 | 1 |
ports_medium_numeric |
ports_medium_numeric | float | 0% | 1 | 1.0 |
ports_small_text |
ports_small_text | float | 0% | 1 | 0 |
ports_small_numeric |
ports_small_numeric | float | 0% | 1 | 0.0 |
ports_very_small_text |
ports_very_small_text | float | 0% | 1 | 5 |
ports_very_small_numeric |
ports_very_small_numeric | float | 0% | 1 | 5.0 |
ports_size_unknown_text |
ports_size_unknown_text | float | 0% | 1 | 1 |
ports_size_unknown_numeric |
ports_size_unknown_numeric | float | 0% | 1 | 1.0 |
ports_ports_with_oil_terminals_text |
Ports with oil terminals (text) | float | 0% | 1 | 5 |
ports_ports_with_oil_terminals_numeric |
Ports with oil terminals (numeric) | float | 0% | 1 | 5.0 |
ports_key_ports_text |
ports_key_ports_text | string | 0% | 1 | Douala, Ebome Marine Terminal, Kole Oil Terminal, Kome... |
ports_key_ports_numeric |
ports_key_ports_numeric | float | 0% | 1 | 1.0 |
source_section |
source_section | string | 0% | 1 | Transportation |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/cm.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 1 | CM |
region_name |
Region name | string | SEL | 0% | 1 | Cameroon |
F_TL |
Female population | integer | SEL | 0% | 1 | 14967447 |
M_TL |
Male population | integer | SEL | 0% | 1 | 14474871 |
T_TL |
Total population | integer | SEL | 0% | 1 | 29442318 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_0 |
year |
Reference year | integer | 0% | 1 | 2025 |
F_00_04 |
Female population age 0-4 | integer | 0% | 1 | 2215153 |
F_05_09 |
Female population age 5-9 | integer | 0% | 1 | 1922153 |
F_10_14 |
Female population age 10-14 | integer | 0% | 1 | 1730123 |
F_15_19 |
Female population age 15-19 | integer | 0% | 1 | 1520012 |
F_20_24 |
Female population age 20-24 | integer | 0% | 1 | 1337614 |
F_25_29 |
Female population age 25-29 | integer | 0% | 1 | 1164466 |
F_30_34 |
Female population age 30-34 | integer | 0% | 1 | 988576 |
F_35_39 |
Female population age 35-39 | integer | 0% | 1 | 920373 |
F_40_44 |
Female population age 40-44 | integer | 0% | 1 | 809212 |
F_45_49 |
Female population age 45-49 | integer | 0% | 1 | 660460 |
F_50_54 |
Female population age 50-54 | integer | 0% | 1 | 497807 |
F_55_59 |
Female population age 55-59 | integer | 0% | 1 | 378357 |
F_60_64 |
Female population age 60-64 | integer | 0% | 1 | 305613 |
F_65_69 |
Female population age 65-69 | integer | 0% | 1 | 221286 |
F_70_74 |
Female population age 70-74 | integer | 0% | 1 | 156763 |
F_75_79 |
Female population age 75-79 | integer | 0% | 1 | 73011 |
F_80Plus |
F_80Plus | integer | 0% | 1 | 66468 |
M_00_04 |
Male population age 0-4 | integer | 0% | 1 | 2213906 |
M_05_09 |
Male population age 5-9 | integer | 0% | 1 | 1916425 |
M_10_14 |
Male population age 10-14 | integer | 0% | 1 | 1717974 |
M_15_19 |
Male population age 15-19 | integer | 0% | 1 | 1501706 |
M_20_24 |
Male population age 20-24 | integer | 0% | 1 | 1341471 |
M_25_29 |
Male population age 25-29 | integer | 0% | 1 | 1172953 |
M_30_34 |
Male population age 30-34 | integer | 0% | 1 | 1011764 |
M_35_39 |
Male population age 35-39 | integer | 0% | 1 | 867912 |
M_40_44 |
Male population age 40-44 | integer | 0% | 1 | 683226 |
M_45_49 |
Male population age 45-49 | integer | 0% | 1 | 557590 |
M_50_54 |
Male population age 50-54 | integer | 0% | 1 | 448235 |
| +23 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% | 10 | CM001, CM002, CM003, CM004, CM005 |
region_name |
Region name | string | SEL | 0% | 10 | Adamawa, Centre, East, Far-North, Littoral |
F_TL |
Female population | integer | SEL | 0% | 10 | 796794, 2751647, 644466, 2768123, 2246136 |
M_TL |
Male population | integer | SEL | 0% | 10 | 744979, 2735993, 639305, 2730993, 2252731 |
T_TL |
Total population | integer | SEL | 0% | 10 | 1541773, 5487640, 1283771, 5499116, 4498867 |
| 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 | 2025, 2025, 2025, 2025, 2025 |
F_00_04 |
Female population age 0-4 | integer | 0% | 10 | 131173, 331114, 92189, 540446, 236263 |
F_05_09 |
Female population age 5-9 | integer | 0% | 10 | 110787, 306047, 80313, 432057, 223087 |
F_10_14 |
Female population age 10-14 | integer | 0% | 10 | 94880, 295655, 73593, 348253, 228743 |
F_15_19 |
Female population age 15-19 | integer | 0% | 10 | 79681, 269005, 69875, 283753, 221013 |
F_20_24 |
Female population age 20-24 | integer | 0% | 10 | 73819, 253126, 66318, 253319, 189619 |
F_25_29 |
Female population age 25-29 | integer | 0% | 10 | 65668, 208502, 54406, 221159, 164648 |
F_30_34 |
Female population age 30-34 | integer | 0% | 10 | 53104, 191115, 40770, 157927, 156122 |
F_35_39 |
Female population age 35-39 | integer | 0% | 10 | 45354, 200113, 38057, 117503, 169334 |
F_40_44 |
Female population age 40-44 | integer | 0% | 10 | 37916, 189734, 32914, 96582, 172287 |
F_45_49 |
Female population age 45-49 | integer | 0% | 10 | 29734, 148146, 25172, 86578, 143927 |
F_50_54 |
Female population age 50-54 | integer | 0% | 10 | 22899, 105477, 19917, 69146, 104056 |
F_55_59 |
Female population age 55-59 | integer | 0% | 10 | 16860, 81016, 16125, 48972, 78409 |
F_60_64 |
Female population age 60-64 | integer | 0% | 10 | 14141, 63258, 12627, 45565, 60060 |
F_65_69 |
Female population age 65-69 | integer | 0% | 10 | 8897, 49557, 9952, 25758, 44973 |
F_70_74 |
Female population age 70-74 | integer | 0% | 10 | 6504, 31213, 6358, 24749, 29187 |
F_75_79 |
Female population age 75-79 | integer | 0% | 10 | 2728, 15651, 3318, 7269, 13566 |
F_80Plus |
F_80Plus | integer | 0% | 10 | 2649, 12918, 2562, 9087, 10842 |
M_00_04 |
Male population age 0-4 | integer | 0% | 10 | 125784, 324896, 91784, 557901, 238982 |
M_05_09 |
Male population age 5-9 | integer | 0% | 10 | 104416, 299853, 79588, 449577, 225598 |
M_10_14 |
Male population age 10-14 | integer | 0% | 10 | 88889, 290246, 72901, 361972, 231568 |
M_15_19 |
Male population age 15-19 | integer | 0% | 10 | 74014, 264692, 69176, 294711, 223792 |
M_20_24 |
Male population age 20-24 | integer | 0% | 10 | 71082, 256492, 67718, 259056, 196398 |
M_25_29 |
Male population age 25-29 | integer | 0% | 10 | 65045, 213066, 56406, 227433, 167068 |
M_30_34 |
Male population age 30-34 | integer | 0% | 10 | 54070, 192792, 46134, 170317, 155966 |
M_35_39 |
Male population age 35-39 | integer | 0% | 10 | 41305, 193907, 36033, 114699, 162661 |
M_40_44 |
Male population age 40-44 | integer | 0% | 10 | 31944, 182314, 28285, 71870, 156559 |
M_45_49 |
Male population age 45-49 | integer | 0% | 10 | 24457, 151304, 24416, 56244, 136378 |
M_50_54 |
Male population age 50-54 | integer | 0% | 10 | 18839, 115427, 20003, 45321, 113497 |
| +23 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% | 2 | CM005004, CM002007 |
region_name |
Region name | string | SEL | 0% | 1 | NA, NA |
F_TL |
Female population | integer | SEL | 0% | 2 | 1906354, 1879435 |
M_TL |
Male population | integer | SEL | 0% | 2 | 1910178, 1883496 |
T_TL |
Total population | integer | SEL | 0% | 2 | 3816532, 3762931 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_2, admin_2 |
year |
Reference year | integer | 0% | 1 | 2025, 2025 |
Metropolis |
Metropolis | string | 0% | 2 | Ville de Douala, Ville de Yaoundé |
F_00_04 |
Female population age 0-4 | integer | 0% | 2 | 191305, 201544 |
F_05_09 |
Female population age 5-9 | integer | 0% | 2 | 181516, 190546 |
F_10_14 |
Female population age 10-14 | integer | 0% | 2 | 189712, 189774 |
F_15_19 |
Female population age 15-19 | integer | 0% | 2 | 187628, 176967 |
F_20_24 |
Female population age 20-24 | integer | 0% | 2 | 161912, 170249 |
F_25_29 |
Female population age 25-29 | integer | 0% | 2 | 140346, 144249 |
F_30_34 |
Female population age 30-34 | integer | 0% | 2 | 133008, 133635 |
F_35_39 |
Female population age 35-39 | integer | 0% | 2 | 146876, 148114 |
F_40_44 |
Female population age 40-44 | integer | 0% | 2 | 155611, 151377 |
F_45_49 |
Female population age 45-49 | integer | 0% | 2 | 130418, 120744 |
F_50_54 |
Female population age 50-54 | integer | 0% | 2 | 92024, 82276 |
F_55_59 |
Female population age 55-59 | integer | 0% | 2 | 67955, 59731 |
F_60_64 |
Female population age 60-64 | integer | 0% | 2 | 50589, 43842 |
F_65_69 |
Female population age 65-69 | integer | 0% | 2 | 36527, 32060 |
F_70_74 |
Female population age 70-74 | integer | 0% | 2 | 22923, 18811 |
F_75_79 |
Female population age 75-79 | integer | 0% | 2 | 10252, 8963 |
F_80Plus |
F_80Plus | integer | 0% | 2 | 7752, 6553 |
M_00_04 |
Male population age 0-4 | integer | 0% | 2 | 193481, 199082 |
M_05_09 |
Male population age 5-9 | integer | 0% | 2 | 183463, 188642 |
M_10_14 |
Male population age 10-14 | integer | 0% | 2 | 191945, 188688 |
M_15_19 |
Male population age 15-19 | integer | 0% | 2 | 189721, 176688 |
M_20_24 |
Male population age 20-24 | integer | 0% | 2 | 166720, 172322 |
M_25_29 |
Male population age 25-29 | integer | 0% | 2 | 140383, 144422 |
M_30_34 |
Male population age 30-34 | integer | 0% | 2 | 129152, 128543 |
M_35_39 |
Male population age 35-39 | integer | 0% | 2 | 137199, 137643 |
M_40_44 |
Male population age 40-44 | integer | 0% | 2 | 140900, 145350 |
M_45_49 |
Male population age 45-49 | integer | 0% | 2 | 124465, 124368 |
| +24 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 | CM, CM, CM, CM, CM |
admin_level |
Admin level | integer | SEL | 0% | 1 | 1, 1, 1, 1, 1 |
iso3 |
Country code | string | SEL | 0% | 1 | CMR, CMR, CMR, CMR, CMR |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
retail |
retail | float | 0% | 7 | -0.25, 8.11, 0.0, 0.0, 7.36 |
grocery |
grocery | float | 0% | 9 | -0.04, 48.34, 0.0, 1.15, 14.81 |
parks |
parks | float | 0% | 7 | 0.0, -6.88, 0.0, 0.0, 14.41 |
transit |
transit | float | 0% | 7 | 0.0, 45.11, 0.0, 0.0, 21.61 |
workplaces |
workplaces | float | 0% | 10 | 14.68, -0.86, 16.46, 1.16, 4.31 |
residential |
residential | float | 0% | 7 | -0.23, 6.49, 0.0, 0.0, 4.55 |
region |
region | string | 0% | 10 | Adamawa, Centre, East, Far North, Littoral |
observation_count |
observation_count | integer | 0% | 9 | 1898, 2922, 1786, 1898, 3636 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR, CMR, CMR, CMR, CMR |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 6 | Bamileke, Beti (and related peoples), Fulani (and other... |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 2 | JUNIOR PARTNER, SENIOR PARTNER, JUNIOR PARTNER, JUNIOR... |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 5 | 0.25, 0.18, 0.14, 0.12, 0.08 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 6 | 47101000, 47103000, 47104000, 47105000, 47102000 |
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 | CMR, CMR, CMR, CMR, CMR |
gns_language_code |
gns_language_code | string | CCL | 0% | 5 | fra, eng, spa, fas, deu |
gns_language_name |
gns_language_name | string | CCL | 0% | 5 | French, English, Spanish, Persian, German |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 5 | 982, 113, 4, 3, 1 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 5 | 89.0299, 10.2448, 0.3626, 0.272, 0.0907 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 1 | 0, 0, 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, 0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | CMR |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Cameroon |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 5 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 0 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 99.9934 |
gns_non_roman_name_count |
gns_non_roman_name_count | integer | CCL | 0% | 1 | 0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
gns_name_count |
gns_name_count | integer | 0% | 1 | 30425 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 23957 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 30423 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 2 |
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 | 18358 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 14410 |
gns_name_count_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 9607 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 7768 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 1923 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 1447 |
gns_name_count_vegetation |
gns_name_count_vegetation | integer | 0% | 1 | 53 |
gns_feature_count_vegetation |
gns_feature_count_vegetation | integer | 0% | 1 | 45 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 192 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 146 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 183 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 57 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 109 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 84 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR |
economic_conditions |
Economic conditions | integer | CCL | 0% | 1 | 1 |
living_conditions |
Living conditions | integer | CCL | 0% | 1 | 1 |
employment_situation |
Employment situation | integer | CCL | 0% | 1 | 1 |
food_insecurity |
Food insecurity | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
round |
round | string | 0% | 1 | |
year |
year | string | 0% | 1 | |
region |
region | string | 0% | 1 | |
source |
source | string | 0% | 1 | Afrobarometer |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR |
women_equal_rights |
Women equal rights | integer | CCL | 0% | 1 | 1 |
women_political_leaders |
Women political leaders | integer | CCL | 0% | 1 | 1 |
women_land_rights |
Women land rights | integer | CCL | 0% | 1 | 1 |
domestic_violence_justified |
Domestic violence justified | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
round |
round | string | 0% | 1 | |
year |
year | string | 0% | 1 | |
region |
region | string | 0% | 1 | |
source |
source | string | 0% | 1 | Afrobarometer |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR |
trust_president |
Trust president | integer | CCL | 0% | 1 | 1 |
trust_parliament |
Trust parliament | integer | CCL | 0% | 1 | 1 |
trust_courts |
Trust courts | integer | CCL | 0% | 1 | 1 |
trust_police |
Trust police | integer | CCL | 0% | 1 | 1 |
trust_army |
Trust army | integer | CCL | 0% | 1 | 1 |
corruption_perception |
Corruption perception | integer | CCL | 0% | 1 | 1 |
democracy_satisfaction |
Democracy satisfaction | integer | CCL | 0% | 1 | 1 |
democracy_preference |
Democracy preference | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
round |
round | string | 0% | 1 | |
year |
year | string | 0% | 1 | |
region |
region | string | 0% | 1 | |
source |
source | string | 0% | 1 | Afrobarometer |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR |
emigration_considered |
Emigration considered | integer | CCL | 0% | 1 | 1 |
immigration_attitude |
Immigration attitude | integer | CCL | 0% | 1 | 1 |
foreign_workers_attitude |
Foreign workers attitude | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
round |
round | string | 0% | 1 | |
year |
year | string | 0% | 1 | |
region |
region | string | 0% | 1 | |
source |
source | string | 0% | 1 | Afrobarometer |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CMR |
trust_relatives |
Trust relatives | integer | CCL | 0% | 1 | 1 |
trust_neighbors |
Trust neighbors | integer | CCL | 0% | 1 | 1 |
trust_other_ethnic |
Trust other ethnic | integer | CCL | 0% | 1 | 1 |
trust_other_religion |
Trust other religion | integer | CCL | 0% | 1 | 1 |
national_identity_vs_ethnic |
National identity vs ethnic | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
round |
round | string | 0% | 1 | |
year |
year | string | 0% | 1 | |
region |
region | string | 0% | 1 | |
source |
source | string | 0% | 1 | Afrobarometer |
| 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 | CMR |
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 | 143 |
oc_anti_money_laundering_2023 |
oc_anti_money_laundering_2023 | float | 0% | 1 | 3.5 |
oc_anti_money_laundering_2021 |
oc_anti_money_laundering_2021 | float | 0% | 1 | 3.5 |
oc_anti_money_laundering_2019 |
oc_anti_money_laundering_2019 | float | 0% | 1 | 3.5 |
oc_arms_trafficking_rank |
oc_arms_trafficking_rank | integer | 0% | 1 | 37 |
oc_arms_trafficking_2023 |
oc_arms_trafficking_2023 | float | 0% | 1 | 7.5 |
oc_arms_trafficking_2021 |
oc_arms_trafficking_2021 | float | 0% | 1 | 6.5 |
oc_arms_trafficking_2019 |
oc_arms_trafficking_2019 | integer | 0% | 1 | 6 |
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_cannabis_trade_2019 |
oc_cannabis_trade_2019 | integer | 0% | 1 | 6 |
oc_cocaine_trade_rank |
oc_cocaine_trade_rank | integer | 0% | 1 | 126 |
oc_cocaine_trade_2023 |
oc_cocaine_trade_2023 | float | 0% | 1 | 3.5 |
oc_cocaine_trade_2021 |
oc_cocaine_trade_2021 | float | 0% | 1 | 3.5 |
oc_cocaine_trade_2019 |
oc_cocaine_trade_2019 | integer | 0% | 1 | 2 |
oc_criminal_actors_rank |
oc_criminal_actors_rank | integer | 0% | 1 | 55 |
oc_criminal_actors_2023 |
oc_criminal_actors_2023 | float | 0% | 1 | 6.3 |
oc_criminal_actors_2021 |
oc_criminal_actors_2021 | float | 0% | 1 | 6.38 |
oc_criminal_actors_2019 |
oc_criminal_actors_2019 | integer | 0% | 1 | 6 |
oc_criminal_markets_rank |
oc_criminal_markets_rank | integer | 0% | 1 | 38 |
oc_criminal_markets_2023 |
oc_criminal_markets_2023 | float | 0% | 1 | 6.23 |
oc_criminal_markets_2021 |
oc_criminal_markets_2021 | float | 0% | 1 | 6.25 |
oc_criminal_markets_2019 |
oc_criminal_markets_2019 | float | 0% | 1 | 5.95 |
oc_criminal_networks_rank |
oc_criminal_networks_rank | integer | 0% | 1 | 21 |
| +103 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 |
|---|---|---|---|
| French (fra) | 982 | 89.0% | — |
| English (eng) | 113 | 10.2% | — |
| Spanish (spa) | 4 | 0.4% | — |
| Persian (fas) | 3 | 0.3% | — |
| German (deu) | 1 | 0.1% | — |
23,957 distinct features ·
5 languages ·
0 scripts ·
2 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.