Cameroon

CMR Global Data Lab CMR-GDL Development Indices

374 rows · 1 table(s) Global Data Lab 0 1 2 3 9 SEL 2 ext ▶

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1 Admin 1 — 1 table(s)

CMR GDL - Subnational Indices — 374 rows, 11 columns

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Field details — 11 fields (type, nulls, unique, samples)

Standards-Aligned Fields (9)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (2) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`year`	year	integer	0%	10	1990, 1990, 1990, 1990, 1990
`level`	level	string	0%	2	national, subnational, subnational, subnational, subnational

CMR Glottolog Language Catalog CMR-GLOTTOLOG Language

317 rows · 1 table(s) Glottolog Language Catalog 0 1 2 3 1 SEL 12 CCL 3 ext ▶

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0 Admin 0 — 1 table(s)

CMR Glottolog - Languages — 317 rows, 16 columns

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Field details — 16 fields (type, nulls, unique, samples)

Standards-Aligned Fields (13)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`glottocode`	Glottocode	string	CCL	0%	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

Extension Fields (3) — supplemental data preserved outside core SEL/CCL schema

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	[], [], [], [], []

CMR UNHCR Refugee Data Finder CMR-UNHCR Migration

150 rows · 2 table(s) UNHCR Refugee Data Finder 0 1 2 3 12 CCL 36 ext ▶

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0 Admin 0 — 2 table(s)

CMR UNHCR - Hosted Populations — 75 rows, 24 columns

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Field details — 24 fields (type, nulls, unique, samples)

Standards-Aligned Fields (6)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_of_origin_iso`	Country of origin iso	string	CCL	0%	1	-, -, -, -, -
`refugees`	Refugees	integer	CCL	0%	75	2116011, 1952928, 1847304, 1749628, 1717966
`idps`	Idps	integer	CCL	0%	34	0, 0, 0, 0, 0
`stateless`	Stateless	integer	CCL	0%	23	0, 0, 0, 0, 0
`others_of_concern`	Others of concern	integer	CCL	0%	30	0, 0, 0, 0, 0
`total_population`	Total population	string	CCL	100%	-	-

Extension Fields (18) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`year`	year	integer	0%	75	1951, 1952, 1953, 1954, 1955
`country_of_origin`	country_of_origin	string	100%	-	-
`country_of_asylum`	country_of_asylum	string	100%	-	-
`country_of_asylum_iso`	country_of_asylum_iso	string	0%	1	-, -, -, -, -
`population_type`	population_type	string	100%	-	-
`asylum_seekers`	asylum_seekers	integer	0%	34	0, 0, 0, 0, 0
`female_total`	female_total	string	100%	-	-
`male_total`	male_total	string	100%	-	-
`female_0_4`	female_0_4	string	100%	-	-
`female_5_11`	female_5_11	string	100%	-	-
`female_12_17`	female_12_17	string	100%	-	-
`female_18_59`	female_18_59	string	100%	-	-
`female_60_plus`	female_60_plus	string	100%	-	-
`male_0_4`	male_0_4	string	100%	-	-
`male_5_11`	male_5_11	string	100%	-	-
`male_12_17`	male_12_17	string	100%	-	-
`male_18_59`	male_18_59	string	100%	-	-
`male_60_plus`	male_60_plus	string	100%	-	-

CMR UNHCR - Origin Populations — 75 rows, 24 columns

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Field details — 24 fields (type, nulls, unique, samples)

Standards-Aligned Fields (6)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_of_origin_iso`	Country of origin iso	string	CCL	0%	1	-, -, -, -, -
`refugees`	Refugees	integer	CCL	0%	75	2116011, 1952928, 1847304, 1749628, 1717966
`idps`	Idps	integer	CCL	0%	34	0, 0, 0, 0, 0
`stateless`	Stateless	integer	CCL	0%	23	0, 0, 0, 0, 0
`others_of_concern`	Others of concern	integer	CCL	0%	30	0, 0, 0, 0, 0
`total_population`	Total population	string	CCL	100%	-	-

Extension Fields (18) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`year`	year	integer	0%	75	1951, 1952, 1953, 1954, 1955
`country_of_origin`	country_of_origin	string	100%	-	-
`country_of_asylum`	country_of_asylum	string	100%	-	-
`country_of_asylum_iso`	country_of_asylum_iso	string	0%	1	-, -, -, -, -
`population_type`	population_type	string	100%	-	-
`asylum_seekers`	asylum_seekers	integer	0%	34	0, 0, 0, 0, 0
`female_total`	female_total	string	100%	-	-
`male_total`	male_total	string	100%	-	-
`female_0_4`	female_0_4	string	100%	-	-
`female_5_11`	female_5_11	string	100%	-	-
`female_12_17`	female_12_17	string	100%	-	-
`female_18_59`	female_18_59	string	100%	-	-
`female_60_plus`	female_60_plus	string	100%	-	-
`male_0_4`	male_0_4	string	100%	-	-
`male_5_11`	male_5_11	string	100%	-	-
`male_12_17`	male_12_17	string	100%	-	-
`male_18_59`	male_18_59	string	100%	-	-
`male_60_plus`	male_60_plus	string	100%	-	-

CMR World Bank Open Data CMR-WORLD_BANK Development Indicators

132 rows · 2 table(s) World Bank Open Data 0 1 2 3 19 SEL 4 ext ▶

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0 Admin 0 — 2 table(s)

CMR World Bank - Development Indicators — 66 rows, 9 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (2) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_name`	country_name	string	0%	1	Cameroon, Cameroon, Cameroon, Cameroon, Cameroon
`year`	year	integer	0%	66	1960, 1961, 1962, 1963, 1964

CMR World Bank - Health Indicators — 66 rows, 14 columns

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Field details — 14 fields (type, nulls, unique, samples)

Standards-Aligned Fields (12)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (2) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_name`	country_name	string	0%	1	Cameroon, Cameroon, Cameroon, Cameroon, Cameroon
`year`	year	integer	0%	66	1960, 1961, 1962, 1963, 1964

CMR USAID DHS Program CMR-DHS Health Surveys

129 rows · 2 table(s) USAID DHS Program 0 1 2 3 7 SEL 3 CCL 10 ext ▶

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1 Admin 1 — 2 table(s)

CMR DHS - Ethnicity Indicators — 68 rows, 8 columns

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Field details — 8 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

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

Extension Fields (5) — supplemental data preserved outside core SEL/CCL schema

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

CMR DHS - Health Indicators — 61 rows, 12 columns

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Field details — 12 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

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

Extension Fields (5) — supplemental data preserved outside core SEL/CCL schema

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

CMR LandScan Global (ORNL) CMR-LANDSCAN Modeled Population

55 rows · 3 table(s) LandScan Global (ORNL) 0 1 2 3 Locality 21 SEL 2 ext ▶

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0 Admin 0 — 1 table(s)

CMR LandScan - Population Admin0 (admin_0) — 1 rows, 7 columns

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Field details — 7 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

1 Admin 1 — 1 table(s)

CMR LandScan - Population Admin1 (admin_1) — 10 rows, 7 columns

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Field details — 7 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Locality Locality — 1 table(s)

CMR LandScan - Cities (locality) — 44 rows, 9 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (2) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`ghs_pop_2025`	ghs_pop_2025	integer	0%	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

CMR GHS Urban Centre Database (EU JRC) CMR-GHSL_UCDB Modeled Population

44 rows · 1 table(s) GHS Urban Centre Database (EU JRC) 0 1 2 3 Locality 3 SEL 7 ext ▶

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Locality Locality — 1 table(s)

CMR GHS-UCDB - Cities (locality) — 44 rows, 10 columns

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Field details — 10 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`city_name`	Admin name	string	SEL	0%	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

Extension Fields (7) — supplemental data preserved outside core SEL/CCL schema

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%	-	-

CMR D-PLACE CMR-DPLACE Ethnographic Societies

33 rows · 1 table(s) D-PLACE 0 1 2 3 1 SEL 10 CCL 7 ext ▶

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0 Admin 0 — 1 table(s)

CMR D-PLACE - Dplace Ea Societies — 33 rows, 18 columns

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Field details — 18 fields (type, nulls, unique, samples)

Standards-Aligned Fields (11)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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,...

Extension Fields (7) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_name`	country_name	string	0%	1	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

CMR OpenFactBook CMR-OPENFACTBOOK Country Profile

15 rows · 15 table(s) OpenFactBook 0 1 2 3 95 SEL 3 CCL 621 ext ▶

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0 Admin 0 — 15 table(s)

CMR OpenFactBook - Communications — 1 rows, 22 columns

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Field details — 22 fields (type, nulls, unique, samples)

Standards-Aligned Fields (8)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`telephones_fixed_lines_subscriptions_per_100_inhabitants_numeric`	Fixed line subscriptions per 100	float	SEL	0%	1	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

Extension Fields (14) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`telephones_fixed_lines_total_subscriptions_text`	telephones_fixed_lines_total_subscriptions_text	string	0%	1	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

CMR OpenFactBook - Economy — 1 rows, 155 columns

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Field details — 155 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`real_gdp_per_capita_real_gdp_per_capita_2024_numeric`	Real gdp per capita 2024 (numeric)	float	SEL	0%	1	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

Extension Fields (150) — supplemental data preserved outside core SEL/CCL schema

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.

CMR OpenFactBook - Energy — 1 rows, 45 columns

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Field details — 45 fields (type, nulls, unique, samples)

Standards-Aligned Fields (4)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`electricity_access_electrification_total_population_numeric`	Electricity access percent	float	SEL	0%	1	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

Extension Fields (41) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`electricity_access_electrification_total_population_text`	electricity_access_electrification_total_population_text	string	0%	1	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.

CMR OpenFactBook - Environment — 1 rows, 56 columns

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Field details — 56 fields (type, nulls, unique, samples)

Standards-Aligned Fields (8)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`land_use_agricultural_land_numeric`	Agricultural land percent	float	SEL	0%	1	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

Extension Fields (48) — supplemental data preserved outside core SEL/CCL schema

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.

CMR OpenFactBook - Ethnic Groups — 1 rows, 9 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	CMR
`country_name`	Country name	string	SEL	0%	1	Cameroon
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (6) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`nationality_noun_text`	nationality_noun_text	string	0%	1	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

CMR OpenFactBook - Geography — 1 rows, 60 columns

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Field details — 60 fields (type, nulls, unique, samples)

Standards-Aligned Fields (13)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`area_total_numeric`	Area sqkm	float	SEL	0%	1	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

Extension Fields (47) — supplemental data preserved outside core SEL/CCL schema

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.

CMR OpenFactBook - Government — 1 rows, 118 columns

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Field details — 118 fields (type, nulls, unique, samples)

Standards-Aligned Fields (2)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	CMR
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (116) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_name_conventional_long_form_text`	country_name_conventional_long_form_text	string	0%	1	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.

CMR OpenFactBook - Introduction — 1 rows, 7 columns

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Field details — 7 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	CMR
`country_name`	Country name	string	SEL	0%	1	Cameroon
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (4) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`background_text`	background_text	string	0%	1	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

CMR OpenFactBook - Languages — 1 rows, 8 columns

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Field details — 8 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	CMR
`country_name`	Country name	string	SEL	0%	1	Cameroon
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (5) — supplemental data preserved outside core SEL/CCL schema

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

CMR OpenFactBook - Migration — 1 rows, 9 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	CMR
`country_name`	Country name	string	SEL	0%	1	Cameroon
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (6) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`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

CMR OpenFactBook - Military And Security — 1 rows, 27 columns

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Field details — 27 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	CMR
`country_name`	Country name	string	SEL	0%	1	Cameroon
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (24) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`military_and_security_forces_text`	military_and_security_forces_text	string	0%	1	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

CMR OpenFactBook - People And Society — 1 rows, 152 columns

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Field details — 152 fields (type, nulls, unique, samples)

Standards-Aligned Fields (29)

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

Extension Fields (123) — supplemental data preserved outside core SEL/CCL schema

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.

CMR OpenFactBook - Religions — 1 rows, 26 columns

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Field details — 26 fields (type, nulls, unique, samples)

Standards-Aligned Fields (6)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (4) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`religions_text`	religions_text	string	0%	1	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

Pending (16) — awaiting mapping

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

CMR OpenFactBook - Terrorism — 1 rows, 6 columns

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Field details — 6 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	CMR
`country_name`	Country name	string	SEL	0%	1	Cameroon
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (3) — supplemental data preserved outside core SEL/CCL schema

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

CMR OpenFactBook - Transportation — 1 rows, 35 columns

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Field details — 35 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`civil_aircraft_registration_country_code_prefix_text`	Civil aircraft registration country code prefix text	string	SEL+	0%	1	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

Extension Fields (30) — supplemental data preserved outside core SEL/CCL schema

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

CMR HDX COD — Population Statistics (OCHA/UNFPA) CMR-COD_PS Census Derived Population

13 rows · 3 table(s) HDX COD — Population Statistics (OCHA/UNFPA) 0 1 2 3 15 SEL ▶

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0 Admin 0 — 1 table(s)

CMR Cod Ps - Cmr Codps (admin_0) — 1 rows, 58 columns

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Field details — 58 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

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

Pending (53) — awaiting mapping

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.

1 Admin 1 — 1 table(s)

CMR Cod Ps - Cmr Codps (admin_1) — 10 rows, 58 columns

Loading data…

Field details — 58 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

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

Pending (53) — awaiting mapping

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.

2 Admin 2 — 1 table(s)

CMR Cod Ps - Cmr Codps (admin_2) — 2 rows, 59 columns

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Field details — 59 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

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

Pending (54) — awaiting mapping

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.

CMR Google Community Mobility (2020-2022) CMR-GOOGLE-MOBILITY Mobility

10 rows · 1 table(s) Google 0 1 2 3 3 SEL 8 ext ▶

or use the per-admin-level buttons below. Free downloads return a 10-row sample. Contact us for the full pack.

1 Admin 1 — 1 table(s)

CMR Mobility by Region — 10 rows, 11 columns

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Field details — 11 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (8) — supplemental data preserved outside core SEL/CCL schema

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

CMR Ethnic Power Relations Dataset CMR-EPR Political Ethnicity

6 rows · 1 table(s) Ethnic Power Relations Dataset 0 1 2 3 1 SEL 5 CCL 2 ext ▶

or use the per-admin-level buttons below. Free downloads return a 10-row sample. Contact us for the full pack.

0 Admin 0 — 1 table(s)

CMR EPR - Groups — 6 rows, 8 columns

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Field details — 8 fields (type, nulls, unique, samples)

Standards-Aligned Fields (6)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (2) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`year`	year	integer	0%	1	2021, 2021, 2021, 2021, 2021
`group_relevance`	group_relevance	string	0%	1	, , , ,

CMR NGA GEOnet Names Server (GNS) CMR-NGA_GNS Language

6 rows · 2 table(s) NGA GEOnet Names Server (GNS) 0 1 2 3 4 SEL 12 CCL 20 ext ▶

or use the per-admin-level buttons below. Free downloads return a 10-row sample. Contact us for the full pack.

0 Admin 0 — 2 table(s)

CMR Nga Gns - Language — 5 rows, 9 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (9)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	country_code	string	SEL	0%	1	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

CMR Nga Gns - Summary — 1 rows, 27 columns

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Field details — 27 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	country_code	string	SEL	0%	1	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

Extension Fields (20) — supplemental data preserved outside core SEL/CCL schema

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

CMR Afrobarometer CMR-AFROBAROMETER Attitudes Values

5 rows · 5 table(s) Afrobarometer 0 1 2 3 5 SEL 24 CCL 20 ext ▶

or use the per-admin-level buttons below. Free downloads return a 10-row sample. Contact us for the full pack.

0 Admin 0 — 5 table(s)

CMR Afrobarometer - Economic Indicators — 1 rows, 9 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (4) — supplemental data preserved outside core SEL/CCL schema

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

CMR Afrobarometer - Gender Indicators — 1 rows, 9 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (4) — supplemental data preserved outside core SEL/CCL schema

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

CMR Afrobarometer - Governance Indicators — 1 rows, 13 columns

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Field details — 13 fields (type, nulls, unique, samples)

Standards-Aligned Fields (9)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (4) — supplemental data preserved outside core SEL/CCL schema

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

CMR Afrobarometer - Migration Indicators — 1 rows, 8 columns

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Field details — 8 fields (type, nulls, unique, samples)

Standards-Aligned Fields (4)

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

Extension Fields (4) — supplemental data preserved outside core SEL/CCL schema

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

CMR Afrobarometer - Social Trust Indicators — 1 rows, 10 columns

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Field details — 10 fields (type, nulls, unique, samples)

Standards-Aligned Fields (6)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Extension Fields (4) — supplemental data preserved outside core SEL/CCL schema

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

CMR Global Organized Crime Index CMR-OCINDEX Crime Index

1 rows · 1 table(s) GI-TOC / ENACT 0 1 2 3 ▶

or use the per-admin-level buttons below. Free downloads return a 10-row sample. Contact us for the full pack.

0 Admin 0 — 1 table(s)

CMR Organized Crime Scores 2025 — 1 rows, 35 columns

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Field details — 35 fields (type, nulls, unique, samples)

Extension Fields (35) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`oc_anti_money_laundering`	oc_anti_money_laundering	numeric	0%	1	-
`oc_arms_trafficking`	oc_arms_trafficking	numeric	0%	1	-
`oc_cannabis_trade`	oc_cannabis_trade	numeric	0%	1	-
`oc_cocaine_trade`	oc_cocaine_trade	numeric	0%	1	-
`oc_criminal_actors`	oc_criminal_actors	numeric	0%	1	-
`oc_criminal_markets`	oc_criminal_markets	numeric	0%	1	-
`oc_criminal_networks`	oc_criminal_networks	numeric	0%	1	-
`oc_criminality`	oc_criminality	numeric	0%	1	-
`oc_cyber_dependent_crimes`	oc_cyber_dependent_crimes	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_financial_crimes`	oc_financial_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_human_smuggling`	oc_human_smuggling	numeric	0%	1	-
`oc_human_trafficking`	oc_human_trafficking	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_judicial_system_and_detention`	oc_judicial_system_and_detention	numeric	0%	1	-
`oc_law_enforcement`	oc_law_enforcement	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_political_leadership_and_governance`	oc_political_leadership_and_governance	numeric	0%	1	-
`oc_prevention`	oc_prevention	numeric	0%	1	-
`oc_private_sector_actors`	oc_private_sector_actors	numeric	0%	1	-
+5 more extension fields — download the CSV/Parquet to see them all.

HERA · Human Entity Reference Atlas by Masego Inc

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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%	—

Source	Type	Access
HDX COD — Population Statistics (OCHA/UNFPA)	international_organization	bulk_download
Global Data Lab	academic	api
Google	commercial	bulk_download
GI-TOC / ENACT (Global Initiative Against Transnational Organized Crime · ENACT)	academic	bulk_download
Afrobarometer	academic	api
World Bank Open Data	international_organization	api
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
USAID DHS Program (US Agency for International Development · Demographic and Health Surveys)	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