ⓘ 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 | MRT, MRT, MRT, MRT, MRT |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 13 | Total, Adrar, Assaba, Brakna, Gorgol |
human_development_index |
Human development index | float | SEL | 0% | 83 | 0.415, 0.393, 0.389, 0.376, 0.343 |
health_index |
Health index | float | SEL | 0% | 81 | 0.586, 0.482, 0.668, 0.622, 0.579 |
education_index |
Education index | float | SEL | 0% | 86 | 0.205, 0.221, 0.164, 0.153, 0.125 |
income_index |
Income index | float | SEL | 0% | 62 | 0.597, 0.569, 0.537, 0.561, 0.556 |
life_expectancy |
Life expectancy | float | SEL | 0% | 99 | 58.09, 51.3, 63.41, 60.43, 57.62 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 98 | 3.071, 3.032, 2.105, 2.037, 1.661 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 8 | 1990, 1990, 1990, 1990, 1990 |
level |
level | string | 0% | 2 | national, subnational, subnational, subnational, subnational |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MR, MR, MR, MR, MR |
population_count |
Population count | float | SEL | 2% | 65 | 824298.0, 846167.0, 869184.0, 893423.0, 918955.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 43.611, 44.307, 45.047, 45.794, 46.581 |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 3% | 64 | 188.158401597739, 188.995146612769, 188.249348047987,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 94% | 4 | 51.2099990844727, 62.0699996948242, 65.1100006103516,... |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 63 | 253.4, 246.5, 240.0, 233.6, 226.8 |
poverty_headcount_pct |
Poverty headcount percent | float | SEL | 89% | 7 | 56.5, 50.5, 51.0, 46.7, 42.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Mauritania, Mauritania, Mauritania, Mauritania, Mauritania |
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 | MR, MR, MR, MR, MR |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 43.611, 44.307, 45.047, 45.794, 46.581 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 3% | 63 | 59.2, 58.9, 58.6, 58.4, 58.3 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 63 | 253.4, 246.5, 240.0, 233.6, 226.8 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 37 | 998.0, 961.0, 914.0, 887.0, 883.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 63 | 6.149, 6.199, 6.244, 6.312, 6.37 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 64 | 46.249, 46.602, 46.8, 47.119, 47.315 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 64 | 20.04, 19.68, 19.271, 18.857, 18.407 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 68% | 20 | 0.024, 0.027, 0.056, 0.055, 0.069 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 91% | 6 | 0.20484359562397, 0.34400001168251, 0.344300001859665,... |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 33% | 31 | 18.0, 20.0, 20.0, 21.0, 27.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 3.37824655, 3.5718379, 4.00224972, 4.03254652, 3.70429492 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Mauritania, Mauritania, Mauritania, Mauritania, Mauritania |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 100% | - | - |
women_who_are_literate |
Women who are literate | float | CCL | 0% | 14 | 76.9, 49.8, 54.7, 86.9, 31.1 |
men_who_are_literate |
Men who are literate | float | CCL | 0% | 14 | 96.0, 68.4, 64.8, 92.9, 53.4 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Mauritania, Mauritania, Mauritania, Mauritania, Mauritania |
survey_year |
survey_year | integer | 0% | 1 | 2020, 2020, 2020, 2020, 2020 |
region |
region | string | 0% | 14 | Adrar, Assaba, Brakna, Dakhlet Nouadhibou, Gorgol |
survey_id |
survey_id | string | 0% | 1 | MR2020DHS, MR2020DHS, MR2020DHS, MR2020DHS, MR2020DHS |
survey_type |
survey_type | string | 0% | 1 | DHS, DHS, DHS, DHS, DHS |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 100% | - | - |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 0% | 16 | 69.0, 41.0, 36.0, 31.0, 42.0 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 0% | 18 | 85.0, 53.0, 43.0, 38.0, 51.0 |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 0% | 19 | 54.3, 38.3, 43.1, 36.9, 39.8 |
children_underweight |
Children underweight | float | CCL | 0% | 19 | 18.8, 19.1, 15.2, 3.9, 21.7 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Mauritania, Mauritania, Mauritania, Mauritania, Mauritania |
survey_year |
survey_year | integer | 0% | 2 | 2020, 2020, 2020, 2020, 2020 |
region |
region | string | 0% | 19 | Adrar, Assaba, Brakna, Dakhlet Nouadhibou, Gorgol |
survey_id |
survey_id | string | 0% | 2 | MR2020DHS, MR2020DHS, MR2020DHS, MR2020DHS, MR2020DHS |
survey_type |
survey_type | string | 0% | 1 | DHS, DHS, DHS, DHS, DHS |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MRT |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | Mauritania |
admin_code |
Admin code | string | SEL | 0% | 1 | 45414712B39761203107443 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 1035114.8661 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 4301053 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 4.16 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MRT, MRT, MRT, MRT, MRT |
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% | 13 | Nouakchott, Hodh ech Chargui, Gorgol, Assaba, Hodh el Gharbi |
admin_code |
Admin code | string | SEL | 0% | 13 | 64602211B45475199809733, 64602211B22115476481884,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 13 | 1497.8095, 186370.1014, 13796.2057, 35873.9478, 50276.1866 |
pop_2024 |
Population count | integer | SEL | 0% | 13 | 1267947, 533985, 396531, 395548, 376228 |
pop_density_2024 |
Population density | float | SEL | 0% | 13 | 846.53, 2.87, 28.74, 11.03, 7.48 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MRT, MRT, MRT, MRT, MRT |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality, locality, locality, locality |
admin_name |
Admin name | string | SEL | 0% | 6 | Nouakchott, Nouadhibou, Kiffa, Kaédi, Zouérat |
admin_code |
Admin code | integer | SEL | 0% | 6 | 222, 41, 675, 386, 533 |
area_sqkm |
Area sqkm | float | SEL | 0% | 6 | 177.0372, 37.8101, 19.8879, 9.9433, 9.953 |
pop_2024 |
Population count | integer | SEL | 0% | 6 | 1178965, 135042, 72010, 57944, 44639 |
pop_density_2024 |
Population density | float | SEL | 0% | 6 | 6659.42, 3571.59, 3620.79, 5827.44, 4484.98 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 6 | 1625384, 177469, 89005, 61350, 50285 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 6 | 0.725, 0.761, 0.809, 0.944, 0.888 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
telephones_fixed_lines_subscriptions_per_100_inhabitants_numeric |
Fixed line subscriptions per 100 | float | SEL | 0% | 1 | 1.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 92.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .mr |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 37.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric |
Broadband subscriptions per 100 | float | SEL | 0% | 1 | 2022.0 |
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
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 | 48,000 (2022 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 48000.0 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 1 (2022 est.) |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 4.76 million (2024 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 4.76 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 92 (2024 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | 12 TV stations, 6 state-owned and 6 private; 19 radio... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 12.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 37% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 14,000 (2022 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 14000.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text | string | 0% | 1 | (2022 est.) less than 1 |
source_section |
source_section | string | 0% | 1 | Communications |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/mr.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 | 6400.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 10.767 |
population_below_poverty_line_numeric |
Poverty headcount percent | float | SEL | 0% | 1 | 31.8 |
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
economic_overview_text |
economic_overview_text | string | 0% | 1 | lower middle-income West African economy; primarily... |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $33.069 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 | 33.069 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $31.434 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 | 31.434 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $29.514 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 | 29.514 |
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 | 5.2% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | 5.2 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 6.5% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 6.5 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 6.8% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 6.8 |
real_gdp_growth_rate_note |
real_gdp_growth_rate_note | string | 0% | 1 | note: annual GDP % growth based on constant local currency |
real_gdp_per_capita_real_gdp_per_capita_2024_text |
Real gdp per capita 2024 (text) | string | 0% | 1 | $6,400 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $6,300 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 6300.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $6,100 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 6100.0 |
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 | $10.767 billion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 2.5% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 2.5 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text |
Inflation rate consumer prices 2023 (text) | string | 0% | 1 | 5% (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric |
Inflation rate consumer prices 2023 (numeric) | float | 0% | 1 | 5.0 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 9.5% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 9.5 |
inflation_rate_consumer_prices_note |
inflation_rate_consumer_prices_note | string | 0% | 1 | note: annual % change based on consumer prices |
gdp_composition_by_sector_of_origin_agriculture_text |
gdp_composition_by_sector_of_origin_agriculture_text | string | 0% | 1 | 18.6% (2024 est.) |
| +114 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 | 49.0 |
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
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 | 49% (2022 est.) |
electricity_access_electrification_urban_areas_text |
electricity_access_electrification_urban_areas_text | string | 0% | 1 | 91.6% |
electricity_access_electrification_urban_areas_numeric |
electricity_access_electrification_urban_areas_numeric | float | 0% | 1 | 91.6 |
electricity_installed_generating_capacity_text |
electricity_installed_generating_capacity_text | string | 0% | 1 | 812,000 kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 812000.0 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 1.7 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 1.7 |
electricity_imports_text |
electricity_imports_text | string | 0% | 1 | 378 million kWh (2023 est.) |
electricity_imports_numeric |
electricity_imports_numeric | float | 0% | 1 | 378.0 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 320 million kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 320.0 |
electricity_generation_sources_fossil_fuels_text |
electricity_generation_sources_fossil_fuels_text | string | 0% | 1 | 72.4% of total installed capacity (2023 est.) |
electricity_generation_sources_fossil_fuels_numeric |
electricity_generation_sources_fossil_fuels_numeric | float | 0% | 1 | 72.4 |
electricity_generation_sources_solar_text |
electricity_generation_sources_solar_text | string | 0% | 1 | 8.5% of total installed capacity (2023 est.) |
electricity_generation_sources_solar_numeric |
electricity_generation_sources_solar_numeric | float | 0% | 1 | 8.5 |
electricity_generation_sources_wind_text |
electricity_generation_sources_wind_text | string | 0% | 1 | 6.3% of total installed capacity (2023 est.) |
electricity_generation_sources_wind_numeric |
electricity_generation_sources_wind_numeric | float | 0% | 1 | 6.3 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 12.8% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 12.8 |
coal_imports_text |
coal_imports_text | string | 0% | 1 | 1 metric tons (2023 est.) |
coal_imports_numeric |
coal_imports_numeric | float | 0% | 1 | 1.0 |
petroleum_refined_petroleum_consumption_text |
petroleum_refined_petroleum_consumption_text | string | 0% | 1 | 32,000 bbl/day (2023 est.) |
petroleum_refined_petroleum_consumption_numeric |
petroleum_refined_petroleum_consumption_numeric | float | 0% | 1 | 32000.0 |
petroleum_crude_oil_estimated_reserves_text |
petroleum_crude_oil_estimated_reserves_text | string | 0% | 1 | 20 million barrels (2021 est.) |
petroleum_crude_oil_estimated_reserves_numeric |
petroleum_crude_oil_estimated_reserves_numeric | float | 0% | 1 | 20.0 |
natural_gas_proven_reserves_text |
natural_gas_proven_reserves_text | string | 0% | 1 | 28.317 billion cubic meters (2021 est.) |
natural_gas_proven_reserves_numeric |
natural_gas_proven_reserves_numeric | float | 0% | 1 | 28.317 |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_text |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_text | string | 0% | 1 | 14.135 million Btu/person (2023 est.) |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_numeric |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_numeric | float | 0% | 1 | 14.135 |
source_section |
source_section | string | 0% | 1 | Energy |
| +1 more extension field — 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 | 38.5 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 1.0 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 57.7 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 3.84 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 454000.0 |
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
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 | desertification caused in part by overgrazing,... |
international_environmental_agreements_party_to_text |
international_environmental_agreements_party_to_text | string | 0% | 1 | Biodiversity, Climate Change, Climate Change-Kyoto... |
international_environmental_agreements_signed_but_not_ratified_text |
international_environmental_agreements_signed_but_not_ratified_text | string | 0% | 1 | none of the selected agreements |
climate_text |
climate_text | string | 0% | 1 | desert; constantly hot, dry, dusty |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 38.5% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 0.4% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 0.4 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.0 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 38.1% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 38.1 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 1% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 60.5% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 60.5 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 57.7% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 3.84% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 4.86 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 4.86 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 4.86 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 | 4.86 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 35.1 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 35.1 |
waste_and_recycling_municipal_solid_waste_generated_annually_text |
waste_and_recycling_municipal_solid_waste_generated_annually_text | string | 0% | 1 | 454,000 tons (2024 est.) |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_text |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_text | string | 0% | 1 | 10% (2022 est.) |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_numeric |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_numeric | float | 0% | 1 | 10.0 |
total_water_withdrawal_municipal_text |
total_water_withdrawal_municipal_text | string | 0% | 1 | 95.4 million cubic meters (2022 est.) |
total_water_withdrawal_municipal_numeric |
total_water_withdrawal_municipal_numeric | float | 0% | 1 | 95.4 |
total_water_withdrawal_industrial_text |
total_water_withdrawal_industrial_text | string | 0% | 1 | 31.8 million cubic meters (2022 est.) |
total_water_withdrawal_industrial_numeric |
total_water_withdrawal_industrial_numeric | float | 0% | 1 | 31.8 |
total_water_withdrawal_agricultural_text |
total_water_withdrawal_agricultural_text | string | 0% | 1 | 1.223 billion cubic meters (2022 est.) |
| +5 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
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 | Mauritanian(s) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Mauritanian |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | Black Moors (Haratines - Arabic-speaking descendants of... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 40.0 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/mr.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 1030700.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 1030700.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 0.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 5002.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 754.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 915.0 |
elevation_lowest_point_numeric |
Elevation min m | float | SEL | 0% | 1 | -5.0 |
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 38.5 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 1.0 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 450.0 |
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
location_text |
location_text | string | 0% | 1 | Western Africa, bordering the North Atlantic Ocean,... |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 20 00 N, 12 00 W |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 20.0 |
map_references_text |
map_references_text | string | 0% | 1 | Africa |
area_total_text |
area_total_text | string | 0% | 1 | 1,030,700 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 1,030,700 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 0 sq km |
area_comparative_text |
area_comparative_text | string | 0% | 1 | slightly larger than three times the size of New Mexico;... |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 5,002 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | Algeria 460 km; Mali 2,236 km; Morocco 1,564 km; Senegal 742 km |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 460.0 |
coastline_text |
coastline_text | string | 0% | 1 | 754 km |
maritime_claims_territorial_sea_text |
maritime_claims_territorial_sea_text | string | 0% | 1 | 12 nm |
maritime_claims_territorial_sea_numeric |
maritime_claims_territorial_sea_numeric | float | 0% | 1 | 12.0 |
maritime_claims_contiguous_zone_text |
maritime_claims_contiguous_zone_text | string | 0% | 1 | 24 nm |
maritime_claims_contiguous_zone_numeric |
maritime_claims_contiguous_zone_numeric | float | 0% | 1 | 24.0 |
maritime_claims_exclusive_economic_zone_text |
maritime_claims_exclusive_economic_zone_text | string | 0% | 1 | 200 nm |
maritime_claims_exclusive_economic_zone_numeric |
maritime_claims_exclusive_economic_zone_numeric | float | 0% | 1 | 200.0 |
maritime_claims_continental_shelf_text |
maritime_claims_continental_shelf_text | string | 0% | 1 | 200 nm or to the edge of the continental margin |
maritime_claims_continental_shelf_numeric |
maritime_claims_continental_shelf_numeric | float | 0% | 1 | 200.0 |
climate_text |
climate_text | string | 0% | 1 | desert; constantly hot, dry, dusty |
terrain_text |
terrain_text | string | 0% | 1 | mostly barren, flat plains of the Sahara; some central hills |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Kediet Ijill 915 m |
elevation_lowest_point_text |
elevation_lowest_point_text | string | 0% | 1 | Sebkhet Te-n-Dghamcha -5 m |
elevation_mean_elevation_text |
elevation_mean_elevation_text | string | 0% | 1 | 276 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 276.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | iron ore, gypsum, copper, phosphate, diamonds, gold, oil, fish |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 38.5% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 0.4% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 0.4 |
| +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 | MRT |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name_conventional_long_form_text |
country_name_conventional_long_form_text | string | 0% | 1 | Islamic Republic of Mauritania |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Mauritania |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | Al Jumhuriyah al Islamiyah al Muritaniyah |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Muritaniyah |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | named for the ancient kingdom of Mauretania (3rd century... |
country_name_etymology_numeric |
country_name_etymology_numeric | float | 0% | 1 | 3.0 |
government_type_text |
government_type_text | string | 0% | 1 | presidential republic |
capital_name_text |
capital_name_text | string | 0% | 1 | Nouakchott |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 18 04 N, 15 58 W |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 18.0 |
capital_time_difference_text |
capital_time_difference_text | string | 0% | 1 | UTC 0 (5 hours ahead of Washington, DC, during Standard Time) |
capital_time_difference_numeric |
capital_time_difference_numeric | float | 0% | 1 | 0.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | the meaning of the name is unclear; it may derive from... |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 15 regions (wilayas, singular - wilaya); Adrar, Assaba,... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 15.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | mixed system of Islamic and French civil law |
constitution_history_text |
constitution_history_text | string | 0% | 1 | previous 1964; latest adopted 12 July 1991 |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 1964.0 |
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 | has not submitted an ICJ jurisdiction declaration;... |
citizenship_citizenship_by_birth_text |
Citizenship by birth (text) | string | 0% | 1 | no |
citizenship_citizenship_by_descent_only_text |
Citizenship by descent only (text) | string | 0% | 1 | at least one parent must be a citizen of Mauritania |
citizenship_dual_citizenship_recognized_text |
citizenship_dual_citizenship_recognized_text | string | 0% | 1 | no |
citizenship_residency_requirement_for_naturalization_text |
citizenship_residency_requirement_for_naturalization_text | string | 0% | 1 | 5 years |
citizenship_residency_requirement_for_naturalization_numeric |
citizenship_residency_requirement_for_naturalization_numeric | float | 0% | 1 | 5.0 |
suffrage_text |
suffrage_text | string | 0% | 1 | 18 years of age; universal |
suffrage_numeric |
suffrage_numeric | float | 0% | 1 | 18.0 |
executive_branch_chief_of_state_text |
executive_branch_chief_of_state_text | string | 0% | 1 | President Mohamed Ould Cheikh el GHAZOUANI (since 1 August 2019) |
executive_branch_chief_of_state_numeric |
executive_branch_chief_of_state_numeric | float | 0% | 1 | 1.0 |
executive_branch_head_of_government_text |
executive_branch_head_of_government_text | string | 0% | 1 | Prime Minister Moctar Ould DIAY (since 2 August 2024) |
| +72 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 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | The Amazigh and Bafour people were among the earliest... |
background_numeric |
background_numeric | float | 0% | 1 | 1960.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/mr.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_languages_text |
Languages (text) | string | 0% | 1 | Arabic (official and national), Pular, Soninke, Wolof... |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | كتاب حقائق العالم، المصدر الذي لا يمكن الاستغناء عنه... |
languages_note |
languages_note | string | 0% | 1 | note: the spoken Arabic in Mauritania differs... |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/mr.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
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 | 162,277 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 162277.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/mr.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
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 | Mauritanian Armed Forces (aka Armée Nationale... |
military_and_security_forces_numeric |
military_and_security_forces_numeric | float | 0% | 1 | 2025.0 |
military_expenditures_military_expenditures_2024_text |
Military expenditures 2024 (text) | string | 0% | 1 | 2.4% of GDP (2024 est.) |
military_expenditures_military_expenditures_2024_numeric |
Military expenditures 2024 (numeric) | float | 0% | 1 | 2.4 |
military_expenditures_military_expenditures_2023_text |
Military expenditures 2023 (text) | string | 0% | 1 | 2.5% of GDP (2023 est.) |
military_expenditures_military_expenditures_2023_numeric |
Military expenditures 2023 (numeric) | float | 0% | 1 | 2.5 |
military_expenditures_military_expenditures_2022_text |
Military expenditures 2022 (text) | string | 0% | 1 | 2.5% of GDP (2022 est.) |
military_expenditures_military_expenditures_2022_numeric |
Military expenditures 2022 (numeric) | float | 0% | 1 | 2.5 |
military_expenditures_military_expenditures_2021_text |
Military expenditures 2021 (text) | string | 0% | 1 | 2.4% of GDP (2021 est.) |
military_expenditures_military_expenditures_2021_numeric |
Military expenditures 2021 (numeric) | float | 0% | 1 | 2.4 |
military_expenditures_military_expenditures_2020_text |
Military expenditures 2020 (text) | string | 0% | 1 | 2.5% of GDP (2020 est.) |
military_expenditures_military_expenditures_2020_numeric |
Military expenditures 2020 (numeric) | float | 0% | 1 | 2.5 |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | estimated 17,000 active Mauritanian Armed Forces;... |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 17000.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the military's inventory is limited and made up largely... |
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 is the legal minimum age for voluntary military... |
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 | 450 (plus about 325 police) Central African Republic... |
military_deployments_numeric |
military_deployments_numeric | float | 0% | 1 | 450.0 |
military_note_text |
military_note_text | string | 0% | 1 | founded in 1960, the Mauritanian military is responsible... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 1960.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/mr.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 5202109.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 2578114.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 2623995.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 35.7 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 59.9 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 4.4 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 84.7 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 77.8 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 7.0 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 18.6 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | 2.88 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 34.01 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 5.18 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | 0.0 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 57.7 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 3.84 |
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 | 0.93 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 381.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 29.9 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 65.9 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 4.76 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 2.34 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 0.26 |
literacy_total_population_numeric |
Literacy rate percent | float | SEL | 0% | 1 | 59.5 |
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
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 | 5,202,109 (2025 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 2,578,114 |
population_female_text |
population_female_text | string | 0% | 1 | 2,623,995 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 35.7% (male 776,035/female 770,132) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 59.9% (male 1,227,347/female 1,363,938) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 4.4% (2024 est.) (male 80,308/female 110,280) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 84.7 (2025 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 77.8 (2025 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 7 (2025 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 14.3 (2025 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 14.3 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 18.6 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 21.1 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 21.1 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 23.1 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 23.1 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | 2.88% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 34.01 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 5.18 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | 0 migrant(s)/1,000 population (2025 est.) |
population_distribution_text |
population_distribution_text | string | 0% | 1 | vast areas of the country, particularly in the central,... |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 57.7% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 3.84% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 1.492 million NOUAKCHOTT (capital) (2023) |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 1.492 |
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 | 1.01 male(s)/female |
sex_ratio_0_14_years_numeric |
sex_ratio_0_14_years_numeric | float | 0% | 1 | 1.01 |
sex_ratio_15_64_years_text |
sex_ratio_15_64_years_text | string | 0% | 1 | 0.9 male(s)/female |
sex_ratio_15_64_years_numeric |
sex_ratio_15_64_years_numeric | float | 0% | 1 | 0.9 |
| +92 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 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_ethnicity_primary_label_synth |
Black Moors (Haratines - Arabic-speaking descendants of African origin who are or were enslaved by White Moors) | string | CCL | 0% | - | Black Moors (Haratines - Arabic-speaking descendants of... |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Muslim (official) 100% |
religions_numeric |
religions_numeric | float | 0% | 1 | 100.0 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/mr.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_muslim_official_pct_synth |
Muslim (official) | numeric | 0% | - | 100.0 |
composition_ethnicity_black_moors_haratines_arabic_speaking_descendants_of_african_origin_who_are_or_were_enslaved_by_white_moors_pct_synth |
Black Moors (Haratines - Arabic-speaking descendants of African origin who are or were enslaved by White Moors) | numeric | 0% | - | 40.0 |
composition_ethnicity_white_moors_of_arab_amazigh_descent_known_as_beydane_pct_synth |
White Moors (of Arab-Amazigh descent, known as Beydane) | numeric | 0% | - | 30.0 |
composition_ethnicity_sub_saharan_mauritanians_non_arabic_speaking_largely_resident_in_or_originating_from_the_senegal_river_valley_including_halpulaar_fulani_soninke_wolof_and_bambara_ethnic_groups_pct_synth |
Sub-Saharan Mauritanians (non-Arabic speaking, largely resident in or originating from the Senegal River Valley, including Halpulaar, Fulani, Soninke, Wolof, and Bambara ethnic groups) | numeric | 0% | - | 30.0 |
composition_ethnicity_primary_share_pct_synth |
Black Moors (Haratines - Arabic-speaking descendants of African origin who are or were enslaved by White Moors) | numeric | 0% | - | 40.0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
terrorist_group_s_text |
terrorist_group_s_text | string | 0% | 1 | Al-Qa'ida in the Islamic Maghreb (AQIM) |
source_section |
source_section | string | 0% | 1 | Terrorism |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/mr.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 | 5T |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 25.0 |
country_code |
Country code | string | SEL | 0% | 1 | MRT |
country_name |
Country name | string | SEL | 0% | 1 | Mauritania |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
civil_aircraft_registration_country_code_prefix_numeric |
civil_aircraft_registration_country_code_prefix_numeric | float | 0% | 1 | 5.0 |
airports_text |
airports_text | string | 0% | 1 | 25 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 3 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 3.0 |
railways_total_text |
railways_total_text | string | 0% | 1 | 728 km (2014) |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 728.0 |
railways_standard_gauge_text |
railways_standard_gauge_text | string | 0% | 1 | 728 km (2014) 1.435-m gauge |
railways_standard_gauge_numeric |
railways_standard_gauge_numeric | float | 0% | 1 | 728.0 |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 11 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 11.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | general cargo 2, other 9 |
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 | 2 (2024) |
ports_total_ports_numeric |
ports_total_ports_numeric | float | 0% | 1 | 2.0 |
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 | 1 |
ports_small_numeric |
ports_small_numeric | float | 0% | 1 | 1.0 |
ports_very_small_text |
ports_very_small_text | float | 0% | 1 | 0 |
ports_very_small_numeric |
ports_very_small_numeric | float | 0% | 1 | 0.0 |
ports_ports_with_oil_terminals_text |
Ports with oil terminals (text) | float | 0% | 1 | 2 |
ports_ports_with_oil_terminals_numeric |
Ports with oil terminals (numeric) | float | 0% | 1 | 2.0 |
ports_key_ports_text |
ports_key_ports_text | string | 0% | 1 | Nouadhibou, Nouakchott |
source_section |
source_section | string | 0% | 1 | Transportation |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/mr.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 1 | MR |
region_name |
Region name | string | SEL | 0% | 1 | Mauritania |
F_TL |
Female population | string | SEL | 0% | 1 | 2,199,480 |
M_TL |
Male population | string | SEL | 0% | 1 | 2,172,559 |
T_TL |
Total population | string | SEL | 0% | 1 | 4,372,038 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_0 |
year |
Reference year | integer | 0% | 1 | 2022 |
year |
year | integer | 0% | 1 | 2022 |
F_00_04 |
Female population age 0-4 | string | 0% | 1 | 300,948 |
F_05_09 |
Female population age 5-9 | string | 0% | 1 | 271,299 |
F_10_14 |
Female population age 10-14 | string | 0% | 1 | 281,680 |
F_15_19 |
Female population age 15-19 | string | 0% | 1 | 243,985 |
F_20_24 |
Female population age 20-24 | string | 0% | 1 | 205,847 |
F_25_29 |
Female population age 25-29 | string | 0% | 1 | 175,660 |
F_30_34 |
Female population age 30-34 | string | 0% | 1 | 149,406 |
F_35_39 |
Female population age 35-39 | string | 0% | 1 | 127,388 |
F_40_44 |
Female population age 40-44 | string | 0% | 1 | 105,471 |
F_45_49 |
Female population age 45-49 | string | 0% | 1 | 87,495 |
F_50_54 |
Female population age 50-54 | string | 0% | 1 | 71,249 |
F_55_59 |
Female population age 55-59 | string | 0% | 1 | 56,291 |
F_60_64 |
Female population age 60-64 | string | 0% | 1 | 43,039 |
F_65_69 |
Female population age 65-69 | string | 0% | 1 | 31,104 |
F_70_74 |
Female population age 70-74 | string | 0% | 1 | 20,615 |
F_75_79 |
Female population age 75-79 | string | 0% | 1 | 13,058 |
F_80Plus |
F_80Plus | string | 0% | 1 | 14,940 |
M_00_04 |
Male population age 0-4 | string | 0% | 1 | 314,834 |
M_05_09 |
Male population age 5-9 | string | 0% | 1 | 285,237 |
M_10_14 |
Male population age 10-14 | string | 0% | 1 | 297,441 |
M_15_19 |
Male population age 15-19 | string | 0% | 1 | 249,225 |
M_20_24 |
Male population age 20-24 | string | 0% | 1 | 201,404 |
M_25_29 |
Male population age 25-29 | string | 0% | 1 | 166,185 |
M_30_34 |
Male population age 30-34 | string | 0% | 1 | 136,579 |
M_35_39 |
Male population age 35-39 | string | 0% | 1 | 114,528 |
M_40_44 |
Male population age 40-44 | string | 0% | 1 | 93,075 |
M_45_49 |
Male population age 45-49 | string | 0% | 1 | 77,194 |
| +24 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% | 13 | MR01, MR02, MR03, MR04, MR05 |
region_name |
Region name | string | SEL | 0% | 13 | Adrar, Assaba, Brakna, Dakhlet-Nouadhibou, Gorgol |
F_TL |
Female population | integer | SEL | 0% | 13 | 31242, 215455, 176957, 66282, 201471 |
M_TL |
Male population | integer | SEL | 0% | 13 | 29601, 189935, 157794, 91539, 186991 |
T_TL |
Total population | integer | SEL | 0% | 13 | 60843, 405389, 334750, 157821, 388461 |
| 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 | 2022, 2022, 2022, 2022, 2022 |
year |
year | integer | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
F_00_04 |
Female population age 0-4 | integer | 0% | 13 | 3848, 31425, 25363, 8499, 31768 |
F_05_09 |
Female population age 5-9 | integer | 0% | 13 | 3540, 27634, 22582, 7964, 27712 |
F_10_14 |
Female population age 10-14 | integer | 0% | 13 | 3761, 27834, 23085, 8145, 27581 |
F_15_19 |
Female population age 15-19 | integer | 0% | 13 | 3309, 23592, 19605, 7041, 22958 |
F_20_24 |
Female population age 20-24 | integer | 0% | 13 | 2803, 19338, 15890, 6489, 18274 |
F_25_29 |
Female population age 25-29 | integer | 0% | 13 | 2406, 16195, 13169, 6512, 14859 |
F_30_34 |
Female population age 30-34 | integer | 0% | 13 | 2096, 13826, 11003, 5491, 12142 |
F_35_39 |
Female population age 35-39 | integer | 0% | 13 | 1860, 11870, 9404, 4294, 10151 |
F_40_44 |
Female population age 40-44 | integer | 0% | 13 | 1630, 9893, 7888, 3811, 8294 |
F_45_49 |
Female population age 45-49 | integer | 0% | 13 | 1437, 8352, 6767, 2487, 6930 |
F_50_54 |
Female population age 50-54 | integer | 0% | 13 | 1238, 6756, 5686, 2204, 5632 |
F_55_59 |
Female population age 55-59 | integer | 0% | 13 | 1023, 5468, 4730, 1236, 4537 |
F_60_64 |
Female population age 60-64 | integer | 0% | 13 | 784, 4291, 3881, 968, 3539 |
F_65_69 |
Female population age 65-69 | integer | 0% | 13 | 574, 3276, 2946, 466, 2651 |
F_70_74 |
Female population age 70-74 | integer | 0% | 13 | 374, 2330, 2003, 289, 1825 |
F_75_79 |
Female population age 75-79 | integer | 0% | 13 | 227, 1672, 1270, 175, 1239 |
F_80Plus |
F_80Plus | integer | 0% | 13 | 333, 1706, 1683, 208, 1380 |
M_00_04 |
Male population age 0-4 | integer | 0% | 13 | 3818, 33876, 27013, 8758, 33298 |
M_05_09 |
Male population age 5-9 | integer | 0% | 13 | 3585, 29211, 23729, 8285, 28937 |
M_10_14 |
Male population age 10-14 | integer | 0% | 13 | 3903, 28341, 23644, 9086, 28411 |
M_15_19 |
Male population age 15-19 | integer | 0% | 13 | 3329, 21872, 18613, 9131, 22218 |
M_20_24 |
Male population age 20-24 | integer | 0% | 13 | 2652, 15331, 13366, 10712, 16018 |
M_25_29 |
Male population age 25-29 | integer | 0% | 13 | 2187, 11552, 10111, 10489, 12096 |
M_30_34 |
Male population age 30-34 | integer | 0% | 13 | 1826, 9098, 7760, 8731, 9266 |
M_35_39 |
Male population age 35-39 | integer | 0% | 13 | 1595, 7688, 6392, 6893, 7558 |
M_40_44 |
Male population age 40-44 | integer | 0% | 13 | 1355, 6623, 5267, 5937, 6120 |
M_45_49 |
Male population age 45-49 | integer | 0% | 13 | 1190, 5761, 4537, 4192, 5171 |
| +24 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
glottocode |
Glottocode | string | CCL | 0% | 10 | amer1248, hass1238, imer1236, koyr1240, maas1239 |
name |
Name | string | CCL | 0% | 10 | American Sign Language, Hassaniyya, Imeraguen, Koyra... |
iso639_3 |
Iso639 3 | string | CCL | 0% | 10 | ase, mey, ime, khq, ffm |
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% | 6 | sign1238, afro1255, book1242, song1307, atla1278 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 0% | 9 | amer1258, west3017, book1242, nort2822, fula1264 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 8 | ['BB', 'BF', 'BJ', 'BO', 'CA', 'CD', 'CF', 'CI', 'CN',... |
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% | 4 | 2, 0, 0, 2, 2 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 0% | 10 | 33.8117, 18.29, 18.37331, 16.192, 11.1324 |
longitude |
longitude | float | 0% | 10 | -81.6121, -14.11, -16.34726, -3.73962, -3.64763 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 6 | Nouakchott, Nouadhibou, Fassala, Kiffa, Kaédi |
country_code |
Country code | string | SEL | 0% | 1 | MRT, MRT, MRT, MRT, MRT |
population |
Population count | integer | SEL | 0% | 6 | 1625384, 177469, 114618, 89005, 61350 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 6 | 222, 41, 814, 675, 386 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Mauritania, Mauritania, Mauritania, Mauritania, Mauritania |
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 | MRT |
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 | MRT |
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 | MRT |
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 | MRT |
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 | MRT |
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 |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | MRT, MRT, MRT, MRT |
gns_language_code |
gns_language_code | string | CCL | 0% | 4 | ara, fra, eng, deu |
gns_language_name |
gns_language_name | string | CCL | 0% | 4 | Arabic, French, English, German |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 4 | 2557, 392, 23, 1 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 4 | 86.0074, 13.1853, 0.7736, 0.0336 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 2 | 1269, 0, 0, 0 |
gns_dominant_script_code |
gns_dominant_script_code | string | CCL | 0% | 2 | Arab, , , |
gns_dominant_script_name |
gns_dominant_script_name | string | CCL | 0% | 2 | Arabic, , , |
gns_script_count |
gns_script_count | integer | CCL | 0% | 2 | 1, 0, 0, 0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | MRT |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Mauritania |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 4 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 1 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 99.9919 |
gns_non_roman_name_count |
gns_non_roman_name_count | integer | CCL | 0% | 1 | 1269 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
gns_name_count |
gns_name_count | integer | 0% | 1 | 24547 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 16195 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 24545 |
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_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 6366 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 3797 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 5410 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 3006 |
gns_name_count_populated_places |
gns_name_count_populated_places | integer | 0% | 1 | 9936 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 7679 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 1281 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 701 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 208 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 16 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 1322 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 976 |
gns_name_count_vegetation |
gns_name_count_vegetation | integer | 0% | 1 | 19 |
gns_feature_count_vegetation |
gns_feature_count_vegetation | integer | 0% | 1 | 16 |
gns_name_count_transportation_networks |
gns_name_count_transportation_networks | integer | 0% | 1 | 5 |
gns_feature_count_transportation_networks |
gns_feature_count_transportation_networks | integer | 0% | 1 | 4 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MRT, MRT, MRT |
society_id |
Society id | string | CCL | 0% | 3 | Cc1, Cc19, Cc20 |
society_name |
Society name | string | CCL | 0% | 3 | Regeibat, Trarza, Zenaga |
language_glottocode |
Language glottocode | string | CCL | 0% | 2 | hass1238, hass1238, zena1248 |
language_name |
Language name | string | CCL | 0% | 1 | , , |
kinship_system |
Kinship system | string | CCL | 0% | 3 | EA001:0; EA002:1; EA003:0; EA004:7; EA005:2, EA001:0;... |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 2 | EA006:1; EA007:8; EA008:7; EA009:2; EA010:8, EA006:1;... |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 3 | EA028:6; EA029:4; EA030:2; EA031:NA; EA032:4, EA028:6;... |
political_complexity |
Political complexity | string | CCL | 0% | 2 | EA033:4; EA034:4; EA035:NA, EA033:4; EA034:4; EA035:NA,... |
religion_importance |
Religion importance | string | CCL | 0% | 2 | EA034:4; EA112:8, EA034:4; EA112:NA, EA034:4; EA112:NA |
residence_pattern |
Residence pattern | string | CCL | 0% | 1 | EA011:1; EA012:8; EA013:9, EA011:1; EA012:8; EA013:9,... |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Mauritania, Mauritania, Mauritania |
dataset |
dataset | string | 0% | 1 | EA, EA, EA |
region |
region | string | 0% | 1 | , , |
latitude |
latitude | float | 0% | 2 | 22.0, 18.0, 18.0 |
longitude |
longitude | float | 0% | 3 | -13.0, -15.0, -8.0 |
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 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MRT, MRT, MRT |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 3 | Haratins (Black Moors), White Moors (Beydan), Black Africans |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 3 | JUNIOR PARTNER, SENIOR PARTNER, POWERLESS |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 2 | 0.4, 0.3, 0.3 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 3 | 43502000, 43501000, 43503000 |
regional_autonomy |
Regional autonomy | string | CCL | 0% | 1 | false, false, false |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 1 | 2021, 2021, 2021 |
group_relevance |
group_relevance | string | 0% | 1 | , , |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
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 | MRT |
source |
source | string | 0% | 1 | Global Organized Crime Index |
source_url |
source_url | string | 0% | 1 | https://ocindex.net/ |
year |
year | integer | 0% | 1 | 2025 |
license |
license | string | 0% | 1 | Creative Commons (GI-TOC / ENACT) |
oc_anti_money_laundering_rank |
oc_anti_money_laundering_rank | integer | 0% | 1 | 98 |
oc_anti_money_laundering_2023 |
oc_anti_money_laundering_2023 | float | 0% | 1 | 4.5 |
oc_anti_money_laundering_2021 |
oc_anti_money_laundering_2021 | integer | 0% | 1 | 4 |
oc_anti_money_laundering_2019 |
oc_anti_money_laundering_2019 | integer | 0% | 1 | 3 |
oc_arms_trafficking_rank |
oc_arms_trafficking_rank | integer | 0% | 1 | 120 |
oc_arms_trafficking_2023 |
oc_arms_trafficking_2023 | float | 0% | 1 | 3.5 |
oc_arms_trafficking_2021 |
oc_arms_trafficking_2021 | integer | 0% | 1 | 4 |
oc_arms_trafficking_2019 |
oc_arms_trafficking_2019 | float | 0% | 1 | 3.5 |
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 | float | 0% | 1 | 6.5 |
oc_cannabis_trade_2019 |
oc_cannabis_trade_2019 | integer | 0% | 1 | 6 |
oc_cocaine_trade_rank |
oc_cocaine_trade_rank | integer | 0% | 1 | 89 |
oc_cocaine_trade_2023 |
oc_cocaine_trade_2023 | float | 0% | 1 | 4.5 |
oc_cocaine_trade_2021 |
oc_cocaine_trade_2021 | float | 0% | 1 | 4.5 |
oc_cocaine_trade_2019 |
oc_cocaine_trade_2019 | integer | 0% | 1 | 5 |
oc_criminal_actors_rank |
oc_criminal_actors_rank | integer | 0% | 1 | 136 |
oc_criminal_actors_2023 |
oc_criminal_actors_2023 | float | 0% | 1 | 4.5 |
oc_criminal_actors_2021 |
oc_criminal_actors_2021 | float | 0% | 1 | 4.75 |
oc_criminal_actors_2019 |
oc_criminal_actors_2019 | float | 0% | 1 | 5.5 |
oc_criminal_markets_rank |
oc_criminal_markets_rank | integer | 0% | 1 | 122 |
oc_criminal_markets_2023 |
oc_criminal_markets_2023 | float | 0% | 1 | 4.27 |
oc_criminal_markets_2021 |
oc_criminal_markets_2021 | integer | 0% | 1 | 4 |
oc_criminal_markets_2019 |
oc_criminal_markets_2019 | float | 0% | 1 | 3.7 |
oc_criminal_networks_rank |
oc_criminal_networks_rank | integer | 0% | 1 | 105 |
| +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 |
|---|---|---|---|
| Arabic (ara) | 2,557 | 86.0% | Arabic |
| French (fra) | 392 | 13.2% | — |
| English (eng) | 23 | 0.8% | — |
16,195 distinct features ·
4 languages ·
1 script ·
1,269 names in non-Roman script ·
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.