ⓘ 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 | URY, URY, URY, URY, URY |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 8 | Total, Centro (Durazno and Tacuarembo), Centro Sur... |
human_development_index |
Human development index | float | SEL | 0% | 66 | 0.758, 0.718, 0.754, 0.757, 0.72 |
health_index |
Health index | float | SEL | 0% | 9 | 0.815, 0.815, 0.815, 0.815, 0.815 |
education_index |
Education index | float | SEL | 0% | 78 | 0.72, 0.626, 0.712, 0.716, 0.632 |
income_index |
Income index | float | SEL | 0% | 56 | 0.742, 0.725, 0.74, 0.744, 0.724 |
life_expectancy |
Life expectancy | float | SEL | 0% | 13 | 72.99, 72.99, 72.99, 72.99, 72.99 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 91 | 10.81, 8.787, 9.699, 10.34, 9.833 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 13 | 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 | UY, UY, UY, UY, UY |
population_count |
Population count | float | SEL | 2% | 65 | 2529957.0, 2562044.0, 2593298.0, 2623766.0, 2653180.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 63 | 67.683, 67.81, 67.911, 68.023, 68.112 |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 2% | 65 | 491.031760304596, 603.966513233705, 659.393716891716,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 68% | 21 | 93.8600006103516, 95.379997253418, 96.7799987792969,... |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 63.3, 62.1, 60.6, 59.3, 58.3 |
poverty_headcount_pct |
Poverty headcount percent | float | SEL | 94% | 4 | 11.6, 9.9, 19.7, 17.3 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Uruguay, Uruguay, Uruguay, Uruguay, Uruguay |
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 | UY, UY, UY, UY, UY |
life_expectancy |
Life expectancy | float | SEL | 3% | 63 | 67.683, 67.81, 67.911, 68.023, 68.112 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 18% | 46 | 22.7, 23.9, 25.5, 26.6, 26.3 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 63.3, 62.1, 60.6, 59.3, 58.3 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 21 | 41.0, 41.0, 41.0, 39.0, 36.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 62 | 2.827, 2.846, 2.866, 2.884, 2.863 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 64 | 21.797, 21.814, 21.826, 21.81, 21.48 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 62 | 9.766, 9.724, 9.702, 9.681, 9.668 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 73% | 18 | 1.064, 1.136, 1.093, 1.111, 1.997 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 61% | 21 | 5.5118203163147, 5.91270017623901, 5.00180006027222,... |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 32% | 18 | 53.0, 57.0, 67.0, 73.0, 62.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 9.17182446, 9.75702, 9.64023018, 9.57667351, 8.26618195 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Uruguay, Uruguay, Uruguay, Uruguay, Uruguay |
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 | 0% | 1 | URY |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | Uruguay |
admin_code |
Admin code | string | SEL | 0% | 1 | 38943091B55852499818945 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 176833.7916 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 3402029 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 19.24 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | URY, URY, URY, URY, URY |
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% | 19 | Montevideo, Canelones, Maldonado, Salto, Colonia |
admin_code |
Admin code | string | SEL | 0% | 19 | 27058087B97113143242340, 27058087B19329078127106,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 19 | 528.5791, 4524.3804, 4804.1806, 14182.3809, 6117.0115 |
pop_2024 |
Population count | integer | SEL | 0% | 19 | 1316024, 597876, 190265, 129595, 124738 |
pop_density_2024 |
Population density | float | SEL | 0% | 19 | 2489.74, 132.15, 39.6, 9.14, 20.39 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | URY, URY, URY, URY, URY |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality, locality, locality, locality |
admin_name |
Admin name | string | SEL | 0% | 8 | Montevideo, Las Piedras, Salto, Ciudad de la Costa, Maldonado |
admin_code |
Admin code | integer | SEL | 0% | 8 | 804, 670, 36, 931, 1051 |
area_sqkm |
Area sqkm | float | SEL | 0% | 8 | 236.447, 27.9379, 21.932, 47.888, 35.9157 |
pop_2024 |
Population count | integer | SEL | 0% | 8 | 1292415, 117730, 91683, 81368, 79865 |
pop_density_2024 |
Population density | float | SEL | 0% | 8 | 5465.98, 4213.99, 4180.33, 1699.13, 2223.68 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 8 | 1219222, 106086, 96048, 99151, 124858 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 8 | 1.06, 1.11, 0.955, 0.821, 0.64 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 1 | UY |
region_name |
Region name | string | SEL | 0% | 1 | Uruguay |
F_TL |
Female population | integer | SEL | 0% | 1 | 1835590 |
M_TL |
Male population | integer | SEL | 0% | 1 | 1730941 |
T_TL |
Total population | integer | SEL | 0% | 1 | 3566539 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_0 |
year |
Reference year | integer | 0% | 1 | 2023 |
year |
year | integer | 0% | 1 | 2023 |
F_00_04 |
Female population age 0-4 | integer | 0% | 1 | 109353 |
F_05_09 |
Female population age 5-9 | integer | 0% | 1 | 111362 |
F_10_14 |
Female population age 10-14 | integer | 0% | 1 | 113779 |
F_15_19 |
Female population age 15-19 | integer | 0% | 1 | 118513 |
F_20_24 |
Female population age 20-24 | integer | 0% | 1 | 126940 |
F_25_29 |
Female population age 25-29 | integer | 0% | 1 | 133528 |
F_30_34 |
Female population age 30-34 | integer | 0% | 1 | 126151 |
F_35_39 |
Female population age 35-39 | integer | 0% | 1 | 120751 |
F_40_44 |
Female population age 40-44 | integer | 0% | 1 | 119927 |
F_45_49 |
Female population age 45-49 | integer | 0% | 1 | 120000 |
F_50_54 |
Female population age 50-54 | integer | 0% | 1 | 109359 |
F_55_59 |
Female population age 55-59 | integer | 0% | 1 | 103061 |
F_60_64 |
Female population age 60-64 | integer | 0% | 1 | 101323 |
F_65_69 |
Female population age 65-69 | integer | 0% | 1 | 90463 |
F_70_74 |
Female population age 70-74 | integer | 0% | 1 | 74063 |
F_75_79 |
Female population age 75-79 | integer | 0% | 1 | 60590 |
F_80_84 |
Female population age 80-84 | integer | 0% | 1 | 45340 |
F_85_89 |
Female population age 85-89 | integer | 0% | 1 | 30003 |
F_90Plus |
F_90Plus | integer | 0% | 1 | 20911 |
M_00_04 |
Male population age 0-4 | integer | 0% | 1 | 114656 |
M_05_09 |
Male population age 5-9 | integer | 0% | 1 | 116722 |
M_10_14 |
Male population age 10-14 | integer | 0% | 1 | 119036 |
M_15_19 |
Male population age 15-19 | integer | 0% | 1 | 123774 |
M_20_24 |
Male population age 20-24 | integer | 0% | 1 | 131938 |
M_25_29 |
Male population age 25-29 | integer | 0% | 1 | 136950 |
M_30_34 |
Male population age 30-34 | integer | 0% | 1 | 127608 |
M_35_39 |
Male population age 35-39 | integer | 0% | 1 | 121053 |
| +30 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% | 19 | UY01, UY02, UY03, UY04, UY05 |
region_name |
Region name | string | SEL | 0% | 19 | Artigas, Canelones, Cerro Largo, Colonia, Durazno |
F_TL |
Female population | integer | SEL | 0% | 19 | 37030, 318429, 45781, 67173, 29818 |
M_TL |
Male population | integer | SEL | 0% | 19 | 36269, 307268, 43881, 65343, 29126 |
T_TL |
Total population | integer | SEL | 0% | 19 | 73299, 625697, 89662, 132517, 58944 |
| 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 | 2023, 2023, 2023, 2023, 2023 |
year |
year | integer | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
F_00_04 |
Female population age 0-4 | integer | 0% | 19 | 2367, 19216, 2799, 3855, 1876 |
F_05_09 |
Female population age 5-9 | integer | 0% | 19 | 2517, 19453, 2925, 4099, 1981 |
F_10_14 |
Female population age 10-14 | integer | 0% | 19 | 2633, 19991, 3074, 4371, 2017 |
F_15_19 |
Female population age 15-19 | integer | 0% | 19 | 2399, 21325, 3142, 4094, 1974 |
F_20_24 |
Female population age 20-24 | integer | 0% | 19 | 2569, 22205, 3077, 3891, 1978 |
F_25_29 |
Female population age 25-29 | integer | 0% | 19 | 2808, 23204, 3323, 4452, 2217 |
F_30_34 |
Female population age 30-34 | integer | 0% | 19 | 2403, 22454, 2954, 4399, 1985 |
F_35_39 |
Female population age 35-39 | integer | 0% | 19 | 2272, 21498, 2716, 4374, 1884 |
F_40_44 |
Female population age 40-44 | integer | 0% | 19 | 2230, 21190, 2926, 4459, 1943 |
F_45_49 |
Female population age 45-49 | integer | 0% | 19 | 2198, 21701, 3053, 4320, 1939 |
F_50_54 |
Female population age 50-54 | integer | 0% | 19 | 2223, 19454, 2779, 4166, 1752 |
F_55_59 |
Female population age 55-59 | integer | 0% | 19 | 2284, 18082, 2577, 3985, 1701 |
F_60_64 |
Female population age 60-64 | integer | 0% | 19 | 2101, 17267, 2533, 3892, 1608 |
F_65_69 |
Female population age 65-69 | integer | 0% | 19 | 1812, 15166, 2257, 3519, 1411 |
F_70_74 |
Female population age 70-74 | integer | 0% | 19 | 1451, 12058, 1949, 2981, 1170 |
F_75_79 |
Female population age 75-79 | integer | 0% | 19 | 1130, 9657, 1554, 2438, 957 |
F_80_84 |
Female population age 80-84 | integer | 0% | 19 | 787, 7091, 1087, 1835, 715 |
F_85_89 |
Female population age 85-89 | integer | 0% | 18 | 510, 4491, 658, 1226, 441 |
F_90Plus |
F_90Plus | integer | 0% | 19 | 327, 2917, 390, 809, 258 |
M_00_04 |
Male population age 0-4 | integer | 0% | 19 | 2492, 20217, 2958, 4013, 1929 |
M_05_09 |
Male population age 5-9 | integer | 0% | 19 | 2661, 20503, 3117, 4255, 2022 |
M_10_14 |
Male population age 10-14 | integer | 0% | 18 | 2804, 20877, 3308, 4464, 2078 |
M_15_19 |
Male population age 15-19 | integer | 0% | 19 | 2706, 22465, 3275, 4396, 2101 |
M_20_24 |
Male population age 20-24 | integer | 0% | 19 | 2679, 23207, 3303, 4297, 2215 |
M_25_29 |
Male population age 25-29 | integer | 0% | 19 | 2800, 23825, 3384, 4635, 2272 |
M_30_34 |
Male population age 30-34 | integer | 0% | 19 | 2429, 22893, 2893, 4488, 1988 |
M_35_39 |
Male population age 35-39 | integer | 0% | 19 | 2269, 21586, 2641, 4517, 1902 |
| +30 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | UY, UY, UY, UY, UY |
admin_level |
Admin level | integer | SEL | 0% | 1 | 1, 1, 1, 1, 1 |
iso3 |
Country code | string | SEL | 0% | 1 | URY, URY, URY, URY, URY |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
retail |
retail | float | 0% | 19 | 5.27, -22.26, -11.67, -21.22, -2.58 |
grocery |
grocery | float | 0% | 19 | 22.99, -2.77, 12.01, -10.79, 14.49 |
parks |
parks | float | 0% | 19 | -33.23, -41.02, -14.31, -44.06, -10.26 |
transit |
transit | float | 0% | 19 | -7.17, -29.84, -10.32, -45.72, -7.45 |
workplaces |
workplaces | float | 0% | 19 | 8.35, -0.68, 5.73, -0.86, 10.43 |
residential |
residential | float | 0% | 18 | 1.17, 5.54, 3.31, 5.11, 1.17 |
region |
region | string | 0% | 19 | Artigas Department, Canelones Department, Cerro Largo... |
observation_count |
observation_count | integer | 0% | 8 | 950, 974, 967, 974, 949 |
| 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 | 36.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 146.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .uy |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 90.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric |
Broadband subscriptions per 100 | float | SEL | 0% | 1 | 32.0 |
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
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 | 1.205 million (2023 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 1.205 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 36 (2023 est.) |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 4.93 million (2024 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 4.93 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 146 (2024 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | mix of privately owned and state-run broadcast media;... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 100.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 90% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 1.1 million (2023 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 1.1 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 32 (2023 est.) |
source_section |
source_section | string | 0% | 1 | Communications |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/uy.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 | 32000.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 80.962 |
population_below_poverty_line_numeric |
Poverty headcount percent | float | SEL | 0% | 1 | 10.1 |
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
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 | high-income, export-oriented South American economy;... |
economic_overview_numeric |
economic_overview_numeric | float | 0% | 1 | 2019.0 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $108.502 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 | 108.502 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $105.231 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 | 105.231 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $104.456 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 | 104.456 |
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 | 3.1% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | 3.1 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 0.7% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 0.7 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 4.5% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 4.5 |
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 | $32,000 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $31,100 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 31100.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $30,800 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 30800.0 |
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 | $80.962 billion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 4.8% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 4.8 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text |
Inflation rate consumer prices 2023 (text) | string | 0% | 1 | 5.9% (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric |
Inflation rate consumer prices 2023 (numeric) | float | 0% | 1 | 5.9 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 9.1% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 9.1 |
inflation_rate_consumer_prices_note |
inflation_rate_consumer_prices_note | string | 0% | 1 | note: annual % change based on consumer prices |
| +120 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
electricity_access_electrification_total_population_numeric |
Electricity access percent | float | SEL | 0% | 1 | 100.0 |
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
electricity_access_electrification_total_population_text |
electricity_access_electrification_total_population_text | string | 0% | 1 | 100% (2022 est.) |
electricity_installed_generating_capacity_text |
electricity_installed_generating_capacity_text | string | 0% | 1 | 5.682 million kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 5.682 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 9.826 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 9.826 |
electricity_exports_text |
electricity_exports_text | string | 0% | 1 | 2 billion kWh (2023 est.) |
electricity_exports_numeric |
electricity_exports_numeric | float | 0% | 1 | 2.0 |
electricity_imports_text |
electricity_imports_text | string | 0% | 1 | 84 million kWh (2023 est.) |
electricity_imports_numeric |
electricity_imports_numeric | float | 0% | 1 | 84.0 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 1.136 billion kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 1.136 |
electricity_generation_sources_fossil_fuels_text |
electricity_generation_sources_fossil_fuels_text | string | 0% | 1 | 8% of total installed capacity (2023 est.) |
electricity_generation_sources_fossil_fuels_numeric |
electricity_generation_sources_fossil_fuels_numeric | float | 0% | 1 | 8.0 |
electricity_generation_sources_solar_text |
electricity_generation_sources_solar_text | string | 0% | 1 | 3.8% of total installed capacity (2023 est.) |
electricity_generation_sources_solar_numeric |
electricity_generation_sources_solar_numeric | float | 0% | 1 | 3.8 |
electricity_generation_sources_wind_text |
electricity_generation_sources_wind_text | string | 0% | 1 | 37% of total installed capacity (2023 est.) |
electricity_generation_sources_wind_numeric |
electricity_generation_sources_wind_numeric | float | 0% | 1 | 37.0 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 27.3% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 27.3 |
electricity_generation_sources_biomass_and_waste_text |
electricity_generation_sources_biomass_and_waste_text | string | 0% | 1 | 23.9% of total installed capacity (2023 est.) |
electricity_generation_sources_biomass_and_waste_numeric |
electricity_generation_sources_biomass_and_waste_numeric | float | 0% | 1 | 23.9 |
coal_consumption_text |
coal_consumption_text | string | 0% | 1 | 8,000 metric tons (2023 est.) |
coal_consumption_numeric |
coal_consumption_numeric | float | 0% | 1 | 8000.0 |
coal_imports_text |
coal_imports_text | string | 0% | 1 | 13,000 metric tons (2023 est.) |
coal_imports_numeric |
coal_imports_numeric | float | 0% | 1 | 13000.0 |
petroleum_total_petroleum_production_text |
petroleum_total_petroleum_production_text | string | 0% | 1 | 400 bbl/day (2023 est.) |
petroleum_total_petroleum_production_numeric |
petroleum_total_petroleum_production_numeric | float | 0% | 1 | 400.0 |
petroleum_refined_petroleum_consumption_text |
petroleum_refined_petroleum_consumption_text | string | 0% | 1 | 50,000 bbl/day (2023 est.) |
petroleum_refined_petroleum_consumption_numeric |
petroleum_refined_petroleum_consumption_numeric | float | 0% | 1 | 50000.0 |
natural_gas_consumption_text |
natural_gas_consumption_text | string | 0% | 1 | 90.018 million cubic meters (2023 est.) |
| +7 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 81.4 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 11.4 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 95.8 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 0.4 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 1.26 |
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
environmental_issues_text |
environmental_issues_text | string | 0% | 1 | water pollution from meat-packing, tannery industries;... |
international_environmental_agreements_party_to_text |
international_environmental_agreements_party_to_text | string | 0% | 1 | Antarctic-Environmental Protection, Antarctic-Marine... |
international_environmental_agreements_signed_but_not_ratified_text |
international_environmental_agreements_signed_but_not_ratified_text | string | 0% | 1 | Marine Dumping-London Convention, Marine Life Conservation |
climate_text |
climate_text | string | 0% | 1 | warm temperate; freezing temperatures almost unknown |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 81.4% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 12.6% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 12.6 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.2% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.2 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 68.6% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 68.6 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 11.4% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 7.3% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 7.3 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 95.8% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 0.4% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 6.896 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 6.896 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 39,000 metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_numeric |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_numeric | float | 0% | 1 | 39000.0 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 6.681 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 | 6.681 |
carbon_dioxide_emissions_from_consumed_natural_gas_text |
carbon_dioxide_emissions_from_consumed_natural_gas_text | string | 0% | 1 | 177,000 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 | 177000.0 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 8.5 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 8.5 |
methane_emissions_energy_text |
methane_emissions_energy_text | string | 0% | 1 | 18.1 kt (2022-2024 est.) |
methane_emissions_energy_numeric |
methane_emissions_energy_numeric | float | 0% | 1 | 18.1 |
methane_emissions_agriculture_text |
methane_emissions_agriculture_text | string | 0% | 1 | 730.6 kt (2019-2021 est.) |
methane_emissions_agriculture_numeric |
methane_emissions_agriculture_numeric | float | 0% | 1 | 730.6 |
| +21 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 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
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 | Uruguayan(s) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Uruguayan |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | White 87.7%, Black 4.6%, Indigenous 2.4%, other 0.3%,... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 87.7 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/uy.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 176215.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 175015.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 1200.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 1591.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 660.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 514.0 |
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 | 81.4 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 11.4 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 2230.0 |
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
location_text |
location_text | string | 0% | 1 | Southern South America, bordering the South Atlantic... |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 33 00 S, 56 00 W |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 33.0 |
map_references_text |
map_references_text | string | 0% | 1 | South America |
area_total_text |
area_total_text | string | 0% | 1 | 176,215 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 175,015 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 1,200 sq km |
area_comparative_text |
area_comparative_text | string | 0% | 1 | about the size of Virginia and West Virginia combined;... |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 1,591 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | Argentina 541 km; Brazil 1,050 km |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 541.0 |
coastline_text |
coastline_text | string | 0% | 1 | 660 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 the edge of continental margin |
maritime_claims_continental_shelf_numeric |
maritime_claims_continental_shelf_numeric | float | 0% | 1 | 200.0 |
climate_text |
climate_text | string | 0% | 1 | warm temperate; freezing temperatures almost unknown |
terrain_text |
terrain_text | string | 0% | 1 | mostly rolling plains and low hills; fertile coastal lowland |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Cerro Catedral 514 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 | 109 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 109.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | arable land, hydropower, minor minerals, fish |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 81.4% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 12.6% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 12.6 |
| +19 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 | URY |
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 | Oriental Republic of Uruguay |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Uruguay |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | República Oriental del Uruguay |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Uruguay |
country_name_former_text |
country_name_former_text | string | 0% | 1 | Banda Oriental, Cisplatine Province |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | name derives from the Uruguay River, which makes up the... |
government_type_text |
government_type_text | string | 0% | 1 | presidential republic |
capital_name_text |
capital_name_text | string | 0% | 1 | Montevideo |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 34 51 S, 56 10 W |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 34.0 |
capital_time_difference_text |
capital_time_difference_text | string | 0% | 1 | UTC-3 (2 hours ahead of Washington, DC, during Standard Time) |
capital_time_difference_numeric |
capital_time_difference_numeric | float | 0% | 1 | -3.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | the origin of the name is disputed but refers to a hill... |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 19 departments (departamentos, singular - departamento);... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 19.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | civil law system based on the Spanish civil code |
constitution_history_text |
constitution_history_text | string | 0% | 1 | several previous; latest approved by plebiscite 27... |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 27.0 |
constitution_amendment_process_text |
constitution_amendment_process_text | string | 0% | 1 | initiated by public petition of at least 10% of... |
constitution_amendment_process_numeric |
constitution_amendment_process_numeric | float | 0% | 1 | 10.0 |
international_law_organization_participation_text |
international_law_organization_participation_text | string | 0% | 1 | accepts compulsory ICJ jurisdiction; accepts ICCt jurisdiction |
citizenship_citizenship_by_birth_text |
Citizenship by birth (text) | string | 0% | 1 | yes |
citizenship_citizenship_by_descent_only_text |
Citizenship by descent only (text) | string | 0% | 1 | yes |
citizenship_dual_citizenship_recognized_text |
citizenship_dual_citizenship_recognized_text | string | 0% | 1 | yes |
citizenship_residency_requirement_for_naturalization_text |
citizenship_residency_requirement_for_naturalization_text | string | 0% | 1 | 3-5 years |
citizenship_residency_requirement_for_naturalization_numeric |
citizenship_residency_requirement_for_naturalization_numeric | float | 0% | 1 | 3.0 |
suffrage_text |
suffrage_text | string | 0% | 1 | 18 years of age; universal and compulsory |
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 Yamandú ORSI Martínez (since 1 March 2025) |
executive_branch_chief_of_state_numeric |
executive_branch_chief_of_state_numeric | float | 0% | 1 | 1.0 |
| +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 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | The Spanish founded the city of Montevideo in modern-day... |
background_numeric |
background_numeric | float | 0% | 1 | 1726.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/uy.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_languages_text |
Languages (text) | string | 0% | 1 | Spanish (official, Rioplatense is the most widely spoken dialect) |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | La Libreta Informativa del Mundo, la fuente... |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/uy.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
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 | 32,149 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 32149.0 |
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 33 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 33.0 |
refugees_and_internally_displaced_persons_stateless_persons_text |
refugees_and_internally_displaced_persons_stateless_persons_text | string | 0% | 1 | 5 (2024 est.) |
refugees_and_internally_displaced_persons_stateless_persons_numeric |
refugees_and_internally_displaced_persons_stateless_persons_numeric | float | 0% | 1 | 5.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/uy.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
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 | Armed Forces of Uruguay (Fuerzas Armadas del Uruguay or... |
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 | 2.1% of GDP (2024 est.) |
military_expenditures_military_expenditures_2024_numeric |
Military expenditures 2024 (numeric) | float | 0% | 1 | 2.1 |
military_expenditures_military_expenditures_2023_text |
Military expenditures 2023 (text) | string | 0% | 1 | 2% of GDP (2023 est.) |
military_expenditures_military_expenditures_2023_numeric |
Military expenditures 2023 (numeric) | float | 0% | 1 | 2.0 |
military_expenditures_military_expenditures_2022_text |
Military expenditures 2022 (text) | string | 0% | 1 | 2% of GDP (2022 est.) |
military_expenditures_military_expenditures_2022_numeric |
Military expenditures 2022 (numeric) | float | 0% | 1 | 2.0 |
military_expenditures_military_expenditures_2021_text |
Military expenditures 2021 (text) | string | 0% | 1 | 2.3% of GDP (2021 est.) |
military_expenditures_military_expenditures_2021_numeric |
Military expenditures 2021 (numeric) | float | 0% | 1 | 2.3 |
military_expenditures_military_expenditures_2020_text |
Military expenditures 2020 (text) | string | 0% | 1 | 2% of GDP (2020 est.) |
military_expenditures_military_expenditures_2020_numeric |
Military expenditures 2020 (numeric) | float | 0% | 1 | 2.0 |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | approximately 23,000 active-duty Armed Forces (15,000... |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 23000.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the military's inventory includes a variety of mostly... |
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 | generally 18-30 years of age (up to 22 for the Navy and... |
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 | 630 Democratic Republic of the Congo (MONUSCO); 210... |
military_deployments_numeric |
military_deployments_numeric | float | 0% | 1 | 630.0 |
military_note_text |
military_note_text | string | 0% | 1 | the armed forces are responsible for defense of the... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 2018.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/uy.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 3449444.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 1678419.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 1771025.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 18.9 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 65.4 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 15.7 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 48.7 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 26.2 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 22.5 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 37.4 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | -0.06 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 9.05 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 9.88 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | 0.19 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 95.8 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 0.4 |
sex_ratio_at_birth_numeric |
Sex ratio at birth | float | SEL | 0% | 1 | 1.04 |
sex_ratio_total_population_numeric |
Sex ratio overall | float | SEL | 0% | 1 | 0.94 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 15.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 6.9 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 78.9 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 1.27 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 0.62 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 4.67 |
hospital_bed_density_numeric |
Hospital beds per 1000 | float | SEL | 0% | 1 | 2.5 |
literacy_total_population_numeric |
Literacy rate percent | float | SEL | 0% | 1 | 98.9 |
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
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 | 3,449,444 (2025 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 1,678,419 |
population_female_text |
population_female_text | string | 0% | 1 | 1,771,025 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 18.9% (male 329,268/female 317,925) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 65.4% (male 1,112,622/female 1,128,418) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 15.7% (2024 est.) (male 218,242/female 318,855) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 48.7 (2025 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 26.2 (2025 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 22.5 (2025 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 4.4 (2025 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 4.4 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 37.4 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 34.9 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 34.9 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 38.2 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 38.2 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | -0.06% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 9.05 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 9.88 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | 0.19 migrant(s)/1,000 population (2025 est.) |
population_distribution_text |
population_distribution_text | string | 0% | 1 | most of the country's population resides in the southern... |
population_distribution_numeric |
population_distribution_numeric | float | 0% | 1 | 80.0 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 95.8% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 0.4% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 1.774 million MONTEVIDEO (capital) (2023) |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 1.774 |
sex_ratio_at_birth_text |
sex_ratio_at_birth_text | string | 0% | 1 | 1.04 male(s)/female |
sex_ratio_0_14_years_text |
sex_ratio_0_14_years_text | string | 0% | 1 | 1.04 male(s)/female |
sex_ratio_0_14_years_numeric |
sex_ratio_0_14_years_numeric | float | 0% | 1 | 1.04 |
sex_ratio_15_64_years_text |
sex_ratio_15_64_years_text | string | 0% | 1 | 0.99 male(s)/female |
| +86 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_religion_other_pct_synth |
other | numeric | CCL | 0% | - | 1.0 |
composition_ethnicity_primary_label_synth |
White | string | CCL | 0% | - | White |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Roman Catholic 36.5%, Protestant 5% (Evangelical... |
religions_numeric |
religions_numeric | float | 0% | 1 | 36.5 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/uy.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_roman_catholic_pct_synth |
Roman Catholic | numeric | 0% | - | 36.5 |
composition_religion_protestant_pct_synth |
Protestant | numeric | 0% | - | 5.0 |
composition_religion_protestant__evangelical_non_specific_pct_synth |
Evangelical (non-specific) | numeric | 0% | - | 4.6 |
composition_religion_protestant__adventist_pct_synth |
Adventist | numeric | 0% | - | 0.2 |
composition_religion_protestant__protestant_non_specific_pct_synth |
Protestant (non-specific) | numeric | 0% | - | 0.3 |
composition_religion_african_american_cults_umbanda_pct_synth |
African American Cults/Umbanda | numeric | 0% | - | 2.8 |
composition_religion_jehovah_s_witness_pct_synth |
Jehovah's Witness | numeric | 0% | - | 0.6 |
composition_religion_church_of_jesus_christ_pct_synth |
Church of Jesus Christ | numeric | 0% | - | 0.2 |
composition_religion_believer_not_belonging_to_the_church_pct_synth |
Believer (not belonging to the church) | numeric | 0% | - | 1.8 |
composition_religion_agnostic_pct_synth |
agnostic | numeric | 0% | - | 0.3 |
composition_religion_atheist_pct_synth |
atheist | numeric | 0% | - | 1.3 |
composition_religion_none_pct_synth |
none | numeric | 0% | - | 47.3 |
composition_religion_unspecified_roman_catholic_42_pct_synth |
unspecified Roman Catholic 42% | numeric | 0% | - | 3.4 |
composition_religion_unspecified_pct_synth |
unspecified | numeric | 0% | - | 24.0 |
composition_ethnicity_white_pct_synth |
White | numeric | 0% | - | 87.7 |
composition_ethnicity_black_pct_synth |
Black | numeric | 0% | - | 4.6 |
composition_ethnicity_indigenous_pct_synth |
Indigenous | numeric | 0% | - | 2.4 |
composition_ethnicity_other_pct_synth |
other | numeric | 0% | - | 0.3 |
composition_ethnicity_none_or_unspecified_pct_synth |
none or unspecified | numeric | 0% | - | 5.0 |
composition_ethnicity_primary_share_pct_synth |
White | numeric | 0% | - | 87.7 |
| 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 | CX |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 65.0 |
country_code |
Country code | string | SEL | 0% | 1 | URY |
country_name |
Country name | string | SEL | 0% | 1 | Uruguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
airports_text |
airports_text | string | 0% | 1 | 65 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 4 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 4.0 |
railways_total_text |
railways_total_text | string | 0% | 1 | 1,673 km (2016) (operational; government claims overall... |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 1673.0 |
railways_standard_gauge_text |
railways_standard_gauge_text | string | 0% | 1 | 1,673 km (2016) 1.435-m gauge |
railways_standard_gauge_numeric |
railways_standard_gauge_numeric | float | 0% | 1 | 1673.0 |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 58 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 58.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | container ship 1, general cargo 4, oil tanker 3, other 50 |
merchant_marine_by_type_numeric |
merchant_marine_by_type_numeric | float | 0% | 1 | 1.0 |
ports_total_ports_text |
ports_total_ports_text | string | 0% | 1 | 8 (2024) |
ports_total_ports_numeric |
ports_total_ports_numeric | float | 0% | 1 | 8.0 |
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 | 6 |
ports_very_small_numeric |
ports_very_small_numeric | float | 0% | 1 | 6.0 |
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 | Colonia, Fray Bentos, Jose Ignacio, La Paloma,... |
source_section |
source_section | string | 0% | 1 | Transportation |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/uy.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
glottocode |
Glottocode | string | CCL | 0% | 9 | chan1296, char1240, east2295, guen1235, mbya1239 |
name |
Name | string | CCL | 0% | 9 | Chaná, Charrúa, Eastern Yiddish, Güenoa, Mbyá Guaraní |
iso639_3 |
Iso639 3 | string | CCL | 44% | 5 | ydd, gun, por, spa, ugy |
level |
Level | string | CCL | 0% | 1 | language, language, language, language, language |
family_name |
Family name | string | CCL | 100% | - | - |
family_glottocode |
Family glottocode | string | CCL | 0% | 5 | char1238, char1238, indo1319, char1238, tupi1275 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 0% | 7 | char1238, char1238, schl1237, char1238, tupi1282 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 5 | ['UY'], ['UY'], ['AR', 'AU', 'BE', 'BY', 'CA', 'CR',... |
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% | 5 | 0, 0, 12, 0, 2 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 11% | 8 | -33.69, -34.9, 51.75, -33.810189, -26.0188 |
longitude |
longitude | float | 11% | 8 | -57.78, -56.16, 19.42, -54.473877, -52.711 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 8 | Montevideo, Maldonado, Las Piedras, Ciudad de la Costa, Salto |
country_code |
Country code | string | SEL | 0% | 1 | URY, URY, URY, URY, URY |
population |
Population count | integer | SEL | 0% | 8 | 1219222, 124858, 106086, 99151, 96048 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 8 | 804, 1051, 670, 931, 36 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Uruguay, Uruguay, Uruguay, Uruguay, Uruguay |
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 | URY, URY, URY |
gns_language_code |
gns_language_code | string | CCL | 0% | 3 | spa, eng, por |
gns_language_name |
gns_language_name | string | CCL | 0% | 3 | Spanish, English, Portuguese |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 3 | 4781, 154, 16 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 3 | 96.5664, 3.1105, 0.3232 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 1 | 0, 0, 0 |
gns_dominant_script_code |
gns_dominant_script_code | string | CCL | 0% | 1 | , , |
gns_dominant_script_name |
gns_dominant_script_name | string | CCL | 0% | 1 | , , |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 0, 0, 0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | URY |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Uruguay |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 3 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 0 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 99.9686 |
gns_non_roman_name_count |
gns_non_roman_name_count | integer | CCL | 0% | 1 | 0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
gns_name_count |
gns_name_count | integer | 0% | 1 | 12726 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 7376 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 12722 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 4 |
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 | 6537 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 2997 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 2657 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 1906 |
gns_name_count_populated_places |
gns_name_count_populated_places | integer | 0% | 1 | 1505 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 1043 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 1261 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 862 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 315 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 145 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 451 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 423 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | URY, URY |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 2 | Whites/mestizos, Afro-Uruguayans |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 2 | MONOPOLY, POWERLESS |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 2 | 0.908, 0.078 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 2 | 16501000, 16502000 |
regional_autonomy |
Regional autonomy | string | CCL | 0% | 2 | , false |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 1 | 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 | URY |
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 | 20 |
oc_anti_money_laundering_2023 |
oc_anti_money_laundering_2023 | float | 0% | 1 | 6.5 |
oc_anti_money_laundering_2021 |
oc_anti_money_laundering_2021 | integer | 0% | 1 | 7 |
oc_arms_trafficking_rank |
oc_arms_trafficking_rank | integer | 0% | 1 | 120 |
oc_arms_trafficking_2023 |
oc_arms_trafficking_2023 | integer | 0% | 1 | 3 |
oc_arms_trafficking_2021 |
oc_arms_trafficking_2021 | float | 0% | 1 | 2.5 |
oc_cannabis_trade_rank |
oc_cannabis_trade_rank | integer | 0% | 1 | 145 |
oc_cannabis_trade_2023 |
oc_cannabis_trade_2023 | integer | 0% | 1 | 4 |
oc_cannabis_trade_2021 |
oc_cannabis_trade_2021 | integer | 0% | 1 | 4 |
oc_cocaine_trade_rank |
oc_cocaine_trade_rank | integer | 0% | 1 | 47 |
oc_cocaine_trade_2023 |
oc_cocaine_trade_2023 | integer | 0% | 1 | 6 |
oc_cocaine_trade_2021 |
oc_cocaine_trade_2021 | integer | 0% | 1 | 5 |
oc_criminal_actors_rank |
oc_criminal_actors_rank | integer | 0% | 1 | 165 |
oc_criminal_actors_2023 |
oc_criminal_actors_2023 | float | 0% | 1 | 3.1 |
oc_criminal_actors_2021 |
oc_criminal_actors_2021 | float | 0% | 1 | 2.63 |
oc_criminal_markets_rank |
oc_criminal_markets_rank | integer | 0% | 1 | 162 |
oc_criminal_markets_2023 |
oc_criminal_markets_2023 | float | 0% | 1 | 3.33 |
oc_criminal_markets_2021 |
oc_criminal_markets_2021 | float | 0% | 1 | 2.75 |
oc_criminal_networks_rank |
oc_criminal_networks_rank | integer | 0% | 1 | 143 |
oc_criminal_networks_2023 |
oc_criminal_networks_2023 | float | 0% | 1 | 4.5 |
oc_criminal_networks_2021 |
oc_criminal_networks_2021 | float | 0% | 1 | 4.5 |
oc_criminality_rank |
oc_criminality_rank | integer | 0% | 1 | 165 |
oc_criminality_2023 |
oc_criminality_2023 | float | 0% | 1 | 3.22 |
oc_criminality_2021 |
oc_criminality_2021 | float | 0% | 1 | 2.69 |
oc_cyber_dependent_crimes_rank |
oc_cyber_dependent_crimes_rank | integer | 0% | 1 | 95 |
| +74 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | URY |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
wave |
wave | integer | 0% | 1 | 7 |
wave_years |
wave_years | string | 0% | 1 | 2017-2022 |
source |
source | string | 0% | 1 | World Values Survey |
importance_religion |
importance_religion | integer | 0% | 1 | 1 |
importance_family |
importance_family | integer | 0% | 1 | 1 |
importance_friends |
importance_friends | integer | 0% | 1 | 1 |
trust_people |
trust_people | integer | 0% | 1 | 1 |
trust_family |
trust_family | integer | 0% | 1 | 1 |
life_satisfaction |
life_satisfaction | integer | 0% | 1 | 1 |
happiness |
happiness | integer | 0% | 1 | 1 |
freedom_choice |
freedom_choice | integer | 0% | 1 | 1 |
gender_jobs_scarce |
gender_jobs_scarce | integer | 0% | 1 | 1 |
gender_political_leaders |
gender_political_leaders | integer | 0% | 1 | 1 |
gender_university |
gender_university | integer | 0% | 1 | 1 |
justifiable_divorce |
justifiable_divorce | integer | 0% | 1 | 1 |
justifiable_homosexuality |
justifiable_homosexuality | integer | 0% | 1 | 1 |
immigration_policy |
immigration_policy | integer | 0% | 1 | 1 |
immigrants_jobs |
immigrants_jobs | integer | 0% | 1 | 1 |
immigrants_culture |
immigrants_culture | integer | 0% | 1 | 1 |
confidence_government |
confidence_government | integer | 0% | 1 | 1 |
confidence_parliament |
confidence_parliament | integer | 0% | 1 | 1 |
confidence_police |
confidence_police | integer | 0% | 1 | 1 |
confidence_courts |
confidence_courts | integer | 0% | 1 | 1 |
confidence_press |
confidence_press | integer | 0% | 1 | 1 |
democracy_importance |
democracy_importance | integer | 0% | 1 | 1 |
Which languages name the landscape here, and in which writing systems. A language's toponymic footprint and its speaker population are different measures and often diverge. Counts include variant and foreign-language renderings of the same place, so a language can rank high because outside sources record names in it rather than because it is spoken locally — and a widely spoken language can be almost absent where official naming is in another language.
| Language | Place names | Share | Script |
|---|---|---|---|
| Spanish (spa) | 4,781 | 96.6% | — |
| English (eng) | 154 | 3.1% | — |
| Portuguese (por) | 16 | 0.3% | — |
7,376 distinct features ·
3 languages ·
0 scripts ·
4 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.
| Source | Type | Access |
|---|---|---|
| HDX COD — Population Statistics (OCHA/UNFPA) | international_organization | bulk_download |
| commercial | bulk_download | |
| Global Data Lab | academic | api |
| GI-TOC / ENACT (Global Initiative Against Transnational Organized Crime · ENACT) | academic | bulk_download |
| World Values Survey | academic | metadata_catalog |
| World Bank Open Data | international_organization | api |
| Ethnic Power Relations Dataset | academic | bulk_download |
| NGA GEOnet Names Server (GNS) | official_government | bulk_download |
| UNHCR Refugee Data Finder (UN High Commissioner for Refugees) | international_organization | api |
| Glottolog Language Catalog | academic | bulk_download |
| GHS Urban Centre Database (Global Human Settlement · EU Joint Research Centre) | international_organization | bulk_download |
| LandScan Global (ORNL — Oak Ridge National Laboratory) | research_institution | earth_engine |
| OpenFactBook | community_compilation | bulk_download |
Pick datasets and admin level(s). You'll get a .zip with one CSV per dataset, each filtered to the levels you choose.