| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
admin_code |
Admin code | integer | SEL | 0% | 16 | 15, 1, 2, 3, 4 |
admin_name |
Admin name | string | SEL | 0% | 16 | REGIÓN DE ARICA Y PARINACOTA, REGIÓN DE TARAPACÁ, REGIÓN... |
TOTAL_PERS |
Population count | integer | SEL | 0% | 16 | 226068, 330558, 607534, 286168, 757586 |
HOMBRES |
Population male | integer | SEL | 0% | 16 | 112581, 167793, 315014, 144420, 368774 |
MUJERES |
Population female | integer | SEL | 0% | 16 | 113487, 162765, 292520, 141748, 388812 |
TOTAL_VIVI |
Dwelling count | integer | SEL | 0% | 16 | 76201, 117809, 196349, 121094, 308608 |
| 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 |
year | integer | 0% | 1 | 2017, 2017, 2017, 2017, 2017 |
PARTICULAR |
PARTICULAR | integer | 0% | 16 | 75902, 117450, 195173, 120645, 307844 |
COLECTIVAS |
COLECTIVAS | integer | 0% | 16 | 299, 359, 1176, 449, 764 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
admin_code |
Admin code | integer | SEL | 0% | 56 | 151, 152, 11, 14, 21 |
admin_name |
Admin name | string | SEL | 0% | 56 | ARICA, PARINACOTA, IQUIQUE, TAMARUGAL, ANTOFAGASTA |
TOTAL_PERS |
Population count | integer | SEL | 0% | 56 | 222619, 3449, 299843, 30715, 398843 |
HOMBRES |
Population male | integer | SEL | 0% | 56 | 110115, 2466, 149103, 18690, 206024 |
MUJERES |
Population female | integer | SEL | 0% | 56 | 112504, 983, 150740, 12025, 192819 |
TOTAL_VIVI |
Dwelling count | integer | SEL | 0% | 56 | 73587, 2614, 100164, 17645, 121830 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
admin_level | string | 0% | 1 | admin_2, admin_2, admin_2, admin_2, admin_2 |
year |
year | integer | 0% | 1 | 2017, 2017, 2017, 2017, 2017 |
PARTICULAR |
PARTICULAR | integer | 0% | 56 | 73341, 2561, 99887, 17563, 121326 |
COLECTIVAS |
COLECTIVAS | integer | 0% | 51 | 246, 53, 277, 82, 504 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
admin_code |
Admin code | integer | SEL | 0% | 100 | 15101, 15102, 15201, 15202, 1101 |
admin_name |
Admin name | string | SEL | 0% | 100 | ARICA, CAMARONES, PUTRE, GENERAL LAGOS, IQUIQUE |
TOTAL_PERS |
Population count | integer | SEL | 0% | 100 | 221364, 1255, 2765, 684, 191468 |
HOMBRES |
Population male | integer | SEL | 0% | 100 | 109389, 726, 2054, 412, 94897 |
MUJERES |
Population female | integer | SEL | 0% | 100 | 111975, 529, 711, 272, 96571 |
TOTAL_VIVI |
Dwelling count | integer | SEL | 0% | 100 | 72639, 948, 1917, 697, 66986 |
DENSIDAD |
Population density | float | SEL | 0% | 92 | 46.2, 0.3, 0.5, 0.3, 83.7 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
admin_level | string | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
year |
year | integer | 0% | 1 | 2017, 2017, 2017, 2017, 2017 |
region_code |
region_code | integer | 0% | 7 | 15, 15, 15, 15, 1 |
provincia_code |
provincia_code | integer | 0% | 22 | 151, 151, 152, 152, 11 |
PARTICULAR |
PARTICULAR | integer | 0% | 100 | 72414, 927, 1875, 686, 66725 |
COLECTIVAS |
COLECTIVAS | integer | 0% | 65 | 225, 21, 42, 11, 261 |
INDICE_MAS |
INDICE_MAS | float | 0% | 76 | 97.7, 137.2, 288.9, 151.5, 98.3 |
INDICE_DEP |
INDICE_DEP | float | 0% | 78 | 48.9, 46.8, 21.3, 41.9, 43.8 |
IND_DEP_JU |
IND_DEP_JU | float | 0% | 77 | 32.7, 22.7, 11, 21.4, 30.5 |
IND_DEP_VE |
IND_DEP_VE | float | 0% | 78 | 16.2, 24.1, 10.3, 20.5, 13.3 |
ⓘ 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 | CHL, CHL, CHL, CHL, CHL |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 14 | Total, Aysén, Antofagasta, Araucanía, Atacama |
human_development_index |
Human development index | float | SEL | 0% | 71 | 0.745, 0.706, 0.768, 0.687, 0.748 |
health_index |
Health index | float | SEL | 0% | 54 | 0.826, 0.822, 0.798, 0.81, 0.851 |
education_index |
Education index | float | SEL | 0% | 73 | 0.708, 0.629, 0.789, 0.602, 0.702 |
income_index |
Income index | float | SEL | 0% | 66 | 0.706, 0.679, 0.72, 0.664, 0.701 |
life_expectancy |
Life expectancy | float | SEL | 0% | 88 | 73.68, 73.46, 71.88, 72.67, 75.29 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 93 | 10.62, 9.43, 11.84, 9.029, 10.53 |
| 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 |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 1 | CL |
region_name |
Region name | string | SEL | 0% | 1 | Chile |
F_TL |
Female population | integer | SEL | 0% | 1 | 10045585 |
M_TL |
Male population | integer | SEL | 0% | 1 | 9782978 |
T_TL |
Total population | integer | SEL | 0% | 1 | 19828563 |
| 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 | integer | 0% | 1 | 577504 |
F_05_09 |
Female population age 5-9 | integer | 0% | 1 | 620033 |
F_10_14 |
Female population age 10-14 | integer | 0% | 1 | 637702 |
F_15_19 |
Female population age 15-19 | integer | 0% | 1 | 605608 |
F_20_24 |
Female population age 20-24 | integer | 0% | 1 | 678709 |
F_25_29 |
Female population age 25-29 | integer | 0% | 1 | 785739 |
F_30_34 |
Female population age 30-34 | integer | 0% | 1 | 835861 |
F_35_39 |
Female population age 35-39 | integer | 0% | 1 | 732919 |
F_40_44 |
Female population age 40-44 | integer | 0% | 1 | 686173 |
F_45_49 |
Female population age 45-49 | integer | 0% | 1 | 661003 |
F_50_54 |
Female population age 50-54 | integer | 0% | 1 | 622004 |
F_55_59 |
Female population age 55-59 | integer | 0% | 1 | 608970 |
F_60_64 |
Female population age 60-64 | integer | 0% | 1 | 542388 |
F_65_69 |
Female population age 65-69 | integer | 0% | 1 | 464538 |
F_70_74 |
Female population age 70-74 | integer | 0% | 1 | 354224 |
F_75_79 |
Female population age 75-79 | integer | 0% | 1 | 256314 |
F_80Plus |
F_80Plus | integer | 0% | 1 | 375896 |
M_00_04 |
Male population age 0-4 | integer | 0% | 1 | 599782 |
M_05_09 |
Male population age 5-9 | integer | 0% | 1 | 643572 |
M_10_14 |
Male population age 10-14 | integer | 0% | 1 | 660773 |
M_15_19 |
Male population age 15-19 | integer | 0% | 1 | 626479 |
M_20_24 |
Male population age 20-24 | integer | 0% | 1 | 700037 |
M_25_29 |
Male population age 25-29 | integer | 0% | 1 | 808991 |
M_30_34 |
Male population age 30-34 | integer | 0% | 1 | 860590 |
M_35_39 |
Male population age 35-39 | integer | 0% | 1 | 750870 |
M_40_44 |
Male population age 40-44 | integer | 0% | 1 | 693436 |
M_45_49 |
Male population age 45-49 | integer | 0% | 1 | 655076 |
| +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% | 72 | CL02, CL15, CL03, CL11, CL08 |
region_name |
Region name | string | SEL | 0% | 72 | Región de Antofagasta, Región de Arica y Parinacota,... |
F_TL |
Female population | integer | SEL | 0% | 72 | 352724, 127901, 157536, 53523, 860371 |
M_TL |
Male population | integer | SEL | 0% | 72 | 356913, 129821, 160468, 54524, 815898 |
T_TL |
Total population | integer | SEL | 0% | 72 | 709637, 257722, 318004, 108047, 1676269 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 2 | 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 |
ADM1_ES_UNFPA |
ADM1_ES_UNFPA | string | 0% | 16 | Antofagasta, Arica y Parinacota, Atacama, Aysén del... |
F_00_04 |
Female population age 0-4 | integer | 0% | 72 | 23252, 7787, 10120, 3268, 45469 |
F_05_09 |
Female population age 5-9 | integer | 0% | 72 | 23604, 8730, 11638, 3777, 52067 |
F_10_14 |
Female population age 10-14 | integer | 0% | 72 | 24349, 9171, 12400, 4016, 55283 |
F_15_19 |
Female population age 15-19 | integer | 0% | 72 | 22761, 8309, 9746, 3241, 53742 |
F_20_24 |
Female population age 20-24 | integer | 0% | 72 | 27231, 9102, 9945, 2610, 59259 |
F_25_29 |
Female population age 25-29 | integer | 0% | 72 | 33301, 9747, 11966, 3683, 62088 |
F_30_34 |
Female population age 30-34 | integer | 0% | 72 | 33257, 10048, 13287, 5044, 65100 |
F_35_39 |
Female population age 35-39 | integer | 0% | 72 | 28637, 9333, 11508, 4403, 57309 |
F_40_44 |
Female population age 40-44 | integer | 0% | 72 | 26030, 8539, 10245, 4031, 58121 |
F_45_49 |
Female population age 45-49 | integer | 0% | 71 | 24351, 8112, 9496, 3831, 57443 |
F_50_54 |
Female population age 50-54 | integer | 0% | 72 | 19890, 7615, 9349, 3314, 57858 |
F_55_59 |
Female population age 55-59 | integer | 0% | 72 | 17572, 7273, 9402, 3029, 56047 |
F_60_64 |
Female population age 60-64 | integer | 0% | 72 | 15235, 6503, 8388, 2695, 48921 |
F_65_69 |
Female population age 65-69 | integer | 0% | 72 | 12310, 5595, 6912, 2307, 42548 |
F_70_74 |
Female population age 70-74 | integer | 0% | 71 | 8402, 4418, 4911, 1581, 32003 |
F_75_79 |
Female population age 75-79 | integer | 0% | 72 | 5249, 3304, 3428, 1026, 23634 |
F_80Plus |
F_80Plus | integer | 0% | 72 | 7293, 4315, 4795, 1667, 33479 |
M_00_04 |
Male population age 0-4 | integer | 0% | 72 | 24352, 8100, 10523, 3383, 47175 |
M_05_09 |
Male population age 5-9 | integer | 0% | 72 | 24995, 9080, 12080, 3927, 54180 |
M_10_14 |
Male population age 10-14 | integer | 0% | 72 | 25789, 9635, 12923, 4301, 57550 |
M_15_19 |
Male population age 15-19 | integer | 0% | 72 | 24366, 9547, 10526, 3834, 55500 |
M_20_24 |
Male population age 20-24 | integer | 0% | 72 | 28147, 10981, 10684, 2820, 59594 |
M_25_29 |
Male population age 25-29 | integer | 0% | 72 | 34045, 10810, 12359, 3530, 61704 |
M_30_34 |
Male population age 30-34 | integer | 0% | 72 | 34113, 10906, 13886, 4794, 64125 |
M_35_39 |
Male population age 35-39 | integer | 0% | 72 | 29535, 9909, 12112, 4319, 53940 |
M_40_44 |
Male population age 40-44 | integer | 0% | 72 | 26851, 8828, 11020, 4192, 54651 |
| +25 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% | 100 | CL02101, CL02102, CL02103, CL02104, CL02201 |
region_name |
Region name | string | SEL | 0% | 100 | Antofagasta, Mejillones, Sierra Gorda, Taltal, Calama |
F_TL |
Female population | integer | SEL | 0% | 100 | 218174, 7398, 843, 6823, 96609 |
M_TL |
Male population | integer | SEL | 0% | 100 | 219709, 8032, 941, 7060, 97966 |
T_TL |
Total population | integer | SEL | 0% | 99 | 437883, 15430, 1784, 13883, 194575 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
year |
Reference year | integer | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
year |
year | integer | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
ADM1_ES_UNFPA |
ADM1_ES_UNFPA | string | 0% | 7 | Antofagasta, Antofagasta, Antofagasta, Antofagasta, Antofagasta |
ADM2_ES_UNFPA |
ADM2_ES_UNFPA | string | 0% | 19 | Antofagasta, Antofagasta, Antofagasta, Antofagasta, El Loa |
ADM3_ES_UNFPA |
ADM3_ES_UNFPA | string | 0% | 100 | Antofagasta, Mejillones, Sierra Gorda, Taltal, Calama |
F_00_04 |
Female population age 0-4 | integer | 0% | 99 | 13878, 541, 63, 454, 6747 |
F_05_09 |
Female population age 5-9 | integer | 0% | 100 | 14094, 534, 64, 500, 6774 |
F_10_14 |
Female population age 10-14 | integer | 0% | 100 | 14483, 550, 57, 588, 7100 |
F_15_19 |
Female population age 15-19 | integer | 0% | 96 | 14356, 501, 50, 413, 6098 |
F_20_24 |
Female population age 20-24 | integer | 0% | 96 | 18095, 616, 73, 403, 6603 |
F_25_29 |
Female population age 25-29 | integer | 0% | 98 | 20692, 785, 78, 551, 8966 |
F_30_34 |
Female population age 30-34 | integer | 0% | 100 | 20105, 694, 91, 572, 9587 |
F_35_39 |
Female population age 35-39 | integer | 0% | 96 | 17507, 595, 81, 538, 8177 |
F_40_44 |
Female population age 40-44 | integer | 0% | 99 | 16089, 483, 70, 468, 7392 |
F_45_49 |
Female population age 45-49 | integer | 0% | 98 | 15042, 475, 59, 465, 6799 |
F_50_54 |
Female population age 50-54 | integer | 0% | 98 | 12032, 422, 38, 400, 5698 |
F_55_59 |
Female population age 55-59 | integer | 0% | 96 | 10795, 368, 36, 374, 4809 |
F_60_64 |
Female population age 60-64 | integer | 0% | 99 | 9493, 280, 31, 341, 3986 |
F_65_69 |
Female population age 65-69 | integer | 0% | 98 | 7832, 218, 22, 252, 3107 |
F_70_74 |
Female population age 70-74 | integer | 0% | 100 | 5356, 149, 13, 192, 2046 |
F_75_79 |
Female population age 75-79 | integer | 0% | 94 | 3461, 100, 5, 105, 1174 |
F_80Plus |
F_80Plus | integer | 0% | 96 | 4864, 87, 12, 207, 1546 |
M_00_04 |
Male population age 0-4 | integer | 0% | 97 | 14535, 520, 54, 490, 7129 |
M_05_09 |
Male population age 5-9 | integer | 0% | 96 | 15133, 503, 67, 531, 7019 |
M_10_14 |
Male population age 10-14 | integer | 0% | 97 | 15538, 517, 56, 557, 7396 |
M_15_19 |
Male population age 15-19 | integer | 0% | 92 | 15345, 445, 43, 416, 6767 |
M_20_24 |
Male population age 20-24 | integer | 0% | 97 | 18738, 595, 52, 416, 6980 |
M_25_29 |
Male population age 25-29 | integer | 0% | 98 | 21473, 866, 87, 585, 8974 |
M_30_34 |
Male population age 30-34 | integer | 0% | 97 | 21030, 823, 115, 580, 9410 |
| +27 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 | CL, CL, CL, CL, CL |
population_count |
Population count | float | SEL | 2% | 65 | 8153350.0, 8324802.0, 8497059.0, 8670144.0, 8842525.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 57.216, 57.309, 57.811, 58.349, 58.812 |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 2% | 65 | 516.487539077836, 594.436306222113, 678.584336588862,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 89% | 7 | 91.129997253418, 94.2900009155273, 95.7200012207031,... |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 61 | 153.2, 148.6, 142.8, 136.1, 127.2 |
poverty_headcount_pct |
Poverty headcount percent | float | SEL | 76% | 16 | 45.1, 38.6, 32.8, 27.7, 23.2 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Chile, Chile, Chile, Chile, Chile |
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 | CL, CL, CL, CL, CL |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 57.216, 57.309, 57.811, 58.349, 58.812 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 15% | 40 | 34.1, 30.9, 29.5, 29.3, 28.9 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 61 | 153.2, 148.6, 142.8, 136.1, 127.2 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 33 | 73.0, 70.0, 67.0, 64.0, 62.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 61 | 4.697, 4.655, 4.602, 4.536, 4.457 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 63 | 35.309, 34.792, 34.284, 33.704, 33.056 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 64 | 10.968, 10.913, 10.64, 10.363, 10.128 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 55% | 29 | 0.559, 0.473, 0.463, 0.516, 0.817 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 53% | 28 | 3.6742901802063, 3.77640008926392, 3.40639996528625,... |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 32% | 10 | 93.0, 99.0, 99.0, 89.0, 99.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 62% | 25 | 7.00020742, 7.09733105, 7.20833778, 7.25047779, 6.91028595 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Chile, Chile, Chile, Chile, Chile |
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 | CHL |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | Republic of Chile |
admin_code |
Admin code | string | SEL | 0% | 1 | 41092099B20826146210768 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 736592.7811 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 18407372 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 24.99 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHL, CHL, CHL, CHL, CHL |
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% | 16 | Región Metropolitana de Santiago, Región de Valparaíso,... |
admin_code |
Admin code | string | SEL | 0% | 16 | 47653553B78904739401519, 47653553B5611469222723,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 16 | 15393.7119, 16238.3715, 23990.6264, 30307.895, 31797.5597 |
pop_2024 |
Population count | integer | SEL | 0% | 16 | 7823143, 1856216, 1560177, 1084144, 963730 |
pop_density_2024 |
Population density | float | SEL | 0% | 16 | 508.2, 114.31, 65.03, 35.77, 30.31 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHL, CHL, CHL, CHL, CHL |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality, locality, locality, locality |
admin_name |
Admin name | string | SEL | 0% | 38 | Santiago, Valparaíso, Concepción, Antofagasta, Iquique |
admin_code |
Admin code | integer | SEL | 0% | 38 | 2334, 1162, 1668, 373, 210 |
area_sqkm |
Area sqkm | float | SEL | 0% | 38 | 798.8828, 151.5843, 101.8049, 55.7445, 50.7397 |
pop_2024 |
Population count | integer | SEL | 0% | 38 | 6641766, 812554, 449643, 383077, 329297 |
pop_density_2024 |
Population density | float | SEL | 0% | 38 | 8313.82, 5360.41, 4416.71, 6872.01, 6489.93 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 38 | 6633767, 838446, 508455, 365402, 316450 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 38 | 1.001, 0.969, 0.884, 1.048, 1.041 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 38 | Santiago, Valparaíso, Concepción, Antofagasta, Temuco |
country_code |
Country code | string | SEL | 0% | 1 | CHL, CHL, CHL, CHL, CHL |
population |
Population count | integer | SEL | 0% | 38 | 6633767, 838446, 508455, 365402, 355236 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 38 | 2334, 1162, 1668, 373, 3052 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Chile, Chile, Chile, Chile, Chile |
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 |
|---|---|---|---|---|---|---|
glottocode |
Glottocode | string | CCL | 0% | 18 | alac1239, cent2142, chil1264, chil1283, chon1248 |
name |
Name | string | CCL | 0% | 18 | Alacalufe-Austral, Central Aymara, Chilean Sign... |
iso639_3 |
Iso639 3 | string | CCL | 28% | 13 | ayr, csg, cqu, huh, kbf |
level |
Level | string | CCL | 0% | 1 | language, language, language, language, language |
family_name |
Family name | string | CCL | 100% | - | - |
family_glottocode |
Family glottocode | string | CCL | 17% | 10 | kawe1237, ayma1253, sign1238, book1242, uncl1493 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 17% | 12 | kawe1237, nucl1667, deaf1237, book1242, uncl1493 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 5 | ['CL'], ['AR', 'BO', 'CL', 'PE'], ['CL'], ['CL'], ['CL'] |
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% | 7 | 0, 0, 0, 0, 0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 6% | 17 | -54.788017, -17.0, -32.781, -23.7036, -44.298692 |
longitude |
longitude | float | 6% | 17 | -70.140381, -68.5, -70.6698, -67.7604, -73.879395 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CL, CL, CL, CL, CL |
admin_level |
Admin level | integer | SEL | 0% | 1 | 1, 1, 1, 1, 1 |
iso3 |
Country code | string | SEL | 0% | 1 | CHL, CHL, CHL, CHL, CHL |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
retail |
retail | float | 0% | 16 | -18.75, -25.45, -27.01, -16.27, -12.07 |
grocery |
grocery | float | 0% | 16 | -1.81, -6.89, 1.52, 5.72, -1.79 |
parks |
parks | float | 0% | 16 | -34.11, -28.96, -43.45, -17.75, -39.57 |
transit |
transit | float | 0% | 16 | -17.15, -11.43, -29.06, -20.46, -20.96 |
workplaces |
workplaces | float | 0% | 16 | 1.46, 3.05, -3.45, 8.38, 4.3 |
residential |
residential | float | 0% | 15 | 8.58, 15.27, 10.55, 9.54, 4.92 |
region |
region | string | 0% | 16 | Antofagasta, Araucania, Arica y Parinacota, Atacama, Aysén |
observation_count |
observation_count | integer | 0% | 14 | 3871, 2922, 1948, 3865, 4708 |
| 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 | 8.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 133.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .cl |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 95.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric |
Broadband subscriptions per 100 | float | SEL | 0% | 1 | 23.0 |
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 | 1.74 million (2024 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 1.74 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 8 (2024 est.) |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 26.2 million (2024 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 26.2 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 133 (2024 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | national and local terrestrial TV channels, coupled with... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 250.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 95% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 4.52 million (2023 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 4.52 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 23 (2023 est.) |
source_section |
source_section | string | 0% | 1 | Communications |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/ci.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 | 30200.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 330.267 |
population_below_poverty_line_numeric |
Poverty headcount percent | float | SEL | 0% | 1 | 6.5 |
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 | export-driven economy; leading copper producer; though... |
economic_overview_numeric |
economic_overview_numeric | float | 0% | 1 | -19.0 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $596.556 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 | 596.556 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $581.187 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 | 581.187 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $578.173 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 | 578.173 |
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 | 2.6% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | 2.6 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 0.5% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 0.5 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 2.2% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 2.2 |
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 | $30,200 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $29,600 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 29600.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $29,600 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 29600.0 |
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 | $330.267 billion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 4.3% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 4.3 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text |
Inflation rate consumer prices 2023 (text) | string | 0% | 1 | 7.6% (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric |
Inflation rate consumer prices 2023 (numeric) | float | 0% | 1 | 7.6 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 11.6% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 11.6 |
inflation_rate_consumer_prices_note |
inflation_rate_consumer_prices_note | string | 0% | 1 | note: annual % change based on consumer prices |
| +119 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 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 | 39.238 million kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 39.238 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 83.295 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 83.295 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 4.384 billion kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 4.384 |
electricity_generation_sources_fossil_fuels_text |
electricity_generation_sources_fossil_fuels_text | string | 0% | 1 | 35.6% of total installed capacity (2023 est.) |
electricity_generation_sources_fossil_fuels_numeric |
electricity_generation_sources_fossil_fuels_numeric | float | 0% | 1 | 35.6 |
electricity_generation_sources_solar_text |
electricity_generation_sources_solar_text | string | 0% | 1 | 20.6% of total installed capacity (2023 est.) |
electricity_generation_sources_solar_numeric |
electricity_generation_sources_solar_numeric | float | 0% | 1 | 20.6 |
electricity_generation_sources_wind_text |
electricity_generation_sources_wind_text | string | 0% | 1 | 10.8% of total installed capacity (2023 est.) |
electricity_generation_sources_wind_numeric |
electricity_generation_sources_wind_numeric | float | 0% | 1 | 10.8 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 26.6% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 26.6 |
electricity_generation_sources_geothermal_text |
electricity_generation_sources_geothermal_text | string | 0% | 1 | 0.5% of total installed capacity (2023 est.) |
electricity_generation_sources_geothermal_numeric |
electricity_generation_sources_geothermal_numeric | float | 0% | 1 | 0.5 |
electricity_generation_sources_biomass_and_waste_text |
electricity_generation_sources_biomass_and_waste_text | string | 0% | 1 | 5.9% of total installed capacity (2023 est.) |
electricity_generation_sources_biomass_and_waste_numeric |
electricity_generation_sources_biomass_and_waste_numeric | float | 0% | 1 | 5.9 |
coal_production_text |
coal_production_text | string | 0% | 1 | 474,000 metric tons (2023 est.) |
coal_production_numeric |
coal_production_numeric | float | 0% | 1 | 474000.0 |
coal_consumption_text |
coal_consumption_text | string | 0% | 1 | 8.087 million metric tons (2023 est.) |
coal_consumption_numeric |
coal_consumption_numeric | float | 0% | 1 | 8.087 |
coal_exports_text |
coal_exports_text | string | 0% | 1 | 63,000 metric tons (2023 est.) |
coal_exports_numeric |
coal_exports_numeric | float | 0% | 1 | 63000.0 |
coal_imports_text |
coal_imports_text | string | 0% | 1 | 7.589 million metric tons (2023 est.) |
coal_imports_numeric |
coal_imports_numeric | float | 0% | 1 | 7.589 |
coal_proven_reserves_text |
coal_proven_reserves_text | string | 0% | 1 | 1.181 billion metric tons (2023 est.) |
coal_proven_reserves_numeric |
coal_proven_reserves_numeric | float | 0% | 1 | 1.181 |
petroleum_total_petroleum_production_text |
petroleum_total_petroleum_production_text | string | 0% | 1 | 11,000 bbl/day (2023 est.) |
| +19 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 | 14.4 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 24.5 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 88.0 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 0.78 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 6.517 |
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 | air pollution from industrial and vehicle emissions;... |
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 | none of the selected agreements |
climate_text |
climate_text | string | 0% | 1 | temperate; desert in north; Mediterranean in central... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 14.4% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 1.9% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 1.9 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.7% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.7 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 11.8% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 11.8 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 24.5% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 61.1% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 61.1 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 88% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 0.78% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 83.058 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 83.058 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 14.773 million 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 | 14.773 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 55.504 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 | 55.504 |
carbon_dioxide_emissions_from_consumed_natural_gas_text |
carbon_dioxide_emissions_from_consumed_natural_gas_text | string | 0% | 1 | 12.781 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_from_consumed_natural_gas_numeric |
carbon_dioxide_emissions_from_consumed_natural_gas_numeric | float | 0% | 1 | 12.781 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 18.8 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 18.8 |
waste_and_recycling_municipal_solid_waste_generated_annually_text |
waste_and_recycling_municipal_solid_waste_generated_annually_text | string | 0% | 1 | 6.517 million tons (2024 est.) |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_text |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_text | string | 0% | 1 | 1% (2022 est.) |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_numeric |
waste_and_recycling_percent_of_municipal_solid_waste_recycled_numeric | float | 0% | 1 | 1.0 |
total_water_withdrawal_municipal_text |
total_water_withdrawal_municipal_text | string | 0% | 1 | 1.29 billion cubic meters (2022 est.) |
| +13 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 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 | Chilean(s) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Chilean |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | White and non-Indigenous 88.9%, Mapuche 9.1%, Aymara... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 88.9 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/ci.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 756102.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 743812.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 12290.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 7801.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 6435.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 6893.0 |
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 | 14.4 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 24.5 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 9094.0 |
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 Pacific... |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 30 00 S, 71 00 W |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 30.0 |
map_references_text |
map_references_text | string | 0% | 1 | South America |
area_total_text |
area_total_text | string | 0% | 1 | 756,102 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 743,812 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 12,290 sq km |
area_note |
area_note | string | 0% | 1 | note: includes Easter Island (Isla de Pascua) and Isla... |
area_comparative_text |
area_comparative_text | string | 0% | 1 | slightly smaller than twice the size of Montana |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 7,801 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | Argentina 6,691 km; Bolivia 942 km; Peru 168 km |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 6691.0 |
coastline_text |
coastline_text | string | 0% | 1 | 6,435 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 | 200/350 nm |
maritime_claims_continental_shelf_numeric |
maritime_claims_continental_shelf_numeric | float | 0% | 1 | 200.0 |
climate_text |
climate_text | string | 0% | 1 | temperate; desert in north; Mediterranean in central... |
terrain_text |
terrain_text | string | 0% | 1 | low coastal mountains, fertile central valley, rugged... |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Nevado Ojos del Salado 6,893 m (highest volcano in the world) |
elevation_lowest_point_text |
elevation_lowest_point_text | string | 0% | 1 | Pacific Ocean 0 m |
elevation_mean_elevation_text |
elevation_mean_elevation_text | string | 0% | 1 | 1,871 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 1871.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | copper, timber, iron ore, nitrates, precious metals,... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 14.4% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 1.9% (2023 est.) |
| +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 | CHL |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name_conventional_long_form_text |
country_name_conventional_long_form_text | string | 0% | 1 | Republic of Chile |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Chile |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | República de Chile |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Chile |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | derivation of the name is unclear; it may come from a... |
government_type_text |
government_type_text | string | 0% | 1 | presidential republic |
capital_name_text |
capital_name_text | string | 0% | 1 | Santiago; note - Valparaiso is the seat of the national... |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 33 27 S, 70 40 W |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 33.0 |
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_daylight_saving_time_text |
capital_daylight_saving_time_text | string | 0% | 1 | +1hr, begins second Sunday in August; ends second Sunday... |
capital_daylight_saving_time_numeric |
capital_daylight_saving_time_numeric | float | 0% | 1 | 1.0 |
capital_time_zone_note_text |
capital_time_zone_note_text | string | 0% | 1 | Chile has three time zones: the continental portion at... |
capital_time_zone_note_numeric |
capital_time_zone_note_numeric | float | 0% | 1 | -3.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | Santiago is named after Saint James, the patron saint of... |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 16 regions (regiones, singular - region); Antofagasta,... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 16.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | civil law system influenced by several Western European... |
constitution_history_text |
constitution_history_text | string | 0% | 1 | many previous; latest adopted 11 September 1980,... |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 11.0 |
constitution_amendment_process_text |
constitution_amendment_process_text | string | 0% | 1 | proposed by members of either house of the National... |
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 | 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 | 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 |
| +93 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | Indigenous groups inhabited central and southern Chile... |
background_numeric |
background_numeric | float | 0% | 1 | 16.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/ci.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 99.5% (official), English 10.2%, Indigenous 1%... |
languages_languages_numeric |
Languages (numeric) | float | 0% | 1 | 99.5 |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | La Libreta Informativa del Mundo, la fuente... |
languages_note |
languages_note | string | 0% | 1 | note: shares sum to more than 100% because some... |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/ci.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 | 15,788 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 15788.0 |
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 8,323 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 8323.0 |
refugees_and_internally_displaced_persons_stateless_persons_text |
refugees_and_internally_displaced_persons_stateless_persons_text | string | 0% | 1 | 1,688 (2024 est.) |
refugees_and_internally_displaced_persons_stateless_persons_numeric |
refugees_and_internally_displaced_persons_stateless_persons_numeric | float | 0% | 1 | 1688.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/ci.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 Chile (Fuerzas Armadas de Chile):... |
military_and_security_forces_numeric |
military_and_security_forces_numeric | float | 0% | 1 | 2025.0 |
military_expenditures_military_expenditures_2024_text |
Military expenditures 2024 (text) | string | 0% | 1 | 1.5% of GDP (2024 est.) |
military_expenditures_military_expenditures_2024_numeric |
Military expenditures 2024 (numeric) | float | 0% | 1 | 1.5 |
military_expenditures_military_expenditures_2023_text |
Military expenditures 2023 (text) | string | 0% | 1 | 1.5% of GDP (2023 est.) |
military_expenditures_military_expenditures_2023_numeric |
Military expenditures 2023 (numeric) | float | 0% | 1 | 1.5 |
military_expenditures_military_expenditures_2022_text |
Military expenditures 2022 (text) | string | 0% | 1 | 1.6% of GDP (2022 est.) |
military_expenditures_military_expenditures_2022_numeric |
Military expenditures 2022 (numeric) | float | 0% | 1 | 1.6 |
military_expenditures_military_expenditures_2021_text |
Military expenditures 2021 (text) | string | 0% | 1 | 2% of GDP (2021 est.) |
military_expenditures_military_expenditures_2021_numeric |
Military expenditures 2021 (numeric) | float | 0% | 1 | 2.0 |
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 70,000 active Armed Forces (40,000 Army;... |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 70000.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the Chilean military's inventory is comprised of a mix... |
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 | 18-24 for voluntary military service for men and women... |
military_service_age_and_obligation_numeric |
military_service_age_and_obligation_numeric | float | 0% | 1 | 18.0 |
military_note_text |
military_note_text | string | 0% | 1 | the Chilean military's responsibilities are territorial... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 1810.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/ci.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 19091343.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 9379883.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 9711460.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 19.2 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 67.3 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 13.6 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 45.0 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 24.1 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 20.9 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 38.9 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | 0.46 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 8.81 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 6.79 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | 2.58 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 88.0 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 0.78 |
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 | 0.97 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 10.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 4.5 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 80.3 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 1.25 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 0.61 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 3.33 |
hospital_bed_density_numeric |
Hospital beds per 1000 | float | SEL | 0% | 1 | 2.0 |
literacy_total_population_numeric |
Literacy rate percent | float | SEL | 0% | 1 | 96.4 |
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 | 19,091,343 (2025 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 9,379,883 |
population_female_text |
population_female_text | string | 0% | 1 | 9,711,460 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 19.2% (male 1,822,908/female 1,751,528) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 67.3% (male 6,274,620/female 6,278,467) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 13.6% (2024 est.) (male 1,072,208/female 1,464,921) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 45 (2025 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 24.1 (2025 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 20.9 (2025 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 4.8 (2025 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 4.8 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 38.9 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 35.8 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 35.8 |
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 | 0.46% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 8.81 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 6.79 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | 2.58 migrant(s)/1,000 population (2025 est.) |
population_distribution_text |
population_distribution_text | string | 0% | 1 | 90% of the population is located in the middle third of... |
population_distribution_numeric |
population_distribution_numeric | float | 0% | 1 | 90.0 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 88% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 0.78% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 6.903 million SANTIAGO (capital), 1.009 million... |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 6.903 |
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 | 1 male(s)/female |
| +84 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_ethnicity_primary_label_synth |
White and non-Indigenous | string | CCL | 0% | - | White and non-Indigenous |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Catholic 57%, none 25.7%, Evangelical or Protestant... |
religions_numeric |
religions_numeric | float | 0% | 1 | 57.0 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/ci.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_catholic_pct_synth |
Catholic | numeric | 0% | - | 57.0 |
composition_religion_none_pct_synth |
none | numeric | 0% | - | 25.7 |
composition_religion_evangelical_or_protestant_pct_synth |
Evangelical or Protestant | numeric | 0% | - | 16.2 |
composition_religion_other_christians_and_traditions_related_to_christ_1_3_buddhist_pct_synth |
other Christians and traditions related to Christ 1.3%; : Buddhist | numeric | 0% | - | 0.5 |
composition_religion_catholic_orthodox_pct_synth |
Catholic Orthodox | numeric | 0% | - | - |
composition_religion_church_of_jesus_christ_of_latter_day_saints_pct_synth |
Church of Jesus Christ of Latter-Day Saints | numeric | 0% | - | - |
composition_religion_islam_pct_synth |
Islam | numeric | 0% | - | - |
composition_religion_judaism_pct_synth |
Judaism | numeric | 0% | - | - |
composition_religion_other_religions_pct_synth |
other religions | numeric | 0% | - | - |
composition_religion_no_religion_pct_synth |
no religion | numeric | 0% | - | - |
composition_ethnicity_white_and_non_indigenous_pct_synth |
White and non-Indigenous | numeric | 0% | - | 88.9 |
composition_ethnicity_mapuche_pct_synth |
Mapuche | numeric | 0% | - | 9.1 |
composition_ethnicity_aymara_pct_synth |
Aymara | numeric | 0% | - | 0.7 |
composition_ethnicity_other_indigenous_groups_pct_synth |
other Indigenous groups | numeric | 0% | - | 1.0 |
composition_ethnicity_unspecified_pct_synth |
unspecified | numeric | 0% | - | 0.3 |
composition_ethnicity_primary_share_pct_synth |
White and non-Indigenous | numeric | 0% | - | 88.9 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
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 | Tren de Aragua (TdA) |
source_section |
source_section | string | 0% | 1 | Terrorism |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/ci.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 | CC |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 379.0 |
country_code |
Country code | string | SEL | 0% | 1 | CHL |
country_name |
Country name | string | SEL | 0% | 1 | Chile |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
airports_text |
airports_text | string | 0% | 1 | 379 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 115 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 115.0 |
railways_total_text |
railways_total_text | string | 0% | 1 | 7,281.5 km (2014) |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 7281.5 |
railways_narrow_gauge_text |
railways_narrow_gauge_text | string | 0% | 1 | 3,853.5 km (2014) 1.000-m gauge |
railways_narrow_gauge_numeric |
railways_narrow_gauge_numeric | float | 0% | 1 | 3853.5 |
railways_broad_gauge_text |
railways_broad_gauge_text | string | 0% | 1 | 3,428 km (2014) 1.676-m gauge (1,691 km electrified) |
railways_broad_gauge_numeric |
railways_broad_gauge_numeric | float | 0% | 1 | 3428.0 |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 249 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 249.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | bulk carrier 3, container ship 5, general cargo 66, oil... |
merchant_marine_by_type_numeric |
merchant_marine_by_type_numeric | float | 0% | 1 | 3.0 |
ports_total_ports_text |
ports_total_ports_text | string | 0% | 1 | 39 (2024) |
ports_total_ports_numeric |
ports_total_ports_numeric | float | 0% | 1 | 39.0 |
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 | 2 |
ports_medium_numeric |
ports_medium_numeric | float | 0% | 1 | 2.0 |
ports_small_text |
ports_small_text | float | 0% | 1 | 10 |
ports_small_numeric |
ports_small_numeric | float | 0% | 1 | 10.0 |
ports_very_small_text |
ports_very_small_text | float | 0% | 1 | 27 |
ports_very_small_numeric |
ports_very_small_numeric | float | 0% | 1 | 27.0 |
ports_ports_with_oil_terminals_text |
Ports with oil terminals (text) | float | 0% | 1 | 25 |
ports_ports_with_oil_terminals_numeric |
Ports with oil terminals (numeric) | float | 0% | 1 | 25.0 |
ports_key_ports_text |
ports_key_ports_text | string | 0% | 1 | Antofagasta, Bahia de Valdivia, Bahia de Valparaiso,... |
source_section |
source_section | string | 0% | 1 | Transportation |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/ci.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHL, CHL, CHL, CHL |
society_id |
Society id | string | CCL | 0% | 4 | Sg1, Sg3, Sg5, Ij9 |
society_name |
Society name | string | CCL | 0% | 4 | Yahgan, Ona, Alacaluf, Easter Islanders |
language_glottocode |
Language glottocode | string | CCL | 0% | 4 | yama1264, onaa1245, qawa1238, rapa1244 |
language_name |
Language name | string | CCL | 0% | 1 | , , , |
kinship_system |
Kinship system | string | CCL | 0% | 3 | EA001:1; EA002:2; EA003:7; EA004:0; EA005:0, EA001:1;... |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 4 | EA006:2; EA007:3; EA008:2; EA009:2; EA010:10, EA006:6;... |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 3 | EA028:1; EA029:1; EA030:1; EA031:1; EA032:2, EA028:1;... |
political_complexity |
Political complexity | string | CCL | 0% | 4 | EA033:1; EA034:4; EA035:2, EA033:1; EA034:2; EA035:2,... |
religion_importance |
Religion importance | string | CCL | 0% | 4 | EA034:4; EA112:1, EA034:2; EA112:7, EA034:1; EA112:8,... |
residence_pattern |
Residence pattern | string | CCL | 0% | 4 | EA011:1; EA012:10; EA013:9, EA011:1; EA012:10; EA013:2,... |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Chile, Chile, Chile, Chile |
dataset |
dataset | string | 0% | 1 | EA, EA, EA, EA |
region |
region | string | 0% | 1 | , , , |
latitude |
latitude | float | 0% | 4 | -55.02, -54.0, -52.0, -27.12 |
longitude |
longitude | float | 0% | 4 | -68.98, -69.0, -74.0, -109.36 |
assignment_method |
assignment_method | string | 0% | 1 | point_in_polygon, point_in_polygon, point_in_polygon,... |
assignment_confidence |
assignment_confidence | string | 0% | 1 | approximate, approximate, approximate, approximate |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | CHL, CHL, CHL |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 3 | Whites/mestizos, Mapuche, Other indigenous groups |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 3 | MONOPOLY, DISCRIMINATED, POWERLESS |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 3 | 0.872, 0.099, 0.029 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 3 | 15501000, 15502000, 15503000 |
regional_autonomy |
Regional autonomy | string | CCL | 0% | 2 | , false, false |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 1 | 2021, 2021, 2021 |
group_relevance |
group_relevance | string | 0% | 1 | , , |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | CHL, CHL |
gns_language_code |
gns_language_code | string | CCL | 0% | 2 | spa, eng |
gns_language_name |
gns_language_name | string | CCL | 0% | 2 | Spanish, English |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 2 | 26351, 49 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 2 | 99.8144, 0.1856 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 1 | 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 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | CHL |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Chile |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 2 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 0 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 99.9806 |
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 | 56650 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 45306 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 56639 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 11 |
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_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 2245 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 2089 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 19865 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 15895 |
gns_name_count_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 16014 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 12147 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 9445 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 7869 |
gns_name_count_transportation_networks |
gns_name_count_transportation_networks | integer | 0% | 1 | 34 |
gns_feature_count_transportation_networks |
gns_feature_count_transportation_networks | integer | 0% | 1 | 26 |
gns_name_count_populated_places |
gns_name_count_populated_places | integer | 0% | 1 | 8129 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 6826 |
gns_name_count_vegetation |
gns_name_count_vegetation | integer | 0% | 1 | 18 |
gns_feature_count_vegetation |
gns_feature_count_vegetation | integer | 0% | 1 | 17 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 900 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 437 |
| 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 | CHL |
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 | float | 0% | 1 | 6.5 |
oc_arms_trafficking_rank |
oc_arms_trafficking_rank | integer | 0% | 1 | 53 |
oc_arms_trafficking_2023 |
oc_arms_trafficking_2023 | float | 0% | 1 | 6.5 |
oc_arms_trafficking_2021 |
oc_arms_trafficking_2021 | float | 0% | 1 | 5.5 |
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_cocaine_trade_rank |
oc_cocaine_trade_rank | integer | 0% | 1 | 24 |
oc_cocaine_trade_2023 |
oc_cocaine_trade_2023 | float | 0% | 1 | 7.5 |
oc_cocaine_trade_2021 |
oc_cocaine_trade_2021 | integer | 0% | 1 | 7 |
oc_criminal_actors_rank |
oc_criminal_actors_rank | integer | 0% | 1 | 78 |
oc_criminal_actors_2023 |
oc_criminal_actors_2023 | float | 0% | 1 | 5.3 |
oc_criminal_actors_2021 |
oc_criminal_actors_2021 | float | 0% | 1 | 4.75 |
oc_criminal_markets_rank |
oc_criminal_markets_rank | integer | 0% | 1 | 71 |
oc_criminal_markets_2023 |
oc_criminal_markets_2023 | float | 0% | 1 | 5.07 |
oc_criminal_markets_2021 |
oc_criminal_markets_2021 | float | 0% | 1 | 4.45 |
oc_criminal_networks_rank |
oc_criminal_networks_rank | integer | 0% | 1 | 74 |
oc_criminal_networks_2023 |
oc_criminal_networks_2023 | integer | 0% | 1 | 6 |
oc_criminal_networks_2021 |
oc_criminal_networks_2021 | float | 0% | 1 | 5.5 |
oc_criminality_rank |
oc_criminality_rank | integer | 0% | 1 | 76 |
oc_criminality_2023 |
oc_criminality_2023 | float | 0% | 1 | 5.18 |
oc_criminality_2021 |
oc_criminality_2021 | float | 0% | 1 | 4.6 |
oc_cyber_dependent_crimes_rank |
oc_cyber_dependent_crimes_rank | integer | 0% | 1 | 60 |
| +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 | CHL |
| 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) | 26,351 | 99.8% | — |
| English (eng) | 49 | 0.2% | — |
45,306 distinct features ·
2 languages ·
0 scripts ·
11 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.