| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
population_count |
Population count | float | SEL | 0% | 27 | 1581196.0, 830018.0, 3941613.0, 636707.0, 8120131.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_code |
Administrative code | float | 0% | 27 | 11, 12, 13, 14, 15 |
admin_name |
Geographic unit name | string | 0% | 27 | Rondônia, Acre, Amazonas, Roraima, Pará |
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
população_residente_-_percentual_do_tota |
Resident population - percentage of total | float | 0% | 1 | 100.0, 100.0, 100.0, 100.0, 100.0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
population_15_64 |
Population aged 15 to 64 | float | SEL | 0% | 27 | 1256403.0, 624035.0, 2935887.0, 461473.0, 6269212.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_code |
Administrative code | float | 0% | 27 | 11, 12, 13, 14, 15 |
admin_name |
Geographic unit name | string | 0% | 27 | Rondônia, Acre, Amazonas, Roraima, Pará |
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
pessoas_de_14_anos_ou_mais_de_idade_-_pe |
Persons aged 14 years or older - percentage of total | float | 0% | 1 | 100.0, 100.0, 100.0, 100.0, 100.0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
literacy_rate_pct |
Literacy rate (percent) | float | SEL | 0% | 26 | 93.55, 87.87, 93.06, 93.08, 91.24 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_code |
Administrative code | float | 0% | 27 | 11, 12, 13, 14, 15 |
admin_name |
Geographic unit name | string | 0% | 27 | Rondônia, Acre, Amazonas, Roraima, Pará |
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
population_count |
Population count | float | SEL | 0% | 27 | 1581196.0, 830018.0, 3941613.0, 636707.0, 8120131.0 |
densidade_demográfica |
Population density | float | SEL | 0% | 27 | 6.65, 5.06, 2.53, 2.85, 6.52 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_code |
Administrative code | float | 0% | 27 | 11, 12, 13, 14, 15 |
admin_name |
Geographic unit name | string | 0% | 27 | Rondônia, Acre, Amazonas, Roraima, Pará |
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
área_da_unidade_territorial |
Area of territorial unit | float | 0% | 27 | 237754.172, 164173.429, 1559255.881, 223644.53, 1245870.704 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
population_count |
Population count | float | SEL | 0% | 27 | 1581196.0, 830018.0, 3941613.0, 636707.0, 8120131.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_code |
Administrative code | float | 0% | 27 | 11, 12, 13, 14, 15 |
admin_name |
Geographic unit name | string | 0% | 27 | Rondônia, Acre, Amazonas, Roraima, Pará |
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
população_residente_-_percentual_do_tota |
Resident population - percentage of total | float | 0% | 1 | 100.0, 100.0, 100.0, 100.0, 100.0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
population_count |
Population count | float | SEL | 0% | 100 | 21494.0, 96833.0, 5351.0, 86887.0, 15890.0 |
densidade_demográfica |
Population density | float | SEL | 0% | 91 | 3.04, 21.88, 4.07, 22.91, 5.71 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_code |
Administrative code | float | 0% | 100 | 1100015, 1100023, 1100031, 1100049, 1100056 |
admin_name |
Geographic unit name | string | 0% | 100 | Alta Floresta D'Oeste - RO, Ariquemes - RO, Cabixi - RO,... |
year |
Year | float | 0% | 1 | 2022, 2022, 2022, 2022, 2022 |
área_da_unidade_territorial |
Area of territorial unit | float | 0% | 100 | 7067.127, 4426.571, 1314.352, 3793.0, 2783.3 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
admin_level |
Administrative level (admin_0..admin_3) | string | SEL | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
admin_name |
Geographic unit name | string | SEL | 0% | 1 | , , , , |
setor_code |
Census-sector identifier (15-digit IBGE code) | float | SEL | 0% | 100 | 110001505000002, 110001505000003, 110001505000004,... |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
CD_setor |
Census-sector code (15-digit) | float | 0% | 100 | 110001505000002.0, 110001505000003.0, 110001505000004.0,... |
V00644 |
Aged 15-19 | float | 0% | 52 | 88.0, 38.0, 26.0, 75.0, 52.0 |
V00645 |
Aged 20-24 | float | 0% | 52 | 68.0, 47.0, 11.0, 71.0, 51.0 |
V00646 |
Aged 25-29 | float | 0% | 51 | 58.0, 44.0, 11.0, 53.0, 61.0 |
V00647 |
Aged 30-34 | float | 0% | 48 | 71.0, 44.0, 16.0, 64.0, 66.0 |
V00648 |
Aged 35-39 | float | 0% | 51 | 73.0, 39.0, 17.0, 60.0, 44.0 |
V00649 |
Aged 40-44 | float | 0% | 49 | 64.0, 47.0, 23.0, 51.0, 64.0 |
V00650 |
Aged 45-49 | float | 0% | 52 | 65.0, 48.0, 14.0, 41.0, 52.0 |
V00651 |
Aged 50-54 | float | 0% | 46 | 70.0, 31.0, 16.0, 41.0, 51.0 |
V00652 |
Aged 55-59 | float | 0% | 45 | 54.0, 17.0, 9.0, 47.0, 42.0 |
V00653 |
Aged 60-64 | float | 0% | 41 | 41.0, 26.0, 12.0, 38.0, 38.0 |
V00654 |
Aged 65-69 | float | 0% | 37 | 25.0, 21.0, 11.0, 19.0, 25.0 |
V00655 |
Aged 70-79 | float | 0% | 37 | 41.0, 23.0, 10.0, 24.0, 29.0 |
V00656 |
80 years and over | float | 0% | 23 | 12.0, 11.0, 7.0, 16.0, 17.0 |
V00657 |
Aged 15-19, color or race é white | float | 0% | 26 | 24.0, 11.0, 8.0, 25.0, 12.0 |
V00658 |
Aged 15-19, color or race é black | float | 0% | 10 | 5.0, 0.0, 0.0, 6.0, X |
V00659 |
Aged 15-19, color or race é yellow (Asian) | float | 0% | 2 | 0.0, 0.0, 0.0, 0.0, 0.0 |
V00660 |
Aged 15-19, color or race é brown (parda) | float | 0% | 41 | 58.0, 24.0, 18.0, 43.0, 38.0 |
V00661 |
Aged 15-19, color or race é indigenous | string | 0% | 8 | X, 3.0, 0.0, X, 0.0 |
V00662 |
Aged 20-24, color or race é white | float | 0% | 28 | 12.0, 15.0, X, 21.0, 13.0 |
V00663 |
Aged 20-24, color or race é black | float | 0% | 12 | 4.0, X, 0.0, 7.0, 5.0 |
V00664 |
Aged 20-24, color or race é yellow (Asian) | string | 0% | 2 | X, 0.0, 0.0, 0.0, 0.0 |
V00665 |
Aged 20-24, color or race é brown (parda) | float | 0% | 39 | 45.0, 30.0, 9.0, 41.0, 32.0 |
V00666 |
Aged 20-24, color or race é indigenous | float | 0% | 7 | 6.0, X, 0.0, X, X |
V00667 |
Aged 25-29, color or race é white | float | 0% | 28 | 27.0, 16.0, 4.0, 15.0, 19.0 |
V00668 |
Aged 25-29, color or race é black | float | 0% | 10 | 3.0, 3.0, X, 4.0, 5.0 |
V00669 |
Aged 25-29, color or race é yellow (Asian) | float | 0% | 2 | 0.0, 0.0, 0.0, 0.0, 0.0 |
V00670 |
Aged 25-29, color or race é brown (parda) | float | 0% | 40 | 28.0, 25.0, 5.0, 32.0, 35.0 |
V00671 |
Aged 25-29, color or race é indigenous | float | 0% | 8 | 0.0, 0.0, 0.0, X, X |
V00672 |
Aged 30-34, color or race é white | float | 0% | 30 | 19.0, 16.0, 5.0, 12.0, 17.0 |
| +335 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
admin_level |
Administrative level (admin_0..admin_3) | string | SEL | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
admin_name |
Geographic unit name | string | SEL | 0% | 7 | Alta Floresta D'Oeste, Alta Floresta D'Oeste, Alta... |
setor_code |
Census-sector identifier (15-digit IBGE code) | float | SEL | 0% | 100 | 110001505000002, 110001505000003, 110001505000004,... |
AREA_KM2 |
Sector area in square kilometres | float | SEL | 0% | 100 | 0.5393102, 0.2362175, 0.2118666, 0.5054477, 0.2990424 |
v0001 |
Total resident population | float | SEL | 0% | 85 | 928.0, 556.0, 222.0, 785.0, 748.0 |
v0002 |
Total private permanent households | float | SEL | 0% | 81 | 376.0, 243.0, 102.0, 318.0, 334.0 |
v0003 |
Total occupied private permanent households | float | SEL | 0% | 78 | 376.0, 243.0, 102.0, 318.0, 334.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
CD_SETOR |
Census-sector code (15-digit) | float | 0% | 100 | 110001505000002.0, 110001505000003.0, 110001505000004.0,... |
SITUACAO |
Setting (urban or rural label) | string | 0% | 2 | Urbana, Urbana, Urbana, Urbana, Urbana |
CD_SIT |
Setting code (urban/rural numeric) | float | 0% | 5 | 1.0, 1.0, 1.0, 1.0, 1.0 |
CD_TIPO |
Sector-type code (regular, special, etc.) | float | 0% | 5 | 0.0, 0.0, 0.0, 0.0, 0.0 |
CD_REGIAO |
Macro-region code (1=North, 2=Northeast, 3=Southeast, 4=South, 5=Center-West) | float | 0% | 1 | 1.0, 1.0, 1.0, 1.0, 1.0 |
NM_REGIAO |
Macro-region name | string | 0% | 1 | Norte, Norte, Norte, Norte, Norte |
CD_UF |
State (UF) code | float | 0% | 1 | 11.0, 11.0, 11.0, 11.0, 11.0 |
NM_UF |
State name | string | 0% | 1 | Rondônia, Rondônia, Rondônia, Rondônia, Rondônia |
CD_MUN |
Municipality code (7-digit) | float | 0% | 2 | 1100015.0, 1100015.0, 1100015.0, 1100015.0, 1100015.0 |
NM_MUN |
Municipality name | string | 0% | 2 | Alta Floresta D'Oeste, Alta Floresta D'Oeste, Alta... |
CD_DIST |
District code | float | 0% | 7 | 110001505.0, 110001505.0, 110001505.0, 110001505.0, 110001505.0 |
NM_DIST |
District name | string | 0% | 7 | Alta Floresta D'Oeste, Alta Floresta D'Oeste, Alta... |
CD_SUBDIST |
Sub-district code | float | 0% | 7 | 11000150500.0, 11000150500.0, 11000150500.0,... |
NM_SUBDIST |
Sub-district name | string | 100% | - | - |
CD_BAIRRO |
Neighborhood code | float | 0% | 12 | 1100015006.0, 1100015006.0, 1100015005.0, 1100015005.0,... |
NM_BAIRRO |
Neighborhood name | string | 67% | 11 | Redondo, Redondo, Princesa Isabel, Princesa Isabel,... |
CD_NU |
Urban-nucleus code | string | 0% | 2 | ., ., ., ., . |
NM_NU |
Urban-nucleus name | string | 99% | 1 | Loteamento Canaã |
CD_FCU |
Concentrated-rural-fringe code | string | 0% | 1 | ., ., ., ., . |
NM_FCU |
Concentrated-rural-fringe name | string | 100% | - | - |
CD_AGLOM |
Population-agglomeration code | string | 0% | 20 | ., ., ., ., . |
NM_AGLOM |
Population-agglomeration name | string | 81% | 19 | Vila Marcão, Aldeia Indígena Aldeia Jatobá, Aldeia... |
CD_RGINT |
Intermediate Geographic Region code | float | 0% | 2 | 1102.0, 1102.0, 1102.0, 1102.0, 1102.0 |
NM_RGINT |
Intermediate Geographic Region name | string | 0% | 2 | Ji-Paraná, Ji-Paraná, Ji-Paraná, Ji-Paraná, Ji-Paraná |
CD_RGI |
Immediate Geographic Region code | float | 0% | 2 | 110005.0, 110005.0, 110005.0, 110005.0, 110005.0 |
NM_RGI |
Immediate Geographic Region name | string | 0% | 2 | Cacoal, Cacoal, Cacoal, Cacoal, Cacoal |
CD_CONCURB |
Urban concentration code | string | 0% | 1 | ., ., ., ., . |
NM_CONCURB |
Urban concentration name | string | 100% | - | - |
v0004 |
Average resident population per occupied private permanent household | float | 0% | 5 | 0.0, 0.0, 0.0, 0.0, 0.0 |
v0005 |
Average household nominal monthly income (BRL) | float | 0% | 23 | 2.8, 2.7, 2.6, 2.8, 2.6 |
| +4 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
admin_level |
Administrative level (admin_0..admin_3) | string | SEL | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
admin_name |
Geographic unit name | string | SEL | 0% | 1 | , , , , |
setor_code |
Census-sector identifier (15-digit IBGE code) | float | SEL | 0% | 100 | 110001505000002, 110001505000003, 110001505000004,... |
V01317 |
Color or race é white | float | CCL | 0% | 73 | 312.0, 189.0, 71.0, 255.0, 229.0 |
V01318 |
Color or race é black | float | CCL | 0% | 51 | 87.0, 25.0, 14.0, 54.0, 49.0 |
V01319 |
Color or race é yellow (Asian) | string | CCL | 0% | 8 | X, 0.0, 0.0, X, X |
V01320 |
Color or race é brown (parda) | float | CCL | 0% | 76 | 514.0, 336.0, 135.0, 460.0, 459.0 |
V01321 |
Color or race é indigenous | float | CCL | 0% | 20 | 13.0, 6.0, X, 14.0, 10.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
CD_SETOR |
Census-sector code (15-digit) | float | 0% | 100 | 110001505000002.0, 110001505000003.0, 110001505000004.0,... |
V01322 |
Male, color or race é white | float | 0% | 65 | 138.0, 80.0, 26.0, 136.0, 105.0 |
V01323 |
Male, color or race é black | float | 0% | 38 | 45.0, 13.0, 8.0, 35.0, 29.0 |
V01324 |
Male, color or race é yellow (Asian) | float | 0% | 6 | 0.0, 0.0, 0.0, X, X |
V01325 |
Male, color or race é brown (parda) | float | 0% | 66 | 238.0, 174.0, 74.0, 232.0, 233.0 |
V01326 |
Male, color or race é indigenous | float | 0% | 16 | 7.0, 3.0, 0.0, 4.0, 5.0 |
V01327 |
Female, color or race é white | float | 0% | 69 | 174.0, 109.0, 45.0, 119.0, 124.0 |
V01328 |
Female, color or race é black | float | 0% | 33 | 42.0, 12.0, 6.0, 19.0, 20.0 |
V01329 |
Female, color or race é yellow (Asian) | string | 0% | 5 | X, 0.0, 0.0, 0.0, 0.0 |
V01330 |
Female, color or race é brown (parda) | float | 0% | 70 | 276.0, 162.0, 61.0, 228.0, 226.0 |
V01331 |
Female, color or race é indigenous | float | 0% | 14 | 6.0, 3.0, X, 10.0, 5.0 |
V01332 |
Color or race of persons responsible for the household pelo households é white | float | 0% | 59 | 109.0, 60.0, 30.0, 85.0, 100.0 |
V01333 |
Color or race of persons responsible for the household pelo households é black | float | 0% | 34 | 44.0, 14.0, 10.0, 19.0, 21.0 |
V01334 |
Color or race of persons responsible for the household pelo households é yellow (Asian) | float | 0% | 5 | 0.0, 0.0, 0.0, X, X |
V01335 |
Color or race of persons responsible for the household pelo households é brown (parda) | float | 0% | 67 | 179.0, 132.0, 44.0, 175.0, 164.0 |
V01336 |
Color or race of persons responsible for the household pelo households é indigenous | float | 0% | 11 | 4.0, X, X, X, 5.0 |
V01337 |
Color or race of persons responsible for the household pelo households é white, sex of persons responsible for the household pelo households é male | float | 0% | 49 | 53.0, 25.0, 7.0, 29.0, 41.0 |
V01338 |
Color or race of persons responsible for the household pelo households é white, sex of persons responsible for the household pelo households é female | float | 0% | 48 | 56.0, 35.0, 23.0, 56.0, 59.0 |
V01339 |
Color or race of persons responsible for the household pelo households é black, sex of persons responsible for the household pelo households é male | float | 0% | 21 | 25.0, 3.0, 4.0, 11.0, 10.0 |
V01340 |
Color or race of persons responsible for the household pelo households é black, sex of persons responsible for the household pelo households é female | float | 0% | 20 | 19.0, 11.0, 6.0, 8.0, 11.0 |
V01341 |
Color or race of persons responsible for the household pelo households é yellow (Asian), sex of persons responsible for the household pelo households é male | float | 0% | 2 | 0.0, 0.0, 0.0, X, X |
V01342 |
Color or race of persons responsible for the household pelo households é yellow (Asian), sex of persons responsible for the household pelo households é female | float | 0% | 3 | 0.0, 0.0, 0.0, 0.0, 0.0 |
V01343 |
Color or race of persons responsible for the household pelo households é brown (parda), sex of persons responsible for the household pelo households é male | float | 0% | 52 | 80.0, 51.0, 15.0, 58.0, 97.0 |
V01344 |
Color or race of persons responsible for the household pelo households é brown (parda), sex of persons responsible for the household pelo households é female | float | 0% | 55 | 99.0, 81.0, 29.0, 117.0, 67.0 |
V01345 |
Color or race of persons responsible for the household pelo households é indigenous, sex of persons responsible for the household pelo households é male | string | 0% | 9 | X, X, 0.0, X, X |
V01346 |
Color or race of persons responsible for the household pelo households é indigenous, sex of persons responsible for the household pelo households é female | string | 0% | 7 | X, 0.0, X, X, 3.0 |
V01347 |
Color or race of persons responsible for the household pelo households é white, aged 12-17 | float | 0% | 5 | 0.0, X, 0.0, 3.0, 0.0 |
V01348 |
Color or race of persons responsible for the household pelo households é white, aged 18-24 | float | 0% | 11 | 4.0, 7.0, X, 11.0, 7.0 |
V01349 |
Color or race of persons responsible for the household pelo households é white, aged 25-39 | float | 0% | 33 | 23.0, 17.0, 5.0, 13.0, 27.0 |
V01350 |
Color or race of persons responsible for the household pelo households é white, aged 40-59 | float | 0% | 42 | 54.0, 21.0, 14.0, 29.0, 42.0 |
| +63 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code (ISO 3166-1 alpha-3) | string | SEL+ | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
admin_level |
Administrative level (admin_0..admin_3) | string | SEL | 0% | 1 | admin_3, admin_3, admin_3, admin_3, admin_3 |
admin_name |
Geographic unit name | string | SEL | 0% | 1 | , , , , |
setor_code |
Census-sector identifier (15-digit IBGE code) | float | SEL | 0% | 100 | 110001505000002, 110001505000003, 110001505000004,... |
population_0_14 |
Population aged 0-14 (both sexes, derived) | integer | SEL | 0% | - | - |
population_60_plus |
Population aged 60 and over (both sexes, derived) | integer | SEL | 0% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
CD_setor |
Census-sector code (15-digit) | float | 0% | 100 | 110001505000002.0, 110001505000003.0, 110001505000004.0,... |
V01006 |
Quantidade of residents | float | 0% | 81 | 928.0, 556.0, 222.0, 785.0, 748.0 |
V01007 |
Male | float | 0% | 83 | 428.0, 270.0, 108.0, 408.0, 373.0 |
V01008 |
Female | float | 0% | 83 | 500.0, 286.0, 114.0, 377.0, 375.0 |
V01009 |
Male, aged 0-4 | float | 0% | 32 | 30.0, 15.0, 5.0, 36.0, 28.0 |
V01010 |
Male, aged 5-9 | float | 0% | 36 | 39.0, 20.0, 4.0, 33.0, 25.0 |
V01011 |
Male, aged 10-14 | float | 0% | 35 | 24.0, 20.0, 9.0, 34.0, 33.0 |
V01012 |
Male, aged 15-19 | float | 0% | 38 | 44.0, 19.0, 14.0, 41.0, 27.0 |
V01013 |
Male, aged 20-24 | float | 0% | 35 | 36.0, 30.0, 7.0, 42.0, 24.0 |
V01014 |
Male, aged 25-29 | float | 0% | 37 | 25.0, 20.0, 5.0, 27.0, 31.0 |
V01015 |
Male, aged 30-39 | float | 0% | 51 | 63.0, 46.0, 16.0, 65.0, 52.0 |
V01016 |
Male, aged 40-49 | float | 0% | 49 | 53.0, 45.0, 13.0, 42.0, 52.0 |
V01017 |
Male, aged 50-59 | float | 0% | 47 | 57.0, 21.0, 14.0, 38.0, 50.0 |
V01018 |
Male, aged 60-69 | float | 0% | 35 | 34.0, 20.0, 10.0, 32.0, 29.0 |
V01019 |
Male, 70 years and over | float | 0% | 28 | 23.0, 14.0, 11.0, 18.0, 22.0 |
V01020 |
Female, aged 0-4 | float | 0% | 30 | 38.0, 22.0, 8.0, 25.0, 22.0 |
V01021 |
Female, aged 5-9 | float | 0% | 31 | 29.0, 16.0, 7.0, 30.0, 27.0 |
V01022 |
Female, aged 10-14 | float | 0% | 31 | 38.0, 27.0, 6.0, 27.0, 21.0 |
V01023 |
Female, aged 15-19 | float | 0% | 36 | 44.0, 19.0, 12.0, 34.0, 25.0 |
V01024 |
Female, aged 20-24 | float | 0% | 34 | 32.0, 17.0, 4.0, 29.0, 27.0 |
V01025 |
Female, aged 25-29 | float | 0% | 41 | 33.0, 24.0, 6.0, 26.0, 30.0 |
V01026 |
Female, aged 30-39 | float | 0% | 50 | 81.0, 37.0, 17.0, 59.0, 58.0 |
V01027 |
Female, aged 40-49 | float | 0% | 49 | 76.0, 50.0, 24.0, 50.0, 64.0 |
V01028 |
Female, aged 50-59 | float | 0% | 44 | 67.0, 27.0, 11.0, 50.0, 43.0 |
V01029 |
Female, aged 60-69 | float | 0% | 39 | 32.0, 27.0, 13.0, 25.0, 34.0 |
V01030 |
Female, 70 years and over | float | 0% | 31 | 30.0, 20.0, 6.0, 22.0, 24.0 |
V01031 |
Aged 0-4 | float | 0% | 47 | 68.0, 37.0, 13.0, 61.0, 50.0 |
V01032 |
Aged 5-9 | float | 0% | 48 | 68.0, 36.0, 11.0, 63.0, 52.0 |
V01033 |
Aged 10-14 | float | 0% | 53 | 62.0, 47.0, 15.0, 61.0, 54.0 |
V01034 |
Aged 15-19 | float | 0% | 52 | 88.0, 38.0, 26.0, 75.0, 52.0 |
| +9 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 | BRA, BRA, BRA, BRA, BRA |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 28 | Total, Acre, Alagoas, Amapa, Amazonas |
human_development_index |
Human development index | float | SEL | 0% | 76 | 0.737, 0.657, 0.654, 0.734, 0.692 |
health_index |
Health index | float | SEL | 0% | 49 | 0.706, 0.692, 0.679, 0.707, 0.706 |
education_index |
Education index | float | SEL | 0% | 87 | 0.783, 0.664, 0.651, 0.815, 0.717 |
income_index |
Income index | float | SEL | 0% | 68 | 0.725, 0.618, 0.635, 0.687, 0.655 |
life_expectancy |
Life expectancy | float | SEL | 0% | 84 | 65.86, 64.95, 64.11, 65.99, 65.87 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 89 | 11.75, 9.23, 8.319, 12.0, 10.93 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 4 | 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 | BRA |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | Brazil |
admin_code |
Admin code | string | SEL | 0% | 1 | 88855331B58508533874502 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 8510278.5336 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 219575585 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 25.8 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
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% | 27 | Sao Paulo, Minas Gerais, Rio de Jeneiro, Bahia, Parana |
admin_code |
Admin code | string | SEL | 0% | 27 | 14911670B46470234103867, 14911670B44044837234259,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 27 | 249712.4481, 590464.5793, 45709.8674, 569146.6403, 198860.7151 |
pop_2024 |
Population count | integer | SEL | 0% | 27 | 48490484, 22168908, 17123520, 15397692, 12786651 |
pop_density_2024 |
Population density | float | SEL | 0% | 27 | 194.19, 37.54, 374.61, 27.05, 64.3 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality, locality, locality, locality |
admin_name |
Admin name | string | SEL | 0% | 100 | São Paulo, Rio de Janeiro, Belo Horizonte, Recife, Fortaleza |
admin_code |
Admin code | integer | SEL | 0% | 100 | 7277, 7799, 7676, 8388, 8154 |
area_sqkm |
Area sqkm | float | SEL | 0% | 100 | 2101.367, 1278.9784, 605.8658, 487.831, 410.2606 |
pop_2024 |
Population count | integer | SEL | 0% | 100 | 21124070, 9220846, 4006447, 3327682, 3221684 |
pop_density_2024 |
Population density | float | SEL | 0% | 100 | 10052.54, 7209.54, 6612.76, 6821.38, 7852.77 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 100 | 19485158, 9853693, 4376747, 3847558, 3324149 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 93 | 1.084, 0.936, 0.915, 0.865, 0.969 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 100 | São Paulo, Rio de Janeiro, Belo Horizonte, Recife, Fortaleza |
country_code |
Country code | string | SEL | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
population |
Population count | integer | SEL | 0% | 100 | 19485158, 9853693, 4376747, 3847558, 3324149 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 100 | 7277, 7799, 7676, 8388, 8154 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Brazil, Brazil, Brazil, Brazil, Brazil |
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% | 100 | acro1239, agav1236, aika1237, akaw1239, akun1241 |
name |
Name | string | CCL | 0% | 100 | Acroá, Agavotaguerra, Aikanã, Akawaio-Ingariko, Akuntsu |
iso639_3 |
Iso639 3 | string | CCL | 28% | 72 | acs, avo, tba, ake, aqz |
level |
Level | string | CCL | 0% | 1 | language, language, language, language, language |
family_name |
Family name | string | CCL | 100% | - | - |
family_glottocode |
Family glottocode | string | CCL | 6% | 20 | nucl1710, unat1236, cari1283, tupi1275, unat1236 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 6% | 74 | jece1235, araw1288, kapo1251, akun1243, namb1301 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 15 | ['BR'], ['BR'], ['BR'], ['BR', 'GY', 'VE'], ['BR'] |
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% | 9 | 0, 0, 1, 2, 0 |
country_code |
Country code | string | SEL | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 7% | 93 | -12.20318, -13.29849, -12.6695, 6.16277, -12.8322 |
longitude |
longitude | float | 7% | 93 | -45.08975, -53.43936, -60.5353, -60.862, -60.9716 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
source |
source | string | 0% | 1 | Glottolog 5.0, Glottolog 5.0, Glottolog 5.0, Glottolog... |
source_url |
source_url | string | 0% | 1 | https://glottolog.org, https://glottolog.org,... |
license |
license | string | 0% | 1 | CC BY 4.0, CC BY 4.0, CC BY 4.0, CC BY 4.0, CC BY 4.0 |
data_vintage |
data_vintage | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
| 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% | - | - |
source |
source | string | 0% | 1 | UNHCR Refugee Data Finder, UNHCR Refugee Data Finder,... |
source_url |
source_url | string | 0% | 1 | https://www.unhcr.org/refugee-statistics/,... |
license |
license | string | 0% | 1 | Open access with attribution, Open access with... |
country_code |
country_code | string | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
| 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% | - | - |
source |
source | string | 0% | 1 | UNHCR Refugee Data Finder, UNHCR Refugee Data Finder,... |
source_url |
source_url | string | 0% | 1 | https://www.unhcr.org/refugee-statistics/,... |
license |
license | string | 0% | 1 | Open access with attribution, Open access with... |
country_code |
country_code | string | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BR, BR, BR, BR, BR |
population_count |
Population count | float | SEL | 2% | 65 | 72388126.0, 74605447.0, 76865323.0, 79164235.0, 81488595.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 53.162, 53.594, 54.017, 54.452, 54.848 |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 2% | 65 | 235.266009502589, 231.564063269854, 250.200572910273,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 67% | 22 | 74.5899963378906, 86.370002746582, 88.620002746582,... |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 169.4, 164.7, 160.3, 156.1, 152.2 |
poverty_headcount_pct |
Poverty headcount percent | string | SEL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Brazil, Brazil, Brazil, Brazil, Brazil |
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 | BR, BR, BR, BR, BR |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 53.162, 53.594, 54.017, 54.452, 54.848 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 8% | 58 | 49.5, 49.2, 48.9, 48.7, 48.4 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 169.4, 164.7, 160.3, 156.1, 152.2 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 30 | 186.0, 176.0, 167.0, 161.0, 150.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 63 | 6.051, 6.022, 5.984, 5.93, 5.818 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 64 | 43.85, 43.292, 42.698, 42.014, 41.001 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 64 | 13.591, 13.265, 12.949, 12.627, 12.304 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 65% | 23 | 0.374, 0.4, 0.492, 0.624, 0.767 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 58% | 24 | 3.20179533958435, 3.69180011749268, 4.9951000213623,... |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 32% | 27 | 37.0, 47.0, 56.0, 60.0, 68.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 8.33457184, 8.54963303, 8.69686985, 8.18899441, 8.12491989 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Brazil, Brazil, Brazil, Brazil, Brazil |
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 | BRA, BRA, BRA, BRA, BRA |
society_id |
Society id | string | CCL | 0% | 30 | Sc15, Sc5, Sd1, Sd2, Sd3 |
society_name |
Society name | string | CCL | 0% | 30 | Taulípang, Wapishana, Munduruku, Tapirapé, Palikur |
language_glottocode |
Language glottocode | string | CCL | 0% | 30 | taul1252, wapi1253, mund1330, tapi1254, pali1279 |
language_name |
Language name | string | CCL | 0% | 1 | , , , , |
kinship_system |
Kinship system | string | CCL | 0% | 20 | EA001:1; EA002:2; EA003:3; EA004:0; EA005:4, EA001:2;... |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 25 | EA006:2; EA007:8; EA008:2; EA009:2; EA010:9, EA006:2;... |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 21 | EA028:3; EA029:5; EA030:7; EA031:NA; EA032:2, EA028:3;... |
political_complexity |
Political complexity | string | CCL | 0% | 11 | EA033:1; EA034:NA; EA035:NA, EA033:1; EA034:NA; EA035:2,... |
religion_importance |
Religion importance | string | CCL | 0% | 16 | EA034:NA; EA112:4, EA034:NA; EA112:2, EA034:1; EA112:1,... |
residence_pattern |
Residence pattern | string | CCL | 0% | 13 | EA011:3; EA012:9; EA013:9, EA011:1; EA012:10; EA013:9,... |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Brazil, Brazil, Brazil, Brazil, Brazil |
dataset |
dataset | string | 0% | 1 | EA, EA, EA, EA, EA |
region |
region | string | 0% | 1 | , , , , |
latitude |
latitude | float | 0% | 21 | 4.0, 3.0, -6.0, -11.0, 3.0 |
longitude |
longitude | float | 0% | 19 | -62.0, -60.0, -58.0, -52.0, -52.0 |
assignment_method |
assignment_method | string | 0% | 1 | point_in_polygon, point_in_polygon, point_in_polygon,... |
assignment_confidence |
assignment_confidence | string | 0% | 1 | approximate, approximate, approximate, approximate, approximate |
source |
source | string | 0% | 1 | D-PLACE: Database of Places, Language, Culture, and... |
source_url |
source_url | string | 0% | 1 | https://d-place.org, https://d-place.org,... |
license |
license | string | 0% | 1 | CC BY 4.0, CC BY 4.0, CC BY 4.0, CC BY 4.0, CC BY 4.0 |
data_vintage |
data_vintage | float | 0% | 1 | 2024, 2024, 2024, 2024, 2024 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
society_id |
Society id | string | CCL | 0% | 30 | Sc15, Sc5, Sd1, Sd2, Sd3 |
society_name |
Society name | string | CCL | 0% | 30 | Taulípang, Wapishana, Munduruku, Tapirapé, Palikur |
language_glottocode |
Language glottocode | string | CCL | 0% | 30 | taul1252, wapi1253, mund1330, tapi1254, pali1279 |
language_name |
Language name | string | CCL | 0% | 1 | , , , , |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Brazil, Brazil, Brazil, Brazil, Brazil |
dataset |
dataset | string | 0% | 1 | EA, EA, EA, EA, EA |
region |
region | string | 0% | 1 | , , , , |
latitude |
latitude | float | 0% | 21 | 4.0, 3.0, -6.0, -11.0, 3.0 |
longitude |
longitude | float | 0% | 19 | -62.0, -60.0, -58.0, -52.0, -52.0 |
assignment_method |
assignment_method | string | 0% | 1 | point_in_polygon, point_in_polygon, point_in_polygon,... |
assignment_confidence |
assignment_confidence | string | 0% | 1 | approximate, approximate, approximate, approximate, approximate |
mode_of_marriage |
mode_of_marriage | integer | 0% | 5 | 1, 2, 1, 1, 0 |
family_organization |
family_organization | integer | 0% | 7 | 2, 2, 3, 1, 2 |
marital_composition |
marital_composition | integer | 0% | 5 | 3, 2, 2, 3, 3 |
community_marriage_org |
community_marriage_org | integer | 0% | 3 | 0, 0, 0, 0, 0 |
kin_group_structure |
kin_group_structure | integer | 0% | 6 | 4, 4, 4, 5, 5 |
mode_of_marriage_transaction |
mode_of_marriage_transaction | integer | 3% | 4 | 2, 2, 2, 6, 6 |
bride_price_type |
bride_price_type | integer | 3% | 2 | 8, 8, 8, 8, 8 |
ground_for_divorce |
ground_for_divorce | integer | 7% | 6 | 2, 4, 8, 8, 1 |
ease_of_divorce |
ease_of_divorce | integer | 7% | 5 | 2, 6, 2, 1, 1 |
marriage_arrangement |
marriage_arrangement | integer | 7% | 8 | 9, 9, 11, 9, 2 |
predominant_subsistence |
predominant_subsistence | integer | 7% | 3 | 3, 3, 3, 3, 3 |
gathering_dependence |
gathering_dependence | integer | 7% | 3 | 5, 5, 5, 5, 5 |
hunting_dependence |
hunting_dependence | integer | 7% | 6 | 7, 7, 7, 7, 7 |
fishing_dependence |
fishing_dependence | integer | 37% | 5 | 2, 3, 2, 1, 3 |
animal_husbandry_dependence |
animal_husbandry_dependence | integer | 7% | 3 | 2, 3, 3, 3, 2 |
jurisdictional_hierarchy |
jurisdictional_hierarchy | integer | 7% | 3 | 1, 1, 1, 1, 1 |
community_integration |
community_integration | integer | 30% | 3 | 1, 1, 1, 1, 1 |
settlement_pattern |
settlement_pattern | integer | 43% | 2 | 2, 2, 2, 2, 2 |
high_gods |
high_gods | integer | 17% | 7 | 4, 2, 1, 1, 7 |
residence_after_marriage |
residence_after_marriage | integer | 7% | 3 | 3, 1, 2, 3, 1 |
community_residence |
community_residence | integer | 7% | 8 | 9, 10, 11, 9, 8 |
norms_of_residence |
norms_of_residence | integer | 7% | 4 | 9, 9, 1, 9, 3 |
source |
source | string | 0% | 1 | D-PLACE: Database of Places, Language, Culture, and... |
| +3 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 | BR, BR, BR, BR, BR |
admin_level |
Admin level | integer | SEL | 0% | 1 | 1, 1, 1, 1, 1 |
iso3 |
Country code | string | SEL | 0% | 1 | BRA, BRA, BRA, BRA, BRA |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
retail |
retail | float | 0% | 27 | -14.51, -1.22, -3.49, 8.56, 1.41 |
grocery |
grocery | float | 0% | 27 | 34.4, 12.26, 5.38, 34.28, 13.33 |
parks |
parks | float | 0% | 27 | -7.52, 0.64, -10.07, 4.32, -3.4 |
transit |
transit | float | 0% | 26 | 0.68, 26.59, 0.4, -0.95, 0.57 |
workplaces |
workplaces | float | 0% | 27 | -0.1, 14.27, 8.82, 20.24, 30.09 |
residential |
residential | float | 0% | 26 | 8.02, 3.27, 1.47, 4.13, 3.22 |
region |
region | string | 0% | 27 | Federal District, State of Acre, State of Alagoas, State... |
observation_count |
observation_count | integer | 0% | 27 | 974, 6356, 32005, 4500, 12879 |
| 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 | 11.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 102.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .br |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 84.0 |
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 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
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 | 22.5 million (2024 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 22.5 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 11 (2024 est.) |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 216 million (2024 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 216.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 102 (2024 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | state-run Radiobras operates a radio and a TV network;... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 1000.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 84% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 48.4 million (2023 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 48.4 |
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/br.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 | 19600.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 2.179 |
population_below_poverty_line_numeric |
Poverty headcount percent | float | SEL | 0% | 1 | 4.2 |
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
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 | upper-middle-income, largest Latin American economy;... |
economic_overview_numeric |
economic_overview_numeric | float | 0% | 1 | 20.0 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $4.165 trillion (2024 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_numeric |
Real gdp purchasing power parity 2024 (numeric) | float | 0% | 1 | 4.165 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $4.029 trillion (2023 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_numeric |
Real gdp purchasing power parity 2023 (numeric) | float | 0% | 1 | 4.029 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $3.902 trillion (2022 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_numeric |
Real gdp purchasing power parity 2022 (numeric) | float | 0% | 1 | 3.902 |
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 | 3.4% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | 3.4 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 3.2% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 3.2 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 3% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 3.0 |
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 | $19,600 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $19,100 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 19100.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $18,600 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 18600.0 |
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 | $2.179 trillion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 4.4% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 4.4 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text |
Inflation rate consumer prices 2023 (text) | string | 0% | 1 | 4.6% (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric |
Inflation rate consumer prices 2023 (numeric) | float | 0% | 1 | 4.6 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 9.3% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 9.3 |
inflation_rate_consumer_prices_note |
inflation_rate_consumer_prices_note | string | 0% | 1 | note: annual % change based on consumer prices |
| +123 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 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
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_access_electrification_urban_areas_text |
electricity_access_electrification_urban_areas_text | string | 0% | 1 | 100% |
electricity_access_electrification_urban_areas_numeric |
electricity_access_electrification_urban_areas_numeric | float | 0% | 1 | 100.0 |
electricity_access_electrification_rural_areas_text |
electricity_access_electrification_rural_areas_text | string | 0% | 1 | 97.3% |
electricity_access_electrification_rural_areas_numeric |
electricity_access_electrification_rural_areas_numeric | float | 0% | 1 | 97.3 |
electricity_installed_generating_capacity_text |
electricity_installed_generating_capacity_text | string | 0% | 1 | 240.251 million kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 240.251 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 608.451 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 608.451 |
electricity_exports_text |
electricity_exports_text | string | 0% | 1 | 7.186 billion kWh (2023 est.) |
electricity_exports_numeric |
electricity_exports_numeric | float | 0% | 1 | 7.186 |
electricity_imports_text |
electricity_imports_text | string | 0% | 1 | 22.294 billion kWh (2023 est.) |
electricity_imports_numeric |
electricity_imports_numeric | float | 0% | 1 | 22.294 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 106.916 billion kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 106.916 |
electricity_generation_sources_fossil_fuels_text |
electricity_generation_sources_fossil_fuels_text | string | 0% | 1 | 8.9% of total installed capacity (2023 est.) |
electricity_generation_sources_fossil_fuels_numeric |
electricity_generation_sources_fossil_fuels_numeric | float | 0% | 1 | 8.9 |
electricity_generation_sources_nuclear_text |
electricity_generation_sources_nuclear_text | string | 0% | 1 | 2.1% of total installed capacity (2023 est.) |
electricity_generation_sources_nuclear_numeric |
electricity_generation_sources_nuclear_numeric | float | 0% | 1 | 2.1 |
electricity_generation_sources_solar_text |
electricity_generation_sources_solar_text | string | 0% | 1 | 6.9% of total installed capacity (2023 est.) |
electricity_generation_sources_solar_numeric |
electricity_generation_sources_solar_numeric | float | 0% | 1 | 6.9 |
electricity_generation_sources_wind_text |
electricity_generation_sources_wind_text | string | 0% | 1 | 13.5% of total installed capacity (2023 est.) |
electricity_generation_sources_wind_numeric |
electricity_generation_sources_wind_numeric | float | 0% | 1 | 13.5 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 60.2% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 60.2 |
electricity_generation_sources_biomass_and_waste_text |
electricity_generation_sources_biomass_and_waste_text | string | 0% | 1 | 8.3% of total installed capacity (2023 est.) |
electricity_generation_sources_biomass_and_waste_numeric |
electricity_generation_sources_biomass_and_waste_numeric | float | 0% | 1 | 8.3 |
nuclear_energy_number_of_operational_nuclear_reactors_text |
nuclear_energy_number_of_operational_nuclear_reactors_text | string | 0% | 1 | 2 (2025) |
nuclear_energy_number_of_operational_nuclear_reactors_numeric |
nuclear_energy_number_of_operational_nuclear_reactors_numeric | float | 0% | 1 | 2.0 |
nuclear_energy_number_of_nuclear_reactors_under_construction_text |
nuclear_energy_number_of_nuclear_reactors_under_construction_text | string | 0% | 1 | 1 (2025) |
| +35 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 | 28.3 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 58.9 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 87.8 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 0.87 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 79.07 |
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
environmental_issues_text |
environmental_issues_text | string | 0% | 1 | deforestation in Amazon Basin; illegal wildlife trade;... |
international_environmental_agreements_party_to_text |
international_environmental_agreements_party_to_text | string | 0% | 1 | Antarctic-Environmental Protection, Antarctic-Marine... |
international_environmental_agreements_party_to_numeric |
international_environmental_agreements_party_to_numeric | float | 0% | 1 | 2006.0 |
international_environmental_agreements_signed_but_not_ratified_text |
international_environmental_agreements_signed_but_not_ratified_text | string | 0% | 1 | Marine Dumping-London Protocol |
climate_text |
climate_text | string | 0% | 1 | mostly tropical, but temperate in south |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 28.3% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 6.7% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 6.7 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.9% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.9 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 20.7% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 20.7 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 58.9% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 12.7% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 12.7 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 87.8% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 0.87% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 437.769 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 437.769 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 53.664 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 | 53.664 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 331.079 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 | 331.079 |
carbon_dioxide_emissions_from_consumed_natural_gas_text |
carbon_dioxide_emissions_from_consumed_natural_gas_text | string | 0% | 1 | 53.026 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 | 53.026 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 10.9 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 10.9 |
methane_emissions_energy_text |
methane_emissions_energy_text | string | 0% | 1 | 1,759.1 kt (2022-2024 est.) |
methane_emissions_energy_numeric |
methane_emissions_energy_numeric | float | 0% | 1 | 1759.1 |
methane_emissions_agriculture_text |
methane_emissions_agriculture_text | string | 0% | 1 | 13,761.9 kt (2019-2021 est.) |
| +22 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 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
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 | Brazilian(s) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Brazilian |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | mixed 45.3%, White 43.5%, Black 10.2%, Indigenous 0.6%,... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 45.3 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/br.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 8515770.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 8358140.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 157630.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 16145.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 7491.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 2994.0 |
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 | 28.3 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 58.9 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 91833.0 |
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
location_text |
location_text | string | 0% | 1 | Eastern South America, bordering the Atlantic Ocean |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 10 00 S, 55 00 W |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 10.0 |
map_references_text |
map_references_text | string | 0% | 1 | South America |
area_total_text |
area_total_text | string | 0% | 1 | 8,515,770 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 8,358,140 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 157,630 sq km |
area_note |
area_note | string | 0% | 1 | note: includes Arquipelago de Fernando de Noronha, Atol... |
area_comparative_text |
area_comparative_text | string | 0% | 1 | slightly smaller than the US |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 16,145 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | Argentina 1,263 km; Bolivia 3,403 km; Colombia 1,790 km;... |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 1263.0 |
coastline_text |
coastline_text | string | 0% | 1 | 7,491 km |
maritime_claims_territorial_sea_text |
maritime_claims_territorial_sea_text | string | 0% | 1 | 12 nm |
maritime_claims_territorial_sea_numeric |
maritime_claims_territorial_sea_numeric | float | 0% | 1 | 12.0 |
maritime_claims_contiguous_zone_text |
maritime_claims_contiguous_zone_text | string | 0% | 1 | 24 nm |
maritime_claims_contiguous_zone_numeric |
maritime_claims_contiguous_zone_numeric | float | 0% | 1 | 24.0 |
maritime_claims_exclusive_economic_zone_text |
maritime_claims_exclusive_economic_zone_text | string | 0% | 1 | 200 nm |
maritime_claims_exclusive_economic_zone_numeric |
maritime_claims_exclusive_economic_zone_numeric | float | 0% | 1 | 200.0 |
maritime_claims_continental_shelf_text |
maritime_claims_continental_shelf_text | string | 0% | 1 | 200 nm or to edge of the continental margin |
maritime_claims_continental_shelf_numeric |
maritime_claims_continental_shelf_numeric | float | 0% | 1 | 200.0 |
climate_text |
climate_text | string | 0% | 1 | mostly tropical, but temperate in south |
terrain_text |
terrain_text | string | 0% | 1 | mostly flat to rolling lowlands in north; some plains,... |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Pico da Neblina 2,994 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 | 320 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 320.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | alumina, bauxite, beryllium, gold, iron ore, manganese,... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 28.3% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 6.7% (2023 est.) |
| +24 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 | BRA |
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 | Federative Republic of Brazil |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Brazil |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | República Federativa do Brasil |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Brasil |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | the country name derives from the brazil tree that used... |
government_type_text |
government_type_text | string | 0% | 1 | federal presidential republic |
capital_name_text |
capital_name_text | string | 0% | 1 | Brasília |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 15 47 S, 47 55 W |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 15.0 |
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_time_zone_note_text |
capital_time_zone_note_text | string | 0% | 1 | Brazil has four time zones, including one for the... |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | the name is the Latinized form of the country name,... |
capital_etymology_numeric |
capital_etymology_numeric | float | 0% | 1 | 1960.0 |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 26 states (estados, singular - estado) and 1 federal... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 26.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | civil law |
constitution_history_text |
constitution_history_text | string | 0% | 1 | several previous; latest ratified 5 October 1988 |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 5.0 |
constitution_amendment_process_text |
constitution_amendment_process_text | string | 0% | 1 | proposed by at least one third of either house of the... |
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 | 4 years |
citizenship_residency_requirement_for_naturalization_numeric |
citizenship_residency_requirement_for_naturalization_numeric | float | 0% | 1 | 4.0 |
suffrage_text |
suffrage_text | string | 0% | 1 | voluntary between 16 to 18 years of age, over 70, and if... |
suffrage_numeric |
suffrage_numeric | float | 0% | 1 | 16.0 |
executive_branch_chief_of_state_text |
executive_branch_chief_of_state_text | string | 0% | 1 | President Luiz Inácio LULA da Silva (since 1 January 2023) |
executive_branch_chief_of_state_numeric |
executive_branch_chief_of_state_numeric | float | 0% | 1 | 1.0 |
| +94 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 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | After more than three centuries under Portuguese rule,... |
background_numeric |
background_numeric | float | 0% | 1 | 1822.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/br.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_languages_text |
Languages (text) | string | 0% | 1 | Portuguese (official and most widely spoken language);... |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | O Livro de Fatos Mundiais, a fonte indispensável para... |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/br.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
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 | 331,097 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 331097.0 |
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 19,043 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 19043.0 |
refugees_and_internally_displaced_persons_stateless_persons_text |
refugees_and_internally_displaced_persons_stateless_persons_text | string | 0% | 1 | 27 (2024 est.) |
refugees_and_internally_displaced_persons_stateless_persons_numeric |
refugees_and_internally_displaced_persons_stateless_persons_numeric | float | 0% | 1 | 27.0 |
trafficking_in_persons_tier_rating_text |
trafficking_in_persons_tier_rating_text | string | 0% | 1 | Tier 2 Watch List — Brazil did not demonstrate overall... |
trafficking_in_persons_tier_rating_numeric |
trafficking_in_persons_tier_rating_numeric | float | 0% | 1 | 2.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/br.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
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 | Brazilian Armed Forces (Forças Armadas Brasileiras):... |
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 | 1.1% of GDP (2024 est.) |
military_expenditures_military_expenditures_2024_numeric |
Military expenditures 2024 (numeric) | float | 0% | 1 | 1.1 |
military_expenditures_military_expenditures_2023_text |
Military expenditures 2023 (text) | string | 0% | 1 | 1.1% of GDP (2023 est.) |
military_expenditures_military_expenditures_2023_numeric |
Military expenditures 2023 (numeric) | float | 0% | 1 | 1.1 |
military_expenditures_military_expenditures_2022_text |
Military expenditures 2022 (text) | string | 0% | 1 | 1.2% of GDP (2022 est.) |
military_expenditures_military_expenditures_2022_numeric |
Military expenditures 2022 (numeric) | float | 0% | 1 | 1.2 |
military_expenditures_military_expenditures_2021_text |
Military expenditures 2021 (text) | string | 0% | 1 | 1.3% of GDP (2021 est.) |
military_expenditures_military_expenditures_2021_numeric |
Military expenditures 2021 (numeric) | float | 0% | 1 | 1.3 |
military_expenditures_military_expenditures_2020_text |
Military expenditures 2020 (text) | string | 0% | 1 | 1.4% of GDP (2020 est.) |
military_expenditures_military_expenditures_2020_numeric |
Military expenditures 2020 (numeric) | float | 0% | 1 | 1.4 |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | approximately 360,000 active Armed Forces (220,000 Army;... |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 360000.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the Brazilian military's inventory consists of a mix of... |
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 | 18-45 years of age for compulsory military service for... |
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 Brazilian Armed Forces (BAF) are the second largest... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 1640.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/br.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 221359387.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 108753532.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 112605855.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 19.6 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 69.5 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 10.9 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 44.3 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 28.1 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 16.2 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 35.4 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | 0.58 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 13.04 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 7.07 |
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 | 87.8 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 0.87 |
sex_ratio_at_birth_numeric |
Sex ratio at birth | float | SEL | 0% | 1 | 1.05 |
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 | 67.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 12.7 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 76.3 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 1.73 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 0.84 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 2.36 |
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 | 94.8 |
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
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 | 221,359,387 (2025 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 108,753,532 |
population_female_text |
population_female_text | string | 0% | 1 | 112,605,855 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 19.6% (male 22,025,593/female 21,088,398) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 69.5% (male 75,889,089/female 77,118,722) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 10.9% (2024 est.) (male 10,251,809/female 13,677,901) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 44.3 (2025 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 28.1 (2025 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 16.2 (2025 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 6.2 (2025 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 6.2 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 35.4 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 34 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 34.0 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 36.1 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 36.1 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | 0.58% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 13.04 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 7.07 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 | the vast majority of people live along or near the... |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 87.8% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 0.87% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 22.620 million São Paulo, 13.728 million Rio de Janeiro,... |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 22.62 |
sex_ratio_at_birth_text |
sex_ratio_at_birth_text | string | 0% | 1 | 1.05 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 | 0.98 male(s)/female |
sex_ratio_15_64_years_numeric |
sex_ratio_15_64_years_numeric | float | 0% | 1 | 0.98 |
| +85 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 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_religion_other_pct_synth |
other | numeric | CCL | 0% | - | 4.0 |
composition_ethnicity_primary_label_synth |
mixed | string | CCL | 0% | - | mixed |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Roman Catholic 56.8%, Evangelical 26.9%, none 9.3%,... |
religions_numeric |
religions_numeric | float | 0% | 1 | 56.8 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/br.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_roman_catholic_pct_synth |
Roman Catholic | numeric | 0% | - | 56.8 |
composition_religion_evangelical_pct_synth |
Evangelical | numeric | 0% | - | 26.9 |
composition_religion_none_pct_synth |
none | numeric | 0% | - | 9.3 |
composition_religion_spirtism_esp_rita_pct_synth |
Spirtism (Espírita) | numeric | 0% | - | 1.8 |
composition_religion_unspecified_pct_synth |
unspecified | numeric | 0% | - | 1.4 |
composition_religion_umbanda_and_candombl_pct_synth |
Umbanda and Candomblé | numeric | 0% | - | 1.1 |
composition_religion_indigenous_religions_pct_synth |
Indigenous religions | numeric | 0% | - | 0.06 |
composition_religion_undeclared_pct_synth |
undeclared | numeric | 0% | - | 0.2 |
composition_ethnicity_mixed_pct_synth |
mixed | numeric | 0% | - | 45.3 |
composition_ethnicity_white_pct_synth |
White | numeric | 0% | - | 43.5 |
composition_ethnicity_black_pct_synth |
Black | numeric | 0% | - | 10.2 |
composition_ethnicity_indigenous_pct_synth |
Indigenous | numeric | 0% | - | 0.6 |
composition_ethnicity_asian_pct_synth |
Asian | numeric | 0% | - | 0.4 |
composition_ethnicity_primary_share_pct_synth |
mixed | numeric | 0% | - | 45.3 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
space_agency_agencies_text |
space_agency_agencies_text | string | 0% | 1 | Brazilian Space Agency (Agência Espacial Brasileira,... |
space_agency_agencies_numeric |
space_agency_agencies_numeric | float | 0% | 1 | 1994.0 |
space_launch_site_s_text |
space_launch_site_s_text | string | 0% | 1 | Alcantara Launch Center (Maranhão state); Barreira do... |
space_launch_site_s_numeric |
space_launch_site_s_numeric | float | 0% | 1 | 2025.0 |
space_program_overview_text |
space_program_overview_text | string | 0% | 1 | develops, builds, operates, and tracks satellites,... |
space_program_overview_numeric |
space_program_overview_numeric | float | 0% | 1 | 2025.0 |
key_space_program_milestones_text |
key_space_program_milestones_text | string | 0% | 1 | 1960s - established a national space program under the... |
key_space_program_milestones_numeric |
key_space_program_milestones_numeric | float | 0% | 1 | 1960.0 |
source_section |
source_section | string | 0% | 1 | Space |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/br.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
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 | Hizballah; Tren de Aragua (TdA) |
source_section |
source_section | string | 0% | 1 | Terrorism |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/br.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
illicit_drugs_usg_identification_text |
illicit_drugs_usg_identification_text | string | 0% | 1 | major precursor-chemical producer (2025) |
illicit_drugs_usg_identification_numeric |
illicit_drugs_usg_identification_numeric | float | 0% | 1 | 2025.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/br.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 | PP |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 5297.0 |
country_code |
Country code | string | SEL | 0% | 1 | BRA |
country_name |
Country name | string | SEL | 0% | 1 | Brazil |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
airports_text |
airports_text | string | 0% | 1 | 5,297 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 1,871 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 1871.0 |
railways_total_text |
railways_total_text | string | 0% | 1 | 29,849.9 km (2014) |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 29849.9 |
railways_standard_gauge_text |
railways_standard_gauge_text | string | 0% | 1 | 194 km (2014) 1.435-m gauge |
railways_standard_gauge_numeric |
railways_standard_gauge_numeric | float | 0% | 1 | 194.0 |
railways_narrow_gauge_text |
railways_narrow_gauge_text | string | 0% | 1 | 23,341.6 km (2014) 1.000-m gauge (24 km electrified) |
railways_narrow_gauge_numeric |
railways_narrow_gauge_numeric | float | 0% | 1 | 23341.6 |
railways_broad_gauge_text |
railways_broad_gauge_text | string | 0% | 1 | 5,822.3 km (2014) 1.600-m gauge (498.3 km electrified) |
railways_broad_gauge_numeric |
railways_broad_gauge_numeric | float | 0% | 1 | 5822.3 |
railways_dual_gauge_text |
railways_dual_gauge_text | string | 0% | 1 | 492 km (2014) 1.600-1.000-m gauge |
railways_dual_gauge_numeric |
railways_dual_gauge_numeric | float | 0% | 1 | 492.0 |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 888 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 888.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | bulk carrier 13, container ship 20, general cargo 38,... |
merchant_marine_by_type_numeric |
merchant_marine_by_type_numeric | float | 0% | 1 | 13.0 |
ports_total_ports_text |
ports_total_ports_text | string | 0% | 1 | 45 (2024) |
ports_total_ports_numeric |
ports_total_ports_numeric | float | 0% | 1 | 45.0 |
ports_large_text |
ports_large_text | float | 0% | 1 | 4 |
ports_large_numeric |
ports_large_numeric | float | 0% | 1 | 4.0 |
ports_medium_text |
ports_medium_text | float | 0% | 1 | 7 |
ports_medium_numeric |
ports_medium_numeric | float | 0% | 1 | 7.0 |
ports_small_text |
ports_small_text | float | 0% | 1 | 19 |
ports_small_numeric |
ports_small_numeric | float | 0% | 1 | 19.0 |
ports_very_small_text |
ports_very_small_text | float | 0% | 1 | 15 |
ports_very_small_numeric |
ports_very_small_numeric | float | 0% | 1 | 15.0 |
ports_ports_with_oil_terminals_text |
Ports with oil terminals (text) | float | 0% | 1 | 31 |
ports_ports_with_oil_terminals_numeric |
Ports with oil terminals (numeric) | float | 0% | 1 | 31.0 |
ports_key_ports_text |
ports_key_ports_text | string | 0% | 1 | Belem, DTSE/Gegua Oil Terminal, Itajai, Port de... |
| +2 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 | BRA, BRA, BRA, BRA |
gns_language_code |
gns_language_code | string | CCL | 0% | 4 | por, spa, fra, eng |
gns_language_name |
gns_language_name | string | CCL | 0% | 4 | Portuguese, Spanish, French, English |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 4 | 211639, 203, 103, 43 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 4 | 99.8354, 0.0958, 0.0486, 0.0203 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 1 | 0, 0, 0, 0 |
gns_dominant_script_code |
gns_dominant_script_code | string | CCL | 0% | 1 | , , , |
gns_dominant_script_name |
gns_dominant_script_name | string | CCL | 0% | 1 | , , , |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 0, 0, 0, 0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | BRA |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Brazil |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 4 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 0 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 99.997 |
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 | 266623 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 228920 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 266615 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 8 |
gns_source_build_date |
gns_source_build_date | string | 0% | 1 | Wed, 05 Aug 2026 |
gns_source_change_date |
gns_source_change_date | string | 0% | 1 | 2026-08-05 |
gns_name_count_populated_places |
gns_name_count_populated_places | integer | 0% | 1 | 84257 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 71218 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 39132 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 37467 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 5192 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 4939 |
gns_name_count_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 109945 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 95464 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 16712 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 14181 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 11330 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 5601 |
gns_name_count_vegetation |
gns_name_count_vegetation | integer | 0% | 1 | 29 |
gns_feature_count_vegetation |
gns_feature_count_vegetation | integer | 0% | 1 | 28 |
gns_name_count_transportation_networks |
gns_name_count_transportation_networks | integer | 0% | 1 | 26 |
gns_feature_count_transportation_networks |
gns_feature_count_transportation_networks | integer | 0% | 1 | 22 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA, BRA, BRA |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 3 | Afrobrazilians, Whites, Indigenous peoples |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 2 | POWERLESS, MONOPOLY, POWERLESS |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 3 | 0.507, 0.477, 0.004 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 3 | 14002000, 14001000, 14003000 |
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 | BRA |
| 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 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | BRA |
importance_family_mean |
Importance family mean | float | CCL | 0% | 1 | 1.17 |
importance_friends_mean |
Importance friends mean | float | CCL | 0% | 1 | 1.795 |
importance_leisure_mean |
Importance leisure mean | float | CCL | 0% | 1 | 2.694 |
importance_politics_mean |
Importance politics mean | float | CCL | 0% | 1 | 1.44 |
importance_religion_mean |
Importance religion mean | float | CCL | 0% | 1 | 1.736 |
happiness_mean |
Happiness mean | float | CCL | 0% | 1 | 1.829 |
freedom_of_choice_mean |
Freedom of choice mean | float | CCL | 0% | 1 | 7.556 |
life_satisfaction_mean |
Life satisfaction mean | float | CCL | 0% | 1 | 7.563 |
trust_most_people_mean |
Trust most people mean | float | CCL | 0% | 1 | 1.934 |
trust_family_mean |
Trust family mean | float | CCL | 0% | 1 | 1.545 |
trust_neighbors_mean |
Trust neighbors mean | float | CCL | 0% | 1 | 2.53 |
trust_people_know_personally_mean |
Trust people know personally mean | float | CCL | 0% | 1 | 2.381 |
trust_strangers_mean |
Trust strangers mean | float | CCL | 0% | 1 | 3.201 |
trust_other_religion_mean |
Trust other religion mean | float | CCL | 0% | 1 | 2.529 |
trust_other_nationality_mean |
Trust other nationality mean | float | CCL | 0% | 1 | 2.907 |
confidence_parliament_mean |
Confidence parliament mean | float | CCL | 0% | 1 | 2.244 |
confidence_government_mean |
Confidence government mean | float | CCL | 0% | 1 | 2.29 |
confidence_press_mean |
Confidence press mean | float | CCL | 0% | 1 | 2.951 |
confidence_police_mean |
Confidence police mean | float | CCL | 0% | 1 | 2.541 |
confidence_courts_mean |
Confidence courts mean | float | CCL | 0% | 1 | 2.59 |
gender_jobs_scarce_men_priority_mean |
Gender jobs scarce men priority mean | float | CCL | 0% | 1 | 2.991 |
gender_men_better_political_leaders_mean |
Gender men better political leaders mean | float | CCL | 0% | 1 | 3.169 |
gender_university_more_important_for_boys_mean |
Gender university more important for boys mean | float | CCL | 0% | 1 | 2.968 |
immigration_policy_mean |
Immigration policy mean | float | CCL | 0% | 1 | 3.05 |
immigrants_take_jobs_mean |
Immigrants take jobs mean | float | CCL | 0% | 1 | 1.047 |
immigrants_increase_crime_mean |
Immigrants increase crime mean | float | CCL | 0% | 1 | 1.359 |
justifiable_homosexuality_mean |
Justifiable homosexuality mean | float | CCL | 0% | 1 | 4.947 |
justifiable_divorce_mean |
Justifiable divorce mean | float | CCL | 0% | 1 | 2.506 |
importance_democracy_mean |
Importance democracy mean | float | CCL | 0% | 1 | 8.179 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
wave |
wave | integer | 0% | 1 | 7 |
wave_years |
wave_years | string | 0% | 1 | 2017-2022 |
respondents |
respondents | integer | 0% | 1 | 1762 |
source |
source | string | 0% | 1 | World Values Survey Wave 7 |
importance_family_n |
importance_family_n | integer | 0% | 1 | 1762 |
importance_family_domain |
importance_family_domain | string | 0% | 1 | cultural_practice |
importance_friends_n |
importance_friends_n | integer | 0% | 1 | 1759 |
importance_friends_domain |
importance_friends_domain | string | 0% | 1 | cultural_practice |
importance_leisure_n |
importance_leisure_n | integer | 0% | 1 | 1730 |
importance_leisure_domain |
importance_leisure_domain | string | 0% | 1 | cultural_practice |
importance_politics_n |
importance_politics_n | integer | 0% | 1 | 1758 |
importance_politics_domain |
importance_politics_domain | string | 0% | 1 | cultural_practice |
importance_religion_n |
importance_religion_n | integer | 0% | 1 | 1755 |
importance_religion_domain |
importance_religion_domain | string | 0% | 1 | religion |
happiness_n |
happiness_n | integer | 0% | 1 | 1745 |
happiness_domain |
happiness_domain | string | 0% | 1 | cultural_practice |
freedom_of_choice_n |
freedom_of_choice_n | integer | 0% | 1 | 1718 |
freedom_of_choice_domain |
freedom_of_choice_domain | string | 0% | 1 | cultural_practice |
life_satisfaction_n |
life_satisfaction_n | integer | 0% | 1 | 1754 |
life_satisfaction_domain |
life_satisfaction_domain | string | 0% | 1 | cultural_practice |
trust_most_people_n |
trust_most_people_n | integer | 0% | 1 | 1730 |
trust_most_people_domain |
trust_most_people_domain | string | 0% | 1 | social_structure |
trust_family_n |
trust_family_n | integer | 0% | 1 | 1752 |
trust_family_domain |
trust_family_domain | string | 0% | 1 | social_structure |
trust_neighbors_n |
trust_neighbors_n | integer | 0% | 1 | 1723 |
trust_neighbors_domain |
trust_neighbors_domain | string | 0% | 1 | social_structure |
trust_people_know_personally_n |
trust_people_know_personally_n | integer | 0% | 1 | 1740 |
trust_people_know_personally_domain |
trust_people_know_personally_domain | string | 0% | 1 | social_structure |
trust_strangers_n |
trust_strangers_n | integer | 0% | 1 | 1729 |
trust_strangers_domain |
trust_strangers_domain | string | 0% | 1 | social_structure |
| +34 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
oc_anti_money_laundering |
oc_anti_money_laundering | numeric | 0% | 1 | - |
oc_arms_trafficking |
oc_arms_trafficking | numeric | 0% | 1 | - |
oc_cannabis_trade |
oc_cannabis_trade | numeric | 0% | 1 | - |
oc_cocaine_trade |
oc_cocaine_trade | numeric | 0% | 1 | - |
oc_criminal_actors |
oc_criminal_actors | numeric | 0% | 1 | - |
oc_criminal_markets |
oc_criminal_markets | numeric | 0% | 1 | - |
oc_criminal_networks |
oc_criminal_networks | numeric | 0% | 1 | - |
oc_criminality |
oc_criminality | numeric | 0% | 1 | - |
oc_cyber_dependent_crimes |
oc_cyber_dependent_crimes | numeric | 0% | 1 | - |
oc_economic_regulatory_capacity |
oc_economic_regulatory_capacity | numeric | 0% | 1 | - |
oc_extortion_and_protection_racketeering |
oc_extortion_and_protection_racketeering | numeric | 0% | 1 | - |
oc_fauna_crimes |
oc_fauna_crimes | numeric | 0% | 1 | - |
oc_financial_crimes |
oc_financial_crimes | numeric | 0% | 1 | - |
oc_flora_crimes |
oc_flora_crimes | numeric | 0% | 1 | - |
oc_foreign_actors |
oc_foreign_actors | numeric | 0% | 1 | - |
oc_government_transparency_and_accountability |
oc_government_transparency_and_accountability | numeric | 0% | 1 | - |
oc_heroin_trade |
oc_heroin_trade | numeric | 0% | 1 | - |
oc_human_smuggling |
oc_human_smuggling | numeric | 0% | 1 | - |
oc_human_trafficking |
oc_human_trafficking | numeric | 0% | 1 | - |
oc_illicit_trade_in_excisable_goods |
oc_illicit_trade_in_excisable_goods | numeric | 0% | 1 | - |
oc_international_cooperation |
oc_international_cooperation | numeric | 0% | 1 | - |
oc_judicial_system_and_detention |
oc_judicial_system_and_detention | numeric | 0% | 1 | - |
oc_law_enforcement |
oc_law_enforcement | numeric | 0% | 1 | - |
oc_mafia_style_groups |
oc_mafia_style_groups | numeric | 0% | 1 | - |
oc_national_policies_and_laws |
oc_national_policies_and_laws | numeric | 0% | 1 | - |
oc_non_renewable_resource_crimes |
oc_non_renewable_resource_crimes | numeric | 0% | 1 | - |
oc_non_state_actors |
oc_non_state_actors | numeric | 0% | 1 | - |
oc_political_leadership_and_governance |
oc_political_leadership_and_governance | numeric | 0% | 1 | - |
oc_prevention |
oc_prevention | numeric | 0% | 1 | - |
oc_private_sector_actors |
oc_private_sector_actors | numeric | 0% | 1 | - |
| +5 more extension fields — download the CSV/Parquet to see them all. | |||||
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.
| Language | Place names | Share | Script |
|---|---|---|---|
| Portuguese (por) | 211,639 | 99.8% | — |
| Spanish (spa) | 203 | 0.1% | — |
228,920 distinct features ·
4 languages ·
0 scripts ·
8 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 |
|---|---|---|
| IBGE SIDRA | official_nso | api |
| Global Data Lab | academic | api |
| GI-TOC / ENACT (Global Initiative Against Transnational Organized Crime · ENACT) | academic | bulk_download |
| World Values Survey | academic | metadata_catalog |
| commercial | bulk_download | |
| World Bank Open Data | international_organization | api |
| Ethnic Power Relations Dataset | academic | bulk_download |
| D-PLACE (Database of Places, Language, Culture & Environment) | academic | bulk_download |
| NGA GEOnet Names Server (GNS) | official_government | bulk_download |
| UNHCR Refugee Data Finder (UN High Commissioner for Refugees) | international_organization | api |
| Glottolog Language Catalog | academic | bulk_download |
| LandScan Global (ORNL — Oak Ridge National Laboratory) | research_institution | earth_engine |
| GHS Urban Centre Database (Global Human Settlement · EU Joint Research Centre) | international_organization | bulk_download |
| 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.