| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 1 | PY |
region_name |
Region name | string | SEL | 0% | 1 | Paraguay |
F_TL |
Female population | integer | SEL | 0% | 1 | 3751918 |
M_TL |
Male population | integer | SEL | 0% | 1 | 3798623 |
T_TL |
Total population | integer | SEL | 0% | 1 | 7552654 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_0 |
year |
Reference year | integer | 0% | 1 | 2023 |
year |
year | integer | 0% | 1 | 2023 |
F_00_04 |
Female population age 0-4 | integer | 0% | 1 | 346850 |
F_05_09 |
Female population age 5-9 | integer | 0% | 1 | 344854 |
F_10_14 |
Female population age 10-14 | integer | 0% | 1 | 342156 |
F_15_19 |
Female population age 15-19 | integer | 0% | 1 | 334830 |
F_20_24 |
Female population age 20-24 | integer | 0% | 1 | 324811 |
F_25_29 |
Female population age 25-29 | integer | 0% | 1 | 314641 |
F_30_34 |
Female population age 30-34 | integer | 0% | 1 | 299821 |
F_35_39 |
Female population age 35-39 | integer | 0% | 1 | 275637 |
F_40_44 |
Female population age 40-44 | integer | 0% | 1 | 235326 |
F_45_49 |
Female population age 45-49 | integer | 0% | 1 | 195970 |
F_50_54 |
Female population age 50-54 | integer | 0% | 1 | 173235 |
F_55_59 |
Female population age 55-59 | integer | 0% | 1 | 149852 |
F_60_64 |
Female population age 60-64 | integer | 0% | 1 | 125570 |
F_65_69 |
Female population age 65-69 | integer | 0% | 1 | 101409 |
F_70_74 |
Female population age 70-74 | integer | 0% | 1 | 74134 |
F_75_79 |
Female population age 75-79 | integer | 0% | 1 | 49469 |
F_80Plus |
F_80Plus | integer | 0% | 1 | 63353 |
M_00_04 |
Male population age 0-4 | integer | 0% | 1 | 361411 |
M_05_09 |
Male population age 5-9 | integer | 0% | 1 | 358523 |
M_10_14 |
Male population age 10-14 | integer | 0% | 1 | 354907 |
M_15_19 |
Male population age 15-19 | integer | 0% | 1 | 346732 |
M_20_24 |
Male population age 20-24 | integer | 0% | 1 | 335520 |
M_25_29 |
Male population age 25-29 | integer | 0% | 1 | 323831 |
M_30_34 |
Male population age 30-34 | integer | 0% | 1 | 306932 |
M_35_39 |
Male population age 35-39 | integer | 0% | 1 | 280266 |
M_40_44 |
Male population age 40-44 | integer | 0% | 1 | 234559 |
M_45_49 |
Male population age 45-49 | integer | 0% | 1 | 192577 |
| +24 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 18 | PY17, PY10, PY13, PY00, PY16 |
region_name |
Region name | string | SEL | 0% | 18 | Alto Paraguay, Alto Paraná, Amambay, Asunción, Boquerón |
F_TL |
Female population | integer | SEL | 0% | 18 | 9021, 427292, 90007, 274224, 34242 |
M_TL |
Male population | integer | SEL | 0% | 18 | 10210, 437264, 89682, 246849, 36213 |
T_TL |
Total population | integer | SEL | 0% | 18 | 19263, 864721, 179729, 521082, 70478 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
year |
Reference year | integer | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
year |
year | integer | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
F_00_04 |
Female population age 0-4 | integer | 0% | 18 | 1021, 40720, 8784, 17967, 3604 |
F_05_09 |
Female population age 5-9 | integer | 0% | 18 | 955, 40450, 8695, 19300, 3462 |
F_10_14 |
Female population age 10-14 | integer | 0% | 18 | 919, 40375, 8605, 21352, 3281 |
F_15_19 |
Female population age 15-19 | integer | 0% | 18 | 909, 39828, 8389, 22552, 3047 |
F_20_24 |
Female population age 20-24 | integer | 0% | 18 | 907, 38690, 8001, 21627, 2789 |
F_25_29 |
Female population age 25-29 | integer | 0% | 18 | 816, 35461, 7571, 18130, 2664 |
F_30_34 |
Female population age 30-34 | integer | 0% | 18 | 654, 33515, 7151, 17370, 2556 |
F_35_39 |
Female population age 35-39 | integer | 0% | 18 | 546, 32378, 6548, 19057, 2395 |
F_40_44 |
Female population age 40-44 | integer | 0% | 18 | 448, 28611, 5450, 22177, 2167 |
F_45_49 |
Female population age 45-49 | integer | 0% | 18 | 384, 24239, 4420, 20178, 1927 |
F_50_54 |
Female population age 50-54 | integer | 0% | 18 | 347, 20947, 3892, 15015, 1671 |
F_55_59 |
Female population age 55-59 | integer | 0% | 18 | 304, 16739, 3367, 12763, 1338 |
F_60_64 |
Female population age 60-64 | integer | 0% | 18 | 263, 12789, 2845, 12264, 1071 |
F_65_69 |
Female population age 65-69 | integer | 0% | 18 | 208, 9458, 2288, 10872, 819 |
F_70_74 |
Female population age 70-74 | integer | 0% | 18 | 141, 6232, 1600, 8678, 580 |
F_75_79 |
Female population age 75-79 | integer | 0% | 18 | 93, 3599, 1051, 6269, 400 |
F_80Plus |
F_80Plus | integer | 0% | 18 | 106, 3261, 1350, 8653, 471 |
M_00_04 |
Male population age 0-4 | integer | 0% | 18 | 1054, 42409, 9148, 18732, 3743 |
M_05_09 |
Male population age 5-9 | integer | 0% | 18 | 986, 42117, 9018, 20038, 3589 |
M_10_14 |
Male population age 10-14 | integer | 0% | 18 | 973, 42182, 8872, 21925, 3396 |
M_15_19 |
Male population age 15-19 | integer | 0% | 18 | 921, 42319, 8563, 22812, 3156 |
M_20_24 |
Male population age 20-24 | integer | 0% | 18 | 897, 41313, 7970, 21555, 2933 |
M_25_29 |
Male population age 25-29 | integer | 0% | 18 | 935, 37727, 7547, 18433, 2829 |
M_30_34 |
Male population age 30-34 | integer | 0% | 18 | 807, 34401, 7154, 17254, 2776 |
M_35_39 |
Male population age 35-39 | integer | 0% | 18 | 685, 30964, 6470, 17273, 2711 |
M_40_44 |
Male population age 40-44 | integer | 0% | 18 | 534, 25939, 5345, 18029, 2415 |
M_45_49 |
Male population age 45-49 | integer | 0% | 18 | 423, 22161, 4429, 15966, 2030 |
| +24 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 100 | PY1704, PY1705, PY1701, PY1702, PY1001 |
region_name |
Region name | string | SEL | 0% | 100 | Bahia Negra, Carmelo Peralta, Fuerte Olimpo, Puerto... |
F_TL |
Female population | integer | SEL | 0% | 100 | 1092, 2291, 2234, 3404, 153957 |
M_TL |
Male population | integer | SEL | 0% | 100 | 1431, 2412, 2507, 3860, 157241 |
T_TL |
Total population | integer | SEL | 0% | 100 | 2528, 4713, 4752, 7270, 311206 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_2, admin_2, admin_2, admin_2, admin_2 |
year |
Reference year | integer | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
year |
year | integer | 0% | 1 | 2023, 2023, 2023, 2023, 2023 |
F_00_04 |
Female population age 0-4 | integer | 0% | 97 | 124, 259, 253, 385, 14670 |
F_05_09 |
Female population age 5-9 | integer | 0% | 93 | 116, 242, 237, 360, 14572 |
F_10_14 |
Female population age 10-14 | integer | 0% | 96 | 111, 233, 228, 347, 14545 |
F_15_19 |
Female population age 15-19 | integer | 0% | 95 | 110, 231, 225, 343, 14348 |
F_20_24 |
Female population age 20-24 | integer | 0% | 98 | 110, 230, 225, 342, 13938 |
F_25_29 |
Female population age 25-29 | integer | 0% | 97 | 99, 207, 202, 308, 12776 |
F_30_34 |
Female population age 30-34 | integer | 0% | 95 | 79, 166, 162, 247, 12075 |
F_35_39 |
Female population age 35-39 | integer | 0% | 96 | 66, 139, 135, 206, 11666 |
F_40_44 |
Female population age 40-44 | integer | 0% | 96 | 54, 114, 111, 169, 10308 |
F_45_49 |
Female population age 45-49 | integer | 0% | 94 | 46, 98, 95, 145, 8733 |
F_50_54 |
Female population age 50-54 | integer | 0% | 95 | 42, 88, 86, 131, 7549 |
F_55_59 |
Female population age 55-59 | integer | 0% | 95 | 37, 77, 75, 115, 6032 |
F_60_64 |
Female population age 60-64 | integer | 0% | 91 | 32, 67, 65, 99, 4609 |
F_65_69 |
Female population age 65-69 | integer | 0% | 91 | 25, 53, 51, 79, 3410 |
F_70_74 |
Female population age 70-74 | integer | 0% | 88 | 17, 36, 35, 53, 2248 |
F_75_79 |
Female population age 75-79 | integer | 0% | 85 | 11, 24, 23, 35, 1300 |
F_80Plus |
F_80Plus | integer | 0% | 87 | 13, 27, 26, 40, 1178 |
M_00_04 |
Male population age 0-4 | integer | 0% | 100 | 148, 249, 259, 398, 15248 |
M_05_09 |
Male population age 5-9 | integer | 0% | 98 | 138, 233, 242, 373, 15144 |
M_10_14 |
Male population age 10-14 | integer | 0% | 98 | 136, 230, 239, 368, 15166 |
M_15_19 |
Male population age 15-19 | integer | 0% | 98 | 129, 218, 226, 348, 15216 |
M_20_24 |
Male population age 20-24 | integer | 0% | 98 | 126, 212, 220, 339, 14854 |
M_25_29 |
Male population age 25-29 | integer | 0% | 96 | 131, 221, 230, 353, 13565 |
M_30_34 |
Male population age 30-34 | integer | 0% | 99 | 113, 191, 198, 305, 12370 |
M_35_39 |
Male population age 35-39 | integer | 0% | 98 | 96, 162, 168, 259, 11134 |
M_40_44 |
Male population age 40-44 | integer | 0% | 99 | 75, 126, 131, 202, 9327 |
M_45_49 |
Male population age 45-49 | integer | 0% | 97 | 59, 100, 104, 160, 7969 |
| +24 more pending fields — download the CSV/Parquet to see them all. | |||||
ⓘ Global Data Lab publishes its own subnational regions, which match national admin units in some countries and group several together in others. The level shown is the nearest administrative tier, not a claim that these are that tier.
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY, PRY, PRY, PRY, PRY |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 6 | Total, Central (Asuncion, Central), North-East... |
human_development_index |
Human development index | float | SEL | 0% | 80 | 0.635, 0.684, 0.609, 0.592, 0.607 |
health_index |
Health index | float | SEL | 0% | 67 | 0.728, 0.744, 0.716, 0.714, 0.735 |
education_index |
Education index | float | SEL | 0% | 87 | 0.509, 0.565, 0.477, 0.463, 0.467 |
income_index |
Income index | float | SEL | 0% | 66 | 0.69, 0.762, 0.661, 0.628, 0.652 |
life_expectancy |
Life expectancy | float | SEL | 0% | 95 | 67.34, 68.34, 66.56, 66.43, 67.77 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 97 | 7.63, 9.563, 6.54, 6.158, 6.45 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 17 | 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 | PY, PY, PY, PY, PY |
population_count |
Population count | float | SEL | 2% | 65 | 1883514.0, 1927394.0, 1973130.0, 2021909.0, 2073119.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 60.197, 60.517, 60.816, 61.101, 61.368 |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 2% | 65 | 153.375216758109, 167.092827495951, 182.805194132375,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 77% | 15 | 78.4599990844727, 90.2699966430664, 94.5599975585938,... |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 81.8, 81.1, 80.6, 80.2, 79.9 |
poverty_headcount_pct |
Poverty headcount percent | float | SEL | 62% | 25 | 36.1, 37.3, 36.8, 57.7, 51.4 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Paraguay, Paraguay, Paraguay, Paraguay, Paraguay |
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 | PY, PY, PY, PY, PY |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 60.197, 60.517, 60.816, 61.101, 61.368 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 14% | 57 | 31.1, 31.0, 30.9, 30.6, 30.4 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 81.8, 81.1, 80.6, 80.2, 79.9 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 32 | 237.0, 230.0, 225.0, 220.0, 209.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 64 | 6.5, 6.489, 6.472, 6.447, 6.421 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 64 | 42.421, 42.312, 42.187, 42.068, 41.691 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 64 | 10.561, 10.385, 10.218, 10.048, 10.009 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 68% | 21 | 0.534, 0.533, 0.435, 0.439, 0.563 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 53% | 23 | 2.38925075531006, 1.62940001487732, 1.68299996852875,... |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 32% | 31 | 17.0, 28.0, 34.0, 45.0, 67.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 6.01865244, 5.60815811, 4.75770569, 4.90703917, 4.93224335 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Paraguay, Paraguay, Paraguay, Paraguay, Paraguay |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
glottocode |
Glottocode | string | CCL | 0% | 33 | ache1246, anga1316, ayor1240, cham1315, chir1286 |
name |
Name | string | CCL | 0% | 33 | Aché, Angaité, Ayoreo, Chamacoco, Chiripá |
iso639_3 |
Iso639 3 | string | CCL | 9% | 30 | guq, aqt, ayo, ceg, nhd |
level |
Level | string | CCL | 0% | 1 | language, language, language, language, language |
family_name |
Family name | string | CCL | 100% | - | - |
family_glottocode |
Family glottocode | string | CCL | 3% | 9 | tupi1275, leng1261, zamu1243, zamu1243, tupi1275 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 3% | 18 | tupi1277, east2852, zamu1244, zamu1243, para1319 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 10 | ['PY'], ['PY'], ['BO', 'PY'], ['BO', 'BR', 'PY'], ['AR',... |
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% | 6 | 0, 0, 1, 2, 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 0% | 33 | -25.5865, -22.85, -19.220055, -20.5899, -25.6521 |
longitude |
longitude | float | 0% | 33 | -56.4697, -58.45, -60.217495, -58.2005, -55.051 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | Paraguay |
admin_code |
Admin code | string | SEL | 0% | 1 | 89047665B96161090665764 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 399671.1594 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 7525166 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 18.83 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY, PRY, PRY, PRY, PRY |
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% | 18 | CENTRAL, ALTO PARANA, ITAPUA, CAAGUAZU, ASUNCION |
admin_code |
Admin code | string | SEL | 0% | 18 | 63826900B88193761383216, 63826900B70318852287741,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 18 | 2412.3987, 14207.458, 15866.9866, 12904.7522, 128.6966 |
pop_2024 |
Population count | integer | SEL | 0% | 18 | 2303676, 861463, 639763, 581638, 529201 |
pop_density_2024 |
Population density | float | SEL | 0% | 17 | 954.93, 60.63, 40.32, 45.07, 4112.0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY, PRY, PRY, PRY, PRY |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality, locality, locality, locality |
admin_name |
Admin name | string | SEL | 0% | 9 | Asuncion, Ciudad del Este, Encarnacion, Coronel Oviedo,... |
admin_code |
Admin code | integer | SEL | 0% | 9 | 217, 1050, 930, 527, 379 |
area_sqkm |
Area sqkm | float | SEL | 0% | 8 | 381.3695, 105.5521, 45.8195, 22.9029, 24.8821 |
pop_2024 |
Population count | integer | SEL | 0% | 9 | 1907550, 385353, 130224, 85007, 79747 |
pop_density_2024 |
Population density | float | SEL | 0% | 9 | 5001.84, 3650.83, 2842.11, 3711.63, 3204.99 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 9 | 1175482, 422701, 177551, 109880, 127053 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 9 | 1.623, 0.912, 0.733, 0.774, 0.628 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PY, PY, PY, PY, PY |
admin_level |
Admin level | integer | SEL | 0% | 1 | 1, 1, 1, 1, 1 |
iso3 |
Country code | string | SEL | 0% | 1 | PRY, PRY, PRY, PRY, PRY |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
retail |
retail | float | 0% | 17 | -17.36, -10.84, -19.76, -6.36, -6.07 |
grocery |
grocery | float | 0% | 17 | -4.36, 4.93, 8.33, 5.22, 11.82 |
parks |
parks | float | 0% | 16 | -15.52, 0.0, -25.65, -4.47, 2.3 |
transit |
transit | float | 0% | 15 | -39.37, -17.38, -29.94, 0.0, -38.24 |
workplaces |
workplaces | float | 0% | 17 | -9.44, -1.6, -2.76, -1.97, 5.25 |
residential |
residential | float | 0% | 15 | 7.83, 10.27, 7.0, 0.0, 17.07 |
region |
region | string | 0% | 17 | Alto Paraná Department, Amambay Department, Asunción,... |
observation_count |
observation_count | integer | 0% | 8 | 974, 971, 974, 948, 971 |
| 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 | 3.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 127.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .py |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 78.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric |
Broadband subscriptions per 100 | float | SEL | 0% | 1 | 13.0 |
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
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 | 206,000 (2023 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 206000.0 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 3 (2023 est.) |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 8.67 million (2023 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 8.67 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 127 (2023 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | 6 privately owned TV stations; about 75 commercial and... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 6.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 78% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 878,000 (2023 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 878000.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 13 (2023 est.) |
source_section |
source_section | string | 0% | 1 | Communications |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.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 | 16300.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 44.458 |
population_below_poverty_line_numeric |
Poverty headcount percent | float | SEL | 0% | 1 | 24.7 |
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
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 South American economy; COVID-19 hit... |
economic_overview_numeric |
economic_overview_numeric | float | 0% | 1 | -19.0 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $112.919 billion (2024 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_numeric |
Real gdp purchasing power parity 2024 (numeric) | float | 0% | 1 | 112.919 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $108.316 billion (2023 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_numeric |
Real gdp purchasing power parity 2023 (numeric) | float | 0% | 1 | 108.316 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $103.159 billion (2022 est.) |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_numeric |
Real gdp purchasing power parity 2022 (numeric) | float | 0% | 1 | 103.159 |
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 | 4.2% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | 4.2 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 5% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 5.0 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 0.2% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 0.2 |
real_gdp_growth_rate_note |
real_gdp_growth_rate_note | string | 0% | 1 | note: annual GDP % growth based on constant local currency |
real_gdp_per_capita_real_gdp_per_capita_2024_text |
Real gdp per capita 2024 (text) | string | 0% | 1 | $16,300 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $15,800 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 15800.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $15,300 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 15300.0 |
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 | $44.458 billion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 3.8% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 3.8 |
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 | 9.8% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 9.8 |
inflation_rate_consumer_prices_note |
inflation_rate_consumer_prices_note | string | 0% | 1 | note: annual % change based on consumer prices |
| +122 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 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
electricity_access_electrification_total_population_text |
electricity_access_electrification_total_population_text | string | 0% | 1 | 100% (2022 est.) |
electricity_installed_generating_capacity_text |
electricity_installed_generating_capacity_text | string | 0% | 1 | 8.928 million kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 8.928 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 14.835 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 14.835 |
electricity_exports_text |
electricity_exports_text | string | 0% | 1 | 24.202 billion kWh (2023 est.) |
electricity_exports_numeric |
electricity_exports_numeric | float | 0% | 1 | 24.202 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 5.209 billion kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 5.209 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 99.4% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 99.4 |
electricity_generation_sources_biomass_and_waste_text |
electricity_generation_sources_biomass_and_waste_text | string | 0% | 1 | 0.5% of total installed capacity (2023 est.) |
electricity_generation_sources_biomass_and_waste_numeric |
electricity_generation_sources_biomass_and_waste_numeric | float | 0% | 1 | 0.5 |
coal_consumption_text |
coal_consumption_text | string | 0% | 1 | 700 metric tons (2023 est.) |
coal_consumption_numeric |
coal_consumption_numeric | float | 0% | 1 | 700.0 |
coal_exports_text |
coal_exports_text | string | 0% | 1 | 10 metric tons (2023 est.) |
coal_exports_numeric |
coal_exports_numeric | float | 0% | 1 | 10.0 |
coal_imports_text |
coal_imports_text | string | 0% | 1 | 100 metric tons (2023 est.) |
coal_imports_numeric |
coal_imports_numeric | float | 0% | 1 | 100.0 |
petroleum_total_petroleum_production_text |
petroleum_total_petroleum_production_text | string | 0% | 1 | 2,000 bbl/day (2023 est.) |
petroleum_total_petroleum_production_numeric |
petroleum_total_petroleum_production_numeric | float | 0% | 1 | 2000.0 |
petroleum_refined_petroleum_consumption_text |
petroleum_refined_petroleum_consumption_text | string | 0% | 1 | 52,000 bbl/day (2023 est.) |
petroleum_refined_petroleum_consumption_numeric |
petroleum_refined_petroleum_consumption_numeric | float | 0% | 1 | 52000.0 |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_text |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_text | string | 0% | 1 | 25.733 million Btu/person (2023 est.) |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_numeric |
energy_consumption_per_capita_total_energy_consumption_per_capita_2023_numeric | float | 0% | 1 | 25.733 |
source_section |
source_section | string | 0% | 1 | Energy |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 54.1 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 36.9 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 63.1 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 1.64 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 1.819 |
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
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; water pollution; toxic dumping in rivers... |
international_environmental_agreements_party_to_text |
international_environmental_agreements_party_to_text | string | 0% | 1 | Biodiversity, Climate Change, Climate Change-Kyoto... |
international_environmental_agreements_signed_but_not_ratified_text |
international_environmental_agreements_signed_but_not_ratified_text | string | 0% | 1 | Nuclear Test Ban, Tropical Timber 2006 |
international_environmental_agreements_signed_but_not_ratified_numeric |
international_environmental_agreements_signed_but_not_ratified_numeric | float | 0% | 1 | 2006.0 |
climate_text |
climate_text | string | 0% | 1 | subtropical to temperate; substantial rainfall in the... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 54.1% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 11.5% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 11.5 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.2% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.2 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 42.4% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 42.4 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 36.9% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 7% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 7.0 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 63.1% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 1.64% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 7.509 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 7.509 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 2,000 metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_numeric |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_numeric | float | 0% | 1 | 2000.0 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 7.507 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 | 7.507 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 12.5 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 12.5 |
methane_emissions_energy_text |
methane_emissions_energy_text | string | 0% | 1 | 37.3 kt (2022-2024 est.) |
methane_emissions_energy_numeric |
methane_emissions_energy_numeric | float | 0% | 1 | 37.3 |
methane_emissions_agriculture_text |
methane_emissions_agriculture_text | string | 0% | 1 | 813 kt (2019-2021 est.) |
methane_emissions_agriculture_numeric |
methane_emissions_agriculture_numeric | float | 0% | 1 | 813.0 |
methane_emissions_waste_text |
methane_emissions_waste_text | string | 0% | 1 | 101.2 kt (2019-2021 est.) |
| +16 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 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
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 | Paraguayan(s) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Paraguayan |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | Mestizo (mixed Spanish and Indigenous ancestry) 95%, other 5% |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 95.0 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 406752.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 397302.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 9450.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 4655.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 0.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 842.0 |
elevation_lowest_point_numeric |
Elevation min m | float | SEL | 0% | 1 | 46.0 |
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 54.1 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 36.9 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 1362.0 |
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
location_text |
location_text | string | 0% | 1 | Central South America, northeast of Argentina, southwest... |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 23 00 S, 58 00 W |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 23.0 |
map_references_text |
map_references_text | string | 0% | 1 | South America |
area_total_text |
area_total_text | string | 0% | 1 | 406,752 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 397,302 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 9,450 sq km |
area_comparative_text |
area_comparative_text | string | 0% | 1 | about three times the size of New York State; slightly... |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 4,655 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | Argentina 2,531 km; Bolivia 753 km; Brazil 1,371 km |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 2531.0 |
coastline_text |
coastline_text | string | 0% | 1 | 0 km (landlocked) |
maritime_claims_text |
maritime_claims_text | string | 0% | 1 | none (landlocked) |
climate_text |
climate_text | string | 0% | 1 | subtropical to temperate; substantial rainfall in the... |
terrain_text |
terrain_text | string | 0% | 1 | grassy plains and wooded hills east of Rio Paraguay;... |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Cerro Pero 842 m |
elevation_lowest_point_text |
elevation_lowest_point_text | string | 0% | 1 | junction of Río Paraguay and Río Paraná 46 m |
elevation_mean_elevation_text |
elevation_mean_elevation_text | string | 0% | 1 | 178 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 178.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | hydropower, timber, iron ore, manganese, limestone |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 54.1% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 11.5% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 11.5 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.2% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.2 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 42.4% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 42.4 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 36.9% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 7% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 7.0 |
| +12 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 | PRY |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name_conventional_long_form_text |
country_name_conventional_long_form_text | string | 0% | 1 | Republic of Paraguay |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Paraguay |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | República del Paraguay |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Paraguay |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | derives from the river of the same name; the river's... |
government_type_text |
government_type_text | string | 0% | 1 | presidential republic |
capital_name_text |
capital_name_text | string | 0% | 1 | Asunción |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 25 16 S, 57 40 W |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 25.0 |
capital_time_difference_text |
capital_time_difference_text | string | 0% | 1 | UTC-3 (2 hour ahead of Washington, DC, during Standard Time) |
capital_time_difference_numeric |
capital_time_difference_numeric | float | 0% | 1 | -3.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | the name means "assumption" in Spanish; the Spanish... |
capital_etymology_numeric |
capital_etymology_numeric | float | 0% | 1 | 15.0 |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 17 departments (departamentos, singular - departamento)... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 17.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | civil law system with influences from Argentine,... |
constitution_history_text |
constitution_history_text | string | 0% | 1 | several previous; latest approved and promulgated 20 June 1992 |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 20.0 |
constitution_amendment_process_text |
constitution_amendment_process_text | string | 0% | 1 | proposed at the initiative of at least one quarter of... |
constitution_amendment_process_numeric |
constitution_amendment_process_numeric | float | 0% | 1 | 30000.0 |
international_law_organization_participation_text |
international_law_organization_participation_text | string | 0% | 1 | accepts compulsory ICJ jurisdiction; accepts ICCt jurisdiction |
citizenship_citizenship_by_birth_text |
Citizenship by birth (text) | string | 0% | 1 | yes |
citizenship_citizenship_by_descent_only_text |
Citizenship by descent only (text) | string | 0% | 1 | at least one parent must be a native-born citizen of Paraguay |
citizenship_dual_citizenship_recognized_text |
citizenship_dual_citizenship_recognized_text | string | 0% | 1 | yes |
citizenship_residency_requirement_for_naturalization_text |
citizenship_residency_requirement_for_naturalization_text | string | 0% | 1 | 3 years |
citizenship_residency_requirement_for_naturalization_numeric |
citizenship_residency_requirement_for_naturalization_numeric | float | 0% | 1 | 3.0 |
suffrage_text |
suffrage_text | string | 0% | 1 | 18 years of age; universal and compulsory until the age of 75 |
suffrage_numeric |
suffrage_numeric | float | 0% | 1 | 18.0 |
executive_branch_chief_of_state_text |
executive_branch_chief_of_state_text | string | 0% | 1 | President Santiago PEÑA Palacios (since 15 August 2023) |
executive_branch_chief_of_state_numeric |
executive_branch_chief_of_state_numeric | float | 0% | 1 | 15.0 |
| +90 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 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | Several Indigenous groups, principally belonging to the... |
background_numeric |
background_numeric | float | 0% | 1 | 16.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_languages_text |
Languages (text) | string | 0% | 1 | Spanish (official) and Guarani (official) 46.3%, only... |
languages_languages_numeric |
Languages (numeric) | float | 0% | 1 | 46.3 |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | La Libreta Informativa del Mundo, la fuente... |
languages_note |
languages_note | string | 0% | 1 | note: data represent predominant household language |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
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 | 7,649 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 7649.0 |
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 141 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 141.0 |
refugees_and_internally_displaced_persons_stateless_persons_text |
refugees_and_internally_displaced_persons_stateless_persons_text | string | 0% | 1 | 5 (2024 est.) |
refugees_and_internally_displaced_persons_stateless_persons_numeric |
refugees_and_internally_displaced_persons_stateless_persons_numeric | float | 0% | 1 | 5.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
military_and_security_forces_text |
military_and_security_forces_text | string | 0% | 1 | Armed Forces of Paraguay (Fuerzas Armadas de Paraguay;... |
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 | 0.8% of GDP (2024 est.) |
military_expenditures_military_expenditures_2024_numeric |
Military expenditures 2024 (numeric) | float | 0% | 1 | 0.8 |
military_expenditures_military_expenditures_2023_text |
Military expenditures 2023 (text) | string | 0% | 1 | 0.8% of GDP (2023 est.) |
military_expenditures_military_expenditures_2023_numeric |
Military expenditures 2023 (numeric) | float | 0% | 1 | 0.8 |
military_expenditures_military_expenditures_2022_text |
Military expenditures 2022 (text) | string | 0% | 1 | 0.8% of GDP (2022 est.) |
military_expenditures_military_expenditures_2022_numeric |
Military expenditures 2022 (numeric) | float | 0% | 1 | 0.8 |
military_expenditures_military_expenditures_2021_text |
Military expenditures 2021 (text) | string | 0% | 1 | 1% of GDP (2021 est.) |
military_expenditures_military_expenditures_2021_numeric |
Military expenditures 2021 (numeric) | float | 0% | 1 | 1.0 |
military_expenditures_military_expenditures_2020_text |
Military expenditures 2020 (text) | string | 0% | 1 | 1% of GDP (2020 est.) |
military_expenditures_military_expenditures_2020_numeric |
Military expenditures 2020 (numeric) | float | 0% | 1 | 1.0 |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | approximately 15,000 active duty Armed Forces (2025) |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 15000.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the military's inventory is comprised of mostly older or... |
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 | 18-25 years of age for voluntary service for men and... |
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 Paraguayan military is responsible for external... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 1930.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 7604044.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 3809407.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 3794637.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 22.2 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 68.4 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 9.4 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 46.7 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 32.4 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 14.3 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 32.3 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | 1.06 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 15.66 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 4.97 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | -0.07 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 63.1 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 1.64 |
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 | 1.0 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 58.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 21.4 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 78.8 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 1.88 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 0.92 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 3.89 |
hospital_bed_density_numeric |
Hospital beds per 1000 | float | SEL | 0% | 1 | 1.0 |
literacy_total_population_numeric |
Literacy rate percent | float | SEL | 0% | 1 | 94.9 |
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
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 | 7,604,044 (2025 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 3,809,407 |
population_female_text |
population_female_text | string | 0% | 1 | 3,794,637 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 22.2% (male 850,191/female 821,237) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 68.4% (male 2,582,021/female 2,561,962) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 9.4% (2024 est.) (male 337,164/female 369,974) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 46.7 (2025 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 32.4 (2025 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 14.3 (2025 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 7 (2025 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 7.0 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 32.3 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 31.6 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 31.6 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 32 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 32.0 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | 1.06% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 15.66 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 4.97 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | -0.07 migrant(s)/1,000 population (2025 est.) |
population_distribution_text |
population_distribution_text | string | 0% | 1 | most of the population resides in the eastern half of... |
population_distribution_numeric |
population_distribution_numeric | float | 0% | 1 | 60.0 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 63.1% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 1.64% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 3.511 million ASUNCION (capital) (2023) |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 3.511 |
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 | 1.01 male(s)/female |
| +86 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_religion_other_pct_synth |
other | numeric | CCL | 0% | - | 0.6 |
composition_ethnicity_primary_label_synth |
Mestizo (mixed Spanish and Indigenous ancestry) | string | CCL | 0% | - | Mestizo (mixed Spanish and Indigenous ancestry) |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Roman Catholic 80.4%, Protestant 7% (Evangelical... |
religions_numeric |
religions_numeric | float | 0% | 1 | 80.4 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_roman_catholic_pct_synth |
Roman Catholic | numeric | 0% | - | 80.4 |
composition_religion_protestant_pct_synth |
Protestant | numeric | 0% | - | 7.0 |
composition_religion_protestant__evangelical_non_specific_pct_synth |
Evangelical (non-specific) | numeric | 0% | - | 6.7 |
composition_religion_protestant__evangelical_pentecostal_pct_synth |
Evangelical Pentecostal | numeric | 0% | - | 0.05 |
composition_religion_protestant__adventist_pct_synth |
Adventist | numeric | 0% | - | 0.05 |
composition_religion_protestant__protestant_non_specific_pct_synth |
Protestant (non-specific) | numeric | 0% | - | 0.05 |
composition_religion_believer_not_belonging_to_the_church_pct_synth |
Believer (not belonging to the church) | numeric | 0% | - | 5.7 |
composition_religion_agnostic_pct_synth |
agnostic | numeric | 0% | - | 0.05 |
composition_religion_none_pct_synth |
none | numeric | 0% | - | 0.2 |
composition_religion_unspecified_pct_synth |
unspecified | numeric | 0% | - | 6.2 |
composition_ethnicity_mestizo_mixed_spanish_and_indigenous_ancestry_pct_synth |
Mestizo (mixed Spanish and Indigenous ancestry) | numeric | 0% | - | 95.0 |
composition_ethnicity_other_pct_synth |
other | numeric | 0% | - | 5.0 |
composition_ethnicity_primary_share_pct_synth |
Mestizo (mixed Spanish and Indigenous ancestry) | numeric | 0% | - | 95.0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
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 | Space Agency of Paraguay (Agencia Especial del Paraguay,... |
space_agency_agencies_numeric |
space_agency_agencies_numeric | float | 0% | 1 | 2014.0 |
space_program_overview_text |
space_program_overview_text | string | 0% | 1 | has a small, recently established space program focused... |
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 | 2017 - organized country’s first international... |
key_space_program_milestones_numeric |
key_space_program_milestones_numeric | float | 0% | 1 | 2017.0 |
source_section |
source_section | string | 0% | 1 | Space |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
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 |
source_section |
source_section | string | 0% | 1 | Terrorism |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.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 | ZP |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 83.0 |
country_code |
Country code | string | SEL | 0% | 1 | PRY |
country_name |
Country name | string | SEL | 0% | 1 | Paraguay |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
airports_text |
airports_text | string | 0% | 1 | 83 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 29 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 29.0 |
railways_total_text |
railways_total_text | string | 0% | 1 | 30 km (2014) |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 30.0 |
railways_standard_gauge_text |
railways_standard_gauge_text | string | 0% | 1 | 30 km (2014) 1.435-m gauge |
railways_standard_gauge_numeric |
railways_standard_gauge_numeric | float | 0% | 1 | 30.0 |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 108 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 108.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | container ship 2, general cargo 22, oil tanker 5, other 79 |
merchant_marine_by_type_numeric |
merchant_marine_by_type_numeric | float | 0% | 1 | 2.0 |
ports_total_ports_text |
ports_total_ports_text | string | 0% | 1 | 1 (2024) |
ports_total_ports_numeric |
ports_total_ports_numeric | float | 0% | 1 | 1.0 |
ports_large_text |
ports_large_text | float | 0% | 1 | 0 |
ports_large_numeric |
ports_large_numeric | float | 0% | 1 | 0.0 |
ports_medium_text |
ports_medium_text | float | 0% | 1 | 0 |
ports_medium_numeric |
ports_medium_numeric | float | 0% | 1 | 0.0 |
ports_small_text |
ports_small_text | float | 0% | 1 | 0 |
ports_small_numeric |
ports_small_numeric | float | 0% | 1 | 0.0 |
ports_very_small_text |
ports_very_small_text | float | 0% | 1 | 1 |
ports_very_small_numeric |
ports_very_small_numeric | float | 0% | 1 | 1.0 |
ports_ports_with_oil_terminals_text |
Ports with oil terminals (text) | float | 0% | 1 | 0 |
ports_ports_with_oil_terminals_numeric |
Ports with oil terminals (numeric) | float | 0% | 1 | 0.0 |
ports_key_ports_text |
ports_key_ports_text | string | 0% | 1 | Puerto de Asuncion |
source_section |
source_section | string | 0% | 1 | Transportation |
source_profile_path |
source_profile_path | string | 0% | 1 | south-america/pa.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 9 | Asuncion, Ciudad del Este, Encarnacion, Pedro Juan... |
country_code |
Country code | string | SEL | 0% | 1 | PRY, PRY, PRY, PRY, PRY |
population |
Population count | integer | SEL | 0% | 9 | 1175482, 422701, 177551, 127053, 109880 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 9 | 217, 1050, 930, 379, 527 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Paraguay, Paraguay, Paraguay, Paraguay, Paraguay |
population_year |
population_year | integer | 0% | 1 | 2025, 2025, 2025, 2025, 2025 |
latitude |
latitude | string | 100% | - | - |
longitude |
longitude | string | 100% | - | - |
region |
region | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | PRY, PRY, PRY, PRY |
gns_language_code |
gns_language_code | string | CCL | 0% | 4 | spa, por, grn, eng |
gns_language_name |
gns_language_name | string | CCL | 0% | 4 | Spanish, Portuguese, Guarani, English |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 3 | 9074, 5, 3, 3 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 3 | 99.8789, 0.055, 0.033, 0.033 |
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 | PRY |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Paraguay |
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 | 99.9846 |
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 | 12964 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 10297 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 12962 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 2 |
gns_source_build_date |
gns_source_build_date | string | 0% | 1 | Wed, 05 Aug 2026 |
gns_source_change_date |
gns_source_change_date | string | 0% | 1 | 2026-08-05 |
gns_name_count_populated_places |
gns_name_count_populated_places | integer | 0% | 1 | 8126 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 6827 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 609 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 542 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 385 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 342 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 958 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 284 |
gns_name_count_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 1945 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 1588 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 897 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 687 |
gns_name_count_vegetation |
gns_name_count_vegetation | integer | 0% | 1 | 41 |
gns_feature_count_vegetation |
gns_feature_count_vegetation | integer | 0% | 1 | 25 |
gns_name_count_transportation_networks |
gns_name_count_transportation_networks | integer | 0% | 1 | 3 |
gns_feature_count_transportation_networks |
gns_feature_count_transportation_networks | integer | 0% | 1 | 2 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 100% | - | - |
contraception_modern_pct |
Contraception modern percent | float | SEL | 0% | 4 | 29.1, 18.7, 24.0, 16.8 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 0% | 4 | 29.0, 34.0, 41.0, 42.0 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 0% | 4 | 40.0, 44.0, 51.0, 56.0 |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 0% | 4 | 43.6, 39.3, 27.8, 20.1 |
children_underweight |
Children underweight | float | CCL | 0% | 3 | 2.7, 2.7, 1.9, 4.3 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Paraguay, Paraguay, Paraguay, Paraguay |
survey_year |
survey_year | integer | 0% | 1 | 1990, 1990, 1990, 1990 |
region |
region | string | 0% | 4 | Asunción and MA, Center - South, East, North |
survey_id |
survey_id | string | 0% | 1 | PY1990DHS, PY1990DHS, PY1990DHS, PY1990DHS |
survey_type |
survey_type | string | 0% | 1 | DHS, DHS, DHS, DHS |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY, PRY, PRY, PRY |
society_id |
Society id | string | CCL | 0% | 4 | Sh2, Sh5, Sh6, Sh9 |
society_name |
Society name | string | CCL | 0% | 4 | Terena, Choroti, Chamacoco, Lengua |
language_glottocode |
Language glottocode | string | CCL | 0% | 4 | tere1279, iyow1239, cham1315, nort2971 |
language_name |
Language name | string | CCL | 0% | 1 | , , , |
kinship_system |
Kinship system | string | CCL | 0% | 4 | EA001:2; EA002:1; EA003:3; EA004:1; EA005:3, EA001:4;... |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 4 | EA006:6; EA007:8; EA008:8; EA009:2; EA010:9, EA006:2;... |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 4 | EA028:3; EA029:5; EA030:2; EA031:NA; EA032:4, EA028:2;... |
political_complexity |
Political complexity | string | CCL | 0% | 4 | EA033:1; EA034:2; EA035:NA, EA033:1; EA034:1; EA035:5,... |
religion_importance |
Religion importance | string | CCL | 0% | 4 | EA034:2; EA112:1, EA034:1; EA112:NA, EA034:3; EA112:2,... |
residence_pattern |
Residence pattern | string | CCL | 0% | 3 | EA011:2; EA012:2; EA013:9, EA011:3; EA012:9; EA013:9,... |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Paraguay, Paraguay, Paraguay, Paraguay |
dataset |
dataset | string | 0% | 1 | EA, EA, EA, EA |
region |
region | string | 0% | 1 | , , , |
latitude |
latitude | float | 0% | 4 | -21.0, -22.0, -20.0, -23.0 |
longitude |
longitude | float | 0% | 3 | -58.0, -62.0, -59.0, -59.0 |
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 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | PRY, PRY |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 2 | Whites/mestizos, Tupi-Guaraní and other indigenous groups |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 2 | MONOPOLY, POWERLESS |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 2 | 0.945, 0.02 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 2 | 15001000, 15005000 |
regional_autonomy |
Regional autonomy | string | CCL | 0% | 2 | , false |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 1 | 2021, 2021 |
group_relevance |
group_relevance | string | 0% | 1 | , |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
oc_anti_money_laundering |
oc_anti_money_laundering | numeric | CCL | 0% | 1 | - |
oc_arms_trafficking |
oc_arms_trafficking | numeric | CCL | 0% | 1 | - |
oc_criminal_actors |
oc_criminal_actors | numeric | CCL | 0% | 1 | - |
oc_criminal_markets |
oc_criminal_markets | numeric | CCL | 0% | 1 | - |
oc_criminality |
oc_criminality | numeric | CCL | 0% | 1 | - |
oc_cyber_dependent_crimes |
oc_cyber_dependent_crimes | numeric | CCL | 0% | 1 | - |
oc_financial_crimes |
oc_financial_crimes | numeric | CCL | 0% | 1 | - |
oc_human_smuggling |
oc_human_smuggling | numeric | CCL | 0% | 1 | - |
oc_human_trafficking |
oc_human_trafficking | numeric | CCL | 0% | 1 | - |
oc_judicial_system_and_detention |
oc_judicial_system_and_detention | numeric | CCL | 0% | 1 | - |
oc_law_enforcement |
oc_law_enforcement | numeric | CCL | 0% | 1 | - |
oc_political_leadership_and_governance |
oc_political_leadership_and_governance | numeric | CCL | 0% | 1 | - |
oc_resilience |
oc_resilience | numeric | CCL | 0% | 1 | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
oc_cannabis_trade |
oc_cannabis_trade | numeric | 0% | 1 | - |
oc_cocaine_trade |
oc_cocaine_trade | numeric | 0% | 1 | - |
oc_criminal_networks |
oc_criminal_networks | numeric | 0% | 1 | - |
oc_economic_regulatory_capacity |
oc_economic_regulatory_capacity | numeric | 0% | 1 | - |
oc_extortion_and_protection_racketeering |
oc_extortion_and_protection_racketeering | numeric | 0% | 1 | - |
oc_fauna_crimes |
oc_fauna_crimes | numeric | 0% | 1 | - |
oc_flora_crimes |
oc_flora_crimes | numeric | 0% | 1 | - |
oc_foreign_actors |
oc_foreign_actors | numeric | 0% | 1 | - |
oc_government_transparency_and_accountability |
oc_government_transparency_and_accountability | numeric | 0% | 1 | - |
oc_heroin_trade |
oc_heroin_trade | numeric | 0% | 1 | - |
oc_illicit_trade_in_excisable_goods |
oc_illicit_trade_in_excisable_goods | numeric | 0% | 1 | - |
oc_international_cooperation |
oc_international_cooperation | numeric | 0% | 1 | - |
oc_mafia_style_groups |
oc_mafia_style_groups | numeric | 0% | 1 | - |
oc_national_policies_and_laws |
oc_national_policies_and_laws | numeric | 0% | 1 | - |
oc_non_renewable_resource_crimes |
oc_non_renewable_resource_crimes | numeric | 0% | 1 | - |
oc_non_state_actors |
oc_non_state_actors | numeric | 0% | 1 | - |
oc_prevention |
oc_prevention | numeric | 0% | 1 | - |
oc_private_sector_actors |
oc_private_sector_actors | numeric | 0% | 1 | - |
oc_state_embedded_actors |
oc_state_embedded_actors | numeric | 0% | 1 | - |
oc_synthetic_drug_trade |
oc_synthetic_drug_trade | numeric | 0% | 1 | - |
oc_territorial_integrity |
oc_territorial_integrity | numeric | 0% | 1 | - |
oc_trade_in_counterfeit_goods |
oc_trade_in_counterfeit_goods | numeric | 0% | 1 | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
iso3 |
iso3 | string | 0% | 1 | PRY |
source |
source | string | 0% | 1 | Global Organized Crime Index |
source_url |
source_url | string | 0% | 1 | https://ocindex.net/ |
year |
year | integer | 0% | 1 | 2025 |
license |
license | string | 0% | 1 | Creative Commons (GI-TOC / ENACT) |
oc_anti_money_laundering_rank |
oc_anti_money_laundering_rank | integer | 0% | 1 | 170 |
oc_anti_money_laundering_2023 |
oc_anti_money_laundering_2023 | float | 0% | 1 | 2.5 |
oc_anti_money_laundering_2021 |
oc_anti_money_laundering_2021 | float | 0% | 1 | 2.5 |
oc_arms_trafficking_rank |
oc_arms_trafficking_rank | integer | 0% | 1 | 6 |
oc_arms_trafficking_2023 |
oc_arms_trafficking_2023 | integer | 0% | 1 | 9 |
oc_arms_trafficking_2021 |
oc_arms_trafficking_2021 | float | 0% | 1 | 8.5 |
oc_cannabis_trade_rank |
oc_cannabis_trade_rank | integer | 0% | 1 | 1 |
oc_cannabis_trade_2023 |
oc_cannabis_trade_2023 | integer | 0% | 1 | 9 |
oc_cannabis_trade_2021 |
oc_cannabis_trade_2021 | integer | 0% | 1 | 9 |
oc_cocaine_trade_rank |
oc_cocaine_trade_rank | integer | 0% | 1 | 7 |
oc_cocaine_trade_2023 |
oc_cocaine_trade_2023 | float | 0% | 1 | 8.5 |
oc_cocaine_trade_2021 |
oc_cocaine_trade_2021 | integer | 0% | 1 | 7 |
oc_criminal_actors_rank |
oc_criminal_actors_rank | integer | 0% | 1 | 3 |
oc_criminal_actors_2023 |
oc_criminal_actors_2023 | float | 0% | 1 | 8.3 |
oc_criminal_actors_2021 |
oc_criminal_actors_2021 | float | 0% | 1 | 7.5 |
oc_criminal_markets_rank |
oc_criminal_markets_rank | integer | 0% | 1 | 18 |
oc_criminal_markets_2023 |
oc_criminal_markets_2023 | float | 0% | 1 | 6.73 |
oc_criminal_markets_2021 |
oc_criminal_markets_2021 | float | 0% | 1 | 5.9 |
oc_criminal_networks_rank |
oc_criminal_networks_rank | integer | 0% | 1 | 7 |
oc_criminal_networks_2023 |
oc_criminal_networks_2023 | integer | 0% | 1 | 8 |
oc_criminal_networks_2021 |
oc_criminal_networks_2021 | float | 0% | 1 | 7.5 |
oc_criminality_rank |
oc_criminality_rank | integer | 0% | 1 | 4 |
oc_criminality_2023 |
oc_criminality_2023 | float | 0% | 1 | 7.52 |
oc_criminality_2021 |
oc_criminality_2021 | float | 0% | 1 | 6.7 |
oc_cyber_dependent_crimes_rank |
oc_cyber_dependent_crimes_rank | integer | 0% | 1 | 38 |
| +74 more pending fields — download the CSV/Parquet to see them all. | |||||
Which languages name the landscape here, and in which writing systems. A language's toponymic footprint and its speaker population are different measures and often diverge. Counts include variant and foreign-language renderings of the same place, so a language can rank high because outside sources record names in it rather than because it is spoken locally — and a widely spoken language can be almost absent where official naming is in another language.
| Language | Place names | Share | Script |
|---|---|---|---|
| Spanish (spa) | 9,074 | 99.9% | — |
| Portuguese (por) | 5 | 0.1% | — |
10,297 distinct features ·
4 languages ·
0 scripts ·
2 conventional English names
Source: NGA GEOnet Names Server
(public domain) · rebuilt Wed, 05 Aug 2026.
Names follow the US/BGN convention.
The data providers this country's datasets are sourced from — each links out to the provider.
Pick datasets and admin level(s). You'll get a .zip with one CSV per dataset, each filtered to the levels you choose.