ⓘ 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 | SDN, SDN, SDN, SDN, SDN |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 16 | Total, Al Gedarif, Al Gezira, Blue Nile, Kassala |
human_development_index |
Human development index | float | SEL | 0% | 82 | 0.501, 0.451, 0.576, 0.384, 0.42 |
health_index |
Health index | float | SEL | 0% | 76 | 0.635, 0.599, 0.681, 0.498, 0.62 |
education_index |
Education index | float | SEL | 0% | 85 | 0.398, 0.338, 0.486, 0.255, 0.264 |
income_index |
Income index | float | SEL | 0% | 81 | 0.497, 0.453, 0.577, 0.444, 0.452 |
life_expectancy |
Life expectancy | float | SEL | 0% | 97 | 61.26, 58.92, 64.25, 52.38, 60.29 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 99 | 5.967, 4.174, 7.358, 2.628, 3.153 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 7 | 2008, 2008, 2008, 2008, 2008 |
level |
level | string | 0% | 2 | national, subnational, subnational, subnational, subnational |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 1 | SD |
region_name |
Region name | string | SEL | 0% | 1 | Sudan (the) |
F_TL |
Female population | integer | SEL | 0% | 1 | 23757049 |
M_TL |
Male population | integer | SEL | 0% | 1 | 23757480 |
T_TL |
Total population | integer | SEL | 0% | 1 | 47514529 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
Admin level | string | 0% | 1 | admin_0 |
year |
Reference year | integer | 0% | 1 | 2024 |
ADM0_AR |
ADM0_AR | string | 0% | 1 | السودان |
F_00_04 |
Female population age 0-4 | integer | 0% | 1 | 3621634 |
F_05_09 |
Female population age 5-9 | integer | 0% | 1 | 3169357 |
F_10_14 |
Female population age 10-14 | integer | 0% | 1 | 2853401 |
F_15_19 |
Female population age 15-19 | integer | 0% | 1 | 2539533 |
F_20_24 |
Female population age 20-24 | integer | 0% | 1 | 2055672 |
F_25_29 |
Female population age 25-29 | integer | 0% | 1 | 1742641 |
F_30_34 |
Female population age 30-34 | integer | 0% | 1 | 1552997 |
F_35_39 |
Female population age 35-39 | integer | 0% | 1 | 1333732 |
F_40_44 |
Female population age 40-44 | integer | 0% | 1 | 1164006 |
F_45_49 |
Female population age 45-49 | integer | 0% | 1 | 1008331 |
F_50_54 |
Female population age 50-54 | integer | 0% | 1 | 838353 |
F_55_59 |
Female population age 55-59 | integer | 0% | 1 | 641233 |
F_60_64 |
Female population age 60-64 | integer | 0% | 1 | 472341 |
F_65_69 |
Female population age 65-69 | integer | 0% | 1 | 324510 |
F_70_74 |
Female population age 70-74 | integer | 0% | 1 | 208851 |
F_75_79 |
Female population age 75-79 | integer | 0% | 1 | 130091 |
F_80Plus |
F_80Plus | integer | 0% | 1 | 100366 |
M_00_04 |
Male population age 0-4 | integer | 0% | 1 | 3696093 |
M_05_09 |
Male population age 5-9 | integer | 0% | 1 | 3208029 |
M_10_14 |
Male population age 10-14 | integer | 0% | 1 | 2878133 |
M_15_19 |
Male population age 15-19 | integer | 0% | 1 | 2545728 |
M_20_24 |
Male population age 20-24 | integer | 0% | 1 | 2005672 |
M_25_29 |
Male population age 25-29 | integer | 0% | 1 | 1857938 |
M_30_34 |
Male population age 30-34 | integer | 0% | 1 | 1725828 |
M_35_39 |
Male population age 35-39 | integer | 0% | 1 | 1276412 |
M_40_44 |
Male population age 40-44 | integer | 0% | 1 | 993966 |
M_45_49 |
Male population age 45-49 | integer | 0% | 1 | 880465 |
| +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 | SD15, SD08, SD06, SD05, SD12 |
region_name |
Region name | string | SEL | 0% | 18 | Aj Jazirah, Blue Nile, Central Darfur, East Darfur, Gedaref |
F_TL |
Female population | integer | SEL | 0% | 18 | 2754548, 461013, 628513, 1295396, 1551306 |
M_TL |
Male population | integer | SEL | 0% | 18 | 2583000, 462415, 592112, 1180899, 1449946 |
T_TL |
Total population | integer | SEL | 0% | 18 | 5337548, 923428, 1220625, 2476295, 3001252 |
| 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 | 2024, 2024, 2024, 2024, 2024 |
ADM0_AR |
ADM0_AR | string | 0% | 1 | السودان, السودان, السودان, السودان, السودان |
ADM1_AR |
ADM1_AR | string | 0% | 18 | الجزيرة, النيل الأزرق, وسط دارفور, شرق دارفور, القضارف |
F_00_04 |
Female population age 0-4 | integer | 0% | 18 | 401391, 89833, 117797, 268121, 264452 |
F_05_09 |
Female population age 5-9 | integer | 0% | 18 | 362644, 69558, 91809, 173234, 226677 |
F_10_14 |
Female population age 10-14 | integer | 0% | 18 | 331698, 62218, 80435, 140469, 202123 |
F_15_19 |
Female population age 15-19 | integer | 0% | 18 | 304473, 59354, 68580, 121203, 171725 |
F_20_24 |
Female population age 20-24 | integer | 0% | 18 | 254796, 44121, 51184, 97054, 128287 |
F_25_29 |
Female population age 25-29 | integer | 0% | 18 | 202633, 28987, 42938, 90459, 111027 |
F_30_34 |
Female population age 30-34 | integer | 0% | 18 | 171717, 21880, 37659, 84308, 99074 |
F_35_39 |
Female population age 35-39 | integer | 0% | 18 | 142814, 19700, 31527, 68176, 80263 |
F_40_44 |
Female population age 40-44 | integer | 0% | 18 | 126574, 17923, 26710, 57527, 65792 |
F_45_49 |
Female population age 45-49 | integer | 0% | 18 | 114640, 14145, 22208, 50883, 55082 |
F_50_54 |
Female population age 50-54 | integer | 0% | 18 | 98156, 10814, 17825, 42713, 44920 |
F_55_59 |
Female population age 55-59 | integer | 0% | 18 | 78754, 7917, 13183, 30951, 34472 |
F_60_64 |
Female population age 60-64 | integer | 0% | 18 | 61631, 5888, 9976, 25644, 25825 |
F_65_69 |
Female population age 65-69 | integer | 0% | 18 | 43980, 3906, 6917, 19210, 17674 |
F_70_74 |
Female population age 70-74 | integer | 0% | 18 | 28654, 2286, 4370, 12037, 11247 |
F_75_79 |
Female population age 75-79 | integer | 0% | 18 | 17269, 1393, 2854, 7617, 7036 |
F_80Plus |
F_80Plus | integer | 0% | 18 | 12724, 1090, 2541, 5790, 5630 |
M_00_04 |
Male population age 0-4 | integer | 0% | 18 | 410072, 89938, 119417, 247582, 266288 |
M_05_09 |
Male population age 5-9 | integer | 0% | 18 | 371738, 69615, 93892, 134986, 222945 |
M_10_14 |
Male population age 10-14 | integer | 0% | 18 | 338855, 61941, 80161, 141486, 192914 |
M_15_19 |
Male population age 15-19 | integer | 0% | 18 | 308992, 58320, 67727, 121199, 161824 |
M_20_24 |
Male population age 20-24 | integer | 0% | 18 | 251350, 42941, 48228, 78687, 120009 |
M_25_29 |
Male population age 25-29 | integer | 0% | 18 | 199904, 30080, 42378, 90880, 105017 |
M_30_34 |
Male population age 30-34 | integer | 0% | 18 | 162513, 24185, 37058, 92470, 92031 |
M_35_39 |
Male population age 35-39 | integer | 0% | 18 | 108888, 16842, 24195, 59280, 62759 |
M_40_44 |
Male population age 40-44 | integer | 0% | 18 | 81284, 12895, 16689, 41031, 45189 |
| +25 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 100 | SD15034, SD15035, SD15036, SD15037, SD15031 |
region_name |
Region name | string | SEL | 0% | 99 | Al Hasahisa, Al Kamlin, Al Manaqil, Al Qurashi, Janub Al Jazirah |
F_TL |
Female population | integer | SEL | 0% | 100 | 486599, 332736, 447543, 286953, 435126 |
M_TL |
Male population | integer | SEL | 0% | 100 | 454556, 323503, 414058, 265550, 403060 |
T_TL |
Total population | integer | SEL | 0% | 100 | 941155, 656239, 861601, 552503, 838186 |
| 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 | 2024, 2024, 2024, 2024, 2024 |
ADM0_AR |
ADM0_AR | string | 0% | 1 | السودان, السودان, السودان, السودان, السودان |
ADM1_AR |
ADM1_AR | string | 0% | 11 | الجزيرة, الجزيرة, الجزيرة, الجزيرة, الجزيرة |
ADM2_AR |
ADM2_AR | string | 0% | 99 | الحصاحيصا, الكاملين, المناقل, القرشي, جنوب الجزيرة |
F_00_04 |
Female population age 0-4 | integer | 0% | 99 | 71820, 50357, 66907, 43008, 63817 |
F_05_09 |
Female population age 5-9 | integer | 0% | 99 | 63976, 42967, 58652, 37472, 58297 |
F_10_14 |
Female population age 10-14 | integer | 0% | 100 | 57921, 38994, 54188, 34575, 52494 |
F_15_19 |
Female population age 15-19 | integer | 0% | 100 | 51681, 35742, 52507, 33547, 45969 |
F_20_24 |
Female population age 20-24 | integer | 0% | 100 | 43473, 30095, 43598, 27932, 38762 |
F_25_29 |
Female population age 25-29 | integer | 0% | 100 | 35623, 24039, 33237, 21313, 32290 |
F_30_34 |
Female population age 30-34 | integer | 0% | 99 | 30249, 20569, 27685, 17758, 27466 |
F_35_39 |
Female population age 35-39 | integer | 0% | 100 | 24824, 17469, 22868, 14673, 22369 |
F_40_44 |
Female population age 40-44 | integer | 0% | 100 | 22166, 15494, 19910, 12771, 19811 |
F_45_49 |
Female population age 45-49 | integer | 0% | 99 | 20799, 13887, 17527, 11244, 18344 |
F_50_54 |
Female population age 50-54 | integer | 0% | 100 | 18116, 11801, 14621, 9379, 15965 |
F_55_59 |
Female population age 55-59 | integer | 0% | 100 | 14501, 9400, 11419, 7322, 12984 |
F_60_64 |
Female population age 60-64 | integer | 0% | 98 | 11681, 8281, 8885, 5811, 9947 |
F_65_69 |
Female population age 65-69 | integer | 0% | 100 | 8445, 5874, 6555, 4280, 7117 |
F_70_74 |
Female population age 70-74 | integer | 0% | 98 | 5529, 3794, 4384, 2861, 4632 |
F_75_79 |
Female population age 75-79 | integer | 0% | 96 | 3306, 2267, 2675, 1748, 2769 |
F_80Plus |
F_80Plus | integer | 0% | 95 | 2489, 1706, 1925, 1259, 2093 |
M_00_04 |
Male population age 0-4 | integer | 0% | 100 | 73200, 50947, 68357, 43884, 65321 |
M_05_09 |
Male population age 5-9 | integer | 0% | 99 | 65348, 43977, 59831, 38248, 59488 |
M_10_14 |
Male population age 10-14 | integer | 0% | 100 | 58781, 39635, 55037, 35143, 53313 |
M_15_19 |
Male population age 15-19 | integer | 0% | 99 | 51953, 35939, 52969, 33860, 46268 |
M_20_24 |
Male population age 20-24 | integer | 0% | 100 | 42964, 29831, 42542, 27262, 37692 |
M_25_29 |
Male population age 25-29 | integer | 0% | 100 | 35902, 24722, 32184, 20667, 31168 |
M_30_34 |
Male population age 30-34 | integer | 0% | 100 | 29388, 21194, 25134, 16156, 25440 |
M_35_39 |
Male population age 35-39 | integer | 0% | 99 | 19348, 15702, 15836, 10199, 16736 |
| +26 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SD, SD, SD, SD, SD |
population_count |
Population count | float | SEL | 2% | 65 | 8364489.0, 8634941.0, 8919028.0, 9218077.0, 9531109.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 49.566, 49.964, 50.419, 50.816, 50.879 |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 2% | 65 | 99.7131195068359, 105.313102722168, 111.213455200195,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 97% | 2 | 61.3499984741211, 53.5200004577637 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 177.8, 175.0, 172.4, 169.8, 167.4 |
poverty_headcount_pct |
Poverty headcount percent | float | SEL | 99% | 1 | 46.5 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Sudan, Sudan, Sudan, Sudan, Sudan |
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 | SD, SD, SD, SD, SD |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 49.566, 49.964, 50.419, 50.816, 50.879 |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 17% | 51 | 46.8, 46.6, 46.4, 46.2, 46.1 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 3% | 64 | 177.8, 175.0, 172.4, 169.8, 167.4 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 39 | 980.0, 938.0, 914.0, 877.0, 881.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 63 | 6.663, 6.656, 6.704, 6.758, 6.804 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 64 | 47.667, 47.595, 47.957, 48.272, 48.512 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 64 | 16.316, 16.03, 15.743, 15.496, 15.445 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 74% | 14 | 0.03, 0.041, 0.068, 0.068, 0.11 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 58% | 16 | 1.00650095939636, 1.04260003566742, 0.9932000041008,... |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 32% | 29 | 1.0, 1.0, 2.0, 3.0, 4.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 3.60664487, 3.36456871, 3.30010891, 3.89187932, 4.15593481 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Sudan, Sudan, Sudan, Sudan, Sudan |
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% | 100 | ache1245, adam1253, afit1238, ajas1235, akaa1242 |
name |
Name | string | CCL | 0% | 100 | Acheron, Adamawa Fulfulde, Afitti, Aja (South Sudan), Aka |
iso639_3 |
Iso639 3 | string | CCL | 7% | 93 | acz, fub, aft, aja, soh |
level |
Level | string | CCL | 0% | 1 | language, language, language, language, language |
family_name |
Family name | string | CCL | 100% | - | - |
family_glottocode |
Family glottocode | string | CCL | 4% | 25 | narr1279, atla1278, nyim1244, kres1240, east2386 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 4% | 62 | ache1247, adam1260, nyim1244, kres1240, akak1254 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 18 | ['SD'], ['CM', 'ER', 'ET', 'NG', 'SD', 'TD'], ['SD'],... |
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% | 15 | 2, 6, 0, 0, 0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 1% | 99 | 10.8827, 8.140326, 12.446, 8.58003, 11.2101 |
longitude |
longitude | float | 1% | 99 | 30.3187, 13.077338, 30.7611, 25.6122, 33.6524 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | Sudan |
admin_code |
Admin code | string | SEL | 0% | 1 | 86632940B79902438371927 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 1871528.541 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 50440195 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 26.95 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN, SDN, SDN, SDN, SDN |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
admin_name |
Admin name | string | SEL | 0% | 19 | Gezira, Khartoum, South Darfur, North Darfur, Kassala |
admin_code |
Admin code | string | SEL | 0% | 19 | 86620642B80352504723135, 86620642B69351377969837,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 19 | 27149.2762, 21219.3804, 85827.3573, 317217.0699, 48695.6116 |
pop_2024 |
Population count | integer | SEL | 0% | 19 | 6176613, 5655763, 4051728, 3311892, 3307456 |
pop_density_2024 |
Population density | float | SEL | 0% | 19 | 227.51, 266.54, 47.21, 10.44, 67.92 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN, SDN, SDN, SDN, SDN |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality, locality, locality, locality |
admin_name |
Admin name | string | SEL | 0% | 80 | Khartoum, Port Sudan, Nyala, Kassala, Wad Madanī |
admin_code |
Admin code | integer | SEL | 0% | 80 | 4155, 5561, 2047, 5438, 4682 |
area_sqkm |
Area sqkm | float | SEL | 0% | 79 | 952.5076, 100.476, 103.3639, 64.626, 61.6359 |
pop_2024 |
Population count | integer | SEL | 0% | 80 | 4436362, 1291442, 1129548, 937711, 451869 |
pop_density_2024 |
Population density | float | SEL | 0% | 80 | 4657.56, 12853.24, 10927.88, 14509.81, 7331.26 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 80 | 7114789, 536782, 1038790, 404472, 405413 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 79 | 0.624, 2.406, 1.087, 2.318, 1.115 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 80 | Khartoum, Nyala, Kebkabiya, Al-Ubayyid, Al-Fashir |
country_code |
Country code | string | SEL | 0% | 1 | SDN, SDN, SDN, SDN, SDN |
population |
Population count | integer | SEL | 0% | 80 | 7114789, 1038790, 727487, 679642, 665730 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 80 | 4155, 2047, 1313, 3858, 2575 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Sudan, Sudan, Sudan, Sudan, Sudan |
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 | SDN, SDN, SDN, SDN, SDN |
society_id |
Society id | string | CCL | 0% | 23 | Ai10, Ai2, Ai37, Ai39, Ai4 |
society_name |
Society name | string | CCL | 0% | 23 | Otoro, Nyaro, Koalib, Mesakin, Ingassana |
language_glottocode |
Language glottocode | string | CCL | 0% | 21 | otor1240, kooo1244, koal1240, ngil1242, gaam1241 |
language_name |
Language name | string | CCL | 0% | 1 | , , , , |
kinship_system |
Kinship system | string | CCL | 0% | 14 | EA001:0; EA002:2; EA003:0; EA004:2; EA005:6, EA001:0;... |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 17 | EA006:1; EA007:8; EA008:5; EA009:5; EA010:8, EA006:1;... |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 14 | EA028:5; EA029:6; EA030:6; EA031:NA; EA032:3, EA028:NA;... |
political_complexity |
Political complexity | string | CCL | 0% | 7 | EA033:2; EA034:NA; EA035:NA, EA033:NA; EA034:NA;... |
religion_importance |
Religion importance | string | CCL | 0% | 7 | EA034:NA; EA112:8, EA034:NA; EA112:NA, EA034:NA;... |
residence_pattern |
Residence pattern | string | CCL | 0% | 6 | EA011:1; EA012:8; EA013:2, EA011:1; EA012:8; EA013:9,... |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Sudan, Sudan, Sudan, Sudan, Sudan |
dataset |
dataset | string | 0% | 1 | EA, EA, EA, EA, EA |
region |
region | string | 0% | 1 | , , , , |
latitude |
latitude | float | 0% | 9 | 12.0, 11.0, 12.0, 11.0, 11.0 |
longitude |
longitude | float | 0% | 12 | 31.0, 31.0, 31.0, 30.0, 34.0 |
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 |
| 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 | 2022.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 74.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .sd |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 26.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric |
Broadband subscriptions per 100 | float | SEL | 0% | 1 | 2022.0 |
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
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 | 156,000 (2022 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 156000.0 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | (2022 est.) less than 1 |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 34.7 million (2022 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 34.7 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 74 (2022 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | state-owned broadcasters that self-censor but are... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 2022.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 26% (2020 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 30,000 (2022 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 30000.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text | string | 0% | 1 | (2022 est.) less than 1 |
source_section |
source_section | string | 0% | 1 | Communications |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/su.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 | 1900.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 49.91 |
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
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 | low-income Sahel economy devastated by ongoing civil... |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $94.42 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 | 94.42 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $109.147 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 | 109.147 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $154.672 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 | 154.672 |
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 | -13.5% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | -13.5 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | -29.4% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | -29.4 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | -1% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | -1.0 |
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 | $1,900 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $2,200 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 2200.0 |
real_gdp_per_capita_real_gdp_per_capita_2022_text |
Real gdp per capita 2022 (text) | string | 0% | 1 | $3,100 (2022 est.) |
real_gdp_per_capita_real_gdp_per_capita_2022_numeric |
Real gdp per capita 2022 (numeric) | float | 0% | 1 | 3100.0 |
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 | $49.91 billion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 138.8% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 138.8 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2021_text |
Inflation rate consumer prices 2021 (text) | string | 0% | 1 | 359.1% (2021 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2021_numeric |
Inflation rate consumer prices 2021 (numeric) | float | 0% | 1 | 359.1 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2020_text |
Inflation rate consumer prices 2020 (text) | string | 0% | 1 | 163.3% (2020 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2020_numeric |
Inflation rate consumer prices 2020 (numeric) | float | 0% | 1 | 163.3 |
inflation_rate_consumer_prices_note |
inflation_rate_consumer_prices_note | string | 0% | 1 | note: annual % change based on consumer prices |
gdp_composition_by_sector_of_origin_agriculture_text |
gdp_composition_by_sector_of_origin_agriculture_text | string | 0% | 1 | 22.1% (2024 est.) |
| +108 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 | 63.2 |
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
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 | 63.2% (2022 est.) |
electricity_access_electrification_urban_areas_text |
electricity_access_electrification_urban_areas_text | string | 0% | 1 | 84% |
electricity_access_electrification_urban_areas_numeric |
electricity_access_electrification_urban_areas_numeric | float | 0% | 1 | 84.0 |
electricity_access_electrification_rural_areas_text |
electricity_access_electrification_rural_areas_text | string | 0% | 1 | 49.4% |
electricity_access_electrification_rural_areas_numeric |
electricity_access_electrification_rural_areas_numeric | float | 0% | 1 | 49.4 |
electricity_installed_generating_capacity_text |
electricity_installed_generating_capacity_text | string | 0% | 1 | 3.815 million kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 3.815 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 13.983 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 13.983 |
electricity_imports_text |
electricity_imports_text | string | 0% | 1 | 882 million kWh (2023 est.) |
electricity_imports_numeric |
electricity_imports_numeric | float | 0% | 1 | 882.0 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 3.646 billion kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 3.646 |
electricity_generation_sources_fossil_fuels_text |
electricity_generation_sources_fossil_fuels_text | string | 0% | 1 | 29.9% of total installed capacity (2023 est.) |
electricity_generation_sources_fossil_fuels_numeric |
electricity_generation_sources_fossil_fuels_numeric | float | 0% | 1 | 29.9 |
electricity_generation_sources_solar_text |
electricity_generation_sources_solar_text | string | 0% | 1 | 0.8% of total installed capacity (2023 est.) |
electricity_generation_sources_solar_numeric |
electricity_generation_sources_solar_numeric | float | 0% | 1 | 0.8 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 68.7% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 68.7 |
electricity_generation_sources_biomass_and_waste_text |
electricity_generation_sources_biomass_and_waste_text | string | 0% | 1 | 0.6% of total installed capacity (2023 est.) |
electricity_generation_sources_biomass_and_waste_numeric |
electricity_generation_sources_biomass_and_waste_numeric | float | 0% | 1 | 0.6 |
coal_exports_text |
coal_exports_text | string | 0% | 1 | 15 metric tons (2023 est.) |
coal_exports_numeric |
coal_exports_numeric | float | 0% | 1 | 15.0 |
coal_imports_text |
coal_imports_text | string | 0% | 1 | 200 metric tons (2023 est.) |
coal_imports_numeric |
coal_imports_numeric | float | 0% | 1 | 200.0 |
petroleum_total_petroleum_production_text |
petroleum_total_petroleum_production_text | string | 0% | 1 | 68,000 bbl/day (2023 est.) |
petroleum_total_petroleum_production_numeric |
petroleum_total_petroleum_production_numeric | float | 0% | 1 | 68000.0 |
petroleum_refined_petroleum_consumption_text |
petroleum_refined_petroleum_consumption_text | string | 0% | 1 | 129,000 bbl/day (2023 est.) |
petroleum_refined_petroleum_consumption_numeric |
petroleum_refined_petroleum_consumption_numeric | float | 0% | 1 | 129000.0 |
petroleum_crude_oil_estimated_reserves_text |
petroleum_crude_oil_estimated_reserves_text | string | 0% | 1 | 1.25 billion barrels (2021 est.) |
| +7 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 60.3 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 12.0 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 36.3 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 3.43 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 2.831 |
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
environmental_issues_text |
environmental_issues_text | string | 0% | 1 | water pollution; inadequate supplies of potable water;... |
international_environmental_agreements_party_to_text |
international_environmental_agreements_party_to_text | string | 0% | 1 | Biodiversity, Climate Change, Climate Change-Kyoto... |
international_environmental_agreements_signed_but_not_ratified_text |
international_environmental_agreements_signed_but_not_ratified_text | string | 0% | 1 | none of the selected agreements |
climate_text |
climate_text | string | 0% | 1 | hot and dry; arid desert; rainy season varies by region... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 60.3% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 11.2% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 11.2 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.1% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.1 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 49% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 49.0 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 12% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 27.7% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 27.7 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 36.3% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 3.43% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 18.242 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 18.242 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 300 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 | 300.0 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 18.242 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 | 18.242 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 24.4 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 24.4 |
methane_emissions_energy_text |
methane_emissions_energy_text | string | 0% | 1 | 218.5 kt (2022-2024 est.) |
methane_emissions_energy_numeric |
methane_emissions_energy_numeric | float | 0% | 1 | 218.5 |
methane_emissions_agriculture_text |
methane_emissions_agriculture_text | string | 0% | 1 | 1,509.6 kt (2019-2021 est.) |
methane_emissions_agriculture_numeric |
methane_emissions_agriculture_numeric | float | 0% | 1 | 1509.6 |
methane_emissions_waste_text |
methane_emissions_waste_text | string | 0% | 1 | 198.7 kt (2019-2021 est.) |
methane_emissions_waste_numeric |
methane_emissions_waste_numeric | float | 0% | 1 | 198.7 |
| +15 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 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
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 | Sudanese (singular and plural) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Sudanese |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | Sudanese Arab (approximately 70%), Fur, Beja, Nuba,... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 70.0 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/su.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 1861484.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 1731671.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 129813.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 6819.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 853.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 3042.0 |
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 | 60.3 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 12.0 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 15504.0 |
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
location_text |
location_text | string | 0% | 1 | north-eastern Africa, bordering the Red Sea, between... |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 15 00 N, 30 00 E |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 15.0 |
map_references_text |
map_references_text | string | 0% | 1 | Africa |
area_total_text |
area_total_text | string | 0% | 1 | 1,861,484 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 1,731,671 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 129,813 sq km |
area_comparative_text |
area_comparative_text | string | 0% | 1 | slightly less than one-fifth the size of the US |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 6,819 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | Central African Republic 174 km; Chad 1,403 km; Egypt... |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 174.0 |
land_boundaries_note |
land_boundaries_note | string | 0% | 1 | note: Sudan-South Sudan boundary represents 1 January... |
coastline_text |
coastline_text | string | 0% | 1 | 853 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 | 18 nm |
maritime_claims_contiguous_zone_numeric |
maritime_claims_contiguous_zone_numeric | float | 0% | 1 | 18.0 |
maritime_claims_continental_shelf_text |
maritime_claims_continental_shelf_text | string | 0% | 1 | 200-m depth or to the depth of exploitation |
maritime_claims_continental_shelf_numeric |
maritime_claims_continental_shelf_numeric | float | 0% | 1 | 200.0 |
climate_text |
climate_text | string | 0% | 1 | hot and dry; arid desert; rainy season varies by region... |
terrain_text |
terrain_text | string | 0% | 1 | generally flat, featureless plain; desert dominates the north |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Jabal Marrah 3,042 m |
elevation_lowest_point_text |
elevation_lowest_point_text | string | 0% | 1 | Red Sea 0 m |
elevation_mean_elevation_text |
elevation_mean_elevation_text | string | 0% | 1 | 568 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 568.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | petroleum; small reserves of iron ore, copper, chromium... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 60.3% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 11.2% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 11.2 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0.1% (2023 est.) |
| +19 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
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 the Sudan |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Sudan |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | Jumhuriyat as-Sudan |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | As-Sudan |
country_name_former_text |
country_name_former_text | string | 0% | 1 | Anglo-Egyptian Sudan, Democratic Republic of the Sudan |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | the name derives from the Arabic balad-as-sudan, meaning... |
government_type_text |
government_type_text | string | 0% | 1 | presidential republic |
capital_name_text |
capital_name_text | string | 0% | 1 | Khartoum |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 15 36 N, 32 32 E |
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 (8 hours ahead of Washington, DC, during Standard Time) |
capital_time_difference_numeric |
capital_time_difference_numeric | float | 0% | 1 | 3.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | the name derives from the Arabic words ras (head or end)... |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 18 states (wilayat, singular - wilayah); Blue Nile,... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 18.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | mixed system of Islamic law and English common law |
constitution_history_text |
constitution_history_text | string | 0% | 1 | previous 1973, 1998, 2005 (interim constitution, which... |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 1973.0 |
constitution_note |
constitution_note | string | 0% | 1 | note: amended 2020 to incorporate the Juba Agreement for... |
international_law_organization_participation_text |
international_law_organization_participation_text | string | 0% | 1 | accepts compulsory ICJ jurisdiction with reservations;... |
international_law_organization_participation_numeric |
international_law_organization_participation_numeric | float | 0% | 1 | 2008.0 |
citizenship_citizenship_by_birth_text |
Citizenship by birth (text) | string | 0% | 1 | no |
citizenship_citizenship_by_descent_only_text |
Citizenship by descent only (text) | string | 0% | 1 | the father must be a citizen of Sudan |
citizenship_dual_citizenship_recognized_text |
citizenship_dual_citizenship_recognized_text | string | 0% | 1 | no |
citizenship_residency_requirement_for_naturalization_text |
citizenship_residency_requirement_for_naturalization_text | string | 0% | 1 | 10 years |
citizenship_residency_requirement_for_naturalization_numeric |
citizenship_residency_requirement_for_naturalization_numeric | float | 0% | 1 | 10.0 |
suffrage_text |
suffrage_text | string | 0% | 1 | 17 years of age; universal |
suffrage_numeric |
suffrage_numeric | float | 0% | 1 | 17.0 |
executive_branch_chief_of_state_text |
executive_branch_chief_of_state_text | string | 0% | 1 | Sovereign Council Chair and Commander-in-Chief of the... |
executive_branch_chief_of_state_numeric |
executive_branch_chief_of_state_numeric | float | 0% | 1 | 11.0 |
| +53 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 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | Long referred to as Nubia, modern-day Sudan was the site... |
background_numeric |
background_numeric | float | 0% | 1 | 2500.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/su.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_languages_text |
Languages (text) | string | 0% | 1 | Arabic (official), English (official), Nubian, Ta Bedawie, Fur |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | كتاب حقائق العالم، المصدر الذي لا يمكن الاستغناء عنه... |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/su.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
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 | 837,988 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 837988.0 |
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 11,559,970 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 11559970.0 |
trafficking_in_persons_tier_rating_text |
trafficking_in_persons_tier_rating_text | string | 0% | 1 | Tier 3 — Sudan does not fully meet the minimum standards... |
trafficking_in_persons_tier_rating_numeric |
trafficking_in_persons_tier_rating_numeric | float | 0% | 1 | 3.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/su.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
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 | Sudanese Armed Forces (SAF): Ground Force (Sudanese... |
military_and_security_forces_numeric |
military_and_security_forces_numeric | float | 0% | 1 | 2025.0 |
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_expenditures_military_expenditures_2019_text |
Military expenditures 2019 (text) | string | 0% | 1 | 2.4% of GDP (2019 est.) |
military_expenditures_military_expenditures_2019_numeric |
Military expenditures 2019 (numeric) | float | 0% | 1 | 2.4 |
military_expenditures_military_expenditures_2018_text |
Military expenditures 2018 (text) | string | 0% | 1 | 2% of GDP (2018 est.) |
military_expenditures_military_expenditures_2018_numeric |
Military expenditures 2018 (numeric) | float | 0% | 1 | 2.0 |
military_expenditures_military_expenditures_2017_text |
Military expenditures 2017 (text) | string | 0% | 1 | 3.6% of GDP (2017 est.) |
military_expenditures_military_expenditures_2017_numeric |
Military expenditures 2017 (numeric) | float | 0% | 1 | 3.6 |
military_expenditures_note |
military_expenditures_note | string | 0% | 1 | note: many defense expenditures are probably off-budget |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | prior to the outbreak of fighting between the SAF and... |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 2023.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the SAF's inventory includes a mix of mostly Chinese,... |
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 | 18-33 years of age for compulsory or voluntary military... |
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 primary responsibilities of the Sudanese Armed... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 2023.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/su.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 50467278.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 25335092.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 25132186.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 40.1 |
age_structure_15_64_years_numeric |
Population 15 64 percent | float | SEL | 0% | 1 | 56.7 |
age_structure_65_years_and_over_numeric |
Population 65 plus percent | float | SEL | 0% | 1 | 3.2 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 76.4 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 70.7 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 5.7 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 19.5 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | 2.54 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 32.95 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 6.0 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | -1.55 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 36.3 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 3.43 |
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 | 1.01 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 256.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 39.7 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 67.8 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 4.41 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 2.15 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 0.25 |
hospital_bed_density_numeric |
Hospital beds per 1000 | float | SEL | 0% | 1 | 0.7 |
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
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 | 50,467,278 (2024 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 25,335,092 |
population_female_text |
population_female_text | string | 0% | 1 | 25,132,186 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 40.1% (male 10,278,453/female 9,949,343) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 56.7% (male 14,211,514/female 14,390,486) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 3.2% (2024 est.) (male 845,125/female 792,357) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 76.4 (2024 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 70.7 (2024 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 5.7 (2024 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 17.5 (2024 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 17.5 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 19.5 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 19 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 19.0 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 19.6 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 19.6 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | 2.54% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 32.95 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 6 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | -1.55 migrant(s)/1,000 population (2025 est.) |
population_distribution_text |
population_distribution_text | string | 0% | 1 | with the exception of a ribbon of settlement that... |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 36.3% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 3.43% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 6.344 million KHARTOUM (capital), 1.057 million Nyala (2023) |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 6.344 |
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 | 1.03 male(s)/female |
sex_ratio_0_14_years_numeric |
sex_ratio_0_14_years_numeric | float | 0% | 1 | 1.03 |
sex_ratio_15_64_years_text |
sex_ratio_15_64_years_text | string | 0% | 1 | 0.99 male(s)/female |
sex_ratio_15_64_years_numeric |
sex_ratio_15_64_years_numeric | float | 0% | 1 | 0.99 |
| +56 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 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Sunni Muslim, small Christian minority |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/su.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_sunni_muslim_pct_synth |
Sunni Muslim | numeric | 0% | - | - |
composition_religion_small_christian_minority_pct_synth |
small Christian minority | numeric | 0% | - | - |
composition_ethnicity_sudanese_arab_pct_synth |
Sudanese Arab | numeric | 0% | - | - |
composition_ethnicity_fur_pct_synth |
Fur | numeric | 0% | - | - |
composition_ethnicity_beja_pct_synth |
Beja | numeric | 0% | - | - |
composition_ethnicity_nuba_pct_synth |
Nuba | numeric | 0% | - | - |
composition_ethnicity_ingessana_pct_synth |
Ingessana | numeric | 0% | - | - |
composition_ethnicity_uduk_pct_synth |
Uduk | numeric | 0% | - | - |
composition_ethnicity_fallata_pct_synth |
Fallata | numeric | 0% | - | - |
composition_ethnicity_masalit_pct_synth |
Masalit | numeric | 0% | - | - |
composition_ethnicity_dajo_pct_synth |
Dajo | numeric | 0% | - | - |
composition_ethnicity_gimir_pct_synth |
Gimir | numeric | 0% | - | - |
composition_ethnicity_tunjur_pct_synth |
Tunjur | numeric | 0% | - | - |
composition_ethnicity_berti_there_are_over_500_ethnic_groups_pct_synth |
Berti; there are over 500 ethnic groups | numeric | 0% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
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 | Islamic State of Iraq and ash-Sham (ISIS); al-Qa’ida;... |
source_section |
source_section | string | 0% | 1 | Terrorism |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/su.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 | ST |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 45.0 |
country_code |
Country code | string | SEL | 0% | 1 | SDN |
country_name |
Country name | string | SEL | 0% | 1 | Sudan |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
airports_text |
airports_text | string | 0% | 1 | 45 (2025) |
heliports_text |
heliports_text | string | 0% | 1 | 8 (2025) |
heliports_numeric |
heliports_numeric | float | 0% | 1 | 8.0 |
railways_total_text |
railways_total_text | string | 0% | 1 | 7,251 km (2014) |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 7251.0 |
railways_narrow_gauge_text |
railways_narrow_gauge_text | string | 0% | 1 | 5,851 km (2014) 1.067-m gauge |
railways_narrow_gauge_numeric |
railways_narrow_gauge_numeric | float | 0% | 1 | 5851.0 |
railways_note |
railways_note | string | 0% | 1 | 1,400 km 0.600-m gauge for cotton plantations |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 14 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 14.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | other 14 |
merchant_marine_by_type_numeric |
merchant_marine_by_type_numeric | float | 0% | 1 | 14.0 |
ports_total_ports_text |
ports_total_ports_text | string | 0% | 1 | 4 (2024) |
ports_total_ports_numeric |
ports_total_ports_numeric | float | 0% | 1 | 4.0 |
ports_large_text |
ports_large_text | float | 0% | 1 | 0 |
ports_large_numeric |
ports_large_numeric | float | 0% | 1 | 0.0 |
ports_medium_text |
ports_medium_text | float | 0% | 1 | 2 |
ports_medium_numeric |
ports_medium_numeric | float | 0% | 1 | 2.0 |
ports_small_text |
ports_small_text | float | 0% | 1 | 2 |
ports_small_numeric |
ports_small_numeric | float | 0% | 1 | 2.0 |
ports_very_small_text |
ports_very_small_text | float | 0% | 1 | 0 |
ports_very_small_numeric |
ports_very_small_numeric | float | 0% | 1 | 0.0 |
ports_ports_with_oil_terminals_text |
Ports with oil terminals (text) | float | 0% | 1 | 3 |
ports_ports_with_oil_terminals_numeric |
Ports with oil terminals (numeric) | float | 0% | 1 | 3.0 |
ports_key_ports_text |
ports_key_ports_text | string | 0% | 1 | Al Khair Oil Terminal, Beshayer Oil Terminal, Port... |
source_section |
source_section | string | 0% | 1 | Transportation |
source_profile_path |
source_profile_path | string | 0% | 1 | africa/su.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN, SDN, SDN, SDN, SDN |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 9 | Other Arab Groups, Other Northern Groups, Shaygiyya,... |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 3 | POWERLESS, POWERLESS, DOMINANT, POWERLESS, DISCRIMINATED |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 9 | 0.32, 0.22, 0.19, 0.09, 0.07 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 9 | 62509000, 62510000, 62512000, 62503000, 62507000 |
regional_autonomy |
Regional autonomy | string | CCL | 0% | 2 | false, false, , false, false |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 1 | 2021, 2021, 2021, 2021, 2021 |
group_relevance |
group_relevance | string | 0% | 1 | , , , , |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 100% | - | - |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 0% | 6 | 62.0, 92.0, 96.0, 77.0, 75.0 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 0% | 6 | 122.0, 163.0, 178.0, 108.0, 134.0 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Sudan, Sudan, Sudan, Sudan, Sudan |
survey_year |
survey_year | integer | 0% | 1 | 1990, 1990, 1990, 1990, 1990 |
region |
region | string | 0% | 6 | Central, Darfur, Eastern, Khartoum, Kordofan |
survey_id |
survey_id | string | 0% | 1 | SD1990DHS, SD1990DHS, SD1990DHS, SD1990DHS, SD1990DHS |
survey_type |
survey_type | string | 0% | 1 | DHS, DHS, DHS, DHS, DHS |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
economic_conditions |
Economic conditions | integer | CCL | 0% | 1 | 1 |
living_conditions |
Living conditions | integer | CCL | 0% | 1 | 1 |
employment_situation |
Employment situation | integer | CCL | 0% | 1 | 1 |
food_insecurity |
Food insecurity | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
round |
round | string | 0% | 1 | |
year |
year | string | 0% | 1 | |
region |
region | string | 0% | 1 | |
source |
source | string | 0% | 1 | Afrobarometer |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
women_equal_rights |
Women equal rights | integer | CCL | 0% | 1 | 1 |
women_political_leaders |
Women political leaders | integer | CCL | 0% | 1 | 1 |
women_land_rights |
Women land rights | integer | CCL | 0% | 1 | 1 |
domestic_violence_justified |
Domestic violence justified | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
round |
round | string | 0% | 1 | |
year |
year | string | 0% | 1 | |
region |
region | string | 0% | 1 | |
source |
source | string | 0% | 1 | Afrobarometer |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
trust_president |
Trust president | integer | CCL | 0% | 1 | 1 |
trust_parliament |
Trust parliament | integer | CCL | 0% | 1 | 1 |
trust_courts |
Trust courts | integer | CCL | 0% | 1 | 1 |
trust_police |
Trust police | integer | CCL | 0% | 1 | 1 |
trust_army |
Trust army | integer | CCL | 0% | 1 | 1 |
corruption_perception |
Corruption perception | integer | CCL | 0% | 1 | 1 |
democracy_satisfaction |
Democracy satisfaction | integer | CCL | 0% | 1 | 1 |
democracy_preference |
Democracy preference | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
round |
round | string | 0% | 1 | |
year |
year | string | 0% | 1 | |
region |
region | string | 0% | 1 | |
source |
source | string | 0% | 1 | Afrobarometer |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
emigration_considered |
Emigration considered | integer | CCL | 0% | 1 | 1 |
immigration_attitude |
Immigration attitude | integer | CCL | 0% | 1 | 1 |
foreign_workers_attitude |
Foreign workers attitude | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
round |
round | string | 0% | 1 | |
year |
year | string | 0% | 1 | |
region |
region | string | 0% | 1 | |
source |
source | string | 0% | 1 | Afrobarometer |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | SDN |
trust_relatives |
Trust relatives | integer | CCL | 0% | 1 | 1 |
trust_neighbors |
Trust neighbors | integer | CCL | 0% | 1 | 1 |
trust_other_ethnic |
Trust other ethnic | integer | CCL | 0% | 1 | 1 |
trust_other_religion |
Trust other religion | integer | CCL | 0% | 1 | 1 |
national_identity_vs_ethnic |
National identity vs ethnic | integer | CCL | 0% | 1 | 1 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
round |
round | string | 0% | 1 | |
year |
year | string | 0% | 1 | |
region |
region | string | 0% | 1 | |
source |
source | string | 0% | 1 | Afrobarometer |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | SDN, SDN, SDN, SDN |
gns_language_code |
gns_language_code | string | CCL | 0% | 4 | ara, eng, rus, fra |
gns_language_name |
gns_language_name | string | CCL | 0% | 4 | Arabic, English, Russian, French |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 4 | 13397, 1186, 134, 1 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 4 | 91.0246, 8.0582, 0.9104, 0.0068 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 3 | 189, 0, 7, 0 |
gns_dominant_script_code |
gns_dominant_script_code | string | CCL | 0% | 3 | Arab, , Cyrl, |
gns_dominant_script_name |
gns_dominant_script_name | string | CCL | 0% | 3 | Arabic, , Cyrillic, |
gns_script_count |
gns_script_count | integer | CCL | 0% | 2 | 1, 0, 1, 0 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | SDN |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Sudan |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 4 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 3 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 99.9653 |
gns_non_roman_name_count |
gns_non_roman_name_count | integer | CCL | 0% | 1 | 198 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
gns_name_count |
gns_name_count | integer | 0% | 1 | 37413 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 26221 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 37400 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 13 |
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_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 306 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 47 |
gns_name_count_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 13098 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 9534 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 1332 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 1011 |
gns_name_count_populated_places |
gns_name_count_populated_places | integer | 0% | 1 | 11159 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 7470 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 10384 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 7477 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 961 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 552 |
gns_name_count_transportation_networks |
gns_name_count_transportation_networks | integer | 0% | 1 | 87 |
gns_feature_count_transportation_networks |
gns_feature_count_transportation_networks | integer | 0% | 1 | 48 |
gns_name_count_vegetation |
gns_name_count_vegetation | integer | 0% | 1 | 86 |
gns_feature_count_vegetation |
gns_feature_count_vegetation | integer | 0% | 1 | 82 |
| 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 | SDN |
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 | 160 |
oc_anti_money_laundering_2023 |
oc_anti_money_laundering_2023 | float | 0% | 1 | 3.5 |
oc_anti_money_laundering_2021 |
oc_anti_money_laundering_2021 | integer | 0% | 1 | 4 |
oc_anti_money_laundering_2019 |
oc_anti_money_laundering_2019 | integer | 0% | 1 | 4 |
oc_arms_trafficking_rank |
oc_arms_trafficking_rank | integer | 0% | 1 | 1 |
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_arms_trafficking_2019 |
oc_arms_trafficking_2019 | integer | 0% | 1 | 9 |
oc_cannabis_trade_rank |
oc_cannabis_trade_rank | integer | 0% | 1 | 30 |
oc_cannabis_trade_2023 |
oc_cannabis_trade_2023 | float | 0% | 1 | 7.5 |
oc_cannabis_trade_2021 |
oc_cannabis_trade_2021 | integer | 0% | 1 | 8 |
oc_cannabis_trade_2019 |
oc_cannabis_trade_2019 | float | 0% | 1 | 8.5 |
oc_cocaine_trade_rank |
oc_cocaine_trade_rank | integer | 0% | 1 | 178 |
oc_cocaine_trade_2023 |
oc_cocaine_trade_2023 | float | 0% | 1 | 2.5 |
oc_cocaine_trade_2021 |
oc_cocaine_trade_2021 | float | 0% | 1 | 2.5 |
oc_cocaine_trade_2019 |
oc_cocaine_trade_2019 | float | 0% | 1 | 2.5 |
oc_criminal_actors_rank |
oc_criminal_actors_rank | integer | 0% | 1 | 11 |
oc_criminal_actors_2023 |
oc_criminal_actors_2023 | float | 0% | 1 | 7.5 |
oc_criminal_actors_2021 |
oc_criminal_actors_2021 | float | 0% | 1 | 7.38 |
oc_criminal_actors_2019 |
oc_criminal_actors_2019 | integer | 0% | 1 | 7 |
oc_criminal_markets_rank |
oc_criminal_markets_rank | integer | 0% | 1 | 54 |
oc_criminal_markets_2023 |
oc_criminal_markets_2023 | float | 0% | 1 | 5.23 |
oc_criminal_markets_2021 |
oc_criminal_markets_2021 | float | 0% | 1 | 5.55 |
oc_criminal_markets_2019 |
oc_criminal_markets_2019 | float | 0% | 1 | 5.75 |
oc_criminal_networks_rank |
oc_criminal_networks_rank | integer | 0% | 1 | 57 |
| +103 more pending fields — download the CSV/Parquet to see them all. | |||||
Which languages name the landscape here, and in which writing systems. A language's toponymic footprint and its speaker population are different measures and often diverge. Counts include variant and foreign-language renderings of the same place, so a language can rank high because outside sources record names in it rather than because it is spoken locally — and a widely spoken language can be almost absent where official naming is in another language.
| Language | Place names | Share | Script |
|---|---|---|---|
| Arabic (ara) | 13,397 | 91.0% | Arabic |
| English (eng) | 1,186 | 8.1% | — |
| Russian (rus) | 134 | 0.9% | Cyrillic |
26,221 distinct features ·
4 languages ·
3 scripts ·
198 names in non-Roman script ·
13 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.