| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 1 | MN, MN, MN, MN, MN |
region_name |
Region name | string | SEL | 0% | 92 | Baganuur, Bagaxangai, Bayangol, Bayanzu'rx, Nalaix |
F_TL |
Female population | integer | SEL | 0% | 99 | 14862, 2027, 117823, 174322, 19153 |
M_TL |
Male population | integer | SEL | 0% | 100 | 13925, 2073, 103561, 162610, 17758 |
T_TL |
Total population | integer | SEL | 0% | 100 | 28787, 4100, 221384, 336932, 36911 |
| 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 | 2017, 2017, 2017, 2017, 2017 |
Adm0_en |
Adm0_en | string | 0% | 1 | Mongolia, Mongolia, Mongolia, Mongolia, Mongolia |
Adm0_mn |
Adm0_mn | string | 0% | 1 | монгол, монгол, монгол, монгол, монгол |
Region |
Region | string | 0% | 2 | Eastern region, Eastern region, Eastern region, Eastern... |
ADM1_MN |
ADM1_MN | string | 0% | 7 | Улаанбаатар, Улаанбаатар, Улаанбаатар, Улаанбаатар, Улаанбаатар |
ADM2_MN |
ADM2_MN | string | 0% | 91 | Багануур, Багахангай, Баянгол, Баянзүрх, Налайх |
ADM2_PCODE |
ADM2_PCODE | string | 0% | 100 | MN1101, MN1104, MN1107, MN1110, MN1113 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
pcode |
Admin code | string | SEL | 0% | 22 | MN83, MN82, MN81, MN85, MN84 |
region_name |
Region name | string | SEL | 0% | 22 | Bayan-Olgii, Govi-Altai, Zavkhan, Uvs, Khovd |
T_TL |
Total population | integer | SEL | 0% | 22 | 103003, 56908, 70244, 79857, 88738 |
M_TL |
Male population | integer | SEL | 0% | 22 | 51334, 28559, 35562, 40669, 44601 |
F_TL |
Female population | integer | SEL | 0% | 22 | 51669, 28349, 34681, 39188, 44137 |
| 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 | 2021, 2021, 2021, 2021, 2021 |
ADM0_EN |
ADM0_EN | string | 0% | 1 | Mongolia, Mongolia, Mongolia, Mongolia, Mongolia |
ADM0_MN |
ADM0_MN | string | 0% | 1 | монгол, монгол, монгол, монгол, монгол |
ADM1_MN |
ADM1_MN | string | 0% | 22 | Баян-Өлгий, Говь-Алтай, Завхан, Увс, Ховд |
T_00_04 |
Total population age 0-4 | integer | 0% | 21 | 14626, 6006, 7172, 10135, 11684 |
T_05_09 |
Total population age 5-9 | integer | 0% | 22 | 12155, 6136, 7223, 9386, 9940 |
T_10_14 |
Total population age 10-14 | integer | 0% | 22 | 10038, 5227, 6719, 8092, 8157 |
T_15_19 |
Total population age 15-19 | integer | 0% | 22 | 9565, 4524, 5263, 6859, 7388 |
T_20_24 |
Total population age 20-24 | integer | 0% | 22 | 8850, 5090, 5976, 6897, 8605 |
T_25_29 |
Total population age 25-29 | integer | 0% | 22 | 8504, 4724, 5878, 6208, 7889 |
T_30_34 |
Total population age 30-34 | integer | 0% | 22 | 8013, 4284, 4974, 5632, 6762 |
T_35_39 |
Total population age 35-39 | integer | 0% | 22 | 6623, 4040, 5051, 4976, 5499 |
T_40_44 |
Total population age 40-44 | integer | 0% | 22 | 5769, 3903, 5004, 4742, 5216 |
T_45_49 |
Total population age 45-49 | integer | 0% | 22 | 5233, 3567, 4573, 4615, 4692 |
T_50_54 |
Total population age 50-54 | integer | 0% | 21 | 4257, 3030, 3914, 4219, 3989 |
T_55_59 |
Total population age 55-59 | integer | 0% | 22 | 3489, 2382, 3125, 3276, 3453 |
T_60_64 |
Total population age 60-64 | integer | 0% | 22 | 2528, 1784, 2329, 2117, 2431 |
T_65_69 |
Total population age 65-69 | integer | 0% | 22 | 1383, 905, 1172, 1077, 1291 |
T_70Plus |
T_70Plus | integer | 0% | 22 | 1970, 1307, 1871, 1627, 1743 |
M_00_04 |
Male population age 0-4 | integer | 0% | 22 | 7347, 3008, 3617, 5096, 5880 |
M_05_09 |
Male population age 5-9 | integer | 0% | 22 | 6168, 3199, 3802, 4890, 5185 |
M_10_14 |
Male population age 10-14 | integer | 0% | 20 | 5051, 2716, 3456, 4169, 4234 |
M_15_19 |
Male population age 15-19 | integer | 0% | 22 | 4779, 2314, 2765, 3539, 3765 |
M_20_24 |
Male population age 20-24 | integer | 0% | 22 | 4411, 2679, 3132, 3602, 4376 |
M_25_29 |
Male population age 25-29 | integer | 0% | 22 | 4248, 2372, 3071, 3358, 3996 |
M_30_34 |
Male population age 30-34 | integer | 0% | 22 | 4099, 2239, 2573, 2977, 3439 |
M_35_39 |
Male population age 35-39 | integer | 0% | 22 | 3349, 2058, 2539, 2579, 2825 |
M_40_44 |
Male population age 40-44 | integer | 0% | 22 | 2921, 1966, 2518, 2412, 2621 |
M_45_49 |
Male population age 45-49 | integer | 0% | 22 | 2513, 1807, 2335, 2304, 2299 |
| +20 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 | MNG, MNG, MNG, MNG, MNG |
region_code |
Admin code | string | SEL | 100% | - | - |
region_name |
Admin name | string | SEL | 0% | 6 | Total, Central (Dornogovi, Dundgovi, Umnugovi, Selenge,... |
human_development_index |
Human development index | float | SEL | 0% | 83 | 0.592, 0.588, 0.569, 0.555, 0.656 |
health_index |
Health index | float | SEL | 0% | 73 | 0.597, 0.63, 0.602, 0.593, 0.639 |
education_index |
Education index | float | SEL | 0% | 90 | 0.563, 0.53, 0.517, 0.52, 0.63 |
income_index |
Income index | float | SEL | 0% | 85 | 0.617, 0.61, 0.591, 0.553, 0.703 |
life_expectancy |
Life expectancy | float | SEL | 0% | 98 | 58.82, 60.93, 59.11, 58.54, 61.55 |
mean_years_schooling |
Mean years schooling | float | SEL | 0% | 99 | 8.442, 8.13, 7.854, 7.65, 9.634 |
| 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 | MN, MN, MN, MN, MN |
population_count |
Population count | float | SEL | 2% | 65 | 977595.0, 1009284.0, 1041444.0, 1071362.0, 1100234.0 |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 44.5310487804878, 45.3926829268293, 46.2474146341463,... |
gdp_per_capita_usd |
Gdp per capita usd | float | SEL | 32% | 45 | 1235.14422497627, 1325.46680536613, 1429.62551800828,... |
literacy_rate_pct |
Literacy rate percent | float | SEL | 88% | 8 | 97.7699966430664, 98.2600021362305, 96.9000015258789,... |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 30% | 46 | 173.4, 167.0, 160.9, 155.3, 149.8 |
poverty_headcount_pct |
Poverty headcount percent | float | SEL | 88% | 8 | 38.8, 33.7, 27.4, 21.6, 29.6 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Mongolia, Mongolia, Mongolia, Mongolia, Mongolia |
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 | MN, MN, MN, MN, MN |
life_expectancy |
Life expectancy | float | SEL | 3% | 64 | 44.5310487804878, 45.3926829268293, 46.2474146341463,... |
infant_mortality_per_1000 |
Infant mortality per 1000 | float | SEL | 42% | 34 | 29.7, 29.5, 29.4, 29.4, 29.3 |
under5_mortality_per_1000 |
Under5 mortality per 1000 | float | SEL | 30% | 46 | 173.4, 167.0, 160.9, 155.3, 149.8 |
maternal_mortality_per_100k |
Maternal mortality per 100k | float | SEL | 41% | 34 | 352.0, 346.0, 341.0, 335.0, 311.0 |
fertility_rate |
Fertility rate | float | SEL | 3% | 46 | 6.817, 6.963, 7.098, 7.238, 7.329 |
birth_rate_per_1000 |
Birth rate per 1000 | float | SEL | 3% | 64 | 44.129, 44.177, 44.118, 44.158, 43.989 |
death_rate_per_1000 |
Death rate per 1000 | float | SEL | 3% | 60 | 22.928, 22.506, 22.072, 21.624, 20.979 |
physicians_per_1000 |
Physicians per 1000 | float | SEL | 53% | 31 | 0.91, 1.378, 1.729, 2.538, 2.695 |
hospital_beds_per_1000 |
Hospital beds per 1000 | float | SEL | 56% | 28 | 8.681960105896, 9.49520015716553, 11.1971998214722,... |
vaccination_rate_pct |
Vaccination rate percent | float | SEL | 32% | 17 | 76.0, 78.0, 79.0, 79.0, 77.0 |
health_expenditure_pct_gdp |
Health expenditure percent gdp | float | SEL | 64% | 24 | 6.07605076, 5.4423995, 5.49190998, 4.29768944, 4.30204487 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Mongolia, Mongolia, Mongolia, Mongolia, Mongolia |
year |
year | integer | 0% | 66 | 1960, 1961, 1962, 1963, 1964 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_of_origin_iso |
Country of origin iso | string | CCL | 0% | 1 | -, -, -, -, - |
refugees |
Refugees | integer | CCL | 0% | 75 | 2116011, 1952928, 1847304, 1749628, 1717966 |
idps |
Idps | integer | CCL | 0% | 34 | 0, 0, 0, 0, 0 |
stateless |
Stateless | integer | CCL | 0% | 23 | 0, 0, 0, 0, 0 |
others_of_concern |
Others of concern | integer | CCL | 0% | 30 | 0, 0, 0, 0, 0 |
total_population |
Total population | string | CCL | 100% | - | - |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
year |
year | integer | 0% | 75 | 1951, 1952, 1953, 1954, 1955 |
country_of_origin |
country_of_origin | string | 100% | - | - |
country_of_asylum |
country_of_asylum | string | 100% | - | - |
country_of_asylum_iso |
country_of_asylum_iso | string | 0% | 1 | -, -, -, -, - |
population_type |
population_type | string | 100% | - | - |
asylum_seekers |
asylum_seekers | integer | 0% | 34 | 0, 0, 0, 0, 0 |
female_total |
female_total | string | 100% | - | - |
male_total |
male_total | string | 100% | - | - |
female_0_4 |
female_0_4 | string | 100% | - | - |
female_5_11 |
female_5_11 | string | 100% | - | - |
female_12_17 |
female_12_17 | string | 100% | - | - |
female_18_59 |
female_18_59 | string | 100% | - | - |
female_60_plus |
female_60_plus | string | 100% | - | - |
male_0_4 |
male_0_4 | string | 100% | - | - |
male_5_11 |
male_5_11 | string | 100% | - | - |
male_12_17 |
male_12_17 | string | 100% | - | - |
male_18_59 |
male_18_59 | string | 100% | - | - |
male_60_plus |
male_60_plus | string | 100% | - | - |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MNG |
admin_level |
Admin level | string | SEL | 0% | 1 | admin_0 |
admin_name |
Admin name | string | SEL | 0% | 1 | Mongolia |
admin_code |
Admin code | string | SEL | 0% | 1 | 74336971B39832911189143 |
area_sqkm |
Area sqkm | float | SEL | 0% | 1 | 1565200.1921 |
pop_2024 |
Population count | integer | SEL | 0% | 1 | 3281522 |
pop_density_2024 |
Population density | float | SEL | 0% | 1 | 2.1 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MNG, MNG, MNG, MNG, MNG |
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% | 22 | Ulaanbaatar, Hovsgel, Övörkhangai, Selenge, Bayan-Ölgii |
admin_code |
Admin code | string | SEL | 0% | 22 | 14279143B69842940795179, 14279143B20985490361275,... |
area_sqkm |
Area sqkm | float | SEL | 0% | 22 | 4759.596, 102116.9302, 63000.1987, 41938.2943, 46101.8865 |
pop_2024 |
Population count | integer | SEL | 0% | 22 | 1494861, 138724, 118137, 110365, 108228 |
pop_density_2024 |
Population density | float | SEL | 0% | 20 | 314.07, 1.36, 1.88, 2.63, 2.35 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MNG, MNG |
admin_level |
Admin level | string | SEL | 0% | 1 | locality, locality |
admin_name |
Admin name | string | SEL | 0% | 2 | Ulaanbaatar, Erdenet |
admin_code |
Admin code | integer | SEL | 0% | 2 | 337, 168 |
area_sqkm |
Area sqkm | float | SEL | 0% | 2 | 235.1575, 18.0171 |
pop_2024 |
Population count | integer | SEL | 0% | 2 | 970038, 65297 |
pop_density_2024 |
Population density | float | SEL | 0% | 2 | 4125.06, 3624.17 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
ghs_pop_2025 |
ghs_pop_2025 | integer | 0% | 2 | 1634097, 97743 |
landscan_vs_ghs_ratio |
landscan_vs_ghs_ratio | float | 0% | 2 | 0.594, 0.668 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
admin_code |
Admin code | string | SEL | 0% | 1 | MNG |
admin_name |
Admin name | string | SEL | 0% | 1 | Mongolia |
population_count |
Population count | integer | SEL | 0% | 1 | 3572835 |
household_count |
Household count | integer | SEL | 0% | 1 | 1011078 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
admin_level | string | 0% | 1 | admin_0 |
year |
year | integer | 0% | 1 | 2025 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
admin_code |
Admin code | string | SEL | 0% | 22 | bayan_ulgii, govi_altai, zavkhan, uvs, khovd |
admin_name |
Admin name | string | SEL | 0% | 22 | Bayan-Ulgii, Govi-Altai, Zavkhan, Uvs, Khovd |
population_count |
Population count | integer | SEL | 0% | 22 | 119138, 56752, 70926, 85245, 93094 |
household_count |
Household count | integer | SEL | 0% | 22 | 26382, 16359, 21586, 22805, 24294 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
admin_level |
admin_level | string | 0% | 1 | admin_1, admin_1, admin_1, admin_1, admin_1 |
year |
year | integer | 0% | 1 | 2025, 2025, 2025, 2025, 2025 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
glottocode |
Glottocode | string | CCL | 0% | 19 | chin1476, daur1238, even1259, halh1238, kalm1243 |
name |
Name | string | CCL | 0% | 19 | China Buriat, Dagur, Evenki, Halh Mongolian, Oirad-Kalmyk-Darkhat |
iso639_3 |
Iso639 3 | string | CCL | 5% | 18 | bxu, dta, evn, khk, xal |
level |
Level | string | CCL | 0% | 1 | language, language, language, language, language |
family_name |
Family name | string | CCL | 100% | - | - |
family_glottocode |
Family glottocode | string | CCL | 0% | 8 | mong1349, mong1349, tung1282, mong1349, mong1349 |
parent_name |
Parent name | string | CCL | 100% | - | - |
parent_glottocode |
Parent glottocode | string | CCL | 0% | 14 | buri1258, mong1329, nort3147, mong1331, mong1331 |
endangerment_status |
Endangerment status | string | CCL | 100% | - | - |
country_codes |
Country codes | string | SEL+ | 0% | 10 | ['CN', 'MN', 'RU'], ['CN', 'KZ', 'MN'], ['CN', 'MN',... |
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% | 13 | 1, 8, 24, 5, 21 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
latitude |
latitude | float | 0% | 19 | 48.7593, 48.0, 61.972, 48.32397, 46.566667 |
longitude |
longitude | float | 0% | 19 | 117.786, 124.0, 94.689, 106.28874, 45.316667 |
classification |
classification | string | 0% | 1 | [], [], [], [], [] |
| 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 | 15.0 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric |
Mobile subscriptions per 100 | float | SEL | 0% | 1 | 142.0 |
internet_country_code_text |
Internet country code text | string | SEL+ | 0% | 1 | .mn |
internet_users_percent_of_population_numeric |
Internet penetration percent | float | SEL | 0% | 1 | 83.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric |
Broadband subscriptions per 100 | float | SEL | 0% | 1 | 15.0 |
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
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 | 524,000 (2023 est.) |
telephones_fixed_lines_total_subscriptions_numeric |
telephones_fixed_lines_total_subscriptions_numeric | float | 0% | 1 | 524000.0 |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text |
telephones_fixed_lines_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 15 (2023 est.) |
telephones_mobile_cellular_total_subscriptions_text |
telephones_mobile_cellular_total_subscriptions_text | string | 0% | 1 | 4.84 million (2023 est.) |
telephones_mobile_cellular_total_subscriptions_numeric |
telephones_mobile_cellular_total_subscriptions_numeric | float | 0% | 1 | 4.84 |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text |
telephones_mobile_cellular_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 142 (2022 est.) |
broadcast_media_text |
broadcast_media_text | string | 0% | 1 | state-run radio and TV provider is now a public-service... |
broadcast_media_numeric |
broadcast_media_numeric | float | 0% | 1 | 68.0 |
internet_users_percent_of_population_text |
internet_users_percent_of_population_text | string | 0% | 1 | 83% (2023 est.) |
broadband_fixed_subscriptions_total_text |
broadband_fixed_subscriptions_total_text | string | 0% | 1 | 499,000 (2023 est.) |
broadband_fixed_subscriptions_total_numeric |
broadband_fixed_subscriptions_total_numeric | float | 0% | 1 | 499000.0 |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text |
broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text | string | 0% | 1 | 15 (2023 est.) |
source_section |
source_section | string | 0% | 1 | Communications |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/mg.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 | 16800.0 |
gdp_official_exchange_rate_numeric |
Gdp total usd | float | SEL | 0% | 1 | 23.586 |
population_below_poverty_line_numeric |
Poverty headcount percent | float | SEL | 0% | 1 | 27.1 |
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
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 | lower middle-income East Asian economy; large human... |
economic_overview_numeric |
economic_overview_numeric | float | 0% | 1 | 3.0 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text |
Real gdp purchasing power parity 2024 (text) | string | 0% | 1 | $59.221 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 | 59.221 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text |
Real gdp purchasing power parity 2023 (text) | string | 0% | 1 | $56.474 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 | 56.474 |
real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text |
Real gdp purchasing power parity 2022 (text) | string | 0% | 1 | $52.572 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 | 52.572 |
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 | 4.9% (2024 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric |
Real gdp growth rate 2024 (numeric) | float | 0% | 1 | 4.9 |
real_gdp_growth_rate_real_gdp_growth_rate_2023_text |
Real gdp growth rate 2023 (text) | string | 0% | 1 | 7.4% (2023 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric |
Real gdp growth rate 2023 (numeric) | float | 0% | 1 | 7.4 |
real_gdp_growth_rate_real_gdp_growth_rate_2022_text |
Real gdp growth rate 2022 (text) | string | 0% | 1 | 5% (2022 est.) |
real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric |
Real gdp growth rate 2022 (numeric) | float | 0% | 1 | 5.0 |
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 | $16,800 (2024 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_text |
Real gdp per capita 2023 (text) | string | 0% | 1 | $16,200 (2023 est.) |
real_gdp_per_capita_real_gdp_per_capita_2023_numeric |
Real gdp per capita 2023 (numeric) | float | 0% | 1 | 16200.0 |
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 | $23.586 billion (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text |
Inflation rate consumer prices 2024 (text) | string | 0% | 1 | 6.8% (2024 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric |
Inflation rate consumer prices 2024 (numeric) | float | 0% | 1 | 6.8 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text |
Inflation rate consumer prices 2023 (text) | string | 0% | 1 | 10.3% (2023 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric |
Inflation rate consumer prices 2023 (numeric) | float | 0% | 1 | 10.3 |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text |
Inflation rate consumer prices 2022 (text) | string | 0% | 1 | 15.1% (2022 est.) |
inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric |
Inflation rate consumer prices 2022 (numeric) | float | 0% | 1 | 15.1 |
inflation_rate_consumer_prices_note |
inflation_rate_consumer_prices_note | string | 0% | 1 | note: annual % change based on consumer prices |
| +119 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
electricity_access_electrification_total_population_numeric |
Electricity access percent | float | SEL | 0% | 1 | 100.0 |
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
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 | 1.51 million kW (2023 est.) |
electricity_installed_generating_capacity_numeric |
electricity_installed_generating_capacity_numeric | float | 0% | 1 | 1.51 |
electricity_consumption_text |
electricity_consumption_text | string | 0% | 1 | 8.997 billion kWh (2023 est.) |
electricity_consumption_numeric |
electricity_consumption_numeric | float | 0% | 1 | 8.997 |
electricity_exports_text |
electricity_exports_text | string | 0% | 1 | 24 million kWh (2023 est.) |
electricity_exports_numeric |
electricity_exports_numeric | float | 0% | 1 | 24.0 |
electricity_imports_text |
electricity_imports_text | string | 0% | 1 | 2.224 billion kWh (2023 est.) |
electricity_imports_numeric |
electricity_imports_numeric | float | 0% | 1 | 2.224 |
electricity_transmission_distribution_losses_text |
electricity_transmission_distribution_losses_text | string | 0% | 1 | 1.113 billion kWh (2023 est.) |
electricity_transmission_distribution_losses_numeric |
electricity_transmission_distribution_losses_numeric | float | 0% | 1 | 1.113 |
electricity_generation_sources_fossil_fuels_text |
electricity_generation_sources_fossil_fuels_text | string | 0% | 1 | 90.4% of total installed capacity (2023 est.) |
electricity_generation_sources_fossil_fuels_numeric |
electricity_generation_sources_fossil_fuels_numeric | float | 0% | 1 | 90.4 |
electricity_generation_sources_solar_text |
electricity_generation_sources_solar_text | string | 0% | 1 | 2.4% of total installed capacity (2023 est.) |
electricity_generation_sources_solar_numeric |
electricity_generation_sources_solar_numeric | float | 0% | 1 | 2.4 |
electricity_generation_sources_wind_text |
electricity_generation_sources_wind_text | string | 0% | 1 | 6.4% of total installed capacity (2023 est.) |
electricity_generation_sources_wind_numeric |
electricity_generation_sources_wind_numeric | float | 0% | 1 | 6.4 |
electricity_generation_sources_hydroelectricity_text |
electricity_generation_sources_hydroelectricity_text | string | 0% | 1 | 0.8% of total installed capacity (2023 est.) |
electricity_generation_sources_hydroelectricity_numeric |
electricity_generation_sources_hydroelectricity_numeric | float | 0% | 1 | 0.8 |
coal_production_text |
coal_production_text | string | 0% | 1 | 64.824 million metric tons (2023 est.) |
coal_production_numeric |
coal_production_numeric | float | 0% | 1 | 64.824 |
coal_consumption_text |
coal_consumption_text | string | 0% | 1 | 8.941 million metric tons (2023 est.) |
coal_consumption_numeric |
coal_consumption_numeric | float | 0% | 1 | 8.941 |
coal_exports_text |
coal_exports_text | string | 0% | 1 | 55.884 million metric tons (2023 est.) |
coal_exports_numeric |
coal_exports_numeric | float | 0% | 1 | 55.884 |
coal_imports_text |
coal_imports_text | string | 0% | 1 | 900 metric tons (2023 est.) |
coal_imports_numeric |
coal_imports_numeric | float | 0% | 1 | 900.0 |
coal_proven_reserves_text |
coal_proven_reserves_text | string | 0% | 1 | 2.52 billion metric tons (2023 est.) |
coal_proven_reserves_numeric |
coal_proven_reserves_numeric | float | 0% | 1 | 2.52 |
petroleum_total_petroleum_production_text |
petroleum_total_petroleum_production_text | string | 0% | 1 | 15,000 bbl/day (2023 est.) |
| +7 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 69.0 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 9.1 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 69.1 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 1.4 |
waste_and_recycling_municipal_solid_waste_generated_annually_numeric |
Municipal waste kg per capita | float | SEL | 0% | 1 | 2.9 |
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
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 | limited natural freshwater resources in some areas; air... |
international_environmental_agreements_party_to_text |
international_environmental_agreements_party_to_text | string | 0% | 1 | Antarctic Treaty, Biodiversity, Climate Change, Climate... |
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 | desert; continental (large daily and seasonal temperature ranges) |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 69% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 0.7% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 0.7 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.0 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 68.2% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 68.2 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 9.1% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 21.9% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 21.9 |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 69.1% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 1.4% annual rate of change (2020-25 est.) |
carbon_dioxide_emissions_total_emissions_text |
carbon_dioxide_emissions_total_emissions_text | string | 0% | 1 | 19.203 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_total_emissions_numeric |
carbon_dioxide_emissions_total_emissions_numeric | float | 0% | 1 | 19.203 |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text | string | 0% | 1 | 13.489 million metric tonnes of CO2 (2023 est.) |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_numeric |
carbon_dioxide_emissions_from_coal_and_metallurgical_coke_numeric | float | 0% | 1 | 13.489 |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text |
carbon_dioxide_emissions_from_petroleum_and_other_liquids_text | string | 0% | 1 | 5.714 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 | 5.714 |
particulate_matter_emissions_text |
particulate_matter_emissions_text | string | 0% | 1 | 41.3 micrograms per cubic meter (2019 est.) |
particulate_matter_emissions_numeric |
particulate_matter_emissions_numeric | float | 0% | 1 | 41.3 |
methane_emissions_energy_text |
methane_emissions_energy_text | string | 0% | 1 | 532.2 kt (2022-2024 est.) |
methane_emissions_energy_numeric |
methane_emissions_energy_numeric | float | 0% | 1 | 532.2 |
methane_emissions_agriculture_text |
methane_emissions_agriculture_text | string | 0% | 1 | 525.2 kt (2019-2021 est.) |
methane_emissions_agriculture_numeric |
methane_emissions_agriculture_numeric | float | 0% | 1 | 525.2 |
methane_emissions_waste_text |
methane_emissions_waste_text | string | 0% | 1 | 14.2 kt (2019-2021 est.) |
methane_emissions_waste_numeric |
methane_emissions_waste_numeric | float | 0% | 1 | 14.2 |
| +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 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
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 | Mongolian(s) |
nationality_adjective_text |
nationality_adjective_text | string | 0% | 1 | Mongolian |
ethnic_groups_text |
ethnic_groups_text | string | 0% | 1 | Khalkh 83.8%, Kazak 3.8%, Durvud 2.6%, Bayad 2%, Buriad... |
ethnic_groups_numeric |
ethnic_groups_numeric | float | 0% | 1 | 83.8 |
source_section |
source_section | string | 0% | 1 | People and Society:ethnic_groups |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/mg.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
area_total_numeric |
Area sqkm | float | SEL | 0% | 1 | 1564116.0 |
area_land_numeric |
Area land sqkm | float | SEL | 0% | 1 | 1553556.0 |
area_water_numeric |
Area water sqkm | float | SEL | 0% | 1 | 10560.0 |
land_boundaries_total_numeric |
Land boundary km | float | SEL | 0% | 1 | 8082.0 |
coastline_numeric |
Coastline km | float | SEL | 0% | 1 | 0.0 |
elevation_highest_point_numeric |
Elevation max m | float | SEL | 0% | 1 | 4374.0 |
elevation_lowest_point_numeric |
Elevation min m | float | SEL | 0% | 1 | 560.0 |
land_use_agricultural_land_numeric |
Agricultural land percent | float | SEL | 0% | 1 | 69.0 |
land_use_forest_numeric |
Forest area percent | float | SEL | 0% | 1 | 9.1 |
irrigated_land_numeric |
Irrigated land sqkm | float | SEL | 0% | 1 | 796.0 |
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
location_text |
location_text | string | 0% | 1 | Northern Asia, between China and Russia |
geographic_coordinates_text |
geographic_coordinates_text | string | 0% | 1 | 46 00 N, 105 00 E |
geographic_coordinates_numeric |
geographic_coordinates_numeric | float | 0% | 1 | 46.0 |
map_references_text |
map_references_text | string | 0% | 1 | Asia |
area_total_text |
area_total_text | string | 0% | 1 | 1,564,116 sq km |
area_land_text |
area_land_text | string | 0% | 1 | 1,553,556 sq km |
area_water_text |
area_water_text | string | 0% | 1 | 10,560 sq km |
area_comparative_text |
area_comparative_text | string | 0% | 1 | slightly smaller than Alaska; more than twice the size of Texas |
land_boundaries_total_text |
land_boundaries_total_text | string | 0% | 1 | 8,082 km |
land_boundaries_border_countries_text |
land_boundaries_border_countries_text | string | 0% | 1 | China 4,630 km; Russia 3,452 km |
land_boundaries_border_countries_numeric |
land_boundaries_border_countries_numeric | float | 0% | 1 | 4630.0 |
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 | desert; continental (large daily and seasonal temperature ranges) |
terrain_text |
terrain_text | string | 0% | 1 | vast semidesert and desert plains, grassy steppe,... |
elevation_highest_point_text |
elevation_highest_point_text | string | 0% | 1 | Nayramadlin Orgil (Khuiten Peak) 4,374 m |
elevation_lowest_point_text |
elevation_lowest_point_text | string | 0% | 1 | Hoh Nuur 560 m |
elevation_mean_elevation_text |
elevation_mean_elevation_text | string | 0% | 1 | 1,528 m |
elevation_mean_elevation_numeric |
elevation_mean_elevation_numeric | float | 0% | 1 | 1528.0 |
natural_resources_text |
natural_resources_text | string | 0% | 1 | oil, coal, copper, molybdenum, tungsten, phosphates,... |
land_use_agricultural_land_text |
land_use_agricultural_land_text | string | 0% | 1 | 69% (2023 est.) |
land_use_agricultural_land_arable_land_text |
land_use_agricultural_land_arable_land_text | string | 0% | 1 | arable land: 0.7% (2023 est.) |
land_use_agricultural_land_arable_land_numeric |
land_use_agricultural_land_arable_land_numeric | float | 0% | 1 | 0.7 |
land_use_agricultural_land_permanent_crops_text |
land_use_agricultural_land_permanent_crops_text | string | 0% | 1 | permanent crops: 0% (2023 est.) |
land_use_agricultural_land_permanent_crops_numeric |
land_use_agricultural_land_permanent_crops_numeric | float | 0% | 1 | 0.0 |
land_use_agricultural_land_permanent_pasture_text |
land_use_agricultural_land_permanent_pasture_text | string | 0% | 1 | permanent pasture: 68.2% (2023 est.) |
land_use_agricultural_land_permanent_pasture_numeric |
land_use_agricultural_land_permanent_pasture_numeric | float | 0% | 1 | 68.2 |
land_use_forest_text |
land_use_forest_text | string | 0% | 1 | 9.1% (2023 est.) |
land_use_other_text |
land_use_other_text | string | 0% | 1 | 21.9% (2023 est.) |
land_use_other_numeric |
land_use_other_numeric | float | 0% | 1 | 21.9 |
| +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 | MNG |
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 | none |
country_name_conventional_short_form_text |
country_name_conventional_short_form_text | string | 0% | 1 | Mongolia |
country_name_local_long_form_text |
country_name_local_long_form_text | string | 0% | 1 | none |
country_name_local_short_form_text |
country_name_local_short_form_text | string | 0% | 1 | Mongol Uls |
country_name_former_text |
country_name_former_text | string | 0% | 1 | Outer Mongolia, Mongolian People's Republic |
country_name_etymology_text |
country_name_etymology_text | string | 0% | 1 | name comes from the Mongol people, whose name derives... |
government_type_text |
government_type_text | string | 0% | 1 | semi-presidential republic |
capital_name_text |
capital_name_text | string | 0% | 1 | Ulaanbaatar |
capital_geographic_coordinates_text |
capital_geographic_coordinates_text | string | 0% | 1 | 47 55 N, 106 55 E |
capital_geographic_coordinates_numeric |
capital_geographic_coordinates_numeric | float | 0% | 1 | 47.0 |
capital_time_difference_text |
capital_time_difference_text | string | 0% | 1 | UTC+8 (13 hours ahead of Washington, DC, during Standard Time) |
capital_time_difference_numeric |
capital_time_difference_numeric | float | 0% | 1 | 8.0 |
capital_daylight_saving_time_text |
capital_daylight_saving_time_text | string | 0% | 1 | +1hr, begins last Saturday in March; ends last Saturday... |
capital_daylight_saving_time_numeric |
capital_daylight_saving_time_numeric | float | 0% | 1 | 1.0 |
capital_time_zone_note_text |
capital_time_zone_note_text | string | 0% | 1 | Mongolia has two time zones - Ulaanbaatar Time (8 hours... |
capital_time_zone_note_numeric |
capital_time_zone_note_numeric | float | 0% | 1 | 8.0 |
capital_etymology_text |
capital_etymology_text | string | 0% | 1 | the name means "red hero" in Mongolian and honors... |
capital_etymology_numeric |
capital_etymology_numeric | float | 0% | 1 | 1920.0 |
administrative_divisions_text |
administrative_divisions_text | string | 0% | 1 | 21 provinces (aymguud, singular - aymag) and 1... |
administrative_divisions_numeric |
administrative_divisions_numeric | float | 0% | 1 | 21.0 |
legal_system_text |
legal_system_text | string | 0% | 1 | civil law system influenced by Soviet and... |
constitution_history_text |
constitution_history_text | string | 0% | 1 | several previous; latest adopted 13 January 1992,... |
constitution_history_numeric |
constitution_history_numeric | float | 0% | 1 | 13.0 |
constitution_amendment_process_text |
constitution_amendment_process_text | string | 0% | 1 | proposed by the State Great Hural, by the president of... |
international_law_organization_participation_text |
international_law_organization_participation_text | string | 0% | 1 | has not submitted an ICJ jurisdiction declaration;... |
citizenship_citizenship_by_birth_text |
Citizenship by birth (text) | string | 0% | 1 | no |
citizenship_citizenship_by_descent_only_text |
Citizenship by descent only (text) | string | 0% | 1 | both parents must be citizens of Mongolia; one parent if... |
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 | 5 years |
citizenship_residency_requirement_for_naturalization_numeric |
citizenship_residency_requirement_for_naturalization_numeric | float | 0% | 1 | 5.0 |
| +77 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 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
background_text |
background_text | string | 0% | 1 | The peoples of Mongolia have a long history under a... |
background_numeric |
background_numeric | float | 0% | 1 | 4.0 |
source_section |
source_section | string | 0% | 1 | Introduction |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/mg.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
languages_languages_text |
Languages (text) | string | 0% | 1 | Mongolian 90% (official, Khalkha dialect is... |
languages_languages_numeric |
Languages (numeric) | float | 0% | 1 | 90.0 |
languages_major_language_sample_s_text |
languages_major_language_sample_s_text | string | 0% | 1 | Дэлхийн баримтат ном, үндсэн мэдээллийн зайлшгүй эх... |
source_section |
source_section | string | 0% | 1 | People and Society:languages |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/mg.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
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 | 26 (2024 est.) |
refugees_and_internally_displaced_persons_refugees_numeric |
refugees_and_internally_displaced_persons_refugees_numeric | float | 0% | 1 | 26.0 |
refugees_and_internally_displaced_persons_idps_text |
refugees_and_internally_displaced_persons_idps_text | string | 0% | 1 | 22 (2024 est.) |
refugees_and_internally_displaced_persons_idps_numeric |
refugees_and_internally_displaced_persons_idps_numeric | float | 0% | 1 | 22.0 |
refugees_and_internally_displaced_persons_stateless_persons_text |
refugees_and_internally_displaced_persons_stateless_persons_text | string | 0% | 1 | 17 (2024 est.) |
refugees_and_internally_displaced_persons_stateless_persons_numeric |
refugees_and_internally_displaced_persons_stateless_persons_numeric | float | 0% | 1 | 17.0 |
source_section |
source_section | string | 0% | 1 | Transnational Issues:migration |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/mg.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
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 | Mongolian Armed Forces (MAF): Land Force, Air Force,... |
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 | 0.7% of GDP (2024 est.) |
military_expenditures_military_expenditures_2024_numeric |
Military expenditures 2024 (numeric) | float | 0% | 1 | 0.7 |
military_expenditures_military_expenditures_2023_text |
Military expenditures 2023 (text) | string | 0% | 1 | 0.6% of GDP (2023 est.) |
military_expenditures_military_expenditures_2023_numeric |
Military expenditures 2023 (numeric) | float | 0% | 1 | 0.6 |
military_expenditures_military_expenditures_2022_text |
Military expenditures 2022 (text) | string | 0% | 1 | 0.6% of GDP (2022 est.) |
military_expenditures_military_expenditures_2022_numeric |
Military expenditures 2022 (numeric) | float | 0% | 1 | 0.6 |
military_expenditures_military_expenditures_2021_text |
Military expenditures 2021 (text) | string | 0% | 1 | 0.8% of GDP (2021 est.) |
military_expenditures_military_expenditures_2021_numeric |
Military expenditures 2021 (numeric) | float | 0% | 1 | 0.8 |
military_expenditures_military_expenditures_2020_text |
Military expenditures 2020 (text) | string | 0% | 1 | 0.8% of GDP (2020 est.) |
military_expenditures_military_expenditures_2020_numeric |
Military expenditures 2020 (numeric) | float | 0% | 1 | 0.8 |
military_and_security_service_personnel_strengths_text |
military_and_security_service_personnel_strengths_text | string | 0% | 1 | information varies; estimated 10-20,000 active Mongolian... |
military_and_security_service_personnel_strengths_numeric |
military_and_security_service_personnel_strengths_numeric | float | 0% | 1 | 10.0 |
military_equipment_inventories_and_acquisitions_text |
military_equipment_inventories_and_acquisitions_text | string | 0% | 1 | the MAF's inventory is comprised largely of Soviet-era... |
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_deployments_text |
military_deployments_text | string | 0% | 1 | 850 South Sudan (UNMISS) (2025) |
military_deployments_numeric |
military_deployments_numeric | float | 0% | 1 | 850.0 |
military_note_text |
military_note_text | string | 0% | 1 | the Mongolian Armed Forces (MAF) are responsible for... |
military_note_numeric |
military_note_numeric | float | 0% | 1 | 2005.0 |
source_section |
source_section | string | 0% | 1 | Military and Security |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/mg.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
population_total_numeric |
Population count | float | SEL | 0% | 1 | 3281676.0 |
population_male_numeric |
Population male | float | SEL | 0% | 1 | 1595596.0 |
population_female_numeric |
Population female | float | SEL | 0% | 1 | 1686080.0 |
age_structure_0_14_years_numeric |
Population 0 14 percent | float | SEL | 0% | 1 | 25.7 |
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 | 5.9 |
dependency_ratios_total_dependency_ratio_numeric |
Total dependency ratio | float | SEL | 0% | 1 | 59.1 |
dependency_ratios_youth_dependency_ratio_numeric |
Youth dependency ratio | float | SEL | 0% | 1 | 50.2 |
dependency_ratios_elderly_dependency_ratio_numeric |
Elderly dependency ratio | float | SEL | 0% | 1 | 8.9 |
median_age_total_numeric |
Median age | float | SEL | 0% | 1 | 28.8 |
population_growth_rate_numeric |
Population growth rate percent | float | SEL | 0% | 1 | 1.08 |
birth_rate_numeric |
Birth rate per 1000 | float | SEL | 0% | 1 | 18.01 |
death_rate_numeric |
Death rate per 1000 | float | SEL | 0% | 1 | 5.35 |
net_migration_rate_numeric |
Net migration per 1000 | float | SEL | 0% | 1 | -1.83 |
urbanization_urban_population_numeric |
Urban population percent | float | SEL | 0% | 1 | 69.1 |
urbanization_rate_of_urbanization_numeric |
Urban growth rate percent | float | SEL | 0% | 1 | 1.4 |
sex_ratio_at_birth_numeric |
Sex ratio at birth | float | SEL | 0% | 1 | 1.05 |
sex_ratio_total_population_numeric |
Sex ratio overall | float | SEL | 0% | 1 | 0.95 |
maternal_mortality_ratio_numeric |
Maternal mortality per 100k | float | SEL | 0% | 1 | 41.0 |
infant_mortality_rate_total_numeric |
Infant mortality per 1000 | float | SEL | 0% | 1 | 8.6 |
life_expectancy_at_birth_total_population_numeric |
Life expectancy | float | SEL | 0% | 1 | 71.9 |
total_fertility_rate_numeric |
Fertility rate | float | SEL | 0% | 1 | 2.6 |
gross_reproduction_rate_numeric |
Gross reproduction rate | float | SEL | 0% | 1 | 1.27 |
physician_density_numeric |
Physicians per 1000 | float | SEL | 0% | 1 | 4.13 |
hospital_bed_density_numeric |
Hospital beds per 1000 | float | SEL | 0% | 1 | 10.6 |
literacy_total_population_numeric |
Literacy rate percent | float | SEL | 0% | 1 | 98.6 |
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
population_total_text |
population_total_text | string | 0% | 1 | 3,281,676 (2024 est.) |
population_male_text |
population_male_text | string | 0% | 1 | 1,595,596 |
population_female_text |
population_female_text | string | 0% | 1 | 1,686,080 |
age_structure_0_14_years_text |
age_structure_0_14_years_text | string | 0% | 1 | 25.7% (male 429,867/female 412,943) |
age_structure_15_64_years_text |
age_structure_15_64_years_text | string | 0% | 1 | 68.4% (male 1,087,487/female 1,156,547) |
age_structure_65_years_and_over_text |
age_structure_65_years_and_over_text | string | 0% | 1 | 5.9% (2024 est.) (male 78,242/female 116,590) |
dependency_ratios_total_dependency_ratio_text |
dependency_ratios_total_dependency_ratio_text | string | 0% | 1 | 59.1 (2024 est.) |
dependency_ratios_youth_dependency_ratio_text |
dependency_ratios_youth_dependency_ratio_text | string | 0% | 1 | 50.2 (2024 est.) |
dependency_ratios_elderly_dependency_ratio_text |
dependency_ratios_elderly_dependency_ratio_text | string | 0% | 1 | 8.9 (2024 est.) |
dependency_ratios_potential_support_ratio_text |
dependency_ratios_potential_support_ratio_text | string | 0% | 1 | 11.2 (2024 est.) |
dependency_ratios_potential_support_ratio_numeric |
dependency_ratios_potential_support_ratio_numeric | float | 0% | 1 | 11.2 |
median_age_total_text |
median_age_total_text | string | 0% | 1 | 28.8 years (2025 est.) |
median_age_male_text |
median_age_male_text | string | 0% | 1 | 30.1 years |
median_age_male_numeric |
median_age_male_numeric | float | 0% | 1 | 30.1 |
median_age_female_text |
median_age_female_text | string | 0% | 1 | 32.8 years |
median_age_female_numeric |
median_age_female_numeric | float | 0% | 1 | 32.8 |
population_growth_rate_text |
population_growth_rate_text | string | 0% | 1 | 1.08% (2025 est.) |
birth_rate_text |
birth_rate_text | string | 0% | 1 | 18.01 births/1,000 population (2025 est.) |
death_rate_text |
death_rate_text | string | 0% | 1 | 5.35 deaths/1,000 population (2025 est.) |
net_migration_rate_text |
net_migration_rate_text | string | 0% | 1 | -1.83 migrant(s)/1,000 population (2025 est.) |
population_distribution_text |
population_distribution_text | string | 0% | 1 | population sparsely distributed throughout the country;... |
urbanization_urban_population_text |
urbanization_urban_population_text | string | 0% | 1 | 69.1% of total population (2023) |
urbanization_rate_of_urbanization_text |
urbanization_rate_of_urbanization_text | string | 0% | 1 | 1.4% annual rate of change (2020-25 est.) |
major_urban_areas_population_text |
major_urban_areas_population_text | string | 0% | 1 | 1.673 million ULAANBAATAR (capital) (2023) |
major_urban_areas_population_numeric |
major_urban_areas_population_numeric | float | 0% | 1 | 1.673 |
sex_ratio_at_birth_text |
sex_ratio_at_birth_text | string | 0% | 1 | 1.05 male(s)/female |
sex_ratio_0_14_years_text |
sex_ratio_0_14_years_text | string | 0% | 1 | 1.04 male(s)/female |
sex_ratio_0_14_years_numeric |
sex_ratio_0_14_years_numeric | float | 0% | 1 | 1.04 |
sex_ratio_15_64_years_text |
sex_ratio_15_64_years_text | string | 0% | 1 | 0.94 male(s)/female |
sex_ratio_15_64_years_numeric |
sex_ratio_15_64_years_numeric | float | 0% | 1 | 0.94 |
| +93 more extension fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
composition_religion_buddhist_pct_synth |
Buddhist | numeric | CCL | 0% | - | 51.8 |
composition_religion_muslim_pct_synth |
Muslim | numeric | CCL | 0% | - | 3.2 |
composition_religion_christian_pct_synth |
Christian | numeric | CCL | 0% | - | 1.3 |
composition_religion_other_pct_synth |
Other | numeric | CCL | 0% | - | 0.6 |
composition_ethnicity_primary_label_synth |
Khalkh | string | CCL | 0% | - | Khalkh |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
religions_text |
religions_text | string | 0% | 1 | Buddhist 51.8%, no religion 40.6%, Muslim 3.2%, Shaman... |
religions_numeric |
religions_numeric | float | 0% | 1 | 51.8 |
source_section |
source_section | string | 0% | 1 | People and Society:religions |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/mg.json |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
composition_religion_no_religion_pct_synth |
no religion | numeric | 0% | - | 40.6 |
composition_religion_shaman_pct_synth |
Shaman | numeric | 0% | - | 2.5 |
composition_ethnicity_khalkh_pct_synth |
Khalkh | numeric | 0% | - | 83.8 |
composition_ethnicity_kazak_pct_synth |
Kazak | numeric | 0% | - | 3.8 |
composition_ethnicity_durvud_pct_synth |
Durvud | numeric | 0% | - | 2.6 |
composition_ethnicity_bayad_pct_synth |
Bayad | numeric | 0% | - | 2.0 |
composition_ethnicity_buriad_pct_synth |
Buriad | numeric | 0% | - | 1.4 |
composition_ethnicity_zakhchin_pct_synth |
Zakhchin | numeric | 0% | - | 1.2 |
composition_ethnicity_dariganga_pct_synth |
Dariganga | numeric | 0% | - | 1.1 |
composition_ethnicity_other_pct_synth |
other | numeric | 0% | - | 4.1 |
composition_ethnicity_primary_share_pct_synth |
Khalkh | numeric | 0% | - | 83.8 |
| 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 | JU |
airports_numeric |
Airports count | float | SEL | 0% | 1 | 37.0 |
country_code |
Country code | string | SEL | 0% | 1 | MNG |
country_name |
Country name | string | SEL | 0% | 1 | Mongolia |
admin_level |
Admin level | string | SEL | 0% | 1 | national |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
airports_text |
airports_text | string | 0% | 1 | 37 (2025) |
railways_total_text |
railways_total_text | string | 0% | 1 | 1,815 km (2017) |
railways_total_numeric |
railways_total_numeric | float | 0% | 1 | 1815.0 |
railways_broad_gauge_text |
railways_broad_gauge_text | string | 0% | 1 | 1,815 km (2017) 1.520-m gauge |
railways_broad_gauge_numeric |
railways_broad_gauge_numeric | float | 0% | 1 | 1815.0 |
railways_note |
railways_note | string | 0% | 1 | note: national operator Ulaanbaatar Railway is jointly... |
merchant_marine_total_text |
merchant_marine_total_text | string | 0% | 1 | 318 (2023) |
merchant_marine_total_numeric |
merchant_marine_total_numeric | float | 0% | 1 | 318.0 |
merchant_marine_by_type_text |
merchant_marine_by_type_text | string | 0% | 1 | bulk carrier 8, container ship 8, general cargo 151, oil... |
merchant_marine_by_type_numeric |
merchant_marine_by_type_numeric | float | 0% | 1 | 8.0 |
source_section |
source_section | string | 0% | 1 | Transportation |
source_profile_path |
source_profile_path | string | 0% | 1 | east-n-southeast-asia/mg.json |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | MNG, MNG, MNG, MNG, MNG |
gns_language_code |
gns_language_code | string | CCL | 0% | 6 | mon, rus, zho, eng, uig |
gns_language_name |
gns_language_name | string | CCL | 0% | 6 | Mongolian, Russian, Chinese, English, Uighur |
gns_toponym_count |
gns_toponym_count | integer | CCL | 0% | 6 | 1898, 306, 265, 66, 6 |
gns_toponym_share_pct |
gns_toponym_share_pct | float | CCL | 0% | 6 | 74.6656, 12.0378, 10.4249, 2.5964, 0.236 |
gns_non_roman_toponym_count |
gns_non_roman_toponym_count | integer | CCL | 0% | 5 | 748, 130, 26, 0, 3 |
gns_dominant_script_code |
gns_dominant_script_code | string | CCL | 0% | 4 | Cyrl, Cyrl, Hans, , Arab |
gns_dominant_script_name |
gns_dominant_script_name | string | CCL | 0% | 4 | Cyrillic, Cyrillic, Han (Simplified variant), , Arabic |
gns_script_count |
gns_script_count | integer | CCL | 0% | 3 | 1, 1, 2, 0, 1 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
country_code | string | SEL | 0% | 1 | MNG |
admin_level |
admin_level | integer | SEL | 0% | 1 | 0 |
gns_country_name |
gns_country_name | string | SEL | 0% | 1 | Mongolia |
gns_language_count |
gns_language_count | integer | CCL | 0% | 1 | 6 |
gns_script_count |
gns_script_count | integer | CCL | 0% | 1 | 3 |
gns_endonym_share_pct |
gns_endonym_share_pct | float | CCL | 0% | 1 | 99.9847 |
gns_non_roman_name_count |
gns_non_roman_name_count | integer | CCL | 0% | 1 | 911 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
gns_name_count |
gns_name_count | integer | 0% | 1 | 19650 |
gns_feature_count |
gns_feature_count | integer | 0% | 1 | 6849 |
gns_endonym_count |
gns_endonym_count | integer | 0% | 1 | 19647 |
gns_exonym_count |
gns_exonym_count | integer | 0% | 1 | 3 |
gns_source_build_date |
gns_source_build_date | string | 0% | 1 | Wed, 05 Aug 2026 |
gns_source_change_date |
gns_source_change_date | string | 0% | 1 | 2026-08-05 |
gns_name_count_hydrographic |
gns_name_count_hydrographic | integer | 0% | 1 | 6400 |
gns_feature_count_hydrographic |
gns_feature_count_hydrographic | integer | 0% | 1 | 2457 |
gns_name_count_populated_places |
gns_name_count_populated_places | integer | 0% | 1 | 6211 |
gns_feature_count_populated_places |
gns_feature_count_populated_places | integer | 0% | 1 | 1517 |
gns_name_count_hypsographic |
gns_name_count_hypsographic | integer | 0% | 1 | 4180 |
gns_feature_count_hypsographic |
gns_feature_count_hypsographic | integer | 0% | 1 | 1884 |
gns_name_count_areas_localities |
gns_name_count_areas_localities | integer | 0% | 1 | 377 |
gns_feature_count_areas_localities |
gns_feature_count_areas_localities | integer | 0% | 1 | 176 |
gns_name_count_spot_features |
gns_name_count_spot_features | integer | 0% | 1 | 889 |
gns_feature_count_spot_features |
gns_feature_count_spot_features | integer | 0% | 1 | 452 |
gns_name_count_administrative_regions |
gns_name_count_administrative_regions | integer | 0% | 1 | 1571 |
gns_feature_count_administrative_regions |
gns_feature_count_administrative_regions | integer | 0% | 1 | 350 |
gns_name_count_vegetation |
gns_name_count_vegetation | integer | 0% | 1 | 18 |
gns_feature_count_vegetation |
gns_feature_count_vegetation | integer | 0% | 1 | 11 |
gns_name_count_transportation_networks |
gns_name_count_transportation_networks | integer | 0% | 1 | 4 |
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 | 0% | 1 | MN, MN, MN |
admin_level |
Admin level | integer | SEL | 0% | 1 | 1, 1, 1 |
iso3 |
Country code | string | SEL | 0% | 1 | MNG, MNG, MNG |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
retail |
retail | float | 0% | 2 | 0.0, 0.0, 40.49 |
grocery |
grocery | float | 0% | 2 | 0.0, 0.0, 99.6 |
parks |
parks | float | 0% | 2 | 0.0, 0.0, 44.37 |
transit |
transit | float | 0% | 2 | 0.0, 0.0, 54.82 |
workplaces |
workplaces | float | 0% | 3 | -61.19, -49.71, 27.06 |
residential |
residential | float | 0% | 2 | 0.0, 0.0, 3.48 |
region |
region | string | 0% | 3 | Darkhan-Uul, Orkhon, Ulaanbaatar |
observation_count |
observation_count | integer | 0% | 3 | 26, 49, 974 |
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MNG, MNG |
ethnic_group_name |
Ethnic group name | string | CCL | 0% | 2 | Mongols, Kazakh |
ethnic_power_status |
Ethnic power status | string | CCL | 0% | 2 | DOMINANT, POWERLESS |
ethnic_population_share |
Ethnic population share | float | CCL | 0% | 2 | 0.85, 0.04 |
ethnic_group_id |
Ethnic group id | float | CCL | 0% | 2 | 71203000, 71202000 |
regional_autonomy |
Regional autonomy | string | CCL | 0% | 2 | , true |
| 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 |
|---|---|---|---|---|---|---|
city_name |
Admin name | string | SEL | 0% | 2 | Ulaanbaatar, Erdenet |
country_code |
Country code | string | SEL | 0% | 1 | MNG, MNG |
population |
Population count | integer | SEL | 0% | 2 | 1634097, 97743 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
city_id |
city_id | integer | 0% | 2 | 337, 168 |
name_alternates |
name_alternates | string | 100% | - | - |
country_name |
country_name | string | 0% | 1 | Mongolia, Mongolia |
population_year |
population_year | integer | 0% | 1 | 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 | MNG |
society_id |
Society id | string | CCL | 0% | 1 | Eb3 |
society_name |
Society name | string | CCL | 0% | 1 | Khalka |
language_glottocode |
Language glottocode | string | CCL | 0% | 1 | halh1238 |
language_name |
Language name | string | CCL | 0% | 1 | |
kinship_system |
Kinship system | string | CCL | 0% | 1 | EA001:0; EA002:1; EA003:0; EA004:8; EA005:1 |
marriage_pattern |
Marriage pattern | string | CCL | 0% | 1 | EA006:1; EA007:7; EA008:6; EA009:1; EA010:8 |
subsistence_pattern |
Subsistence pattern | string | CCL | 0% | 1 | EA028:2; EA029:NA; EA030:2; EA031:1; EA032:3 |
political_complexity |
Political complexity | string | CCL | 0% | 1 | EA033:4; EA034:NA; EA035:NA |
religion_importance |
Religion importance | string | CCL | 0% | 1 | EA034:NA; EA112:8 |
residence_pattern |
Residence pattern | string | CCL | 0% | 1 | EA011:1; EA012:8; EA013:2 |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
country_name |
country_name | string | 0% | 1 | Mongolia |
dataset |
dataset | string | 0% | 1 | EA |
region |
region | string | 0% | 1 | |
latitude |
latitude | float | 0% | 1 | 46.0 |
longitude |
longitude | float | 0% | 1 | 97.0 |
assignment_method |
assignment_method | string | 0% | 1 | point_in_polygon |
assignment_confidence |
assignment_confidence | string | 0% | 1 | approximate |
| 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 | MNG |
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 | 75 |
oc_anti_money_laundering_2023 |
oc_anti_money_laundering_2023 | float | 0% | 1 | 4.5 |
oc_anti_money_laundering_2021 |
oc_anti_money_laundering_2021 | integer | 0% | 1 | 4 |
oc_arms_trafficking_rank |
oc_arms_trafficking_rank | integer | 0% | 1 | 148 |
oc_arms_trafficking_2023 |
oc_arms_trafficking_2023 | integer | 0% | 1 | 3 |
oc_arms_trafficking_2021 |
oc_arms_trafficking_2021 | float | 0% | 1 | 3.5 |
oc_cannabis_trade_rank |
oc_cannabis_trade_rank | integer | 0% | 1 | 173 |
oc_cannabis_trade_2023 |
oc_cannabis_trade_2023 | float | 0% | 1 | 3.5 |
oc_cannabis_trade_2021 |
oc_cannabis_trade_2021 | integer | 0% | 1 | 4 |
oc_cocaine_trade_rank |
oc_cocaine_trade_rank | integer | 0% | 1 | 191 |
oc_cocaine_trade_2023 |
oc_cocaine_trade_2023 | integer | 0% | 1 | 2 |
oc_cocaine_trade_2021 |
oc_cocaine_trade_2021 | integer | 0% | 1 | 2 |
oc_criminal_actors_rank |
oc_criminal_actors_rank | integer | 0% | 1 | 142 |
oc_criminal_actors_2023 |
oc_criminal_actors_2023 | float | 0% | 1 | 4.4 |
oc_criminal_actors_2021 |
oc_criminal_actors_2021 | float | 0% | 1 | 4.13 |
oc_criminal_markets_rank |
oc_criminal_markets_rank | integer | 0% | 1 | 152 |
oc_criminal_markets_2023 |
oc_criminal_markets_2023 | float | 0% | 1 | 3.83 |
oc_criminal_markets_2021 |
oc_criminal_markets_2021 | float | 0% | 1 | 3.9 |
oc_criminal_networks_rank |
oc_criminal_networks_rank | integer | 0% | 1 | 143 |
oc_criminal_networks_2023 |
oc_criminal_networks_2023 | float | 0% | 1 | 4.5 |
oc_criminal_networks_2021 |
oc_criminal_networks_2021 | float | 0% | 1 | 4.5 |
oc_criminality_rank |
oc_criminality_rank | integer | 0% | 1 | 153 |
oc_criminality_2023 |
oc_criminality_2023 | float | 0% | 1 | 4.12 |
oc_criminality_2021 |
oc_criminality_2021 | float | 0% | 1 | 4.01 |
oc_cyber_dependent_crimes_rank |
oc_cyber_dependent_crimes_rank | integer | 0% | 1 | 50 |
| +74 more pending fields — download the CSV/Parquet to see them all. | |||||
| Field Name | Label | Type | Schema | Nulls | Unique | Samples |
|---|---|---|---|---|---|---|
country_code |
Country code | string | SEL | 0% | 1 | MNG |
| Field Name | Label | Type | Nulls | Unique | Samples |
|---|---|---|---|---|---|
wave |
wave | integer | 0% | 1 | 7 |
wave_years |
wave_years | string | 0% | 1 | 2017-2022 |
source |
source | string | 0% | 1 | World Values Survey |
importance_religion |
importance_religion | integer | 0% | 1 | 1 |
importance_family |
importance_family | integer | 0% | 1 | 1 |
importance_friends |
importance_friends | integer | 0% | 1 | 1 |
trust_people |
trust_people | integer | 0% | 1 | 1 |
trust_family |
trust_family | integer | 0% | 1 | 1 |
life_satisfaction |
life_satisfaction | integer | 0% | 1 | 1 |
happiness |
happiness | integer | 0% | 1 | 1 |
freedom_choice |
freedom_choice | integer | 0% | 1 | 1 |
gender_jobs_scarce |
gender_jobs_scarce | integer | 0% | 1 | 1 |
gender_political_leaders |
gender_political_leaders | integer | 0% | 1 | 1 |
gender_university |
gender_university | integer | 0% | 1 | 1 |
justifiable_divorce |
justifiable_divorce | integer | 0% | 1 | 1 |
justifiable_homosexuality |
justifiable_homosexuality | integer | 0% | 1 | 1 |
immigration_policy |
immigration_policy | integer | 0% | 1 | 1 |
immigrants_jobs |
immigrants_jobs | integer | 0% | 1 | 1 |
immigrants_culture |
immigrants_culture | integer | 0% | 1 | 1 |
confidence_government |
confidence_government | integer | 0% | 1 | 1 |
confidence_parliament |
confidence_parliament | integer | 0% | 1 | 1 |
confidence_police |
confidence_police | integer | 0% | 1 | 1 |
confidence_courts |
confidence_courts | integer | 0% | 1 | 1 |
confidence_press |
confidence_press | integer | 0% | 1 | 1 |
democracy_importance |
democracy_importance | integer | 0% | 1 | 1 |
Which languages name the landscape here, and in which writing systems. A language's toponymic footprint and its speaker population are different measures and often diverge. Counts include variant and foreign-language renderings of the same place, so a language can rank high because outside sources record names in it rather than because it is spoken locally — and a widely spoken language can be almost absent where official naming is in another language.
| Language | Place names | Share | Script |
|---|---|---|---|
| Mongolian (mon) | 1,898 | 74.7% | Cyrillic |
| Russian (rus) | 306 | 12.0% | Cyrillic |
| Chinese (zho) | 265 | 10.4% | Han (Simplified variant) +1 |
| English (eng) | 66 | 2.6% | — |
| Uighur (uig) | 6 | 0.2% | Arabic |
6,849 distinct features ·
6 languages ·
3 scripts ·
911 names in non-Roman script ·
3 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.