Myanmar

MMR Global Data Lab MMR-GDL Development Indices

510 rows · 1 table(s) · 2023 Global Data Lab 0 1 2 3 9 SEL 2 ext ▶

ⓘ 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.

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1 Admin 1 — 1 table(s)

MMR GDL - Subnational Indices — 510 rows, 11 columns

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Field details — 11 fields (type, nulls, unique, samples)

Standards-Aligned Fields (9)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR, MMR, MMR, MMR, MMR
`region_code`	Admin code	string	SEL	100%	-	-
`region_name`	Admin name	string	SEL	0%	15	Total, Ayeyarwaddy, Bago, Chin, Kachin
`human_development_index`	Human development index	float	SEL	0%	70	0.389, 0.369, 0.395, 0.387, 0.418
`health_index`	Health index	float	SEL	0%	78	0.572, 0.553, 0.551, 0.517, 0.592
`education_index`	Education index	float	SEL	0%	72	0.358, 0.342, 0.371, 0.378, 0.386
`income_index`	Income index	float	SEL	0%	69	0.288, 0.265, 0.301, 0.296, 0.319
`life_expectancy`	Life expectancy	float	SEL	0%	99	57.16, 55.96, 55.84, 53.58, 58.5
`mean_years_schooling`	Mean years schooling	float	SEL	0%	93	5.367, 5.205, 5.682, 5.02, 5.66

Extension Fields (2) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`year`	year	integer	0%	7	1990, 1990, 1990, 1990, 1990
`level`	level	string	0%	2	national, subnational, subnational, subnational, subnational

MMR Glottolog Language Catalog MMR-GLOTTOLOG Language

150 rows · 1 table(s) · 2024 Glottolog Language Catalog 0 1 2 3 1 SEL 12 CCL 3 ext ▶

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0 Admin 0 — 1 table(s)

MMR Glottolog - Languages — 150 rows, 16 columns

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Field details — 16 fields (type, nulls, unique, samples)

Standards-Aligned Fields (13)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`glottocode`	Glottocode	string	CCL	0%	100	acha1249, akeu1235, akha1245, akya1234, anal1239
`name`	Name	string	CCL	0%	100	Longchuan Achang, Akeu, Akha, Akyaung Ari Naga, Anal
`iso639_3`	Iso639 3	string	CCL	4%	96	acn, aeu, ahk, nqy, anm
`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	sino1245, sino1245, sino1245, book1242, sino1245
`parent_name`	Parent name	string	CCL	100%	-	-
`parent_glottocode`	Parent glottocode	string	CCL	0%	70	acha1252, akeu1236, akha1246, pend1244, anal1240
`endangerment_status`	Endangerment status	string	CCL	100%	-	-
`country_codes`	Country codes	string	SEL+	0%	15	['CN', 'MM'], ['CN', 'LA', 'MM', 'TH'], ['CN', 'LA',...
`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	3, 0, 2, 0, 2

Extension Fields (3) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`latitude`	latitude	float	5%	95	24.3479, 22.1959, 21.2309, 24.0506, 24.754303
`longitude`	longitude	float	5%	95	97.7438, 101.0823, 100.964, 94.2806, 94.033796
`classification`	classification	string	0%	1	[], [], [], [], []

MMR World Bank Open Data MMR-WORLD_BANK Development Indicators

132 rows · 2 table(s) · 2024 World Bank Open Data 0 1 2 3 19 SEL 4 ext ▶

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0 Admin 0 — 2 table(s)

MMR World Bank - Development Indicators — 66 rows, 9 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MM, MM, MM, MM, MM
`population_count`	Population count	float	SEL	2%	65	21730250.0, 22210581.0, 22704719.0, 23213408.0, 23737315.0
`life_expectancy`	Life expectancy	float	SEL	3%	64	44.086, 44.603, 45.264, 45.951, 46.653
`gdp_per_capita_usd`	Gdp per capita usd	float	SEL	2%	65	25.0847757223623, 27.2654541223873, 27.9470039695431,...
`literacy_rate_pct`	Literacy rate percent	float	SEL	89%	7	78.5699996948242, 89.9400024414062, 90.3600006103516,...
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	15%	56	180.2, 176.9, 173.5, 170.3, 166.8
`poverty_headcount_pct`	Poverty headcount percent	float	SEL	94%	4	48.2, 42.2, 32.1, 24.8

Extension Fields (2) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_name`	country_name	string	0%	1	Myanmar, Myanmar, Myanmar, Myanmar, Myanmar
`year`	year	integer	0%	66	1960, 1961, 1962, 1963, 1964

MMR World Bank - Health Indicators — 66 rows, 14 columns

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Field details — 14 fields (type, nulls, unique, samples)

Standards-Aligned Fields (12)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MM, MM, MM, MM, MM
`life_expectancy`	Life expectancy	float	SEL	3%	64	44.086, 44.603, 45.264, 45.951, 46.653
`infant_mortality_per_1000`	Infant mortality per 1000	float	SEL	47%	35	48.5, 47.7, 46.9, 45.9, 44.9
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	15%	56	180.2, 176.9, 173.5, 170.3, 166.8
`maternal_mortality_per_100k`	Maternal mortality per 100k	float	SEL	41%	39	674.0, 652.0, 631.0, 616.0, 603.0
`fertility_rate`	Fertility rate	float	SEL	3%	63	5.901, 5.9, 5.904, 5.905, 5.907
`birth_rate_per_1000`	Birth rate per 1000	float	SEL	3%	63	41.919, 41.416, 40.964, 40.509, 40.09
`death_rate_per_1000`	Death rate per 1000	float	SEL	3%	64	20.518, 20.038, 19.474, 18.903, 18.338
`physicians_per_1000`	Physicians per 1000	float	SEL	65%	23	0.065, 0.085, 0.114, 0.203, 0.27
`hospital_beds_per_1000`	Hospital beds per 1000	float	SEL	65%	19	0.663009285926819, 0.85809999704361, 0.857100009918213,...
`vaccination_rate_pct`	Vaccination rate percent	float	SEL	32%	26	4.0, 5.0, 9.0, 11.0, 12.0
`health_expenditure_pct_gdp`	Health expenditure percent gdp	float	SEL	64%	24	2.00781965, 2.16208982, 2.59446764, 2.3959713, 2.33253765

Extension Fields (2) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_name`	country_name	string	0%	1	Myanmar, Myanmar, Myanmar, Myanmar, Myanmar
`year`	year	integer	0%	66	1960, 1961, 1962, 1963, 1964

MMR LandScan Global (ORNL) MMR-LANDSCAN Modeled Population

128 rows · 3 table(s) · 2024 LandScan Global (ORNL) 0 1 2 3 Locality 21 SEL 2 ext ▶

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0 Admin 0 — 1 table(s)

MMR LandScan - Population Admin0 (admin_0) — 1 rows, 7 columns

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Field details — 7 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR
`admin_level`	Admin level	string	SEL	0%	1	admin_0
`admin_name`	Admin name	string	SEL	0%	1	Myanmar
`admin_code`	Admin code	string	SEL	0%	1	35516675B14551075264028
`area_sqkm`	Area sqkm	float	SEL	0%	1	668565.9119
`pop_2024`	Population count	integer	SEL	0%	1	57298378
`pop_density_2024`	Population density	float	SEL	0%	1	85.7

1 Admin 1 — 1 table(s)

MMR LandScan - Population Admin1 (admin_1) — 14 rows, 7 columns

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Field details — 7 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR, MMR, MMR, MMR, MMR
`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%	14	Yangon, Mandalay, Shan, Ayeyarwady, Saigang
`admin_code`	Admin code	string	SEL	0%	14	20573499B24734669936209, 20573499B45980987355836,...
`area_sqkm`	Area sqkm	float	SEL	0%	14	9788.3045, 38005.8049, 155714.089, 33583.2328, 93617.9257
`pop_2024`	Population count	integer	SEL	0%	14	8650437, 8360928, 6807728, 6798611, 6010541
`pop_density_2024`	Population density	float	SEL	0%	14	883.75, 219.99, 43.72, 202.44, 64.2

Locality Locality — 1 table(s)

MMR LandScan - Cities (locality) — 113 rows, 9 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR, MMR, MMR, MMR, MMR
`admin_level`	Admin level	string	SEL	0%	1	locality, locality, locality, locality, locality
`admin_name`	Admin name	string	SEL	0%	100	Yangon, Mandalay, Pegu, Taunggyi, Pyinmana [Nay Pyi Taw]
`admin_code`	Admin code	integer	SEL	0%	100	5029, 2597, 5344, 4582, 3687
`area_sqkm`	Area sqkm	float	SEL	0%	96	541.9619, 204.0007, 42.7625, 57.7136, 88.5398
`pop_2024`	Population count	integer	SEL	0%	100	5955694, 1700181, 309891, 268891, 251102
`pop_density_2024`	Population density	float	SEL	0%	100	10989.14, 8334.19, 7246.79, 4659.06, 2836.04

Extension Fields (2) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`ghs_pop_2025`	ghs_pop_2025	integer	0%	100	6190958, 1849446, 392534, 383382, 556726
`landscan_vs_ghs_ratio`	landscan_vs_ghs_ratio	float	0%	96	0.962, 0.919, 0.789, 0.701, 0.451

MMR GHS Urban Centre Database (EU JRC) MMR-GHSL_UCDB Modeled Population

113 rows · 1 table(s) · 2025 GHS Urban Centre Database (EU JRC) 0 1 2 3 Locality 3 SEL 7 ext ▶

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Locality Locality — 1 table(s)

MMR GHS-UCDB - Cities (locality) — 113 rows, 10 columns

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Field details — 10 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`city_name`	Admin name	string	SEL	0%	100	Yangon, Mandalay, Pyinmana [Nay Pyi Taw], Pegu, Taunggyi
`country_code`	Country code	string	SEL	0%	1	MMR, MMR, MMR, MMR, MMR
`population`	Population count	integer	SEL	0%	100	6190958, 1849446, 556726, 392534, 383382

Extension Fields (7) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`city_id`	city_id	integer	0%	100	5029, 2597, 3687, 5344, 4582
`name_alternates`	name_alternates	string	100%	-	-
`country_name`	country_name	string	0%	1	Myanmar, Myanmar, Myanmar, Myanmar, Myanmar
`population_year`	population_year	integer	0%	1	2025, 2025, 2025, 2025, 2025
`latitude`	latitude	string	100%	-	-
`longitude`	longitude	string	100%	-	-
`region`	region	string	100%	-	-

MMR NGA GEOnet Names Server (GNS) MMR-NGA_GNS Language

91 rows · 3 table(s) · 2026 NGA GEOnet Names Server (GNS) 0 1 2 3 5 SEL 12 CCL 31 ext ▶

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0 Admin 0 — 3 table(s)

MMR Nga Gns - Language — 4 rows, 9 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (9)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	country_code	string	SEL	0%	1	MMR, MMR, MMR, MMR
`gns_language_code`	gns_language_code	string	CCL	0%	4	mya, tha, eng, zho
`gns_language_name`	gns_language_name	string	CCL	0%	4	Burmese, Thai, English, Chinese
`gns_toponym_count`	gns_toponym_count	integer	CCL	0%	4	48890, 90, 19, 4
`gns_toponym_share_pct`	gns_toponym_share_pct	float	CCL	0%	4	99.7694, 0.1837, 0.0388, 0.0082
`gns_non_roman_toponym_count`	gns_non_roman_toponym_count	integer	CCL	0%	4	22170, 42, 0, 1
`gns_dominant_script_code`	gns_dominant_script_code	string	CCL	0%	3	Mymr, Thai, Thai, Hans
`gns_dominant_script_name`	gns_dominant_script_name	string	CCL	0%	3	Myanmar (Burmese), Thai, Thai, Han (Simplified variant)
`gns_script_count`	gns_script_count	integer	CCL	0%	3	3, 2, 1, 1

MMR Nga Gns - Summary — 1 rows, 27 columns

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Field details — 27 fields (type, nulls, unique, samples)

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	country_code	string	SEL	0%	1	MMR
`admin_level`	admin_level	integer	SEL	0%	1	0
`gns_country_name`	gns_country_name	string	SEL	0%	1	Burma
`gns_language_count`	gns_language_count	integer	CCL	0%	1	4
`gns_script_count`	gns_script_count	integer	CCL	0%	1	6
`gns_endonym_share_pct`	gns_endonym_share_pct	float	CCL	0%	1	99.9852
`gns_non_roman_name_count`	gns_non_roman_name_count	integer	CCL	0%	1	22214

Extension Fields (20) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`gns_name_count`	gns_name_count	integer	0%	1	101296
`gns_feature_count`	gns_feature_count	integer	0%	1	65017
`gns_endonym_count`	gns_endonym_count	integer	0%	1	101281
`gns_exonym_count`	gns_exonym_count	integer	0%	1	15
`gns_source_build_date`	gns_source_build_date	string	0%	1	Wed, 05 Aug 2026
`gns_source_change_date`	gns_source_change_date	string	0%	1	2026-08-05
`gns_name_count_populated_places`	gns_name_count_populated_places	integer	0%	1	87366
`gns_feature_count_populated_places`	gns_feature_count_populated_places	integer	0%	1	54123
`gns_name_count_spot_features`	gns_name_count_spot_features	integer	0%	1	1931
`gns_feature_count_spot_features`	gns_feature_count_spot_features	integer	0%	1	1108
`gns_name_count_hypsographic`	gns_name_count_hypsographic	integer	0%	1	4583
`gns_feature_count_hypsographic`	gns_feature_count_hypsographic	integer	0%	1	3681
`gns_name_count_hydrographic`	gns_name_count_hydrographic	integer	0%	1	6691
`gns_feature_count_hydrographic`	gns_feature_count_hydrographic	integer	0%	1	5681
`gns_name_count_areas_localities`	gns_name_count_areas_localities	integer	0%	1	393
`gns_feature_count_areas_localities`	gns_feature_count_areas_localities	integer	0%	1	328
`gns_name_count_administrative_regions`	gns_name_count_administrative_regions	integer	0%	1	331
`gns_feature_count_administrative_regions`	gns_feature_count_administrative_regions	integer	0%	1	95
`gns_name_count_vegetation`	gns_name_count_vegetation	integer	0%	1	1
`gns_feature_count_vegetation`	gns_feature_count_vegetation	integer	0%	1	1

MMR Nga Gns - Admin Crosswalk — 86 rows, 12 columns

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Field details — 12 fields (type, nulls, unique, samples)

Standards-Aligned Fields (1)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	country_code	string	SEL	0%	1	MMR, MMR, MMR, MMR, MMR

Extension Fields (11) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`gns_ufi`	gns_ufi	integer	0%	86	-417417, -438970, -412046, -417566, -419740
`admin_designation`	admin_designation	string	0%	2	ADM1, ADM1, ADM1, ADM1, ADM1
`gns_bgn_name`	gns_bgn_name	string	0%	85	Ayeyarwady, Bago, Chin State, Kachin State, Kayah State
`gns_local_name`	gns_local_name	string	100%	-	-
`iso_3166_2`	iso_3166_2	string	0%	15	MM-07, MM-02, MM-14, MM-11, MM-12
`parent_code`	parent_code	string	0%	15	MM-07, MM-02, MM-14, MM-11, MM-12
`gns_prominence_band`	gns_prominence_band	integer	0%	4	9, 9, 9, 9, 9
`latitude`	latitude	float	0%	84	17.0, 18.25, 22.0, 26.0, 19.25
`longitude`	longitude	float	0%	84	95.0, 96.25, 93.5, 97.5, 97.5
`gns_mgrs`	gns_mgrs	string	0%	86	46QGD1292380642, 47QKA0920020032, 46QEK5161132911,...
`name_variant_count`	name_variant_count	integer	0%	9	7, 4, 4, 2, 4

MMR UNHCR Refugee Data Finder MMR-UNHCR Migration

61 rows · 2 table(s) · 2025 UNHCR Refugee Data Finder 0 1 2 3 12 CCL 36 ext ▶

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0 Admin 0 — 2 table(s)

MMR UNHCR - Hosted Populations — 21 rows, 24 columns

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Field details — 24 fields (type, nulls, unique, samples)

Standards-Aligned Fields (6)

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%	-	-

Extension Fields (18) — supplemental data preserved outside core SEL/CCL schema

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%	-	-

MMR UNHCR - Origin Populations — 40 rows, 24 columns

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Field details — 24 fields (type, nulls, unique, samples)

Standards-Aligned Fields (6)

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%	-	-

Extension Fields (18) — supplemental data preserved outside core SEL/CCL schema

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%	-	-

MMR USAID DHS Program MMR-DHS Health Surveys

30 rows · 2 table(s) · 2016 USAID DHS Program 0 1 2 3 5 SEL 3 CCL 10 ext ▶

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1 Admin 1 — 2 table(s)

MMR DHS - Ethnicity Indicators — 15 rows, 8 columns

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Field details — 8 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	100%	-	-
`women_who_are_literate`	Women who are literate	float	CCL	0%	15	89.0, 92.8, 72.6, 95.1, 85.3
`men_who_are_literate`	Men who are literate	float	CCL	0%	15	94.4, 91.7, 85.2, 96.2, 87.8

Extension Fields (5) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_name`	country_name	string	0%	1	Myanmar, Myanmar, Myanmar, Myanmar, Myanmar
`survey_year`	survey_year	integer	0%	1	2016, 2016, 2016, 2016, 2016
`region`	region	string	0%	15	Ayeyarwaddy, Bago, Chin, Kachin, Kayah
`survey_id`	survey_id	string	0%	1	MM2016DHS, MM2016DHS, MM2016DHS, MM2016DHS, MM2016DHS
`survey_type`	survey_type	string	0%	1	DHS, DHS, DHS, DHS, DHS

MMR DHS - Health Indicators — 15 rows, 10 columns

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Field details — 10 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	100%	-	-
`contraception_modern_pct`	Contraception modern percent	float	SEL	0%	14	36.7, 37.7, 16.4, 26.8, 31.6
`infant_mortality_per_1000`	Infant mortality per 1000	float	SEL	0%	14	66.0, 80.0, 75.0, 50.0, 38.0
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	0%	14	82.0, 83.0, 104.0, 61.0, 50.0
`children_underweight`	Children underweight	float	CCL	0%	15	24.6, 17.6, 16.7, 17.3, 17.9

Extension Fields (5) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_name`	country_name	string	0%	1	Myanmar, Myanmar, Myanmar, Myanmar, Myanmar
`survey_year`	survey_year	integer	0%	1	2016, 2016, 2016, 2016, 2016
`region`	region	string	0%	15	Ayeyarwaddy, Bago, Chin, Kachin, Kayah
`survey_id`	survey_id	string	0%	1	MM2016DHS, MM2016DHS, MM2016DHS, MM2016DHS, MM2016DHS
`survey_type`	survey_type	string	0%	1	DHS, DHS, DHS, DHS, DHS

MMR OpenFactBook MMR-OPENFACTBOOK Country Profile

15 rows · 15 table(s) · 2024 OpenFactBook 0 1 2 3 96 SEL 6 CCL 594 ext ▶

or use the per-admin-level buttons below. Free downloads return a 10-row sample. Contact us for the full pack.

0 Admin 0 — 15 table(s)

MMR OpenFactBook - Communications — 1 rows, 21 columns

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Field details — 22 fields (type, nulls, unique, samples)

Standards-Aligned Fields (8)

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	1.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric`	Mobile subscriptions per 100	float	SEL	0%	1	114.0
`internet_country_code_text`	Internet country code text	string	SEL+	0%	1	.mm
`internet_users_percent_of_population_numeric`	Internet penetration percent	float	SEL	0%	1	59.0
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric`	Broadband subscriptions per 100	float	SEL	0%	1	3.0
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (14) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`telephones_fixed_lines_total_subscriptions_text`	telephones_fixed_lines_total_subscriptions_text	string	0%	1	559,000 (2024 est.)
`telephones_fixed_lines_total_subscriptions_numeric`	telephones_fixed_lines_total_subscriptions_numeric	float	0%	1	559000.0
`telephones_fixed_lines_subscriptions_per_100_inhabitants_text`	telephones_fixed_lines_subscriptions_per_100_inhabitants_text	string	0%	1	1 (2024 est.)
`telephones_mobile_cellular_total_subscriptions_text`	telephones_mobile_cellular_total_subscriptions_text	string	0%	1	62.3 million (2024 est.)
`telephones_mobile_cellular_total_subscriptions_numeric`	telephones_mobile_cellular_total_subscriptions_numeric	float	0%	1	62.3
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_text`	telephones_mobile_cellular_subscriptions_per_100_inhabitants_text	string	0%	1	114 (2024 est.)
`broadcast_media_text`	broadcast_media_text	string	0%	1	government controls all domestic broadcast media; 2...
`broadcast_media_numeric`	broadcast_media_numeric	float	0%	1	2.0
`internet_users_percent_of_population_text`	internet_users_percent_of_population_text	string	0%	1	59% (2023 est.)
`broadband_fixed_subscriptions_total_text`	broadband_fixed_subscriptions_total_text	string	0%	1	1.51 million (2023 est.)
`broadband_fixed_subscriptions_total_numeric`	broadband_fixed_subscriptions_total_numeric	float	0%	1	1.51
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text`	broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text	string	0%	1	3 (2023 est.)
`source_section`	source_section	string	0%	1	Communications
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/bm.json

MMR OpenFactBook - Economy — 1 rows, 139 columns

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Field details — 144 fields (type, nulls, unique, samples)

Standards-Aligned Fields (6)

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	5300.0
`gdp_official_exchange_rate_numeric`	Gdp total usd	float	SEL	0%	1	74.08
`population_below_poverty_line_numeric`	Poverty headcount percent	float	SEL	0%	1	24.8
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (138) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`economic_overview_text`	economic_overview_text	string	0%	1	slowly recovering Southeast Asian economy; household...
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text`	Real gdp purchasing power parity 2024 (text)	string	0%	1	$287.559 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	287.559
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text`	Real gdp purchasing power parity 2023 (text)	string	0%	1	$290.381 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	290.381
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text`	Real gdp purchasing power parity 2022 (text)	string	0%	1	$287.624 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	287.624
`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	-1% (2024 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric`	Real gdp growth rate 2024 (numeric)	float	0%	1	-1.0
`real_gdp_growth_rate_real_gdp_growth_rate_2023_text`	Real gdp growth rate 2023 (text)	string	0%	1	1% (2023 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric`	Real gdp growth rate 2023 (numeric)	float	0%	1	1.0
`real_gdp_growth_rate_real_gdp_growth_rate_2022_text`	Real gdp growth rate 2022 (text)	string	0%	1	4% (2022 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric`	Real gdp growth rate 2022 (numeric)	float	0%	1	4.0
`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	$5,300 (2024 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_text`	Real gdp per capita 2023 (text)	string	0%	1	$5,400 (2023 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_numeric`	Real gdp per capita 2023 (numeric)	float	0%	1	5400.0
`real_gdp_per_capita_real_gdp_per_capita_2022_text`	Real gdp per capita 2022 (text)	string	0%	1	$5,400 (2022 est.)
`real_gdp_per_capita_real_gdp_per_capita_2022_numeric`	Real gdp per capita 2022 (numeric)	float	0%	1	5400.0
`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	$74.08 billion (2024 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2019_text`	Inflation rate consumer prices 2019 (text)	string	0%	1	8.8% (2019 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2019_numeric`	Inflation rate consumer prices 2019 (numeric)	float	0%	1	8.8
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2018_text`	Inflation rate consumer prices 2018 (text)	string	0%	1	6.9% (2018 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2018_numeric`	Inflation rate consumer prices 2018 (numeric)	float	0%	1	6.9
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2017_text`	Inflation rate consumer prices 2017 (text)	string	0%	1	4.6% (2017 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2017_numeric`	Inflation rate consumer prices 2017 (numeric)	float	0%	1	4.6
`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	20.8% (2024 est.)
+108 more extension fields — download the CSV/Parquet to see them all.

MMR OpenFactBook - Energy — 1 rows, 55 columns

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Field details — 55 fields (type, nulls, unique, samples)

Standards-Aligned Fields (4)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`electricity_access_electrification_total_population_numeric`	Electricity access percent	float	SEL	0%	1	73.7
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (51) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`electricity_access_electrification_total_population_text`	electricity_access_electrification_total_population_text	string	0%	1	73.7% (2022 est.)
`electricity_access_electrification_urban_areas_text`	electricity_access_electrification_urban_areas_text	string	0%	1	93.9%
`electricity_access_electrification_urban_areas_numeric`	electricity_access_electrification_urban_areas_numeric	float	0%	1	93.9
`electricity_access_electrification_rural_areas_text`	electricity_access_electrification_rural_areas_text	string	0%	1	62.8%
`electricity_access_electrification_rural_areas_numeric`	electricity_access_electrification_rural_areas_numeric	float	0%	1	62.8
`electricity_installed_generating_capacity_text`	electricity_installed_generating_capacity_text	string	0%	1	7.419 million kW (2023 est.)
`electricity_installed_generating_capacity_numeric`	electricity_installed_generating_capacity_numeric	float	0%	1	7.419
`electricity_consumption_text`	electricity_consumption_text	string	0%	1	23.625 billion kWh (2023 est.)
`electricity_consumption_numeric`	electricity_consumption_numeric	float	0%	1	23.625
`electricity_exports_text`	electricity_exports_text	string	0%	1	200 million kWh (2023 est.)
`electricity_exports_numeric`	electricity_exports_numeric	float	0%	1	200.0
`electricity_transmission_distribution_losses_text`	electricity_transmission_distribution_losses_text	string	0%	1	1.855 billion kWh (2023 est.)
`electricity_transmission_distribution_losses_numeric`	electricity_transmission_distribution_losses_numeric	float	0%	1	1.855
`electricity_generation_sources_fossil_fuels_text`	electricity_generation_sources_fossil_fuels_text	string	0%	1	61.8% of total installed capacity (2023 est.)
`electricity_generation_sources_fossil_fuels_numeric`	electricity_generation_sources_fossil_fuels_numeric	float	0%	1	61.8
`electricity_generation_sources_solar_text`	electricity_generation_sources_solar_text	string	0%	1	0.4% of total installed capacity (2023 est.)
`electricity_generation_sources_solar_numeric`	electricity_generation_sources_solar_numeric	float	0%	1	0.4
`electricity_generation_sources_hydroelectricity_text`	electricity_generation_sources_hydroelectricity_text	string	0%	1	36.7% of total installed capacity (2023 est.)
`electricity_generation_sources_hydroelectricity_numeric`	electricity_generation_sources_hydroelectricity_numeric	float	0%	1	36.7
`electricity_generation_sources_biomass_and_waste_text`	electricity_generation_sources_biomass_and_waste_text	string	0%	1	1% of total installed capacity (2023 est.)
`electricity_generation_sources_biomass_and_waste_numeric`	electricity_generation_sources_biomass_and_waste_numeric	float	0%	1	1.0
`coal_production_text`	coal_production_text	string	0%	1	1.031 million metric tons (2023 est.)
`coal_production_numeric`	coal_production_numeric	float	0%	1	1.031
`coal_consumption_text`	coal_consumption_text	string	0%	1	907,000 metric tons (2023 est.)
`coal_consumption_numeric`	coal_consumption_numeric	float	0%	1	907000.0
`coal_exports_text`	coal_exports_text	string	0%	1	221,000 metric tons (2023 est.)
`coal_exports_numeric`	coal_exports_numeric	float	0%	1	221000.0
`coal_imports_text`	coal_imports_text	string	0%	1	67,000 metric tons (2023 est.)
`coal_imports_numeric`	coal_imports_numeric	float	0%	1	67000.0
`coal_proven_reserves_text`	coal_proven_reserves_text	string	0%	1	252 million metric tons (2023 est.)
+21 more extension fields — download the CSV/Parquet to see them all.

MMR OpenFactBook - Environment — 1 rows, 43 columns

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Field details — 48 fields (type, nulls, unique, samples)

Standards-Aligned Fields (8)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`land_use_agricultural_land_numeric`	Agricultural land percent	float	SEL	0%	1	19.9
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	42.4
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	32.1
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	1.85
`waste_and_recycling_municipal_solid_waste_generated_annually_numeric`	Municipal waste kg per capita	float	SEL	0%	1	4.677
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (40) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`environmental_issues_text`	environmental_issues_text	string	0%	1	deforestation; industrial pollution of air, soil, and...
`international_environmental_agreements_party_to_text`	international_environmental_agreements_party_to_text	string	0%	1	Biodiversity, Climate Change, Climate Change-Kyoto...
`international_environmental_agreements_party_to_numeric`	international_environmental_agreements_party_to_numeric	float	0%	1	2006.0
`international_environmental_agreements_signed_but_not_ratified_text`	international_environmental_agreements_signed_but_not_ratified_text	string	0%	1	none of the selected agreements
`climate_text`	climate_text	string	0%	1	tropical monsoon; cloudy, rainy, hot, humid summers...
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	19.9% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 16.9% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	16.9
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 2.3% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	2.3
`land_use_agricultural_land_permanent_pasture_text`	land_use_agricultural_land_permanent_pasture_text	string	0%	1	permanent pasture: 0.7% (2023 est.)
`land_use_agricultural_land_permanent_pasture_numeric`	land_use_agricultural_land_permanent_pasture_numeric	float	0%	1	0.7
`land_use_forest_text`	land_use_forest_text	string	0%	1	42.4% (2023 est.)
`land_use_other_text`	land_use_other_text	string	0%	1	37.7% (2023 est.)
`land_use_other_numeric`	land_use_other_numeric	float	0%	1	37.7
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	32.1% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	1.85% annual rate of change (2020-25 est.)
`carbon_dioxide_emissions_total_emissions_text`	carbon_dioxide_emissions_total_emissions_text	string	0%	1	27.005 million metric tonnes of CO2 (2023 est.)
`carbon_dioxide_emissions_total_emissions_numeric`	carbon_dioxide_emissions_total_emissions_numeric	float	0%	1	27.005
`carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text`	carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text	string	0%	1	1.24 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	1.24
`carbon_dioxide_emissions_from_petroleum_and_other_liquids_text`	carbon_dioxide_emissions_from_petroleum_and_other_liquids_text	string	0%	1	17.39 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	17.39
`carbon_dioxide_emissions_from_consumed_natural_gas_text`	carbon_dioxide_emissions_from_consumed_natural_gas_text	string	0%	1	8.376 million metric tonnes of CO2 (2023 est.)
`carbon_dioxide_emissions_from_consumed_natural_gas_numeric`	carbon_dioxide_emissions_from_consumed_natural_gas_numeric	float	0%	1	8.376
`particulate_matter_emissions_text`	particulate_matter_emissions_text	string	0%	1	27.2 micrograms per cubic meter (2019 est.)
`particulate_matter_emissions_numeric`	particulate_matter_emissions_numeric	float	0%	1	27.2
`waste_and_recycling_municipal_solid_waste_generated_annually_text`	waste_and_recycling_municipal_solid_waste_generated_annually_text	string	0%	1	4.677 million tons (2024 est.)
`waste_and_recycling_percent_of_municipal_solid_waste_recycled_text`	waste_and_recycling_percent_of_municipal_solid_waste_recycled_text	string	0%	1	12.3% (2022 est.)
`waste_and_recycling_percent_of_municipal_solid_waste_recycled_numeric`	waste_and_recycling_percent_of_municipal_solid_waste_recycled_numeric	float	0%	1	12.3
+10 more extension fields — download the CSV/Parquet to see them all.

MMR OpenFactBook - Ethnic Groups — 1 rows, 8 columns

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Field details — 9 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (6) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`nationality_noun_text`	nationality_noun_text	string	0%	1	Burmese (singular and plural)
`nationality_adjective_text`	nationality_adjective_text	string	0%	1	Burmese
`ethnic_groups_text`	ethnic_groups_text	string	0%	1	Burman (Bamar) 68%, Shan 9%, Karen 7%, Rakhine 4%,...
`ethnic_groups_numeric`	ethnic_groups_numeric	float	0%	1	68.0
`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/bm.json

MMR OpenFactBook - Geography — 1 rows, 58 columns

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Field details — 62 fields (type, nulls, unique, samples)

Standards-Aligned Fields (13)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`area_total_numeric`	Area sqkm	float	SEL	0%	1	676578.0
`area_land_numeric`	Area land sqkm	float	SEL	0%	1	653508.0
`area_water_numeric`	Area water sqkm	float	SEL	0%	1	23070.0
`land_boundaries_total_numeric`	Land boundary km	float	SEL	0%	1	6522.0
`coastline_numeric`	Coastline km	float	SEL	0%	1	1930.0
`elevation_highest_point_numeric`	Elevation max m	float	SEL	0%	1	5870.0
`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	19.9
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	42.4
`irrigated_land_numeric`	Irrigated land sqkm	float	SEL	0%	1	17140.0
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (49) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`location_text`	location_text	string	0%	1	Southeastern Asia, bordering the Andaman Sea and the Bay...
`geographic_coordinates_text`	geographic_coordinates_text	string	0%	1	22 00 N, 98 00 E
`geographic_coordinates_numeric`	geographic_coordinates_numeric	float	0%	1	22.0
`map_references_text`	map_references_text	string	0%	1	Southeast Asia
`area_total_text`	area_total_text	string	0%	1	676,578 sq km
`area_land_text`	area_land_text	string	0%	1	653,508 sq km
`area_water_text`	area_water_text	string	0%	1	23,070 sq km
`area_comparative_text`	area_comparative_text	string	0%	1	slightly smaller than Texas
`land_boundaries_total_text`	land_boundaries_total_text	string	0%	1	6,522 km
`land_boundaries_border_countries_text`	land_boundaries_border_countries_text	string	0%	1	Bangladesh 271 km; China 2,129 km; India 1,468 km; Laos...
`land_boundaries_border_countries_numeric`	land_boundaries_border_countries_numeric	float	0%	1	271.0
`coastline_text`	coastline_text	string	0%	1	1,930 km
`maritime_claims_territorial_sea_text`	maritime_claims_territorial_sea_text	string	0%	1	12 nm
`maritime_claims_territorial_sea_numeric`	maritime_claims_territorial_sea_numeric	float	0%	1	12.0
`maritime_claims_contiguous_zone_text`	maritime_claims_contiguous_zone_text	string	0%	1	24 nm
`maritime_claims_contiguous_zone_numeric`	maritime_claims_contiguous_zone_numeric	float	0%	1	24.0
`maritime_claims_exclusive_economic_zone_text`	maritime_claims_exclusive_economic_zone_text	string	0%	1	200 nm
`maritime_claims_exclusive_economic_zone_numeric`	maritime_claims_exclusive_economic_zone_numeric	float	0%	1	200.0
`maritime_claims_continental_shelf_text`	maritime_claims_continental_shelf_text	string	0%	1	200 nm or to the edge of the continental margin
`maritime_claims_continental_shelf_numeric`	maritime_claims_continental_shelf_numeric	float	0%	1	200.0
`climate_text`	climate_text	string	0%	1	tropical monsoon; cloudy, rainy, hot, humid summers...
`terrain_text`	terrain_text	string	0%	1	central lowlands ringed by steep, rugged highlands
`elevation_highest_point_text`	elevation_highest_point_text	string	0%	1	Gamlang Razi 5,870 m
`elevation_lowest_point_text`	elevation_lowest_point_text	string	0%	1	Andaman Sea/Bay of Bengal 0 m
`elevation_mean_elevation_text`	elevation_mean_elevation_text	string	0%	1	702 m
`elevation_mean_elevation_numeric`	elevation_mean_elevation_numeric	float	0%	1	702.0
`natural_resources_text`	natural_resources_text	string	0%	1	petroleum, timber, tin, antimony, zinc, copper,...
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	19.9% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 16.9% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	16.9
+19 more extension fields — download the CSV/Parquet to see them all.

MMR OpenFactBook - Government — 1 rows, 73 columns

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Field details — 102 fields (type, nulls, unique, samples)

Standards-Aligned Fields (2)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (100) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_name_conventional_long_form_text`	country_name_conventional_long_form_text	string	0%	1	Union of Burma
`country_name_conventional_short_form_text`	country_name_conventional_short_form_text	string	0%	1	Burma
`country_name_local_long_form_text`	country_name_local_long_form_text	string	0%	1	Pyidaungzu Thammada Myanma Naingngandaw (translated as...
`country_name_local_short_form_text`	country_name_local_short_form_text	string	0%	1	Myanma Naingngandaw
`country_name_former_text`	country_name_former_text	string	0%	1	Socialist Republic of the Union of Burma, Union of Myanmar
`country_name_etymology_text`	country_name_etymology_text	string	0%	1	both "Burma" and "Myanmar" derive from the name of the...
`country_name_note`	country_name_note	string	0%	1	note: since 1989 the military authorities in Burma and...
`government_type_text`	government_type_text	string	0%	1	military regime
`capital_name_text`	capital_name_text	string	0%	1	Rangoon (aka Yangon, continues to be recognized as the...
`capital_geographic_coordinates_text`	capital_geographic_coordinates_text	string	0%	1	16 48 N, 96 10 E
`capital_geographic_coordinates_numeric`	capital_geographic_coordinates_numeric	float	0%	1	16.0
`capital_time_difference_text`	capital_time_difference_text	string	0%	1	UTC+6.5 (11.5 hours ahead of Washington, DC, during...
`capital_time_difference_numeric`	capital_time_difference_numeric	float	0%	1	6.5
`capital_etymology_text`	capital_etymology_text	string	0%	1	Rangoon/Yangon derives from the Burmese words yan and...
`administrative_divisions_text`	administrative_divisions_text	string	0%	1	7 regions (taing-myar, singular - taing), 7 states (pyi...
`administrative_divisions_numeric`	administrative_divisions_numeric	float	0%	1	7.0
`legal_system_text`	legal_system_text	string	0%	1	mixed legal system of English common law (as introduced...
`constitution_history_text`	constitution_history_text	string	0%	1	previous 1947, 1974 (suspended until 2008); latest...
`constitution_history_numeric`	constitution_history_numeric	float	0%	1	1947.0
`constitution_amendment_process_text`	constitution_amendment_process_text	string	0%	1	proposals require at least 20% approval by the Assembly...
`constitution_amendment_process_numeric`	constitution_amendment_process_numeric	float	0%	1	20.0
`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 Burma
`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	none
`citizenship_note`	citizenship_note	string	0%	1	note: an applicant for naturalization must be the child...
`suffrage_text`	suffrage_text	string	0%	1	18 years of age; universal
`suffrage_numeric`	suffrage_numeric	float	0%	1	18.0
`executive_branch_chief_of_state_text`	executive_branch_chief_of_state_text	string	0%	1	Acting President Sr. Gen. MIN AUNG HLAING (since 31 July 2025)
+70 more extension fields — download the CSV/Parquet to see them all.

MMR OpenFactBook - Introduction — 1 rows, 6 columns

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Field details — 7 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (4) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`background_text`	background_text	string	0%	1	Burma is home to ethnic Burmans and scores of other...
`background_numeric`	background_numeric	float	0%	1	1820.0
`source_section`	source_section	string	0%	1	Introduction
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/bm.json

MMR OpenFactBook - Languages — 1 rows, 8 columns

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Field details — 8 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (5) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`languages_languages_text`	Languages (text)	string	0%	1	Burmese (official)
`languages_major_language_sample_s_text`	languages_major_language_sample_s_text	string	0%	1	ကမ္ဘာ့အချက်အလက်စာအုပ်- အခြေခံအချက်အလက်တွေအတွက်...
`languages_note`	languages_note	string	0%	1	note: minority ethnic groups use their own languages
`source_section`	source_section	string	0%	1	People and Society:languages
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/bm.json

MMR OpenFactBook - Migration — 1 rows, 10 columns

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Field details — 11 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (8) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`refugees_and_internally_displaced_persons_idps_text`	refugees_and_internally_displaced_persons_idps_text	string	0%	1	3,646,658 (2024 est.)
`refugees_and_internally_displaced_persons_idps_numeric`	refugees_and_internally_displaced_persons_idps_numeric	float	0%	1	3646658.0
`refugees_and_internally_displaced_persons_stateless_persons_text`	refugees_and_internally_displaced_persons_stateless_persons_text	string	0%	1	619,429 (2024 est.)
`refugees_and_internally_displaced_persons_stateless_persons_numeric`	refugees_and_internally_displaced_persons_stateless_persons_numeric	float	0%	1	619429.0
`trafficking_in_persons_tier_rating_text`	trafficking_in_persons_tier_rating_text	string	0%	1	Tier 3 — Burma 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	east-n-southeast-asia/bm.json

MMR OpenFactBook - Military And Security — 1 rows, 21 columns

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Field details — 25 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (22) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`military_and_security_forces_text`	military_and_security_forces_text	string	0%	1	Burmese Defense Service (aka Armed Forces of Burma,...
`military_and_security_forces_numeric`	military_and_security_forces_numeric	float	0%	1	2025.0
`military_expenditures_military_expenditures_2023_text`	Military expenditures 2023 (text)	string	0%	1	3.9% of GDP (2023 est.)
`military_expenditures_military_expenditures_2023_numeric`	Military expenditures 2023 (numeric)	float	0%	1	3.9
`military_expenditures_military_expenditures_2022_text`	Military expenditures 2022 (text)	string	0%	1	3.6% of GDP (2022 est.)
`military_expenditures_military_expenditures_2022_numeric`	Military expenditures 2022 (numeric)	float	0%	1	3.6
`military_expenditures_military_expenditures_2021_text`	Military expenditures 2021 (text)	string	0%	1	3.5% of GDP (2021 est.)
`military_expenditures_military_expenditures_2021_numeric`	Military expenditures 2021 (numeric)	float	0%	1	3.5
`military_expenditures_military_expenditures_2020_text`	Military expenditures 2020 (text)	string	0%	1	3% of GDP (2020 est.)
`military_expenditures_military_expenditures_2020_numeric`	Military expenditures 2020 (numeric)	float	0%	1	3.0
`military_expenditures_military_expenditures_2019_text`	Military expenditures 2019 (text)	string	0%	1	4.1% of GDP (2019 est.)
`military_expenditures_military_expenditures_2019_numeric`	Military expenditures 2019 (numeric)	float	0%	1	4.1
`military_and_security_service_personnel_strengths_text`	military_and_security_service_personnel_strengths_text	string	0%	1	information varies; estimated 150,000 active military...
`military_and_security_service_personnel_strengths_numeric`	military_and_security_service_personnel_strengths_numeric	float	0%	1	150000.0
`military_equipment_inventories_and_acquisitions_text`	military_equipment_inventories_and_acquisitions_text	string	0%	1	the Burmese military's inventory is comprised of mostly...
`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	18-35 years of age (men) and 18-27 years of age (women)...
`military_service_age_and_obligation_numeric`	military_service_age_and_obligation_numeric	float	0%	1	18.0
`military_note_text`	military_note_text	string	0%	1	since the country’s founding, the Tatmadaw has been...
`military_note_numeric`	military_note_numeric	float	0%	1	1962.0
`source_section`	source_section	string	0%	1	Military and Security
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/bm.json

MMR OpenFactBook - People And Society — 1 rows, 139 columns

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Field details — 152 fields (type, nulls, unique, samples)

Standards-Aligned Fields (29)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`population_total_numeric`	Population count	float	SEL	0%	1	57931718.0
`population_male_numeric`	Population male	float	SEL	0%	1	28591467.0
`population_female_numeric`	Population female	float	SEL	0%	1	29340251.0
`age_structure_0_14_years_numeric`	Population 0 14 percent	float	SEL	0%	1	24.4
`age_structure_15_64_years_numeric`	Population 15 64 percent	float	SEL	0%	1	68.5
`age_structure_65_years_and_over_numeric`	Population 65 plus percent	float	SEL	0%	1	7.1
`dependency_ratios_total_dependency_ratio_numeric`	Total dependency ratio	float	SEL	0%	1	45.7
`dependency_ratios_youth_dependency_ratio_numeric`	Youth dependency ratio	float	SEL	0%	1	35.0
`dependency_ratios_elderly_dependency_ratio_numeric`	Elderly dependency ratio	float	SEL	0%	1	10.7
`median_age_total_numeric`	Median age	float	SEL	0%	1	31.1
`population_growth_rate_numeric`	Population growth rate percent	float	SEL	0%	1	0.69
`birth_rate_numeric`	Birth rate per 1000	float	SEL	0%	1	15.44
`death_rate_numeric`	Death rate per 1000	float	SEL	0%	1	7.17
`net_migration_rate_numeric`	Net migration per 1000	float	SEL	0%	1	-1.36
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	32.1
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	1.85
`sex_ratio_at_birth_numeric`	Sex ratio at birth	float	SEL	0%	1	1.06
`sex_ratio_total_population_numeric`	Sex ratio overall	float	SEL	0%	1	0.97
`maternal_mortality_ratio_numeric`	Maternal mortality per 100k	float	SEL	0%	1	185.0
`infant_mortality_rate_total_numeric`	Infant mortality per 1000	float	SEL	0%	1	30.8
`life_expectancy_at_birth_total_population_numeric`	Life expectancy	float	SEL	0%	1	70.3
`total_fertility_rate_numeric`	Fertility rate	float	SEL	0%	1	1.95
`gross_reproduction_rate_numeric`	Gross reproduction rate	float	SEL	0%	1	0.95
`physician_density_numeric`	Physicians per 1000	float	SEL	0%	1	0.76
`hospital_bed_density_numeric`	Hospital beds per 1000	float	SEL	0%	1	1.1
`literacy_total_population_numeric`	Literacy rate percent	float	SEL	0%	1	93.5
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (123) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`population_total_text`	population_total_text	string	0%	1	57,931,718 (2025 est.)
`population_male_text`	population_male_text	string	0%	1	28,591,467
`population_female_text`	population_female_text	string	0%	1	29,340,251
`age_structure_0_14_years_text`	age_structure_0_14_years_text	string	0%	1	24.4% (male 7,197,177/female 6,843,879)
`age_structure_15_64_years_text`	age_structure_15_64_years_text	string	0%	1	68.5% (male 19,420,361/female 19,998,625)
`age_structure_65_years_and_over_text`	age_structure_65_years_and_over_text	string	0%	1	7.1% (2024 est.) (male 1,770,293/female 2,296,804)
`dependency_ratios_total_dependency_ratio_text`	dependency_ratios_total_dependency_ratio_text	string	0%	1	45.7 (2025 est.)
`dependency_ratios_youth_dependency_ratio_text`	dependency_ratios_youth_dependency_ratio_text	string	0%	1	35 (2025 est.)
`dependency_ratios_elderly_dependency_ratio_text`	dependency_ratios_elderly_dependency_ratio_text	string	0%	1	10.7 (2025 est.)
`dependency_ratios_potential_support_ratio_text`	dependency_ratios_potential_support_ratio_text	string	0%	1	9.3 (2025 est.)
`dependency_ratios_potential_support_ratio_numeric`	dependency_ratios_potential_support_ratio_numeric	float	0%	1	9.3
`median_age_total_text`	median_age_total_text	string	0%	1	31.1 years (2025 est.)
`median_age_male_text`	median_age_male_text	string	0%	1	29.9 years
`median_age_male_numeric`	median_age_male_numeric	float	0%	1	29.9
`median_age_female_text`	median_age_female_text	string	0%	1	31.6 years
`median_age_female_numeric`	median_age_female_numeric	float	0%	1	31.6
`population_growth_rate_text`	population_growth_rate_text	string	0%	1	0.69% (2025 est.)
`birth_rate_text`	birth_rate_text	string	0%	1	15.44 births/1,000 population (2025 est.)
`death_rate_text`	death_rate_text	string	0%	1	7.17 deaths/1,000 population (2025 est.)
`net_migration_rate_text`	net_migration_rate_text	string	0%	1	-1.36 migrant(s)/1,000 population (2025 est.)
`population_distribution_text`	population_distribution_text	string	0%	1	population concentrated along coastal areas and in...
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	32.1% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	1.85% annual rate of change (2020-25 est.)
`major_urban_areas_population_text`	major_urban_areas_population_text	string	0%	1	5.610 million RANGOON (Yangon) (capital), 1.532 million...
`major_urban_areas_population_numeric`	major_urban_areas_population_numeric	float	0%	1	5.61
`sex_ratio_at_birth_text`	sex_ratio_at_birth_text	string	0%	1	1.06 male(s)/female
`sex_ratio_0_14_years_text`	sex_ratio_0_14_years_text	string	0%	1	1.05 male(s)/female
`sex_ratio_0_14_years_numeric`	sex_ratio_0_14_years_numeric	float	0%	1	1.05
`sex_ratio_15_64_years_text`	sex_ratio_15_64_years_text	string	0%	1	0.97 male(s)/female
`sex_ratio_15_64_years_numeric`	sex_ratio_15_64_years_numeric	float	0%	1	0.97
+93 more extension fields — download the CSV/Parquet to see them all.

MMR OpenFactBook - Religions — 1 rows, 6 columns

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Field details — 24 fields (type, nulls, unique, samples)

Standards-Aligned Fields (9)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national
`composition_religion_buddhist_pct_synth`	Buddhist	numeric	CCL	0%	-	87.9
`composition_religion_christian_pct_synth`	Christian	numeric	CCL	0%	-	6.2
`composition_religion_muslim_pct_synth`	Muslim	numeric	CCL	0%	-	4.3
`composition_religion_hindu_pct_synth`	Hindu	numeric	CCL	0%	-	0.5
`composition_religion_other_pct_synth`	other	numeric	CCL	0%	-	0.2
`composition_ethnicity_primary_label_synth`	Burman (Bamar)	string	CCL	0%	-	Burman (Bamar)

Extension Fields (4) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`religions_text`	religions_text	string	0%	1	Buddhist 87.9%, Christian 6.2%, Muslim 4.3%, Animist...
`religions_numeric`	religions_numeric	float	0%	1	87.9
`source_section`	source_section	string	0%	1	People and Society:religions
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/bm.json

Pending (11) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`composition_religion_animist_pct_synth`	Animist	numeric	0%	-	0.8
`composition_religion_none_pct_synth`	none	numeric	0%	-	0.1
`composition_ethnicity_burman_bamar_pct_synth`	Burman (Bamar)	numeric	0%	-	68.0
`composition_ethnicity_shan_pct_synth`	Shan	numeric	0%	-	9.0
`composition_ethnicity_karen_pct_synth`	Karen	numeric	0%	-	7.0
`composition_ethnicity_rakhine_pct_synth`	Rakhine	numeric	0%	-	4.0
`composition_ethnicity_chinese_pct_synth`	Chinese	numeric	0%	-	3.0
`composition_ethnicity_indian_pct_synth`	Indian	numeric	0%	-	2.0
`composition_ethnicity_mon_pct_synth`	Mon	numeric	0%	-	2.0
`composition_ethnicity_other_pct_synth`	other	numeric	0%	-	5.0
`composition_ethnicity_primary_share_pct_synth`	Burman (Bamar)	numeric	0%	-	68.0

MMR OpenFactBook - Transnational Issues — 1 rows, 6 columns

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Field details — 7 fields (type, nulls, unique, samples)

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (4) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`illicit_drugs_usg_identification_text`	illicit_drugs_usg_identification_text	string	0%	1	major illicit drug-producing and/or drug-transit...
`illicit_drugs_usg_identification_numeric`	illicit_drugs_usg_identification_numeric	float	0%	1	2025.0
`source_section`	source_section	string	0%	1	Transnational Issues
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/bm.json

MMR OpenFactBook - Transportation — 1 rows, 29 columns

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Field details — 31 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

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	XY
`airports_numeric`	Airports count	float	SEL	0%	1	74.0
`country_code`	Country code	string	SEL	0%	1	MMR
`country_name`	Country name	string	SEL	0%	1	Burma
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (26) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`airports_text`	airports_text	string	0%	1	74 (2025)
`heliports_text`	heliports_text	string	0%	1	6 (2025)
`heliports_numeric`	heliports_numeric	float	0%	1	6.0
`railways_total_text`	railways_total_text	string	0%	1	5,031 km (2008)
`railways_total_numeric`	railways_total_numeric	float	0%	1	5031.0
`railways_narrow_gauge_text`	railways_narrow_gauge_text	string	0%	1	5,031 km (2008) 1.000-m gauge
`railways_narrow_gauge_numeric`	railways_narrow_gauge_numeric	float	0%	1	5031.0
`merchant_marine_total_text`	merchant_marine_total_text	string	0%	1	101 (2023)
`merchant_marine_total_numeric`	merchant_marine_total_numeric	float	0%	1	101.0
`merchant_marine_by_type_text`	merchant_marine_by_type_text	string	0%	1	bulk carrier 1, general cargo 44, oil tanker 5, other 51
`merchant_marine_by_type_numeric`	merchant_marine_by_type_numeric	float	0%	1	1.0
`ports_total_ports_text`	ports_total_ports_text	string	0%	1	7 (2024)
`ports_total_ports_numeric`	ports_total_ports_numeric	float	0%	1	7.0
`ports_large_text`	ports_large_text	float	0%	1	0
`ports_large_numeric`	ports_large_numeric	float	0%	1	0.0
`ports_medium_text`	ports_medium_text	float	0%	1	0
`ports_medium_numeric`	ports_medium_numeric	float	0%	1	0.0
`ports_small_text`	ports_small_text	float	0%	1	5
`ports_small_numeric`	ports_small_numeric	float	0%	1	5.0
`ports_very_small_text`	ports_very_small_text	float	0%	1	2
`ports_very_small_numeric`	ports_very_small_numeric	float	0%	1	2.0
`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	Bassein, Mergui, Moulmein Harbor, Rangoon, Sittwe
`source_section`	source_section	string	0%	1	Transportation
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/bm.json

MMR D-PLACE MMR-DPLACE Ethnographic Societies

8 rows · 1 table(s) · 2024 D-PLACE 0 1 2 3 1 SEL 10 CCL 7 ext ▶

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0 Admin 0 — 1 table(s)

MMR D-PLACE - Dplace Ea Societies — 8 rows, 18 columns

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Field details — 18 fields (type, nulls, unique, samples)

Standards-Aligned Fields (11)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR, MMR, MMR, MMR, MMR
`society_id`	Society id	string	CCL	0%	8	Ei18, Ei19, Ei3, Ei4, Ei5
`society_name`	Society name	string	CCL	0%	8	Palaung, Chin, Burmese, Maras, Kachin
`language_glottocode`	Language glottocode	string	CCL	0%	8	shwe1236, asho1236, nucl1310, mara1382, kach1280
`language_name`	Language name	string	CCL	0%	1	, , , ,
`kinship_system`	Kinship system	string	CCL	0%	6	EA001:0; EA002:0; EA003:0; EA004:2; EA005:8, EA001:0;...
`marriage_pattern`	Marriage pattern	string	CCL	0%	6	EA006:1; EA007:8; EA008:2; EA009:2; EA010:10, EA006:1;...
`subsistence_pattern`	Subsistence pattern	string	CCL	0%	6	EA028:3; EA029:6; EA030:7; EA031:2; EA032:2, EA028:3;...
`political_complexity`	Political complexity	string	CCL	0%	7	EA033:2; EA034:1; EA035:NA, EA033:2; EA034:1; EA035:NA,...
`religion_importance`	Religion importance	string	CCL	0%	7	EA034:1; EA112:4, EA034:1; EA112:1, EA034:1; EA112:4,...
`residence_pattern`	Residence pattern	string	CCL	0%	4	EA011:1; EA012:10; EA013:2, EA011:1; EA012:8; EA013:2,...

Extension Fields (7) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_name`	country_name	string	0%	1	Myanmar, Myanmar, Myanmar, Myanmar, Myanmar
`dataset`	dataset	string	0%	1	EA, EA, EA, EA, EA
`region`	region	string	0%	1	, , , ,
`latitude`	latitude	float	0%	7	23.0, 22.0, 20.0, 22.0, 26.0
`longitude`	longitude	float	0%	7	97.0, 94.0, 95.0, 93.0, 97.0
`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

MMR Global Organized Crime Index MMR-OCINDEX Crime Index

1 rows · 1 table(s) · 2025 GI-TOC / ENACT 0 1 2 3 13 CCL 22 ext ▶

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0 Admin 0 — 1 table(s)

MMR Organized Crime Scores 2025 — 1 rows, 35 columns

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Field details — 139 fields (type, nulls, unique, samples)

Standards-Aligned Fields (13)

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	-

Extension Fields (22) — supplemental data preserved outside core SEL/CCL schema

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	-

Pending (104) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`iso3`	iso3	string	0%	1	MMR
`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	187
`oc_anti_money_laundering_2023`	oc_anti_money_laundering_2023	integer	0%	1	2
`oc_anti_money_laundering_2021`	oc_anti_money_laundering_2021	integer	0%	1	3
`oc_arms_trafficking_rank`	oc_arms_trafficking_rank	integer	0%	1	6
`oc_arms_trafficking_2023`	oc_arms_trafficking_2023	integer	0%	1	9
`oc_arms_trafficking_2021`	oc_arms_trafficking_2021	integer	0%	1	8
`oc_cannabis_trade_rank`	oc_cannabis_trade_rank	integer	0%	1	114
`oc_cannabis_trade_2023`	oc_cannabis_trade_2023	float	0%	1	4.5
`oc_cannabis_trade_2021`	oc_cannabis_trade_2021	float	0%	1	4.5
`oc_cocaine_trade_rank`	oc_cocaine_trade_rank	integer	0%	1	178
`oc_cocaine_trade_2023`	oc_cocaine_trade_2023	float	0%	1	3.5
`oc_cocaine_trade_2021`	oc_cocaine_trade_2021	float	0%	1	3.5
`oc_criminal_actors_rank`	oc_criminal_actors_rank	integer	0%	1	2
`oc_criminal_actors_2023`	oc_criminal_actors_2023	float	0%	1	8.6
`oc_criminal_actors_2021`	oc_criminal_actors_2021	float	0%	1	8.13
`oc_criminal_markets_rank`	oc_criminal_markets_rank	integer	0%	1	2
`oc_criminal_markets_2023`	oc_criminal_markets_2023	float	0%	1	7.7
`oc_criminal_markets_2021`	oc_criminal_markets_2021	float	0%	1	7.05
`oc_criminal_networks_rank`	oc_criminal_networks_rank	integer	0%	1	7
`oc_criminal_networks_2023`	oc_criminal_networks_2023	integer	0%	1	8
`oc_criminal_networks_2021`	oc_criminal_networks_2021	float	0%	1	7.5
`oc_criminality_rank`	oc_criminality_rank	integer	0%	1	1
`oc_criminality_2023`	oc_criminality_2023	float	0%	1	8.15
`oc_criminality_2021`	oc_criminality_2021	float	0%	1	7.59
`oc_cyber_dependent_crimes_rank`	oc_cyber_dependent_crimes_rank	integer	0%	1	15
+74 more pending fields — download the CSV/Parquet to see them all.

MMR World Values Survey MMR-WVS Attitudes Values

1 rows · 1 table(s) · 2022 World Values Survey 0 1 2 3 1 SEL 25 ext ▶

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0 Admin 0 — 1 table(s)

MMR WVS - Country Aggregates — 1 rows, 26 columns

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Field details — 26 fields (type, nulls, unique, samples)

Standards-Aligned Fields (1)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	MMR

Extension Fields (25) — supplemental data preserved outside core SEL/CCL schema

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

HERA · Human Entity Reference Atlas by Masego Inc

Build a download

Language	Place names	Share	Script
Burmese (mya)	47,950	99.8%	Myanmar (Burmese) +2
Thai (tha)	90	0.2%	Thai +1

Source	Type	Access
NGA GEOnet Names Server (GNS)	official_government	bulk_download
UNHCR Refugee Data Finder (UN High Commissioner for Refugees)	international_organization	api
USAID DHS Program (US Agency for International Development · Demographic and Health Surveys)	international_organization	api
Glottolog Language Catalog	academic	bulk_download
Global Data Lab	academic	api
GI-TOC / ENACT (Global Initiative Against Transnational Organized Crime · ENACT)	academic	bulk_download
World Values Survey	academic	metadata_catalog
World Bank Open Data	international_organization	api
D-PLACE (Database of Places, Language, Culture & Environment)	academic	bulk_download
LandScan Global (ORNL — Oak Ridge National Laboratory)	research_institution	earth_engine
GHS Urban Centre Database (Global Human Settlement · EU Joint Research Centre)	international_organization	bulk_download
OpenFactBook	community_compilation	bulk_download