Thailand

THA Thailand - Economic, Social, Environmental, Health THA-HDX-Thailand_-_Economic,_Social,_Enviro Indicators

87,417 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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THA Thailand - Economic, Social, Environmental, Health — 87,417 rows, 3,270 columns

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Field details — 3270 fields (type, nulls, unique, samples)

Extension Fields (3270) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	THA
`Fertilizer_consumption_pct_of_fertilizer_production`	Fertilizer_consumption_pct_of_fertilizer_production	float	0%	1	423.26635318055
`Fertilizer_consumption_kilograms_per_hectare_of_arable_land`	Fertilizer_consumption_kilograms_per_hectare_of_arable_land	float	0%	1	287.332398706679
`Agricultural_land_sq._km`	Agricultural_land_sq._km	float	0%	1	223760.0
`Agricultural_land_pct_of_land_area`	Agricultural_land_pct_of_land_area	float	0%	1	43.7980778641195
`Arable_land_hectares`	Arable_land_hectares	float	0%	1	15835200.0
`Arable_land_hectares_per_person`	Arable_land_hectares_per_person	float	0%	1	0.220846056343833
`Arable_land_pct_of_land_area`	Arable_land_pct_of_land_area	float	0%	1	30.9953218892521
`Land_under_cereal_production_hectares`	Land_under_cereal_production_hectares	float	0%	1	12544291.0
`Permanent_cropland_pct_of_land_area`	Permanent_cropland_pct_of_land_area	float	0%	1	11.2368611638513
`Rural_land_area_where_elevation_is_below_5_meters_sq._km`	Rural_land_area_where_elevation_is_below_5_meters_sq._km	float	0%	1	17671.4169857
`Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area`	Rural_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area	float	0%	1	3.4555076912689
`Forest_area_sq._km`	Forest_area_sq._km	float	0%	1	197650.0
`Forest_area_pct_of_land_area`	Forest_area_pct_of_land_area	float	0%	1	38.6873886746658
`Average_precipitation_in_depth_mm_per_year`	Average_precipitation_in_depth_mm_per_year	float	0%	1	1622.0
`Land_area_sq._km`	Land_area_sq._km	float	0%	1	510890.0
`Rural_land_area_sq._km`	Rural_land_area_sq._km	float	0%	1	491891.9109971
`Cereal_production_metric_tons`	Cereal_production_metric_tons	float	0%	1	38532088.18
`Crop_production_index_2014-2016_=_100`	Crop_production_index_2014-2016_=_100	float	0%	1	106.6
`Food_production_index_2014-2016_=_100`	Food_production_index_2014-2016_=_100	float	0%	1	104.2
`Livestock_production_index_2014-2016_=_100`	Livestock_production_index_2014-2016_=_100	float	0%	1	103.25
`Surface_area_sq._km`	Surface_area_sq._km	float	0%	1	513115.021
`Cereal_yield_kg_per_hectare`	Cereal_yield_kg_per_hectare	float	0%	1	3071.7
`Access_to_electricity_rural_pct_of_rural_population`	Access_to_electricity_rural_pct_of_rural_population	float	0%	1	100.0
`Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_`	Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_	float	0%	1	2.82043269411516
`Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal`	Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal	float	0%	1	90.37448086
`Agriculture_forestry_and_fishing_value_added_current_USusd`	Agriculture_forestry_and_fishing_value_added_current_USusd	float	0%	1	45865619933.0314
`Agriculture_forestry_and_fishing_value_added_pct_of_GDP`	Agriculture_forestry_and_fishing_value_added_pct_of_GDP	float	0%	1	8.7111266189882
`Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate`	Employment_in_agriculture_female_pct_of_female_employment_modeled_ILO_estimate	float	0%	1	24.8174803830863
`Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate`	Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate	float	0%	1	31.719704411814
+3240 more extension fields — download the CSV/Parquet to see them all.

THA Thailand - Health Indicators THA-HDX-Thailand_-_Health_Indicators Indicators

24,529 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

THA Thailand - Health Indicators — 24,529 rows, 17 columns

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Field details — 17 fields (type, nulls, unique, samples)

Extension Fields (17) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`GHO (CODE)`	GHO (CODE)	string	0%	68	AIR_7, MORT_100, NCD_BMI_PLUS1C, NCD_BMI_MINUS2C, NUT_CF_MMF
`GHO (DISPLAY)`	GHO (DISPLAY)	string	0%	68	Ambient air pollution attributable DALYs, Number of...
`GHO (URL)`	GHO (URL)	string	0%	66	https://www.who.int/data/gho/data/indicators/indicator-de...
`YEAR (DISPLAY)`	YEAR (DISPLAY)	string	0%	32	2018, 2002, 2014, 2013, 2019
`STARTYEAR`	STARTYEAR	string	0%	32	2018, 2002, 2014, 2013, 2019
`ENDYEAR`	ENDYEAR	string	0%	32	2018, 2002, 2014, 2013, 2019
`REGION (CODE)`	REGION (CODE)	string	0%	1	SEAR, SEAR, SEAR, SEAR, SEAR
`REGION (DISPLAY)`	REGION (DISPLAY)	string	0%	1	South-East Asia, South-East Asia, South-East Asia,...
`COUNTRY (CODE)`	COUNTRY (CODE)	string	0%	1	THA, THA, THA, THA, THA
`COUNTRY (DISPLAY)`	COUNTRY (DISPLAY)	string	0%	1	Thailand, Thailand, Thailand, Thailand, Thailand
`DIMENSION (TYPE)`	DIMENSION (TYPE)	string	10%	11	SEX, SEX, SEX, SEX, EDUCATIONLEVEL
`DIMENSION (CODE)`	DIMENSION (CODE)	string	10%	29	SEX_MLE, SEX_BTSX, SEX_BTSX, SEX_MLE,...
`DIMENSION (NAME)`	DIMENSION (NAME)	string	10%	28	Male, Both sexes, Both sexes, Male, None and primary education
`Numeric`	Numeric	string	13%	85	75590.488, 1484.11167, 20.421997, 8.4584892, 89.3
`Value`	Value	string	0%	90	75 590 [43 790-107 516], 1484.1, 20.4 [19.2-21.7], 8.5...
`Low`	Low	float	39%	60	43790.451, 19.194393, 7.2853938, 85.4, 181.4
`High`	High	float	39%	60	107516.042, 21.678594, 9.7346835, 92.2, 241.3

THA HDX HAPI Data for Thailand THA-HDX-HDX_HAPI_Data_for_Thailand Indicators

18,616 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

THA HDX HAPI Data for Thailand — 18,616 rows, 14 columns

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`origin_location_code`	origin_location_code	string	0%	5	AFG, AFG, AFG, AFG, AFG
`origin_has_hrp`	origin_has_hrp	string	0%	2	True, True, True, True, True
`origin_in_gho`	origin_in_gho	string	0%	2	True, True, True, True, True
`asylum_location_code`	asylum_location_code	string	0%	1	THA, THA, THA, THA, THA
`asylum_has_hrp`	asylum_has_hrp	string	0%	1	False, False, False, False, False
`asylum_in_gho`	asylum_in_gho	string	0%	1	False, False, False, False, False
`population_group`	population_group	string	0%	2	ASY, ASY, ASY, ASY, ASY
`gender`	gender	string	0%	3	f, f, f, f, f
`age_range`	age_range	string	0%	6	0-4, 5-11, 12-17, 18-59, 60+
`min_age`	min_age	string	0%	6	0, 5, 12, 18, 60
`max_age`	max_age	string	0%	5	4, 11, 17, 59, None
`population`	population	string	0%	26	0, 0, 0, 7, 0
`reference_period_start`	reference_period_start	string	0%	1	2020-01-01, 2020-01-01, 2020-01-01, 2020-01-01, 2020-01-01
`reference_period_end`	reference_period_end	string	0%	1	2020-12-31, 2020-12-31, 2020-12-31, 2020-12-31, 2020-12-31

THA Thailand - Education THA-HDX-Thailand_-_Education Indicators

14,762 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

THA Thailand - Education — 14,762 rows, 878 columns

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Field details — 878 fields (type, nulls, unique, samples)

Extension Fields (878) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	THA
`Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education	float	0%	1	2.47
`Barro-Lee:_Percentage_of_population_age_15-19_with_no_education`	Barro-Lee:_Percentage_of_population_age_15-19_with_no_education	float	0%	1	2.46
`Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education	float	0%	1	3.82
`Barro-Lee:_Percentage_of_population_age_15+_with_no_education`	Barro-Lee:_Percentage_of_population_age_15+_with_no_education	float	0%	1	3.44
`Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education	float	0%	1	2.47
`Barro-Lee:_Percentage_of_population_age_20-24_with_no_education`	Barro-Lee:_Percentage_of_population_age_20-24_with_no_education	float	0%	1	2.46
`Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education	float	0%	1	3.7
`Barro-Lee:_Percentage_of_population_age_25-29_with_no_education`	Barro-Lee:_Percentage_of_population_age_25-29_with_no_education	float	0%	1	4.07
`Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education	float	0%	1	4.1
`Barro-Lee:_Percentage_of_population_age_25+_with_no_education`	Barro-Lee:_Percentage_of_population_age_25+_with_no_education	float	0%	1	3.66
`Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education	float	0%	1	2.52
`Barro-Lee:_Percentage_of_population_age_30-34_with_no_education`	Barro-Lee:_Percentage_of_population_age_30-34_with_no_education	float	0%	1	2.91
`Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education	float	0%	1	1.75
`Barro-Lee:_Percentage_of_population_age_35-39_with_no_education`	Barro-Lee:_Percentage_of_population_age_35-39_with_no_education	float	0%	1	1.94
`Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education	float	0%	1	1.24
`Barro-Lee:_Percentage_of_population_age_40-44_with_no_education`	Barro-Lee:_Percentage_of_population_age_40-44_with_no_education	float	0%	1	1.37
`Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education	float	0%	1	2.58
`Barro-Lee:_Percentage_of_population_age_45-49_with_no_education`	Barro-Lee:_Percentage_of_population_age_45-49_with_no_education	float	0%	1	2.33
`Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education	float	0%	1	3.56
`Barro-Lee:_Percentage_of_population_age_50-54_with_no_education`	Barro-Lee:_Percentage_of_population_age_50-54_with_no_education	float	0%	1	3.1
`Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education	float	0%	1	3.95
`Barro-Lee:_Percentage_of_population_age_55-59_with_no_education`	Barro-Lee:_Percentage_of_population_age_55-59_with_no_education	float	0%	1	3.3
`Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education	float	0%	1	4.64
`Barro-Lee:_Percentage_of_population_age_60-64_with_no_education`	Barro-Lee:_Percentage_of_population_age_60-64_with_no_education	float	0%	1	3.83
`Barro-Lee:_Population_in_thousands_age_15-19_total`	Barro-Lee:_Population_in_thousands_age_15-19_total	float	0%	1	5245.0
`Barro-Lee:_Population_in_thousands_age_15-19_female`	Barro-Lee:_Population_in_thousands_age_15-19_female	float	0%	1	2597.0
`Barro-Lee:_Population_in_thousands_age_15+_total`	Barro-Lee:_Population_in_thousands_age_15+_total	float	0%	1	51912.0
`Barro-Lee:_Population_in_thousands_age_15+_female`	Barro-Lee:_Population_in_thousands_age_15+_female	float	0%	1	26746.0
`Barro-Lee:_Population_in_thousands_age_20-24_total`	Barro-Lee:_Population_in_thousands_age_20-24_total	float	0%	1	5360.0
+848 more extension fields — download the CSV/Parquet to see them all.

THA Thailand - Social Protection and Labor THA-HDX-Thailand_-_Social_Protection_and_La Indicators

9,401 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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THA Thailand - Social Protection And Labor — 9,401 rows, 1,067 columns

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Field details — 1067 fields (type, nulls, unique, samples)

Extension Fields (1067) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	THA
`Adequacy_of_benefits_in_extreme_poor_<usd2.15_a_day_pct_-All_Social_Protection_a`	Adequacy_of_benefits_in_extreme_poor_<usd2.15_a_day_pct_-All_Social_Protection_a	float	0%	1	14.1702576054903
`Adequacy_of_benefits_pct_-All_Social_Protection_and_Labor_-rural`	Adequacy_of_benefits_pct_-All_Social_Protection_and_Labor_-rural	float	0%	1	73.3922331259547
`Adequacy_of_benefits_pct_-All_Social_Protection_and_Labor_-urban`	Adequacy_of_benefits_pct_-All_Social_Protection_and_Labor_-urban	float	0%	1	81.4972070835447
`Adequacy_of_benefits_in_1st_quintile_poorest_pct_-All_Social_Protection_and_Labo`	Adequacy_of_benefits_in_1st_quintile_poorest_pct_-All_Social_Protection_and_Labo	float	0%	1	67.4578013753521
`Adequacy_of_benefits_in_2nd_quintile_pct_-All_Social_Protection_and_Labor_preT`	Adequacy_of_benefits_in_2nd_quintile_pct_-All_Social_Protection_and_Labor_preT	float	0%	1	70.4645821736462
`Adequacy_of_benefits_in_2nd_quintile_pct_-All_Social_Protection_and_Labor_-rural`	Adequacy_of_benefits_in_2nd_quintile_pct_-All_Social_Protection_and_Labor_-rural	float	0%	1	29.0197540385186
`Adequacy_of_benefits_in_2nd_quintile_pct_-All_Social_Protection_and_Labor`	Adequacy_of_benefits_in_2nd_quintile_pct_-All_Social_Protection_and_Labor	float	0%	1	44.3398046740306
`Adequacy_of_benefits_in_2nd_quintile_pct_-All_Social_Protection_and_Labor_-urban`	Adequacy_of_benefits_in_2nd_quintile_pct_-All_Social_Protection_and_Labor_-urban	float	0%	1	64.7062919379438
`Adequacy_of_benefits_in_3rd_quintile_pct_-All_Social_Protection_and_Labor_preT`	Adequacy_of_benefits_in_3rd_quintile_pct_-All_Social_Protection_and_Labor_preT	float	0%	1	60.5885875004644
`Adequacy_of_benefits_in_3rd_quintile_pct_-All_Social_Protection_and_Labor_-rural`	Adequacy_of_benefits_in_3rd_quintile_pct_-All_Social_Protection_and_Labor_-rural	float	0%	1	44.2476534654564
`Adequacy_of_benefits_in_3rd_quintile_pct_-All_Social_Protection_and_Labor`	Adequacy_of_benefits_in_3rd_quintile_pct_-All_Social_Protection_and_Labor	float	0%	1	61.5564916213638
`Adequacy_of_benefits_in_3rd_quintile_pct_-All_Social_Protection_and_Labor_-urban`	Adequacy_of_benefits_in_3rd_quintile_pct_-All_Social_Protection_and_Labor_-urban	float	0%	1	89.8777622071532
`Adequacy_of_benefits_in_4th_quintile_pct_-All_Social_Protection_and_Labor_preT`	Adequacy_of_benefits_in_4th_quintile_pct_-All_Social_Protection_and_Labor_preT	float	0%	1	62.0526366301106
`Adequacy_of_benefits_in_4th_quintile_pct_-All_Social_Protection_and_Labor_-rural`	Adequacy_of_benefits_in_4th_quintile_pct_-All_Social_Protection_and_Labor_-rural	float	0%	1	57.9125255042098
`Adequacy_of_benefits_in_4th_quintile_pct_-All_Social_Protection_and_Labor`	Adequacy_of_benefits_in_4th_quintile_pct_-All_Social_Protection_and_Labor	float	0%	1	83.4556010004489
`Adequacy_of_benefits_in_4th_quintile_pct_-All_Social_Protection_and_Labor_-urban`	Adequacy_of_benefits_in_4th_quintile_pct_-All_Social_Protection_and_Labor_-urban	float	0%	1	92.3515040474682
`Adequacy_of_benefits_in_5th_quintile_richest_pct_-All_Social_Protection_and_Labo`	Adequacy_of_benefits_in_5th_quintile_richest_pct_-All_Social_Protection_and_Labo	float	0%	1	78.4469630960978
`Average_per_capita_transfer_held_by_extreme_poor_<usd2.15_a_day_-All_Social_Prot`	Average_per_capita_transfer_held_by_extreme_poor_<usd2.15_a_day_-All_Social_Prot	float	0%	1	0.291666865348816
`Average_per_capita_transfer_-All_Social_Protection_and_Labor_-rural`	Average_per_capita_transfer_-All_Social_Protection_and_Labor_-rural	float	0%	1	11.8333665518774
`Average_per_capita_transfer_-All_Social_Protection_and_Labor`	Average_per_capita_transfer_-All_Social_Protection_and_Labor	float	0%	1	16.3414367821998
`Average_per_capita_transfer_-All_Social_Protection_and_Labor_-urban`	Average_per_capita_transfer_-All_Social_Protection_and_Labor_-urban	float	0%	1	20.5857601078902
`Average_per_capita_transfer_held_by_1st_quintile_poorest_-All_Social_Protection_`	Average_per_capita_transfer_held_by_1st_quintile_poorest_-All_Social_Protection_	float	0%	1	4.73302976860292
`Average_per_capita_transfer_held_by_2nd_quintile_-All_Social_Protection_and_Labo`	Average_per_capita_transfer_held_by_2nd_quintile_-All_Social_Protection_and_Labo	float	0%	1	7.72707278347403
`Average_per_capita_transfer_held_by_3rd_quintile_-All_Social_Protection_and_Labo`	Average_per_capita_transfer_held_by_3rd_quintile_-All_Social_Protection_and_Labo	float	0%	1	14.8784044813301
`Average_per_capita_transfer_held_by_4th_quintile_-All_Social_Protection_and_Labo`	Average_per_capita_transfer_held_by_4th_quintile_-All_Social_Protection_and_Labo	float	0%	1	21.2771379579
`Average_per_capita_transfer_held_by_5th_quintile_richest_-All_Social_Protection_`	Average_per_capita_transfer_held_by_5th_quintile_richest_-All_Social_Protection_	float	0%	1	33.3248055212988
`Benefits_incidence_in_extreme_poor_<usd2.15_a_day_pct_-All_Social_Protection_and`	Benefits_incidence_in_extreme_poor_<usd2.15_a_day_pct_-All_Social_Protection_and	float	0%	1	0.0
`Benefits_incidence_in_1st_quintile_poorest_pct_-All_Social_Protection_and_Labor_`	Benefits_incidence_in_1st_quintile_poorest_pct_-All_Social_Protection_and_Labor_	float	0%	1	2.37182064951307
`Benefits_incidence_in_2nd_quintile_pct_-All_Social_Protection_and_Labor_preT`	Benefits_incidence_in_2nd_quintile_pct_-All_Social_Protection_and_Labor_preT	float	0%	1	10.0990700653651
+1037 more extension fields — download the CSV/Parquet to see them all.

THA Thailand - Gender THA-HDX-Thailand_-_Gender Indicators

4,335 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

THA Thailand - Gender — 4,335 rows, 181 columns

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Field details — 181 fields (type, nulls, unique, samples)

Extension Fields (181) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	THA
`Firms_with_female_top_manager_pct_of_firms`	Firms_with_female_top_manager_pct_of_firms	float	0%	1	64.84489441
`Firms_with_female_participation_in_ownership_pct_of_firms`	Firms_with_female_participation_in_ownership_pct_of_firms	float	0%	1	64.44339752
`Literacy_rate_youth_female_pct_of_females_ages_15-24`	Literacy_rate_youth_female_pct_of_females_ages_15-24	float	0%	1	98.4300003051758
`Literacy_rate_youth_ages_15-24_gender_parity_index_GPI`	Literacy_rate_youth_ages_15-24_gender_parity_index_GPI	float	0%	1	1.0
`Literacy_rate_youth_male_pct_of_males_ages_15-24`	Literacy_rate_youth_male_pct_of_males_ages_15-24	float	0%	1	97.9400024414062
`Literacy_rate_adult_female_pct_of_females_ages_15_and_above`	Literacy_rate_adult_female_pct_of_females_ages_15_and_above	float	0%	1	91.4899978637695
`Literacy_rate_adult_male_pct_of_males_ages_15_and_above`	Literacy_rate_adult_male_pct_of_males_ages_15_and_above	float	0%	1	90.6699981689453
`School_enrollment_primary_gross_gender_parity_index_GPI`	School_enrollment_primary_gross_gender_parity_index_GPI	float	0%	1	0.992965281009674
`School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI`	School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI	float	0%	1	1.02751123905182
`School_enrollment_secondary_gross_gender_parity_index_GPI`	School_enrollment_secondary_gross_gender_parity_index_GPI	float	0%	1	1.05888855457306
`School_enrollment_tertiary_gross_gender_parity_index_GPI`	School_enrollment_tertiary_gross_gender_parity_index_GPI	float	0%	1	1.25606592688301
`School_enrollment_preprimary_female_pct_gross`	School_enrollment_preprimary_female_pct_gross	float	0%	1	74.3641738891602
`School_enrollment_preprimary_male_pct_gross`	School_enrollment_preprimary_male_pct_gross	float	0%	1	74.3750381469727
`Primary_completion_rate_female_pct_of_relevant_age_group`	Primary_completion_rate_female_pct_of_relevant_age_group	float	0%	1	106.242303607168
`Primary_completion_rate_male_pct_of_relevant_age_group`	Primary_completion_rate_male_pct_of_relevant_age_group	float	0%	1	107.863771915623
`Educational_attainment_at_least_completed_primary_population_25+_years_female_pc`	Educational_attainment_at_least_completed_primary_population_25+_years_female_pc	float	0%	1	71.6529489150172
`Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_`	Educational_attainment_at_least_completed_primary_population_25+_years_male_pct_	float	0%	1	79.7035194027619
`Educational_attainment_at_least_completed_primary_population_25+_years_total_pct`	Educational_attainment_at_least_completed_primary_population_25+_years_total_pct	float	0%	1	75.4452061182075
`Primary_education_pupils_pct_female`	Primary_education_pupils_pct_female	float	0%	1	48.52339
`School_enrollment_primary_female_pct_gross`	School_enrollment_primary_female_pct_gross	float	0%	1	99.9599469853848
`School_enrollment_primary_male_pct_gross`	School_enrollment_primary_male_pct_gross	float	0%	1	101.462596580922
`Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag`	Gross_intake_ratio_in_first_grade_of_primary_education_female_pct_of_relevant_ag	float	0%	1	96.75865
`Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_`	Gross_intake_ratio_in_first_grade_of_primary_education_male_pct_of_relevant_age_	float	0%	1	97.08458
`School_enrollment_primary_female_pct_net`	School_enrollment_primary_female_pct_net	float	0%	1	97.85243
`School_enrollment_primary_male_pct_net`	School_enrollment_primary_male_pct_net	float	0%	1	98.30077
`Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population`	Net_intake_rate_in_grade_1_female_pct_of_official_school-age_population	float	0%	1	63.36986
`Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population`	Net_intake_rate_in_grade_1_male_pct_of_official_school-age_population	float	0%	1	62.70631
`Persistence_to_grade_5_female_pct_of_cohort`	Persistence_to_grade_5_female_pct_of_cohort	float	0%	1	99.9496765136719
`Persistence_to_grade_5_male_pct_of_cohort`	Persistence_to_grade_5_male_pct_of_cohort	float	0%	1	97.5978622436523
+151 more extension fields — download the CSV/Parquet to see them all.

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

1,357 rows · 3 table(s) · 2026 NGA GEOnet Names Server (GNS) 0 1 2 3 5 SEL 12 CCL 33 ext ▶

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0 Admin 0 — 3 table(s)

THA Nga Gns - Language — 7 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	THA, THA, THA, THA, THA
`gns_language_code`	gns_language_code	string	CCL	0%	7	tha, lao, khm, mfa, eng
`gns_language_name`	gns_language_name	string	CCL	0%	7	Thai, Lao, Khmer, Malay, Pattani, English
`gns_toponym_count`	gns_toponym_count	integer	CCL	0%	7	489369, 95, 71, 23, 9
`gns_toponym_share_pct`	gns_toponym_share_pct	float	CCL	0%	7	99.9579, 0.0194, 0.0145, 0.0047, 0.0018
`gns_non_roman_toponym_count`	gns_non_roman_toponym_count	integer	CCL	0%	3	243586, 0, 30, 0, 0
`gns_dominant_script_code`	gns_dominant_script_code	string	CCL	0%	3	Thai, , Khmr, ,
`gns_dominant_script_name`	gns_dominant_script_name	string	CCL	0%	3	Thai, , Khmer, ,
`gns_script_count`	gns_script_count	integer	CCL	0%	3	2, 0, 1, 0, 0

THA Nga Gns - Summary — 1 rows, 29 columns

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Field details — 29 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	THA
`admin_level`	admin_level	integer	SEL	0%	1	0
`gns_country_name`	gns_country_name	string	SEL	0%	1	Thailand
`gns_language_count`	gns_language_count	integer	CCL	0%	1	7
`gns_script_count`	gns_script_count	integer	CCL	0%	1	3
`gns_endonym_share_pct`	gns_endonym_share_pct	float	CCL	0%	1	99.9985
`gns_non_roman_name_count`	gns_non_roman_name_count	integer	CCL	0%	1	243678

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

Field Name	Label	Type	Nulls	Unique	Samples
`gns_name_count`	gns_name_count	integer	0%	1	530474
`gns_feature_count`	gns_feature_count	integer	0%	1	250995
`gns_endonym_count`	gns_endonym_count	integer	0%	1	530466
`gns_exonym_count`	gns_exonym_count	integer	0%	1	8
`gns_source_build_date`	gns_source_build_date	string	0%	1	Wed, 05 Aug 2026
`gns_source_change_date`	gns_source_change_date	string	0%	1	2026-08-05
`gns_name_count_populated_places`	gns_name_count_populated_places	integer	0%	1	193137
`gns_feature_count_populated_places`	gns_feature_count_populated_places	integer	0%	1	87956
`gns_name_count_hydrographic`	gns_name_count_hydrographic	integer	0%	1	111388
`gns_feature_count_hydrographic`	gns_feature_count_hydrographic	integer	0%	1	53960
`gns_name_count_hypsographic`	gns_name_count_hypsographic	integer	0%	1	30795
`gns_feature_count_hypsographic`	gns_feature_count_hypsographic	integer	0%	1	13997
`gns_name_count_spot_features`	gns_name_count_spot_features	integer	0%	1	191140
`gns_feature_count_spot_features`	gns_feature_count_spot_features	integer	0%	1	93806
`gns_name_count_vegetation`	gns_name_count_vegetation	integer	0%	1	25
`gns_feature_count_vegetation`	gns_feature_count_vegetation	integer	0%	1	24
`gns_name_count_transportation_networks`	gns_name_count_transportation_networks	integer	0%	1	48
`gns_feature_count_transportation_networks`	gns_feature_count_transportation_networks	integer	0%	1	42
`gns_name_count_areas_localities`	gns_name_count_areas_localities	integer	0%	1	58
`gns_feature_count_areas_localities`	gns_feature_count_areas_localities	integer	0%	1	29
`gns_name_count_administrative_regions`	gns_name_count_administrative_regions	integer	0%	1	3883
`gns_feature_count_administrative_regions`	gns_feature_count_administrative_regions	integer	0%	1	1181

THA Nga Gns - Admin Crosswalk — 1,349 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	THA, THA, THA, THA, THA

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

Field Name	Label	Type	Nulls	Unique	Samples
`gns_ufi`	gns_ufi	integer	0%	100	415786, -3232491, 11324555, -3246714, -3246738
`admin_designation`	admin_designation	string	0%	2	ADM1, ADM1, ADM1, ADM1, ADM1
`gns_bgn_name`	gns_bgn_name	string	0%	100	Amnat Charoen, Ang Thong, Bueng Kan, Buri Ram, Chachoengsao
`gns_local_name`	gns_local_name	string	0%	100	จังหวัดอำนาจเจริญ, จังหวัดอ่างทอง, จังหวัดบึงกาฬ,...
`iso_3166_2`	iso_3166_2	string	0%	77	TH-37, TH-15, TH-38, TH-31, TH-24
`parent_code`	parent_code	string	0%	77	TH-37, TH-15, TH-38, TH-31, TH-24
`gns_prominence_band`	gns_prominence_band	integer	0%	3	9, 9, 3, 9, 3
`latitude`	latitude	float	0%	93	15.916667, 14.6125, 18.1625, 14.85, 13.629167
`longitude`	longitude	float	0%	91	104.75, 100.358333, 103.75, 102.991667, 101.416667
`gns_mgrs`	gns_mgrs	string	0%	100	48PVC7324159734, 47PPS4630315905, 48QUF6778508614,...
`name_variant_count`	name_variant_count	integer	0%	12	4, 6, 4, 8, 8

THA HDX COD — Population Statistics (OCHA/UNFPA) THA-COD_PS Census Derived Population

1,006 rows · 3 table(s) · 2023 HDX COD — Population Statistics (OCHA/UNFPA) 0 1 2 3 15 SEL ▶

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

0 Admin 0 — 1 table(s)

THA Cod Ps - Tha Codps (admin_0) — 1 rows, 59 columns

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Field details — 59 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`pcode`	Admin code	string	SEL	0%	1	TH
`region_name`	Region name	string	SEL	0%	1	Thailand
`F_TL`	Female population	integer	SEL	0%	1	35455997
`M_TL`	Male population	integer	SEL	0%	1	33938765
`T_TL`	Total population	integer	SEL	0%	1	69394762

Pending (54) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`admin_level`	Admin level	string	0%	1	admin_0
`year`	Reference year	integer	0%	1	2023
`year`	year	integer	0%	1	2023
`F_00_04`	Female population age 0-4	integer	0%	1	1773335
`F_05_09`	Female population age 5-9	integer	0%	1	1828335
`F_10_14`	Female population age 10-14	integer	0%	1	1838898
`F_15_19`	Female population age 15-19	integer	0%	1	1924036
`F_20_24`	Female population age 20-24	integer	0%	1	2131537
`F_25_29`	Female population age 25-29	integer	0%	1	2506866
`F_30_34`	Female population age 30-34	integer	0%	1	2481079
`F_35_39`	Female population age 35-39	integer	0%	1	2434471
`F_40_44`	Female population age 40-44	integer	0%	1	2731092
`F_45_49`	Female population age 45-49	integer	0%	1	2760029
`F_50_54`	Female population age 50-54	integer	0%	1	2734093
`F_55_59`	Female population age 55-59	integer	0%	1	2655430
`F_60_64`	Female population age 60-64	integer	0%	1	2376889
`F_65_69`	Female population age 65-69	integer	0%	1	1919154
`F_70_74`	Female population age 70-74	integer	0%	1	1365210
`F_75_79`	Female population age 75-79	integer	0%	1	893086
`F_80Plus`	F_80Plus	integer	0%	1	1102457
`M_00_04`	Male population age 0-4	integer	0%	1	1864486
`M_05_09`	Male population age 5-9	integer	0%	1	1921012
`M_10_14`	Male population age 10-14	integer	0%	1	1930241
`M_15_19`	Male population age 15-19	integer	0%	1	2013094
`M_20_24`	Male population age 20-24	integer	0%	1	2214379
`M_25_29`	Male population age 25-29	integer	0%	1	2585561
`M_30_34`	Male population age 30-34	integer	0%	1	2528428
`M_35_39`	Male population age 35-39	integer	0%	1	2429627
`M_40_44`	Male population age 40-44	integer	0%	1	2709313
`M_45_49`	Male population age 45-49	integer	0%	1	2698928
+24 more pending fields — download the CSV/Parquet to see them all.

1 Admin 1 — 1 table(s)

THA Cod Ps - Tha Codps (admin_1) — 77 rows, 59 columns

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Field details — 59 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`pcode`	Admin code	string	SEL	0%	77	TH37, TH15, TH10, TH38, TH31
`region_name`	Region name	string	SEL	0%	77	Amnat Charoen, Ang Thong, Bangkok, Bueng Kan, Buri Ram
`F_TL`	Female population	integer	SEL	0%	77	91583, 106897, 5883668, 143647, 459143
`M_TL`	Male population	integer	SEL	0%	77	88146, 94295, 5595670, 140084, 429215
`T_TL`	Total population	integer	SEL	0%	77	179729, 201192, 11479338, 283731, 888358

Pending (54) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`admin_level`	Admin level	string	0%	1	admin_1, admin_1, admin_1, admin_1, admin_1
`year`	Reference year	integer	0%	1	2023, 2023, 2023, 2023, 2023
`year`	year	integer	0%	1	2023, 2023, 2023, 2023, 2023
`F_00_04`	Female population age 0-4	integer	0%	77	5736, 4955, 224135, 10757, 31742
`F_05_09`	Female population age 5-9	integer	0%	77	6171, 5111, 220157, 11128, 33336
`F_10_14`	Female population age 10-14	integer	0%	77	6527, 5641, 227055, 10252, 32723
`F_15_19`	Female population age 15-19	integer	0%	77	4989, 4825, 309234, 7250, 23875
`F_20_24`	Female population age 20-24	integer	0%	77	2724, 3872, 490628, 4467, 13796
`F_25_29`	Female population age 25-29	integer	0%	77	3481, 4670, 588958, 6267, 16872
`F_30_34`	Female population age 30-34	integer	0%	77	4388, 5100, 538011, 8206, 21628
`F_35_39`	Female population age 35-39	integer	0%	77	5903, 5283, 473289, 9430, 26350
`F_40_44`	Female population age 40-44	integer	0%	77	7140, 6698, 496749, 10360, 31540
`F_45_49`	Female population age 45-49	integer	0%	77	6936, 8339, 463673, 10701, 33494
`F_50_54`	Female population age 50-54	integer	0%	77	7354, 8985, 433726, 11209, 34564
`F_55_59`	Female population age 55-59	integer	0%	76	7547, 9812, 391030, 11195, 37347
`F_60_64`	Female population age 60-64	integer	0%	77	7045, 8817, 336248, 10417, 37360
`F_65_69`	Female population age 65-69	integer	0%	77	5917, 7808, 251431, 8704, 31043
`F_70_74`	Female population age 70-74	integer	0%	77	4062, 6763, 178449, 5481, 21615
`F_75_79`	Female population age 75-79	integer	0%	77	2715, 4516, 109142, 3740, 14555
`F_80Plus`	F_80Plus	integer	0%	77	2948, 5702, 151753, 4083, 17303
`M_00_04`	Male population age 0-4	integer	0%	77	6082, 5157, 229607, 11153, 33014
`M_05_09`	Male population age 5-9	integer	0%	77	6527, 5623, 240164, 11725, 35174
`M_10_14`	Male population age 10-14	integer	0%	77	6719, 5902, 241414, 10749, 34299
`M_15_19`	Male population age 15-19	integer	0%	77	5543, 5511, 326826, 7530, 25232
`M_20_24`	Male population age 20-24	integer	0%	77	3309, 4376, 457686, 5080, 15506
`M_25_29`	Male population age 25-29	integer	0%	77	3690, 5290, 566975, 6725, 17546
`M_30_34`	Male population age 30-34	integer	0%	77	4256, 5128, 540221, 7963, 20332
`M_35_39`	Male population age 35-39	integer	0%	77	5503, 5068, 494802, 9038, 24021
`M_40_44`	Male population age 40-44	integer	0%	76	7002, 6321, 498461, 10441, 29117
`M_45_49`	Male population age 45-49	integer	0%	77	7142, 7461, 463225, 10263, 31090
+24 more pending fields — download the CSV/Parquet to see them all.

2 Admin 2 — 1 table(s)

THA Cod Ps - Tha Codps (admin_2) — 928 rows, 58 columns

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Field details — 58 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`pcode`	Admin code	string	SEL	0%	100	TH3702, TH3706, TH3707, TH3701, TH3703
`region_name`	Region name	string	SEL	0%	100	Chanuman, Hua Taphan, Lue Amnat, Mueang Amnat Charoen,...
`F_TL`	Female population	string	SEL	0%	100	12,501, 11,437, 8,975, 32,969, 11,917
`M_TL`	Male population	string	SEL	0%	100	12,488, 10,683, 8,435, 31,637, 11,873
`T_TL`	Total population	string	SEL	0%	100	24,989, 22,120, 17,410, 64,606, 23,790

Pending (53) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`admin_level`	Admin level	string	0%	1	admin_2, admin_2, admin_2, admin_2, admin_2
`year`	Reference year	integer	0%	1	2023, 2023, 2023, 2023, 2023
`F_00_04`	Female population age 0-4	string	0%	99	931, 689, 555, 1,924, 825
`F_05_09`	Female population age 5-9	string	0%	100	1,050, 716, 562, 2,047, 912
`F_10_14`	Female population age 10-14	string	0%	100	1,043, 713, 606, 2,323, 946
`F_15_19`	Female population age 15-19	string	0%	98	699, 529, 436, 1,929, 677
`F_20_24`	Female population age 20-24	string	0%	97	408, 253, 231, 1,098, 382
`F_25_29`	Female population age 25-29	string	0%	98	544, 345, 289, 1,321, 509
`F_30_34`	Female population age 30-34	string	0%	98	693, 466, 375, 1,645, 598
`F_35_39`	Female population age 35-39	string	0%	100	832, 682, 548, 2,168, 835
`F_40_44`	Female population age 40-44	string	0%	100	948, 858, 704, 2,666, 927
`F_45_49`	Female population age 45-49	string	0%	100	855, 865, 697, 2,654, 852
`F_50_54`	Female population age 50-54	string	0%	98	942, 949, 715, 2,702, 887
`F_55_59`	Female population age 55-59	string	0%	99	988, 1,043, 739, 2,612, 938
`F_60_64`	Female population age 60-64	string	0%	99	838, 1,012, 693, 2,532, 792
`F_65_69`	Female population age 65-69	string	0%	99	654, 950, 680, 2,015, 640
`F_70_74`	Female population age 70-74	string	0%	98	465, 590, 484, 1,405, 473
`F_75_79`	Female population age 75-79	string	0%	97	280, 389, 319, 922, 350
`F_80Plus`	F_80Plus	string	0%	100	331, 388, 342, 1,006, 374
`M_00_04`	Male population age 0-4	string	0%	97	992, 731, 554, 2,000, 947
`M_05_09`	Male population age 5-9	string	0%	100	1,045, 792, 604, 2,194, 964
`M_10_14`	Male population age 10-14	string	0%	99	1,048, 785, 629, 2,348, 971
`M_15_19`	Male population age 15-19	string	0%	98	809, 586, 486, 2,118, 739
`M_20_24`	Male population age 20-24	string	0%	100	525, 311, 259, 1,342, 439
`M_25_29`	Male population age 25-29	string	0%	98	586, 335, 301, 1,408, 516
`M_30_34`	Male population age 30-34	string	0%	100	673, 437, 354, 1,588, 592
`M_35_39`	Male population age 35-39	string	0%	99	809, 579, 511, 2,039, 761
`M_40_44`	Male population age 40-44	string	0%	99	942, 767, 717, 2,634, 945
`M_45_49`	Male population age 45-49	string	0%	98	890, 852, 694, 2,737, 905
`M_50_54`	Male population age 50-54	string	0%	100	940, 908, 683, 2,626, 828
+23 more pending fields — download the CSV/Parquet to see them all.

THA Thailand - Human Development Indicators THA-HDX-Thailand_-_Human_Development_Indica Indicators

965 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

THA Thailand - Human Development Indicators — 965 rows, 49 columns

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Field details — 49 fields (type, nulls, unique, samples)

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

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	THA
`eys`	eys	float	0%	1	15.359
`eys_f`	eys_f	float	0%	1	15.501
`eys_m`	eys_m	float	0%	1	15.224
`gdi_group`	gdi_group	float	0%	1	1.0
`gii_rank`	gii_rank	float	0%	1	73.0
`gni_pc_f`	gni_pc_f	float	0%	1	18716.639
`gni_pc_m`	gni_pc_m	float	0%	1	22518.74
`gnipc`	gnipc	float	0%	1	20569.902
`hdi_f`	hdi_f	float	0%	1	0.802
`hdi_m`	hdi_m	float	0%	1	0.795
`hdi_rank`	hdi_rank	float	0%	1	76.0
`ineq_edu`	ineq_edu	float	0%	1	15.954
`ineq_inc`	ineq_inc	float	0%	1	21.71
`ineq_le`	ineq_le	float	0%	1	7.34
`le`	le	float	0%	1	76.412
`le_f`	le_f	float	0%	1	80.861
`le_m`	le_m	float	0%	1	72.161
`lfpr_f`	lfpr_f	float	0%	1	60.61
`lfpr_m`	lfpr_m	float	0%	1	76.61
`loss`	loss	float	0%	1	15.163
`mf`	mf	float	0%	1	11.854
`mmr`	mmr	float	0%	1	28.6
`abr`	abr	float	0%	1	26.145
`co2_prod`	co2_prod	float	0%	1	3.682
`coef_ineq`	coef_ineq	float	0%	1	15.001
`mys`	mys	float	0%	1	9.04
`mys_f`	mys_f	float	0%	1	8.87
`mys_m`	mys_m	float	0%	1	9.23
`pop_total`	pop_total	float	0%	1	71.702
+19 more extension fields — download the CSV/Parquet to see them all.

THA Thailand - Risk Assessment Indicators THA-HDX-Thailand_-_Risk_Assessment_Indicato Indicators

928 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

THA Thailand - Risk Assessment Indicators — 928 rows, 8 columns

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`ADM2_PCODE`	ADM2_PCODE	string	0%	100	TH1001, TH1002, TH1003, TH1004, TH1005
`ADM_PCODE`	ADM_PCODE	string	0%	100	TH1001, TH1002, TH1003, TH1004, TH1005
`female_pop`	female_pop	string	0%	100	45959, 77519, 111065, 41532, 170807
`children_u5`	children_u5	string	0%	98	1925, 4219, 12804, 1885, 12644
`female_u5`	female_u5	string	0%	100	963, 2004, 6172, 933, 6183
`elderly`	elderly	string	0%	100	13718, 19906, 24037, 10824, 29932
`pop_u15`	pop_u15	string	0%	100	8093, 15963, 38905, 7767, 38617
`female_u15`	female_u15	string	0%	100	4003, 7775, 18889, 3813, 18844

THA Thailand - Urban Development THA-HDX-Thailand_-_Urban_Development Indicators

621 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

THA Thailand - Urban Development — 621 rows, 18 columns

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	THA
`Urban_land_area_where_elevation_is_below_5_meters_sq._km`	Urban_land_area_where_elevation_is_below_5_meters_sq._km	float	0%	1	4007.04395499
`Urban_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area`	Urban_land_area_where_elevation_is_below_5_meters_pct_of_total_land_area	float	0%	1	0.783546176117354
`Urban_land_area_sq._km`	Urban_land_area_sq._km	float	0%	1	19506.66092189
`Access_to_electricity_urban_pct_of_urban_population`	Access_to_electricity_urban_pct_of_urban_population	float	0%	1	100.0
`PM2.5_air_pollution_mean_annual_exposure_micrograms_per_cubic_meter`	PM2.5_air_pollution_mean_annual_exposure_micrograms_per_cubic_meter	float	0%	1	31.0072016277159
`PM2.5_air_pollution_population_exposed_to_levels_exceeding_WHO_guideline_value_p`	PM2.5_air_pollution_population_exposed_to_levels_exceeding_WHO_guideline_value_p	float	0%	1	100.0
`Population_density_people_per_sq._km_of_land_area`	Population_density_people_per_sq._km_of_land_area	float	0%	1	140.348088629646
`Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_`	Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_	float	0%	1	14.6506060086
`Population_living_in_slums_pct_of_urban_population`	Population_living_in_slums_pct_of_urban_population	float	0%	1	2.0
`Population_in_largest_city`	Population_in_largest_city	float	0%	1	11391704.0
`Population_in_the_largest_city_pct_of_urban_population`	Population_in_the_largest_city_pct_of_urban_population	float	0%	1	25.3279557460735
`Population_in_urban_agglomerations_of_more_than_1_million`	Population_in_urban_agglomerations_of_more_than_1_million	float	0%	1	15520484.0
`Population_in_urban_agglomerations_of_more_than_1_million_pct_of_total_populatio`	Population_in_urban_agglomerations_of_more_than_1_million_pct_of_total_populatio	float	0%	1	21.6706418441487
`Mortality_caused_by_road_traffic_injury_per_100000_population`	Mortality_caused_by_road_traffic_injury_per_100000_population	float	0%	1	32.2
`Urban_population_growth_annual_pct`	Urban_population_growth_annual_pct	float	0%	1	1.47434839627653
`Urban_population`	Urban_population	float	0%	1	44340234.0
`Urban_population_pct_of_total_population`	Urban_population_pct_of_total_population	float	0%	1	61.8689338391321

THA Thailand - Demographic, Health, Education and Tran THA-HDX-Thailand_-_Demographic,_Health,_Edu Indicators

354 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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

0 Admin 0 — 1 table(s)

THA Thailand - Demographic, Health, Education And Tran — 354 rows, 11 columns

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`category`	category	string	0%	8	Streets, Streets, Crime, Crime, City prosperity
`indicator`	indicator	string	0%	32	composite_street_connectivity_index_city_core,...
`indicator_friendly`	indicator_friendly	string	0%	32	Composite Street Connectivity Index – city core, Road...
`type_data`	type_data	string	0%	5	index, n, 000 population, 000 population, p
`latitude`	latitude	string	0%	4	13.749999, 15, n, n, 13.749999
`longitude`	longitude	string	0%	4	100.516645, 100, 15, 15, 100.516645
`region_id`	region_id	string	0%	2	789, 789, 100, 100, 789
`country_id`	country_id	string	0%	2	TH, TH, 789, 789, TH
`name`	name	string	0%	4	Bangkok, Thailand, TH, TH, Bangkok
`year`	year	string	0%	29	2013, 2009, Thailand, Thailand, 2012
`value`	value	string	0%	98	0.475, 35, 2000, 1999, 0.794

THA Global Data Lab THA-GDL Development Indices

204 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.

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

1 Admin 1 — 1 table(s)

THA GDL - Subnational Indices — 204 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	THA, THA, THA, THA, THA
`region_code`	Admin code	string	SEL	100%	-	-
`region_name`	Admin name	string	SEL	0%	6	Total, Bangkok, Central, North, Northeast
`human_development_index`	Human development index	float	SEL	0%	81	0.626, 0.681, 0.629, 0.612, 0.611
`health_index`	Health index	float	SEL	0%	61	0.753, 0.748, 0.762, 0.744, 0.754
`education_index`	Education index	float	SEL	0%	90	0.487, 0.599, 0.481, 0.456, 0.463
`income_index`	Income index	float	SEL	0%	63	0.671, 0.703, 0.68, 0.674, 0.651
`life_expectancy`	Life expectancy	float	SEL	0%	88	68.92, 68.65, 69.53, 68.35, 69.02
`mean_years_schooling`	Mean years schooling	float	SEL	0%	99	7.301, 10.07, 7.439, 6.238, 6.578

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

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

THA LandScan Global (ORNL) THA-LANDSCAN Modeled Population

132 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)

THA 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	THA
`admin_level`	Admin level	string	SEL	0%	1	admin_0
`admin_name`	Admin name	string	SEL	0%	1	Thailand
`admin_code`	Admin code	string	SEL	0%	1	76911100B81675122338640
`area_sqkm`	Area sqkm	float	SEL	0%	1	514957.0226
`pop_2024`	Population count	integer	SEL	0%	1	69749656
`pop_density_2024`	Population density	float	SEL	0%	1	135.45

1 Admin 1 — 1 table(s)

THA LandScan - Population Admin1 (admin_1) — 77 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	THA, THA, THA, THA, THA
`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%	77	Bangkok, Nakhon Ratchasima Province, Samut Prakan...
`admin_code`	Admin code	string	SEL	0%	77	36821470B28205534186964, 36821470B25997690360286,...
`area_sqkm`	Area sqkm	float	SEL	0%	77	1571.5835, 20731.7405, 953.0656, 10737.0639, 22684.016
`pop_2024`	Population count	integer	SEL	0%	77	9146400, 2570832, 2277166, 1790185, 1738047
`pop_density_2024`	Population density	float	SEL	0%	77	5819.86, 124.0, 2389.31, 166.73, 76.62

Locality Locality — 1 table(s)

THA LandScan - Cities (locality) — 54 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	THA, THA, THA, THA, THA
`admin_level`	Admin level	string	SEL	0%	1	locality, locality, locality, locality, locality
`admin_name`	Admin name	string	SEL	0%	54	Bangkok, Chiang Mai, Chon Buri, Phuket, Hat Yai
`admin_code`	Admin code	integer	SEL	0%	54	2315, 173, 2790, 1645, 3429
`area_sqkm`	Area sqkm	float	SEL	0%	54	2680.9854, 223.7987, 168.9823, 123.1973, 80.4747
`pop_2024`	Population count	integer	SEL	0%	54	14045746, 409776, 339021, 313320, 272045
`pop_density_2024`	Population density	float	SEL	0%	54	5239.02, 1831.0, 2006.25, 2543.24, 3380.5

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%	54	19048032, 692242, 263106, 462804, 436777
`landscan_vs_ghs_ratio`	landscan_vs_ghs_ratio	float	0%	52	0.737, 0.592, 1.289, 0.677, 0.623

THA World Bank Open Data THA-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)

THA 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	TH, TH, TH, TH, TH
`population_count`	Population count	float	SEL	2%	65	26851747.0, 27650334.0, 28481040.0, 29342322.0, 30232141.0
`life_expectancy`	Life expectancy	float	SEL	3%	64	50.608, 51.065, 51.444, 51.988, 52.539
`gdp_per_capita_usd`	Gdp per capita usd	float	SEL	2%	65	102.814571454958, 109.728794269464, 116.179493337844,...
`literacy_rate_pct`	Literacy rate percent	float	SEL	85%	10	87.9800033569336, 92.6500015258789, 93.5100021362305,...
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	3%	64	146.6, 141.7, 136.9, 132.2, 127.5
`poverty_headcount_pct`	Poverty headcount percent	float	SEL	61%	26	65.2, 58.0, 50.0, 42.5, 35.4

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	Thailand, Thailand, Thailand, Thailand, Thailand
`year`	year	integer	0%	66	1960, 1961, 1962, 1963, 1964

THA 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	TH, TH, TH, TH, TH
`life_expectancy`	Life expectancy	float	SEL	3%	64	50.608, 51.065, 51.444, 51.988, 52.539
`infant_mortality_per_1000`	Infant mortality per 1000	float	SEL	3%	64	57.2, 56.5, 55.7, 54.8, 53.8
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	3%	64	146.6, 141.7, 136.9, 132.2, 127.5
`maternal_mortality_per_100k`	Maternal mortality per 100k	float	SEL	41%	23	88.0, 78.0, 72.0, 67.0, 64.0
`fertility_rate`	Fertility rate	float	SEL	3%	64	6.325, 6.324, 6.331, 6.342, 6.309
`birth_rate_per_1000`	Birth rate per 1000	float	SEL	3%	64	43.803, 43.582, 43.397, 43.23, 42.764
`death_rate_per_1000`	Death rate per 1000	float	SEL	3%	64	14.971, 14.608, 14.299, 13.896, 13.486
`physicians_per_1000`	Physicians per 1000	float	SEL	56%	28	0.129, 0.14, 0.121, 0.147, 0.16
`hospital_beds_per_1000`	Hospital beds per 1000	float	SEL	50%	29	0.740034878253937, 1.13730001449585, 1.11189997196198,...
`vaccination_rate_pct`	Vaccination rate percent	float	SEL	32%	19	49.0, 52.0, 49.0, 49.0, 53.0
`health_expenditure_pct_gdp`	Health expenditure percent gdp	float	SEL	64%	24	3.10125351, 3.02623773, 3.334723, 3.24312782, 3.13893151

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	Thailand, Thailand, Thailand, Thailand, Thailand
`year`	year	integer	0%	66	1960, 1961, 1962, 1963, 1964

THA UNHCR Refugee Data Finder THA-UNHCR Migration

87 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)

THA UNHCR - Hosted Populations — 51 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%	-	-

THA UNHCR - Origin Populations — 36 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%	-	-

THA Glottolog Language Catalog THA-GLOTTOLOG Language

83 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)

THA Glottolog - Languages — 83 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%	83	aheu1239, akeu1235, akha1245, bank1251, bisu1244
`name`	Name	string	CCL	0%	83	Thavung, Akeu, Akha, Ban Khor Sign Language, Bisu
`iso639_3`	Iso639 3	string	CCL	2%	81	thm, aeu, ahk, bfk, bzi
`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	aust1305, sino1245, sino1245, sign1238, sino1245
`parent_name`	Parent name	string	CCL	100%	-	-
`parent_glottocode`	Parent glottocode	string	CCL	0%	54	chut1252, akeu1236, akha1246, deaf1237, bisu1246
`endangerment_status`	Endangerment status	string	CCL	100%	-	-
`country_codes`	Country codes	string	SEL+	0%	20	['LA', 'TH'], ['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%	11	0, 0, 2, 0, 0

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

Field Name	Label	Type	Nulls	Unique	Samples
`latitude`	latitude	float	0%	83	17.7655, 22.1959, 21.2309, 16.911, 20.8542
`longitude`	longitude	float	0%	83	104.229, 101.0823, 100.964, 103.296, 99.9862
`classification`	classification	string	0%	1	[], [], [], [], []

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

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

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

Locality Locality — 1 table(s)

THA GHS-UCDB - Cities (locality) — 54 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%	54	Bangkok, Chiang Mai, Phuket, Hat Yai, Lop Buri
`country_code`	Country code	string	SEL	0%	1	THA, THA, THA, THA, THA
`population`	Population count	integer	SEL	0%	54	19048032, 692242, 462804, 436777, 422600

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

Field Name	Label	Type	Nulls	Unique	Samples
`city_id`	city_id	integer	0%	54	2315, 173, 1645, 3429, 2391
`name_alternates`	name_alternates	string	100%	-	-
`country_name`	country_name	string	0%	1	Thailand, Thailand, Thailand, Thailand, Thailand
`population_year`	population_year	integer	0%	1	2025, 2025, 2025, 2025, 2025
`latitude`	latitude	string	100%	-	-
`longitude`	longitude	string	100%	-	-
`region`	region	string	100%	-	-

THA OpenFactBook THA-OPENFACTBOOK Country Profile

16 rows · 16 table(s) · 2024 OpenFactBook 0 1 2 3 99 SEL 5 CCL 650 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 — 16 table(s)

THA 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	6.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric`	Mobile subscriptions per 100	float	SEL	0%	1	161.0
`internet_country_code_text`	Internet country code text	string	SEL+	0%	1	.th
`internet_users_percent_of_population_numeric`	Internet penetration percent	float	SEL	0%	1	90.0
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric`	Broadband subscriptions per 100	float	SEL	0%	1	16.0
`country_code`	Country code	string	SEL	0%	1	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`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	4.087 million (2023 est.)
`telephones_fixed_lines_total_subscriptions_numeric`	telephones_fixed_lines_total_subscriptions_numeric	float	0%	1	4.087
`telephones_fixed_lines_subscriptions_per_100_inhabitants_text`	telephones_fixed_lines_subscriptions_per_100_inhabitants_text	string	0%	1	6 (2023 est.)
`telephones_mobile_cellular_total_subscriptions_text`	telephones_mobile_cellular_total_subscriptions_text	string	0%	1	115 million (2024 est.)
`telephones_mobile_cellular_total_subscriptions_numeric`	telephones_mobile_cellular_total_subscriptions_numeric	float	0%	1	115.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_text`	telephones_mobile_cellular_subscriptions_per_100_inhabitants_text	string	0%	1	161 (2024 est.)
`broadcast_media_text`	broadcast_media_text	string	0%	1	26 digital TV stations and 6 terrestrial TV stations...
`broadcast_media_numeric`	broadcast_media_numeric	float	0%	1	26.0
`internet_users_percent_of_population_text`	internet_users_percent_of_population_text	string	0%	1	90% (2023 est.)
`broadband_fixed_subscriptions_total_text`	broadband_fixed_subscriptions_total_text	string	0%	1	11.5 million (2023 est.)
`broadband_fixed_subscriptions_total_numeric`	broadband_fixed_subscriptions_total_numeric	float	0%	1	11.5
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text`	broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text	string	0%	1	16 (2023 est.)
`source_section`	source_section	string	0%	1	Communications
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/th.json

THA OpenFactBook - Economy — 1 rows, 153 columns

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Field details — 159 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	21700.0
`gdp_official_exchange_rate_numeric`	Gdp total usd	float	SEL	0%	1	526.411
`population_below_poverty_line_numeric`	Poverty headcount percent	float	SEL	0%	1	5.4
`country_code`	Country code	string	SEL	0%	1	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (153) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`economic_overview_text`	economic_overview_text	string	0%	1	upper middle-income Southeast Asian economy; substantial...
`economic_overview_numeric`	economic_overview_numeric	float	0%	1	4.0
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text`	Real gdp purchasing power parity 2024 (text)	string	0%	1	$1.558 trillion (2024 est.)
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_numeric`	Real gdp purchasing power parity 2024 (numeric)	float	0%	1	1.558
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text`	Real gdp purchasing power parity 2023 (text)	string	0%	1	$1.519 trillion (2023 est.)
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_numeric`	Real gdp purchasing power parity 2023 (numeric)	float	0%	1	1.519
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text`	Real gdp purchasing power parity 2022 (text)	string	0%	1	$1.489 trillion (2022 est.)
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_numeric`	Real gdp purchasing power parity 2022 (numeric)	float	0%	1	1.489
`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	2.5% (2024 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric`	Real gdp growth rate 2024 (numeric)	float	0%	1	2.5
`real_gdp_growth_rate_real_gdp_growth_rate_2023_text`	Real gdp growth rate 2023 (text)	string	0%	1	2% (2023 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric`	Real gdp growth rate 2023 (numeric)	float	0%	1	2.0
`real_gdp_growth_rate_real_gdp_growth_rate_2022_text`	Real gdp growth rate 2022 (text)	string	0%	1	2.6% (2022 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric`	Real gdp growth rate 2022 (numeric)	float	0%	1	2.6
`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	$21,700 (2024 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_text`	Real gdp per capita 2023 (text)	string	0%	1	$21,200 (2023 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_numeric`	Real gdp per capita 2023 (numeric)	float	0%	1	21200.0
`real_gdp_per_capita_real_gdp_per_capita_2022_text`	Real gdp per capita 2022 (text)	string	0%	1	$20,800 (2022 est.)
`real_gdp_per_capita_real_gdp_per_capita_2022_numeric`	Real gdp per capita 2022 (numeric)	float	0%	1	20800.0
`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	$526.411 billion (2024 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text`	Inflation rate consumer prices 2024 (text)	string	0%	1	1.4% (2024 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric`	Inflation rate consumer prices 2024 (numeric)	float	0%	1	1.4
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text`	Inflation rate consumer prices 2023 (text)	string	0%	1	8.5% (2023 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric`	Inflation rate consumer prices 2023 (numeric)	float	0%	1	8.5
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text`	Inflation rate consumer prices 2022 (text)	string	0%	1	-1.6% (2022 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric`	Inflation rate consumer prices 2022 (numeric)	float	0%	1	-1.6
`inflation_rate_consumer_prices_note`	inflation_rate_consumer_prices_note	string	0%	1	note: annual % change based on consumer prices
+123 more extension fields — download the CSV/Parquet to see them all.

THA OpenFactBook - Energy — 1 rows, 57 columns

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Field details — 57 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	99.9
`country_code`	Country code	string	SEL	0%	1	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (53) — 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	99.9% (2022 est.)
`electricity_access_electrification_urban_areas_text`	electricity_access_electrification_urban_areas_text	string	0%	1	100%
`electricity_access_electrification_urban_areas_numeric`	electricity_access_electrification_urban_areas_numeric	float	0%	1	100.0
`electricity_access_electrification_rural_areas_text`	electricity_access_electrification_rural_areas_text	string	0%	1	100%
`electricity_access_electrification_rural_areas_numeric`	electricity_access_electrification_rural_areas_numeric	float	0%	1	100.0
`electricity_installed_generating_capacity_text`	electricity_installed_generating_capacity_text	string	0%	1	55.971 million kW (2023 est.)
`electricity_installed_generating_capacity_numeric`	electricity_installed_generating_capacity_numeric	float	0%	1	55.971
`electricity_consumption_text`	electricity_consumption_text	string	0%	1	215.281 billion kWh (2023 est.)
`electricity_consumption_numeric`	electricity_consumption_numeric	float	0%	1	215.281
`electricity_exports_text`	electricity_exports_text	string	0%	1	2.256 billion kWh (2023 est.)
`electricity_exports_numeric`	electricity_exports_numeric	float	0%	1	2.256
`electricity_imports_text`	electricity_imports_text	string	0%	1	35.805 billion kWh (2023 est.)
`electricity_imports_numeric`	electricity_imports_numeric	float	0%	1	35.805
`electricity_transmission_distribution_losses_text`	electricity_transmission_distribution_losses_text	string	0%	1	14.44 billion kWh (2023 est.)
`electricity_transmission_distribution_losses_numeric`	electricity_transmission_distribution_losses_numeric	float	0%	1	14.44
`electricity_generation_sources_fossil_fuels_text`	electricity_generation_sources_fossil_fuels_text	string	0%	1	81.9% of total installed capacity (2023 est.)
`electricity_generation_sources_fossil_fuels_numeric`	electricity_generation_sources_fossil_fuels_numeric	float	0%	1	81.9
`electricity_generation_sources_solar_text`	electricity_generation_sources_solar_text	string	0%	1	2.7% of total installed capacity (2023 est.)
`electricity_generation_sources_solar_numeric`	electricity_generation_sources_solar_numeric	float	0%	1	2.7
`electricity_generation_sources_wind_text`	electricity_generation_sources_wind_text	string	0%	1	1.8% of total installed capacity (2023 est.)
`electricity_generation_sources_wind_numeric`	electricity_generation_sources_wind_numeric	float	0%	1	1.8
`electricity_generation_sources_hydroelectricity_text`	electricity_generation_sources_hydroelectricity_text	string	0%	1	3.5% of total installed capacity (2023 est.)
`electricity_generation_sources_hydroelectricity_numeric`	electricity_generation_sources_hydroelectricity_numeric	float	0%	1	3.5
`electricity_generation_sources_biomass_and_waste_text`	electricity_generation_sources_biomass_and_waste_text	string	0%	1	10.1% of total installed capacity (2023 est.)
`electricity_generation_sources_biomass_and_waste_numeric`	electricity_generation_sources_biomass_and_waste_numeric	float	0%	1	10.1
`coal_production_text`	coal_production_text	string	0%	1	12.812 million metric tons (2023 est.)
`coal_production_numeric`	coal_production_numeric	float	0%	1	12.812
`coal_consumption_text`	coal_consumption_text	string	0%	1	42.371 million metric tons (2023 est.)
`coal_consumption_numeric`	coal_consumption_numeric	float	0%	1	42.371
`coal_exports_text`	coal_exports_text	string	0%	1	65,000 metric tons (2023 est.)
+23 more extension fields — download the CSV/Parquet to see them all.

THA OpenFactBook - Environment — 1 rows, 54 columns

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Field details — 60 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	43.8
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	39.0
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	53.6
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	1.43
`waste_and_recycling_municipal_solid_waste_generated_annually_numeric`	Municipal waste kg per capita	float	SEL	0%	1	26.853
`country_code`	Country code	string	SEL	0%	1	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (52) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`environmental_issues_text`	environmental_issues_text	string	0%	1	air pollution from vehicle emissions; water pollution...
`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; rainy, warm, cloudy southwest monsoon (mid-May...
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	43.8% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 31% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	31.0
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 11.2% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	11.2
`land_use_agricultural_land_permanent_pasture_text`	land_use_agricultural_land_permanent_pasture_text	string	0%	1	permanent pasture: 1.6% (2023 est.)
`land_use_agricultural_land_permanent_pasture_numeric`	land_use_agricultural_land_permanent_pasture_numeric	float	0%	1	1.6
`land_use_forest_text`	land_use_forest_text	string	0%	1	39% (2023 est.)
`land_use_other_text`	land_use_other_text	string	0%	1	17.2% (2023 est.)
`land_use_other_numeric`	land_use_other_numeric	float	0%	1	17.2
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	53.6% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	1.43% annual rate of change (2020-25 est.)
`carbon_dioxide_emissions_total_emissions_text`	carbon_dioxide_emissions_total_emissions_text	string	0%	1	336.693 million metric tonnes of CO2 (2023 est.)
`carbon_dioxide_emissions_total_emissions_numeric`	carbon_dioxide_emissions_total_emissions_numeric	float	0%	1	336.693
`carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text`	carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text	string	0%	1	79.928 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	79.928
`carbon_dioxide_emissions_from_petroleum_and_other_liquids_text`	carbon_dioxide_emissions_from_petroleum_and_other_liquids_text	string	0%	1	160.931 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	160.931
`carbon_dioxide_emissions_from_consumed_natural_gas_text`	carbon_dioxide_emissions_from_consumed_natural_gas_text	string	0%	1	95.834 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	95.834
`particulate_matter_emissions_text`	particulate_matter_emissions_text	string	0%	1	26.3 micrograms per cubic meter (2019 est.)
`particulate_matter_emissions_numeric`	particulate_matter_emissions_numeric	float	0%	1	26.3
`methane_emissions_energy_text`	methane_emissions_energy_text	string	0%	1	708.8 kt (2022-2024 est.)
`methane_emissions_energy_numeric`	methane_emissions_energy_numeric	float	0%	1	708.8
`methane_emissions_agriculture_text`	methane_emissions_agriculture_text	string	0%	1	2,109.9 kt (2019-2021 est.)
+22 more extension fields — download the CSV/Parquet to see them all.

THA 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	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`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	Thai (singular and plural)
`nationality_adjective_text`	nationality_adjective_text	string	0%	1	Thai
`ethnic_groups_text`	ethnic_groups_text	string	0%	1	Thai 97.5%, Burmese 1.3%, other 1.1%, unspecified <0.1%...
`ethnic_groups_numeric`	ethnic_groups_numeric	float	0%	1	97.5
`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/th.json

THA OpenFactBook - Geography — 1 rows, 59 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	513120.0
`area_land_numeric`	Area land sqkm	float	SEL	0%	1	510890.0
`area_water_numeric`	Area water sqkm	float	SEL	0%	1	2230.0
`land_boundaries_total_numeric`	Land boundary km	float	SEL	0%	1	5673.0
`coastline_numeric`	Coastline km	float	SEL	0%	1	3219.0
`elevation_highest_point_numeric`	Elevation max m	float	SEL	0%	1	2565.0
`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	43.8
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	39.0
`irrigated_land_numeric`	Irrigated land sqkm	float	SEL	0%	1	64150.0
`country_code`	Country code	string	SEL	0%	1	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`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...
`geographic_coordinates_text`	geographic_coordinates_text	string	0%	1	15 00 N, 100 00 E
`geographic_coordinates_numeric`	geographic_coordinates_numeric	float	0%	1	15.0
`map_references_text`	map_references_text	string	0%	1	Southeast Asia
`area_total_text`	area_total_text	string	0%	1	513,120 sq km
`area_land_text`	area_land_text	string	0%	1	510,890 sq km
`area_water_text`	area_water_text	string	0%	1	2,230 sq km
`area_comparative_text`	area_comparative_text	string	0%	1	about three times the size of Florida; slightly more...
`land_boundaries_total_text`	land_boundaries_total_text	string	0%	1	5,673 km
`land_boundaries_border_countries_text`	land_boundaries_border_countries_text	string	0%	1	Burma 2,416 km; Cambodia 817 km; Laos 1,845 km; Malaysia 595 km
`land_boundaries_border_countries_numeric`	land_boundaries_border_countries_numeric	float	0%	1	2416.0
`coastline_text`	coastline_text	string	0%	1	3,219 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_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-m depth or to the depth of exploitation
`maritime_claims_continental_shelf_numeric`	maritime_claims_continental_shelf_numeric	float	0%	1	200.0
`climate_text`	climate_text	string	0%	1	tropical; rainy, warm, cloudy southwest monsoon (mid-May...
`terrain_text`	terrain_text	string	0%	1	central plain; Khorat Plateau in the east; mountains elsewhere
`elevation_highest_point_text`	elevation_highest_point_text	string	0%	1	Doi Inthanon 2,565 m
`elevation_lowest_point_text`	elevation_lowest_point_text	string	0%	1	Gulf of Thailand 0 m
`elevation_mean_elevation_text`	elevation_mean_elevation_text	string	0%	1	287 m
`elevation_mean_elevation_numeric`	elevation_mean_elevation_numeric	float	0%	1	287.0
`natural_resources_text`	natural_resources_text	string	0%	1	tin, rubber, natural gas, tungsten, tantalum, timber,...
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	43.8% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 31% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	31.0
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 11.2% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	11.2
+19 more extension fields — download the CSV/Parquet to see them all.

THA OpenFactBook - Government — 1 rows, 89 columns

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Field details — 114 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	THA
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (112) — 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	Kingdom of Thailand
`country_name_conventional_short_form_text`	country_name_conventional_short_form_text	string	0%	1	Thailand
`country_name_local_long_form_text`	country_name_local_long_form_text	string	0%	1	Ratcha Anachak Thai
`country_name_local_short_form_text`	country_name_local_short_form_text	string	0%	1	Prathet Thai
`country_name_former_text`	country_name_former_text	string	0%	1	Siam
`country_name_etymology_text`	country_name_etymology_text	string	0%	1	the name means "Land of the Thai," referring to the...
`government_type_text`	government_type_text	string	0%	1	constitutional monarchy
`capital_name_text`	capital_name_text	string	0%	1	Bangkok
`capital_geographic_coordinates_text`	capital_geographic_coordinates_text	string	0%	1	13 45 N, 100 31 E
`capital_geographic_coordinates_numeric`	capital_geographic_coordinates_numeric	float	0%	1	13.0
`capital_time_difference_text`	capital_time_difference_text	string	0%	1	UTC+7 (12 hours ahead of Washington, DC, during Standard Time)
`capital_time_difference_numeric`	capital_time_difference_numeric	float	0%	1	7.0
`capital_etymology_text`	capital_etymology_text	string	0%	1	the name is from the Thai words bang (region) and kok...
`administrative_divisions_text`	administrative_divisions_text	string	0%	1	76 provinces (changwat, singular and plural) and 1...
`administrative_divisions_numeric`	administrative_divisions_numeric	float	0%	1	76.0
`legal_system_text`	legal_system_text	string	0%	1	civil law system with common law influences
`constitution_history_text`	constitution_history_text	string	0%	1	many previous; latest drafted and presented 29 March...
`constitution_history_numeric`	constitution_history_numeric	float	0%	1	29.0
`constitution_amendment_process_text`	constitution_amendment_process_text	string	0%	1	amendments require a majority vote in a joint session 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	at least one parent must be a citizen of Thailand
`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
`suffrage_text`	suffrage_text	string	0%	1	18 years of age; universal and compulsory
`suffrage_numeric`	suffrage_numeric	float	0%	1	18.0
`executive_branch_chief_of_state_text`	executive_branch_chief_of_state_text	string	0%	1	King WACHIRALONGKON; also spelled Vajiralongkorn (since...
`executive_branch_chief_of_state_numeric`	executive_branch_chief_of_state_numeric	float	0%	1	1.0
`executive_branch_head_of_government_text`	executive_branch_head_of_government_text	string	0%	1	Prime Minister ANUTIN Charnvirakul (since 5 Sep 2025)
+82 more extension fields — download the CSV/Parquet to see them all.

THA OpenFactBook - Introduction — 1 rows, 6 columns

Loading data…

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	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`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	Two unified Thai kingdoms emerged in the mid-13th...
`background_numeric`	background_numeric	float	0%	1	-13.0
`source_section`	source_section	string	0%	1	Introduction
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/th.json

THA OpenFactBook - Languages — 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	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`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
`languages_languages_text`	Languages (text)	string	0%	1	Thai (official) only 90.7%, Thai and other languages...
`languages_languages_numeric`	Languages (numeric)	float	0%	1	90.7
`languages_major_language_sample_s_text`	languages_major_language_sample_s_text	string	0%	1	สารานุกรมโลก - แหล่งข้อมูลพื้นฐานที่สำคัญ (Thai)The...
`languages_note`	languages_note	string	0%	1	note: data represent population by language(s) spoken at home
`source_section`	source_section	string	0%	1	People and Society:languages
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/th.json

THA OpenFactBook - Migration — 1 rows, 11 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	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`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_refugees_text`	refugees_and_internally_displaced_persons_refugees_text	string	0%	1	87,025 (2024 est.)
`refugees_and_internally_displaced_persons_refugees_numeric`	refugees_and_internally_displaced_persons_refugees_numeric	float	0%	1	87025.0
`refugees_and_internally_displaced_persons_idps_text`	refugees_and_internally_displaced_persons_idps_text	string	0%	1	19 (2023 est.)
`refugees_and_internally_displaced_persons_idps_numeric`	refugees_and_internally_displaced_persons_idps_numeric	float	0%	1	19.0
`refugees_and_internally_displaced_persons_stateless_persons_text`	refugees_and_internally_displaced_persons_stateless_persons_text	string	0%	1	612,524 (2024 est.)
`refugees_and_internally_displaced_persons_stateless_persons_numeric`	refugees_and_internally_displaced_persons_stateless_persons_numeric	float	0%	1	612524.0
`source_section`	source_section	string	0%	1	Transnational Issues:migration
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/th.json

THA OpenFactBook - Military And Security — 1 rows, 22 columns

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Field details — 27 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	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (24) — 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	Royal Thai Armed Forces (RTARF): Royal Thai Army (RTA),...
`military_and_security_forces_numeric`	military_and_security_forces_numeric	float	0%	1	2025.0
`military_expenditures_military_expenditures_2024_text`	Military expenditures 2024 (text)	string	0%	1	1.1% of GDP (2024 est.)
`military_expenditures_military_expenditures_2024_numeric`	Military expenditures 2024 (numeric)	float	0%	1	1.1
`military_expenditures_military_expenditures_2023_text`	Military expenditures 2023 (text)	string	0%	1	1.3% of GDP (2023 est.)
`military_expenditures_military_expenditures_2023_numeric`	Military expenditures 2023 (numeric)	float	0%	1	1.3
`military_expenditures_military_expenditures_2022_text`	Military expenditures 2022 (text)	string	0%	1	1.3% of GDP (2022 est.)
`military_expenditures_military_expenditures_2022_numeric`	Military expenditures 2022 (numeric)	float	0%	1	1.3
`military_expenditures_military_expenditures_2021_text`	Military expenditures 2021 (text)	string	0%	1	1.3% of GDP (2021 est.)
`military_expenditures_military_expenditures_2021_numeric`	Military expenditures 2021 (numeric)	float	0%	1	1.3
`military_expenditures_military_expenditures_2020_text`	Military expenditures 2020 (text)	string	0%	1	1.4% of GDP (2020 est.)
`military_expenditures_military_expenditures_2020_numeric`	Military expenditures 2020 (numeric)	float	0%	1	1.4
`military_and_security_service_personnel_strengths_text`	military_and_security_service_personnel_strengths_text	string	0%	1	estimated 350,000 active-duty Armed Forces (250,000...
`military_and_security_service_personnel_strengths_numeric`	military_and_security_service_personnel_strengths_numeric	float	0%	1	350000.0
`military_equipment_inventories_and_acquisitions_text`	military_equipment_inventories_and_acquisitions_text	string	0%	1	the RTARF has a diverse array of foreign-supplied...
`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 years of age for voluntary military service for men...
`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	280 South Sudan (UNMISS) (2025)
`military_deployments_numeric`	military_deployments_numeric	float	0%	1	280.0
`military_note_text`	military_note_text	string	0%	1	the missions of the Royal Thai Armed Forces (RTARF)...
`military_note_numeric`	military_note_numeric	float	0%	1	20.0
`source_section`	source_section	string	0%	1	Military and Security
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/th.json

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

Loading data…

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	70025248.0
`population_male_numeric`	Population male	float	SEL	0%	1	34101016.0
`population_female_numeric`	Population female	float	SEL	0%	1	35924232.0
`age_structure_0_14_years_numeric`	Population 0 14 percent	float	SEL	0%	1	15.8
`age_structure_15_64_years_numeric`	Population 15 64 percent	float	SEL	0%	1	69.0
`age_structure_65_years_and_over_numeric`	Population 65 plus percent	float	SEL	0%	1	15.1
`dependency_ratios_total_dependency_ratio_numeric`	Total dependency ratio	float	SEL	0%	1	45.9
`dependency_ratios_youth_dependency_ratio_numeric`	Youth dependency ratio	float	SEL	0%	1	22.9
`dependency_ratios_elderly_dependency_ratio_numeric`	Elderly dependency ratio	float	SEL	0%	1	23.1
`median_age_total_numeric`	Median age	float	SEL	0%	1	41.9
`population_growth_rate_numeric`	Population growth rate percent	float	SEL	0%	1	0.13
`birth_rate_numeric`	Birth rate per 1000	float	SEL	0%	1	9.82
`death_rate_numeric`	Death rate per 1000	float	SEL	0%	1	8.08
`net_migration_rate_numeric`	Net migration per 1000	float	SEL	0%	1	-0.41
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	53.6
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	1.43
`sex_ratio_at_birth_numeric`	Sex ratio at birth	float	SEL	0%	1	1.05
`sex_ratio_total_population_numeric`	Sex ratio overall	float	SEL	0%	1	0.95
`maternal_mortality_ratio_numeric`	Maternal mortality per 100k	float	SEL	0%	1	34.0
`infant_mortality_rate_total_numeric`	Infant mortality per 1000	float	SEL	0%	1	6.2
`life_expectancy_at_birth_total_population_numeric`	Life expectancy	float	SEL	0%	1	78.2
`total_fertility_rate_numeric`	Fertility rate	float	SEL	0%	1	1.55
`gross_reproduction_rate_numeric`	Gross reproduction rate	float	SEL	0%	1	0.75
`physician_density_numeric`	Physicians per 1000	float	SEL	0%	1	0.54
`hospital_bed_density_numeric`	Hospital beds per 1000	float	SEL	0%	1	2.3
`literacy_total_population_numeric`	Literacy rate percent	float	SEL	0%	1	91.1
`country_code`	Country code	string	SEL	0%	1	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`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	70,025,248 (2025 est.)
`population_male_text`	population_male_text	string	0%	1	34,101,016
`population_female_text`	population_female_text	string	0%	1	35,924,232
`age_structure_0_14_years_text`	age_structure_0_14_years_text	string	0%	1	15.8% (male 5,669,592/female 5,394,398)
`age_structure_15_64_years_text`	age_structure_15_64_years_text	string	0%	1	69% (male 23,681,528/female 24,597,535)
`age_structure_65_years_and_over_text`	age_structure_65_years_and_over_text	string	0%	1	15.1% (2024 est.) (male 4,714,191/female 5,863,754)
`dependency_ratios_total_dependency_ratio_text`	dependency_ratios_total_dependency_ratio_text	string	0%	1	45.9 (2025 est.)
`dependency_ratios_youth_dependency_ratio_text`	dependency_ratios_youth_dependency_ratio_text	string	0%	1	22.9 (2025 est.)
`dependency_ratios_elderly_dependency_ratio_text`	dependency_ratios_elderly_dependency_ratio_text	string	0%	1	23.1 (2025 est.)
`dependency_ratios_potential_support_ratio_text`	dependency_ratios_potential_support_ratio_text	string	0%	1	4.3 (2025 est.)
`dependency_ratios_potential_support_ratio_numeric`	dependency_ratios_potential_support_ratio_numeric	float	0%	1	4.3
`median_age_total_text`	median_age_total_text	string	0%	1	41.9 years (2025 est.)
`median_age_male_text`	median_age_male_text	string	0%	1	40.2 years
`median_age_male_numeric`	median_age_male_numeric	float	0%	1	40.2
`median_age_female_text`	median_age_female_text	string	0%	1	42.7 years
`median_age_female_numeric`	median_age_female_numeric	float	0%	1	42.7
`population_growth_rate_text`	population_growth_rate_text	string	0%	1	0.13% (2025 est.)
`birth_rate_text`	birth_rate_text	string	0%	1	9.82 births/1,000 population (2025 est.)
`death_rate_text`	death_rate_text	string	0%	1	8.08 deaths/1,000 population (2025 est.)
`net_migration_rate_text`	net_migration_rate_text	string	0%	1	-0.41 migrant(s)/1,000 population (2025 est.)
`population_distribution_text`	population_distribution_text	string	0%	1	highest population density is found in and around...
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	53.6% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	1.43% annual rate of change (2020-25 est.)
`major_urban_areas_population_text`	major_urban_areas_population_text	string	0%	1	11.070 million BANGKOK (capital), 1.454 Chon Buri, 1.359...
`major_urban_areas_population_numeric`	major_urban_areas_population_numeric	float	0%	1	11.07
`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	1.05 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	0.96 male(s)/female
`sex_ratio_15_64_years_numeric`	sex_ratio_15_64_years_numeric	float	0%	1	0.96
+93 more extension fields — download the CSV/Parquet to see them all.

THA OpenFactBook - Religions — 1 rows, 6 columns

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Field details — 17 fields (type, nulls, unique, samples)

Standards-Aligned Fields (8)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`admin_level`	Admin level	string	SEL	0%	1	national
`composition_religion_buddhist_pct_synth`	Buddhist	numeric	CCL	0%	-	92.5
`composition_religion_muslim_pct_synth`	Muslim	numeric	CCL	0%	-	5.4
`composition_religion_christian_pct_synth`	Christian	numeric	CCL	0%	-	1.2
`composition_religion_other_pct_synth`	other	numeric	CCL	0%	-	0.9
`composition_ethnicity_primary_label_synth`	Thai	string	CCL	0%	-	Thai

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 92.5%, Muslim 5.4%, Christian 1.2%, other 0.9%...
`religions_numeric`	religions_numeric	float	0%	1	92.5
`source_section`	source_section	string	0%	1	People and Society:religions
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/th.json

Pending (5) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`composition_ethnicity_thai_pct_synth`	Thai	numeric	0%	-	97.5
`composition_ethnicity_burmese_pct_synth`	Burmese	numeric	0%	-	1.3
`composition_ethnicity_other_pct_synth`	other	numeric	0%	-	1.1
`composition_ethnicity_unspecified_pct_synth`	unspecified	numeric	0%	-	0.05
`composition_ethnicity_primary_share_pct_synth`	Thai	numeric	0%	-	97.5

THA OpenFactBook - Space — 1 rows, 9 columns

Loading data…

Field details — 13 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	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (10) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`space_agency_agencies_text`	space_agency_agencies_text	string	0%	1	Geo-Informatics and Space Technology Development Agency...
`space_agency_agencies_numeric`	space_agency_agencies_numeric	float	0%	1	2000.0
`space_launch_site_s_text`	space_launch_site_s_text	string	0%	1	none; in 2023, announced intentions to build a spaceport...
`space_launch_site_s_numeric`	space_launch_site_s_numeric	float	0%	1	2023.0
`space_program_overview_text`	space_program_overview_text	string	0%	1	has an ambitious national space program focused on the...
`space_program_overview_numeric`	space_program_overview_numeric	float	0%	1	2021.0
`key_space_program_milestones_text`	key_space_program_milestones_text	string	0%	1	1982 - established first satellite ground station1993 -...
`key_space_program_milestones_numeric`	key_space_program_milestones_numeric	float	0%	1	1982.0
`source_section`	source_section	string	0%	1	Space
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/th.json

THA OpenFactBook - Transnational Issues — 1 rows, 6 columns

Loading data…

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	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`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 precursor-chemical producer (2025)
`illicit_drugs_usg_identification_numeric`	illicit_drugs_usg_identification_numeric	float	0%	1	2025.0
`source_section`	source_section	string	0%	1	Transnational Issues
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/th.json

THA OpenFactBook - Transportation — 1 rows, 30 columns

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Field details — 33 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	HS
`airports_numeric`	Airports count	float	SEL	0%	1	105.0
`country_code`	Country code	string	SEL	0%	1	THA
`country_name`	Country name	string	SEL	0%	1	Thailand
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (28) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`airports_text`	airports_text	string	0%	1	105 (2025)
`heliports_text`	heliports_text	string	0%	1	5 (2025)
`heliports_numeric`	heliports_numeric	float	0%	1	5.0
`railways_total_text`	railways_total_text	string	0%	1	4,127 km (2017)
`railways_total_numeric`	railways_total_numeric	float	0%	1	4127.0
`railways_standard_gauge_text`	railways_standard_gauge_text	string	0%	1	84 km (2017) 1.435-m gauge (84 km electrified)
`railways_standard_gauge_numeric`	railways_standard_gauge_numeric	float	0%	1	84.0
`railways_narrow_gauge_text`	railways_narrow_gauge_text	string	0%	1	4,043 km (2017) 1.000-m gauge
`railways_narrow_gauge_numeric`	railways_narrow_gauge_numeric	float	0%	1	4043.0
`merchant_marine_total_text`	merchant_marine_total_text	string	0%	1	884 (2023)
`merchant_marine_total_numeric`	merchant_marine_total_numeric	float	0%	1	884.0
`merchant_marine_by_type_text`	merchant_marine_by_type_text	string	0%	1	bulk carrier 28, container ship 28, general cargo 88,...
`merchant_marine_by_type_numeric`	merchant_marine_by_type_numeric	float	0%	1	28.0
`ports_total_ports_text`	ports_total_ports_text	string	0%	1	21 (2024)
`ports_total_ports_numeric`	ports_total_ports_numeric	float	0%	1	21.0
`ports_large_text`	ports_large_text	float	0%	1	1
`ports_large_numeric`	ports_large_numeric	float	0%	1	1.0
`ports_medium_text`	ports_medium_text	float	0%	1	2
`ports_medium_numeric`	ports_medium_numeric	float	0%	1	2.0
`ports_small_text`	ports_small_text	float	0%	1	3
`ports_small_numeric`	ports_small_numeric	float	0%	1	3.0
`ports_very_small_text`	ports_very_small_text	float	0%	1	15
`ports_very_small_numeric`	ports_very_small_numeric	float	0%	1	15.0
`ports_ports_with_oil_terminals_text`	Ports with oil terminals (text)	float	0%	1	14
`ports_ports_with_oil_terminals_numeric`	Ports with oil terminals (numeric)	float	0%	1	14.0
`ports_key_ports_text`	ports_key_ports_text	string	0%	1	Bangkok, Laem Chabang, Pattani, Phuket, Sattahip, Si Racha
`source_section`	source_section	string	0%	1	Transportation
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/th.json

THA USAID DHS Program THA-DHS Health Surveys

5 rows · 1 table(s) · 1987 USAID DHS Program 0 1 2 3 3 SEL 5 ext ▶

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

1 Admin 1 — 1 table(s)

THA DHS - Health Indicators — 5 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%	-	-
`infant_mortality_per_1000`	Infant mortality per 1000	float	SEL	0%	4	19.0, 33.0, 40.0, 45.0, 40.0
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	0%	5	27.0, 44.0, 52.0, 53.0, 56.0

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	Thailand, Thailand, Thailand, Thailand, Thailand
`survey_year`	survey_year	integer	0%	1	1987, 1987, 1987, 1987, 1987
`region`	region	string	0%	5	Bangkok, Central, North, Northeast, South
`survey_id`	survey_id	string	0%	1	TH1987DHS, TH1987DHS, TH1987DHS, TH1987DHS, TH1987DHS
`survey_type`	survey_type	string	0%	1	DHS, DHS, DHS, DHS, DHS

THA Ethnic Power Relations Dataset THA-EPR Political Ethnicity

5 rows · 1 table(s) · 2021 Ethnic Power Relations Dataset 0 1 2 3 1 SEL 5 CCL 2 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 — 1 table(s)

THA EPR - Groups — 5 rows, 8 columns

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

Standards-Aligned Fields (6)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	THA, THA, THA, THA, THA
`ethnic_group_name`	Ethnic group name	string	CCL	0%	5	Thai, Chinese, Malay Muslims, Hill Tribes, Shan
`ethnic_power_status`	Ethnic power status	string	CCL	0%	4	DOMINANT, IRRELEVANT, DISCRIMINATED, POWERLESS, POWERLESS
`ethnic_population_share`	Ethnic population share	float	CCL	0%	5	0.815, 0.12, 0.05, 0.01, 0.005
`ethnic_group_id`	Ethnic group id	float	CCL	0%	5	80003000, 80004000, 80001000, 80005000, 80002000
`regional_autonomy`	Regional autonomy	string	CCL	0%	2	, , false, false, false

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

Field Name	Label	Type	Nulls	Unique	Samples
`year`	year	integer	0%	1	2021, 2021, 2021, 2021, 2021
`group_relevance`	group_relevance	string	0%	1	, , , ,

THA D-PLACE THA-DPLACE Ethnographic Societies

2 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)

THA D-PLACE - Dplace Ea Societies — 2 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	THA, THA
`society_id`	Society id	string	CCL	0%	2	Ej12, Ej9
`society_name`	Society name	string	CCL	0%	2	Lawa, Thai
`language_glottocode`	Language glottocode	string	CCL	0%	2	west2396, thai1261
`language_name`	Language name	string	CCL	0%	1	,
`kinship_system`	Kinship system	string	CCL	0%	1	EA001:0; EA002:0; EA003:1; EA004:1; EA005:8, EA001:0;...
`marriage_pattern`	Marriage pattern	string	CCL	0%	2	EA006:1; EA007:8; EA008:6; EA009:1; EA010:8, EA006:3;...
`subsistence_pattern`	Subsistence pattern	string	CCL	0%	2	EA028:3; EA029:6; EA030:7; EA031:4; EA032:3, EA028:6;...
`political_complexity`	Political complexity	string	CCL	0%	2	EA033:2; EA034:1; EA035:NA, EA033:5; EA034:2; EA035:5
`religion_importance`	Religion importance	string	CCL	0%	2	EA034:1; EA112:NA, EA034:2; EA112:4
`residence_pattern`	Residence pattern	string	CCL	0%	2	EA011:1; EA012:8; EA013:3, EA011:2; EA012:6; EA013:9

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	Thailand, Thailand
`dataset`	dataset	string	0%	1	EA, EA
`region`	region	string	0%	1	,
`latitude`	latitude	float	0%	2	18.0, 15.0
`longitude`	longitude	float	0%	2	98.0, 100.0
`assignment_method`	assignment_method	string	0%	1	point_in_polygon, point_in_polygon
`assignment_confidence`	assignment_confidence	string	0%	1	approximate, approximate

THA Global Organized Crime Index THA-OCINDEX Crime Index

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

THA 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	THA
`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	47
`oc_anti_money_laundering_2023`	oc_anti_money_laundering_2023	integer	0%	1	5
`oc_anti_money_laundering_2021`	oc_anti_money_laundering_2021	float	0%	1	4.5
`oc_arms_trafficking_rank`	oc_arms_trafficking_rank	integer	0%	1	53
`oc_arms_trafficking_2023`	oc_arms_trafficking_2023	float	0%	1	6.5
`oc_arms_trafficking_2021`	oc_arms_trafficking_2021	float	0%	1	5.5
`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	integer	0%	1	5
`oc_cocaine_trade_rank`	oc_cocaine_trade_rank	integer	0%	1	111
`oc_cocaine_trade_2023`	oc_cocaine_trade_2023	integer	0%	1	4
`oc_cocaine_trade_2021`	oc_cocaine_trade_2021	integer	0%	1	4
`oc_criminal_actors_rank`	oc_criminal_actors_rank	integer	0%	1	65
`oc_criminal_actors_2023`	oc_criminal_actors_2023	float	0%	1	5.6
`oc_criminal_actors_2021`	oc_criminal_actors_2021	float	0%	1	5.13
`oc_criminal_markets_rank`	oc_criminal_markets_rank	integer	0%	1	14
`oc_criminal_markets_2023`	oc_criminal_markets_2023	float	0%	1	6.77
`oc_criminal_markets_2021`	oc_criminal_markets_2021	float	0%	1	6.4
`oc_criminal_networks_rank`	oc_criminal_networks_rank	integer	0%	1	74
`oc_criminal_networks_2023`	oc_criminal_networks_2023	integer	0%	1	6
`oc_criminal_networks_2021`	oc_criminal_networks_2021	integer	0%	1	5
`oc_criminality_rank`	oc_criminality_rank	integer	0%	1	39
`oc_criminality_2023`	oc_criminality_2023	float	0%	1	6.18
`oc_criminality_2021`	oc_criminality_2021	float	0%	1	5.76
`oc_cyber_dependent_crimes_rank`	oc_cyber_dependent_crimes_rank	integer	0%	1	38
+74 more pending fields — download the CSV/Parquet to see them all.

THA World Values Survey THA-WVS Attitudes Values

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

THA 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	THA

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

Source	Type	Access
HDX COD — Population Statistics (OCHA/UNFPA)	international_organization	bulk_download
HDX (Humanitarian Data Exchange)	international_organization	bulk_download
Global Data Lab	academic	api
World Values Survey	academic	metadata_catalog
Ethnic Power Relations Dataset	academic	bulk_download
D-PLACE (Database of Places, Language, Culture & Environment)	academic	bulk_download
NGA GEOnet Names Server (GNS)	official_government	bulk_download
GI-TOC / ENACT (Global Initiative Against Transnational Organized Crime · ENACT)	academic	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
World Bank Open Data	international_organization	api
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