Indonesia

IDN Indonesia - Economic, Social, Environmental, Healt IDN-HDX-Indonesia_-_Economic,_Social,_Envir Indicators

91,575 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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IDN Indonesia - Economic, Social, Environmental, Healt — 91,575 rows, 3,329 columns

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Field details — 3329 fields (type, nulls, unique, samples)

Extension Fields (3329) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	IDN
`Fertilizer_consumption_pct_of_fertilizer_production`	Fertilizer_consumption_pct_of_fertilizer_production	float	0%	1	121.854810385847
`Fertilizer_consumption_kilograms_per_hectare_of_arable_land`	Fertilizer_consumption_kilograms_per_hectare_of_arable_land	float	0%	1	311.071988639875
`Agricultural_land_sq._km`	Agricultural_land_sq._km	float	0%	1	551222.03
`Agricultural_land_pct_of_land_area`	Agricultural_land_pct_of_land_area	float	0%	1	29.1258057551148
`Arable_land_hectares`	Arable_land_hectares	float	0%	1	17782903.0
`Arable_land_hectares_per_person`	Arable_land_hectares_per_person	float	0%	1	0.0632415760262257
`Arable_land_pct_of_land_area`	Arable_land_pct_of_land_area	float	0%	1	9.3962387268892
`Land_under_cereal_production_hectares`	Land_under_cereal_production_hectares	float	0%	1	12689796.0
`Permanent_cropland_pct_of_land_area`	Permanent_cropland_pct_of_land_area	float	0%	1	13.9173199504689
`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	140582.419643
`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	7.44376393971379
`Forest_area_sq._km`	Forest_area_sq._km	float	0%	1	903165.959
`Forest_area_pct_of_land_area`	Forest_area_pct_of_land_area	float	0%	1	47.7220336902463
`Average_precipitation_in_depth_mm_per_year`	Average_precipitation_in_depth_mm_per_year	float	0%	1	2702.0
`Land_area_sq._km`	Land_area_sq._km	float	0%	1	1892555.47
`Rural_land_area_sq._km`	Rural_land_area_sq._km	float	0%	1	1820838.066132
`Cereal_production_metric_tons`	Cereal_production_metric_tons	float	0%	1	73966646.0
`Crop_production_index_2014-2016_=_100`	Crop_production_index_2014-2016_=_100	float	0%	1	111.41
`Food_production_index_2014-2016_=_100`	Food_production_index_2014-2016_=_100	float	0%	1	117.14
`Livestock_production_index_2014-2016_=_100`	Livestock_production_index_2014-2016_=_100	float	0%	1	189.99
`Surface_area_sq._km`	Surface_area_sq._km	float	0%	1	1916906.77
`Cereal_yield_kg_per_hectare`	Cereal_yield_kg_per_hectare	float	0%	1	5828.8
`Access_to_electricity_rural_pct_of_rural_population`	Access_to_electricity_rural_pct_of_rural_population	float	0%	1	98.6
`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	2.44411367431195
`Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal`	Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal	float	0%	1	85.2067285
`Agriculture_forestry_and_fishing_value_added_current_USusd`	Agriculture_forestry_and_fishing_value_added_current_USusd	float	0%	1	176054814059.639
`Agriculture_forestry_and_fishing_value_added_pct_of_GDP`	Agriculture_forestry_and_fishing_value_added_pct_of_GDP	float	0%	1	12.6086658797584
`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	25.2587381539466
`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	28.638999559361
+3299 more extension fields — download the CSV/Parquet to see them all.

IDN Indonesia - Health Indicators IDN-HDX-Indonesia_-_Health_Indicators Indicators

26,296 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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IDN Indonesia - Health Indicators — 26,296 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%	71	NCD_BMI_30A, HIV_0000000026,...
`GHO (DISPLAY)`	GHO (DISPLAY)	string	0%	71	Prevalence of obesity among adults, BMI ≥ 30...
`GHO (URL)`	GHO (URL)	string	0%	71	https://www.who.int/data/gho/data/indicators/indicator-de...
`YEAR (DISPLAY)`	YEAR (DISPLAY)	string	0%	33	1992, 2015, 2010, 2013, 2007
`STARTYEAR`	STARTYEAR	string	0%	33	1992, 2015, 2010, 2013, 2007
`ENDYEAR`	ENDYEAR	string	0%	33	1992, 2015, 2010, 2013, 2007
`REGION (CODE)`	REGION (CODE)	string	0%	1	WPR, WPR, WPR, WPR, WPR
`REGION (DISPLAY)`	REGION (DISPLAY)	string	0%	1	Western Pacific, Western Pacific, Western Pacific,...
`COUNTRY (CODE)`	COUNTRY (CODE)	string	0%	1	IDN, IDN, IDN, IDN, IDN
`COUNTRY (DISPLAY)`	COUNTRY (DISPLAY)	string	0%	1	Indonesia, Indonesia, Indonesia, Indonesia, Indonesia
`DIMENSION (TYPE)`	DIMENSION (TYPE)	string	8%	10	SEX, RESIDENCEAREATYPE, WEALTHTERCILE,...
`DIMENSION (CODE)`	DIMENSION (CODE)	string	8%	35	SEX_FMLE, RESIDENCEAREATYPE_TOTL, WEALTHTERCILE_TOTL,...
`DIMENSION (NAME)`	DIMENSION (NAME)	string	8%	32	Female, Total, Total, Urban, Urban
`Numeric`	Numeric	string	16%	81	2.5925873, 41000.0, 17.0, 19.9, 26.6
`Value`	Value	string	0%	88	2.6 [2.0-3.3], 41 000 [37 000 - 45 000], 17 [7.1 -...
`Low`	Low	float	40%	54	2.0080164, 37000.0, 7.1, 21.6, 3.7877616
`High`	High	float	40%	60	3.2806724, 45000.0, 30.5, 32.3, 7.0383534

IDN Indonesia - Education IDN-HDX-Indonesia_-_Education Indicators

17,379 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

IDN Indonesia - Education — 17,379 rows, 873 columns

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Field details — 873 fields (type, nulls, unique, samples)

Extension Fields (873) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	IDN
`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	0.92
`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	0.9
`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	10.54
`Barro-Lee:_Percentage_of_population_age_15+_with_no_education`	Barro-Lee:_Percentage_of_population_age_15+_with_no_education	float	0%	1	7.5
`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	1.27
`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	1.1
`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	1.8
`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	1.47
`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	13.28
`Barro-Lee:_Percentage_of_population_age_25+_with_no_education`	Barro-Lee:_Percentage_of_population_age_25+_with_no_education	float	0%	1	9.47
`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	2.37
`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	1.9
`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	5.59
`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	4.03
`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	5.59
`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	4.03
`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	13.26
`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	9.52
`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	13.26
`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	9.52
`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	24.01
`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	16.64
`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	24.01
`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	16.64
`Barro-Lee:_Population_in_thousands_age_15-19_total`	Barro-Lee:_Population_in_thousands_age_15-19_total	float	0%	1	20666.0
`Barro-Lee:_Population_in_thousands_age_15-19_female`	Barro-Lee:_Population_in_thousands_age_15-19_female	float	0%	1	10175.0
`Barro-Lee:_Population_in_thousands_age_15+_total`	Barro-Lee:_Population_in_thousands_age_15+_total	float	0%	1	172622.0
`Barro-Lee:_Population_in_thousands_age_15+_female`	Barro-Lee:_Population_in_thousands_age_15+_female	float	0%	1	87129.0
`Barro-Lee:_Population_in_thousands_age_20-24_total`	Barro-Lee:_Population_in_thousands_age_20-24_total	float	0%	1	20760.0
+843 more extension fields — download the CSV/Parquet to see them all.

IDN Indonesia - Social Protection and Labor IDN-HDX-Indonesia_-_Social_Protection_and_L Indicators

11,144 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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IDN Indonesia - Social Protection And Labor — 11,144 rows, 953 columns

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Field details — 953 fields (type, nulls, unique, samples)

Extension Fields (953) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	IDN
`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	26.0319890344572
`Adequacy_of_benefits_pct_-All_Social_Protection_and_Labor_-rural`	Adequacy_of_benefits_pct_-All_Social_Protection_and_Labor_-rural	float	0%	1	10.3937508957357
`Adequacy_of_benefits_pct_-All_Social_Protection_and_Labor_-urban`	Adequacy_of_benefits_pct_-All_Social_Protection_and_Labor_-urban	float	0%	1	8.45333491822981
`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	16.7906415286707
`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	10.8800370213586
`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	13.8907256006874
`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	12.2959150292141
`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	11.061616823752
`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	8.06248946770298
`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	10.8642692519041
`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	9.45748987558114
`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	7.99625897462222
`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	5.7344333018527
`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	8.62037959846084
`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	6.9520830582438
`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	5.66383233564381
`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	3.25339423460846
`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	0.461927221356516
`Average_per_capita_transfer_-All_Social_Protection_and_Labor_-rural`	Average_per_capita_transfer_-All_Social_Protection_and_Labor_-rural	float	0%	1	0.558198758520917
`Average_per_capita_transfer_-All_Social_Protection_and_Labor`	Average_per_capita_transfer_-All_Social_Protection_and_Labor	float	0%	1	0.523820129696557
`Average_per_capita_transfer_-All_Social_Protection_and_Labor_-urban`	Average_per_capita_transfer_-All_Social_Protection_and_Labor_-urban	float	0%	1	0.490231166805188
`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	0.469286389861467
`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	0.491685697036318
`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	0.495181842678375
`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	0.501597422260879
`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	0.539024606918701
`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	4.75838079365895
`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	29.9313686186993
`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	22.0392120022486
+923 more extension fields — download the CSV/Parquet to see them all.

IDN Indonesia - Gender IDN-HDX-Indonesia_-_Gender Indicators

5,453 rows · 1 table(s) · 2024 HDX 0 1 2 3 ▶

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IDN Indonesia - Gender — 5,453 rows, 233 columns

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Field details — 233 fields (type, nulls, unique, samples)

Extension Fields (233) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	IDN
`Firms_with_female_top_manager_pct_of_firms`	Firms_with_female_top_manager_pct_of_firms	float	0%	1	31.80389023
`Firms_with_female_participation_in_ownership_pct_of_firms`	Firms_with_female_participation_in_ownership_pct_of_firms	float	0%	1	59.38367844
`Literacy_rate_youth_female_pct_of_females_ages_15-24`	Literacy_rate_youth_female_pct_of_females_ages_15-24	float	0%	1	94.72
`Literacy_rate_youth_ages_15-24_gender_parity_index_GPI`	Literacy_rate_youth_ages_15-24_gender_parity_index_GPI	float	0%	1	1.01910901069641
`Literacy_rate_youth_male_pct_of_males_ages_15-24`	Literacy_rate_youth_male_pct_of_males_ages_15-24	float	0%	1	92.91
`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	94.5500030517578
`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	97.4499969482422
`School_enrollment_primary_gross_gender_parity_index_GPI`	School_enrollment_primary_gross_gender_parity_index_GPI	float	0%	1	0.967230021953583
`School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI`	School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI	float	0%	1	0.993399977684021
`School_enrollment_secondary_gross_gender_parity_index_GPI`	School_enrollment_secondary_gross_gender_parity_index_GPI	float	0%	1	1.02502000331879
`School_enrollment_tertiary_gross_gender_parity_index_GPI`	School_enrollment_tertiary_gross_gender_parity_index_GPI	float	0%	1	1.19583636791956
`School_enrollment_preprimary_female_pct_gross`	School_enrollment_preprimary_female_pct_gross	float	0%	1	59.128978729248
`School_enrollment_preprimary_male_pct_gross`	School_enrollment_preprimary_male_pct_gross	float	0%	1	65.4104919433594
`Primary_completion_rate_female_pct_of_relevant_age_group`	Primary_completion_rate_female_pct_of_relevant_age_group	float	0%	1	98.7919848769697
`Primary_completion_rate_male_pct_of_relevant_age_group`	Primary_completion_rate_male_pct_of_relevant_age_group	float	0%	1	101.054087295239
`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	81.1035966749599
`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	86.5573482541628
`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	83.8310823174419
`Primary_education_pupils_pct_female`	Primary_education_pupils_pct_female	float	0%	1	47.77049
`School_enrollment_primary_female_pct_gross`	School_enrollment_primary_female_pct_gross	float	0%	1	99.0626948866048
`School_enrollment_primary_male_pct_gross`	School_enrollment_primary_male_pct_gross	float	0%	1	101.61380480346
`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	100.5169
`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	104.42266
`School_enrollment_primary_female_pct_net`	School_enrollment_primary_female_pct_net	float	0%	1	90.9674
`School_enrollment_primary_male_pct_net`	School_enrollment_primary_male_pct_net	float	0%	1	95.88766
`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	37.2727
`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	43.66138
`Persistence_to_grade_5_female_pct_of_cohort`	Persistence_to_grade_5_female_pct_of_cohort	float	0%	1	99.9835510253906
`Persistence_to_grade_5_male_pct_of_cohort`	Persistence_to_grade_5_male_pct_of_cohort	float	0%	1	99.0687713623047
+203 more extension fields — download the CSV/Parquet to see them all.

IDN Indonesia - Subnational Demographic and Health Dat IDN-HDX-Indonesia_-_Subnational_Demographic Indicators

4,301 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)

IDN Indonesia - Subnational Demographic And Health Dat — 4,301 rows, 30 columns

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Field details — 30 fields (type, nulls, unique, samples)

Extension Fields (30) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`ISO3`	ISO3	string	0%	1	IDN, IDN, IDN, IDN, IDN
`Location`	Location	string	0%	30	Java-Bali, DKI Jakarta, West Java, Central Java, DI Yogyakarta
`DataId`	DataId	string	0%	100	1100367, 164552, 1086256, 1100313, 1107182
`Indicator`	Indicator	string	0%	7	Total fertility rate 15-49, Total fertility rate 15-49,...
`Value`	Value	string	0%	78	2.8, 2.4, 3.3, 3, 2
`Precision`	Precision	string	0%	2	1, 1, 1, 1, 1
`DHS_CountryCode`	DHS_CountryCode	string	0%	1	ID, ID, ID, ID, ID
`CountryName`	CountryName	string	0%	1	Indonesia, Indonesia, Indonesia, Indonesia, Indonesia
`SurveyYear`	SurveyYear	string	0%	2	1987, 1987, 1987, 1987, 1987
`SurveyId`	SurveyId	string	0%	2	ID1987DHS, ID1987DHS, ID1987DHS, ID1987DHS, ID1987DHS
`IndicatorId`	IndicatorId	string	0%	7	FE_FRTR_W_TFR, FE_FRTR_W_TFR, FE_FRTR_W_TFR,...
`IndicatorOrder`	IndicatorOrder	string	0%	7	11763080, 11763080, 11763080, 11763080, 11763080
`IndicatorType`	IndicatorType	string	0%	1	I, I, I, I, I
`CharacteristicId`	CharacteristicId	string	0%	30	414000, 414001, 414002, 414003, 414004
`CharacteristicOrder`	CharacteristicOrder	string	0%	30	1414000, 1414010, 1414020, 1414030, 1414040
`CharacteristicCategory`	CharacteristicCategory	string	0%	1	Region, Region, Region, Region, Region
`CharacteristicLabel`	CharacteristicLabel	string	0%	30	Java-Bali, ..DKI Jakarta, ..West Java, ..Central Java,...
`ByVariableId`	ByVariableId	string	0%	2	0, 0, 0, 0, 0
`ByVariableLabel`	ByVariableLabel	string	82%	1	Ten years preceding the survey, Ten years preceding the...
`IsTotal`	IsTotal	string	0%	1	0, 0, 0, 0, 0
`IsPreferred`	IsPreferred	string	0%	1	1, 1, 1, 1, 1
`SDRID`	SDRID	string	0%	7	FEFRTRWTFR, FEFRTRWTFR, FEFRTRWTFR, FEFRTRWTFR, FEFRTRWTFR
`RegionId`	RegionId	string	0%	39	IDDHS1987414000, IDDHS1987414001, IDDHS1987414002,...
`SurveyYearLabel`	SurveyYearLabel	string	0%	2	1987, 1987, 1987, 1987, 1987
`SurveyType`	SurveyType	string	0%	1	DHS, DHS, DHS, DHS, DHS
`DenominatorWeighted`	DenominatorWeighted	string	75%	16	7265, 543, 2208, 1934, 207
`DenominatorUnweighted`	DenominatorUnweighted	string	75%	16	7729, 1564, 1518, 1265, 976
`CILow`	CILow	string	82%	14	62, 42, 79, 32, 25
`CIHigh`	CIHigh	string	82%	18	79, 63, 113, 61, 48
`LevelRank`	LevelRank	string	42%	2	1, 1, 1, 1, 1

IDN Global Data Lab IDN-GDL Development Indices

1,032 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)

IDN GDL - Subnational Indices — 1,032 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	IDN, IDN, IDN, IDN, IDN
`region_code`	Admin code	string	SEL	100%	-	-
`region_name`	Admin name	string	SEL	0%	31	Total, Bali, Bangka Belitung, Banten, Bengkulu
`human_development_index`	Human development index	float	SEL	0%	74	0.601, 0.639, 0.643, 0.651, 0.577
`health_index`	Health index	float	SEL	0%	85	0.665, 0.724, 0.723, 0.702, 0.583
`education_index`	Education index	float	SEL	0%	78	0.564, 0.572, 0.582, 0.617, 0.59
`income_index`	Income index	float	SEL	0%	80	0.578, 0.629, 0.632, 0.637, 0.558
`life_expectancy`	Life expectancy	float	SEL	0%	96	63.25, 67.06, 66.98, 65.62, 57.89
`mean_years_schooling`	Mean years schooling	float	SEL	0%	100	8.463, 8.447, 9.095, 10.19, 8.91

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

Field Name	Label	Type	Nulls	Unique	Samples
`year`	year	integer	0%	4	1990, 1990, 1990, 1990, 1990
`level`	level	string	0%	2	national, subnational, subnational, subnational, subnational

IDN Indonesia - Human Development Indicators IDN-HDX-Indonesia_-_Human_Development_Indic Indicators

968 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)

IDN Indonesia - Human Development Indicators — 968 rows, 46 columns

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Field details — 46 fields (type, nulls, unique, samples)

Extension Fields (46) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	IDN
`abr`	abr	float	0%	1	26.419
`assets`	assets	float	0%	1	6.8
`child_mortality`	child_mortality	float	0%	1	34.742
`co2_prod`	co2_prod	float	0%	1	2.642
`coef_ineq`	coef_ineq	float	0%	1	16.366
`cooking_fuel`	cooking_fuel	float	0%	1	9.436
`diff_hdi_phdi`	diff_hdi_phdi	float	0%	1	6.044
`drinking_water`	drinking_water	float	0%	1	5.356
`electricity`	electricity	float	0%	1	3.056
`eys`	eys	float	0%	1	13.336
`eys_f`	eys_f	float	0%	1	13.621
`eys_m`	eys_m	float	0%	1	13.057
`gdi_group`	gdi_group	float	0%	1	3.0
`gii_rank`	gii_rank	float	0%	1	108.0
`gni_pc_f`	gni_pc_f	float	0%	1	9073.375
`gni_pc_m`	gni_pc_m	float	0%	1	18283.6
`gnipc`	gnipc	float	0%	1	13700.13
`hdi_f`	hdi_f	float	0%	1	0.704
`hdi_m`	hdi_m	float	0%	1	0.745
`hdi_rank`	hdi_rank	float	0%	1	113.0
`housing`	housing	float	0%	1	5.191
`ineq_edu`	ineq_edu	float	0%	1	12.946
`ineq_inc`	ineq_inc	float	0%	1	23.636
`ineq_le`	ineq_le	float	0%	1	12.516
`le`	le	float	0%	1	71.146
`le_f`	le_f	float	0%	1	73.268
`le_m`	le_m	float	0%	1	69.036
`lfpr_f`	lfpr_f	float	0%	1	53.39
`lfpr_m`	lfpr_m	float	0%	1	82.23
+16 more extension fields — download the CSV/Parquet to see them all.

IDN Indonesia - Demographic, Health, Education and Tra IDN-HDX-Indonesia_-_Demographic,_Health,_Ed Indicators

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

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0 Admin 0 — 1 table(s)

IDN Indonesia - Demographic, Health, Education And Tra — 794 rows, 11 columns

Loading data…

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%	7	Crime, Crime, Health, Health, Transport
`indicator`	indicator	string	0%	19	recorded_assault_rate, recorded_assault_rate,...
`indicator_friendly`	indicator_friendly	string	0%	19	Recorded assault rate per 100, Recorded assault rate per...
`type_data`	type_data	string	0%	4	000 population, 000 population, p, p, n
`latitude`	latitude	string	0%	3	n, n, -5, -5, -5
`longitude`	longitude	string	0%	3	-5, -5, 120, 120, 120
`region_id`	region_id	string	0%	2	120, 120, 789, 789, 789
`country_id`	country_id	string	0%	2	789, 789, ID, ID, ID
`name`	name	string	0%	3	ID, ID, Indonesia, Indonesia, Indonesia
`year`	year	string	0%	29	Indonesia, Indonesia, 1992, 2004, 1990
`value`	value	string	0%	98	2000, 1999, 15.4, 17, 16

IDN Glottolog Language Catalog IDN-GLOTTOLOG Language

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

IDN Glottolog - Languages — 756 rows, 16 columns

Loading data…

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

Standards-Aligned Fields (13)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`glottocode`	Glottocode	string	CCL	0%	100	abai1241, abin1243, abui1241, abun1252, achi1257
`name`	Name	string	CCL	0%	100	Abai Tubu-Abai Sembuak, Abinomn, Abui, Abun, Acehnese
`iso639_3`	Iso639 3	string	CCL	4%	96	bsa, abz, kgr, ace, adb
`level`	Level	string	CCL	0%	1	language, language, language, language, language
`family_name`	Family name	string	CCL	100%	-	-
`family_glottocode`	Family glottocode	string	CCL	2%	17	aust1307, timo1261, aust1307, book1242, timo1261
`parent_name`	Parent name	string	CCL	100%	-	-
`parent_glottocode`	Parent glottocode	string	CCL	2%	85	muru1275, abui1242, cham1327, book1242, adan1252
`endangerment_status`	Endangerment status	string	CCL	100%	-	-
`country_codes`	Country codes	string	SEL+	0%	4	['ID'], ['ID'], ['ID'], ['ID'], ['ID']
`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%	12	0, 0, 4, 3, 7

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

Field Name	Label	Type	Nulls	Unique	Samples
`latitude`	latitude	float	0%	100	3.524226, -2.92281, -8.31058, -0.57073, 3.90757
`longitude`	longitude	float	0%	100	116.162455, 138.891, 124.588, 132.416, 96.6032
`classification`	classification	string	0%	1	[], [], [], [], []

IDN Indonesia - Urban Development IDN-HDX-Indonesia_-_Urban_Development Indicators

641 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)

IDN Indonesia - Urban Development — 641 rows, 18 columns

Loading data…

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	IDN
`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	5029.16204349
`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	0.266291440717653
`Urban_land_area_sq._km`	Urban_land_area_sq._km	float	0%	1	67755.1345869
`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	17.8814994983985
`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	95.5671472610627
`Population_density_people_per_sq._km_of_land_area`	Population_density_people_per_sq._km_of_land_area	float	0%	1	148.57692229227
`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	6.37354752480886
`Population_living_in_slums_pct_of_urban_population`	Population_living_in_slums_pct_of_urban_population	float	0%	1	19.41083
`Population_in_largest_city`	Population_in_largest_city	float	0%	1	11634078.0
`Population_in_the_largest_city_pct_of_urban_population`	Population_in_the_largest_city_pct_of_urban_population	float	0%	1	6.8557484417066
`Population_in_urban_agglomerations_of_more_than_1_million`	Population_in_urban_agglomerations_of_more_than_1_million	float	0%	1	41214600.0
`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	14.4247591033101
`Mortality_caused_by_road_traffic_injury_per_100000_population`	Mortality_caused_by_road_traffic_injury_per_100000_population	float	0%	1	11.3
`Urban_population_growth_annual_pct`	Urban_population_growth_annual_pct	float	0%	1	1.89719567962498
`Urban_population`	Urban_population	float	0%	1	166551891.0
`Urban_population_pct_of_total_population`	Urban_population_pct_of_total_population	float	0%	1	58.7509635387997

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

549 rows · 3 table(s) · 2020 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)

IDN Cod Ps - Idn Codps (admin_0) — 1 rows, 56 columns

Loading data…

Field details — 56 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`pcode`	Admin code	string	SEL	0%	1	ID
`region_name`	Region name	string	SEL	0%	1	Indonesia
`T_TL`	Total population	integer	SEL	0%	1	269603430
`M_TL`	Male population	integer	SEL	0%	1	135337011
`F_TL`	Female population	integer	SEL	0%	1	134266419

Pending (51) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`admin_level`	Admin level	string	0%	1	admin_0
`year`	Reference year	integer	0%	1	2020
`year`	year	integer	0%	1	2020
`T_00_04`	Total population age 0-4	integer	0%	1	21951993
`T_05_09`	Total population age 5-9	integer	0%	1	21945160
`T_10_14`	Total population age 10-14	integer	0%	1	22168842
`T_15_19`	Total population age 15-19	integer	0%	1	22139392
`T_20_24`	Total population age 20-24	integer	0%	1	21958329
`T_25_29`	Total population age 25-29	integer	0%	1	21699966
`T_30_34`	Total population age 30-34	integer	0%	1	21302010
`T_35_39`	Total population age 35-39	integer	0%	1	20783179
`T_40_44`	Total population age 40-44	integer	0%	1	19524038
`T_45_49`	Total population age 45-49	integer	0%	1	18164239
`T_50_54`	Total population age 50-54	integer	0%	1	15923028
`T_55_59`	Total population age 55-59	integer	0%	1	13323796
`T_60_64`	Total population age 60-64	integer	0%	1	10521814
`T_65_69`	Total population age 65-69	integer	0%	1	7680229
`T_70_74`	Total population age 70-74	integer	0%	1	5242370
`T_75Plus`	T_75Plus	integer	0%	1	5275045
`M_00_04`	Male population age 0-4	integer	0%	1	11101528
`M_05_09`	Male population age 5-9	integer	0%	1	11205657
`M_10_14`	Male population age 10-14	integer	0%	1	11284333
`M_15_19`	Male population age 15-19	integer	0%	1	11189861
`M_20_24`	Male population age 20-24	integer	0%	1	11070774
`M_25_29`	Male population age 25-29	integer	0%	1	10963605
`M_30_34`	Male population age 30-34	integer	0%	1	10777337
`M_35_39`	Male population age 35-39	integer	0%	1	10477475
`M_40_44`	Male population age 40-44	integer	0%	1	9830929
`M_45_49`	Male population age 45-49	integer	0%	1	9140315
`M_50_54`	Male population age 50-54	integer	0%	1	7975551
+21 more pending fields — download the CSV/Parquet to see them all.

1 Admin 1 — 1 table(s)

IDN Cod Ps - Idn Codps (admin_1) — 34 rows, 56 columns

Loading data…

Field details — 56 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`pcode`	Admin code	string	SEL	0%	34	ID11, ID51, ID36, ID17, ID34
`region_name`	Region name	string	SEL	0%	34	Aceh, Bali, Banten, Bengkulu, Daerah Istimewa Yogyakarta
`T_TL`	Total population	integer	SEL	0%	34	5388093, 4414431, 12895258, 1994349, 3919197
`M_TL`	Male population	integer	SEL	0%	34	2691784, 2221377, 6557861, 1015234, 1935397
`F_TL`	Female population	integer	SEL	0%	34	2696309, 2193054, 6337397, 979115, 1983800

Pending (51) — 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	2020, 2020, 2020, 2020, 2020
`year`	year	integer	0%	1	2020, 2020, 2020, 2020, 2020
`T_00_04`	Total population age 0-4	integer	0%	34	509320, 315660, 1095985, 168744, 275983
`T_05_09`	Total population age 5-9	integer	0%	34	506731, 313175, 1096826, 165312, 261202
`T_10_14`	Total population age 10-14	integer	0%	34	502503, 339350, 1090395, 164470, 257922
`T_15_19`	Total population age 15-19	integer	0%	34	489870, 340023, 1079525, 162932, 280715
`T_20_24`	Total population age 20-24	integer	0%	34	474318, 353262, 1090531, 162606, 318922
`T_25_29`	Total population age 25-29	integer	0%	34	461848, 355007, 1084772, 163526, 317182
`T_30_34`	Total population age 30-34	integer	0%	34	441242, 349973, 1068828, 162885, 299569
`T_35_39`	Total population age 35-39	integer	0%	34	413277, 351570, 1029714, 159209, 297753
`T_40_44`	Total population age 40-44	integer	0%	34	366305, 332498, 961127, 147807, 282245
`T_45_49`	Total population age 45-49	integer	0%	34	317530, 316001, 880429, 133296, 269682
`T_50_54`	Total population age 50-54	integer	0%	34	264886, 279111, 745488, 117153, 246218
`T_55_59`	Total population age 55-59	integer	0%	34	211271, 235002, 595438, 96905, 222888
`T_60_64`	Total population age 60-64	integer	0%	34	161302, 189211, 440523, 73255, 188700
`T_65_69`	Total population age 65-69	integer	0%	34	114624, 139710, 297488, 51983, 147795
`T_70_74`	Total population age 70-74	integer	0%	34	76867, 98014, 186740, 33600, 110085
`T_75Plus`	T_75Plus	integer	0%	34	76199, 106864, 151449, 30666, 142336
`M_00_04`	Male population age 0-4	integer	0%	34	257539, 159695, 554458, 85292, 139690
`M_05_09`	Male population age 5-9	integer	0%	34	257220, 160681, 556653, 84136, 133517
`M_10_14`	Male population age 10-14	integer	0%	34	254446, 173129, 550754, 83079, 131655
`M_15_19`	Male population age 15-19	integer	0%	34	246241, 173362, 541292, 81962, 140984
`M_20_24`	Male population age 20-24	integer	0%	34	236854, 180556, 545119, 82095, 157648
`M_25_29`	Male population age 25-29	integer	0%	34	231079, 180980, 548471, 83021, 158073
`M_30_34`	Male population age 30-34	integer	0%	34	222395, 178018, 547984, 83719, 151792
`M_35_39`	Male population age 35-39	integer	0%	34	207063, 178538, 532746, 82287, 150402
`M_40_44`	Male population age 40-44	integer	0%	34	182837, 168940, 498873, 75935, 141767
`M_45_49`	Male population age 45-49	integer	0%	34	158211, 159914, 455737, 68167, 134099
`M_50_54`	Male population age 50-54	integer	0%	34	131486, 139612, 383408, 59788, 120237
+21 more pending fields — download the CSV/Parquet to see them all.

2 Admin 2 — 1 table(s)

IDN Cod Ps - Idn Codps (admin_2) — 514 rows, 56 columns

Loading data…

Field details — 56 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`pcode`	Admin code	string	SEL	0%	100	ID1107, ID1112, ID1108, ID1116, ID1103
`region_name`	Region name	string	SEL	0%	100	Aceh Barat, Aceh Barat Daya, Aceh Besar, Aceh Jaya, Aceh Selatan
`T_TL`	Total population	integer	SEL	0%	100	209498, 151828, 424423, 94379, 242200
`M_TL`	Male population	integer	SEL	0%	100	106007, 75292, 217471, 49263, 119001
`F_TL`	Female population	integer	SEL	0%	100	103491, 76536, 206952, 45116, 123199

Pending (51) — 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	2020, 2020, 2020, 2020, 2020
`year`	year	integer	0%	1	2020, 2020, 2020, 2020, 2020
`T_00_04`	Total population age 0-4	integer	0%	100	18469, 12757, 42358, 10076, 19368
`T_05_09`	Total population age 5-9	integer	0%	100	17274, 13388, 35618, 7378, 22388
`T_10_14`	Total population age 10-14	integer	0%	100	17890, 14291, 34747, 7564, 23716
`T_15_19`	Total population age 15-19	integer	0%	100	17930, 13542, 38388, 7129, 21049
`T_20_24`	Total population age 20-24	integer	0%	100	18108, 11479, 41047, 7916, 17140
`T_25_29`	Total population age 25-29	integer	0%	100	18884, 12631, 40239, 9456, 18593
`T_30_34`	Total population age 30-34	integer	0%	100	18748, 12732, 35631, 8543, 19372
`T_35_39`	Total population age 35-39	integer	0%	100	18217, 12188, 33093, 7898, 19830
`T_40_44`	Total population age 40-44	integer	0%	100	15817, 11339, 28352, 6859, 18493
`T_45_49`	Total population age 45-49	integer	0%	100	13380, 9981, 24219, 5743, 15926
`T_50_54`	Total population age 50-54	integer	0%	100	10626, 7949, 19395, 4628, 13144
`T_55_59`	Total population age 55-59	integer	0%	100	7896, 5842, 16481, 3589, 10236
`T_60_64`	Total population age 60-64	integer	0%	100	6405, 4799, 12606, 3024, 8051
`T_65_69`	Total population age 65-69	integer	0%	100	4365, 3751, 8569, 2012, 6308
`T_70_74`	Total population age 70-74	integer	0%	100	2912, 2706, 5944, 1298, 4544
`T_75Plus`	T_75Plus	integer	0%	100	2577, 2453, 7736, 1266, 4042
`M_00_04`	Male population age 0-4	integer	0%	100	9196, 6472, 21564, 5002, 9783
`M_05_09`	Male population age 5-9	integer	0%	100	8622, 6713, 18123, 3746, 11335
`M_10_14`	Male population age 10-14	integer	0%	100	9008, 7262, 17764, 3817, 12168
`M_15_19`	Male population age 15-19	integer	0%	100	8975, 6940, 19751, 3694, 10576
`M_20_24`	Male population age 20-24	integer	0%	100	8861, 5451, 21174, 4112, 8305
`M_25_29`	Male population age 25-29	integer	0%	100	9611, 5988, 20964, 4787, 9104
`M_30_34`	Male population age 30-34	integer	0%	99	9420, 6237, 18768, 4562, 9186
`M_35_39`	Male population age 35-39	integer	0%	100	9326, 5991, 17215, 4258, 9758
`M_40_44`	Male population age 40-44	integer	0%	100	8129, 5623, 14655, 3783, 9014
`M_45_49`	Male population age 45-49	integer	0%	100	7068, 5034, 12657, 3135, 7811
`M_50_54`	Male population age 50-54	integer	0%	100	5542, 4019, 9885, 2454, 6386
+21 more pending fields — download the CSV/Parquet to see them all.

IDN Indonesia - Risk Assessment Indicators IDN-HDX-Indonesia_-_Risk_Assessment_Indicat Indicators

522 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)

IDN Indonesia - Risk Assessment Indicators — 522 rows, 9 columns

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

Extension Fields (9) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`ADM2_PCODE`	ADM2_PCODE	string	0%	100	ID1107, ID1112, ID1108, ID1116, ID1103
`ADM_PCODE`	ADM_PCODE	string	0%	100	ID1107, ID1112, ID1108, ID1116, ID1103
`female_pop_rural`	female_pop_rural	string	0%	100	55170, 27183, 31302, 28909, 43298
`children_u5_rural`	children_u5_rural	string	0%	100	8426, 4220, 5416, 5145, 6113
`female_u5_rural`	female_u5_rural	string	0%	100	4084, 2052, 2627, 2513, 2964
`elderly_rural`	elderly_rural	string	0%	100	8431, 3836, 4698, 4342, 7204
`pop_u15_rural`	pop_u15_rural	string	0%	100	26512, 12699, 16761, 15943, 18794
`female_u15_rural`	female_u15_rural	string	0%	99	12940, 6144, 8152, 7836, 9123
`rural_pop_perc`	rural_pop_perc	float	0%	99	51.38, 33.37, 14.23, 59.64, 34.26

IDN LandScan Global (ORNL) IDN-LANDSCAN Modeled Population

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

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

Loading data…

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	IDN
`admin_level`	Admin level	string	SEL	0%	1	admin_0
`admin_name`	Admin name	string	SEL	0%	1	Indonesia
`admin_code`	Admin code	string	SEL	0%	1	11942859B47275810722289
`area_sqkm`	Area sqkm	float	SEL	0%	1	1890176.2786
`pop_2024`	Population count	integer	SEL	0%	1	278106216
`pop_density_2024`	Population density	float	SEL	0%	1	147.13

1 Admin 1 — 1 table(s)

IDN LandScan - Population Admin1 (admin_1) — 34 rows, 7 columns

Loading data…

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	IDN, IDN, IDN, IDN, IDN
`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%	34	West Java, East Java, Central Java, North Sumatra, Banten
`admin_code`	Admin code	string	SEL	0%	34	65028918B28366581005022, 65028918B43243108525571,...
`area_sqkm`	Area sqkm	float	SEL	0%	34	37676.3162, 47932.4368, 33776.2554, 72301.2913, 9346.3814
`pop_2024`	Population count	integer	SEL	0%	34	50781093, 42132005, 37447172, 15396614, 12325254
`pop_density_2024`	Population density	float	SEL	0%	34	1347.83, 878.99, 1108.68, 212.95, 1318.72

Locality Locality — 1 table(s)

IDN LandScan - Cities (locality) — 369 rows, 9 columns

Loading data…

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	IDN, IDN, IDN, IDN, IDN
`admin_level`	Admin level	string	SEL	0%	1	locality, locality, locality, locality, locality
`admin_name`	Admin name	string	SEL	0%	100	Jakarta, Bandung, Surabaya, Medan, Semarang
`admin_code`	Admin code	integer	SEL	0%	100	5472, 5748, 7459, 1646, 6785
`area_sqkm`	Area sqkm	float	SEL	0%	100	4583.8627, 981.58, 1295.5649, 602.9687, 599.0835
`pop_2024`	Population count	integer	SEL	0%	100	32471474, 6975873, 6431812, 3840163, 2401612
`pop_density_2024`	Population density	float	SEL	0%	100	7083.87, 7106.78, 4964.48, 6368.76, 4008.81

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

Field Name	Label	Type	Nulls	Unique	Samples
`ghs_pop_2025`	ghs_pop_2025	integer	0%	100	40545126, 8691181, 6856993, 4350624, 3274360
`landscan_vs_ghs_ratio`	landscan_vs_ghs_ratio	float	0%	92	0.801, 0.803, 0.938, 0.883, 0.733

IDN USAID DHS Program IDN-DHS Health Surveys

375 rows · 2 table(s) · 2017 USAID DHS Program 0 1 2 3 4 SEL 2 CCL 10 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 — 2 table(s)

IDN DHS - Ethnicity Indicators — 138 rows, 8 columns

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	100%	-	-
`women_who_are_literate`	Women who are literate	float	CCL	0%	74	86.4, 85.5, 90.4, 95.2, 87.1
`men_who_are_literate`	Men who are literate	float	CCL	27%	57	96.5, 95.1, 97.0, 93.0, 94.7

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	Indonesia, Indonesia, Indonesia, Indonesia, Indonesia
`survey_year`	survey_year	integer	0%	4	2003, 2007, 2012, 2017, 2003
`region`	region	string	0%	28	..Bali, ..Bali, ..Bali, ..Bali, ..Bangka Belitung
`survey_id`	survey_id	string	0%	4	ID2003DHS, ID2007DHS, ID2012DHS, ID2017DHS, ID2003DHS
`survey_type`	survey_type	string	0%	1	DHS, DHS, DHS, DHS, DHS

IDN DHS - Health Indicators — 237 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%	54	65.0, 49.0, 58.0, 39.0, 14.0
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	0%	65	80.0, 61.0, 63.0, 44.0, 19.0

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	Indonesia, Indonesia, Indonesia, Indonesia, Indonesia
`survey_year`	survey_year	integer	0%	8	1987, 1991, 1994, 1997, 2003
`region`	region	string	0%	17	..Bali, ..Bali, ..Bali, ..Bali, ..Bali
`survey_id`	survey_id	string	0%	8	ID1987DHS, ID1991DHS, ID1994DHS, ID1997DHS, ID2003DHS
`survey_type`	survey_type	string	0%	1	DHS, DHS, DHS, DHS, DHS

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

369 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)

IDN GHS-UCDB - Cities (locality) — 369 rows, 10 columns

Loading data…

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`city_name`	Admin name	string	SEL	0%	100	Jakarta, Bandung, Surabaya, Medan, Semarang
`country_code`	Country code	string	SEL	0%	1	IDN, IDN, IDN, IDN, IDN
`population`	Population count	integer	SEL	0%	100	40545126, 8691181, 6856993, 4350624, 3274360

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

Field Name	Label	Type	Nulls	Unique	Samples
`city_id`	city_id	integer	0%	100	5472, 5748, 7459, 1646, 6785
`name_alternates`	name_alternates	string	100%	-	-
`country_name`	country_name	string	0%	1	Indonesia, Indonesia, Indonesia, Indonesia, Indonesia
`population_year`	population_year	integer	0%	1	2025, 2025, 2025, 2025, 2025
`latitude`	latitude	string	100%	-	-
`longitude`	longitude	string	100%	-	-
`region`	region	string	100%	-	-

IDN Indonesia - National Demographic and Health Data IDN-HDX-Indonesia_-_National_Demographic_an Indicators

159 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)

IDN Indonesia - National Demographic And Health Data — 159 rows, 29 columns

Loading data…

Field details — 29 fields (type, nulls, unique, samples)

Extension Fields (29) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`ISO3`	ISO3	string	0%	1	IDN, IDN, IDN, IDN, IDN
`DataId`	DataId	string	0%	100	139491, 91599, 91600, 81481, 134449
`Indicator`	Indicator	string	0%	17	Total fertility rate 15-49, Married women currently...
`Value`	Value	string	0%	89	3.1, 47.7, 43.9, 17.2, 67
`Precision`	Precision	string	0%	2	1, 1, 1, 1, 0
`DHS_CountryCode`	DHS_CountryCode	string	0%	1	ID, ID, ID, ID, ID
`CountryName`	CountryName	string	0%	1	Indonesia, Indonesia, Indonesia, Indonesia, Indonesia
`SurveyYear`	SurveyYear	string	0%	6	1987, 1987, 1987, 1987, 1987
`SurveyId`	SurveyId	string	0%	6	ID1987DHS, ID1987DHS, ID1987DHS, ID1987DHS, ID1987DHS
`IndicatorId`	IndicatorId	string	0%	17	FE_FRTR_W_TFR, FP_CUSM_W_ANY, FP_CUSM_W_MOD,...
`IndicatorOrder`	IndicatorOrder	string	0%	17	11763080, 32633010, 32633020, 41633090, 63206030
`IndicatorType`	IndicatorType	string	0%	1	I, I, I, I, I
`CharacteristicId`	CharacteristicId	string	0%	2	1000, 1000, 1000, 1000, 1000
`CharacteristicOrder`	CharacteristicOrder	string	0%	2	0, 0, 0, 0, 0
`CharacteristicCategory`	CharacteristicCategory	string	0%	2	Total, Total, Total, Total, Total
`CharacteristicLabel`	CharacteristicLabel	string	0%	2	Total, Total, Total, Total, Total
`ByVariableId`	ByVariableId	string	0%	5	0, 0, 0, 0, 14001
`ByVariableLabel`	ByVariableLabel	string	60%	4	Five years preceding the survey, Ten years preceding the...
`IsTotal`	IsTotal	string	0%	1	1, 1, 1, 1, 1
`IsPreferred`	IsPreferred	string	0%	2	1, 1, 1, 1, 1
`SDRID`	SDRID	string	0%	17	FEFRTRWTFR, FPCUSMWANY, FPCUSMWMOD, MAAAFMWM2B, CMECMRCIMR
`RegionId`	RegionId	string	100%	-	-
`SurveyYearLabel`	SurveyYearLabel	string	0%	6	1987, 1987, 1987, 1987, 1987
`SurveyType`	SurveyType	string	0%	1	DHS, DHS, DHS, DHS, DHS
`DenominatorWeighted`	DenominatorWeighted	string	45%	43	10907, 10907, 21109, 21109, 21109
`DenominatorUnweighted`	DenominatorUnweighted	string	45%	43	10919, 10919, 21187, 21187, 21187
`CILow`	CILow	string	77%	20	58, 66, 87, 100, 60
`CIHigh`	CIHigh	string	77%	22	77, 82, 110, 121, 75
`LevelRank`	LevelRank	string	100%	-	-

IDN World Bank Open Data IDN-WORLD_BANK Development Indicators

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

IDN 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	ID, ID, ID, ID, ID
`population_count`	Population count	float	SEL	2%	65	88296070.0, 90791249.0, 93375850.0, 96051424.0, 98833749.0
`life_expectancy`	Life expectancy	float	SEL	3%	64	46.835, 47.385, 48.141, 48.742, 49.44
`gdp_per_capita_usd`	Gdp per capita usd	float	SEL	12%	58	53.2051866988581, 64.6547730642556, 74.0988114128793,...
`literacy_rate_pct`	Literacy rate percent	float	SEL	80%	13	67.3099975585938, 81.5199966430664, 90.379997253418,...
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	3%	64	223.8, 217.7, 211.8, 206.0, 200.3
`poverty_headcount_pct`	Poverty headcount percent	float	SEL	59%	25	17.5, 23.4, 19.1, 18.4, 18.2

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

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

Loading data…

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	ID, ID, ID, ID, ID
`life_expectancy`	Life expectancy	float	SEL	3%	64	46.835, 47.385, 48.141, 48.742, 49.44
`infant_mortality_per_1000`	Infant mortality per 1000	float	SEL	3%	64	57.9, 56.8, 55.8, 54.8, 53.8
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	3%	64	223.8, 217.7, 211.8, 206.0, 200.3
`maternal_mortality_per_100k`	Maternal mortality per 100k	float	SEL	41%	38	474.0, 455.0, 437.0, 431.0, 402.0
`fertility_rate`	Fertility rate	float	SEL	3%	62	5.505, 5.522, 5.534, 5.551, 5.568
`birth_rate_per_1000`	Birth rate per 1000	float	SEL	3%	64	44.391, 44.251, 44.013, 43.755, 43.455
`death_rate_per_1000`	Death rate per 1000	float	SEL	3%	62	17.765, 17.441, 16.97, 16.587, 16.135
`physicians_per_1000`	Physicians per 1000	float	SEL	65%	22	0.021, 0.032, 0.037, 0.037, 0.085
`hospital_beds_per_1000`	Hospital beds per 1000	float	SEL	47%	27	0.740457057952881, 0.654600024223328, 0.818300008773804,...
`vaccination_rate_pct`	Vaccination rate percent	float	SEL	33%	32	1.0, 1.0, 6.0, 13.0, 27.0
`health_expenditure_pct_gdp`	Health expenditure percent gdp	float	SEL	64%	24	1.85297656, 2.11850214, 1.98062706, 2.24837184, 2.12002277

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

IDN UNHCR Refugee Data Finder IDN-UNHCR Migration

96 rows · 2 table(s) · 2025 UNHCR Refugee Data Finder 0 1 2 3 12 CCL 36 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 — 2 table(s)

IDN UNHCR - Hosted Populations — 48 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%	-	-

IDN UNHCR - Origin Populations — 48 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%	-	-

IDN HDX HAPI Data for Indonesia IDN-HDX-HDX_HAPI_Data_for_Indonesia Indicators

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

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0 Admin 0 — 1 table(s)

IDN HDX HAPI Data for Indonesia — 40 rows, 16 columns

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

Extension Fields (16) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`location_code`	location_code	string	0%	1	IDN, IDN, IDN, IDN, IDN
`has_hrp`	has_hrp	string	0%	1	False, False, False, False, False
`in_gho`	in_gho	string	0%	1	False, False, False, False, False
`provider_admin1_name`	provider_admin1_name	string	18%	5	Aceh, Aceh, Aceh, Jawa Barat, Jawa Barat
`provider_admin2_name`	provider_admin2_name	string	35%	16	Pidie, Pidie Jaya, Garut, Tabanan, Bangli
`admin1_code`	admin1_code	string	18%	5	ID11, ID11, ID11, ID32, ID32
`admin1_name`	admin1_name	string	18%	5	Aceh, Aceh, Aceh, Jawa Barat, Jawa Barat
`admin2_code`	admin2_code	string	35%	16	ID1109, ID1118, ID3205, ID5102, ID5106
`admin2_name`	admin2_name	string	35%	16	Pidie, Pidie Jaya, Garut, Tabanan, Bangli
`admin_level`	admin_level	string	0%	3	0, 0, 0, 0, 0
`operation`	operation	string	0%	5	Aceh earthquake, Central Sulawesi Earthquake, Central...
`assessment_type`	assessment_type	string	0%	1	SA, SA, SA, SA, SA
`population`	population	string	0%	32	76692, 211906, 110373, 1355, 432015
`reporting_round`	reporting_round	string	0%	2	1, 1, 2, 1, 1
`reference_period_start`	reference_period_start	string	0%	7	2016-12-26, 2018-11-30, 2018-12-30, 2016-11-26, 2018-09-30
`reference_period_end`	reference_period_end	string	0%	7	2016-12-26, 2018-11-30, 2018-12-30, 2016-11-26, 2018-09-30

IDN Google Community Mobility (2020-2022) IDN-GOOGLE-MOBILITY Mobility

34 rows · 1 table(s) · 2022 Google 0 1 2 3 3 SEL 8 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)

IDN Mobility by Region — 34 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	ID, ID, ID, ID, ID
`admin_level`	Admin level	integer	SEL	0%	1	1, 1, 1, 1, 1
`iso3`	Country code	string	SEL	0%	1	IDN, IDN, IDN, IDN, IDN

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

Field Name	Label	Type	Nulls	Unique	Samples
`retail`	retail	float	0%	33	1.12, -27.73, -4.68, -2.74, 9.02
`grocery`	grocery	float	0%	34	19.82, -13.94, 20.33, 8.88, 38.04
`parks`	parks	float	0%	34	-1.87, -30.31, 19.39, 13.78, 0.05
`transit`	transit	float	0%	34	-17.19, -55.52, -16.33, -32.09, -36.96
`workplaces`	workplaces	float	0%	33	-10.61, -29.15, -11.55, -14.14, -8.67
`residential`	residential	float	0%	34	2.64, 12.05, 5.54, 11.88, 5.56
`region`	region	string	0%	34	Aceh, Bali, Bangka Belitung Islands, Banten, Bengkulu
`observation_count`	observation_count	integer	0%	1	974, 974, 974, 974, 974

IDN D-PLACE IDN-DPLACE Ethnographic Societies

27 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)

IDN D-PLACE - Dplace Ea Societies — 27 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	IDN, IDN, IDN, IDN, IDN
`society_id`	Society id	string	CCL	0%	27	Ib2, Ib3, Ib4, Ib6, Ib7
`society_name`	Society name	string	CCL	0%	27	Javanese, Balinese, Toba Batak, Minangkabau, Mentaweians
`language_glottocode`	Language glottocode	string	CCL	0%	27	java1254, bali1278, bata1289, mina1268, ment1249
`language_name`	Language name	string	CCL	0%	1	, , , ,
`kinship_system`	Kinship system	string	CCL	0%	23	EA001:0; EA002:0; EA003:0; EA004:2; EA005:8, EA001:0;...
`marriage_pattern`	Marriage pattern	string	CCL	0%	26	EA006:6; EA007:3; EA008:2; EA009:2; EA010:9, EA006:3;...
`subsistence_pattern`	Subsistence pattern	string	CCL	0%	22	EA028:6; EA029:6; EA030:8; EA031:7; EA032:3, EA028:6;...
`political_complexity`	Political complexity	string	CCL	0%	16	EA033:5; EA034:1; EA035:5, EA033:4; EA034:1; EA035:NA,...
`religion_importance`	Religion importance	string	CCL	0%	16	EA034:1; EA112:4, EA034:1; EA112:4, EA034:4; EA112:4,...
`residence_pattern`	Residence pattern	string	CCL	0%	11	EA011:2; EA012:6; EA013:9, EA011:1; EA012:8; EA013:3,...

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	Indonesia, Indonesia, Indonesia, Indonesia, Indonesia
`dataset`	dataset	string	0%	1	EA, EA, EA, EA, EA
`region`	region	string	0%	1	, , , ,
`latitude`	latitude	float	0%	23	-7.0, -8.18, 2.0, -1.0, -2.93
`longitude`	longitude	float	0%	26	110.0, 115.02, 99.0, 101.0, 100.23
`assignment_method`	assignment_method	string	0%	1	point_in_polygon, point_in_polygon, point_in_polygon,...
`assignment_confidence`	assignment_confidence	string	0%	1	approximate, approximate, approximate, approximate, approximate

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

20 rows · 2 table(s) · 2026 NGA GEOnet Names Server (GNS) 0 1 2 3 4 SEL 12 CCL 24 ext ▶

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0 Admin 0 — 2 table(s)

IDN Nga Gns - Language — 19 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	IDN, IDN, IDN, IDN, IDN
`gns_language_code`	gns_language_code	string	CCL	0%	19	ind, ban, sun, eng, msa
`gns_language_name`	gns_language_name	string	CCL	0%	19	Indonesian, Balinese, Sundanese, English, Malay (generic)
`gns_toponym_count`	gns_toponym_count	integer	CCL	0%	12	332571, 513, 131, 127, 101
`gns_toponym_share_pct`	gns_toponym_share_pct	float	CCL	0%	12	99.7146, 0.1538, 0.0393, 0.0381, 0.0303
`gns_non_roman_toponym_count`	gns_non_roman_toponym_count	integer	CCL	0%	2	0, 0, 0, 0, 0
`gns_dominant_script_code`	gns_dominant_script_code	string	CCL	0%	2	, , , ,
`gns_dominant_script_name`	gns_dominant_script_name	string	CCL	0%	2	, , , ,
`gns_script_count`	gns_script_count	integer	CCL	0%	2	0, 0, 0, 0, 0

IDN Nga Gns - Summary — 1 rows, 31 columns

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Field details — 31 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	IDN
`admin_level`	admin_level	integer	SEL	0%	1	0
`gns_country_name`	gns_country_name	string	SEL	0%	1	Indonesia
`gns_language_count`	gns_language_count	integer	CCL	0%	1	19
`gns_script_count`	gns_script_count	integer	CCL	0%	1	1
`gns_endonym_share_pct`	gns_endonym_share_pct	float	CCL	0%	1	99.9919
`gns_non_roman_name_count`	gns_non_roman_name_count	integer	CCL	0%	1	11

Extension Fields (24) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`gns_name_count`	gns_name_count	integer	0%	1	542356
`gns_feature_count`	gns_feature_count	integer	0%	1	448187
`gns_endonym_count`	gns_endonym_count	integer	0%	1	542312
`gns_exonym_count`	gns_exonym_count	integer	0%	1	44
`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	305583
`gns_feature_count_populated_places`	gns_feature_count_populated_places	integer	0%	1	257916
`gns_name_count_hypsographic`	gns_name_count_hypsographic	integer	0%	1	61436
`gns_feature_count_hypsographic`	gns_feature_count_hypsographic	integer	0%	1	41642
`gns_name_count_administrative_regions`	gns_name_count_administrative_regions	integer	0%	1	100587
`gns_feature_count_administrative_regions`	gns_feature_count_administrative_regions	integer	0%	1	90873
`gns_name_count_hydrographic`	gns_name_count_hydrographic	integer	0%	1	71395
`gns_feature_count_hydrographic`	gns_feature_count_hydrographic	integer	0%	1	55100
`gns_name_count_spot_features`	gns_name_count_spot_features	integer	0%	1	1869
`gns_feature_count_spot_features`	gns_feature_count_spot_features	integer	0%	1	1352
`gns_name_count_areas_localities`	gns_name_count_areas_localities	integer	0%	1	1403
`gns_feature_count_areas_localities`	gns_feature_count_areas_localities	integer	0%	1	1232
`gns_name_count_transportation_networks`	gns_name_count_transportation_networks	integer	0%	1	10
`gns_feature_count_transportation_networks`	gns_feature_count_transportation_networks	integer	0%	1	7
`gns_name_count_vegetation`	gns_name_count_vegetation	integer	0%	1	72
`gns_feature_count_vegetation`	gns_feature_count_vegetation	integer	0%	1	64
`gns_name_count_undersea`	gns_name_count_undersea	integer	0%	1	1
`gns_feature_count_undersea`	gns_feature_count_undersea	integer	0%	1	1

IDN Ethnic Power Relations Dataset IDN-EPR Political Ethnicity

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

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0 Admin 0 — 1 table(s)

IDN EPR - Groups — 16 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	IDN, IDN, IDN, IDN, IDN
`ethnic_group_name`	Ethnic group name	string	CCL	0%	16	Javanese, Sundanese, Madura, Minangkabaus, Malay
`ethnic_power_status`	Ethnic power status	string	CCL	0%	4	SENIOR PARTNER, JUNIOR PARTNER, JUNIOR PARTNER, JUNIOR...
`ethnic_population_share`	Ethnic population share	float	CCL	0%	12	0.45, 0.13, 0.05, 0.03, 0.03
`ethnic_group_id`	Ethnic group id	float	CCL	0%	16	85008000, 85014000, 85009000, 85012000, 85017000
`regional_autonomy`	Regional autonomy	string	CCL	0%	3	true, true, true, true, true

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	, , , ,

IDN OpenFactBook IDN-OPENFACTBOOK Country Profile

16 rows · 16 table(s) · 2024 OpenFactBook 0 1 2 3 99 SEL 4 CCL 641 ext ▶

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0 Admin 0 — 16 table(s)

IDN 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	3.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric`	Mobile subscriptions per 100	float	SEL	0%	1	123.0
`internet_country_code_text`	Internet country code text	string	SEL+	0%	1	.id
`internet_users_percent_of_population_numeric`	Internet penetration percent	float	SEL	0%	1	69.0
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric`	Broadband subscriptions per 100	float	SEL	0%	1	5.0
`country_code`	Country code	string	SEL	0%	1	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`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	9.16 million (2023 est.)
`telephones_fixed_lines_total_subscriptions_numeric`	telephones_fixed_lines_total_subscriptions_numeric	float	0%	1	9.16
`telephones_fixed_lines_subscriptions_per_100_inhabitants_text`	telephones_fixed_lines_subscriptions_per_100_inhabitants_text	string	0%	1	3 (2023 est.)
`telephones_mobile_cellular_total_subscriptions_text`	telephones_mobile_cellular_total_subscriptions_text	string	0%	1	347 million (2024 est.)
`telephones_mobile_cellular_total_subscriptions_numeric`	telephones_mobile_cellular_total_subscriptions_numeric	float	0%	1	347.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_text`	telephones_mobile_cellular_subscriptions_per_100_inhabitants_text	string	0%	1	123 (2024 est.)
`broadcast_media_text`	broadcast_media_text	string	0%	1	mix of about a dozen national TV networks, including 1...
`broadcast_media_numeric`	broadcast_media_numeric	float	0%	1	1.0
`internet_users_percent_of_population_text`	internet_users_percent_of_population_text	string	0%	1	69% (2023 est.)
`broadband_fixed_subscriptions_total_text`	broadband_fixed_subscriptions_total_text	string	0%	1	13.5 million (2023 est.)
`broadband_fixed_subscriptions_total_numeric`	broadband_fixed_subscriptions_total_numeric	float	0%	1	13.5
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text`	broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text	string	0%	1	5 (2023 est.)
`source_section`	source_section	string	0%	1	Communications
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/id.json

IDN OpenFactBook - Economy — 1 rows, 153 columns

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Field details — 158 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	14500.0
`gdp_official_exchange_rate_numeric`	Gdp total usd	float	SEL	0%	1	1.396
`population_below_poverty_line_numeric`	Poverty headcount percent	float	SEL	0%	1	9.0
`country_code`	Country code	string	SEL	0%	1	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (152) — 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, largest and growing Southeast Asian...
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text`	Real gdp purchasing power parity 2024 (text)	string	0%	1	$4.102 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	4.102
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text`	Real gdp purchasing power parity 2023 (text)	string	0%	1	$3.906 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	3.906
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text`	Real gdp purchasing power parity 2022 (text)	string	0%	1	$3.718 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	3.718
`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	5% (2024 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric`	Real gdp growth rate 2024 (numeric)	float	0%	1	5.0
`real_gdp_growth_rate_real_gdp_growth_rate_2023_text`	Real gdp growth rate 2023 (text)	string	0%	1	5% (2023 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric`	Real gdp growth rate 2023 (numeric)	float	0%	1	5.0
`real_gdp_growth_rate_real_gdp_growth_rate_2022_text`	Real gdp growth rate 2022 (text)	string	0%	1	5.3% (2022 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric`	Real gdp growth rate 2022 (numeric)	float	0%	1	5.3
`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	$14,500 (2024 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_text`	Real gdp per capita 2023 (text)	string	0%	1	$13,900 (2023 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_numeric`	Real gdp per capita 2023 (numeric)	float	0%	1	13900.0
`real_gdp_per_capita_real_gdp_per_capita_2022_text`	Real gdp per capita 2022 (text)	string	0%	1	$13,300 (2022 est.)
`real_gdp_per_capita_real_gdp_per_capita_2022_numeric`	Real gdp per capita 2022 (numeric)	float	0%	1	13300.0
`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	$1.396 trillion (2024 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text`	Inflation rate consumer prices 2023 (text)	string	0%	1	3.7% (2023 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric`	Inflation rate consumer prices 2023 (numeric)	float	0%	1	3.7
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text`	Inflation rate consumer prices 2022 (text)	string	0%	1	4.2% (2022 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric`	Inflation rate consumer prices 2022 (numeric)	float	0%	1	4.2
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2021_text`	Inflation rate consumer prices 2021 (text)	string	0%	1	1.6% (2021 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2021_numeric`	Inflation rate consumer prices 2021 (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
`gdp_composition_by_sector_of_origin_agriculture_text`	gdp_composition_by_sector_of_origin_agriculture_text	string	0%	1	12.6% (2024 est.)
+122 more extension fields — download the CSV/Parquet to see them all.

IDN OpenFactBook - Energy — 1 rows, 59 columns

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Field details — 59 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	100.0
`country_code`	Country code	string	SEL	0%	1	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (55) — 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	100% (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	98.2%
`electricity_access_electrification_rural_areas_numeric`	electricity_access_electrification_rural_areas_numeric	float	0%	1	98.2
`electricity_installed_generating_capacity_text`	electricity_installed_generating_capacity_text	string	0%	1	70.826 million kW (2023 est.)
`electricity_installed_generating_capacity_numeric`	electricity_installed_generating_capacity_numeric	float	0%	1	70.826
`electricity_consumption_text`	electricity_consumption_text	string	0%	1	356.135 billion kWh (2023 est.)
`electricity_consumption_numeric`	electricity_consumption_numeric	float	0%	1	356.135
`electricity_imports_text`	electricity_imports_text	string	0%	1	828.198 million kWh (2023 est.)
`electricity_imports_numeric`	electricity_imports_numeric	float	0%	1	828.198
`electricity_transmission_distribution_losses_text`	electricity_transmission_distribution_losses_text	string	0%	1	27.477 billion kWh (2023 est.)
`electricity_transmission_distribution_losses_numeric`	electricity_transmission_distribution_losses_numeric	float	0%	1	27.477
`electricity_generation_sources_fossil_fuels_text`	electricity_generation_sources_fossil_fuels_text	string	0%	1	82% of total installed capacity (2023 est.)
`electricity_generation_sources_fossil_fuels_numeric`	electricity_generation_sources_fossil_fuels_numeric	float	0%	1	82.0
`electricity_generation_sources_solar_text`	electricity_generation_sources_solar_text	string	0%	1	0.2% of total installed capacity (2023 est.)
`electricity_generation_sources_solar_numeric`	electricity_generation_sources_solar_numeric	float	0%	1	0.2
`electricity_generation_sources_wind_text`	electricity_generation_sources_wind_text	string	0%	1	0.1% of total installed capacity (2023 est.)
`electricity_generation_sources_wind_numeric`	electricity_generation_sources_wind_numeric	float	0%	1	0.1
`electricity_generation_sources_hydroelectricity_text`	electricity_generation_sources_hydroelectricity_text	string	0%	1	6.4% of total installed capacity (2023 est.)
`electricity_generation_sources_hydroelectricity_numeric`	electricity_generation_sources_hydroelectricity_numeric	float	0%	1	6.4
`electricity_generation_sources_geothermal_text`	electricity_generation_sources_geothermal_text	string	0%	1	4.4% of total installed capacity (2023 est.)
`electricity_generation_sources_geothermal_numeric`	electricity_generation_sources_geothermal_numeric	float	0%	1	4.4
`electricity_generation_sources_biomass_and_waste_text`	electricity_generation_sources_biomass_and_waste_text	string	0%	1	6.9% of total installed capacity (2023 est.)
`electricity_generation_sources_biomass_and_waste_numeric`	electricity_generation_sources_biomass_and_waste_numeric	float	0%	1	6.9
`coal_production_text`	coal_production_text	string	0%	1	783.453 million metric tons (2023 est.)
`coal_production_numeric`	coal_production_numeric	float	0%	1	783.453
`coal_consumption_text`	coal_consumption_text	string	0%	1	281.159 million metric tons (2023 est.)
`coal_consumption_numeric`	coal_consumption_numeric	float	0%	1	281.159
`coal_exports_text`	coal_exports_text	string	0%	1	519.23 million metric tons (2023 est.)
+25 more extension fields — download the CSV/Parquet to see them all.

IDN 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	29.1
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	50.6
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	58.6
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	1.99
`waste_and_recycling_municipal_solid_waste_generated_annually_numeric`	Municipal waste kg per capita	float	SEL	0%	1	65.2
`country_code`	Country code	string	SEL	0%	1	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`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	large-scale deforestation (much of it illegal) and...
`international_environmental_agreements_party_to_text`	international_environmental_agreements_party_to_text	string	0%	1	Biodiversity, Climate Change, Climate Change-Kyoto...
`international_environmental_agreements_party_to_numeric`	international_environmental_agreements_party_to_numeric	float	0%	1	2006.0
`international_environmental_agreements_signed_but_not_ratified_text`	international_environmental_agreements_signed_but_not_ratified_text	string	0%	1	Marine Life Conservation
`climate_text`	climate_text	string	0%	1	tropical; hot, humid; more moderate in highlands
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	29.1% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 9.4% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	9.4
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 13.9% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	13.9
`land_use_agricultural_land_permanent_pasture_text`	land_use_agricultural_land_permanent_pasture_text	string	0%	1	permanent pasture: 5.8% (2023 est.)
`land_use_agricultural_land_permanent_pasture_numeric`	land_use_agricultural_land_permanent_pasture_numeric	float	0%	1	5.8
`land_use_forest_text`	land_use_forest_text	string	0%	1	50.6% (2023 est.)
`land_use_other_text`	land_use_other_text	string	0%	1	20.3% (2023 est.)
`land_use_other_numeric`	land_use_other_numeric	float	0%	1	20.3
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	58.6% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	1.99% annual rate of change (2020-25 est.)
`carbon_dioxide_emissions_total_emissions_text`	carbon_dioxide_emissions_total_emissions_text	string	0%	1	829.655 million metric tonnes of CO2 (2023 est.)
`carbon_dioxide_emissions_total_emissions_numeric`	carbon_dioxide_emissions_total_emissions_numeric	float	0%	1	829.655
`carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text`	carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text	string	0%	1	527.923 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	527.923
`carbon_dioxide_emissions_from_petroleum_and_other_liquids_text`	carbon_dioxide_emissions_from_petroleum_and_other_liquids_text	string	0%	1	223.352 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	223.352
`carbon_dioxide_emissions_from_consumed_natural_gas_text`	carbon_dioxide_emissions_from_consumed_natural_gas_text	string	0%	1	78.38 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	78.38
`particulate_matter_emissions_text`	particulate_matter_emissions_text	string	0%	1	18.4 micrograms per cubic meter (2019 est.)
`particulate_matter_emissions_numeric`	particulate_matter_emissions_numeric	float	0%	1	18.4
`methane_emissions_energy_text`	methane_emissions_energy_text	string	0%	1	3,621.7 kt (2022-2024 est.)
`methane_emissions_energy_numeric`	methane_emissions_energy_numeric	float	0%	1	3621.7
`methane_emissions_agriculture_text`	methane_emissions_agriculture_text	string	0%	1	3,379.3 kt (2019-2021 est.)
+22 more extension fields — download the CSV/Parquet to see them all.

IDN 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	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`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	Indonesian(s)
`nationality_adjective_text`	nationality_adjective_text	string	0%	1	Indonesian
`ethnic_groups_text`	ethnic_groups_text	string	0%	1	Javanese 40.1%, Sundanese 15.5%, Malay 3.7%, Batak 3.6%,...
`ethnic_groups_numeric`	ethnic_groups_numeric	float	0%	1	40.1
`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/id.json

IDN OpenFactBook - Geography — 1 rows, 53 columns

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Field details — 59 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	1904569.0
`area_land_numeric`	Area land sqkm	float	SEL	0%	1	1811569.0
`area_water_numeric`	Area water sqkm	float	SEL	0%	1	93000.0
`land_boundaries_total_numeric`	Land boundary km	float	SEL	0%	1	2958.0
`coastline_numeric`	Coastline km	float	SEL	0%	1	54716.0
`elevation_highest_point_numeric`	Elevation max m	float	SEL	0%	1	4884.0
`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	29.1
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	50.6
`irrigated_land_numeric`	Irrigated land sqkm	float	SEL	0%	1	67220.0
`country_code`	Country code	string	SEL	0%	1	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (46) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`location_text`	location_text	string	0%	1	Southeastern Asia, archipelago between the Indian Ocean...
`geographic_coordinates_text`	geographic_coordinates_text	string	0%	1	5 00 S, 120 00 E
`geographic_coordinates_numeric`	geographic_coordinates_numeric	float	0%	1	5.0
`map_references_text`	map_references_text	string	0%	1	Southeast Asia
`area_total_text`	area_total_text	string	0%	1	1,904,569 sq km
`area_land_text`	area_land_text	string	0%	1	1,811,569 sq km
`area_water_text`	area_water_text	string	0%	1	93,000 sq km
`area_comparative_text`	area_comparative_text	string	0%	1	slightly less than three times the size of Texas
`land_boundaries_total_text`	land_boundaries_total_text	string	0%	1	2,958 km
`land_boundaries_border_countries_text`	land_boundaries_border_countries_text	string	0%	1	Malaysia 1,881 km; Papua New Guinea 824 km; Timor-Leste 253 km
`land_boundaries_border_countries_numeric`	land_boundaries_border_countries_numeric	float	0%	1	1881.0
`coastline_text`	coastline_text	string	0%	1	54,716 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_note`	maritime_claims_note	string	0%	1	note: measured from claimed archipelagic straight baselines
`climate_text`	climate_text	string	0%	1	tropical; hot, humid; more moderate in highlands
`terrain_text`	terrain_text	string	0%	1	mostly coastal lowlands; larger islands have interior mountains
`elevation_highest_point_text`	elevation_highest_point_text	string	0%	1	Puncak Jaya 4,884 m
`elevation_lowest_point_text`	elevation_lowest_point_text	string	0%	1	Indian/Pacific Oceans 0 m
`elevation_mean_elevation_text`	elevation_mean_elevation_text	string	0%	1	367 m
`elevation_mean_elevation_numeric`	elevation_mean_elevation_numeric	float	0%	1	367.0
`natural_resources_text`	natural_resources_text	string	0%	1	petroleum, tin, natural gas, nickel, timber, bauxite,...
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	29.1% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 9.4% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	9.4
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 13.9% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	13.9
`land_use_agricultural_land_permanent_pasture_text`	land_use_agricultural_land_permanent_pasture_text	string	0%	1	permanent pasture: 5.8% (2023 est.)
+16 more extension fields — download the CSV/Parquet to see them all.

IDN OpenFactBook - Government — 1 rows, 84 columns

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Field details — 112 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	IDN
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (110) — 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	Republic of Indonesia
`country_name_conventional_short_form_text`	country_name_conventional_short_form_text	string	0%	1	Indonesia
`country_name_local_long_form_text`	country_name_local_long_form_text	string	0%	1	Republik Indonesia
`country_name_local_short_form_text`	country_name_local_short_form_text	string	0%	1	Indonesia
`country_name_former_text`	country_name_former_text	string	0%	1	Netherlands East Indies (Dutch East Indies), Netherlands...
`country_name_etymology_text`	country_name_etymology_text	string	0%	1	the name is an 18th-century construct of two Greek...
`country_name_etymology_numeric`	country_name_etymology_numeric	float	0%	1	18.0
`government_type_text`	government_type_text	string	0%	1	presidential republic
`capital_name_text`	capital_name_text	string	0%	1	Jakarta
`capital_geographic_coordinates_text`	capital_geographic_coordinates_text	string	0%	1	6 10 S, 106 49 E
`capital_geographic_coordinates_numeric`	capital_geographic_coordinates_numeric	float	0%	1	6.0
`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_time_zone_note_text`	capital_time_zone_note_text	string	0%	1	Indonesia has three time zones
`capital_etymology_text`	capital_etymology_text	string	0%	1	derives from the Sanscrit name Jayakarta, meaning...
`capital_etymology_numeric`	capital_etymology_numeric	float	0%	1	1527.0
`capital_note`	capital_note	string	0%	1	note: in 2022, the relocation of the country’s capital...
`administrative_divisions_text`	administrative_divisions_text	string	0%	1	35 provinces (provinsi-provinsi, singular - provinsi), 1...
`administrative_divisions_numeric`	administrative_divisions_numeric	float	0%	1	35.0
`legal_system_text`	legal_system_text	string	0%	1	civil law system based on the Roman-Dutch model and...
`constitution_history_text`	constitution_history_text	string	0%	1	drafted July to August 1945, effective 18 August 1945,...
`constitution_history_numeric`	constitution_history_numeric	float	0%	1	1945.0
`constitution_amendment_process_text`	constitution_amendment_process_text	string	0%	1	proposed by the People’s Consultative Assembly, with at...
`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 Indonesia
`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 continuous 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	17 years of age; universal; married persons regardless of age
+80 more extension fields — download the CSV/Parquet to see them all.

IDN OpenFactBook - Introduction — 1 rows, 6 columns

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`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	The archipelago was once largely under the control of...
`background_numeric`	background_numeric	float	0%	1	7.0
`source_section`	source_section	string	0%	1	Introduction
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/id.json

IDN OpenFactBook - Languages — 1 rows, 7 columns

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

Standards-Aligned Fields (3)

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`languages_languages_text`	Languages (text)	string	0%	1	Bahasa Indonesia (official, modified form of Malay),...
`languages_languages_numeric`	Languages (numeric)	float	0%	1	700.0
`languages_major_language_sample_s_text`	languages_major_language_sample_s_text	string	0%	1	Fakta Dunia, sumber informasi dasar yang sangat...
`source_section`	source_section	string	0%	1	People and Society:languages
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/id.json

IDN 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	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`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	11,964 (2024 est.)
`refugees_and_internally_displaced_persons_refugees_numeric`	refugees_and_internally_displaced_persons_refugees_numeric	float	0%	1	11964.0
`refugees_and_internally_displaced_persons_idps_text`	refugees_and_internally_displaced_persons_idps_text	string	0%	1	95,521 (2024 est.)
`refugees_and_internally_displaced_persons_idps_numeric`	refugees_and_internally_displaced_persons_idps_numeric	float	0%	1	95521.0
`refugees_and_internally_displaced_persons_stateless_persons_text`	refugees_and_internally_displaced_persons_stateless_persons_text	string	0%	1	2,643 (2024 est.)
`refugees_and_internally_displaced_persons_stateless_persons_numeric`	refugees_and_internally_displaced_persons_stateless_persons_numeric	float	0%	1	2643.0
`source_section`	source_section	string	0%	1	Transnational Issues:migration
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/id.json

IDN OpenFactBook - Military And Security — 1 rows, 21 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	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`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	Indonesian National Armed Forces (Tentara Nasional...
`military_and_security_forces_numeric`	military_and_security_forces_numeric	float	0%	1	2025.0
`military_expenditures_military_expenditures_2024_text`	Military expenditures 2024 (text)	string	0%	1	0.8% of GDP (2024 est.)
`military_expenditures_military_expenditures_2024_numeric`	Military expenditures 2024 (numeric)	float	0%	1	0.8
`military_expenditures_military_expenditures_2023_text`	Military expenditures 2023 (text)	string	0%	1	0.8% of GDP (2023 est.)
`military_expenditures_military_expenditures_2023_numeric`	Military expenditures 2023 (numeric)	float	0%	1	0.8
`military_expenditures_military_expenditures_2022_text`	Military expenditures 2022 (text)	string	0%	1	0.8% of GDP (2022 est.)
`military_expenditures_military_expenditures_2022_numeric`	Military expenditures 2022 (numeric)	float	0%	1	0.8
`military_expenditures_military_expenditures_2021_text`	Military expenditures 2021 (text)	string	0%	1	0.8% of GDP (2021 est.)
`military_expenditures_military_expenditures_2021_numeric`	Military expenditures 2021 (numeric)	float	0%	1	0.8
`military_expenditures_military_expenditures_2020_text`	Military expenditures 2020 (text)	string	0%	1	0.8% of GDP (2020 est.)
`military_expenditures_military_expenditures_2020_numeric`	Military expenditures 2020 (numeric)	float	0%	1	0.8
`military_and_security_service_personnel_strengths_text`	military_and_security_service_personnel_strengths_text	string	0%	1	approximately 400,000 active Armed Forces, including...
`military_and_security_service_personnel_strengths_numeric`	military_and_security_service_personnel_strengths_numeric	float	0%	1	400000.0
`military_equipment_inventories_and_acquisitions_text`	military_equipment_inventories_and_acquisitions_text	string	0%	1	the military's inventory is a mix of older and new...
`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 service for men and women;...
`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	250 (plus about 170 police) Central African Republic...
`military_deployments_numeric`	military_deployments_numeric	float	0%	1	250.0
`military_note_text`	military_note_text	string	0%	1	the military is responsible for external defense,...
`military_note_numeric`	military_note_numeric	float	0%	1	1960.0
`source_section`	source_section	string	0%	1	Military and Security
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/id.json

IDN OpenFactBook - People And Society — 1 rows, 138 columns

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

Standards-Aligned Fields (29)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`population_total_numeric`	Population count	float	SEL	0%	1	283587097.0
`population_male_numeric`	Population male	float	SEL	0%	1	141778977.0
`population_female_numeric`	Population female	float	SEL	0%	1	141808120.0
`age_structure_0_14_years_numeric`	Population 0 14 percent	float	SEL	0%	1	23.8
`age_structure_15_64_years_numeric`	Population 15 64 percent	float	SEL	0%	1	68.3
`age_structure_65_years_and_over_numeric`	Population 65 plus percent	float	SEL	0%	1	8.0
`dependency_ratios_total_dependency_ratio_numeric`	Total dependency ratio	float	SEL	0%	1	46.1
`dependency_ratios_youth_dependency_ratio_numeric`	Youth dependency ratio	float	SEL	0%	1	34.1
`dependency_ratios_elderly_dependency_ratio_numeric`	Elderly dependency ratio	float	SEL	0%	1	12.0
`median_age_total_numeric`	Median age	float	SEL	0%	1	31.8
`population_growth_rate_numeric`	Population growth rate percent	float	SEL	0%	1	0.7
`birth_rate_numeric`	Birth rate per 1000	float	SEL	0%	1	14.55
`death_rate_numeric`	Death rate per 1000	float	SEL	0%	1	6.82
`net_migration_rate_numeric`	Net migration per 1000	float	SEL	0%	1	-0.7
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	58.6
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	1.99
`sex_ratio_at_birth_numeric`	Sex ratio at birth	float	SEL	0%	1	1.05
`sex_ratio_total_population_numeric`	Sex ratio overall	float	SEL	0%	1	1.0
`maternal_mortality_ratio_numeric`	Maternal mortality per 100k	float	SEL	0%	1	140.0
`infant_mortality_rate_total_numeric`	Infant mortality per 1000	float	SEL	0%	1	18.5
`life_expectancy_at_birth_total_population_numeric`	Life expectancy	float	SEL	0%	1	73.6
`total_fertility_rate_numeric`	Fertility rate	float	SEL	0%	1	1.93
`gross_reproduction_rate_numeric`	Gross reproduction rate	float	SEL	0%	1	0.94
`physician_density_numeric`	Physicians per 1000	float	SEL	0%	1	0.52
`hospital_bed_density_numeric`	Hospital beds per 1000	float	SEL	0%	1	1.4
`literacy_total_population_numeric`	Literacy rate percent	float	SEL	0%	1	96.0
`country_code`	Country code	string	SEL	0%	1	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`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	283,587,097 (2025 est.)
`population_male_text`	population_male_text	string	0%	1	141,778,977
`population_female_text`	population_female_text	string	0%	1	141,808,120
`age_structure_0_14_years_text`	age_structure_0_14_years_text	string	0%	1	23.8% (male 34,247,218/female 32,701,367)
`age_structure_15_64_years_text`	age_structure_15_64_years_text	string	0%	1	68.3% (male 96,268,201/female 95,961,293)
`age_structure_65_years_and_over_text`	age_structure_65_years_and_over_text	string	0%	1	8% (2024 est.) (male 10,284,628/female 12,099,758)
`dependency_ratios_total_dependency_ratio_text`	dependency_ratios_total_dependency_ratio_text	string	0%	1	46.1 (2025 est.)
`dependency_ratios_youth_dependency_ratio_text`	dependency_ratios_youth_dependency_ratio_text	string	0%	1	34.1 (2025 est.)
`dependency_ratios_elderly_dependency_ratio_text`	dependency_ratios_elderly_dependency_ratio_text	string	0%	1	12 (2025 est.)
`dependency_ratios_potential_support_ratio_text`	dependency_ratios_potential_support_ratio_text	string	0%	1	8.3 (2025 est.)
`dependency_ratios_potential_support_ratio_numeric`	dependency_ratios_potential_support_ratio_numeric	float	0%	1	8.3
`median_age_total_text`	median_age_total_text	string	0%	1	31.8 years (2025 est.)
`median_age_male_text`	median_age_male_text	string	0%	1	30.8 years
`median_age_male_numeric`	median_age_male_numeric	float	0%	1	30.8
`median_age_female_text`	median_age_female_text	string	0%	1	32.3 years
`median_age_female_numeric`	median_age_female_numeric	float	0%	1	32.3
`population_growth_rate_text`	population_growth_rate_text	string	0%	1	0.7% (2025 est.)
`birth_rate_text`	birth_rate_text	string	0%	1	14.55 births/1,000 population (2025 est.)
`death_rate_text`	death_rate_text	string	0%	1	6.82 deaths/1,000 population (2025 est.)
`net_migration_rate_text`	net_migration_rate_text	string	0%	1	-0.7 migrant(s)/1,000 population (2025 est.)
`population_distribution_text`	population_distribution_text	string	0%	1	major concentration on the island of Java, which is...
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	58.6% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	1.99% annual rate of change (2020-25 est.)
`major_urban_areas_population_text`	major_urban_areas_population_text	string	0%	1	11.249 million JAKARTA (capital), 3.729 million Bekasi,...
`major_urban_areas_population_numeric`	major_urban_areas_population_numeric	float	0%	1	11.249
`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	1 male(s)/female
`sex_ratio_15_64_years_numeric`	sex_ratio_15_64_years_numeric	float	0%	1	1.0
+93 more extension fields — download the CSV/Parquet to see them all.

IDN OpenFactBook - Religions — 1 rows, 6 columns

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Field details — 30 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	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`admin_level`	Admin level	string	SEL	0%	1	national
`composition_religion_muslim_pct_synth`	Muslim	numeric	CCL	0%	-	87.4
`composition_religion_hindu_pct_synth`	Hindu	numeric	CCL	0%	-	1.7
`composition_religion_other_pct_synth`	other	numeric	CCL	0%	-	0.8
`composition_ethnicity_primary_label_synth`	Javanese	string	CCL	0%	-	Javanese

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	Muslim 87.4%, Protestant 7.5%, Roman Catholic 3.1%,...
`religions_numeric`	religions_numeric	float	0%	1	87.4
`source_section`	source_section	string	0%	1	People and Society:religions
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/id.json

Pending (19) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`composition_religion_protestant_pct_synth`	Protestant	numeric	0%	-	7.5
`composition_religion_roman_catholic_pct_synth`	Roman Catholic	numeric	0%	-	3.1
`composition_ethnicity_javanese_pct_synth`	Javanese	numeric	0%	-	40.1
`composition_ethnicity_sundanese_pct_synth`	Sundanese	numeric	0%	-	15.5
`composition_ethnicity_malay_pct_synth`	Malay	numeric	0%	-	3.7
`composition_ethnicity_batak_pct_synth`	Batak	numeric	0%	-	3.6
`composition_ethnicity_madurese_pct_synth`	Madurese	numeric	0%	-	3.0
`composition_ethnicity_betawi_pct_synth`	Betawi	numeric	0%	-	2.9
`composition_ethnicity_minangkabau_pct_synth`	Minangkabau	numeric	0%	-	2.7
`composition_ethnicity_buginese_pct_synth`	Buginese	numeric	0%	-	2.7
`composition_ethnicity_bantenese_pct_synth`	Bantenese	numeric	0%	-	2.0
`composition_ethnicity_banjarese_pct_synth`	Banjarese	numeric	0%	-	1.7
`composition_ethnicity_balinese_pct_synth`	Balinese	numeric	0%	-	1.7
`composition_ethnicity_acehnese_pct_synth`	Acehnese	numeric	0%	-	1.4
`composition_ethnicity_dayak_pct_synth`	Dayak	numeric	0%	-	1.4
`composition_ethnicity_sasak_pct_synth`	Sasak	numeric	0%	-	1.3
`composition_ethnicity_chinese_pct_synth`	Chinese	numeric	0%	-	1.2
`composition_ethnicity_other_pct_synth`	other	numeric	0%	-	15.0
`composition_ethnicity_primary_share_pct_synth`	Javanese	numeric	0%	-	40.1

IDN OpenFactBook - Space — 1 rows, 8 columns

Loading data…

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	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`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
`space_agency_agencies_text`	space_agency_agencies_text	string	0%	1	Indonesian Space Agency (INASA; formed 2022); National...
`space_agency_agencies_numeric`	space_agency_agencies_numeric	float	0%	1	2022.0
`space_program_overview_text`	space_program_overview_text	string	0%	1	focuses largely on rocket development and satellite...
`space_program_overview_numeric`	space_program_overview_numeric	float	0%	1	2025.0
`key_space_program_milestones_text`	key_space_program_milestones_text	string	0%	1	1964 - launched first sounding rocket (Kartika)1976 -...
`key_space_program_milestones_numeric`	key_space_program_milestones_numeric	float	0%	1	1964.0
`source_section`	source_section	string	0%	1	Space
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/id.json

IDN OpenFactBook - Terrorism — 1 rows, 6 columns

Loading data…

Field details — 6 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	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`admin_level`	Admin level	string	SEL	0%	1	national

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

Field Name	Label	Type	Nulls	Unique	Samples
`terrorist_group_s_text`	terrorist_group_s_text	string	0%	1	Islamic State of Iraq and ash-Sham (aka Jemaah Anshorut...
`source_section`	source_section	string	0%	1	Terrorism
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/id.json

IDN OpenFactBook - Transportation — 1 rows, 30 columns

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Field details — 32 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	PK
`airports_numeric`	Airports count	float	SEL	0%	1	556.0
`country_code`	Country code	string	SEL	0%	1	IDN
`country_name`	Country name	string	SEL	0%	1	Indonesia
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (27) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`airports_text`	airports_text	string	0%	1	556 (2025)
`heliports_text`	heliports_text	string	0%	1	53 (2025)
`heliports_numeric`	heliports_numeric	float	0%	1	53.0
`railways_total_text`	railways_total_text	string	0%	1	8,159 km (2014)
`railways_total_numeric`	railways_total_numeric	float	0%	1	8159.0
`railways_narrow_gauge_text`	railways_narrow_gauge_text	string	0%	1	8,159 km (2014) 1.067-m gauge (565 km electrified)
`railways_narrow_gauge_numeric`	railways_narrow_gauge_numeric	float	0%	1	8159.0
`railways_note`	railways_note	string	0%	1	note: 4,816 km operational
`merchant_marine_total_text`	merchant_marine_total_text	string	0%	1	11,422 (2023)
`merchant_marine_total_numeric`	merchant_marine_total_numeric	float	0%	1	11422.0
`merchant_marine_by_type_text`	merchant_marine_by_type_text	string	0%	1	bulk carrier 160, container ship 219, general cargo...
`merchant_marine_by_type_numeric`	merchant_marine_by_type_numeric	float	0%	1	160.0
`ports_total_ports_text`	ports_total_ports_text	string	0%	1	123 (2024)
`ports_total_ports_numeric`	ports_total_ports_numeric	float	0%	1	123.0
`ports_large_text`	ports_large_text	float	0%	1	3
`ports_large_numeric`	ports_large_numeric	float	0%	1	3.0
`ports_medium_text`	ports_medium_text	float	0%	1	6
`ports_medium_numeric`	ports_medium_numeric	float	0%	1	6.0
`ports_small_text`	ports_small_text	float	0%	1	18
`ports_small_numeric`	ports_small_numeric	float	0%	1	18.0
`ports_very_small_text`	ports_very_small_text	float	0%	1	96
`ports_very_small_numeric`	ports_very_small_numeric	float	0%	1	96.0
`ports_ports_with_oil_terminals_text`	Ports with oil terminals (text)	float	0%	1	79
`ports_ports_with_oil_terminals_numeric`	Ports with oil terminals (numeric)	float	0%	1	79.0
`ports_key_ports_text`	ports_key_ports_text	string	0%	1	Belawan, Cilacap, Dumai, Jakarta, Kasim Terminal, Merak...
`source_section`	source_section	string	0%	1	Transportation
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/id.json

IDN Global Organized Crime Index IDN-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)

IDN 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	IDN
`source`	source	string	0%	1	Global Organized Crime Index
`source_url`	source_url	string	0%	1	https://ocindex.net/
`year`	year	integer	0%	1	2025
`license`	license	string	0%	1	Creative Commons (GI-TOC / ENACT)
`oc_anti_money_laundering_rank`	oc_anti_money_laundering_rank	integer	0%	1	75
`oc_anti_money_laundering_2023`	oc_anti_money_laundering_2023	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	106
`oc_arms_trafficking_2023`	oc_arms_trafficking_2023	float	0%	1	4.5
`oc_arms_trafficking_2021`	oc_arms_trafficking_2021	float	0%	1	4.5
`oc_cannabis_trade_rank`	oc_cannabis_trade_rank	integer	0%	1	30
`oc_cannabis_trade_2023`	oc_cannabis_trade_2023	float	0%	1	6.5
`oc_cannabis_trade_2021`	oc_cannabis_trade_2021	float	0%	1	6.5
`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	24
`oc_criminal_actors_2023`	oc_criminal_actors_2023	float	0%	1	7.1
`oc_criminal_actors_2021`	oc_criminal_actors_2021	float	0%	1	6.75
`oc_criminal_markets_rank`	oc_criminal_markets_rank	integer	0%	1	21
`oc_criminal_markets_2023`	oc_criminal_markets_2023	float	0%	1	6.6
`oc_criminal_markets_2021`	oc_criminal_markets_2021	integer	0%	1	6
`oc_criminal_networks_rank`	oc_criminal_networks_rank	integer	0%	1	21
`oc_criminal_networks_2023`	oc_criminal_networks_2023	float	0%	1	7.5
`oc_criminal_networks_2021`	oc_criminal_networks_2021	float	0%	1	7.5
`oc_criminality_rank`	oc_criminality_rank	integer	0%	1	24
`oc_criminality_2023`	oc_criminality_2023	float	0%	1	6.85
`oc_criminality_2021`	oc_criminality_2021	float	0%	1	6.38
`oc_cyber_dependent_crimes_rank`	oc_cyber_dependent_crimes_rank	integer	0%	1	15
+74 more pending fields — download the CSV/Parquet to see them all.

IDN World Values Survey IDN-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)

IDN 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	IDN

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
World Values Survey	academic	metadata_catalog
GI-TOC / ENACT (Global Initiative Against Transnational Organized Crime · ENACT)	academic	bulk_download
Google	commercial	bulk_download
Ethnic Power Relations Dataset	academic	bulk_download
World Bank Open Data	international_organization	api
D-PLACE (Database of Places, Language, Culture & Environment)	academic	bulk_download
NGA GEOnet Names Server (GNS)	official_government	bulk_download
Global Data Lab	academic	api
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
GHS Urban Centre Database (Global Human Settlement · EU Joint Research Centre)	international_organization	bulk_download
LandScan Global (ORNL — Oak Ridge National Laboratory)	research_institution	earth_engine
OpenFactBook	community_compilation	bulk_download