Philippines

PHL PSA Population Age Sex Province PHL-PSA-POPULATION_AGE_SEX_PROVINCE Census

14,580 rows · 1 table(s) Philippine Statistics Authority 0 1 2 3 9 SEL 19 ext ▶

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2 Admin 2 — 1 table(s)

PHL PSA population_age_sex_province — 14,580 rows, 5 columns

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Field details — 28 fields (type, nulls, unique, samples)

Standards-Aligned Fields (9)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`geo_name`	Geographic unit name	string	SEL	0%	8	PHILIPPINES, NATIONAL CAPITAL REGION (NCR), City of...
`admin_level`	Administrative level	string	SEL	0%	3	admin_0, admin_1, admin_2
`population_count`	Total population (all ages)	integer	SEL	0%	8	109033245, 13484462, 1846513, 425758, 456059, 803159,...
`population_male`	Male population (all ages)	integer	SEL	0%	8	55306793, 6737870, 918643, 209013, 226189, 398811, 1471795, 61222
`population_female`	Female population (all ages)	integer	SEL	0%	8	53726452, 6746592, 927870, 216745, 229870, 404348, 1488253, 65125
`population_0_14`	Population aged 0-14 (both sexes, derived)	integer	SEL	0%	8	33431478, 3695266, 494157, 109913, 125756, 230220, 826435, 30366
`population_15_64`	Population aged 15-64 (both sexes, derived)	integer	SEL	0%	8	69734936, 9150380, 1258152, 295503, 303497, 536723,...
`population_60_plus`	Population aged 60 and over (both sexes, derived)	integer	SEL	0%	8	9242121, 1062581, 155307, 33338, 42607, 59618, 235715, 13215
`population_65_plus`	Population aged 65 and over (both sexes, derived)	integer	SEL	0%	8	5866831, 638816, 94204, 20342, 26806, 36216, 141222, 8386

Extension Fields (19) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	Country code (ISO 3166-1 alpha-3)	string	0%	1	PHL
`household_population`	Household population (all ages)	integer	0%	8	108667043, 13403551, 1837785, 419333, 452961, 801439,...
`pop_age_below_5`	Population aged Below 5 (both sexes)	integer	0%	8	11069479, 1279827, 169275, 38660, 42164, 81168, 291246, 10696
`pop_age_5_9`	Population aged 5-9 (both sexes)	integer	0%	8	11270637, 1237986, 166305, 36697, 42327, 78038, 276602, 10059
`pop_age_10_14`	Population aged 10-14 (both sexes)	integer	0%	8	11091362, 1177453, 158577, 34556, 41265, 71014, 258587, 9611
`pop_age_15_19`	Population aged 15-19 (both sexes)	integer	0%	8	10482815, 1118951, 157770, 31490, 38423, 65702, 242000, 8966
`pop_age_20_24`	Population aged 20-24 (both sexes)	integer	0%	8	10024753, 1284062, 181027, 43835, 40964, 72236, 275540, 11756
`pop_age_25_29`	Population aged 25-29 (both sexes)	integer	0%	8	9229288, 1298890, 178784, 46209, 40636, 76678, 277852, 11645
`pop_age_30_34`	Population aged 30-34 (both sexes)	integer	0%	8	8171423, 1174399, 155850, 39330, 36508, 71801, 253250, 10954
`pop_age_35_39`	Population aged 35-39 (both sexes)	integer	0%	8	7221785, 1017767, 133781, 33001, 32401, 62525, 220352, 9772
`pop_age_40_44`	Population aged 40-44 (both sexes)	integer	0%	8	6528846, 896189, 119221, 28304, 29822, 54119, 195936, 8977
`pop_age_45_49`	Population aged 45-49 (both sexes)	integer	0%	8	5598765, 749356, 101870, 23716, 26360, 43985, 166339, 7741
`pop_age_50_54`	Population aged 50-54 (both sexes)	integer	0%	8	4964629, 654711, 92711, 20232, 23434, 37004, 146739, 6915
`pop_age_55_59`	Population aged 55-59 (both sexes)	integer	0%	8	4137342, 532290, 76035, 16390, 19148, 29271, 119890, 6040
`pop_age_60_64`	Population aged 60-64 (both sexes)	integer	0%	8	3375290, 423765, 61103, 12996, 15801, 23402, 94493, 4829
`pop_age_65_69`	Population aged 65-69 (both sexes)	integer	0%	8	2398116, 281295, 40846, 8772, 11171, 15962, 61637, 3376
`pop_age_70_74`	Population aged 70-74 (both sexes)	integer	0%	8	1578185, 177144, 26818, 5793, 7419, 10223, 37992, 2286
`pop_age_75_79`	Population aged 75-79 (both sexes)	integer	0%	8	932231, 88950, 12938, 2942, 3789, 5029, 19925, 1237
`pop_age_80_years_old_and_over`	Population aged 80 years old and over (both sexes)	integer	0%	8	958299, 91427, 13602, 2835, 4427, 5002, 21668, 1487

PHL PSA Population Households Province PHL-PSA-POPULATION_HOUSEHOLDS_PROVINCE Census

405 rows · 1 table(s) Philippine Statistics Authority 0 1 2 3 4 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)

PHL PSA population_households_province — 405 rows, 3 columns

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Field details — 6 fields (type, nulls, unique, samples)

Standards-Aligned Fields (4)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`geo_name`	Geographic unit name	string	SEL	0%	8	PHILIPPINES, NATIONAL CAPITAL REGION (NCR), City of...
`admin_level`	Administrative level	string	SEL	0%	3	admin_0, admin_1, admin_2
`population_count`	Total population	integer	SEL	0%	8	109033245, 13484462, 1846513, 425758, 456059, 803159,...
`household_count`	Number of households	integer	SEL	0%	8	26393906, 3499652, 486293, 116954, 104415, 212895, 738724, 31519

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

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	Country code (ISO 3166-1 alpha-3)	string	0%	1	PHL
`household_population`	Household population	integer	0%	8	108667043, 13403551, 1837785, 419333, 452961, 801439,...

PHL PSA Population Age Sex Province (pivoted) PHL-PSA-POPULATION_AGE_SEX_PROVINCE-WIDE Census Wide

135 rows · 1 table(s) Philippine Statistics Authority 0 1 2 3 ▶

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2 Admin 2 — 1 table(s)

PHL PSA population_age_sex_province (wide) — 135 rows, 108 columns

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Field details — 108 fields (type, nulls, unique, samples)

Extension Fields (108) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`0_0_0`	0_0_0	numeric	0%	1	-
`0_0_1`	0_0_1	numeric	0%	1	-
`0_0_2`	0_0_2	numeric	0%	1	-
`0_0_3`	0_0_3	numeric	0%	1	-
`0_0_4`	0_0_4	numeric	0%	1	-
`0_0_5`	0_0_5	numeric	0%	1	-
`0_0_6`	0_0_6	numeric	0%	1	-
`0_0_7`	0_0_7	numeric	0%	1	-
`0_0_8`	0_0_8	numeric	0%	1	-
`0_0_9`	0_0_9	numeric	0%	1	-
`0_0_10`	0_0_10	numeric	0%	1	-
`0_0_11`	0_0_11	numeric	0%	1	-
`0_0_12`	0_0_12	numeric	0%	1	-
`0_0_13`	0_0_13	numeric	0%	1	-
`0_0_14`	0_0_14	numeric	0%	1	-
`0_0_15`	0_0_15	numeric	0%	1	-
`0_0_16`	0_0_16	numeric	0%	1	-
`0_0_17`	0_0_17	numeric	0%	1	-
`0_1_0`	0_1_0	numeric	0%	1	-
`0_1_1`	0_1_1	numeric	0%	1	-
`0_1_2`	0_1_2	numeric	0%	1	-
`0_1_3`	0_1_3	numeric	0%	1	-
`0_1_4`	0_1_4	numeric	0%	1	-
`0_1_5`	0_1_5	numeric	0%	1	-
`0_1_6`	0_1_6	numeric	0%	1	-
`0_1_7`	0_1_7	numeric	0%	1	-
`0_1_8`	0_1_8	numeric	0%	1	-
`0_1_9`	0_1_9	numeric	0%	1	-
`0_1_10`	0_1_10	numeric	0%	1	-
`0_1_11`	0_1_11	numeric	0%	1	-
+78 more extension fields — download the CSV/Parquet to see them all.

PHL PSA Poverty Province (pivoted) PHL-PSA-POVERTY_PROVINCE-WIDE Census Wide

103 rows · 1 table(s) Philippine Statistics Authority 0 1 2 3 ▶

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2 Admin 2 — 1 table(s)

PHL PSA poverty_province (wide) — 103 rows, 20 columns

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Field details — 20 fields (type, nulls, unique, samples)

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

Field Name	Label	Type	Nulls	Unique	Samples
`0_0`	0_0	numeric	0%	1	-
`0_1`	0_1	numeric	0%	1	-
`0_2`	0_2	numeric	0%	1	-
`0_3`	0_3	numeric	0%	1	-
`0_4`	0_4	numeric	0%	1	-
`1_0`	1_0	numeric	0%	1	-
`1_1`	1_1	numeric	0%	1	-
`1_2`	1_2	numeric	0%	1	-
`1_3`	1_3	numeric	0%	1	-
`1_4`	1_4	numeric	0%	1	-
`2_0`	2_0	numeric	0%	1	-
`2_1`	2_1	numeric	0%	1	-
`2_2`	2_2	numeric	0%	1	-
`2_3`	2_3	numeric	0%	1	-
`2_4`	2_4	numeric	0%	1	-
`3_0`	3_0	numeric	0%	1	-
`3_1`	3_1	numeric	0%	1	-
`3_2`	3_2	numeric	0%	1	-
`3_3`	3_3	numeric	0%	1	-
`3_4`	3_4	numeric	0%	1	-

PHL PSA Poverty Threshold Region (pivoted) PHL-PSA-POVERTY_THRESHOLD_REGION-WIDE Census Wide

103 rows · 1 table(s) Philippine Statistics Authority 0 1 2 3 ▶

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2 Admin 2 — 1 table(s)

PHL PSA poverty_threshold_region (wide) — 103 rows, 20 columns

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Field details — 20 fields (type, nulls, unique, samples)

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

Field Name	Label	Type	Nulls	Unique	Samples
`0_0`	0_0	numeric	0%	1	-
`0_1`	0_1	numeric	0%	1	-
`0_2`	0_2	numeric	0%	1	-
`0_3`	0_3	numeric	0%	1	-
`0_4`	0_4	numeric	0%	1	-
`1_0`	1_0	numeric	0%	1	-
`1_1`	1_1	numeric	0%	1	-
`1_2`	1_2	numeric	0%	1	-
`1_3`	1_3	numeric	0%	1	-
`1_4`	1_4	numeric	0%	1	-
`2_0`	2_0	numeric	0%	1	-
`2_1`	2_1	numeric	0%	1	-
`2_2`	2_2	numeric	0%	1	-
`2_3`	2_3	numeric	0%	1	-
`2_4`	2_4	numeric	0%	1	-
`3_0`	3_0	numeric	0%	1	-
`3_1`	3_1	numeric	0%	1	-
`3_2`	3_2	numeric	0%	1	-
`3_3`	3_3	numeric	0%	1	-
`3_4`	3_4	numeric	0%	1	-

PHL 2020 CPH — Ethnicity and Religious Affiliation (national) PHL-PSA-ETHNICITY-RELIGION-2020 Census

1 rows · 1 table(s) Philippine Statistics Authority 0 1 2 3 3 SEL 25 CCL 1 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)

Ethnicity and Religion (national) — 1 rows, 29 columns

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

Standards-Aligned Fields (28)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`geo_name`	Geographic unit name	string	SEL	0%	1	Philippines
`admin_level`	Administrative level	string	SEL	0%	1	admin_0
`population_count`	Household population (2020 CPH)	integer	SEL	0%	1	108667043
`ethnicity_tagalog`	Tagalog (26.0% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	28253431
`ethnicity_bisaya_binisaya`	Bisaya/Binisaya (14.3% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	15539387
`ethnicity_ilocano`	Ilocano (8.0% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	8693363
`ethnicity_cebuano`	Cebuano (8.0% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	8693363
`ethnicity_ilonggo_hiligaynon`	Ilonggo/Hiligaynon (7.9% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	8584696
`ethnicity_bikol`	Bikol/Bicol (6.5% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	7063358
`ethnicity_waray`	Waray (3.8% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	4129348
`ethnicity_kapampangan`	Kapampangan (3.0% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	3260011
`ethnicity_maguindanao`	Maguindanao (1.9% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	2064674
`ethnicity_pangasinan`	Pangasinan (1.9% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	2064674
`ip_non_indigenous`	Non-Indigenous Peoples (85.7% of household population, 2020 CPH)	integer	CCL	0%	1	93090000
`ip_ncip_indigenous`	Indigenous Peoples (NCIP-identified) (7.6% of household population, 2020 CPH)	integer	CCL	0%	1	8210000
`ip_ncmf_muslim`	Muslim tribes (NCMF-identified) (5.0% of household population, 2020 CPH)	integer	CCL	0%	1	5480000
`ip_ncip_ncmf_both`	IP and Muslim tribes (both NCIP & NCMF) (1.5% of household population, 2020 CPH)	integer	CCL	0%	1	1630000
`ip_foreign`	Foreign ethnicities (0.2% of household population, 2020 CPH)	integer	CCL	0%	1	230917
`religion_roman_catholic`	Roman Catholic (78.8% of household population, 2020 CPH)	integer	CCL	0%	1	85645362
`religion_islam`	Islam (6.4% of household population, 2020 CPH)	integer	CCL	0%	1	6981710
`religion_iglesia_ni_cristo`	Iglesia ni Cristo (2.6% of household population, 2020 CPH)	integer	CCL	0%	1	2806524
`religion_seventh_day_adventist`	Seventh Day Adventist (0.8% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	869336
`religion_aglipay`	Aglipay (0.8% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	869336
`religion_iglesia_filipina_independiente`	Iglesia Filipina Independiente (0.6% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	652002
`religion_bible_baptist_church`	Bible Baptist Church (0.5% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	543335
`religion_uccp`	United Church of Christ in the Philippines (0.4% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	434668
`religion_jehovahs_witness`	Jehovah's Witness (0.4% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	434668
`religion_church_of_christ`	Church of Christ (0.4% of household population, 2020 CPH) — derived from PSA %	integer	CCL	0%	1	434668

Extension Fields (1) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	Country code (ISO 3166-1 alpha-3)	string	0%	1	PHL

PHL Philippines Rainfall Indicators at Subnational Le PHL-HDX-Philippines__Rainfall_Indicators_at_Subn Climate

159,740 rows · 1 table(s) HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

PHL Philippines Rainfall Indicators at Subnational Le — 159,740 rows, 15 columns

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Field details — 15 fields (type, nulls, unique, samples)

Extension Fields (15) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`date`	date	string	0%	100	1981-01-01, 1981-01-11, 1981-01-21, 1981-02-01, 1981-02-11
`adm_level`	adm_level	string	0%	1	1, 1, 1, 1, 1
`adm_id`	adm_id	string	0%	1	900566, 900566, 900566, 900566, 900566
`PCODE`	PCODE	string	0%	1	PH01, PH01, PH01, PH01, PH01
`n_pixels`	n_pixels	float	0%	1	426.0, 426.0, 426.0, 426.0, 426.0
`rfh`	rfh	float	0%	99	4.906103, 2.225352, 1.9859155, 1.2464789, 0.87558687
`rfh_avg`	rfh_avg	float	0%	36	2.55313, 1.9203442, 2.1950705, 2.1001565, 2.5606415
`r1h`	r1h	float	2%	98	9.117371, 5.4577465, 4.107981, 4.1408453, 7.4788733
`r1h_avg`	r1h_avg	float	2%	36	6.668545, 6.215571, 6.8558683, 7.7507825, 12.155634
`r3h`	r3h	float	8%	92	28.131454, 26.361504, 29.068075, 64.938965, 90.61972
`r3h_avg`	r3h_avg	float	8%	36	42.878483, 49.709232, 61.748512, 87.26675, 129.0716
`rfq`	rfq	float	0%	100	131.15228, 104.40741, 97.09309, 87.97663, 77.71281
`r1q`	r1q	float	2%	98	120.98656, 93.24311, 76.822556, 71.68851, 72.73921
`r3q`	r3q	float	8%	92	69.19905, 57.323967, 51.03946, 75.800835, 71.31989
`version`	version	string	0%	1	final, final, final, final, final

PHL Philippines Food Prices PHL-HDX-Philippines___Food_Prices Food Security

152,385 rows · 1 table(s) HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

PHL Philippines Food Prices — 152,385 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
`date`	date	string	0%	4	2000-01-15, 2000-01-15, 2000-01-15, 2000-01-15, 2000-01-15
`admin1`	admin1	string	0%	7	National Capital region, National Capital region,...
`admin2`	admin2	string	0%	7	Metropolitan Manila, Metropolitan Manila, Metropolitan...
`market`	market	string	0%	7	Metro Manila, Metro Manila, Metro Manila, Metro Manila,...
`market_id`	market_id	string	0%	7	167, 167, 167, 167, 167
`latitude`	latitude	string	0%	7	14.6, 14.6, 14.6, 14.6, 14.6
`longitude`	longitude	string	0%	7	120.98, 120.98, 120.98, 120.98, 120.98
`category`	category	string	0%	2	cereals and tubers, cereals and tubers, cereals and...
`commodity`	commodity	string	0%	6	Rice (milled, superior), Rice (milled, superior), Rice...
`commodity_id`	commodity_id	string	0%	6	593, 593, 80, 80, 140
`unit`	unit	string	0%	1	KG, KG, KG, KG, KG
`priceflag`	priceflag	string	0%	1	actual, actual, actual, actual, actual
`pricetype`	pricetype	string	0%	2	Retail, Wholesale, Retail, Wholesale, Retail
`currency`	currency	string	0%	1	PHP, PHP, PHP, PHP, PHP
`price`	price	string	0%	66	20, 18.35, 18, 16.35, 105.37
`usdprice`	usdprice	string	0%	38	0.49, 0.45, 0.44, 0.4, 2.6

PHL Philippines Open, validated health, climate, env PHL-HDX-Philippines___Open,_validated_health,_cl Climate

74,880 rows · 1 table(s) 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.

3 Admin 3 — 1 table(s)

PHL Philippines Open, validated health, climate, env — 74,880 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
`uuid`	uuid	text	0%	-	-
`freq`	freq	text	0%	-	-
`date`	date	text	0%	-	-
`source_name`	source_name	text	0%	-	-
`source_filename`	source_filename	text	0%	-	-
`adm3_pcode`	adm3_pcode	text	0%	-	-
`disease_icd10_code`	disease_icd10_code	text	0%	-	-
`disease_common_name`	disease_common_name	text	0%	-	-
`case_total`	case_total	text	0%	-	-

PHL Philippines 2015 Census Population by Admin4(Baran PHL-HDX-Philippines_2015_Census_Population_by_Ad Census

42,029 rows · 1 table(s) HDX 0 1 2 3 4 ▶

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

4 Admin 4 — 1 table(s)

PHL Philippines 2015 Census Population by Admin4(Baran — 42,029 rows, 210 columns

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Field details — 210 fields (type, nulls, unique, samples)

Extension Fields (210) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`adm1_code`	adm1 code	text	0%	-	-
`adm1_name`	adm1 name	text	0%	-	-
`adm2_code`	adm2 code	text	0%	-	-
`adm2_name`	adm2 name	text	0%	-	-
`adm3_code`	adm3 code	text	0%	-	-
`adm3_name`	adm3 name	text	0%	-	-
`adm4_code`	adm4 code	text	0%	-	-
`adm4_name`	adm4 name	text	0%	-	-
`FUnder_1`	FUnder 1	text	0%	-	-
`F1`	F1	text	0%	-	-
`F2`	F2	text	0%	-	-
`F3`	F3	text	0%	-	-
`F4`	F4	text	0%	-	-
`F5`	F5	text	0%	-	-
`F6`	F6	text	0%	-	-
`F7`	F7	text	0%	-	-
`F8`	F8	text	0%	-	-
`F9`	F9	text	0%	-	-
`F10`	F10	text	0%	-	-
`F11`	F11	text	0%	-	-
`F12`	F12	text	0%	-	-
`F13`	F13	text	0%	-	-
`F14`	F14	text	0%	-	-
`F15`	F15	text	0%	-	-
`F16`	F16	text	0%	-	-
`F17`	F17	text	0%	-	-
`F18`	F18	text	0%	-	-
`F19`	F19	text	0%	-	-
`F20`	F20	text	0%	-	-
`F21`	F21	text	0%	-	-
+180 more extension fields — download the CSV/Parquet to see them all.

PHL Philippine Dengue Cases and Deaths PHL-HDX-Philippine_Dengue_Cases_and_Deaths Health

32,702 rows · 1 table(s) 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.

1 Admin 1 — 1 table(s)

PHL Philippine Dengue Cases and Deaths — 32,702 rows, 5 columns

Loading data…

Field details — 5 fields (type, nulls, unique, samples)

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

Field Name	Label	Type	Nulls	Unique	Samples
`loc`	loc	string	0%	2	ALBAY, ALBAY, ALBAY, ALBAY, ALBAY
`cases`	cases	string	0%	36	15, 13, 9, 14, 9
`deaths`	deaths	string	0%	3	0, 0, 0, 0, 0
`date`	date	string	0%	52	1/10/2016, 1/17/2016, 1/24/2016, 1/31/2016, 2/7/2016
`Region`	Region	string	0%	2	REGION V-BICOL REGION, REGION V-BICOL REGION, REGION...

PHL Philippines Real Time Prices PHL-HDX-Philippines___Real_Time_Prices Food Security

25,080 rows · 1 table(s) 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.

2 Admin 2 — 1 table(s)

PHL Philippines Real Time Prices — 25,080 rows, 858 columns

Loading data…

Field details — 858 fields (type, nulls, unique, samples)

Extension Fields (858) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`ISO3`	ISO3	string	0%	1	PHL, PHL, PHL, PHL, PHL
`country`	country	string	0%	1	Philippines, Philippines, Philippines, Philippines, Philippines
`adm1_name`	adm1_name	string	0%	1	Cordillera Administrative region, Cordillera...
`adm2_name`	adm2_name	string	0%	1	Abra, Abra, Abra, Abra, Abra
`mkt_name`	mkt_name	string	0%	1	Abra, Abra, Abra, Abra, Abra
`lat`	lat	string	0%	1	17.6, 17.6, 17.6, 17.6, 17.6
`lon`	lon	string	0%	1	120.62, 120.62, 120.62, 120.62, 120.62
`geo_id`	geo_id	string	0%	1	gid_1760000001206200000, gid_1760000001206200000,...
`DATES`	DATES	string	0%	100	2007-01-01, 2007-02-01, 2007-03-01, 2007-04-01, 2007-05-01
`year`	year	string	0%	9	2007, 2007, 2007, 2007, 2007
`month`	month	string	0%	12	1, 2, 3, 4, 5
`currency`	currency	string	0%	1	PHP, PHP, PHP, PHP, PHP
`components`	components	string	0%	1	beans (1 KG, Index Weight = 1), cabbage (1 KG, Index...
`start_dense_data`	start_dense_data	string	0%	1	Jan 2007, Jan 2007, Jan 2007, Jan 2007, Jan 2007
`last_survey_point`	last_survey_point	string	0%	1	Nov 2025, Nov 2025, Nov 2025, Nov 2025, Nov 2025
`data_coverage`	data_coverage	float	0%	1	19.82, 19.82, 19.82, 19.82, 19.82
`data_coverage_recent`	data_coverage_recent	float	0%	1	37.12, 37.12, 37.12, 37.12, 37.12
`index_confidence_score`	index_confidence_score	float	0%	1	0.98, 0.98, 0.98, 0.98, 0.98
`spatially_interpolated`	spatially_interpolated	string	0%	1	0, 0, 0, 0, 0
`apples`	apples	string	100%	-	-
`bananas`	bananas	string	100%	-	-
`beans`	beans	string	100%	-	-
`beans_egyptian`	beans_egyptian	string	100%	-	-
`beans_fao`	beans_fao	string	100%	-	-
`bread`	bread	string	100%	-	-
`bread_fao`	bread_fao	string	100%	-	-
`bulgur`	bulgur	string	100%	-	-
`cabbage`	cabbage	string	100%	-	-
`carrots`	carrots	string	100%	-	-
`cassava`	cassava	string	100%	-	-
+828 more extension fields — download the CSV/Parquet to see them all.

PHL Philippines Health Indicators PHL-HDX-Philippines___Health_Indicators Health

24,263 rows · 1 table(s) 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.

1 Admin 1 — 1 table(s)

PHL Philippines Health Indicators — 24,263 rows, 17 columns

Loading data…

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)	text	0%	-	-
`GHO (DISPLAY)`	GHO (DISPLAY)	text	0%	-	-
`GHO (URL)`	GHO (URL)	text	0%	-	-
`YEAR (DISPLAY)`	YEAR (DISPLAY)	text	0%	-	-
`STARTYEAR`	STARTYEAR	text	0%	-	-
`ENDYEAR`	ENDYEAR	text	0%	-	-
`REGION (CODE)`	REGION (CODE)	text	0%	-	-
`REGION (DISPLAY)`	REGION (DISPLAY)	text	0%	-	-
`COUNTRY (CODE)`	COUNTRY (CODE)	text	0%	-	-
`COUNTRY (DISPLAY)`	COUNTRY (DISPLAY)	text	0%	-	-
`DIMENSION (TYPE)`	DIMENSION (TYPE)	text	0%	-	-
`DIMENSION (CODE)`	DIMENSION (CODE)	text	0%	-	-
`DIMENSION (NAME)`	DIMENSION (NAME)	text	0%	-	-
`Numeric`	Numeric	text	0%	-	-
`Value`	Value	text	0%	-	-
`Low`	Low	text	0%	-	-
`High`	High	text	0%	-	-

PHL Philippines Historical Health Indicators PHL-HDX-Philippines___Historical_Health_Indicato Health

16,850 rows · 1 table(s) 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.

1 Admin 1 — 1 table(s)

PHL Philippines Historical Health Indicators — 16,850 rows, 17 columns

Loading data…

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)	text	0%	-	-
`GHO (DISPLAY)`	GHO (DISPLAY)	text	0%	-	-
`GHO (URL)`	GHO (URL)	text	0%	-	-
`YEAR (DISPLAY)`	YEAR (DISPLAY)	text	0%	-	-
`STARTYEAR`	STARTYEAR	text	0%	-	-
`ENDYEAR`	ENDYEAR	text	0%	-	-
`REGION (CODE)`	REGION (CODE)	text	0%	-	-
`REGION (DISPLAY)`	REGION (DISPLAY)	text	0%	-	-
`COUNTRY (CODE)`	COUNTRY (CODE)	text	0%	-	-
`COUNTRY (DISPLAY)`	COUNTRY (DISPLAY)	text	0%	-	-
`DIMENSION (TYPE)`	DIMENSION (TYPE)	text	0%	-	-
`DIMENSION (CODE)`	DIMENSION (CODE)	text	0%	-	-
`DIMENSION (NAME)`	DIMENSION (NAME)	text	0%	-	-
`Numeric`	Numeric	text	0%	-	-
`Value`	Value	text	0%	-	-
`Low`	Low	text	0%	-	-
`High`	High	text	0%	-	-

PHL Philippines Education PHL-HDX-Philippines___Education Indicators

16,079 rows · 1 table(s) HDX 0 1 2 3 1 SEL 5 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)

PHL Philippines Education — 16,079 rows, 6 columns

Loading data…

Field details — 6 fields (type, nulls, unique, samples)

Standards-Aligned Fields (1)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`Country ISO3`	Country ISO3	text	SEL+	0%	-	-

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

Field Name	Label	Type	Nulls	Unique	Samples
`Country Name`	Country Name	text	0%	-	-
`Year`	Year	text	0%	-	-
`Indicator Name`	Indicator Name	text	0%	-	-
`Indicator Code`	Indicator Code	text	0%	-	-
`Value`	Value	text	0%	-	-

PHL Philippines Healthsites PHL-HDX-Philippines_Healthsites Health

15,252 rows · 1 table(s) 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)

PHL Philippines Healthsites — 15,252 rows, 35 columns

Loading data…

Field details — 35 fields (type, nulls, unique, samples)

Extension Fields (35) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`X`	X	float	9%	91	120.590634537907, 123.805240250065, 123.817510266663,...
`Y`	Y	float	9%	91	15.3343079233724, 10.2510233671717, 10.2579437178888,...
`osm_id`	osm_id	string	0%	100	1667300362, 11469041173, 4631944097, 4047131089, 9849381766
`osm_type`	osm_type	string	0%	2	node, node, node, node, node
`completeness`	completeness	string	0%	8	15.625, 18.75, 25, 12.5, 18.75
`amenity`	amenity	string	7%	5	pharmacy, pharmacy, pharmacy, doctors, pharmacy
`healthcare`	healthcare	string	26%	8	pharmacy, pharmacy, pharmacy, pharmacy, doctor
`name`	name	string	9%	73	Vincarlo Pharma Drugstore, Rose Pharmacy, Rose Pharmacy,...
`operator`	operator	string	88%	11	Rodolfo Saavedra, M.D., Western Visayas Medical Center,...
`source`	source	string	96%	3	GPS, interpolation, interpolation, mercury website
`speciality`	speciality	string	94%	6	dentist, general;paediatrics;blood_check,...
`operator_type`	operator_type	string	95%	3	government, public, government, government, private
`operational_status`	operational_status	string	100%	-	-
`opening_hours`	opening_hours	string	90%	10	Mo-Su 09:00-20:00, Mo-Su 06:00-22:00, 07:00-22:00, Mo-Su...
`beds`	beds	string	100%	-	-
`staff_doctors`	staff_doctors	string	100%	-	-
`staff_nurses`	staff_nurses	string	100%	-	-
`health_amenity_type`	health_amenity_type	string	100%	-	-
`dispensing`	dispensing	string	81%	2	yes, yes, yes, yes, yes
`wheelchair`	wheelchair	string	97%	1	yes, yes, yes
`emergency`	emergency	string	100%	-	-
`insurance`	insurance	string	100%	-	-
`water_source`	water_source	string	100%	-	-
`electricity`	electricity	string	100%	-	-
`is_in_health_area`	is_in_health_area	string	100%	-	-
`is_in_health_zone`	is_in_health_zone	string	100%	-	-
`url`	url	string	100%	-	-
`addr_housenumber`	addr_housenumber	string	100%	-	-
`addr_street`	addr_street	string	49%	32	Cebu South Road, Natalio Bacalso Avenue, Natalio Bacalso...
`addr_postcode`	addr_postcode	string	78%	13	6045, 3309, 6046, 3005, 6052
+5 more extension fields — download the CSV/Parquet to see them all.

PHL Philippines Economy and Growth PHL-HDX-Philippines___Economy_and_Growth Indicators

11,848 rows · 1 table(s) 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)

PHL Philippines Economy and Growth — 11,848 rows, 247 columns

Loading data…

Field details — 247 fields (type, nulls, unique, samples)

Extension Fields (247) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	PHL
`Trade_in_services_pct_of_GDP`	Trade_in_services_pct_of_GDP	float	0%	1	19.3268460131213
`Communications_computer_etc._pct_of_service_imports_BoP`	Communications_computer_etc._pct_of_service_imports_BoP	float	0%	1	32.691464502541
`Primary_income_payments_BoP_current_USusd`	Primary_income_payments_BoP_current_USusd	float	0%	1	12779946040.2907
`Imports_of_goods_and_services_BoP_current_USusd`	Imports_of_goods_and_services_BoP_current_USusd	float	0%	1	161543811954.468
`Insurance_and_financial_services_pct_of_service_imports_BoP`	Insurance_and_financial_services_pct_of_service_imports_BoP	float	0%	1	11.8811329244484
`Goods_imports_BoP_current_USusd`	Goods_imports_BoP_current_USusd	float	0%	1	123919858028.284
`Service_imports_BoP_current_USusd`	Service_imports_BoP_current_USusd	float	0%	1	37623953926.1836
`Charges_for_the_use_of_intellectual_property_payments_BoP_current_USusd`	Charges_for_the_use_of_intellectual_property_payments_BoP_current_USusd	float	0%	1	443107068.46
`Imports_of_goods_services_and_primary_income_BoP_current_USusd`	Imports_of_goods_services_and_primary_income_BoP_current_USusd	float	0%	1	174323757994.759
`Transport_services_pct_of_service_imports_BoP`	Transport_services_pct_of_service_imports_BoP	float	0%	1	19.9182442902911
`Travel_services_pct_of_service_imports_BoP`	Travel_services_pct_of_service_imports_BoP	float	0%	1	33.9777269869803
`Foreign_direct_investment_net_outflows_BoP_current_USusd`	Foreign_direct_investment_net_outflows_BoP_current_USusd	float	0%	1	2871633477.4884
`Foreign_direct_investment_net_outflows_pct_of_GDP`	Foreign_direct_investment_net_outflows_pct_of_GDP	float	0%	1	0.622080708949349
`Secondary_income_other_sectors_payments_BoP_current_USusd`	Secondary_income_other_sectors_payments_BoP_current_USusd	float	0%	1	1153346398.47276
`Personal_remittances_paid_current_USusd`	Personal_remittances_paid_current_USusd	float	0%	1	268879630.201638
`Current_account_balance_BoP_current_USusd`	Current_account_balance_BoP_current_USusd	float	0%	1	-18262196995.7228
`Current_account_balance_pct_of_GDP`	Current_account_balance_pct_of_GDP	float	0%	1	-3.95613177765573
`Net_financial_account_BoP_current_USusd`	Net_financial_account_BoP_current_USusd	float	0%	1	-19594843232.1106
`Net_primary_income_BoP_current_USusd`	Net_primary_income_BoP_current_USusd	float	0%	1	4946227063.73568
`Net_trade_in_goods_and_services_BoP_current_USusd`	Net_trade_in_goods_and_services_BoP_current_USusd	float	0%	1	-54895208989.7739
`Net_trade_in_goods_BoP_current_USusd`	Net_trade_in_goods_BoP_current_USusd	float	0%	1	-68863406422.6474
`Net_errors_and_omissions_BoP_current_USusd`	Net_errors_and_omissions_BoP_current_USusd	float	0%	1	-1404936500.60783
`Foreign_direct_investment_net_BoP_current_USusd`	Foreign_direct_investment_net_BoP_current_USusd	float	0%	1	-6568395421.15439
`Portfolio_investment_net_BoP_current_USusd`	Portfolio_investment_net_BoP_current_USusd	float	0%	1	-4743750575.10458
`Reserves_and_related_items_BoP_current_USusd`	Reserves_and_related_items_BoP_current_USusd	float	0%	1	609606342.215797
`Net_secondary_income_BoP_current_USusd`	Net_secondary_income_BoP_current_USusd	float	0%	1	31686784930.3152
`Net_capital_account_BoP_current_USusd`	Net_capital_account_BoP_current_USusd	float	0%	1	72290264.22
`Grants_excluding_technical_cooperation_BoP_current_USusd`	Grants_excluding_technical_cooperation_BoP_current_USusd	float	0%	1	552855203.0
`Technical_cooperation_grants_BoP_current_USusd`	Technical_cooperation_grants_BoP_current_USusd	float	0%	1	130911045.0
+217 more extension fields — download the CSV/Parquet to see them all.

PHL Philippines Health PHL-HDX-Philippines___Health Health

10,165 rows · 1 table(s) HDX 0 1 2 3 1 SEL 5 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)

PHL Philippines Health — 10,165 rows, 6 columns

Loading data…

Field details — 6 fields (type, nulls, unique, samples)

Standards-Aligned Fields (1)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`Country ISO3`	Country ISO3	text	SEL+	0%	-	-

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

Field Name	Label	Type	Nulls	Unique	Samples
`Country Name`	Country Name	text	0%	-	-
`Year`	Year	text	0%	-	-
`Indicator Name`	Indicator Name	text	0%	-	-
`Indicator Code`	Indicator Code	text	0%	-	-
`Value`	Value	text	0%	-	-

PHL Philippines Environment PHL-HDX-Philippines___Environment Climate

5,009 rows · 1 table(s) 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)

PHL Philippines Environment — 5,009 rows, 147 columns

Loading data…

Field details — 147 fields (type, nulls, unique, samples)

Extension Fields (147) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	PHL
`Agricultural_land_pct_of_land_area`	Agricultural_land_pct_of_land_area	float	0%	1	42.6689472448603
`Arable_land_pct_of_land_area`	Arable_land_pct_of_land_area	float	0%	1	18.7476942683704
`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	12170.141244
`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	4.1356910066334
`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	1511.452095905
`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	0.513625825260924
`Land_area_where_elevation_is_below_5_meters_pct_of_total_land_area`	Land_area_where_elevation_is_below_5_meters_pct_of_total_land_area	float	0%	1	4.64931683189432
`Forest_area_sq._km`	Forest_area_sq._km	float	0%	1	72932.6
`Forest_area_pct_of_land_area`	Forest_area_pct_of_land_area	float	0%	1	24.4600731126539
`Average_precipitation_in_depth_mm_per_year`	Average_precipitation_in_depth_mm_per_year	float	0%	1	2348.0
`Land_area_sq._km`	Land_area_sq._km	float	0%	1	298170.0
`Rural_land_area_sq._km`	Rural_land_area_sq._km	float	0%	1	282119.58210558
`Urban_land_area_sq._km`	Urban_land_area_sq._km	float	0%	1	12151.465331954
`Surface_area_sq._km`	Surface_area_sq._km	float	0%	1	300000.0
`Access_to_clean_fuels_and_technologies_for_cooking_rural_pct_of_rural_population`	Access_to_clean_fuels_and_technologies_for_cooking_rural_pct_of_rural_population	float	0%	1	39.9
`Access_to_clean_fuels_and_technologies_for_cooking_urban_pct_of_urban_population`	Access_to_clean_fuels_and_technologies_for_cooking_urban_pct_of_urban_population	float	0%	1	79.8
`Access_to_clean_fuels_and_technologies_for_cooking_pct_of_population`	Access_to_clean_fuels_and_technologies_for_cooking_pct_of_population	float	0%	1	59.5
`Energy_intensity_level_of_primary_energy_MJ_usd2021_PPP_GDP`	Energy_intensity_level_of_primary_energy_MJ_usd2021_PPP_GDP	float	0%	1	2.78
`Access_to_electricity_pct_of_population`	Access_to_electricity_pct_of_population	float	0%	1	98.0
`Electricity_production_from_oil_gas_and_coal_sources_pct_of_total`	Electricity_production_from_oil_gas_and_coal_sources_pct_of_total	float	0%	1	77.864861229431
`Renewable_electricity_output_pct_of_total_electricity_output`	Renewable_electricity_output_pct_of_total_electricity_output	float	0%	1	22.7211103754847
`Electricity_production_from_renewable_sources_excluding_hydroelectric_kWh`	Electricity_production_from_renewable_sources_excluding_hydroelectric_kWh	float	0%	1	14838030000.0
`Electricity_production_from_renewable_sources_excluding_hydroelectric_pct_of_tot`	Electricity_production_from_renewable_sources_excluding_hydroelectric_pct_of_tot	float	0%	1	14.0338882058072
`Renewable_energy_consumption_pct_of_total_final_energy_consumption`	Renewable_energy_consumption_pct_of_total_final_energy_consumption	float	0%	1	28.0
`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	20.2887417122616
`PM2.5_pollution_population_exposed_to_levels_exceeding_WHO_Interim_Target-1_valu`	PM2.5_pollution_population_exposed_to_levels_exceeding_WHO_Interim_Target-1_valu	float	0%	1	0.0
`PM2.5_pollution_population_exposed_to_levels_exceeding_WHO_Interim_Target-2_valu`	PM2.5_pollution_population_exposed_to_levels_exceeding_WHO_Interim_Target-2_valu	float	0%	1	6.19320697791801
`PM2.5_pollution_population_exposed_to_levels_exceeding_WHO_Interim_Target-3_valu`	PM2.5_pollution_population_exposed_to_levels_exceeding_WHO_Interim_Target-3_valu	float	0%	1	78.5573277504976
`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	96.3706587650922
+117 more extension fields — download the CSV/Parquet to see them all.

PHL Philippines Gender PHL-HDX-Philippines___Gender Indicators

4,955 rows · 1 table(s) 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)

PHL Philippines Gender — 4,955 rows, 238 columns

Loading data…

Field details — 238 fields (type, nulls, unique, samples)

Extension Fields (238) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	PHL
`Firms_with_female_top_manager_pct_of_firms`	Firms_with_female_top_manager_pct_of_firms	float	0%	1	43.44896317
`Firms_with_female_participation_in_ownership_pct_of_firms`	Firms_with_female_participation_in_ownership_pct_of_firms	float	0%	1	56.73667526
`Literacy_rate_youth_female_pct_of_females_ages_15-24`	Literacy_rate_youth_female_pct_of_females_ages_15-24	float	0%	1	99.5199966430664
`Literacy_rate_youth_ages_15-24_gender_parity_index_GPI`	Literacy_rate_youth_ages_15-24_gender_parity_index_GPI	float	0%	1	0.996100008487701
`Literacy_rate_youth_male_pct_of_males_ages_15-24`	Literacy_rate_youth_male_pct_of_males_ages_15-24	float	0%	1	100.0
`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	97.0
`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	98.4100036621094
`School_enrollment_primary_gross_gender_parity_index_GPI`	School_enrollment_primary_gross_gender_parity_index_GPI	float	0%	1	0.976957738399506
`School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI`	School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI	float	0%	1	1.02612137794495
`School_enrollment_secondary_gross_gender_parity_index_GPI`	School_enrollment_secondary_gross_gender_parity_index_GPI	float	0%	1	1.07713508605957
`School_enrollment_tertiary_gross_gender_parity_index_GPI`	School_enrollment_tertiary_gross_gender_parity_index_GPI	float	0%	1	1.2191020570979
`School_enrollment_preprimary_female_pct_gross`	School_enrollment_preprimary_female_pct_gross	float	0%	1	89.6743850708008
`School_enrollment_preprimary_male_pct_gross`	School_enrollment_preprimary_male_pct_gross	float	0%	1	90.7467803955078
`Primary_completion_rate_female_pct_of_relevant_age_group`	Primary_completion_rate_female_pct_of_relevant_age_group	float	0%	1	90.9169158208013
`Primary_completion_rate_male_pct_of_relevant_age_group`	Primary_completion_rate_male_pct_of_relevant_age_group	float	0%	1	91.9628576100481
`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	87.2008438110352
`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	84.1670989990234
`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	85.706413269043
`Primary_education_pupils_pct_female`	Primary_education_pupils_pct_female	float	0%	1	47.89458
`School_enrollment_primary_female_pct_gross`	School_enrollment_primary_female_pct_gross	float	0%	1	92.1194459029965
`School_enrollment_primary_male_pct_gross`	School_enrollment_primary_male_pct_gross	float	0%	1	95.8880950966532
`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	93.47241
`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	95.52592
`School_enrollment_primary_female_pct_net`	School_enrollment_primary_female_pct_net	float	0%	1	93.69001
`School_enrollment_primary_male_pct_net`	School_enrollment_primary_male_pct_net	float	0%	1	93.85718
`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	65.00299
`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	65.11555
`Persistence_to_grade_5_female_pct_of_cohort`	Persistence_to_grade_5_female_pct_of_cohort	float	0%	1	96.5060577392578
`Persistence_to_grade_5_male_pct_of_cohort`	Persistence_to_grade_5_male_pct_of_cohort	float	0%	1	93.9382781982422
+208 more extension fields — download the CSV/Parquet to see them all.

PHL Philippines Data on Conflict Events PHL-HDX-Philippines___Data_on_Conflict_Events Humanitarian

4,368 rows · 1 table(s) HDX 0 1 2 3 ▶

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1 Admin 1 — 1 table(s)

PHL Philippines Data on Conflict Events — 4,368 rows, 50 columns

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Field details — 50 fields (type, nulls, unique, samples)

Extension Fields (50) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`id`	id	string	0%	100	123403, 124029, 125199, 123871, 123430
`relid`	relid	string	0%	100	PHI-1989-1-217-51, PHI-1989-1-217-1, PHI-1989-1-217-2,...
`year`	year	string	0%	2	1989, 1989, 1989, 1989, 1989
`active_year`	active_year	string	0%	1	true, true, true, true, true
`code_status`	code_status	string	0%	1	Clear, Clear, Clear, Clear, Clear
`type_of_violence`	type_of_violence	string	0%	1	1, 1, 1, 1, 1
`conflict_dset_id`	conflict_dset_id	string	0%	1	209, 209, 209, 209, 209
`conflict_new_id`	conflict_new_id	string	0%	1	209, 209, 209, 209, 209
`conflict_name`	conflict_name	string	0%	1	Philippines: Government, Philippines: Government,...
`dyad_dset_id`	dyad_dset_id	string	0%	1	411, 411, 411, 411, 411
`dyad_new_id`	dyad_new_id	string	0%	1	411, 411, 411, 411, 411
`dyad_name`	dyad_name	string	0%	1	Government of Philippines - CPP, Government of...
`side_a_dset_id`	side_a_dset_id	string	0%	1	154, 154, 154, 154, 154
`side_a_new_id`	side_a_new_id	string	0%	1	154, 154, 154, 154, 154
`side_a`	side_a	string	0%	1	Government of Philippines, Government of Philippines,...
`side_b_dset_id`	side_b_dset_id	string	0%	1	169, 169, 169, 169, 169
`side_b_new_id`	side_b_new_id	string	0%	1	169, 169, 169, 169, 169
`side_b`	side_b	string	0%	1	CPP, CPP, CPP, CPP, CPP
`number_of_sources`	number_of_sources	string	0%	3	-1, 1, -1, 1, 1
`source_article`	source_article	string	0%	75	Reuters 3 July 1989 "PHILIPPINES FORMS ELITE ANTI-REBEL...
`source_office`	source_office	string	81%	2	Reuters News, Reuters News, Reuters News, Reuters News,...
`source_date`	source_date	string	81%	15	1989-01-16, 1989-02-07, 1989-02-06, 1989-02-07, 1989-02-09
`source_headline`	source_headline	string	81%	15	EIGHT DIE IN PHILIPPINE FIGHTING, NINE KIDNAPPED.,...
`source_original`	source_original	string	1%	10	military spokesman, military spokesman, military...
`where_prec`	where_prec	string	0%	6	1, 1, 1, 4, 2
`where_coordinates`	where_coordinates	string	0%	70	Manila city, Makilala town, Sultan Kudarat town, Surigao...
`where_description`	where_description	string	0%	77	Manila City, Makilala town, Sultan Kudarat town, Surigao...
`adm_1`	adm_1	string	8%	39	Metropolitan Manila province, Cotabato province,...
`adm_2`	adm_2	string	39%	39	Manila City municipality, Makilala municipality, Sultan...
`latitude`	latitude	float	0%	67	14.6042, 6.9514, 7.27, 8.66667, 14.6042
+20 more extension fields — download the CSV/Parquet to see them all.

PHL Philippines Subnational Demographic and Health D PHL-HDX-Philippines___Subnational_Demographic_an Health

2,621 rows · 1 table(s) HDX 0 1 2 3 1 SEL 29 ext ▶

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1 Admin 1 — 1 table(s)

PHL Philippines Subnational Demographic and Health D — 2,621 rows, 30 columns

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

Standards-Aligned Fields (1)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`ISO3`	ISO3	text	SEL+	0%	-	-

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

Field Name	Label	Type	Nulls	Unique	Samples
`Location`	Location	text	0%	-	-
`DataId`	DataId	text	0%	-	-
`Indicator`	Indicator	text	0%	-	-
`Value`	Value	text	0%	-	-
`Precision`	Precision	text	0%	-	-
`DHS_CountryCode`	DHS_CountryCode	text	0%	-	-
`CountryName`	CountryName	text	0%	-	-
`SurveyYear`	SurveyYear	text	0%	-	-
`SurveyId`	SurveyId	text	0%	-	-
`IndicatorId`	IndicatorId	text	0%	-	-
`IndicatorOrder`	IndicatorOrder	text	0%	-	-
`IndicatorType`	IndicatorType	text	0%	-	-
`CharacteristicId`	CharacteristicId	text	0%	-	-
`CharacteristicOrder`	CharacteristicOrder	text	0%	-	-
`CharacteristicCategory`	CharacteristicCategory	text	0%	-	-
`CharacteristicLabel`	CharacteristicLabel	text	0%	-	-
`ByVariableId`	ByVariableId	text	0%	-	-
`ByVariableLabel`	ByVariableLabel	text	0%	-	-
`IsTotal`	IsTotal	text	0%	-	-
`IsPreferred`	IsPreferred	text	0%	-	-
`SDRID`	SDRID	text	0%	-	-
`RegionId`	RegionId	text	0%	-	-
`SurveyYearLabel`	SurveyYearLabel	text	0%	-	-
`SurveyType`	SurveyType	text	0%	-	-
`DenominatorWeighted`	DenominatorWeighted	text	0%	-	-
`DenominatorUnweighted`	DenominatorUnweighted	text	0%	-	-
`CILow`	CILow	text	0%	-	-
`CIHigh`	CIHigh	text	0%	-	-
`LevelRank`	LevelRank	text	0%	-	-

PHL Philippines Accessibility Indicators PHL-HDX-Philippines___Accessibility_Indicators Infrastructure

2,080 rows · 1 table(s) HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

PHL Philippines Accessibility Indicators — 2,080 rows, 13 columns

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Field details — 13 fields (type, nulls, unique, samples)

Extension Fields (13) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`name`	name	text	0%	-	-
`iso`	iso	text	0%	-	-
`id`	id	text	0%	-	-
`country`	country	text	0%	-	-
`admin_level`	admin_level	text	0%	-	-
`category`	category	text	0%	-	-
`range_type`	range_type	text	0%	-	-
`range`	range	text	0%	-	-
`population_type`	population_type	text	0%	-	-
`population`	population	text	0%	-	-
`population_share`	population_share	text	0%	-	-
`population_interval`	population_interval	text	0%	-	-
`population_interval_share`	population_interval_share	text	0%	-	-

PHL PSA Poverty Province PHL-PSA-POVERTY_PROVINCE Indicators

2,060 rows · 1 table(s) Philippine Statistics Authority 0 1 2 3 ▶

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2 Admin 2 — 1 table(s)

PHL PSA poverty_province — 2,060 rows, 4 columns

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Field details — 4 fields (type, nulls, unique, samples)

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

Field Name	Label	Type	Nulls	Unique	Samples
`Region/Province`	Region/Province	text	0%	-	-
`Item`	Item	text	0%	-	-
`Year`	Year	text	0%	-	-
`Annual Per Capita Poverty Threshold, Poverty Incidence and Magnitude of Poor Population`	Annual Per Capita Poverty Threshold, Poverty Incidence and Magnitude of Poor Population	text	0%	-	-

PHL PSA Poverty Threshold Region PHL-PSA-POVERTY_THRESHOLD_REGION Indicators

2,060 rows · 1 table(s) Philippine Statistics Authority 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.

2 Admin 2 — 1 table(s)

PHL PSA poverty_threshold_region — 2,060 rows, 4 columns

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Field details — 4 fields (type, nulls, unique, samples)

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

Field Name	Label	Type	Nulls	Unique	Samples
`Region/Province`	Region/Province	text	0%	-	-
`Item`	Item	text	0%	-	-
`Year`	Year	text	0%	-	-
`Annual Per Capita Poverty Threshold, Poverty Incidence and Magnitude of Poor Families`	Annual Per Capita Poverty Threshold, Poverty Incidence and Magnitude of Poor Families	text	0%	-	-

PHL Philippines Agriculture and Rural Development PHL-HDX-Philippines___Agriculture_and_Rural_Deve Indicators

1,750 rows · 1 table(s) HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

PHL Philippines Agriculture and Rural Development — 1,750 rows, 37 columns

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Field details — 37 fields (type, nulls, unique, samples)

Extension Fields (37) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	PHL
`Fertilizer_consumption_pct_of_fertilizer_production`	Fertilizer_consumption_pct_of_fertilizer_production	float	0%	1	459.179580194014
`Fertilizer_consumption_kilograms_per_hectare_of_arable_land`	Fertilizer_consumption_kilograms_per_hectare_of_arable_land	float	0%	1	199.449373881932
`Agricultural_land_sq._km`	Agricultural_land_sq._km	float	0%	1	127226.0
`Agricultural_land_pct_of_land_area`	Agricultural_land_pct_of_land_area	float	0%	1	42.6689472448603
`Arable_land_hectares`	Arable_land_hectares	float	0%	1	5590000.0
`Arable_land_hectares_per_person`	Arable_land_hectares_per_person	float	0%	1	0.0486547276784882
`Arable_land_pct_of_land_area`	Arable_land_pct_of_land_area	float	0%	1	18.7476942683704
`Land_under_cereal_production_hectares`	Land_under_cereal_production_hectares	float	0%	1	7356944.0
`Permanent_cropland_pct_of_land_area`	Permanent_cropland_pct_of_land_area	float	0%	1	18.8905657846195
`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	12170.141244
`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	4.1356910066334
`Forest_area_sq._km`	Forest_area_sq._km	float	0%	1	72932.6
`Forest_area_pct_of_land_area`	Forest_area_pct_of_land_area	float	0%	1	24.4600731126539
`Agricultural_irrigated_land_pct_of_total_agricultural_land`	Agricultural_irrigated_land_pct_of_total_agricultural_land	float	0%	1	9.26590538336052
`Average_precipitation_in_depth_mm_per_year`	Average_precipitation_in_depth_mm_per_year	float	0%	1	2348.0
`Land_area_sq._km`	Land_area_sq._km	float	0%	1	298170.0
`Rural_land_area_sq._km`	Rural_land_area_sq._km	float	0%	1	282119.58210558
`Cereal_production_metric_tons`	Cereal_production_metric_tons	float	0%	1	28465199.05
`Crop_production_index_2014-2016_=_100`	Crop_production_index_2014-2016_=_100	float	0%	1	103.98
`Food_production_index_2014-2016_=_100`	Food_production_index_2014-2016_=_100	float	0%	1	100.51
`Livestock_production_index_2014-2016_=_100`	Livestock_production_index_2014-2016_=_100	float	0%	1	90.42
`Surface_area_sq._km`	Surface_area_sq._km	float	0%	1	300000.0
`Cereal_yield_kg_per_hectare`	Cereal_yield_kg_per_hectare	float	0%	1	3869.2
`Access_to_electricity_rural_pct_of_rural_population`	Access_to_electricity_rural_pct_of_rural_population	float	0%	1	97.6
`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	4.58854136068604
`Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal`	Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal	float	0%	1	74.62601713
`Agriculture_forestry_and_fishing_value_added_current_USusd`	Agriculture_forestry_and_fishing_value_added_current_USusd	float	0%	1	41926533969.6326
`Agriculture_forestry_and_fishing_value_added_pct_of_GDP`	Agriculture_forestry_and_fishing_value_added_pct_of_GDP	float	0%	1	9.08252678487007
`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	13.3015608838713
+7 more extension fields — download the CSV/Parquet to see them all.

PHL Philippines Climate Change PHL-HDX-Philippines___Climate_Change Climate

1,563 rows · 1 table(s) HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

PHL Philippines Climate Change — 1,563 rows, 49 columns

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	PHL
`Agricultural_land_sq._km`	Agricultural_land_sq._km	float	0%	1	127226.0
`Agricultural_land_pct_of_land_area`	Agricultural_land_pct_of_land_area	float	0%	1	42.6689472448603
`Arable_land_pct_of_land_area`	Arable_land_pct_of_land_area	float	0%	1	18.7476942683704
`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	12170.141244
`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	4.1356910066334
`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	1511.452095905
`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	0.513625825260924
`Land_area_where_elevation_is_below_5_meters_pct_of_total_land_area`	Land_area_where_elevation_is_below_5_meters_pct_of_total_land_area	float	0%	1	4.64931683189432
`Forest_area_sq._km`	Forest_area_sq._km	float	0%	1	72932.6
`Forest_area_pct_of_land_area`	Forest_area_pct_of_land_area	float	0%	1	24.4600731126539
`Agricultural_irrigated_land_pct_of_total_agricultural_land`	Agricultural_irrigated_land_pct_of_total_agricultural_land	float	0%	1	9.26590538336052
`Average_precipitation_in_depth_mm_per_year`	Average_precipitation_in_depth_mm_per_year	float	0%	1	2348.0
`Cereal_yield_kg_per_hectare`	Cereal_yield_kg_per_hectare	float	0%	1	3869.2
`Foreign_direct_investment_net_inflows_pct_of_GDP`	Foreign_direct_investment_net_inflows_pct_of_GDP	float	0%	1	2.04498934693652
`Access_to_electricity_pct_of_population`	Access_to_electricity_pct_of_population	float	0%	1	98.0
`Electricity_production_from_coal_sources_pct_of_total`	Electricity_production_from_coal_sources_pct_of_total	float	0%	1	59.5695646325606
`Electricity_production_from_hydroelectric_sources_pct_of_total`	Electricity_production_from_hydroelectric_sources_pct_of_total	float	0%	1	9.04272967762184
`Electricity_production_from_natural_gas_sources_pct_of_total`	Electricity_production_from_natural_gas_sources_pct_of_total	float	0%	1	16.0373043985114
`Electricity_production_from_nuclear_sources_pct_of_total`	Electricity_production_from_nuclear_sources_pct_of_total	float	0%	1	0.0
`Electricity_production_from_oil_sources_pct_of_total`	Electricity_production_from_oil_sources_pct_of_total	float	0%	1	2.25799219835897
`Renewable_electricity_output_pct_of_total_electricity_output`	Renewable_electricity_output_pct_of_total_electricity_output	float	0%	1	22.7211103754847
`Electricity_production_from_renewable_sources_excluding_hydroelectric_kWh`	Electricity_production_from_renewable_sources_excluding_hydroelectric_kWh	float	0%	1	14838030000.0
`Electricity_production_from_renewable_sources_excluding_hydroelectric_pct_of_tot`	Electricity_production_from_renewable_sources_excluding_hydroelectric_pct_of_tot	float	0%	1	14.0338882058072
`Renewable_energy_consumption_pct_of_total_final_energy_consumption`	Renewable_energy_consumption_pct_of_total_final_energy_consumption	float	0%	1	28.0
`Energy_use_kg_of_oil_equivalent_per_usd1000_GDP_constant_2021_PPP`	Energy_use_kg_of_oil_equivalent_per_usd1000_GDP_constant_2021_PPP	float	0%	1	58.2412762588087
`Electric_power_consumption_kWh_per_capita`	Electric_power_consumption_kWh_per_capita	float	0%	1	884.680258485773
`Energy_use_kg_of_oil_equivalent_per_capita`	Energy_use_kg_of_oil_equivalent_per_capita	float	0%	1	550.793803994865
`Droughts_floods_extreme_temperatures_pct_of_population_average_1990-2009`	Droughts_floods_extreme_temperatures_pct_of_population_average_1990-2009	float	0%	1	0.806384865170547
`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	4.58854136068604
+19 more extension fields — download the CSV/Parquet to see them all.

PHL Philippines Infrastructure PHL-HDX-Philippines___Infrastructure Infrastructure

1,345 rows · 1 table(s) HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

PHL Philippines Infrastructure — 1,345 rows, 51 columns

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Field details — 51 fields (type, nulls, unique, samples)

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

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	PHL
`ICT_service_exports_BoP_current_USusd`	ICT_service_exports_BoP_current_USusd	float	0%	1	8085429150.08811
`ICT_service_exports_pct_of_service_exports_BoP`	ICT_service_exports_pct_of_service_exports_BoP	float	0%	1	15.6718201065455
`Electricity_production_from_coal_sources_pct_of_total`	Electricity_production_from_coal_sources_pct_of_total	float	0%	1	59.5695646325606
`Electricity_production_from_hydroelectric_sources_pct_of_total`	Electricity_production_from_hydroelectric_sources_pct_of_total	float	0%	1	9.04272967762184
`Electric_power_transmission_and_distribution_losses_pct_of_output`	Electric_power_transmission_and_distribution_losses_pct_of_output	float	0%	1	9.58884455006053
`Electricity_production_from_natural_gas_sources_pct_of_total`	Electricity_production_from_natural_gas_sources_pct_of_total	float	0%	1	16.0373043985114
`Electricity_production_from_nuclear_sources_pct_of_total`	Electricity_production_from_nuclear_sources_pct_of_total	float	0%	1	0.0
`Electricity_production_from_oil_sources_pct_of_total`	Electricity_production_from_oil_sources_pct_of_total	float	0%	1	2.25799219835897
`Electric_power_consumption_kWh_per_capita`	Electric_power_consumption_kWh_per_capita	float	0%	1	884.680258485773
`Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal`	Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal	float	0%	1	74.62601713
`Annual_freshwater_withdrawals_domestic_pct_of_total_freshwater_withdrawal`	Annual_freshwater_withdrawals_domestic_pct_of_total_freshwater_withdrawal	float	0%	1	10.433023
`Annual_freshwater_withdrawals_industry_pct_of_total_freshwater_withdrawal`	Annual_freshwater_withdrawals_industry_pct_of_total_freshwater_withdrawal	float	0%	1	14.94095987
`Annual_freshwater_withdrawals_total_billion_cubic_meters`	Annual_freshwater_withdrawals_total_billion_cubic_meters	float	0%	1	91.03689247
`Annual_freshwater_withdrawals_total_pct_of_internal_resources`	Annual_freshwater_withdrawals_total_pct_of_internal_resources	float	0%	1	19.0056142943633
`Renewable_internal_freshwater_resources_total_billion_cubic_meters`	Renewable_internal_freshwater_resources_total_billion_cubic_meters	float	0%	1	479.0
`Renewable_internal_freshwater_resources_per_capita_cubic_meters`	Renewable_internal_freshwater_resources_per_capita_cubic_meters	float	0%	1	4203.06920924684
`Investment_in_energy_with_private_participation_current_USusd`	Investment_in_energy_with_private_participation_current_USusd	float	0%	1	2081560000.0
`Investment_in_ICT_with_private_participation_current_USusd`	Investment_in_ICT_with_private_participation_current_USusd	float	0%	1	3695290000.0
`Investment_in_transport_with_private_participation_current_USusd`	Investment_in_transport_with_private_participation_current_USusd	float	0%	1	1793820000.0
`Investment_in_water_and_sanitation_with_private_participation_current_USusd`	Investment_in_water_and_sanitation_with_private_participation_current_USusd	float	0%	1	3680000.0
`Public_private_partnerships_investment_in_energy_current_USusd`	Public_private_partnerships_investment_in_energy_current_USusd	float	0%	1	2081560000.0
`Public_private_partnerships_investment_in_ICT_current_USusd`	Public_private_partnerships_investment_in_ICT_current_USusd	float	0%	1	3695290000.0
`Public_private_partnerships_investment_in_transport_current_USusd`	Public_private_partnerships_investment_in_transport_current_USusd	float	0%	1	1793820000.0
`Public_private_partnerships_investment_in_water_and_sanitation_current_USusd`	Public_private_partnerships_investment_in_water_and_sanitation_current_USusd	float	0%	1	3680000.0
`Industrial_design_applications_nonresident_by_count`	Industrial_design_applications_nonresident_by_count	float	0%	1	690.0
`Industrial_design_applications_resident_by_count`	Industrial_design_applications_resident_by_count	float	0%	1	682.0
`Trademark_applications_nonresident_by_count`	Trademark_applications_nonresident_by_count	float	0%	1	29927.0
`Trademark_applications_resident_by_count`	Trademark_applications_resident_by_count	float	0%	1	34976.0
`Air_transport_registered_carrier_departures_worldwide`	Air_transport_registered_carrier_departures_worldwide	float	0%	1	283131.0
+21 more extension fields — download the CSV/Parquet to see them all.

PHL Airports in the Philippines PHL-HDX-Airports_in_the_Philippines Infrastructure

860 rows · 1 table(s) 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.

3 Admin 3 — 1 table(s)

PHL Airports in the Philippines — 860 rows, 24 columns

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`id`	id	string	0%	100	5689, 5742, 5687, 5744, 5736
`ident`	ident	string	0%	100	RPLL, RPVM, RPLC, RPVP, RPVE
`type`	type	string	0%	5	large_airport, large_airport, large_airport,...
`name`	name	string	0%	99	Ninoy Aquino International Airport, Mactan Cebu...
`latitude_deg`	latitude_deg	float	0%	99	14.5086, 10.309261, 15.186, 9.742044, 11.9245
`longitude_deg`	longitude_deg	float	0%	99	121.019997, 123.97974, 120.559998, 118.75911, 121.954002
`elevation_ft`	elevation_ft	string	21%	60	75, 31, 484, 71, 7
`continent`	continent	string	0%	1	AS, AS, AS, AS, AS
`country_name`	country_name	string	0%	1	Philippines, Philippines, Philippines, Philippines, Philippines
`iso_country`	iso_country	string	0%	1	PH, PH, PH, PH, PH
`region_name`	region_name	string	0%	55	National Capital Region (Metropolitan Manila), Cebu...
`iso_region`	iso_region	string	0%	55	PH-00, PH-CEB, PH-PAM, PH-PLW, PH-AKL
`local_region`	local_region	string	0%	55	00, CEB, PAM, PLW, AKL
`municipality`	municipality	string	0%	91	Manila (Pasay), Cebu City/Lapu-Lapu City, Mabalacat,...
`scheduled_service`	scheduled_service	string	0%	2	1, 1, 1, 1, 1
`gps_code`	gps_code	string	26%	74	RPLL, RPVM, RPLC, RPVP, RPVE
`icao_code`	icao_code	string	39%	61	RPLL, RPVM, RPLC, RPVP, RPVE
`iata_code`	iata_code	string	47%	53	MNL, CEB, CRK, PPS, MPH
`local_code`	local_code	string	96%	4	DZR, GUI, ACFC, RP15
`home_link`	home_link	string	90%	10	https://newnaia.com.ph/,...
`wikipedia_link`	wikipedia_link	string	20%	75	https://en.wikipedia.org/wiki/Ninoy_Aquino_International_...
`keywords`	keywords	string	43%	57	Manila International Airport, Jesus Villamor Air Base,...
`score`	score	string	0%	12	1014275, 1275, 1000, 1000, 750
`last_updated`	last_updated	string	0%	98	2026-01-16T05:05:15+00:00, 2026-01-15T13:47:18+00:00,...

PHL Global Data Lab PHL-GDL Development Indices

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

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1 Admin 1 — 1 table(s)

PHL GDL - Subnational Indices — 612 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	PHL, PHL, PHL, PHL, PHL
`region_code`	Admin code	string	SEL	100%	-	-
`region_name`	Admin name	string	SEL	0%	18	Total, ARMM, Cordillera Admin Region, I-Ilocos, II-Cagayan Valley
`human_development_index`	Human development index	float	SEL	0%	73	0.614, 0.516, 0.592, 0.636, 0.636
`health_index`	Health index	float	SEL	0%	72	0.683, 0.651, 0.688, 0.718, 0.687
`education_index`	Education index	float	SEL	0%	77	0.596, 0.471, 0.567, 0.606, 0.627
`income_index`	Income index	float	SEL	0%	68	0.567, 0.448, 0.531, 0.592, 0.597
`life_expectancy`	Life expectancy	float	SEL	0%	97	64.38, 62.29, 64.71, 66.67, 64.63
`mean_years_schooling`	Mean years schooling	float	SEL	0%	100	8.945, 6.526, 8.313, 9.152, 9.468

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

Field Name	Label	Type	Nulls	Unique	Samples
`year`	year	integer	0%	6	1990, 1990, 1990, 1990, 1990
`level`	level	string	0%	2	national, subnational, subnational, subnational, subnational

PHL Philippines Poverty PHL-HDX-Philippines___Poverty Indicators

244 rows · 1 table(s) HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

PHL Philippines Poverty — 244 rows, 23 columns

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Field details — 23 fields (type, nulls, unique, samples)

Extension Fields (23) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	PHL
`Population_living_in_slums_pct_of_urban_population`	Population_living_in_slums_pct_of_urban_population	float	0%	1	35.874
`Income_share_held_by_second_20pct`	Income_share_held_by_second_20pct	float	0%	1	10.7
`Income_share_held_by_third_20pct`	Income_share_held_by_third_20pct	float	0%	1	14.6
`Income_share_held_by_fourth_20pct`	Income_share_held_by_fourth_20pct	float	0%	1	20.9
`Income_share_held_by_highest_20pct`	Income_share_held_by_highest_20pct	float	0%	1	46.9
`Income_share_held_by_highest_10pct`	Income_share_held_by_highest_10pct	float	0%	1	31.6
`Proportion_of_people_living_below_50_percent_of_median_income_pct`	Proportion_of_people_living_below_50_percent_of_median_income_pct	float	0%	1	10.6
`Income_share_held_by_lowest_10pct`	Income_share_held_by_lowest_10pct	float	0%	1	2.9
`Income_share_held_by_lowest_20pct`	Income_share_held_by_lowest_20pct	float	0%	1	6.9
`Poverty_headcount_ratio_at_usd3.00_a_day_2021_PPP_pct_of_population`	Poverty_headcount_ratio_at_usd3.00_a_day_2021_PPP_pct_of_population	float	0%	1	5.3
`Poverty_gap_at_usd3.00_a_day_2021_PPP_pct`	Poverty_gap_at_usd3.00_a_day_2021_PPP_pct	float	0%	1	1.0
`Gini_index`	Gini_index	float	0%	1	39.3
`Poverty_headcount_ratio_at_usd4.20_a_day_2021_PPP_pct_of_population`	Poverty_headcount_ratio_at_usd4.20_a_day_2021_PPP_pct_of_population	float	0%	1	16.9
`Poverty_gap_at_usd4.20_a_day_2021_PPP_pct`	Poverty_gap_at_usd4.20_a_day_2021_PPP_pct	float	0%	1	3.7
`Poverty_headcount_ratio_at_national_poverty_lines_pct_of_population`	Poverty_headcount_ratio_at_national_poverty_lines_pct_of_population	float	0%	1	15.5
`Poverty_headcount_ratio_at_usd8.30_a_day_2021_PPP_pct_of_population`	Poverty_headcount_ratio_at_usd8.30_a_day_2021_PPP_pct_of_population	float	0%	1	58.7
`Poverty_gap_at_usd8.30_a_day_2021_PPP_pct`	Poverty_gap_at_usd8.30_a_day_2021_PPP_pct	float	0%	1	21.5
`Survey_mean_consumption_or_income_per_capita_bottom_40pct_of_population_2021_PPP`	Survey_mean_consumption_or_income_per_capita_bottom_40pct_of_population_2021_PPP	float	0%	1	4.37
`Annualized_average_growth_rate_in_per_capita_real_survey_mean_consumption_or_inc`	Annualized_average_growth_rate_in_per_capita_real_survey_mean_consumption_or_inc	float	0%	1	-0.05
`Survey_mean_consumption_or_income_per_capita_total_population_2021_PPP_usd_per_d`	Survey_mean_consumption_or_income_per_capita_total_population_2021_PPP_usd_per_d	float	0%	1	9.93
`Multidimensional_poverty_headcount_ratio_household_pct_of_total_households`	Multidimensional_poverty_headcount_ratio_household_pct_of_total_households	float	0%	1	17.3
`Multidimensional_poverty_index_scale_0-1`	Multidimensional_poverty_index_scale_0-1	float	0%	1	0.071

PHL USAID DHS Program PHL-DHS Health Surveys

199 rows · 2 table(s) USAID DHS Program 0 1 2 3 6 SEL 2 CCL 10 ext ▶

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1 Admin 1 — 2 table(s)

PHL DHS - Ethnicity Indicators — 60 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%	45	92.3, 93.0, 97.1, 80.5, 81.0
`men_who_are_literate`	Men who are literate	float	CCL	67%	18	92.0, 81.1, 96.8, 98.2, 96.2

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	Philippines, Philippines, Philippines, Philippines, Philippines
`survey_year`	survey_year	integer	0%	3	2003, 2008, 2022, 2003, 2008
`region`	region	string	0%	20	Mindanao, Mindanao, Mindanao, ..BARMM, ..BARMM
`survey_id`	survey_id	string	0%	3	PH2003DHS, PH2008DHS, PH2022DHS, PH2003DHS, PH2008DHS
`survey_type`	survey_type	string	0%	1	DHS, DHS, DHS, DHS, DHS

PHL DHS - Health Indicators — 139 rows, 10 columns

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

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	100%	-	-
`contraception_modern_pct`	Contraception modern percent	float	SEL	0%	78	15.6, 18.7, 22.2, 22.6, 23.5
`infant_mortality_per_1000`	Infant mortality per 1000	float	SEL	0%	43	42.0, 46.0, 34.0, 30.0, 30.0
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	0%	51	75.0, 74.0, 49.0, 47.0, 44.0
`vaccination_rate_pct`	Vaccination rate percent	float	SEL	0%	88	75.4, 71.5, 62.4, 72.9, 71.8

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

Field Name	Label	Type	Nulls	Unique	Samples
`country_name`	country_name	string	0%	1	Philippines, Philippines, Philippines, Philippines, Philippines
`survey_year`	survey_year	integer	0%	7	1993, 1998, 2003, 2008, 2013
`region`	region	string	0%	15	Mindanao, Mindanao, Mindanao, Mindanao, Mindanao
`survey_id`	survey_id	string	0%	7	PH1993DHS, PH1998DHS, PH2003DHS, PH2008DHS, PH2013DHS
`survey_type`	survey_type	string	0%	1	DHS, DHS, DHS, DHS, DHS

PHL Glottolog Language Catalog PHL-GLOTTOLOG Language

179 rows · 1 table(s) 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)

PHL Glottolog - Languages — 179 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	aben1249, adas1235, agta1234, agus1235, agut1237
`name`	Name	string	CCL	0%	100	Abenlen Ayta, Adasen, Agta-Pahanan, Agusan Manobo, Agutaynen
`iso639_3`	Iso639 3	string	CCL	0%	100	abp, tiu, apf, msm, agn
`level`	Level	string	CCL	0%	1	language, language, language, language, language
`family_name`	Family name	string	CCL	100%	-	-
`family_glottocode`	Family glottocode	string	CCL	0%	6	aust1307, aust1307, aust1307, aust1307, aust1307
`parent_name`	Parent name	string	CCL	100%	-	-
`parent_glottocode`	Parent glottocode	string	CCL	0%	74	abel1234, iban1268, para1320, east2478, kala1389
`endangerment_status`	Endangerment status	string	CCL	100%	-	-
`country_codes`	Country codes	string	SEL+	0%	4	['PH'], ['PH'], ['PH'], ['PH'], ['PH']
`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%	9	0, 2, 0, 3, 0

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

Field Name	Label	Type	Nulls	Unique	Samples
`latitude`	latitude	float	1%	99	15.4131, 17.8187, 17.0538, 8.62731, 10.5328
`longitude`	longitude	float	1%	98	120.2, 120.905, 122.2802, 125.742, 119.655
`classification`	classification	string	0%	1	[], [], [], [], []

PHL Philippines National Demographic and Health Data PHL-HDX-Philippines___National_Demographic_and_H Health

152 rows · 1 table(s) HDX 0 1 2 3 1 SEL 28 ext ▶

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1 Admin 1 — 1 table(s)

PHL Philippines National Demographic and Health Data — 152 rows, 29 columns

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

Standards-Aligned Fields (1)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`ISO3`	ISO3	text	SEL+	0%	-	-

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

Field Name	Label	Type	Nulls	Unique	Samples
`DataId`	DataId	text	0%	-	-
`Indicator`	Indicator	text	0%	-	-
`Value`	Value	text	0%	-	-
`Precision`	Precision	text	0%	-	-
`DHS_CountryCode`	DHS_CountryCode	text	0%	-	-
`CountryName`	CountryName	text	0%	-	-
`SurveyYear`	SurveyYear	text	0%	-	-
`SurveyId`	SurveyId	text	0%	-	-
`IndicatorId`	IndicatorId	text	0%	-	-
`IndicatorOrder`	IndicatorOrder	text	0%	-	-
`IndicatorType`	IndicatorType	text	0%	-	-
`CharacteristicId`	CharacteristicId	text	0%	-	-
`CharacteristicOrder`	CharacteristicOrder	text	0%	-	-
`CharacteristicCategory`	CharacteristicCategory	text	0%	-	-
`CharacteristicLabel`	CharacteristicLabel	text	0%	-	-
`ByVariableId`	ByVariableId	text	0%	-	-
`ByVariableLabel`	ByVariableLabel	text	0%	-	-
`IsTotal`	IsTotal	text	0%	-	-
`IsPreferred`	IsPreferred	text	0%	-	-
`SDRID`	SDRID	text	0%	-	-
`RegionId`	RegionId	text	0%	-	-
`SurveyYearLabel`	SurveyYearLabel	text	0%	-	-
`SurveyType`	SurveyType	text	0%	-	-
`DenominatorWeighted`	DenominatorWeighted	text	0%	-	-
`DenominatorUnweighted`	DenominatorUnweighted	text	0%	-	-
`CILow`	CILow	text	0%	-	-
`CIHigh`	CIHigh	text	0%	-	-
`LevelRank`	LevelRank	text	0%	-	-

PHL UNHCR Refugee Data Finder PHL-UNHCR Migration

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

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0 Admin 0 — 2 table(s)

PHL UNHCR - Hosted Populations — 75 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%	-	-

PHL UNHCR - Origin Populations — 75 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%	-	-

PHL LandScan Global (ORNL) PHL-LANDSCAN Modeled Population

135 rows · 3 table(s) 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)

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

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

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	PHL
`admin_level`	Admin level	string	SEL	0%	1	admin_0
`admin_name`	Admin name	string	SEL	0%	1	The Philippines
`admin_code`	Admin code	string	SEL	0%	1	24100683B85265433280220
`area_sqkm`	Area sqkm	float	SEL	0%	1	295277.5799
`pop_2024`	Population count	integer	SEL	0%	1	114764395
`pop_density_2024`	Population density	float	SEL	0%	1	388.67

1 Admin 1 — 1 table(s)

PHL LandScan - Population Admin1 (admin_1) — 17 rows, 7 columns

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

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	PHL, PHL, PHL, PHL, PHL
`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%	17	Calabarzon, NCR, Central Luzon, Western Visayas, Central Visayas
`admin_code`	Admin code	string	SEL	0%	17	36201628B13373758884154, 36201628B69282955287113,...
`area_sqkm`	Area sqkm	float	SEL	0%	17	15849.288, 599.3476, 21309.1386, 20042.983, 14291.9075
`pop_2024`	Population count	integer	SEL	0%	17	17247860, 14479703, 13367681, 8323309, 8319521
`pop_density_2024`	Population density	float	SEL	0%	17	1088.24, 24159.11, 627.32, 415.27, 582.11

Locality Locality — 1 table(s)

PHL LandScan - Cities (locality) — 117 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	PHL, PHL, PHL, PHL, PHL
`admin_level`	Admin level	string	SEL	0%	1	locality, locality, locality, locality, locality
`admin_name`	Admin name	string	SEL	0%	99	Manila, Cebu City, Davao City, Angeles, Dagupan [Lingayen]
`admin_code`	Admin code	integer	SEL	0%	100	2323, 5065, 5872, 2005, 645
`area_sqkm`	Area sqkm	float	SEL	0%	100	2540.0607, 413.4069, 225.5277, 306.219, 356.9656
`pop_2024`	Population count	integer	SEL	0%	100	27215799, 3076557, 1376956, 1369661, 837487
`pop_density_2024`	Population density	float	SEL	0%	100	10714.63, 7441.96, 6105.49, 4472.82, 2346.13

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	25921189, 3191585, 1651086, 1513047, 973316
`landscan_vs_ghs_ratio`	landscan_vs_ghs_ratio	float	0%	90	1.05, 0.964, 0.834, 0.905, 0.86

PHL World Bank Open Data PHL-WORLD_BANK Development Indicators

132 rows · 2 table(s) 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)

PHL 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	PH, PH, PH, PH, PH
`population_count`	Population count	float	SEL	2%	65	27891897.0, 28792621.0, 29723536.0, 30674731.0, 31643032.0
`life_expectancy`	Life expectancy	float	SEL	3%	64	59.175, 59.469, 59.755, 60.018, 60.13
`gdp_per_capita_usd`	Gdp per capita usd	float	SEL	2%	65	269.465146474794, 283.794741192369, 166.689221357377,...
`literacy_rate_pct`	Literacy rate percent	float	SEL	83%	11	83.3199996948242, 93.5699996948242, 93.9199981689453,...
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	3%	58	101.0, 98.0, 95.4, 93.3, 91.3
`poverty_headcount_pct`	Poverty headcount percent	float	SEL	82%	12	34.4, 40.6, 36.8, 33.0, 24.9

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

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

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

Standards-Aligned Fields (12)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	PH, PH, PH, PH, PH
`life_expectancy`	Life expectancy	float	SEL	3%	64	59.175, 59.469, 59.755, 60.018, 60.13
`infant_mortality_per_1000`	Infant mortality per 1000	float	SEL	3%	44	25.2, 25.3, 25.3, 25.3, 25.4
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	3%	58	101.0, 98.0, 95.4, 93.3, 91.3
`maternal_mortality_per_100k`	Maternal mortality per 100k	float	SEL	41%	33	204.0, 199.0, 191.0, 184.0, 177.0
`fertility_rate`	Fertility rate	float	SEL	3%	64	6.996, 6.994, 6.98, 6.952, 6.886
`birth_rate_per_1000`	Birth rate per 1000	float	SEL	3%	64	47.158, 46.699, 46.199, 45.604, 44.792
`death_rate_per_1000`	Death rate per 1000	float	SEL	3%	62	10.014, 9.732, 9.462, 9.203, 9.031
`physicians_per_1000`	Physicians per 1000	float	SEL	49%	32	0.146, 0.111, 0.113, 0.128, 0.15
`hospital_beds_per_1000`	Hospital beds per 1000	float	SEL	46%	27	0.838957667350769, 1.18980002403259, 1.70949995517731,...
`vaccination_rate_pct`	Vaccination rate percent	float	SEL	32%	25	47.0, 54.0, 54.0, 55.0, 57.0
`health_expenditure_pct_gdp`	Health expenditure percent gdp	float	SEL	64%	24	3.05512357, 2.84775972, 2.63767385, 3.07663488, 3.0468533

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

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

117 rows · 1 table(s) 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)

PHL GHS-UCDB - Cities (locality) — 117 rows, 10 columns

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`city_name`	Admin name	string	SEL	0%	99	Manila, Cebu City, Davao City, Angeles, Dagupan [Lingayen]
`country_code`	Country code	string	SEL	0%	1	PHL, PHL, PHL, PHL, PHL
`population`	Population count	integer	SEL	0%	100	25921189, 3191585, 1651086, 1513047, 973316

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	2323, 5065, 5872, 2005, 645
`name_alternates`	name_alternates	string	100%	-	-
`country_name`	country_name	string	0%	1	Philippines, Philippines, Philippines, Philippines, Philippines
`population_year`	population_year	integer	0%	1	2025, 2025, 2025, 2025, 2025
`latitude`	latitude	string	100%	-	-
`longitude`	longitude	string	100%	-	-
`region`	region	string	100%	-	-

PHL Philippines Languages PHL-HDX-Philippines__Languages Ethnolinguistic

117 rows · 1 table(s) HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

PHL Philippines Languages — 117 rows, 14 columns

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`location_code`	location_code	string	0%	1	PHL, PHL, PHL, PHL, PHL
`location_name`	location_name	string	0%	1	Philippines, Philippines, Philippines, Philippines, Philippines
`location_level`	location_level	string	0%	1	0, 0, 0, 0, 0
`language_code`	language_code	string	0%	100	pamp1243, tina1248, maga1263, agut1237, sang1337
`language_name`	language_name	string	0%	100	Pampanga, Tinà Sambal, Mag-Anchi Ayta, Agutaynen, Sangil
`language_rank`	language_rank	string	0%	100	7, 34, 108, 82, 75
`proportion_value`	proportion_value	float	0%	100	0.02675136405664363, 0.0012913360714492592,...
`reliability_score`	reliability_score	float	0%	1	0.883, 0.883, 0.883, 0.883, 0.883
`dataset_name`	dataset_name	string	0%	1	Philippines Census 2010 (IPUMS extract), Philippines...
`url`	url	string	0%	1	https://api.ipums.org/downloads/ipumsi/api/v1/extracts/24...
`source`	source	string	0%	1	IPUMS International, IPUMS International, IPUMS...
`datetime_published`	datetime_published	string	0%	1	12-31-2010, 12-31-2010, 12-31-2010, 12-31-2010, 12-31-2010
`date_creation`	date_creation	string	0%	1	08-07-2025 17:44:24, 08-07-2025 17:44:24, 08-07-2025...
`representivity_rating`	representivity_rating	string	0%	1	very_high, very_high, very_high, very_high, very_high

PHL HDX HAPI Data for Philippines PHL-HDX-HDX_HAPI_Data_for_Philippines Indicators

89 rows · 1 table(s) 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)

PHL HDX HAPI Data for Philippines — 89 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	PHL, PHL, PHL, PHL, PHL
`has_hrp`	has_hrp	string	0%	1	False, False, False, False, False
`in_gho`	in_gho	string	0%	1	True, True, True, True, True
`provider_admin1_name`	provider_admin1_name	string	17%	6	Region VIII, Region VI, Region VI, Region VI, Region VI
`provider_admin2_name`	provider_admin2_name	string	49%	10	Capiz, Capiz, Iloilo, Iloilo, Iloilo
`admin1_code`	admin1_code	string	17%	6	PH08, PH06, PH06, PH06, PH06
`admin1_name`	admin1_name	string	17%	6	Region VIII (Eastern Visayas), Region VI (Western...
`admin2_code`	admin2_code	string	100%	-	-
`admin2_name`	admin2_name	string	100%	-	-
`admin_level`	admin_level	string	0%	3	1, 0, 0, 0, 0
`operation`	operation	string	0%	3	Typhoon Haiyan, Typhoon Haiyan, Earthquakes in Mindanao,...
`assessment_type`	assessment_type	string	0%	2	SA, BA, SA, SA, SA
`population`	population	string	0%	69	34522, 24867, 21350, 25448, 26318
`reporting_round`	reporting_round	string	0%	11	1, 6, 1, 2, 3
`reference_period_start`	reference_period_start	string	0%	12	2013-11-30, 2014-04-30, 2019-11-30, 2019-11-30, 2019-11-30
`reference_period_end`	reference_period_end	string	0%	12	2013-11-30, 2014-04-30, 2019-11-30, 2019-11-30, 2019-11-30

PHL Philippines Risk Assessment Indicators PHL-HDX-Philippines___Risk_Assessment_Indicators Indicators

88 rows · 1 table(s) 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.

2 Admin 2 — 1 table(s)

PHL Philippines Risk Assessment Indicators — 88 rows, 5 columns

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Field details — 5 fields (type, nulls, unique, samples)

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

Field Name	Label	Type	Nulls	Unique	Samples
`ADM2_PCODE`	ADM2_PCODE	text	0%	-	-
`ADM_PCODE`	ADM_PCODE	text	0%	-	-
`education_count`	education_count	text	0%	-	-
`hospitals_count`	hospitals_count	text	0%	-	-
`primary_healthcare_count`	primary_healthcare_count	text	0%	-	-

PHL HDX Subnational Population PHL-HDX-SUBNATIONAL-POP Census

54 rows · 1 table(s) OCHA HDX Humanitarian Data Exchange 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.

2 Admin 2 — 1 table(s)

PHL Subnational Population — 54 rows, 19 columns

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Field details — 19 fields (type, nulls, unique, samples)

Extension Fields (19) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`ISO3`	ISO3	string	0%	1	PHL, PHL, PHL, PHL, PHL
`Country`	Country	string	0%	1	Philippines, Philippines, Philippines, Philippines, Philippines
`ADM1_PCODE`	ADM1 PCODE	string	100%	-	-
`ADM1_NAME`	ADM1 NAME	string	100%	-	-
`ADM2_PCODE`	ADM2 PCODE	string	100%	-	-
`ADM2_NAME`	ADM2 NAME	string	100%	-	-
`ADM3_PCODE`	ADM3 PCODE	string	100%	-	-
`ADM3_NAME`	ADM3 NAME	string	100%	-	-
`ADM4_PCODE`	ADM4 PCODE	string	100%	-	-
`ADM4_NAME`	ADM4 NAME	string	100%	-	-
`Population_group`	Population group	string	0%	54	F_TL, M_TL, T_TL, F_00_04, F_05_09
`Gender`	Gender	string	0%	3	f, m, all, f, f
`Age_range`	Age range	string	0%	18	all, all, all, 0-4, 5-9
`Age_min`	Age min	string	6%	17	0, 5, 10, 15, 20
`Age_max`	Age max	string	11%	16	4, 9, 14, 19, 24
`Population`	Population	string	0%	54	57185530, 58192462, 115377992, 5399605, 5416067
`Reference_year`	Reference year	string	0%	1	2025, 2025, 2025, 2025, 2025
`Source`	Source	string	0%	1	Philippines Statistics Authority (PSA), Philippines...
`Contributor`	Contributor	string	0%	1	UNFPA, UNFPA, UNFPA, UNFPA, UNFPA

PHL Philippines Multidimensional Poverty Index PHL-HDX-Philippines_Multidimensional_Poverty_Ind Indicators

18 rows · 1 table(s) HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

PHL Philippines Multidimensional Poverty Index — 18 rows, 11 columns

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`Country ISO3`	Country ISO3	string	0%	1	PHL, PHL, PHL, PHL, PHL
`Admin 1 PCode`	Admin 1 PCode	string	6%	17	PH01, PH02, PH03, PH04, PH05
`Admin 1 Name`	Admin 1 Name	string	6%	17	Ilocos, Cagayan Valley, Central Luzon, Calabarzon, Bicol
`MPI`	MPI	float	0%	18	0.0158, 0.0112, 0.0052, 0.0071, 0.0077
`Headcount Ratio`	Headcount Ratio	float	0%	18	3.8867, 2.7566, 1.2956, 1.74, 2.1489
`Intensity of Deprivation`	Intensity of Deprivation	float	0%	18	40.6213, 40.6718, 40.2047, 40.5631, 35.8498
`Vulnerable to Poverty`	Vulnerable to Poverty	float	0%	18	5.243, 2.1204, 3.5301, 1.584, 2.2877
`In Severe Poverty`	In Severe Poverty	float	0%	18	0.6867, 0.4855, 0.3563, 0.3724, 0.0716
`Survey`	Survey	string	0%	1	DHS, DHS, DHS, DHS, DHS
`Start Date`	Start Date	string	0%	1	2022-01-01 00:00:00+00:00, 2022-01-01 00:00:00+00:00,...
`End Date`	End Date	string	0%	1	2022-12-31 23:59:59+00:00, 2022-12-31 23:59:59+00:00,...

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

17 rows · 1 table(s) 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)

PHL Mobility by Region — 17 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	PH, PH, PH, PH, PH
`admin_level`	Admin level	integer	SEL	0%	1	1, 1, 1, 1, 1
`iso3`	Country code	string	SEL	0%	1	PHL, PHL, PHL, PHL, PHL

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

Field Name	Label	Type	Nulls	Unique	Samples
`retail`	retail	float	0%	17	18.08, -6.84, -15.24, -9.52, 3.26
`grocery`	grocery	float	0%	17	37.01, 41.76, 8.8, 24.69, 29.21
`parks`	parks	float	0%	17	29.26, 40.77, 30.3, 16.26, 26.06
`transit`	transit	float	0%	17	-33.92, -13.85, -34.95, 12.54, -22.48
`workplaces`	workplaces	float	0%	17	-9.92, -3.89, -16.58, -13.97, -7.34
`residential`	residential	float	0%	17	14.19, 19.7, 19.1, 18.98, 13.67
`region`	region	string	0%	17	Autonomous Region in Muslim Mindanao, Bicol, Cagayan...
`observation_count`	observation_count	integer	0%	1	974, 974, 974, 974, 974

PHL OpenFactBook PHL-OPENFACTBOOK Country Profile

16 rows · 16 table(s) OpenFactBook 0 1 2 3 99 SEL 3 CCL 646 ext ▶

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

0 Admin 0 — 16 table(s)

PHL OpenFactBook - Communications — 1 rows, 22 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	4.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric`	Mobile subscriptions per 100	float	SEL	0%	1	144.0
`internet_country_code_text`	Internet country code text	string	SEL+	0%	1	.ph
`internet_users_percent_of_population_numeric`	Internet penetration percent	float	SEL	0%	1	84.0
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric`	Broadband subscriptions per 100	float	SEL	0%	1	7.0
`country_code`	Country code	string	SEL	0%	1	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`admin_level`	Admin level	string	SEL	0%	1	national

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

Field Name	Label	Type	Nulls	Unique	Samples
`telephones_fixed_lines_total_subscriptions_text`	telephones_fixed_lines_total_subscriptions_text	string	0%	1	4.627 million (2023 est.)
`telephones_fixed_lines_total_subscriptions_numeric`	telephones_fixed_lines_total_subscriptions_numeric	float	0%	1	4.627
`telephones_fixed_lines_subscriptions_per_100_inhabitants_text`	telephones_fixed_lines_subscriptions_per_100_inhabitants_text	string	0%	1	4 (2023 est.)
`telephones_mobile_cellular_total_subscriptions_text`	telephones_mobile_cellular_total_subscriptions_text	string	0%	1	135 million (2023 est.)
`telephones_mobile_cellular_total_subscriptions_numeric`	telephones_mobile_cellular_total_subscriptions_numeric	float	0%	1	135.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_text`	telephones_mobile_cellular_subscriptions_per_100_inhabitants_text	string	0%	1	144 (2022 est.)
`broadcast_media_text`	broadcast_media_text	string	0%	1	multiple national private TV and radio networks;...
`broadcast_media_numeric`	broadcast_media_numeric	float	0%	1	400.0
`internet_users_percent_of_population_text`	internet_users_percent_of_population_text	string	0%	1	84% (2023 est.)
`broadband_fixed_subscriptions_total_text`	broadband_fixed_subscriptions_total_text	string	0%	1	7.51 million (2023 est.)
`broadband_fixed_subscriptions_total_numeric`	broadband_fixed_subscriptions_total_numeric	float	0%	1	7.51
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text`	broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text	string	0%	1	7 (2023 est.)
`source_section`	source_section	string	0%	1	Communications
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/rp.json

PHL OpenFactBook - Economy — 1 rows, 158 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	10400.0
`gdp_official_exchange_rate_numeric`	Gdp total usd	float	SEL	0%	1	461.618
`population_below_poverty_line_numeric`	Poverty headcount percent	float	SEL	0%	1	15.5
`country_code`	Country code	string	SEL	0%	1	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`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	growing Southeast Asian economy; commercial rebound led...
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text`	Real gdp purchasing power parity 2024 (text)	string	0%	1	$1.202 trillion (2024 est.)
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_numeric`	Real gdp purchasing power parity 2024 (numeric)	float	0%	1	1.202
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text`	Real gdp purchasing power parity 2023 (text)	string	0%	1	$1.137 trillion (2023 est.)
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_numeric`	Real gdp purchasing power parity 2023 (numeric)	float	0%	1	1.137
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text`	Real gdp purchasing power parity 2022 (text)	string	0%	1	$1.078 trillion (2022 est.)
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_numeric`	Real gdp purchasing power parity 2022 (numeric)	float	0%	1	1.078
`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	5.7% (2024 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric`	Real gdp growth rate 2024 (numeric)	float	0%	1	5.7
`real_gdp_growth_rate_real_gdp_growth_rate_2023_text`	Real gdp growth rate 2023 (text)	string	0%	1	5.5% (2023 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric`	Real gdp growth rate 2023 (numeric)	float	0%	1	5.5
`real_gdp_growth_rate_real_gdp_growth_rate_2022_text`	Real gdp growth rate 2022 (text)	string	0%	1	7.6% (2022 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric`	Real gdp growth rate 2022 (numeric)	float	0%	1	7.6
`real_gdp_growth_rate_note`	real_gdp_growth_rate_note	string	0%	1	note: annual GDP % growth based on constant local currency
`real_gdp_per_capita_real_gdp_per_capita_2024_text`	Real gdp per capita 2024 (text)	string	0%	1	$10,400 (2024 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_text`	Real gdp per capita 2023 (text)	string	0%	1	$9,900 (2023 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_numeric`	Real gdp per capita 2023 (numeric)	float	0%	1	9900.0
`real_gdp_per_capita_real_gdp_per_capita_2022_text`	Real gdp per capita 2022 (text)	string	0%	1	$9,500 (2022 est.)
`real_gdp_per_capita_real_gdp_per_capita_2022_numeric`	Real gdp per capita 2022 (numeric)	float	0%	1	9500.0
`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	$461.618 billion (2024 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text`	Inflation rate consumer prices 2024 (text)	string	0%	1	3.2% (2024 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric`	Inflation rate consumer prices 2024 (numeric)	float	0%	1	3.2
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text`	Inflation rate consumer prices 2023 (text)	string	0%	1	6% (2023 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric`	Inflation rate consumer prices 2023 (numeric)	float	0%	1	6.0
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text`	Inflation rate consumer prices 2022 (text)	string	0%	1	5.8% (2022 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric`	Inflation rate consumer prices 2022 (numeric)	float	0%	1	5.8
`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	9.1% (2024 est.)
+122 more extension fields — download the CSV/Parquet to see them all.

PHL OpenFactBook - Energy — 1 rows, 55 columns

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

Standards-Aligned Fields (4)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`electricity_access_electrification_total_population_numeric`	Electricity access percent	float	SEL	0%	1	94.8
`country_code`	Country code	string	SEL	0%	1	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`admin_level`	Admin level	string	SEL	0%	1	national

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

Field Name	Label	Type	Nulls	Unique	Samples
`electricity_access_electrification_total_population_text`	electricity_access_electrification_total_population_text	string	0%	1	94.8% (2022 est.)
`electricity_access_electrification_urban_areas_text`	electricity_access_electrification_urban_areas_text	string	0%	1	98%
`electricity_access_electrification_urban_areas_numeric`	electricity_access_electrification_urban_areas_numeric	float	0%	1	98.0
`electricity_access_electrification_rural_areas_text`	electricity_access_electrification_rural_areas_text	string	0%	1	91.1%
`electricity_access_electrification_rural_areas_numeric`	electricity_access_electrification_rural_areas_numeric	float	0%	1	91.1
`electricity_installed_generating_capacity_text`	electricity_installed_generating_capacity_text	string	0%	1	29.174 million kW (2023 est.)
`electricity_installed_generating_capacity_numeric`	electricity_installed_generating_capacity_numeric	float	0%	1	29.174
`electricity_consumption_text`	electricity_consumption_text	string	0%	1	100.824 billion kWh (2023 est.)
`electricity_consumption_numeric`	electricity_consumption_numeric	float	0%	1	100.824
`electricity_transmission_distribution_losses_text`	electricity_transmission_distribution_losses_text	string	0%	1	10.693 billion kWh (2023 est.)
`electricity_transmission_distribution_losses_numeric`	electricity_transmission_distribution_losses_numeric	float	0%	1	10.693
`electricity_generation_sources_fossil_fuels_text`	electricity_generation_sources_fossil_fuels_text	string	0%	1	77.9% of total installed capacity (2023 est.)
`electricity_generation_sources_fossil_fuels_numeric`	electricity_generation_sources_fossil_fuels_numeric	float	0%	1	77.9
`electricity_generation_sources_solar_text`	electricity_generation_sources_solar_text	string	0%	1	1.6% of total installed capacity (2023 est.)
`electricity_generation_sources_solar_numeric`	electricity_generation_sources_solar_numeric	float	0%	1	1.6
`electricity_generation_sources_wind_text`	electricity_generation_sources_wind_text	string	0%	1	0.9% of total installed capacity (2023 est.)
`electricity_generation_sources_wind_numeric`	electricity_generation_sources_wind_numeric	float	0%	1	0.9
`electricity_generation_sources_hydroelectricity_text`	electricity_generation_sources_hydroelectricity_text	string	0%	1	9% of total installed capacity (2023 est.)
`electricity_generation_sources_hydroelectricity_numeric`	electricity_generation_sources_hydroelectricity_numeric	float	0%	1	9.0
`electricity_generation_sources_geothermal_text`	electricity_generation_sources_geothermal_text	string	0%	1	9.3% of total installed capacity (2023 est.)
`electricity_generation_sources_geothermal_numeric`	electricity_generation_sources_geothermal_numeric	float	0%	1	9.3
`electricity_generation_sources_biomass_and_waste_text`	electricity_generation_sources_biomass_and_waste_text	string	0%	1	1.2% of total installed capacity (2023 est.)
`electricity_generation_sources_biomass_and_waste_numeric`	electricity_generation_sources_biomass_and_waste_numeric	float	0%	1	1.2
`coal_production_text`	coal_production_text	string	0%	1	14.457 million metric tons (2023 est.)
`coal_production_numeric`	coal_production_numeric	float	0%	1	14.457
`coal_consumption_text`	coal_consumption_text	string	0%	1	42.859 million metric tons (2023 est.)
`coal_consumption_numeric`	coal_consumption_numeric	float	0%	1	42.859
`coal_exports_text`	coal_exports_text	string	0%	1	8.151 million metric tons (2023 est.)
`coal_exports_numeric`	coal_exports_numeric	float	0%	1	8.151
`coal_imports_text`	coal_imports_text	string	0%	1	36.542 million metric tons (2023 est.)
+21 more extension fields — download the CSV/Parquet to see them all.

PHL OpenFactBook - Environment — 1 rows, 60 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	42.7
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	24.7
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	48.3
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	2.04
`waste_and_recycling_municipal_solid_waste_generated_annually_numeric`	Municipal waste kg per capita	float	SEL	0%	1	14.632
`country_code`	Country code	string	SEL	0%	1	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`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	deforestation, especially in watershed areas; illegal...
`international_environmental_agreements_party_to_text`	international_environmental_agreements_party_to_text	string	0%	1	Biodiversity, Climate Change, Climate Change-Kyoto...
`international_environmental_agreements_party_to_numeric`	international_environmental_agreements_party_to_numeric	float	0%	1	2006.0
`international_environmental_agreements_signed_but_not_ratified_text`	international_environmental_agreements_signed_but_not_ratified_text	string	0%	1	none of the selected agreements
`climate_text`	climate_text	string	0%	1	tropical marine; northeast monsoon (November to April);...
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	42.7% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 18.7% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	18.7
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 18.9% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	18.9
`land_use_agricultural_land_permanent_pasture_text`	land_use_agricultural_land_permanent_pasture_text	string	0%	1	permanent pasture: 5% (2023 est.)
`land_use_agricultural_land_permanent_pasture_numeric`	land_use_agricultural_land_permanent_pasture_numeric	float	0%	1	5.0
`land_use_forest_text`	land_use_forest_text	string	0%	1	24.7% (2023 est.)
`land_use_other_text`	land_use_other_text	string	0%	1	32.7% (2023 est.)
`land_use_other_numeric`	land_use_other_numeric	float	0%	1	32.7
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	48.3% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	2.04% annual rate of change (2020-25 est.)
`carbon_dioxide_emissions_total_emissions_text`	carbon_dioxide_emissions_total_emissions_text	string	0%	1	156.228 million metric tonnes of CO2 (2023 est.)
`carbon_dioxide_emissions_total_emissions_numeric`	carbon_dioxide_emissions_total_emissions_numeric	float	0%	1	156.228
`carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text`	carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text	string	0%	1	88.581 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	88.581
`carbon_dioxide_emissions_from_petroleum_and_other_liquids_text`	carbon_dioxide_emissions_from_petroleum_and_other_liquids_text	string	0%	1	61.597 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	61.597
`carbon_dioxide_emissions_from_consumed_natural_gas_text`	carbon_dioxide_emissions_from_consumed_natural_gas_text	string	0%	1	6.05 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	6.05
`particulate_matter_emissions_text`	particulate_matter_emissions_text	string	0%	1	25.4 micrograms per cubic meter (2019 est.)
`particulate_matter_emissions_numeric`	particulate_matter_emissions_numeric	float	0%	1	25.4
`methane_emissions_energy_text`	methane_emissions_energy_text	string	0%	1	230.7 kt (2022-2024 est.)
`methane_emissions_energy_numeric`	methane_emissions_energy_numeric	float	0%	1	230.7
`methane_emissions_agriculture_text`	methane_emissions_agriculture_text	string	0%	1	1,662.2 kt (2019-2021 est.)
+22 more extension fields — download the CSV/Parquet to see them all.

PHL OpenFactBook - Ethnic Groups — 1 rows, 9 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	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`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	Filipino(s)
`nationality_adjective_text`	nationality_adjective_text	string	0%	1	Philippine
`ethnic_groups_text`	ethnic_groups_text	string	0%	1	Tagalog 26%, Bisaya/Binisaya 14.3%, Ilocano 8%, Cebuano...
`ethnic_groups_numeric`	ethnic_groups_numeric	float	0%	1	26.0
`source_section`	source_section	string	0%	1	People and Society:ethnic_groups
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/rp.json

PHL OpenFactBook - Geography — 1 rows, 55 columns

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Field details — 55 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	300000.0
`area_land_numeric`	Area land sqkm	float	SEL	0%	1	298170.0
`area_water_numeric`	Area water sqkm	float	SEL	0%	1	1830.0
`land_boundaries_total_numeric`	Land boundary km	float	SEL	0%	1	0.0
`coastline_numeric`	Coastline km	float	SEL	0%	1	36289.0
`elevation_highest_point_numeric`	Elevation max m	float	SEL	0%	1	2954.0
`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	42.7
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	24.7
`irrigated_land_numeric`	Irrigated land sqkm	float	SEL	0%	1	16270.0
`country_code`	Country code	string	SEL	0%	1	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (42) — 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 Philippine...
`geographic_coordinates_text`	geographic_coordinates_text	string	0%	1	13 00 N, 122 00 E
`geographic_coordinates_numeric`	geographic_coordinates_numeric	float	0%	1	13.0
`map_references_text`	map_references_text	string	0%	1	Southeast Asia
`area_total_text`	area_total_text	string	0%	1	300,000 sq km
`area_land_text`	area_land_text	string	0%	1	298,170 sq km
`area_water_text`	area_water_text	string	0%	1	1,830 sq km
`area_comparative_text`	area_comparative_text	string	0%	1	slightly less than twice the size of Georgia; slightly...
`land_boundaries_total_text`	land_boundaries_total_text	string	0%	1	0 km
`coastline_text`	coastline_text	string	0%	1	36,289 km
`maritime_claims_territorial_sea_text`	maritime_claims_territorial_sea_text	string	0%	1	irregular polygon extending up to 100 nm from coastline...
`maritime_claims_territorial_sea_numeric`	maritime_claims_territorial_sea_numeric	float	0%	1	100.0
`maritime_claims_exclusive_economic_zone_text`	maritime_claims_exclusive_economic_zone_text	string	0%	1	200 nm
`maritime_claims_exclusive_economic_zone_numeric`	maritime_claims_exclusive_economic_zone_numeric	float	0%	1	200.0
`maritime_claims_continental_shelf_text`	maritime_claims_continental_shelf_text	string	0%	1	to the depth of exploitation
`climate_text`	climate_text	string	0%	1	tropical marine; northeast monsoon (November to April);...
`terrain_text`	terrain_text	string	0%	1	mostly mountains with narrow to extensive coastal lowlands
`elevation_highest_point_text`	elevation_highest_point_text	string	0%	1	Mount Apo 2,954 m
`elevation_lowest_point_text`	elevation_lowest_point_text	string	0%	1	Philippine Sea 0 m
`elevation_mean_elevation_text`	elevation_mean_elevation_text	string	0%	1	442 m
`elevation_mean_elevation_numeric`	elevation_mean_elevation_numeric	float	0%	1	442.0
`natural_resources_text`	natural_resources_text	string	0%	1	timber, petroleum, nickel, cobalt, silver, gold, salt, copper
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	42.7% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 18.7% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	18.7
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 18.9% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	18.9
`land_use_agricultural_land_permanent_pasture_text`	land_use_agricultural_land_permanent_pasture_text	string	0%	1	permanent pasture: 5% (2023 est.)
`land_use_agricultural_land_permanent_pasture_numeric`	land_use_agricultural_land_permanent_pasture_numeric	float	0%	1	5.0
`land_use_forest_text`	land_use_forest_text	string	0%	1	24.7% (2023 est.)
+12 more extension fields — download the CSV/Parquet to see them all.

PHL OpenFactBook - Government — 1 rows, 126 columns

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Field details — 126 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	PHL
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (124) — 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 the Philippines
`country_name_conventional_short_form_text`	country_name_conventional_short_form_text	string	0%	1	Philippines
`country_name_local_long_form_text`	country_name_local_long_form_text	string	0%	1	Republika ng Pilipinas
`country_name_local_short_form_text`	country_name_local_short_form_text	string	0%	1	Pilipinas
`country_name_etymology_text`	country_name_etymology_text	string	0%	1	named in honor of King PHILLIP II of Spain by Spanish...
`country_name_etymology_numeric`	country_name_etymology_numeric	float	0%	1	1543.0
`government_type_text`	government_type_text	string	0%	1	presidential republic
`capital_name_text`	capital_name_text	string	0%	1	Manila
`capital_geographic_coordinates_text`	capital_geographic_coordinates_text	string	0%	1	14 36 N, 120 58 E
`capital_geographic_coordinates_numeric`	capital_geographic_coordinates_numeric	float	0%	1	14.0
`capital_time_difference_text`	capital_time_difference_text	string	0%	1	UTC+8 (13 hours ahead of Washington, DC, during Standard Time)
`capital_time_difference_numeric`	capital_time_difference_numeric	float	0%	1	8.0
`capital_etymology_text`	capital_etymology_text	string	0%	1	derives from the Tagalog word may, meaning "there is,"...
`administrative_divisions_text`	administrative_divisions_text	string	0%	1	81 provinces and 38 chartered cities provinces: Abra,...
`administrative_divisions_numeric`	administrative_divisions_numeric	float	0%	1	81.0
`legal_system_text`	legal_system_text	string	0%	1	mixed system of civil, common, Islamic (sharia), and...
`constitution_history_text`	constitution_history_text	string	0%	1	several previous; latest ratified 2 February 1987,...
`constitution_history_numeric`	constitution_history_numeric	float	0%	1	2.0
`constitution_amendment_process_text`	constitution_amendment_process_text	string	0%	1	proposed by Congress if supported by three fourths of...
`international_law_organization_participation_text`	international_law_organization_participation_text	string	0%	1	accepts compulsory ICJ jurisdiction with reservations;...
`international_law_organization_participation_numeric`	international_law_organization_participation_numeric	float	0%	1	2019.0
`citizenship_citizenship_by_birth_text`	Citizenship by birth (text)	string	0%	1	no
`citizenship_citizenship_by_descent_only_text`	Citizenship by descent only (text)	string	0%	1	at least one parent must be a citizen of the Philippines
`citizenship_dual_citizenship_recognized_text`	citizenship_dual_citizenship_recognized_text	string	0%	1	no
`citizenship_residency_requirement_for_naturalization_text`	citizenship_residency_requirement_for_naturalization_text	string	0%	1	10 years
`citizenship_residency_requirement_for_naturalization_numeric`	citizenship_residency_requirement_for_naturalization_numeric	float	0%	1	10.0
`suffrage_text`	suffrage_text	string	0%	1	18 years of age; universal
`suffrage_numeric`	suffrage_numeric	float	0%	1	18.0
`executive_branch_chief_of_state_text`	executive_branch_chief_of_state_text	string	0%	1	President Ferdinand "BongBong" MARCOS, Jr. (since 30 June 2022)
`executive_branch_chief_of_state_numeric`	executive_branch_chief_of_state_numeric	float	0%	1	30.0
+94 more extension fields — download the CSV/Parquet to see them all.

PHL OpenFactBook - Introduction — 1 rows, 7 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	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`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 Philippine Islands became a Spanish colony during...
`background_numeric`	background_numeric	float	0%	1	16.0
`source_section`	source_section	string	0%	1	Introduction
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/rp.json

PHL OpenFactBook - Languages — 1 rows, 9 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	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`admin_level`	Admin level	string	SEL	0%	1	national

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

Field Name	Label	Type	Nulls	Unique	Samples
`languages_languages_text`	Languages (text)	string	0%	1	Tagalog 39.9%, Bisaya/Binisaya 16%, Hiligaynon/Ilonggo...
`languages_languages_numeric`	Languages (numeric)	float	0%	1	39.9
`languages_major_language_sample_s_text`	languages_major_language_sample_s_text	string	0%	1	Ang World Factbook, ang mapagkukunan ng kailangang...
`languages_note`	languages_note	string	0%	1	note: data represent percentage of households;...
`source_section`	source_section	string	0%	1	People and Society:languages
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/rp.json

PHL 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	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`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	2,342 (2024 est.)
`refugees_and_internally_displaced_persons_refugees_numeric`	refugees_and_internally_displaced_persons_refugees_numeric	float	0%	1	2342.0
`refugees_and_internally_displaced_persons_idps_text`	refugees_and_internally_displaced_persons_idps_text	string	0%	1	1,158,643 (2024 est.)
`refugees_and_internally_displaced_persons_idps_numeric`	refugees_and_internally_displaced_persons_idps_numeric	float	0%	1	1158643.0
`refugees_and_internally_displaced_persons_stateless_persons_text`	refugees_and_internally_displaced_persons_stateless_persons_text	string	0%	1	30 (2024 est.)
`refugees_and_internally_displaced_persons_stateless_persons_numeric`	refugees_and_internally_displaced_persons_stateless_persons_numeric	float	0%	1	30.0
`source_section`	source_section	string	0%	1	Transnational Issues:migration
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/rp.json

PHL OpenFactBook - Military And Security — 1 rows, 25 columns

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

Standards-Aligned Fields (3)

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`military_and_security_forces_text`	military_and_security_forces_text	string	0%	1	Armed Forces of the Philippines (AFP): Army, Navy...
`military_and_security_forces_numeric`	military_and_security_forces_numeric	float	0%	1	2025.0
`military_expenditures_military_expenditures_2024_text`	Military expenditures 2024 (text)	string	0%	1	1.7% of GDP (2024 est.)
`military_expenditures_military_expenditures_2024_numeric`	Military expenditures 2024 (numeric)	float	0%	1	1.7
`military_expenditures_military_expenditures_2023_text`	Military expenditures 2023 (text)	string	0%	1	1.5% of GDP (2023 est.)
`military_expenditures_military_expenditures_2023_numeric`	Military expenditures 2023 (numeric)	float	0%	1	1.5
`military_expenditures_military_expenditures_2022_text`	Military expenditures 2022 (text)	string	0%	1	1.4% of GDP (2022 est.)
`military_expenditures_military_expenditures_2022_numeric`	Military expenditures 2022 (numeric)	float	0%	1	1.4
`military_expenditures_military_expenditures_2021_text`	Military expenditures 2021 (text)	string	0%	1	1.2% of GDP (2021 est.)
`military_expenditures_military_expenditures_2021_numeric`	Military expenditures 2021 (numeric)	float	0%	1	1.2
`military_expenditures_military_expenditures_2020_text`	Military expenditures 2020 (text)	string	0%	1	1.1% of GDP (2020 est.)
`military_expenditures_military_expenditures_2020_numeric`	Military expenditures 2020 (numeric)	float	0%	1	1.1
`military_and_security_service_personnel_strengths_text`	military_and_security_service_personnel_strengths_text	string	0%	1	approximately 145,000 active Armed Forces (105,000 Army;...
`military_and_security_service_personnel_strengths_numeric`	military_and_security_service_personnel_strengths_numeric	float	0%	1	145000.0
`military_equipment_inventories_and_acquisitions_text`	military_equipment_inventories_and_acquisitions_text	string	0%	1	the AFP is equipped with a mix of imported weapons...
`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	some variations in age based on the branch of service,...
`military_service_age_and_obligation_numeric`	military_service_age_and_obligation_numeric	float	0%	1	18.0
`military_note_text`	military_note_text	string	0%	1	the Armed Forces of the Philippines (AFP) are...
`military_note_numeric`	military_note_numeric	float	0%	1	2014.0
`source_section`	source_section	string	0%	1	Military and Security
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/rp.json

PHL OpenFactBook - People And Society — 1 rows, 151 columns

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Field details — 151 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	118277063.0
`population_male_numeric`	Population male	float	SEL	0%	1	59227092.0
`population_female_numeric`	Population female	float	SEL	0%	1	59049971.0
`age_structure_0_14_years_numeric`	Population 0 14 percent	float	SEL	0%	1	30.2
`age_structure_15_64_years_numeric`	Population 15 64 percent	float	SEL	0%	1	64.3
`age_structure_65_years_and_over_numeric`	Population 65 plus percent	float	SEL	0%	1	5.6
`dependency_ratios_total_dependency_ratio_numeric`	Total dependency ratio	float	SEL	0%	1	55.6
`dependency_ratios_youth_dependency_ratio_numeric`	Youth dependency ratio	float	SEL	0%	1	47.0
`dependency_ratios_elderly_dependency_ratio_numeric`	Elderly dependency ratio	float	SEL	0%	1	8.7
`median_age_total_numeric`	Median age	float	SEL	0%	1	27.1
`population_growth_rate_numeric`	Population growth rate percent	float	SEL	0%	1	0.74
`birth_rate_numeric`	Birth rate per 1000	float	SEL	0%	1	16.02
`death_rate_numeric`	Death rate per 1000	float	SEL	0%	1	5.8
`net_migration_rate_numeric`	Net migration per 1000	float	SEL	0%	1	-2.82
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	48.3
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	2.04
`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	84.0
`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	70.8
`total_fertility_rate_numeric`	Fertility rate	float	SEL	0%	1	1.94
`gross_reproduction_rate_numeric`	Gross reproduction rate	float	SEL	0%	1	0.94
`physician_density_numeric`	Physicians per 1000	float	SEL	0%	1	0.79
`hospital_bed_density_numeric`	Hospital beds per 1000	float	SEL	0%	1	1.0
`literacy_total_population_numeric`	Literacy rate percent	float	SEL	0%	1	98.5
`country_code`	Country code	string	SEL	0%	1	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (122) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`population_total_text`	population_total_text	string	0%	1	118,277,063 (2024 est.)
`population_male_text`	population_male_text	string	0%	1	59,227,092
`population_female_text`	population_female_text	string	0%	1	59,049,971
`age_structure_0_14_years_text`	age_structure_0_14_years_text	string	0%	1	30.2% (male 18,234,279/female 17,462,803)
`age_structure_15_64_years_text`	age_structure_15_64_years_text	string	0%	1	64.3% (male 38,381,583/female 37,613,294)
`age_structure_65_years_and_over_text`	age_structure_65_years_and_over_text	string	0%	1	5.6% (2024 est.) (male 2,611,230/female 3,973,874)
`dependency_ratios_total_dependency_ratio_text`	dependency_ratios_total_dependency_ratio_text	string	0%	1	55.6 (2024 est.)
`dependency_ratios_youth_dependency_ratio_text`	dependency_ratios_youth_dependency_ratio_text	string	0%	1	47 (2024 est.)
`dependency_ratios_elderly_dependency_ratio_text`	dependency_ratios_elderly_dependency_ratio_text	string	0%	1	8.7 (2024 est.)
`dependency_ratios_potential_support_ratio_text`	dependency_ratios_potential_support_ratio_text	string	0%	1	11.5 (2024 est.)
`dependency_ratios_potential_support_ratio_numeric`	dependency_ratios_potential_support_ratio_numeric	float	0%	1	11.5
`median_age_total_text`	median_age_total_text	string	0%	1	27.1 years (2025 est.)
`median_age_male_text`	median_age_male_text	string	0%	1	25.1 years
`median_age_male_numeric`	median_age_male_numeric	float	0%	1	25.1
`median_age_female_text`	median_age_female_text	string	0%	1	26.3 years
`median_age_female_numeric`	median_age_female_numeric	float	0%	1	26.3
`population_growth_rate_text`	population_growth_rate_text	string	0%	1	0.74% (2025 est.)
`birth_rate_text`	birth_rate_text	string	0%	1	16.02 births/1,000 population (2025 est.)
`death_rate_text`	death_rate_text	string	0%	1	5.8 deaths/1,000 population (2025 est.)
`net_migration_rate_text`	net_migration_rate_text	string	0%	1	-2.82 migrant(s)/1,000 population (2025 est.)
`population_distribution_text`	population_distribution_text	string	0%	1	population concentrated in areas with good farmland;...
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	48.3% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	2.04% annual rate of change (2020-25 est.)
`major_urban_areas_population_text`	major_urban_areas_population_text	string	0%	1	14.667 million MANILA (capital), 1.949 million Davao,...
`major_urban_areas_population_numeric`	major_urban_areas_population_numeric	float	0%	1	14.667
`sex_ratio_at_birth_text`	sex_ratio_at_birth_text	string	0%	1	1.05 male(s)/female
`sex_ratio_0_14_years_text`	sex_ratio_0_14_years_text	string	0%	1	1.04 male(s)/female
`sex_ratio_0_14_years_numeric`	sex_ratio_0_14_years_numeric	float	0%	1	1.04
`sex_ratio_15_64_years_text`	sex_ratio_15_64_years_text	string	0%	1	1.02 male(s)/female
`sex_ratio_15_64_years_numeric`	sex_ratio_15_64_years_numeric	float	0%	1	1.02
+92 more extension fields — download the CSV/Parquet to see them all.

PHL OpenFactBook - Religions — 1 rows, 27 columns

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Field details — 27 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	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`admin_level`	Admin level	string	SEL	0%	1	national
`composition_religion_muslim_pct_synth`	Muslim	numeric	CCL	0%	-	6.4
`composition_religion_other_pct_synth`	other	numeric	CCL	0%	-	8.2
`composition_ethnicity_primary_label_synth`	Tagalog	string	CCL	0%	-	Tagalog

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	Roman Catholic 78.8%, Muslim 6.4%, Iglesia ni Cristo...
`religions_numeric`	religions_numeric	float	0%	1	78.8
`source_section`	source_section	string	0%	1	People and Society:religions
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/rp.json

Pending (17) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`composition_religion_roman_catholic_pct_synth`	Roman Catholic	numeric	0%	-	78.8
`composition_religion_iglesia_ni_cristo_pct_synth`	Iglesia ni Cristo	numeric	0%	-	2.6
`composition_religion_other_christian_pct_synth`	other Christian	numeric	0%	-	3.9
`composition_religion_none_unspecified_0_1_pct_synth`	none/unspecified <0.1	numeric	0%	-	-
`composition_ethnicity_tagalog_pct_synth`	Tagalog	numeric	0%	-	26.0
`composition_ethnicity_bisaya_binisaya_pct_synth`	Bisaya/Binisaya	numeric	0%	-	14.3
`composition_ethnicity_ilocano_pct_synth`	Ilocano	numeric	0%	-	8.0
`composition_ethnicity_cebuano_pct_synth`	Cebuano	numeric	0%	-	8.0
`composition_ethnicity_illonggo_pct_synth`	Illonggo	numeric	0%	-	7.9
`composition_ethnicity_bikol_bicol_pct_synth`	Bikol/Bicol	numeric	0%	-	6.5
`composition_ethnicity_waray_pct_synth`	Waray	numeric	0%	-	3.8
`composition_ethnicity_kapampangan_pct_synth`	Kapampangan	numeric	0%	-	3.0
`composition_ethnicity_maguindanao_pct_synth`	Maguindanao	numeric	0%	-	1.9
`composition_ethnicity_pangasinan_pct_synth`	Pangasinan	numeric	0%	-	1.9
`composition_ethnicity_other_local_ethnicities_pct_synth`	other local ethnicities	numeric	0%	-	18.5
`composition_ethnicity_foreign_ethnicities_pct_synth`	foreign ethnicities	numeric	0%	-	0.2
`composition_ethnicity_primary_share_pct_synth`	Tagalog	numeric	0%	-	26.0

PHL OpenFactBook - Space — 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	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`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	Philippine Space Agency (PhilSA; established 2019) (2025)
`space_agency_agencies_numeric`	space_agency_agencies_numeric	float	0%	1	2019.0
`space_program_overview_text`	space_program_overview_text	string	0%	1	has a small space program focused on acquiring...
`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	1994 - formed a consortium of companies to acquire and...
`key_space_program_milestones_numeric`	key_space_program_milestones_numeric	float	0%	1	1994.0
`source_section`	source_section	string	0%	1	Space
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/rp.json

PHL OpenFactBook - Terrorism — 1 rows, 6 columns

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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	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`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	Abu Sayyaf Group; Communist Party of the Philippines/New...
`source_section`	source_section	string	0%	1	Terrorism
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/rp.json

PHL OpenFactBook - Transportation — 1 rows, 33 columns

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Field details — 33 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`civil_aircraft_registration_country_code_prefix_text`	Civil aircraft registration country code prefix text	string	SEL+	0%	1	RP
`airports_numeric`	Airports count	float	SEL	0%	1	256.0
`country_code`	Country code	string	SEL	0%	1	PHL
`country_name`	Country name	string	SEL	0%	1	Philippines
`admin_level`	Admin level	string	SEL	0%	1	national

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

Field Name	Label	Type	Nulls	Unique	Samples
`airports_text`	airports_text	string	0%	1	256 (2025)
`heliports_text`	heliports_text	string	0%	1	416 (2025)
`heliports_numeric`	heliports_numeric	float	0%	1	416.0
`railways_total_text`	railways_total_text	string	0%	1	77 km (2017)
`railways_total_numeric`	railways_total_numeric	float	0%	1	77.0
`railways_standard_gauge_text`	railways_standard_gauge_text	string	0%	1	49 km (2017) 1.435-m gauge
`railways_standard_gauge_numeric`	railways_standard_gauge_numeric	float	0%	1	49.0
`railways_narrow_gauge_text`	railways_narrow_gauge_text	string	0%	1	28 km (2017) 1.067-m gauge
`railways_narrow_gauge_numeric`	railways_narrow_gauge_numeric	float	0%	1	28.0
`merchant_marine_total_text`	merchant_marine_total_text	string	0%	1	2,203 (2023)
`merchant_marine_total_numeric`	merchant_marine_total_numeric	float	0%	1	2203.0
`merchant_marine_by_type_text`	merchant_marine_by_type_text	string	0%	1	bulk carrier 52, container ship 43, general cargo 955,...
`merchant_marine_by_type_numeric`	merchant_marine_by_type_numeric	float	0%	1	52.0
`ports_total_ports_text`	ports_total_ports_text	string	0%	1	70 (2024)
`ports_total_ports_numeric`	ports_total_ports_numeric	float	0%	1	70.0
`ports_large_text`	ports_large_text	float	0%	1	2
`ports_large_numeric`	ports_large_numeric	float	0%	1	2.0
`ports_medium_text`	ports_medium_text	float	0%	1	4
`ports_medium_numeric`	ports_medium_numeric	float	0%	1	4.0
`ports_small_text`	ports_small_text	float	0%	1	8
`ports_small_numeric`	ports_small_numeric	float	0%	1	8.0
`ports_very_small_text`	ports_very_small_text	float	0%	1	56
`ports_very_small_numeric`	ports_very_small_numeric	float	0%	1	56.0
`ports_ports_with_oil_terminals_text`	Ports with oil terminals (text)	float	0%	1	22
`ports_ports_with_oil_terminals_numeric`	Ports with oil terminals (numeric)	float	0%	1	22.0
`ports_key_ports_text`	ports_key_ports_text	string	0%	1	Batangas City, Cagayan de Oro, Cebu, Manila, San...
`source_section`	source_section	string	0%	1	Transportation
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/rp.json

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

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

PHL Nga Gns - Language — 12 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	PHL, PHL, PHL, PHL, PHL
`gns_language_code`	gns_language_code	string	CCL	0%	12	fil, eng, spa, tgl, ceb
`gns_language_name`	gns_language_name	string	CCL	0%	12	Filipino; Pilipino, English, Spanish, Tagalog, Cebuano
`gns_toponym_count`	gns_toponym_count	integer	CCL	0%	8	112361, 664, 19, 16, 7
`gns_toponym_share_pct`	gns_toponym_share_pct	float	CCL	0%	8	99.3642, 0.5872, 0.0168, 0.0141, 0.0062
`gns_non_roman_toponym_count`	gns_non_roman_toponym_count	integer	CCL	0%	1	0, 0, 0, 0, 0
`gns_dominant_script_code`	gns_dominant_script_code	string	CCL	0%	1	, , , ,
`gns_dominant_script_name`	gns_dominant_script_name	string	CCL	0%	1	, , , ,
`gns_script_count`	gns_script_count	integer	CCL	0%	1	0, 0, 0, 0, 0

PHL 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	PHL
`admin_level`	admin_level	integer	SEL	0%	1	0
`gns_country_name`	gns_country_name	string	SEL	0%	1	Philippines
`gns_language_count`	gns_language_count	integer	CCL	0%	1	12
`gns_script_count`	gns_script_count	integer	CCL	0%	1	0
`gns_endonym_share_pct`	gns_endonym_share_pct	float	CCL	0%	1	100.0
`gns_non_roman_name_count`	gns_non_roman_name_count	integer	CCL	0%	1	0

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	137104
`gns_feature_count`	gns_feature_count	integer	0%	1	107211
`gns_endonym_count`	gns_endonym_count	integer	0%	1	137104
`gns_exonym_count`	gns_exonym_count	integer	0%	1	0
`gns_source_build_date`	gns_source_build_date	string	0%	1	Wed, 05 Aug 2026
`gns_source_change_date`	gns_source_change_date	string	0%	1	2026-08-05
`gns_name_count_hydrographic`	gns_name_count_hydrographic	integer	0%	1	23875
`gns_feature_count_hydrographic`	gns_feature_count_hydrographic	integer	0%	1	13565
`gns_name_count_hypsographic`	gns_name_count_hypsographic	integer	0%	1	14058
`gns_feature_count_hypsographic`	gns_feature_count_hypsographic	integer	0%	1	10794
`gns_name_count_populated_places`	gns_name_count_populated_places	integer	0%	1	58635
`gns_feature_count_populated_places`	gns_feature_count_populated_places	integer	0%	1	45231
`gns_name_count_transportation_networks`	gns_name_count_transportation_networks	integer	0%	1	11206
`gns_feature_count_transportation_networks`	gns_feature_count_transportation_networks	integer	0%	1	11142
`gns_name_count_spot_features`	gns_name_count_spot_features	integer	0%	1	4641
`gns_feature_count_spot_features`	gns_feature_count_spot_features	integer	0%	1	4503
`gns_name_count_administrative_regions`	gns_name_count_administrative_regions	integer	0%	1	24176
`gns_feature_count_administrative_regions`	gns_feature_count_administrative_regions	integer	0%	1	21518
`gns_name_count_areas_localities`	gns_name_count_areas_localities	integer	0%	1	473
`gns_feature_count_areas_localities`	gns_feature_count_areas_localities	integer	0%	1	424
`gns_name_count_vegetation`	gns_name_count_vegetation	integer	0%	1	25
`gns_feature_count_vegetation`	gns_feature_count_vegetation	integer	0%	1	24
`gns_name_count_undersea`	gns_name_count_undersea	integer	0%	1	15
`gns_feature_count_undersea`	gns_feature_count_undersea	integer	0%	1	10

PHL D-PLACE PHL-DPLACE Ethnographic Societies

12 rows · 1 table(s) D-PLACE 0 1 2 3 1 SEL 10 CCL 7 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)

PHL D-PLACE - Dplace Ea Societies — 12 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	PHL, PHL, PHL, PHL, PHL
`society_id`	Society id	string	CCL	0%	12	Ia12, Ia13, Ia15, Ia16, Ia17
`society_name`	Society name	string	CCL	0%	12	Sugbuanon, Badjau Tawi-Tawi, Manobo, Kalinga, Bilaan
`language_glottocode`	Language glottocode	string	CCL	0%	12	cebu1242, sout2918, agus1235, lubu1243, koro1310
`language_name`	Language name	string	CCL	0%	1	, , , ,
`kinship_system`	Kinship system	string	CCL	0%	10	EA001:0; EA002:0; EA003:2; EA004:1; EA005:7, EA001:0;...
`marriage_pattern`	Marriage pattern	string	CCL	0%	10	EA006:1; EA007:8; EA008:1; EA009:1; EA010:6, EA006:1;...
`subsistence_pattern`	Subsistence pattern	string	CCL	0%	11	EA028:6; EA029:6; EA030:7; EA031:8; EA032:2, EA028:4;...
`political_complexity`	Political complexity	string	CCL	0%	6	EA033:5; EA034:4; EA035:NA, EA033:1; EA034:NA; EA035:NA,...
`religion_importance`	Religion importance	string	CCL	0%	8	EA034:4; EA112:5, EA034:NA; EA112:NA, EA034:NA; EA112:3,...
`residence_pattern`	Residence pattern	string	CCL	0%	6	EA011:2; EA012:6; EA013:9, EA011:2; EA012:2; EA013:9,...

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

Field Name	Label	Type	Nulls	Unique	Samples
`country_name`	country_name	string	0%	1	Philippines, Philippines, Philippines, Philippines, Philippines
`dataset`	dataset	string	0%	1	EA, EA, EA, EA, EA
`region`	region	string	0%	1	, , , ,
`latitude`	latitude	float	0%	8	10.2, 5.09, 8.0, 18.0, 6.0
`longitude`	longitude	float	0%	7	123.65, 119.97, 126.0, 121.0, 125.0
`assignment_method`	assignment_method	string	0%	1	point_in_polygon, point_in_polygon, point_in_polygon,...
`assignment_confidence`	assignment_confidence	string	0%	1	approximate, approximate, approximate, approximate, approximate

PHL Ethnic Power Relations Dataset PHL-EPR Political Ethnicity

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

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

0 Admin 0 — 1 table(s)

PHL EPR - Groups — 4 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	PHL, PHL, PHL, PHL
`ethnic_group_name`	Ethnic group name	string	CCL	0%	4	Christian lowlanders, Indigenous, Moro, Fil-Chinese
`ethnic_power_status`	Ethnic power status	string	CCL	0%	3	DOMINANT, POWERLESS, POWERLESS, IRRELEVANT
`ethnic_population_share`	Ethnic population share	float	CCL	0%	4	0.859, 0.075, 0.051, 0.015
`ethnic_group_id`	Ethnic group id	float	CCL	0%	4	84001000, 84002000, 84003000, 84004000
`regional_autonomy`	Regional autonomy	string	CCL	0%	3	, false, 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
`group_relevance`	group_relevance	string	0%	1	, , ,

PHL PSA Maternal Mortality PHL-PSA-MATERNAL_MORTALITY Health

2 rows · 1 table(s) Philippine Statistics Authority 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

PHL PSA maternal_mortality — 2 rows, 3 columns

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Field details — 3 fields (type, nulls, unique, samples)

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

Field Name	Label	Type	Nulls	Unique	Samples
`Geolocation`	Geolocation	text	0%	-	-
`Year`	Year	text	0%	-	-
`Maternal mortality ratio (per 100,000 live births)`	Maternal mortality ratio (per 100,000 live births)	text	0%	-	-

PHL Philippines Education (pivoted) PHL-HDX-Philippines___Education_wide Indicators Wide

1 rows · 1 table(s) 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)

PHL Philippines Education (wide) — 1 rows, 874 columns

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Field details — 874 fields (type, nulls, unique, samples)

Extension Fields (874) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_15-19_with_no_education`	Barro-Lee:_Percentage_of_population_age_15-19_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_15+_with_no_education`	Barro-Lee:_Percentage_of_population_age_15+_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_20-24_with_no_education`	Barro-Lee:_Percentage_of_population_age_20-24_with_no_education	numeric	0%	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	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_25-29_with_no_education`	Barro-Lee:_Percentage_of_population_age_25-29_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_25+_with_no_education`	Barro-Lee:_Percentage_of_population_age_25+_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_30-34_with_no_education`	Barro-Lee:_Percentage_of_population_age_30-34_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_35-39_with_no_education`	Barro-Lee:_Percentage_of_population_age_35-39_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_40-44_with_no_education`	Barro-Lee:_Percentage_of_population_age_40-44_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_45-49_with_no_education`	Barro-Lee:_Percentage_of_population_age_45-49_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_50-54_with_no_education`	Barro-Lee:_Percentage_of_population_age_50-54_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_55-59_with_no_education`	Barro-Lee:_Percentage_of_population_age_55-59_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education	numeric	0%	1	-
`Barro-Lee:_Percentage_of_population_age_60-64_with_no_education`	Barro-Lee:_Percentage_of_population_age_60-64_with_no_education	numeric	0%	1	-
`Barro-Lee:_Population_in_thousands_age_15-19_total`	Barro-Lee:_Population_in_thousands_age_15-19_total	numeric	0%	1	-
`Barro-Lee:_Population_in_thousands_age_15-19_female`	Barro-Lee:_Population_in_thousands_age_15-19_female	numeric	0%	1	-
`Barro-Lee:_Population_in_thousands_age_15+_total`	Barro-Lee:_Population_in_thousands_age_15+_total	numeric	0%	1	-
`Barro-Lee:_Population_in_thousands_age_15+_female`	Barro-Lee:_Population_in_thousands_age_15+_female	numeric	0%	1	-
`Barro-Lee:_Population_in_thousands_age_20-24_total`	Barro-Lee:_Population_in_thousands_age_20-24_total	numeric	0%	1	-
`Barro-Lee:_Population_in_thousands_age_20-24_female`	Barro-Lee:_Population_in_thousands_age_20-24_female	numeric	0%	1	-
+844 more extension fields — download the CSV/Parquet to see them all.

PHL Philippines Health (pivoted) PHL-HDX-Philippines___Health_wide Indicators Wide

1 rows · 1 table(s) 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)

PHL Philippines Health (wide) — 1 rows, 511 columns

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Field details — 511 fields (type, nulls, unique, samples)

Extension Fields (511) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`Proportion_of_women_subjected_to_physical_and_or_sexual_violence_in_the_last_12_`	Proportion_of_women_subjected_to_physical_and_or_sexual_violence_in_the_last_12_	numeric	0%	1	-
`Women_who_believe_a_husband_is_justified_in_beating_his_wife_when_she_argues_wit`	Women_who_believe_a_husband_is_justified_in_beating_his_wife_when_she_argues_wit	numeric	0%	1	-
`Women_who_believe_a_husband_is_justified_in_beating_his_wife_when_she_burns_the_`	Women_who_believe_a_husband_is_justified_in_beating_his_wife_when_she_burns_the_	numeric	0%	1	-
`Women_who_believe_a_husband_is_justified_in_beating_his_wife_when_she_goes_out_w`	Women_who_believe_a_husband_is_justified_in_beating_his_wife_when_she_goes_out_w	numeric	0%	1	-
`Women_who_believe_a_husband_is_justified_in_beating_his_wife_when_she_neglects_t`	Women_who_believe_a_husband_is_justified_in_beating_his_wife_when_she_neglects_t	numeric	0%	1	-
`Women_who_believe_a_husband_is_justified_in_beating_his_wife_any_of_five_reasons`	Women_who_believe_a_husband_is_justified_in_beating_his_wife_any_of_five_reasons	numeric	0%	1	-
`Women_who_believe_a_husband_is_justified_in_beating_his_wife_when_she_refuses_se`	Women_who_believe_a_husband_is_justified_in_beating_his_wife_when_she_refuses_se	numeric	0%	1	-
`Total_alcohol_consumption_per_capita_female_liters_of_pure_alcohol_projected_est`	Total_alcohol_consumption_per_capita_female_liters_of_pure_alcohol_projected_est	numeric	0%	1	-
`Total_alcohol_consumption_per_capita_liters_of_pure_alcohol_projected_estimates_`	Total_alcohol_consumption_per_capita_liters_of_pure_alcohol_projected_estimates_	numeric	0%	1	-
`Total_alcohol_consumption_per_capita_male_liters_of_pure_alcohol_projected_estim`	Total_alcohol_consumption_per_capita_male_liters_of_pure_alcohol_projected_estim	numeric	0%	1	-
`Prevalence_of_anemia_among_women_of_reproductive_age_pct_of_women_ages_15-49`	Prevalence_of_anemia_among_women_of_reproductive_age_pct_of_women_ages_15-49	numeric	0%	1	-
`Prevalence_of_anemia_among_children_pct_of_children_ages_6-59_months`	Prevalence_of_anemia_among_children_pct_of_children_ages_6-59_months	numeric	0%	1	-
`Prevalence_of_anemia_among_non-pregnant_women_pct_of_women_ages_15-49`	Prevalence_of_anemia_among_non-pregnant_women_pct_of_women_ages_15-49	numeric	0%	1	-
`Condom_use_population_ages_15-24_female_pct_of_females_ages_15-24`	Condom_use_population_ages_15-24_female_pct_of_females_ages_15-24	numeric	0%	1	-
`Condom_use_population_ages_15-24_male_pct_of_males_ages_15-24`	Condom_use_population_ages_15-24_male_pct_of_males_ages_15-24	numeric	0%	1	-
`Cause_of_death_by_communicable_diseases_and_maternal_prenatal_and_nutrition_cond`	Cause_of_death_by_communicable_diseases_and_maternal_prenatal_and_nutrition_cond	numeric	0%	1	-
`Number_of_infant_deaths`	Number_of_infant_deaths	numeric	0%	1	-
`Cause_of_death_by_injury_pct_of_total`	Cause_of_death_by_injury_pct_of_total	numeric	0%	1	-
`Number_of_under-five_deaths`	Number_of_under-five_deaths	numeric	0%	1	-
`Cause_of_death_by_non-communicable_diseases_pct_of_total`	Cause_of_death_by_non-communicable_diseases_pct_of_total	numeric	0%	1	-
`Number_of_neonatal_deaths`	Number_of_neonatal_deaths	numeric	0%	1	-
`Women's_share_of_population_ages_15+_living_with_HIV_pct`	Women's_share_of_population_ages_15+_living_with_HIV_pct	numeric	0%	1	-
`Prevalence_of_HIV_total_pct_of_population_ages_15-49`	Prevalence_of_HIV_total_pct_of_population_ages_15-49	numeric	0%	1	-
`Mortality_rate_under-5_per_1000_live_births`	Mortality_rate_under-5_per_1000_live_births	numeric	0%	1	-
`Mortality_rate_under-5_female_per_1000_live_births`	Mortality_rate_under-5_female_per_1000_live_births	numeric	0%	1	-
`Mortality_rate_under-5_male_per_1000_live_births`	Mortality_rate_under-5_male_per_1000_live_births	numeric	0%	1	-
`Mortality_from_CVD_cancer_diabetes_or_CRD_between_exact_ages_30_and_70_female_pc`	Mortality_from_CVD_cancer_diabetes_or_CRD_between_exact_ages_30_and_70_female_pc	numeric	0%	1	-
`Mortality_from_CVD_cancer_diabetes_or_CRD_between_exact_ages_30_and_70_male_pct`	Mortality_from_CVD_cancer_diabetes_or_CRD_between_exact_ages_30_and_70_male_pct	numeric	0%	1	-
`Mortality_from_CVD_cancer_diabetes_or_CRD_between_exact_ages_30_and_70_pct`	Mortality_from_CVD_cancer_diabetes_or_CRD_between_exact_ages_30_and_70_pct	numeric	0%	1	-
`Mortality_rate_neonatal_per_1000_live_births`	Mortality_rate_neonatal_per_1000_live_births	numeric	0%	1	-
+481 more extension fields — download the CSV/Parquet to see them all.

PHL Global Organized Crime Index PHL-OCINDEX Crime Index

1 rows · 1 table(s) GI-TOC / ENACT 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)

PHL Organized Crime Scores 2025 — 1 rows, 35 columns

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Field details — 35 fields (type, nulls, unique, samples)

Extension Fields (35) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`oc_anti_money_laundering`	oc_anti_money_laundering	numeric	0%	1	-
`oc_arms_trafficking`	oc_arms_trafficking	numeric	0%	1	-
`oc_cannabis_trade`	oc_cannabis_trade	numeric	0%	1	-
`oc_cocaine_trade`	oc_cocaine_trade	numeric	0%	1	-
`oc_criminal_actors`	oc_criminal_actors	numeric	0%	1	-
`oc_criminal_markets`	oc_criminal_markets	numeric	0%	1	-
`oc_criminal_networks`	oc_criminal_networks	numeric	0%	1	-
`oc_criminality`	oc_criminality	numeric	0%	1	-
`oc_cyber_dependent_crimes`	oc_cyber_dependent_crimes	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_financial_crimes`	oc_financial_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_human_smuggling`	oc_human_smuggling	numeric	0%	1	-
`oc_human_trafficking`	oc_human_trafficking	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_judicial_system_and_detention`	oc_judicial_system_and_detention	numeric	0%	1	-
`oc_law_enforcement`	oc_law_enforcement	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_political_leadership_and_governance`	oc_political_leadership_and_governance	numeric	0%	1	-
`oc_prevention`	oc_prevention	numeric	0%	1	-
`oc_private_sector_actors`	oc_private_sector_actors	numeric	0%	1	-
+5 more extension fields — download the CSV/Parquet to see them all.

PHL World Values Survey PHL-WVS Attitudes Values

1 rows · 1 table(s) 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)

PHL 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	PHL

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

Philippines

Build a download

Language	Place names	Share	Script
Filipino; Pilipino (fil)	112,361	99.4%	—
English (eng)	664	0.6%	—

Source	Type	Access
Philippine Statistics Authority	official_nso	bulk_download
Philippine Statistics Authority	official_nso	bulk_download
OCHA HDX Humanitarian Data Exchange (UN Office for the Coordination of Humanitarian Affairs)	international_organization	bulk_download
HDX (Humanitarian Data Exchange)	international_organization	bulk_download
NGA GEOnet Names Server (GNS)	official_government	bulk_download
Google	commercial	bulk_download
Global Data Lab	academic	api
World Values Survey	academic	metadata_catalog
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
GI-TOC / ENACT (Global Initiative Against Transnational Organized Crime · ENACT)	academic	bulk_download
Ethnic Power Relations Dataset	academic	bulk_download
D-PLACE (Database of Places, Language, Culture & Environment)	academic	bulk_download
World Bank Open Data	international_organization	api
LandScan Global (ORNL — Oak Ridge National Laboratory)	research_institution	earth_engine
GHS Urban Centre Database (Global Human Settlement · EU Joint Research Centre)	international_organization	bulk_download
OpenFactBook	community_compilation	bulk_download