Sao Tome and Principe

STP World Bank Open Data STP-WORLD_BANK Development Indicators

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

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

0 Admin 0 — 2 table(s)

STP 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	ST, ST, ST, ST, ST
`population_count`	Population count	float	SEL	2%	65	68012.0, 68707.0, 69403.0, 70112.0, 70865.0
`life_expectancy`	Life expectancy	float	SEL	3%	64	43.564, 45.193, 46.843, 48.4, 49.739
`gdp_per_capita_usd`	Gdp per capita usd	float	SEL	17%	55	479.373226585893, 470.047210516664, 511.225883278212,...
`literacy_rate_pct`	Literacy rate percent	float	SEL	92%	5	57.3199996948242, 73.2399978637695, 84.9100036621094,...
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	11%	57	95.6, 92.9, 90.4, 88.5, 87.1
`poverty_headcount_pct`	Poverty headcount percent	float	SEL	99%	1	55.5

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	Sao Tome and Principe, Sao Tome and Principe, Sao Tome...
`year`	year	integer	0%	66	1960, 1961, 1962, 1963, 1964

STP 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	ST, ST, ST, ST, ST
`life_expectancy`	Life expectancy	float	SEL	3%	64	43.564, 45.193, 46.843, 48.4, 49.739
`infant_mortality_per_1000`	Infant mortality per 1000	float	SEL	41%	38	26.2, 26.6, 26.4, 26.5, 26.3
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	11%	57	95.6, 92.9, 90.4, 88.5, 87.1
`maternal_mortality_per_100k`	Maternal mortality per 100k	float	SEL	41%	30	159.0, 175.0, 161.0, 157.0, 167.0
`fertility_rate`	Fertility rate	float	SEL	3%	63	6.242, 6.263, 6.284, 6.306, 6.327
`birth_rate_per_1000`	Birth rate per 1000	float	SEL	3%	64	44.558, 44.637, 42.747, 41.073, 39.681
`death_rate_per_1000`	Death rate per 1000	float	SEL	3%	63	21.812, 20.512, 19.327, 18.115, 17.097
`physicians_per_1000`	Physicians per 1000	float	SEL	80%	13	0.3, 0.233, 0.438, 0.419, 0.537
`hospital_beds_per_1000`	Hospital beds per 1000	float	SEL	94%	4	40.3154563903809, 26.7122993469238, 4.7372999191, 2.91
`vaccination_rate_pct`	Vaccination rate percent	float	SEL	33%	24	42.0, 34.0, 26.0, 49.0, 48.0
`health_expenditure_pct_gdp`	Health expenditure percent gdp	float	SEL	64%	24	9.31892776, 9.64001942, 9.49860477, 11.46527386, 10.7211771

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	Sao Tome and Principe, Sao Tome and Principe, Sao Tome...
`year`	year	integer	0%	66	1960, 1961, 1962, 1963, 1964

STP Global Data Lab STP-GDL Development Indices

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

ⓘ Global Data Lab publishes its own subnational regions, which match national admin units in some countries and group several together in others. The level shown is the nearest administrative tier, not a claim that these are that tier.

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

1 Admin 1 — 1 table(s)

STP GDL - Subnational Indices — 95 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	STP, STP, STP, STP, STP
`region_code`	Admin code	string	SEL	100%	-	-
`region_name`	Admin name	string	SEL	0%	5	Total, Regiao Centro, Regiao do Principe, Regiao Norte,...
`human_development_index`	Human development index	float	SEL	0%	74	0.572, 0.596, 0.581, 0.528, 0.531
`health_index`	Health index	float	SEL	0%	74	0.653, 0.655, 0.684, 0.627, 0.676
`education_index`	Education index	float	SEL	0%	78	0.521, 0.558, 0.542, 0.46, 0.447
`income_index`	Income index	float	SEL	0%	67	0.551, 0.581, 0.53, 0.511, 0.497
`life_expectancy`	Life expectancy	float	SEL	0%	93	62.43, 62.58, 64.47, 60.77, 63.91
`mean_years_schooling`	Mean years schooling	float	SEL	0%	81	7.817, 8.572, 7.834, 6.559, 6.425

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

Field Name	Label	Type	Nulls	Unique	Samples
`year`	year	integer	0%	19	2005, 2005, 2005, 2005, 2005
`level`	level	string	0%	2	national, subnational, subnational, subnational, subnational

STP UNHCR Refugee Data Finder STP-UNHCR Migration

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

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0 Admin 0 — 2 table(s)

STP UNHCR - Hosted Populations — 0 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%	-	-

STP UNHCR - Origin Populations — 33 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%	-	-

STP OpenFactBook STP-OPENFACTBOOK Country Profile

13 rows · 13 table(s) · 2024 OpenFactBook 0 1 2 3 90 SEL 1 CCL 515 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 — 13 table(s)

STP OpenFactBook - Communications — 1 rows, 21 columns

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

Standards-Aligned Fields (8)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`telephones_fixed_lines_subscriptions_per_100_inhabitants_numeric`	Fixed line subscriptions per 100	float	SEL	0%	1	1.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric`	Mobile subscriptions per 100	float	SEL	0%	1	87.0
`internet_country_code_text`	Internet country code text	string	SEL+	0%	1	.st
`internet_users_percent_of_population_numeric`	Internet penetration percent	float	SEL	0%	1	62.0
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric`	Broadband subscriptions per 100	float	SEL	0%	1	3.0
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`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	2,000 (2023 est.)
`telephones_fixed_lines_total_subscriptions_numeric`	telephones_fixed_lines_total_subscriptions_numeric	float	0%	1	2000.0
`telephones_fixed_lines_subscriptions_per_100_inhabitants_text`	telephones_fixed_lines_subscriptions_per_100_inhabitants_text	string	0%	1	1 (2023 est.)
`telephones_mobile_cellular_total_subscriptions_text`	telephones_mobile_cellular_total_subscriptions_text	string	0%	1	152,000 (2023 est.)
`telephones_mobile_cellular_total_subscriptions_numeric`	telephones_mobile_cellular_total_subscriptions_numeric	float	0%	1	152000.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_text`	telephones_mobile_cellular_subscriptions_per_100_inhabitants_text	string	0%	1	87 (2022 est.)
`broadcast_media_text`	broadcast_media_text	string	0%	1	1 state-owned TV station; 2 state-owned radio stations;...
`broadcast_media_numeric`	broadcast_media_numeric	float	0%	1	1.0
`internet_users_percent_of_population_text`	internet_users_percent_of_population_text	string	0%	1	62% (2023 est.)
`broadband_fixed_subscriptions_total_text`	broadband_fixed_subscriptions_total_text	string	0%	1	6,000 (2023 est.)
`broadband_fixed_subscriptions_total_numeric`	broadband_fixed_subscriptions_total_numeric	float	0%	1	6000.0
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text`	broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text	string	0%	1	3 (2023 est.)
`source_section`	source_section	string	0%	1	Communications
`source_profile_path`	source_profile_path	string	0%	1	africa/tp.json

STP OpenFactBook - Economy — 1 rows, 145 columns

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Field details — 151 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	5500.0
`gdp_official_exchange_rate_numeric`	Gdp total usd	float	SEL	0%	1	764.274
`population_below_poverty_line_numeric`	Poverty headcount percent	float	SEL	0%	1	55.5
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (145) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`economic_overview_text`	economic_overview_text	string	0%	1	lower middle-income Central African island economy;...
`economic_overview_numeric`	economic_overview_numeric	float	0%	1	90.0
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text`	Real gdp purchasing power parity 2024 (text)	string	0%	1	$1.291 billion (2024 est.)
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_numeric`	Real gdp purchasing power parity 2024 (numeric)	float	0%	1	1.291
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text`	Real gdp purchasing power parity 2023 (text)	string	0%	1	$1.279 billion (2023 est.)
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_numeric`	Real gdp purchasing power parity 2023 (numeric)	float	0%	1	1.279
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text`	Real gdp purchasing power parity 2022 (text)	string	0%	1	$1.275 billion (2022 est.)
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_numeric`	Real gdp purchasing power parity 2022 (numeric)	float	0%	1	1.275
`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	0.9% (2024 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric`	Real gdp growth rate 2024 (numeric)	float	0%	1	0.9
`real_gdp_growth_rate_real_gdp_growth_rate_2023_text`	Real gdp growth rate 2023 (text)	string	0%	1	0.4% (2023 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric`	Real gdp growth rate 2023 (numeric)	float	0%	1	0.4
`real_gdp_growth_rate_real_gdp_growth_rate_2022_text`	Real gdp growth rate 2022 (text)	string	0%	1	0.2% (2022 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric`	Real gdp growth rate 2022 (numeric)	float	0%	1	0.2
`real_gdp_growth_rate_note`	real_gdp_growth_rate_note	string	0%	1	note: annual GDP % growth based on constant local currency
`real_gdp_per_capita_real_gdp_per_capita_2024_text`	Real gdp per capita 2024 (text)	string	0%	1	$5,500 (2024 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_text`	Real gdp per capita 2023 (text)	string	0%	1	$5,500 (2023 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_numeric`	Real gdp per capita 2023 (numeric)	float	0%	1	5500.0
`real_gdp_per_capita_real_gdp_per_capita_2022_text`	Real gdp per capita 2022 (text)	string	0%	1	$5,600 (2022 est.)
`real_gdp_per_capita_real_gdp_per_capita_2022_numeric`	Real gdp per capita 2022 (numeric)	float	0%	1	5600.0
`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	$764.274 million (2024 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text`	Inflation rate consumer prices 2024 (text)	string	0%	1	14.4% (2024 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric`	Inflation rate consumer prices 2024 (numeric)	float	0%	1	14.4
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text`	Inflation rate consumer prices 2023 (text)	string	0%	1	21.3% (2023 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric`	Inflation rate consumer prices 2023 (numeric)	float	0%	1	21.3
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text`	Inflation rate consumer prices 2022 (text)	string	0%	1	18% (2022 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric`	Inflation rate consumer prices 2022 (numeric)	float	0%	1	18.0
`inflation_rate_consumer_prices_note`	inflation_rate_consumer_prices_note	string	0%	1	note: annual % change based on consumer prices
+115 more extension fields — download the CSV/Parquet to see them all.

STP OpenFactBook - Energy — 1 rows, 25 columns

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Field details — 25 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	78.0
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (21) — 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	78% (2022 est.)
`electricity_access_electrification_urban_areas_text`	electricity_access_electrification_urban_areas_text	string	0%	1	80%
`electricity_access_electrification_urban_areas_numeric`	electricity_access_electrification_urban_areas_numeric	float	0%	1	80.0
`electricity_access_electrification_rural_areas_text`	electricity_access_electrification_rural_areas_text	string	0%	1	73.7%
`electricity_access_electrification_rural_areas_numeric`	electricity_access_electrification_rural_areas_numeric	float	0%	1	73.7
`electricity_installed_generating_capacity_text`	electricity_installed_generating_capacity_text	string	0%	1	29,000 kW (2023 est.)
`electricity_installed_generating_capacity_numeric`	electricity_installed_generating_capacity_numeric	float	0%	1	29000.0
`electricity_consumption_text`	electricity_consumption_text	string	0%	1	47.05 million kWh (2023 est.)
`electricity_consumption_numeric`	electricity_consumption_numeric	float	0%	1	47.05
`electricity_transmission_distribution_losses_text`	electricity_transmission_distribution_losses_text	string	0%	1	40.95 million kWh (2023 est.)
`electricity_transmission_distribution_losses_numeric`	electricity_transmission_distribution_losses_numeric	float	0%	1	40.95
`electricity_generation_sources_fossil_fuels_text`	electricity_generation_sources_fossil_fuels_text	string	0%	1	93.2% of total installed capacity (2023 est.)
`electricity_generation_sources_fossil_fuels_numeric`	electricity_generation_sources_fossil_fuels_numeric	float	0%	1	93.2
`electricity_generation_sources_hydroelectricity_text`	electricity_generation_sources_hydroelectricity_text	string	0%	1	6.8% of total installed capacity (2023 est.)
`electricity_generation_sources_hydroelectricity_numeric`	electricity_generation_sources_hydroelectricity_numeric	float	0%	1	6.8
`petroleum_refined_petroleum_consumption_text`	petroleum_refined_petroleum_consumption_text	string	0%	1	1,000 bbl/day (2023 est.)
`petroleum_refined_petroleum_consumption_numeric`	petroleum_refined_petroleum_consumption_numeric	float	0%	1	1000.0
`energy_consumption_per_capita_total_energy_consumption_per_capita_2023_text`	energy_consumption_per_capita_total_energy_consumption_per_capita_2023_text	string	0%	1	8.875 million Btu/person (2023 est.)
`energy_consumption_per_capita_total_energy_consumption_per_capita_2023_numeric`	energy_consumption_per_capita_total_energy_consumption_per_capita_2023_numeric	float	0%	1	8.875
`source_section`	source_section	string	0%	1	Energy
`source_profile_path`	source_profile_path	string	0%	1	africa/tp.json

STP OpenFactBook - Environment — 1 rows, 41 columns

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Field details — 43 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	44.8
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	57.5
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	76.4
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	2.96
`waste_and_recycling_municipal_solid_waste_generated_annually_numeric`	Municipal waste kg per capita	float	SEL	0%	1	25600.0
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (35) — 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 and illegal logging; soil erosion and...
`international_environmental_agreements_party_to_text`	international_environmental_agreements_party_to_text	string	0%	1	Biodiversity, Climate Change, Climate Change-Kyoto...
`international_environmental_agreements_signed_but_not_ratified_text`	international_environmental_agreements_signed_but_not_ratified_text	string	0%	1	Comprehensive Nuclear Test Ban
`climate_text`	climate_text	string	0%	1	tropical; hot, humid; one rainy season (October to May)
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	44.8% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 4.2% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	4.2
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 39.6% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	39.6
`land_use_agricultural_land_permanent_pasture_text`	land_use_agricultural_land_permanent_pasture_text	string	0%	1	permanent pasture: 1% (2023 est.)
`land_use_agricultural_land_permanent_pasture_numeric`	land_use_agricultural_land_permanent_pasture_numeric	float	0%	1	1.0
`land_use_forest_text`	land_use_forest_text	string	0%	1	57.5% (2023 est.)
`land_use_other_text`	land_use_other_text	string	0%	1	0% (2023 est.)
`land_use_other_numeric`	land_use_other_numeric	float	0%	1	0.0
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	76.4% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	2.96% annual rate of change (2020-25 est.)
`carbon_dioxide_emissions_total_emissions_text`	carbon_dioxide_emissions_total_emissions_text	string	0%	1	146,000 metric tonnes of CO2 (2023 est.)
`carbon_dioxide_emissions_total_emissions_numeric`	carbon_dioxide_emissions_total_emissions_numeric	float	0%	1	146000.0
`carbon_dioxide_emissions_from_petroleum_and_other_liquids_text`	carbon_dioxide_emissions_from_petroleum_and_other_liquids_text	string	0%	1	146,000 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	146000.0
`particulate_matter_emissions_text`	particulate_matter_emissions_text	string	0%	1	29 micrograms per cubic meter (2019 est.)
`particulate_matter_emissions_numeric`	particulate_matter_emissions_numeric	float	0%	1	29.0
`waste_and_recycling_municipal_solid_waste_generated_annually_text`	waste_and_recycling_municipal_solid_waste_generated_annually_text	string	0%	1	25,600 tons (2024 est.)
`waste_and_recycling_percent_of_municipal_solid_waste_recycled_text`	waste_and_recycling_percent_of_municipal_solid_waste_recycled_text	string	0%	1	16.9% (2022 est.)
`waste_and_recycling_percent_of_municipal_solid_waste_recycled_numeric`	waste_and_recycling_percent_of_municipal_solid_waste_recycled_numeric	float	0%	1	16.9
`total_water_withdrawal_municipal_text`	total_water_withdrawal_municipal_text	string	0%	1	14.7 million cubic meters (2022 est.)
`total_water_withdrawal_municipal_numeric`	total_water_withdrawal_municipal_numeric	float	0%	1	14.7
`total_water_withdrawal_industrial_text`	total_water_withdrawal_industrial_text	string	0%	1	600,000 cubic meters (2022 est.)
`total_water_withdrawal_industrial_numeric`	total_water_withdrawal_industrial_numeric	float	0%	1	600000.0
`total_water_withdrawal_agricultural_text`	total_water_withdrawal_agricultural_text	string	0%	1	25.6 million cubic meters (2022 est.)
+5 more extension fields — download the CSV/Parquet to see them all.

STP OpenFactBook - Ethnic Groups — 1 rows, 8 columns

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`admin_level`	Admin level	string	SEL	0%	1	national

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

Field Name	Label	Type	Nulls	Unique	Samples
`nationality_noun_text`	nationality_noun_text	string	0%	1	Sao Tomean(s)
`nationality_adjective_text`	nationality_adjective_text	string	0%	1	Sao Tomean
`ethnic_groups_text`	ethnic_groups_text	string	0%	1	Mestico, Angolares (descendants of Angolan slaves),...
`source_section`	source_section	string	0%	1	People and Society:ethnic_groups
`source_profile_path`	source_profile_path	string	0%	1	africa/tp.json

STP OpenFactBook - Geography — 1 rows, 48 columns

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Field details — 49 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	964.0
`area_land_numeric`	Area land sqkm	float	SEL	0%	1	964.0
`area_water_numeric`	Area water sqkm	float	SEL	0%	1	0.0
`land_boundaries_total_numeric`	Land boundary km	float	SEL	0%	1	0.0
`coastline_numeric`	Coastline km	float	SEL	0%	1	209.0
`elevation_highest_point_numeric`	Elevation max m	float	SEL	0%	1	2024.0
`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	44.8
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	57.5
`irrigated_land_numeric`	Irrigated land sqkm	float	SEL	0%	1	100.0
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (36) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`location_text`	location_text	string	0%	1	Central Africa, islands in the Gulf of Guinea, just...
`geographic_coordinates_text`	geographic_coordinates_text	string	0%	1	1 00 N, 7 00 E
`geographic_coordinates_numeric`	geographic_coordinates_numeric	float	0%	1	1.0
`map_references_text`	map_references_text	string	0%	1	Africa
`area_total_text`	area_total_text	string	0%	1	964 sq km
`area_land_text`	area_land_text	string	0%	1	964 sq km
`area_water_text`	area_water_text	string	0%	1	0 sq km
`area_comparative_text`	area_comparative_text	string	0%	1	more than five times the size of Washington, D.C.
`land_boundaries_total_text`	land_boundaries_total_text	string	0%	1	0 km
`coastline_text`	coastline_text	string	0%	1	209 km
`maritime_claims_territorial_sea_text`	maritime_claims_territorial_sea_text	string	0%	1	12 nm
`maritime_claims_territorial_sea_numeric`	maritime_claims_territorial_sea_numeric	float	0%	1	12.0
`maritime_claims_exclusive_economic_zone_text`	maritime_claims_exclusive_economic_zone_text	string	0%	1	200 nm
`maritime_claims_exclusive_economic_zone_numeric`	maritime_claims_exclusive_economic_zone_numeric	float	0%	1	200.0
`maritime_claims_note`	maritime_claims_note	string	0%	1	note: measured from claimed archipelagic baselines
`climate_text`	climate_text	string	0%	1	tropical; hot, humid; one rainy season (October to May)
`terrain_text`	terrain_text	string	0%	1	volcanic, mountainous
`elevation_highest_point_text`	elevation_highest_point_text	string	0%	1	Pico de Sao Tome 2,024 m
`elevation_lowest_point_text`	elevation_lowest_point_text	string	0%	1	Atlantic Ocean 0 m
`natural_resources_text`	natural_resources_text	string	0%	1	fish, hydropower
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	44.8% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 4.2% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	4.2
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 39.6% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	39.6
`land_use_agricultural_land_permanent_pasture_text`	land_use_agricultural_land_permanent_pasture_text	string	0%	1	permanent pasture: 1% (2023 est.)
`land_use_agricultural_land_permanent_pasture_numeric`	land_use_agricultural_land_permanent_pasture_numeric	float	0%	1	1.0
`land_use_forest_text`	land_use_forest_text	string	0%	1	57.5% (2023 est.)
`land_use_other_text`	land_use_other_text	string	0%	1	0% (2023 est.)
`land_use_other_numeric`	land_use_other_numeric	float	0%	1	0.0
+6 more extension fields — download the CSV/Parquet to see them all.

STP OpenFactBook - Government — 1 rows, 71 columns

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Field details — 93 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	STP
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (91) — 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	Democratic Republic of Sao Tome and Principe
`country_name_conventional_short_form_text`	country_name_conventional_short_form_text	string	0%	1	Sao Tome and Principe
`country_name_local_long_form_text`	country_name_local_long_form_text	string	0%	1	Republica Democratica de Sao Tome e Principe
`country_name_local_short_form_text`	country_name_local_short_form_text	string	0%	1	Sao Tome e Principe
`country_name_etymology_text`	country_name_etymology_text	string	0%	1	Sao Tome was named after Saint THOMAS the Apostle by the...
`country_name_etymology_numeric`	country_name_etymology_numeric	float	0%	1	21.0
`government_type_text`	government_type_text	string	0%	1	semi-presidential republic
`capital_name_text`	capital_name_text	string	0%	1	Sao Tome
`capital_geographic_coordinates_text`	capital_geographic_coordinates_text	string	0%	1	0 20 N, 6 44 E
`capital_geographic_coordinates_numeric`	capital_geographic_coordinates_numeric	float	0%	1	0.0
`capital_time_difference_text`	capital_time_difference_text	string	0%	1	UTC 0 (5 hours ahead of Washington, DC, during Standard Time)
`capital_time_difference_numeric`	capital_time_difference_numeric	float	0%	1	0.0
`capital_etymology_text`	capital_etymology_text	string	0%	1	named after Saint THOMAS the Apostle by the Portuguese,...
`capital_etymology_numeric`	capital_etymology_numeric	float	0%	1	21.0
`administrative_divisions_text`	administrative_divisions_text	string	0%	1	6 districts (distritos, singular - distrito), 1...
`administrative_divisions_numeric`	administrative_divisions_numeric	float	0%	1	6.0
`legal_system_text`	legal_system_text	string	0%	1	mixed system of civil law based on the Portuguese model...
`constitution_history_text`	constitution_history_text	string	0%	1	approved 5 November 1975
`constitution_history_numeric`	constitution_history_numeric	float	0%	1	5.0
`constitution_amendment_process_text`	constitution_amendment_process_text	string	0%	1	proposed by the National Assembly; passage requires...
`international_law_organization_participation_text`	international_law_organization_participation_text	string	0%	1	has not submitted an ICJ jurisdiction declaration;...
`citizenship_citizenship_by_birth_text`	Citizenship by birth (text)	string	0%	1	no
`citizenship_citizenship_by_descent_only_text`	Citizenship by descent only (text)	string	0%	1	at least one parent must be a citizen of Sao Tome and Principe
`citizenship_dual_citizenship_recognized_text`	citizenship_dual_citizenship_recognized_text	string	0%	1	no
`citizenship_residency_requirement_for_naturalization_text`	citizenship_residency_requirement_for_naturalization_text	string	0%	1	5 years
`citizenship_residency_requirement_for_naturalization_numeric`	citizenship_residency_requirement_for_naturalization_numeric	float	0%	1	5.0
`suffrage_text`	suffrage_text	string	0%	1	18 years of age; universal
`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 Carlos Manuel VILA NOVA (since 2 October 2021)
`executive_branch_chief_of_state_numeric`	executive_branch_chief_of_state_numeric	float	0%	1	2.0
+61 more extension fields — download the CSV/Parquet to see them all.

STP OpenFactBook - Introduction — 1 rows, 6 columns

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`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	Portugal discovered and colonized the uninhabited Sao...
`background_numeric`	background_numeric	float	0%	1	15.0
`source_section`	source_section	string	0%	1	Introduction
`source_profile_path`	source_profile_path	string	0%	1	africa/tp.json

STP OpenFactBook - Languages — 1 rows, 6 columns

Loading data…

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`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
`languages_text`	languages_text	string	0%	1	Portuguese 98.4% (official), Forro 36.2%, Cabo Verdian...
`languages_numeric`	languages_numeric	float	0%	1	98.4
`source_section`	source_section	string	0%	1	People and Society:languages
`source_profile_path`	source_profile_path	string	0%	1	africa/tp.json

STP OpenFactBook - Military And Security — 1 rows, 11 columns

Loading data…

Field details — 15 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	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (12) — 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 Sao Tome and Principe (Forcas Armadas de...
`military_and_security_forces_numeric`	military_and_security_forces_numeric	float	0%	1	2025.0
`military_and_security_service_personnel_strengths_text`	military_and_security_service_personnel_strengths_text	string	0%	1	approximately 500 active Armed Forces (2023)
`military_and_security_service_personnel_strengths_numeric`	military_and_security_service_personnel_strengths_numeric	float	0%	1	500.0
`military_equipment_inventories_and_acquisitions_text`	military_equipment_inventories_and_acquisitions_text	string	0%	1	the FASTP is lightly armed and has a small inventory of...
`military_equipment_inventories_and_acquisitions_numeric`	military_equipment_inventories_and_acquisitions_numeric	float	0%	1	2023.0
`military_service_age_and_obligation_text`	military_service_age_and_obligation_text	string	0%	1	limited information; 18 is the minimum age for...
`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 FASTP is one of the smallest militaries in Africa...
`military_note_numeric`	military_note_numeric	float	0%	1	2024.0
`source_section`	source_section	string	0%	1	Military and Security
`source_profile_path`	source_profile_path	string	0%	1	africa/tp.json

STP OpenFactBook - People And Society — 1 rows, 140 columns

Loading data…

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

Standards-Aligned Fields (29)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`population_total_numeric`	Population count	float	SEL	0%	1	223561.0
`population_male_numeric`	Population male	float	SEL	0%	1	111553.0
`population_female_numeric`	Population female	float	SEL	0%	1	112008.0
`age_structure_0_14_years_numeric`	Population 0 14 percent	float	SEL	0%	1	36.4
`age_structure_15_64_years_numeric`	Population 15 64 percent	float	SEL	0%	1	60.3
`age_structure_65_years_and_over_numeric`	Population 65 plus percent	float	SEL	0%	1	3.2
`dependency_ratios_total_dependency_ratio_numeric`	Total dependency ratio	float	SEL	0%	1	65.8
`dependency_ratios_youth_dependency_ratio_numeric`	Youth dependency ratio	float	SEL	0%	1	60.4
`dependency_ratios_elderly_dependency_ratio_numeric`	Elderly dependency ratio	float	SEL	0%	1	5.4
`median_age_total_numeric`	Median age	float	SEL	0%	1	21.2
`population_growth_rate_numeric`	Population growth rate percent	float	SEL	0%	1	1.39
`birth_rate_numeric`	Birth rate per 1000	float	SEL	0%	1	25.87
`death_rate_numeric`	Death rate per 1000	float	SEL	0%	1	5.84
`net_migration_rate_numeric`	Net migration per 1000	float	SEL	0%	1	-6.15
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	76.4
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	2.96
`sex_ratio_at_birth_numeric`	Sex ratio at birth	float	SEL	0%	1	1.03
`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	75.0
`infant_mortality_rate_total_numeric`	Infant mortality per 1000	float	SEL	0%	1	41.7
`life_expectancy_at_birth_total_population_numeric`	Life expectancy	float	SEL	0%	1	67.7
`total_fertility_rate_numeric`	Fertility rate	float	SEL	0%	1	3.18
`gross_reproduction_rate_numeric`	Gross reproduction rate	float	SEL	0%	1	1.57
`physician_density_numeric`	Physicians per 1000	float	SEL	0%	1	0.46
`hospital_bed_density_numeric`	Hospital beds per 1000	float	SEL	0%	1	2.9
`literacy_total_population_numeric`	Literacy rate percent	float	SEL	0%	1	87.4
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`admin_level`	Admin level	string	SEL	0%	1	national

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

Field Name	Label	Type	Nulls	Unique	Samples
`population_total_text`	population_total_text	string	0%	1	223,561 (2024 est.)
`population_male_text`	population_male_text	string	0%	1	111,553
`population_female_text`	population_female_text	string	0%	1	112,008
`age_structure_0_14_years_text`	age_structure_0_14_years_text	string	0%	1	36.4% (male 41,337/female 40,106)
`age_structure_15_64_years_text`	age_structure_15_64_years_text	string	0%	1	60.3% (male 67,101/female 67,775)
`age_structure_65_years_and_over_text`	age_structure_65_years_and_over_text	string	0%	1	3.2% (2024 est.) (male 3,115/female 4,127)
`dependency_ratios_total_dependency_ratio_text`	dependency_ratios_total_dependency_ratio_text	string	0%	1	65.8 (2024 est.)
`dependency_ratios_youth_dependency_ratio_text`	dependency_ratios_youth_dependency_ratio_text	string	0%	1	60.4 (2024 est.)
`dependency_ratios_elderly_dependency_ratio_text`	dependency_ratios_elderly_dependency_ratio_text	string	0%	1	5.4 (2024 est.)
`dependency_ratios_potential_support_ratio_text`	dependency_ratios_potential_support_ratio_text	string	0%	1	18.6 (2024 est.)
`dependency_ratios_potential_support_ratio_numeric`	dependency_ratios_potential_support_ratio_numeric	float	0%	1	18.6
`median_age_total_text`	median_age_total_text	string	0%	1	21.2 years (2025 est.)
`median_age_male_text`	median_age_male_text	string	0%	1	20.4 years
`median_age_male_numeric`	median_age_male_numeric	float	0%	1	20.4
`median_age_female_text`	median_age_female_text	string	0%	1	21.2 years
`median_age_female_numeric`	median_age_female_numeric	float	0%	1	21.2
`population_growth_rate_text`	population_growth_rate_text	string	0%	1	1.39% (2025 est.)
`birth_rate_text`	birth_rate_text	string	0%	1	25.87 births/1,000 population (2025 est.)
`death_rate_text`	death_rate_text	string	0%	1	5.84 deaths/1,000 population (2025 est.)
`net_migration_rate_text`	net_migration_rate_text	string	0%	1	-6.15 migrant(s)/1,000 population (2025 est.)
`population_distribution_text`	population_distribution_text	string	0%	1	Sao Tome, the capital city, has roughly a quarter of the...
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	76.4% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	2.96% annual rate of change (2020-25 est.)
`major_urban_areas_population_text`	major_urban_areas_population_text	string	0%	1	80,000 SAO TOME (capital) (2018)
`major_urban_areas_population_numeric`	major_urban_areas_population_numeric	float	0%	1	80000.0
`sex_ratio_at_birth_text`	sex_ratio_at_birth_text	string	0%	1	1.03 male(s)/female
`sex_ratio_0_14_years_text`	sex_ratio_0_14_years_text	string	0%	1	1.03 male(s)/female
`sex_ratio_0_14_years_numeric`	sex_ratio_0_14_years_numeric	float	0%	1	1.03
`sex_ratio_15_64_years_text`	sex_ratio_15_64_years_text	string	0%	1	0.99 male(s)/female
`sex_ratio_15_64_years_numeric`	sex_ratio_15_64_years_numeric	float	0%	1	0.99
+93 more extension fields — download the CSV/Parquet to see them all.

STP OpenFactBook - Religions — 1 rows, 6 columns

Loading data…

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

Standards-Aligned Fields (4)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`admin_level`	Admin level	string	SEL	0%	1	national
`composition_religion_other_pct_synth`	other	numeric	CCL	0%	-	6.2

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	Catholic 55.7%, Adventist 4.1%, Assembly of God 3.4%,...
`religions_numeric`	religions_numeric	float	0%	1	55.7
`source_section`	source_section	string	0%	1	People and Society:religions
`source_profile_path`	source_profile_path	string	0%	1	africa/tp.json

Pending (16) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`composition_religion_catholic_pct_synth`	Catholic	numeric	0%	-	55.7
`composition_religion_adventist_pct_synth`	Adventist	numeric	0%	-	4.1
`composition_religion_assembly_of_god_pct_synth`	Assembly of God	numeric	0%	-	3.4
`composition_religion_new_apostolic_pct_synth`	New Apostolic	numeric	0%	-	2.9
`composition_religion_mana_pct_synth`	Mana	numeric	0%	-	2.3
`composition_religion_universal_kingdom_of_god_pct_synth`	Universal Kingdom of God	numeric	0%	-	2.0
`composition_religion_jehovah_s_witness_pct_synth`	Jehovah's Witness	numeric	0%	-	1.2
`composition_religion_none_pct_synth`	none	numeric	0%	-	21.2
`composition_religion_unspecified_pct_synth`	unspecified	numeric	0%	-	1.0
`composition_ethnicity_mestico_pct_synth`	Mestico	numeric	0%	-	-
`composition_ethnicity_angolares_pct_synth`	Angolares	numeric	0%	-	-
`composition_ethnicity_forros_pct_synth`	Forros	numeric	0%	-	-
`composition_ethnicity_servicais_pct_synth`	Servicais	numeric	0%	-	-
`composition_ethnicity_tongas_pct_synth`	Tongas	numeric	0%	-	-
`composition_ethnicity_europeans_pct_synth`	Europeans	numeric	0%	-	-
`composition_ethnicity_asians_pct_synth`	Asians	numeric	0%	-	-

STP OpenFactBook - Transportation — 1 rows, 25 columns

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Field details — 26 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	S9
`airports_numeric`	Airports count	float	SEL	0%	1	2.0
`country_code`	Country code	string	SEL	0%	1	STP
`country_name`	Country name	string	SEL	0%	1	Sao Tome and Principe
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (21) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`civil_aircraft_registration_country_code_prefix_numeric`	civil_aircraft_registration_country_code_prefix_numeric	float	0%	1	9.0
`airports_text`	airports_text	string	0%	1	2 (2025)
`merchant_marine_total_text`	merchant_marine_total_text	string	0%	1	25 (2023)
`merchant_marine_total_numeric`	merchant_marine_total_numeric	float	0%	1	25.0
`merchant_marine_by_type_text`	merchant_marine_by_type_text	string	0%	1	general cargo 15, oil tanker 4, other 6
`merchant_marine_by_type_numeric`	merchant_marine_by_type_numeric	float	0%	1	15.0
`ports_total_ports_text`	ports_total_ports_text	string	0%	1	2 (2024)
`ports_total_ports_numeric`	ports_total_ports_numeric	float	0%	1	2.0
`ports_large_text`	ports_large_text	float	0%	1	0
`ports_large_numeric`	ports_large_numeric	float	0%	1	0.0
`ports_medium_text`	ports_medium_text	float	0%	1	0
`ports_medium_numeric`	ports_medium_numeric	float	0%	1	0.0
`ports_small_text`	ports_small_text	float	0%	1	0
`ports_small_numeric`	ports_small_numeric	float	0%	1	0.0
`ports_very_small_text`	ports_very_small_text	float	0%	1	2
`ports_very_small_numeric`	ports_very_small_numeric	float	0%	1	2.0
`ports_ports_with_oil_terminals_text`	Ports with oil terminals (text)	float	0%	1	0
`ports_ports_with_oil_terminals_numeric`	Ports with oil terminals (numeric)	float	0%	1	0.0
`ports_key_ports_text`	ports_key_ports_text	string	0%	1	Santo Antonio, Sao Tome
`source_section`	source_section	string	0%	1	Transportation
`source_profile_path`	source_profile_path	string	0%	1	africa/tp.json

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

10 rows · 3 table(s) · 2022 HDX COD — Population Statistics (OCHA/UNFPA) 0 1 2 3 15 SEL ▶

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

0 Admin 0 — 1 table(s)

STP Cod Ps - Stp Codps (admin_0) — 1 rows, 53 columns

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Field details — 53 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`pcode`	Admin code	string	SEL	0%	1	ST
`region_name`	Region name	string	SEL	0%	1	Sao Tome and Principe
`F_TL`	Female population	integer	SEL	0%	1	110854
`M_TL`	Male population	integer	SEL	0%	1	108723
`T_TL`	Total population	integer	SEL	0%	1	219577

Pending (48) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`admin_level`	Admin level	string	0%	1	admin_0
`year`	Reference year	integer	0%	1	2022
`year`	year	integer	0%	1	2022
`F_00_04`	Female population age 0-4	integer	0%	1	16778
`F_05_09`	Female population age 5-9	integer	0%	1	15368
`F_10_14`	Female population age 10-14	integer	0%	1	13594
`F_15_19`	Female population age 15-19	integer	0%	1	12123
`F_20_24`	Female population age 20-24	integer	0%	1	10398
`F_25_29`	Female population age 25-29	integer	0%	1	8746
`F_30_34`	Female population age 30-34	integer	0%	1	7326
`F_35_39`	Female population age 35-39	integer	0%	1	5887
`F_40_44`	Female population age 40-44	integer	0%	1	4779
`F_45_49`	Female population age 45-49	integer	0%	1	3821
`F_50_54`	Female population age 50-54	integer	0%	1	3134
`F_55_59`	Female population age 55-59	integer	0%	1	2338
`F_60_64`	Female population age 60-64	integer	0%	1	1850
`F_65_69`	Female population age 65-69	integer	0%	1	1401
`F_70Plus`	F_70Plus	integer	0%	1	3311
`M_00_04`	Male population age 0-4	integer	0%	1	16911
`M_05_09`	Male population age 5-9	integer	0%	1	15471
`M_10_14`	Male population age 10-14	integer	0%	1	13765
`M_15_19`	Male population age 15-19	integer	0%	1	12345
`M_20_24`	Male population age 20-24	integer	0%	1	10299
`M_25_29`	Male population age 25-29	integer	0%	1	8606
`M_30_34`	Male population age 30-34	integer	0%	1	7064
`M_35_39`	Male population age 35-39	integer	0%	1	5615
`M_40_44`	Male population age 40-44	integer	0%	1	4574
`M_45_49`	Male population age 45-49	integer	0%	1	3497
`M_50_54`	Male population age 50-54	integer	0%	1	2888
`M_55_59`	Male population age 55-59	integer	0%	1	2071
+18 more pending fields — download the CSV/Parquet to see them all.

1 Admin 1 — 1 table(s)

STP Cod Ps - Stp Codps (admin_1) — 2 rows, 53 columns

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Field details — 53 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`pcode`	Admin code	string	SEL	0%	2	ST01, ST02
`region_name`	Region name	string	SEL	0%	2	Príncipe, São Tomé
`F_TL`	Female population	integer	SEL	0%	2	4467, 106387
`M_TL`	Male population	integer	SEL	0%	2	4684, 104039
`T_TL`	Total population	integer	SEL	0%	2	9151, 210426

Pending (48) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`admin_level`	Admin level	string	0%	1	admin_1, admin_1
`year`	Reference year	integer	0%	1	2022, 2022
`year`	year	integer	0%	1	2022, 2022
`F_00_04`	Female population age 0-4	integer	0%	2	695, 16083
`F_05_09`	Female population age 5-9	integer	0%	2	677, 14691
`F_10_14`	Female population age 10-14	integer	0%	2	581, 13013
`F_15_19`	Female population age 15-19	integer	0%	2	517, 11606
`F_20_24`	Female population age 20-24	integer	0%	2	366, 10032
`F_25_29`	Female population age 25-29	integer	0%	2	320, 8426
`F_30_34`	Female population age 30-34	integer	0%	2	282, 7044
`F_35_39`	Female population age 35-39	integer	0%	2	241, 5646
`F_40_44`	Female population age 40-44	integer	0%	2	177, 4602
`F_45_49`	Female population age 45-49	integer	0%	2	169, 3652
`F_50_54`	Female population age 50-54	integer	0%	2	105, 3029
`F_55_59`	Female population age 55-59	integer	0%	2	97, 2241
`F_60_64`	Female population age 60-64	integer	0%	2	60, 1790
`F_65_69`	Female population age 65-69	integer	0%	2	60, 1341
`F_70Plus`	F_70Plus	integer	0%	2	120, 3191
`M_00_04`	Male population age 0-4	integer	0%	2	727, 16184
`M_05_09`	Male population age 5-9	integer	0%	2	643, 14828
`M_10_14`	Male population age 10-14	integer	0%	2	597, 13168
`M_15_19`	Male population age 15-19	integer	0%	2	479, 11866
`M_20_24`	Male population age 20-24	integer	0%	2	381, 9918
`M_25_29`	Male population age 25-29	integer	0%	2	368, 8238
`M_30_34`	Male population age 30-34	integer	0%	2	331, 6733
`M_35_39`	Male population age 35-39	integer	0%	2	290, 5325
`M_40_44`	Male population age 40-44	integer	0%	2	201, 4373
`M_45_49`	Male population age 45-49	integer	0%	2	168, 3329
`M_50_54`	Male population age 50-54	integer	0%	2	121, 2767
`M_55_59`	Male population age 55-59	integer	0%	2	88, 1983
+18 more pending fields — download the CSV/Parquet to see them all.

2 Admin 2 — 1 table(s)

STP Cod Ps - Stp Codps (admin_2) — 7 rows, 53 columns

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Field details — 53 fields (type, nulls, unique, samples)

Standards-Aligned Fields (5)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`pcode`	Admin code	string	SEL	0%	7	ST0101, ST0201, ST0202, ST0203, ST0204
`region_name`	Region name	string	SEL	0%	7	Região Autónoma do Príncipe, Agua Grande, Cantagalo, Caue, Lemba
`F_TL`	Female population	integer	SEL	0%	7	4467, 43738, 10394, 3776, 8568
`M_TL`	Male population	integer	SEL	0%	7	4684, 40560, 10663, 4070, 9081
`T_TL`	Total population	integer	SEL	0%	7	9151, 84298, 21057, 7846, 17649

Pending (48) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`admin_level`	Admin level	string	0%	1	admin_2, admin_2, admin_2, admin_2, admin_2
`year`	Reference year	integer	0%	1	2022, 2022, 2022, 2022, 2022
`year`	year	integer	0%	1	2022, 2022, 2022, 2022, 2022
`F_00_04`	Female population age 0-4	integer	0%	7	695, 6162, 1677, 621, 1491
`F_05_09`	Female population age 5-9	integer	0%	7	677, 5415, 1607, 604, 1311
`F_10_14`	Female population age 10-14	integer	0%	7	581, 5161, 1326, 511, 1088
`F_15_19`	Female population age 15-19	integer	0%	7	517, 4927, 1109, 397, 905
`F_20_24`	Female population age 20-24	integer	0%	7	366, 4414, 880, 299, 725
`F_25_29`	Female population age 25-29	integer	0%	7	320, 3769, 750, 237, 629
`F_30_34`	Female population age 30-34	integer	0%	7	282, 3068, 641, 238, 529
`F_35_39`	Female population age 35-39	integer	0%	7	241, 2436, 517, 198, 439
`F_40_44`	Female population age 40-44	integer	0%	7	177, 1983, 456, 157, 366
`F_45_49`	Female population age 45-49	integer	0%	7	169, 1589, 345, 131, 270
`F_50_54`	Female population age 50-54	integer	0%	7	105, 1341, 276, 104, 212
`F_55_59`	Female population age 55-59	integer	0%	7	97, 981, 201, 69, 157
`F_60_64`	Female population age 60-64	integer	0%	7	60, 714, 167, 78, 131
`F_65_69`	Female population age 65-69	integer	0%	7	60, 516, 133, 40, 113
`F_70Plus`	F_70Plus	integer	0%	7	120, 1262, 309, 92, 202
`M_00_04`	Male population age 0-4	integer	0%	7	727, 6184, 1716, 634, 1509
`M_05_09`	Male population age 5-9	integer	0%	7	643, 5543, 1508, 586, 1369
`M_10_14`	Male population age 10-14	integer	0%	7	597, 4895, 1410, 563, 1189
`M_15_19`	Male population age 15-19	integer	0%	7	479, 4585, 1230, 469, 992
`M_20_24`	Male population age 20-24	integer	0%	7	381, 4021, 955, 320, 821
`M_25_29`	Male population age 25-29	integer	0%	7	368, 3373, 789, 291, 681
`M_30_34`	Male population age 30-34	integer	0%	7	331, 2777, 685, 239, 571
`M_35_39`	Male population age 35-39	integer	0%	7	290, 2122, 529, 201, 505
`M_40_44`	Male population age 40-44	integer	0%	7	201, 1789, 476, 181, 352
`M_45_49`	Male population age 45-49	integer	0%	7	168, 1402, 318, 133, 276
`M_50_54`	Male population age 50-54	integer	0%	7	121, 1159, 248, 122, 228
`M_55_59`	Male population age 55-59	integer	0%	7	88, 802, 219, 87, 148
+18 more pending fields — download the CSV/Parquet to see them all.

STP USAID DHS Program STP-DHS Health Surveys

8 rows · 2 table(s) · 2008 USAID DHS Program 0 1 2 3 7 SEL 3 CCL 10 ext ▶

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

1 Admin 1 — 2 table(s)

STP DHS - Ethnicity Indicators — 4 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%	4	89.3, 76.3, 73.9, 90.7
`men_who_are_literate`	Men who are literate	float	CCL	0%	4	96.3, 89.0, 91.9, 94.4

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	Sao Tome and Principe, Sao Tome and Principe, Sao Tome...
`survey_year`	survey_year	integer	0%	1	2008, 2008, 2008, 2008
`region`	region	string	0%	4	Região Centro, Região Norte, Região Sul, Região do Principe
`survey_id`	survey_id	string	0%	1	ST2008DHS, ST2008DHS, ST2008DHS, ST2008DHS
`survey_type`	survey_type	string	0%	1	DHS, DHS, DHS, DHS

STP DHS - Health Indicators — 4 rows, 12 columns

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

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	100%	-	-
`contraception_modern_pct`	Contraception modern percent	float	SEL	0%	4	26.1, 29.9, 26.7, 37.7
`infant_mortality_per_1000`	Infant mortality per 1000	float	SEL	0%	4	47.0, 61.0, 31.0, 16.0
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	0%	4	71.0, 85.0, 61.0, 57.0
`vaccination_rate_pct`	Vaccination rate percent	float	SEL	0%	4	74.8, 71.6, 85.5, 96.4
`children_underweight`	Children underweight	float	CCL	0%	4	12.6, 12.3, 16.3, 13.1
`hiv_prevalence_pct`	Hiv prevalence percent	float	SEL	0%	4	1.4, 2.0, 1.0, 2.2

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	Sao Tome and Principe, Sao Tome and Principe, Sao Tome...
`survey_year`	survey_year	integer	0%	1	2008, 2008, 2008, 2008
`region`	region	string	0%	4	Região Centro, Região Norte, Região Sul, Região do Principe
`survey_id`	survey_id	string	0%	1	ST2008DHS, ST2008DHS, ST2008DHS, ST2008DHS
`survey_type`	survey_type	string	0%	1	DHS, DHS, DHS, DHS

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

5 rows · 2 table(s) · 2026 NGA GEOnet Names Server (GNS) 0 1 2 3 4 SEL 12 CCL 18 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)

STP Nga Gns - Language — 4 rows, 9 columns

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

Standards-Aligned Fields (9)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	country_code	string	SEL	0%	1	STP, STP, STP, STP
`gns_language_code`	gns_language_code	string	CCL	0%	4	por, eng, fra, spa
`gns_language_name`	gns_language_name	string	CCL	0%	4	Portuguese, English, French, Spanish
`gns_toponym_count`	gns_toponym_count	integer	CCL	0%	3	1906, 10, 2, 2
`gns_toponym_share_pct`	gns_toponym_share_pct	float	CCL	0%	3	99.2708, 0.5208, 0.1042, 0.1042
`gns_non_roman_toponym_count`	gns_non_roman_toponym_count	integer	CCL	0%	1	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

STP Nga Gns - Summary — 1 rows, 25 columns

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Field details — 25 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	STP
`admin_level`	admin_level	integer	SEL	0%	1	0
`gns_country_name`	gns_country_name	string	SEL	0%	1	Sao Tome and Principe
`gns_language_count`	gns_language_count	integer	CCL	0%	1	4
`gns_script_count`	gns_script_count	integer	CCL	0%	1	0
`gns_endonym_share_pct`	gns_endonym_share_pct	float	CCL	0%	1	99.897
`gns_non_roman_name_count`	gns_non_roman_name_count	integer	CCL	0%	1	0

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

Field Name	Label	Type	Nulls	Unique	Samples
`gns_name_count`	gns_name_count	integer	0%	1	1941
`gns_feature_count`	gns_feature_count	integer	0%	1	1285
`gns_endonym_count`	gns_endonym_count	integer	0%	1	1939
`gns_exonym_count`	gns_exonym_count	integer	0%	1	2
`gns_source_build_date`	gns_source_build_date	string	0%	1	Wed, 05 Aug 2026
`gns_source_change_date`	gns_source_change_date	string	0%	1	2026-08-05
`gns_name_count_populated_places`	gns_name_count_populated_places	integer	0%	1	736
`gns_feature_count_populated_places`	gns_feature_count_populated_places	integer	0%	1	550
`gns_name_count_hypsographic`	gns_name_count_hypsographic	integer	0%	1	717
`gns_feature_count_hypsographic`	gns_feature_count_hypsographic	integer	0%	1	397
`gns_name_count_hydrographic`	gns_name_count_hydrographic	integer	0%	1	395
`gns_feature_count_hydrographic`	gns_feature_count_hydrographic	integer	0%	1	281
`gns_name_count_administrative_regions`	gns_name_count_administrative_regions	integer	0%	1	24
`gns_feature_count_administrative_regions`	gns_feature_count_administrative_regions	integer	0%	1	9
`gns_name_count_spot_features`	gns_name_count_spot_features	integer	0%	1	51
`gns_feature_count_spot_features`	gns_feature_count_spot_features	integer	0%	1	32
`gns_name_count_areas_localities`	gns_name_count_areas_localities	integer	0%	1	18
`gns_feature_count_areas_localities`	gns_feature_count_areas_localities	integer	0%	1	16

STP Glottolog Language Catalog STP-GLOTTOLOG Language

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

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0 Admin 0 — 1 table(s)

STP Glottolog - Languages — 4 rows, 16 columns

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

Standards-Aligned Fields (13)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`glottocode`	Glottocode	string	CCL	0%	4	ango1258, prin1242, saot1239, saot1241
`name`	Name	string	CCL	0%	4	Angolar, Principense, Sãotomense, Sao Tome and Principe...
`iso639_3`	Iso639 3	string	CCL	25%	3	aoa, pre, cri
`level`	Level	string	CCL	0%	1	language, language, language, language
`family_name`	Family name	string	CCL	100%	-	-
`family_glottocode`	Family glottocode	string	CCL	0%	2	indo1319, indo1319, indo1319, sign1238
`parent_name`	Parent name	string	CCL	100%	-	-
`parent_glottocode`	Parent glottocode	string	CCL	0%	3	saot1242, lowe1440, saot1242, deaf1237
`endangerment_status`	Endangerment status	string	CCL	100%	-	-
`country_codes`	Country codes	string	SEL+	0%	1	['ST'], ['ST'], ['ST'], ['ST']
`child_family_count`	Child family count	integer	CCL	0%	1	0, 0, 0, 0
`child_language_count`	Child language count	integer	CCL	0%	1	0, 0, 0, 0
`child_dialect_count`	Child dialect count	integer	CCL	0%	1	0, 0, 0, 0

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

Field Name	Label	Type	Nulls	Unique	Samples
`latitude`	latitude	float	0%	4	0.11438, 1.614, 0.28332, 0.320259
`longitude`	longitude	float	0%	4	6.59486, 7.392, 6.61935, 6.722558
`classification`	classification	string	0%	1	[], [], [], []

STP LandScan Global (ORNL) STP-LANDSCAN Modeled Population

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

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

0 Admin 0 — 1 table(s)

STP 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	STP
`admin_level`	Admin level	string	SEL	0%	1	admin_0
`admin_name`	Admin name	string	SEL	0%	1	Sao Tome and Principe
`admin_code`	Admin code	string	SEL	0%	1	85558007B40794750917517
`area_sqkm`	Area sqkm	float	SEL	0%	1	990.505
`pop_2024`	Population count	integer	SEL	0%	1	206906
`pop_density_2024`	Population density	float	SEL	0%	1	208.89

1 Admin 1 — 1 table(s)

STP LandScan - Population Admin1 (admin_1) — 2 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	STP, STP
`admin_level`	Admin level	string	SEL	0%	1	admin_1, admin_1
`admin_name`	Admin name	string	SEL	0%	2	São Tomé Province, Príncipe Province
`admin_code`	Admin code	string	SEL	0%	2	19237168B40253326356618, 19237168B82261817076051
`area_sqkm`	Area sqkm	float	SEL	0%	2	851.6761, 138.7976
`pop_2024`	Population count	integer	SEL	0%	2	198176, 8730
`pop_density_2024`	Population density	float	SEL	0%	2	232.69, 62.9

Locality Locality — 1 table(s)

STP LandScan - Cities (locality) — 1 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	STP
`admin_level`	Admin level	string	SEL	0%	1	locality
`admin_name`	Admin name	string	SEL	0%	1	São Tomé
`admin_code`	Admin code	integer	SEL	0%	1	71
`area_sqkm`	Area sqkm	float	SEL	0%	1	34.7655
`pop_2024`	Population count	integer	SEL	0%	1	89050
`pop_density_2024`	Population density	float	SEL	0%	1	2561.45

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%	1	154878
`landscan_vs_ghs_ratio`	landscan_vs_ghs_ratio	float	0%	1	0.575

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

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

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

Locality Locality — 1 table(s)

STP GHS-UCDB - Cities (locality) — 1 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%	1	São Tomé
`country_code`	Country code	string	SEL	0%	1	STP
`population`	Population count	integer	SEL	0%	1	154878

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

Field Name	Label	Type	Nulls	Unique	Samples
`city_id`	city_id	integer	0%	1	71
`name_alternates`	name_alternates	string	100%	-	-
`country_name`	country_name	string	0%	1	São Tomé and Príncipe
`population_year`	population_year	integer	0%	1	2025
`latitude`	latitude	string	100%	-	-
`longitude`	longitude	string	100%	-	-
`region`	region	string	100%	-	-

STP Global Organized Crime Index STP-OCINDEX Crime Index

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

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

0 Admin 0 — 1 table(s)

STP Organized Crime Scores 2025 — 1 rows, 35 columns

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Field details — 168 fields (type, nulls, unique, samples)

Standards-Aligned Fields (13)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`oc_anti_money_laundering`	oc_anti_money_laundering	numeric	CCL	0%	1	-
`oc_arms_trafficking`	oc_arms_trafficking	numeric	CCL	0%	1	-
`oc_criminal_actors`	oc_criminal_actors	numeric	CCL	0%	1	-
`oc_criminal_markets`	oc_criminal_markets	numeric	CCL	0%	1	-
`oc_criminality`	oc_criminality	numeric	CCL	0%	1	-
`oc_cyber_dependent_crimes`	oc_cyber_dependent_crimes	numeric	CCL	0%	1	-
`oc_financial_crimes`	oc_financial_crimes	numeric	CCL	0%	1	-
`oc_human_smuggling`	oc_human_smuggling	numeric	CCL	0%	1	-
`oc_human_trafficking`	oc_human_trafficking	numeric	CCL	0%	1	-
`oc_judicial_system_and_detention`	oc_judicial_system_and_detention	numeric	CCL	0%	1	-
`oc_law_enforcement`	oc_law_enforcement	numeric	CCL	0%	1	-
`oc_political_leadership_and_governance`	oc_political_leadership_and_governance	numeric	CCL	0%	1	-
`oc_resilience`	oc_resilience	numeric	CCL	0%	1	-

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

Field Name	Label	Type	Nulls	Unique	Samples
`oc_cannabis_trade`	oc_cannabis_trade	numeric	0%	1	-
`oc_cocaine_trade`	oc_cocaine_trade	numeric	0%	1	-
`oc_criminal_networks`	oc_criminal_networks	numeric	0%	1	-
`oc_economic_regulatory_capacity`	oc_economic_regulatory_capacity	numeric	0%	1	-
`oc_extortion_and_protection_racketeering`	oc_extortion_and_protection_racketeering	numeric	0%	1	-
`oc_fauna_crimes`	oc_fauna_crimes	numeric	0%	1	-
`oc_flora_crimes`	oc_flora_crimes	numeric	0%	1	-
`oc_foreign_actors`	oc_foreign_actors	numeric	0%	1	-
`oc_government_transparency_and_accountability`	oc_government_transparency_and_accountability	numeric	0%	1	-
`oc_heroin_trade`	oc_heroin_trade	numeric	0%	1	-
`oc_illicit_trade_in_excisable_goods`	oc_illicit_trade_in_excisable_goods	numeric	0%	1	-
`oc_international_cooperation`	oc_international_cooperation	numeric	0%	1	-
`oc_mafia_style_groups`	oc_mafia_style_groups	numeric	0%	1	-
`oc_national_policies_and_laws`	oc_national_policies_and_laws	numeric	0%	1	-
`oc_non_renewable_resource_crimes`	oc_non_renewable_resource_crimes	numeric	0%	1	-
`oc_non_state_actors`	oc_non_state_actors	numeric	0%	1	-
`oc_prevention`	oc_prevention	numeric	0%	1	-
`oc_private_sector_actors`	oc_private_sector_actors	numeric	0%	1	-
`oc_state_embedded_actors`	oc_state_embedded_actors	numeric	0%	1	-
`oc_synthetic_drug_trade`	oc_synthetic_drug_trade	numeric	0%	1	-
`oc_territorial_integrity`	oc_territorial_integrity	numeric	0%	1	-
`oc_trade_in_counterfeit_goods`	oc_trade_in_counterfeit_goods	numeric	0%	1	-

Pending (133) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`iso3`	iso3	string	0%	1	STP
`source`	source	string	0%	1	Global Organized Crime Index
`source_url`	source_url	string	0%	1	https://ocindex.net/
`year`	year	integer	0%	1	2025
`license`	license	string	0%	1	Creative Commons (GI-TOC / ENACT)
`oc_anti_money_laundering_rank`	oc_anti_money_laundering_rank	integer	0%	1	143
`oc_anti_money_laundering_2023`	oc_anti_money_laundering_2023	integer	0%	1	3
`oc_anti_money_laundering_2021`	oc_anti_money_laundering_2021	integer	0%	1	3
`oc_anti_money_laundering_2019`	oc_anti_money_laundering_2019	integer	0%	1	3
`oc_arms_trafficking_rank`	oc_arms_trafficking_rank	integer	0%	1	183
`oc_arms_trafficking_2023`	oc_arms_trafficking_2023	float	0%	1	1.5
`oc_arms_trafficking_2021`	oc_arms_trafficking_2021	integer	0%	1	2
`oc_arms_trafficking_2019`	oc_arms_trafficking_2019	integer	0%	1	3
`oc_cannabis_trade_rank`	oc_cannabis_trade_rank	integer	0%	1	173
`oc_cannabis_trade_2023`	oc_cannabis_trade_2023	float	0%	1	2.5
`oc_cannabis_trade_2021`	oc_cannabis_trade_2021	float	0%	1	2.5
`oc_cannabis_trade_2019`	oc_cannabis_trade_2019	integer	0%	1	3
`oc_cocaine_trade_rank`	oc_cocaine_trade_rank	integer	0%	1	151
`oc_cocaine_trade_2023`	oc_cocaine_trade_2023	integer	0%	1	2
`oc_cocaine_trade_2021`	oc_cocaine_trade_2021	integer	0%	1	2
`oc_cocaine_trade_2019`	oc_cocaine_trade_2019	float	0%	1	1.5
`oc_criminal_actors_rank`	oc_criminal_actors_rank	integer	0%	1	192
`oc_criminal_actors_2023`	oc_criminal_actors_2023	float	0%	1	1.7
`oc_criminal_actors_2021`	oc_criminal_actors_2021	float	0%	1	1.75
`oc_criminal_actors_2019`	oc_criminal_actors_2019	float	0%	1	1.75
`oc_criminal_markets_rank`	oc_criminal_markets_rank	integer	0%	1	190
`oc_criminal_markets_2023`	oc_criminal_markets_2023	float	0%	1	1.7
`oc_criminal_markets_2021`	oc_criminal_markets_2021	float	0%	1	1.8
`oc_criminal_markets_2019`	oc_criminal_markets_2019	integer	0%	1	2
`oc_criminal_networks_rank`	oc_criminal_networks_rank	integer	0%	1	189
+103 more pending fields — download the CSV/Parquet to see them all.

HERA · Human Entity Reference Atlas by Masego Inc

Sao Tome and Principe

Build a download

Language	Place names	Share	Script
Portuguese (por)	1,906	99.3%	—
English (eng)	10	0.5%	—
French (fra)	2	0.1%	—
Spanish (spa)	2	0.1%	—

Source	Type	Access
HDX COD — Population Statistics (OCHA/UNFPA)	international_organization	bulk_download
Global Data Lab	academic	api
GI-TOC / ENACT (Global Initiative Against Transnational Organized Crime · ENACT)	academic	bulk_download
NGA GEOnet Names Server (GNS)	official_government	bulk_download
UNHCR Refugee Data Finder (UN High Commissioner for Refugees)	international_organization	api
USAID DHS Program (US Agency for International Development · Demographic and Health Surveys)	international_organization	api
Glottolog Language Catalog	academic	bulk_download
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