Singapore

SGP Department of Statistics Singapore (SingStat) SGP-SINGSTAT Census

228 rows · 3 tables · 2020 Department of Statistics Singapore (SingStat) 0 1 2 3 9 SEL 6 ext ▶

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0 Admin 0 — 1 table(s)

SGP Singstat - SGP 2020 Census (admin_0) — 1 rows, 5 columns

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`admin_code`	Admin code	string	SEL	0%	1	SGP
`admin_name`	Admin name	string	SEL	0%	1	Singapore
`population_count`	Population count	integer	SEL	0%	1	3771721

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

Field Name	Label	Type	Nulls	Unique	Samples
`admin_level`	admin_level	string	0%	1	admin_0
`year`	year	integer	0%	1	2020

1 Admin 1 — 1 table(s)

SGP Singstat - SGP 2020 Census (admin_1) — 36 rows, 5 columns

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`admin_code`	Admin code	string	SEL	0%	36	ang_mo_kio, bedok, bishan, bukit_batok, bukit_merah
`admin_name`	Admin name	string	SEL	0%	36	Ang Mo Kio, Bedok, Bishan, Bukit Batok, Bukit Merah
`population_count`	Population count	integer	SEL	0%	36	179297, 294519, 91298, 144198, 157122

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

Field Name	Label	Type	Nulls	Unique	Samples
`admin_level`	admin_level	string	0%	1	admin_1, admin_1, admin_1, admin_1, admin_1
`year`	year	integer	0%	1	2020, 2020, 2020, 2020, 2020

2 Admin 2 — 1 table(s)

SGP Singstat - SGP 2020 Census (admin_2) — 191 rows, 5 columns

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`admin_code`	Admin code	string	SEL	0%	97	cheng_san, chong_boon, kebun_bahru, sembawang_hills, shangri_la
`admin_name`	Admin name	string	SEL	0%	97	Cheng San, Chong Boon, Kebun Bahru, Sembawang Hills, Shangri-La
`population_count`	Population count	integer	SEL	0%	100	30503, 29903, 25854, 6851, 21071

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

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`	year	integer	0%	1	2020, 2020, 2020, 2020, 2020

SGP Singapore - Economic, Social, Environmental, Healt SGP-HDX-Singapore_-_Economic,_Social,_Envir Indicators

73,449 rows · 1 table · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

SGP Singapore - Economic, Social, Environmental, Healt — 73,449 rows, 1,966 columns

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Field details — 1967 fields (type, nulls, unique, samples)

Extension Fields (1967) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	SGP
`Fertilizer_consumption_kilograms_per_hectare_of_arable_land`	Fertilizer_consumption_kilograms_per_hectare_of_arable_land	float	0%	1	137.5
`Agricultural_land_sq._km`	Agricultural_land_sq._km	float	0%	1	6.6
`Agricultural_land_pct_of_land_area`	Agricultural_land_pct_of_land_area	float	0%	1	0.919220055710306
`Arable_land_hectares`	Arable_land_hectares	float	0%	1	560.0
`Arable_land_hectares_per_person`	Arable_land_hectares_per_person	float	0%	1	9.46321917085977e-05
`Arable_land_pct_of_land_area`	Arable_land_pct_of_land_area	float	0%	1	0.779944289693593
`Permanent_cropland_pct_of_land_area`	Permanent_cropland_pct_of_land_area	float	0%	1	0.139275766016713
`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	43.8150493208
`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	6.59620407187911
`Forest_area_sq._km`	Forest_area_sq._km	float	0%	1	150.3
`Forest_area_pct_of_land_area`	Forest_area_pct_of_land_area	float	0%	1	20.933147632312
`Average_precipitation_in_depth_mm_per_year`	Average_precipitation_in_depth_mm_per_year	float	0%	1	2497.0
`Land_area_sq._km`	Land_area_sq._km	float	0%	1	718.0
`Rural_land_area_sq._km`	Rural_land_area_sq._km	float	0%	1	210.1625760848
`Crop_production_index_2014-2016_=_100`	Crop_production_index_2014-2016_=_100	float	0%	1	90.86
`Food_production_index_2014-2016_=_100`	Food_production_index_2014-2016_=_100	float	0%	1	131.01
`Livestock_production_index_2014-2016_=_100`	Livestock_production_index_2014-2016_=_100	float	0%	1	139.04
`Surface_area_sq._km`	Surface_area_sq._km	float	0%	1	728.0
`Access_to_electricity_rural_pct_of_rural_population`	Access_to_electricity_rural_pct_of_rural_population	float	0%	1	100.0
`Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_`	Rural_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_	float	0%	1	0.00671097395477561
`Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal`	Annual_freshwater_withdrawals_agriculture_pct_of_total_freshwater_withdrawal	float	0%	1	0.0
`Agriculture_forestry_and_fishing_value_added_current_USusd`	Agriculture_forestry_and_fishing_value_added_current_USusd	float	0%	1	150198356.125017
`Agriculture_forestry_and_fishing_value_added_pct_of_GDP`	Agriculture_forestry_and_fishing_value_added_pct_of_GDP	float	0%	1	0.0274391706944735
`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	0.0759573112147023
`Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate`	Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate	float	0%	1	0.110699529412483
`Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate`	Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate	float	0%	1	0.0954026681981231
`Rural_population`	Rural_population	float	0%	1	0.0
`Rural_population_pct_of_total_population`	Rural_population_pct_of_total_population	float	0%	1	0.0
`Agricultural_raw_materials_imports_pct_of_merchandise_imports`	Agricultural_raw_materials_imports_pct_of_merchandise_imports	float	0%	1	0.207764668293746
+1937 more extension fields — download the CSV/Parquet to see them all.

SGP Singapore - Health Indicators SGP-HDX-Singapore_-_Health_Indicators Indicators

18,120 rows · 1 table · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

SGP Singapore - Health Indicators — 18,120 rows, 17 columns

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`GHO (CODE)`	GHO (CODE)	string	0%	60	NCD_DIABETES_PREVALENCE_AGESTD, MORT_300, MORT_300,...
`GHO (DISPLAY)`	GHO (DISPLAY)	string	0%	60	Prevalence of diabetes, age-standardized, Distribution...
`GHO (URL)`	GHO (URL)	string	0%	58	https://www.who.int/data/gho/data/indicators/indicator-de...
`YEAR (DISPLAY)`	YEAR (DISPLAY)	string	0%	31	2006, 2005, 2012, 2012, 2023
`STARTYEAR`	STARTYEAR	string	0%	31	2006, 2005, 2012, 2012, 2023
`ENDYEAR`	ENDYEAR	string	0%	31	2006, 2005, 2012, 2012, 2023
`REGION (CODE)`	REGION (CODE)	string	0%	1	WPR, WPR, WPR, WPR, WPR
`REGION (DISPLAY)`	REGION (DISPLAY)	string	0%	1	Western Pacific, Western Pacific, Western Pacific,...
`COUNTRY (CODE)`	COUNTRY (CODE)	string	0%	1	SGP, SGP, SGP, SGP, SGP
`COUNTRY (DISPLAY)`	COUNTRY (DISPLAY)	string	0%	1	Singapore, Singapore, Singapore, Singapore, Singapore
`DIMENSION (TYPE)`	DIMENSION (TYPE)	string	10%	8	SEX, AGEGROUP, AGEGROUP, SEX, SEX
`DIMENSION (CODE)`	DIMENSION (CODE)	string	10%	33	SEX_MLE, AGEGROUP_DAYS0-27, AGEGROUP_DAYS0-27, SEX_MLE, SEX_MLE
`DIMENSION (NAME)`	DIMENSION (NAME)	string	10%	33	Male, 0-27 days, 0-27 days, Male, Male
`Numeric`	Numeric	float	18%	64	15.900119, 0.0, 0.06818, 3.5662554, 87.0
`Value`	Value	string	0%	70	15.9 [13.2-18.8], 0, 0.1, 3.6 [1.3-7.0], 87
`Low`	Low	float	49%	42	13.187128, 1.309036, 0.1, 4325.0, 0.0
`High`	High	float	49%	41	18.786639, 7.014671, 0.1, 4713.0, 0.0

SGP Singapore - Education SGP-HDX-Singapore_-_Education Indicators

13,002 rows · 1 table · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

SGP Singapore - Education — 13,002 rows, 869 columns

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Field details — 870 fields (type, nulls, unique, samples)

Extension Fields (870) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	SGP
`Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_15-19_with_no_education	float	0%	1	2.02
`Barro-Lee:_Percentage_of_population_age_15-19_with_no_education`	Barro-Lee:_Percentage_of_population_age_15-19_with_no_education	float	0%	1	1.76
`Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_15+_with_no_education	float	0%	1	18.57
`Barro-Lee:_Percentage_of_population_age_15+_with_no_education`	Barro-Lee:_Percentage_of_population_age_15+_with_no_education	float	0%	1	15.27
`Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_20-24_with_no_education	float	0%	1	1.01
`Barro-Lee:_Percentage_of_population_age_20-24_with_no_education`	Barro-Lee:_Percentage_of_population_age_20-24_with_no_education	float	0%	1	0.9
`Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_25-29_with_no_education	float	0%	1	0.99
`Barro-Lee:_Percentage_of_population_age_25-29_with_no_education`	Barro-Lee:_Percentage_of_population_age_25-29_with_no_education	float	0%	1	0.82
`Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_25+_with_no_education	float	0%	1	19.76
`Barro-Lee:_Percentage_of_population_age_25+_with_no_education`	Barro-Lee:_Percentage_of_population_age_25+_with_no_education	float	0%	1	16.39
`Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_30-34_with_no_education	float	0%	1	1.61
`Barro-Lee:_Percentage_of_population_age_30-34_with_no_education`	Barro-Lee:_Percentage_of_population_age_30-34_with_no_education	float	0%	1	1.36
`Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_35-39_with_no_education	float	0%	1	3.24
`Barro-Lee:_Percentage_of_population_age_35-39_with_no_education`	Barro-Lee:_Percentage_of_population_age_35-39_with_no_education	float	0%	1	2.85
`Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_40-44_with_no_education	float	0%	1	5.8
`Barro-Lee:_Percentage_of_population_age_40-44_with_no_education`	Barro-Lee:_Percentage_of_population_age_40-44_with_no_education	float	0%	1	5.83
`Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_45-49_with_no_education	float	0%	1	10.21
`Barro-Lee:_Percentage_of_population_age_45-49_with_no_education`	Barro-Lee:_Percentage_of_population_age_45-49_with_no_education	float	0%	1	9.73
`Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_50-54_with_no_education	float	0%	1	16.71
`Barro-Lee:_Percentage_of_population_age_50-54_with_no_education`	Barro-Lee:_Percentage_of_population_age_50-54_with_no_education	float	0%	1	14.93
`Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_55-59_with_no_education	float	0%	1	24.26
`Barro-Lee:_Percentage_of_population_age_55-59_with_no_education`	Barro-Lee:_Percentage_of_population_age_55-59_with_no_education	float	0%	1	19.52
`Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education`	Barro-Lee:_Percentage_of_female_population_age_60-64_with_no_education	float	0%	1	37.49
`Barro-Lee:_Percentage_of_population_age_60-64_with_no_education`	Barro-Lee:_Percentage_of_population_age_60-64_with_no_education	float	0%	1	30.03
`Barro-Lee:_Population_in_thousands_age_15-19_total`	Barro-Lee:_Population_in_thousands_age_15-19_total	float	0%	1	356.0
`Barro-Lee:_Population_in_thousands_age_15-19_female`	Barro-Lee:_Population_in_thousands_age_15-19_female	float	0%	1	172.0
`Barro-Lee:_Population_in_thousands_age_15+_total`	Barro-Lee:_Population_in_thousands_age_15+_total	float	0%	1	3872.0
`Barro-Lee:_Population_in_thousands_age_15+_female`	Barro-Lee:_Population_in_thousands_age_15+_female	float	0%	1	1935.0
`Barro-Lee:_Population_in_thousands_age_20-24_total`	Barro-Lee:_Population_in_thousands_age_20-24_total	float	0%	1	300.0
+840 more extension fields — download the CSV/Parquet to see them all.

SGP Singapore - Gender SGP-HDX-Singapore_-_Gender Indicators

4,164 rows · 1 table · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

SGP Singapore - Gender — 4,164 rows, 155 columns

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Field details — 156 fields (type, nulls, unique, samples)

Extension Fields (156) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	SGP
`Firms_with_female_top_manager_pct_of_firms`	Firms_with_female_top_manager_pct_of_firms	float	0%	1	21.80189705
`Firms_with_female_participation_in_ownership_pct_of_firms`	Firms_with_female_participation_in_ownership_pct_of_firms	float	0%	1	35.90182877
`Literacy_rate_youth_female_pct_of_females_ages_15-24`	Literacy_rate_youth_female_pct_of_females_ages_15-24	float	0%	1	99.9100036621094
`Literacy_rate_youth_ages_15-24_gender_parity_index_GPI`	Literacy_rate_youth_ages_15-24_gender_parity_index_GPI	float	0%	1	1.0
`Literacy_rate_youth_male_pct_of_males_ages_15-24`	Literacy_rate_youth_male_pct_of_males_ages_15-24	float	0%	1	99.870002746582
`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	96.4199981689453
`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	98.9400024414062
`School_enrollment_primary_gross_gender_parity_index_GPI`	School_enrollment_primary_gross_gender_parity_index_GPI	float	0%	1	0.999549984931946
`School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI`	School_enrollment_primary_and_secondary_gross_gender_parity_index_GPI	float	0%	1	0.996010005474091
`School_enrollment_secondary_gross_gender_parity_index_GPI`	School_enrollment_secondary_gross_gender_parity_index_GPI	float	0%	1	0.990890026092529
`School_enrollment_tertiary_gross_gender_parity_index_GPI`	School_enrollment_tertiary_gross_gender_parity_index_GPI	float	0%	1	1.09136863649498
`Primary_completion_rate_female_pct_of_relevant_age_group`	Primary_completion_rate_female_pct_of_relevant_age_group	float	0%	1	96.6836866264377
`Primary_completion_rate_male_pct_of_relevant_age_group`	Primary_completion_rate_male_pct_of_relevant_age_group	float	0%	1	97.0022680209052
`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	87.370002746582
`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	92.3099975585938
`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	89.7399978637695
`Primary_education_pupils_pct_female`	Primary_education_pupils_pct_female	float	0%	1	48.8777
`School_enrollment_primary_female_pct_gross`	School_enrollment_primary_female_pct_gross	float	0%	1	100.092255694849
`School_enrollment_primary_male_pct_gross`	School_enrollment_primary_male_pct_gross	float	0%	1	100.39018404908
`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	101.12881
`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	100.9814
`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	98.61301
`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	98.43444
`Persistence_to_grade_5_female_pct_of_cohort`	Persistence_to_grade_5_female_pct_of_cohort	float	0%	1	99.1638870239258
`Persistence_to_grade_5_male_pct_of_cohort`	Persistence_to_grade_5_male_pct_of_cohort	float	0%	1	99.8659820556641
`Persistence_to_last_grade_of_primary_female_pct_of_cohort`	Persistence_to_last_grade_of_primary_female_pct_of_cohort	float	0%	1	98.8533096313477
`Persistence_to_last_grade_of_primary_male_pct_of_cohort`	Persistence_to_last_grade_of_primary_male_pct_of_cohort	float	0%	1	99.8659820556641
`Repeaters_primary_female_pct_of_female_enrollment`	Repeaters_primary_female_pct_of_female_enrollment	float	0%	1	0.13776
`Repeaters_primary_male_pct_of_male_enrollment`	Repeaters_primary_male_pct_of_male_enrollment	float	0%	1	0.17506
+126 more extension fields — download the CSV/Parquet to see them all.

SGP Singapore - Social Protection and Labor SGP-HDX-Singapore_-_Social_Protection_and_L Indicators

2,905 rows · 1 table · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

SGP Singapore - Social Protection And Labor — 2,905 rows, 91 columns

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Field details — 92 fields (type, nulls, unique, samples)

Extension Fields (92) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	SGP
`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	0.0759573112147023
`Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate`	Employment_in_agriculture_male_pct_of_male_employment_modeled_ILO_estimate	float	0%	1	0.110699529412483
`Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate`	Employment_in_agriculture_pct_of_total_employment_modeled_ILO_estimate	float	0%	1	0.0954026681981231
`Employment_to_population_ratio_ages_15-24_female_pct_national_estimate`	Employment_to_population_ratio_ages_15-24_female_pct_national_estimate	float	0%	1	28.362
`Employment_to_population_ratio_ages_15-24_female_pct_modeled_ILO_estimate`	Employment_to_population_ratio_ages_15-24_female_pct_modeled_ILO_estimate	float	0%	1	28.308
`Employment_to_population_ratio_ages_15-24_male_pct_national_estimate`	Employment_to_population_ratio_ages_15-24_male_pct_national_estimate	float	0%	1	33.189
`Employment_to_population_ratio_ages_15-24_male_pct_modeled_ILO_estimate`	Employment_to_population_ratio_ages_15-24_male_pct_modeled_ILO_estimate	float	0%	1	33.079
`Employment_to_population_ratio_ages_15-24_total_pct_national_estimate`	Employment_to_population_ratio_ages_15-24_total_pct_national_estimate	float	0%	1	30.876
`Employment_to_population_ratio_ages_15-24_total_pct_modeled_ILO_estimate`	Employment_to_population_ratio_ages_15-24_total_pct_modeled_ILO_estimate	float	0%	1	30.882
`Employers_female_pct_of_female_employment_modeled_ILO_estimate`	Employers_female_pct_of_female_employment_modeled_ILO_estimate	float	0%	1	2.13993872949428
`Employers_male_pct_of_male_employment_modeled_ILO_estimate`	Employers_male_pct_of_male_employment_modeled_ILO_estimate	float	0%	1	4.38314150504535
`Employers_total_pct_of_total_employment_modeled_ILO_estimate`	Employers_total_pct_of_total_employment_modeled_ILO_estimate	float	0%	1	3.3954689857292
`Self-employed_female_pct_of_female_employment_modeled_ILO_estimate`	Self-employed_female_pct_of_female_employment_modeled_ILO_estimate	float	0%	1	8.28717557202519
`Self-employed_male_pct_of_male_employment_modeled_ILO_estimate`	Self-employed_male_pct_of_male_employment_modeled_ILO_estimate	float	0%	1	16.1567871790095
`Self-employed_total_pct_of_total_employment_modeled_ILO_estimate`	Self-employed_total_pct_of_total_employment_modeled_ILO_estimate	float	0%	1	12.6918308652273
`Female_share_of_employment_in_senior_and_middle_management_pct`	Female_share_of_employment_in_senior_and_middle_management_pct	float	0%	1	40.708
`Employment_to_population_ratio_15+_female_pct_national_estimate`	Employment_to_population_ratio_15+_female_pct_national_estimate	float	0%	1	60.332
`Employment_to_population_ratio_15+_female_pct_modeled_ILO_estimate`	Employment_to_population_ratio_15+_female_pct_modeled_ILO_estimate	float	0%	1	61.745
`Employment_to_population_ratio_15+_male_pct_national_estimate`	Employment_to_population_ratio_15+_male_pct_national_estimate	float	0%	1	71.529
`Employment_to_population_ratio_15+_male_pct_modeled_ILO_estimate`	Employment_to_population_ratio_15+_male_pct_modeled_ILO_estimate	float	0%	1	73.277
`Employment_to_population_ratio_15+_total_pct_national_estimate`	Employment_to_population_ratio_15+_total_pct_national_estimate	float	0%	1	65.735
`Employment_to_population_ratio_15+_total_pct_modeled_ILO_estimate`	Employment_to_population_ratio_15+_total_pct_modeled_ILO_estimate	float	0%	1	67.709
`Vulnerable_employment_female_pct_of_female_employment_modeled_ILO_estimate`	Vulnerable_employment_female_pct_of_female_employment_modeled_ILO_estimate	float	0%	1	6.14723684253092
`Vulnerable_employment_male_pct_of_male_employment_modeled_ILO_estimate`	Vulnerable_employment_male_pct_of_male_employment_modeled_ILO_estimate	float	0%	1	11.7736456739641
`Vulnerable_employment_total_pct_of_total_employment_modeled_ILO_estimate`	Vulnerable_employment_total_pct_of_total_employment_modeled_ILO_estimate	float	0%	1	9.29636187949808
`Wage_and_salaried_workers_female_pct_of_female_employment_modeled_ILO_estimate`	Wage_and_salaried_workers_female_pct_of_female_employment_modeled_ILO_estimate	float	0%	1	91.7128244279748
`Wage_and_salaried_workers_male_pct_of_male_employment_modeled_ILO_estimate`	Wage_and_salaried_workers_male_pct_of_male_employment_modeled_ILO_estimate	float	0%	1	83.8432637173258
`Wage_and_salaried_workers_total_pct_of_total_employment_modeled_ILO_estimate`	Wage_and_salaried_workers_total_pct_of_total_employment_modeled_ILO_estimate	float	0%	1	87.3081691347727
`Contributing_family_workers_female_pct_of_female_employment_modeled_ILO_estimate`	Contributing_family_workers_female_pct_of_female_employment_modeled_ILO_estimate	float	0%	1	0.163042950818611
+62 more extension fields — download the CSV/Parquet to see them all.

SGP Singapore - Human Development Indicators SGP-HDX-Singapore_-_Human_Development_Indic Indicators

958 rows · 1 table · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

SGP Singapore - Human Development Indicators — 958 rows, 36 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	SGP
`abr`	abr	float	0%	1	2.16
`co2_prod`	co2_prod	float	0%	1	8.189
`coef_ineq`	coef_ineq	float	0%	1	12.419
`diff_hdi_phdi`	diff_hdi_phdi	float	0%	1	34.672
`eys`	eys	float	0%	1	16.742
`eys_f`	eys_f	float	0%	1	16.89
`eys_m`	eys_m	float	0%	1	16.638
`gdi_group`	gdi_group	float	0%	1	1.0
`gii_rank`	gii_rank	float	0%	1	8.0
`gni_pc_f`	gni_pc_f	float	0%	1	96099.789
`gni_pc_m`	gni_pc_m	float	0%	1	125388.724
`gnipc`	gnipc	float	0%	1	111239.229
`hdi_f`	hdi_f	float	0%	1	0.944
`hdi_m`	hdi_m	float	0%	1	0.95
`hdi_rank`	hdi_rank	float	0%	1	13.0
`ineq_edu`	ineq_edu	float	0%	1	8.699
`ineq_inc`	ineq_inc	float	0%	1	25.935
`ineq_le`	ineq_le	float	0%	1	2.624
`le`	le	float	0%	1	83.736
`le_f`	le_f	float	0%	1	86.236
`le_m`	le_m	float	0%	1	81.24
`lfpr_f`	lfpr_f	float	0%	1	62.64
`lfpr_m`	lfpr_m	float	0%	1	74.9
`loss`	loss	float	0%	1	13.002
`mf`	mf	float	0%	1	53.04
`mmr`	mmr	float	0%	1	7.453
`mys`	mys	float	0%	1	11.99
`mys_f`	mys_f	float	0%	1	11.67
`mys_m`	mys_m	float	0%	1	12.33
+7 more extension fields — download the CSV/Parquet to see them all.

SGP Singapore - Urban Development SGP-HDX-Singapore_-_Urban_Development Indicators

642 rows · 1 table · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

SGP Singapore - Urban Development — 642 rows, 18 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
`country_code`	country_code	string	0%	1	SGP
`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	20.994755777122
`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	3.16068783881107
`Urban_land_area_sq._km`	Urban_land_area_sq._km	float	0%	1	454.083842663704
`Access_to_electricity_urban_pct_of_urban_population`	Access_to_electricity_urban_pct_of_urban_population	float	0%	1	100.0
`PM2.5_air_pollution_mean_annual_exposure_micrograms_per_cubic_meter`	PM2.5_air_pollution_mean_annual_exposure_micrograms_per_cubic_meter	float	0%	1	13.8691955865476
`PM2.5_air_pollution_population_exposed_to_levels_exceeding_WHO_guideline_value_p`	PM2.5_air_pollution_population_exposed_to_levels_exceeding_WHO_guideline_value_p	float	0%	1	100.0
`Population_density_people_per_sq._km_of_land_area`	Population_density_people_per_sq._km_of_land_area	float	0%	1	8241.8495821727
`Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_`	Urban_population_living_in_areas_where_elevation_is_below_5_meters_pct_of_total_	float	0%	1	0.656566658087191
`Population_living_in_slums_pct_of_urban_population`	Population_living_in_slums_pct_of_urban_population	float	0%	1	0.0
`Population_in_largest_city`	Population_in_largest_city	float	0%	1	6157267.0
`Population_in_the_largest_city_pct_of_urban_population`	Population_in_the_largest_city_pct_of_urban_population	float	0%	1	100.0
`Population_in_urban_agglomerations_of_more_than_1_million`	Population_in_urban_agglomerations_of_more_than_1_million	float	0%	1	6157267.0
`Population_in_urban_agglomerations_of_more_than_1_million_pct_of_total_populatio`	Population_in_urban_agglomerations_of_more_than_1_million_pct_of_total_populatio	float	0%	1	100.0
`Mortality_caused_by_road_traffic_injury_per_100000_population`	Mortality_caused_by_road_traffic_injury_per_100000_population	float	0%	1	2.1
`Urban_population_growth_annual_pct`	Urban_population_growth_annual_pct	float	0%	1	1.99449365639326
`Urban_population`	Urban_population	float	0%	1	6036860.0
`Urban_population_pct_of_total_population`	Urban_population_pct_of_total_population	float	0%	1	100.0
`year`	Reference year	integer	0%	-	-

SGP Singapore - Demographic, Health, Education and Tra SGP-HDX-Singapore_-_Demographic,_Health,_Ed Indicators

244 rows · 1 table · 2024 HDX 0 1 2 3 ▶

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0 Admin 0 — 1 table(s)

SGP Singapore - Demographic, Health, Education And Tra — 244 rows, 11 columns

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`category`	category	string	0%	6	Streets, Crime, Crime, Streets, Crime
`indicator`	indicator	string	0%	29	road_density_national_roads, recorded_theft_rate,...
`indicator_friendly`	indicator_friendly	string	0%	29	Road density (km/100km²), Recorded theft rate per 100,...
`type_data`	type_data	string	0%	5	n, 000 population, 000 population, index, 000 population
`latitude`	latitude	string	0%	3	1.22, n, n, 1.293033, n
`longitude`	longitude	float	0%	3	103.48, 1.22, 1.22, 103.855821, 1.22
`region_id`	region_id	string	0%	2	789, 103.48, 103.48, 789, 103.48
`country_id`	country_id	string	0%	2	SG, 789, 789, SG, 789
`name`	name	string	0%	2	Singapore, SG, SG, Singapore, SG
`year`	year	string	0%	38	2009, Singapore, Singapore, 2013, Singapore
`value`	value	string	0%	58	473, 2000, 1999, 0.307, 2000

SGP World Bank Open Data SGP-WORLD_BANK Development Indicators

198 rows · 3 tables · 2024 World Bank Open Data 0 1 2 3 19 SEL 4 ext ▶

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0 Admin 0 — 3 table(s)

SGP 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	SG, SG, SG, SG, SG
`population_count`	Population count	float	SEL	2%	65	1646400.0, 1702400.0, 1750200.0, 1795000.0, 1841600.0
`life_expectancy`	Life expectancy	float	SEL	3%	63	65.5621951219512, 65.9597073170732, 66.3726341463415,...
`gdp_per_capita_usd`	Gdp per capita usd	float	SEL	2%	65	428.056183371291, 449.148136820776, 472.082740153988,...
`literacy_rate_pct`	Literacy rate percent	float	SEL	77%	15	82.9100036621094, 89.0999984741211, 92.5500030517578,...
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	3%	55	47.6, 43.7, 40.5, 38.1, 36.4
`poverty_headcount_pct`	Poverty headcount percent	string	SEL	100%	-	-

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

SGP 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	SG, SG, SG, SG, SG
`life_expectancy`	Life expectancy	float	SEL	3%	63	65.5621951219512, 65.9597073170732, 66.3726341463415,...
`infant_mortality_per_1000`	Infant mortality per 1000	float	SEL	15%	40	16.3, 15.6, 15.1, 14.6, 14.1
`under5_mortality_per_1000`	Under5 mortality per 1000	float	SEL	3%	55	47.6, 43.7, 40.5, 38.1, 36.4
`maternal_mortality_per_100k`	Maternal mortality per 100k	float	SEL	41%	15	18.0, 18.0, 18.0, 18.0, 18.0
`fertility_rate`	Fertility rate	float	SEL	3%	53	5.76, 5.41, 5.21, 5.16, 4.97
`birth_rate_per_1000`	Birth rate per 1000	float	SEL	3%	52	37.5, 35.2, 33.7, 33.2, 31.6
`death_rate_per_1000`	Death rate per 1000	float	SEL	3%	19	6.2, 5.9, 5.8, 5.6, 5.7
`physicians_per_1000`	Physicians per 1000	float	SEL	41%	39	0.42, 0.526, 0.657, 0.667, 0.851
`hospital_beds_per_1000`	Hospital beds per 1000	float	SEL	58%	25	4.39246654510498, 3.69829988479614, 3.33330011367798,...
`vaccination_rate_pct`	Vaccination rate percent	float	SEL	32%	15	84.0, 87.0, 83.0, 84.0, 77.0
`health_expenditure_pct_gdp`	Health expenditure percent gdp	float	SEL	64%	24	3.343364, 3.16302657, 3.358464, 3.60699272, 3.15019798

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

SGP World Bank - Migration Indicators — 66 rows, 9 columns

Loading data…

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

Pending (9) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	SGP, SGP, SGP, SGP, SGP
`country_name`	country_name	string	0%	1	Singapore, Singapore, Singapore, Singapore, Singapore
`year`	year	integer	0%	66	1960, 1961, 1962, 1963, 1964
`intl_migrant_stock`	intl_migrant_stock	float	88%	8	729377.0, 993616.0, 1319433.0, 1494527.0, 2160350.0
`intl_migrant_stock_pct`	intl_migrant_stock_pct	float	88%	8	24.0, 28.1, 32.7, 35.0, 42.6
`net_migration`	net_migration	float	0%	66	2008.0, 3490.0, 3714.0, 2668.0, 3043.0
`remittances_received_usd`	remittances_received_usd	string	100%	-	-
`remittances_received_pct_gdp`	remittances_received_pct_gdp	string	100%	-	-
`remittances_paid_usd`	remittances_paid_usd	string	100%	-	-

SGP UNHCR Refugee Data Finder SGP-UNHCR Migration

67 rows · 2 tables · 2025 UNHCR Refugee Data Finder 0 1 2 3 12 CCL 36 ext ▶

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0 Admin 0 — 2 table(s)

SGP UNHCR - Hosted Populations — 33 rows, 24 columns

Loading data…

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%	-	-

SGP UNHCR - Origin Populations — 34 rows, 24 columns

Loading data…

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%	-	-

SGP OpenFactBook SGP-OPENFACTBOOK Country Profile

15 rows · 15 tables · 2024 OpenFactBook 0 1 2 3 93 SEL 6 CCL 552 ext ▶

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

0 Admin 0 — 15 table(s)

SGP OpenFactBook - Communications — 1 rows, 21 columns

Loading data…

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

Standards-Aligned Fields (7)

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	33.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric`	Mobile subscriptions per 100	float	SEL	0%	1	171.0
`internet_users_percent_of_population_numeric`	Internet penetration percent	float	SEL	0%	1	94.0
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_numeric`	Broadband subscriptions per 100	float	SEL	0%	1	27.0
`country_code`	Country code	string	SEL	0%	1	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (15) — 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	1.912 million (2023 est.)
`telephones_fixed_lines_total_subscriptions_numeric`	telephones_fixed_lines_total_subscriptions_numeric	float	0%	1	1.912
`telephones_fixed_lines_subscriptions_per_100_inhabitants_text`	telephones_fixed_lines_subscriptions_per_100_inhabitants_text	string	0%	1	33 (2023 est.)
`telephones_mobile_cellular_total_subscriptions_text`	telephones_mobile_cellular_total_subscriptions_text	string	0%	1	9.96 million (2024 est.)
`telephones_mobile_cellular_total_subscriptions_numeric`	telephones_mobile_cellular_total_subscriptions_numeric	float	0%	1	9.96
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_text`	telephones_mobile_cellular_subscriptions_per_100_inhabitants_text	string	0%	1	171 (2024 est.)
`broadcast_media_text`	broadcast_media_text	string	0%	1	state-controlled broadcast media; 6 domestic TV stations...
`broadcast_media_numeric`	broadcast_media_numeric	float	0%	1	6.0
`internet_country_code_text`	Internet country code text	string	0%	1	.sg
`internet_users_percent_of_population_text`	internet_users_percent_of_population_text	string	0%	1	94% (2023 est.)
`broadband_fixed_subscriptions_total_text`	broadband_fixed_subscriptions_total_text	string	0%	1	1.57 million (2023 est.)
`broadband_fixed_subscriptions_total_numeric`	broadband_fixed_subscriptions_total_numeric	float	0%	1	1.57
`broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text`	broadband_fixed_subscriptions_subscriptions_per_100_inhabitants_text	string	0%	1	27 (2023 est.)
`source_section`	source_section	string	0%	1	Communications
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/sn.json

SGP OpenFactBook - Economy — 1 rows, 142 columns

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

Standards-Aligned Fields (5)

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	132600.0
`gdp_official_exchange_rate_numeric`	Gdp total usd	float	SEL	0%	1	547.387
`country_code`	Country code	string	SEL	0%	1	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (142) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`economic_overview_text`	economic_overview_text	string	0%	1	high-income, service-based economy; global financial...
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2024_text`	Real gdp purchasing power parity 2024 (text)	string	0%	1	$800.304 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	800.304
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2023_text`	Real gdp purchasing power parity 2023 (text)	string	0%	1	$766.662 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	766.662
`real_gdp_purchasing_power_parity_real_gdp_purchasing_power_parity_2022_text`	Real gdp purchasing power parity 2022 (text)	string	0%	1	$752.948 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	752.948
`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	4.4% (2024 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2024_numeric`	Real gdp growth rate 2024 (numeric)	float	0%	1	4.4
`real_gdp_growth_rate_real_gdp_growth_rate_2023_text`	Real gdp growth rate 2023 (text)	string	0%	1	1.8% (2023 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2023_numeric`	Real gdp growth rate 2023 (numeric)	float	0%	1	1.8
`real_gdp_growth_rate_real_gdp_growth_rate_2022_text`	Real gdp growth rate 2022 (text)	string	0%	1	4.1% (2022 est.)
`real_gdp_growth_rate_real_gdp_growth_rate_2022_numeric`	Real gdp growth rate 2022 (numeric)	float	0%	1	4.1
`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	$132,600 (2024 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_text`	Real gdp per capita 2023 (text)	string	0%	1	$129,600 (2023 est.)
`real_gdp_per_capita_real_gdp_per_capita_2023_numeric`	Real gdp per capita 2023 (numeric)	float	0%	1	129600.0
`real_gdp_per_capita_real_gdp_per_capita_2022_text`	Real gdp per capita 2022 (text)	string	0%	1	$133,600 (2022 est.)
`real_gdp_per_capita_real_gdp_per_capita_2022_numeric`	Real gdp per capita 2022 (numeric)	float	0%	1	133600.0
`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	$547.387 billion (2024 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_text`	Inflation rate consumer prices 2024 (text)	string	0%	1	2.4% (2024 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2024_numeric`	Inflation rate consumer prices 2024 (numeric)	float	0%	1	2.4
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_text`	Inflation rate consumer prices 2023 (text)	string	0%	1	4.8% (2023 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2023_numeric`	Inflation rate consumer prices 2023 (numeric)	float	0%	1	4.8
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_text`	Inflation rate consumer prices 2022 (text)	string	0%	1	6.1% (2022 est.)
`inflation_rate_consumer_prices_inflation_rate_consumer_prices_2022_numeric`	Inflation rate consumer prices 2022 (numeric)	float	0%	1	6.1
`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	0% (2024 est.)
+112 more extension fields — download the CSV/Parquet to see them all.

SGP OpenFactBook - Energy — 1 rows, 35 columns

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

Standards-Aligned Fields (4)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`electricity_access_electrification_total_population_numeric`	Electricity access percent	float	SEL	0%	1	100.0
`country_code`	Country code	string	SEL	0%	1	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (31) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`electricity_access_electrification_total_population_text`	electricity_access_electrification_total_population_text	string	0%	1	100% (2022 est.)
`electricity_installed_generating_capacity_text`	electricity_installed_generating_capacity_text	string	0%	1	13.134 million kW (2023 est.)
`electricity_installed_generating_capacity_numeric`	electricity_installed_generating_capacity_numeric	float	0%	1	13.134
`electricity_consumption_text`	electricity_consumption_text	string	0%	1	56.672 billion kWh (2023 est.)
`electricity_consumption_numeric`	electricity_consumption_numeric	float	0%	1	56.672
`electricity_transmission_distribution_losses_text`	electricity_transmission_distribution_losses_text	string	0%	1	169.447 million kWh (2023 est.)
`electricity_transmission_distribution_losses_numeric`	electricity_transmission_distribution_losses_numeric	float	0%	1	169.447
`electricity_generation_sources_fossil_fuels_text`	electricity_generation_sources_fossil_fuels_text	string	0%	1	94.8% of total installed capacity (2023 est.)
`electricity_generation_sources_fossil_fuels_numeric`	electricity_generation_sources_fossil_fuels_numeric	float	0%	1	94.8
`electricity_generation_sources_solar_text`	electricity_generation_sources_solar_text	string	0%	1	2% of total installed capacity (2023 est.)
`electricity_generation_sources_solar_numeric`	electricity_generation_sources_solar_numeric	float	0%	1	2.0
`electricity_generation_sources_biomass_and_waste_text`	electricity_generation_sources_biomass_and_waste_text	string	0%	1	3.1% of total installed capacity (2023 est.)
`electricity_generation_sources_biomass_and_waste_numeric`	electricity_generation_sources_biomass_and_waste_numeric	float	0%	1	3.1
`coal_consumption_text`	coal_consumption_text	string	0%	1	1.153 million metric tons (2023 est.)
`coal_consumption_numeric`	coal_consumption_numeric	float	0%	1	1.153
`coal_exports_text`	coal_exports_text	string	0%	1	97 metric tons (2023 est.)
`coal_exports_numeric`	coal_exports_numeric	float	0%	1	97.0
`coal_imports_text`	coal_imports_text	string	0%	1	1.326 million metric tons (2023 est.)
`coal_imports_numeric`	coal_imports_numeric	float	0%	1	1.326
`petroleum_refined_petroleum_consumption_text`	petroleum_refined_petroleum_consumption_text	string	0%	1	1.514 million bbl/day (2023 est.)
`petroleum_refined_petroleum_consumption_numeric`	petroleum_refined_petroleum_consumption_numeric	float	0%	1	1.514
`natural_gas_consumption_text`	natural_gas_consumption_text	string	0%	1	13.134 billion cubic meters (2023 est.)
`natural_gas_consumption_numeric`	natural_gas_consumption_numeric	float	0%	1	13.134
`natural_gas_exports_text`	natural_gas_exports_text	string	0%	1	399.452 million cubic meters (2023 est.)
`natural_gas_exports_numeric`	natural_gas_exports_numeric	float	0%	1	399.452
`natural_gas_imports_text`	natural_gas_imports_text	string	0%	1	13.973 billion cubic meters (2023 est.)
`natural_gas_imports_numeric`	natural_gas_imports_numeric	float	0%	1	13.973
`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	643.259 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	643.259
`source_section`	source_section	string	0%	1	Energy
+1 more extension field — download the CSV/Parquet to see them all.

SGP OpenFactBook - Environment — 1 rows, 43 columns

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Field details — 47 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	0.9
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	22.0
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	100.0
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	0.74
`waste_and_recycling_municipal_solid_waste_generated_annually_numeric`	Municipal waste kg per capita	float	SEL	0%	1	1.87
`country_code`	Country code	string	SEL	0%	1	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (39) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`environmental_issues_text`	environmental_issues_text	string	0%	1	water pollution; industrial pollution; limited...
`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	none of the selected agreements
`climate_text`	climate_text	string	0%	1	tropical; hot, humid, rainy; two distinct monsoon...
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	0.9% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 0.8% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	0.8
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 0.1% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	0.1
`land_use_agricultural_land_permanent_pasture_text`	land_use_agricultural_land_permanent_pasture_text	string	0%	1	permanent pasture: 0% (2022 est.)
`land_use_agricultural_land_permanent_pasture_numeric`	land_use_agricultural_land_permanent_pasture_numeric	float	0%	1	0.0
`land_use_forest_text`	land_use_forest_text	string	0%	1	22% (2023 est.)
`land_use_other_text`	land_use_other_text	string	0%	1	77.1% (2023 est.)
`land_use_other_numeric`	land_use_other_numeric	float	0%	1	77.1
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	100% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	0.74% annual rate of change (2020-25 est.)
`carbon_dioxide_emissions_total_emissions_text`	carbon_dioxide_emissions_total_emissions_text	string	0%	1	238.962 million metric tonnes of CO2 (2023 est.)
`carbon_dioxide_emissions_total_emissions_numeric`	carbon_dioxide_emissions_total_emissions_numeric	float	0%	1	238.962
`carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text`	carbon_dioxide_emissions_from_coal_and_metallurgical_coke_text	string	0%	1	2.338 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	2.338
`carbon_dioxide_emissions_from_petroleum_and_other_liquids_text`	carbon_dioxide_emissions_from_petroleum_and_other_liquids_text	string	0%	1	210.859 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	210.859
`carbon_dioxide_emissions_from_consumed_natural_gas_text`	carbon_dioxide_emissions_from_consumed_natural_gas_text	string	0%	1	25.765 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	25.765
`particulate_matter_emissions_text`	particulate_matter_emissions_text	string	0%	1	10 micrograms per cubic meter (2019 est.)
`particulate_matter_emissions_numeric`	particulate_matter_emissions_numeric	float	0%	1	10.0
`waste_and_recycling_municipal_solid_waste_generated_annually_text`	waste_and_recycling_municipal_solid_waste_generated_annually_text	string	0%	1	1.87 million tons (2024 est.)
`waste_and_recycling_percent_of_municipal_solid_waste_recycled_text`	waste_and_recycling_percent_of_municipal_solid_waste_recycled_text	string	0%	1	51.7% (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	51.7
`total_water_withdrawal_municipal_text`	total_water_withdrawal_municipal_text	string	0%	1	198.207 million cubic meters (2022)
+9 more extension fields — download the CSV/Parquet to see them all.

SGP OpenFactBook - Ethnic Groups — 1 rows, 8 columns

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`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	Singaporean(s)
`nationality_adjective_text`	nationality_adjective_text	string	0%	1	Singapore
`ethnic_groups_text`	ethnic_groups_text	string	0%	1	Chinese 74.2%, Malay 13.7%, Indian 8.9%, other 3.2% (2021 est.)
`ethnic_groups_numeric`	ethnic_groups_numeric	float	0%	1	74.2
`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/sn.json

SGP OpenFactBook - Geography — 1 rows, 47 columns

Loading data…

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	719.0
`area_land_numeric`	Area land sqkm	float	SEL	0%	1	709.2
`area_water_numeric`	Area water sqkm	float	SEL	0%	1	10.0
`land_boundaries_total_numeric`	Land boundary km	float	SEL	0%	1	0.0
`coastline_numeric`	Coastline km	float	SEL	0%	1	193.0
`elevation_highest_point_numeric`	Elevation max m	float	SEL	0%	1	166.0
`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	0.9
`land_use_forest_numeric`	Forest area percent	float	SEL	0%	1	22.0
`irrigated_land_numeric`	Irrigated land sqkm	float	SEL	0%	1	0.0
`country_code`	Country code	string	SEL	0%	1	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`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	Southeastern Asia, islands between Malaysia and Indonesia
`geographic_coordinates_text`	geographic_coordinates_text	string	0%	1	1 22 N, 103 48 E
`geographic_coordinates_numeric`	geographic_coordinates_numeric	float	0%	1	1.0
`map_references_text`	map_references_text	string	0%	1	Southeast Asia
`area_total_text`	area_total_text	string	0%	1	719 sq km
`area_land_text`	area_land_text	string	0%	1	709.2 sq km
`area_water_text`	area_water_text	string	0%	1	10 sq km
`area_comparative_text`	area_comparative_text	string	0%	1	slightly more than 3.5 times the size of Washington, D.C.
`area_comparative_numeric`	area_comparative_numeric	float	0%	1	3.5
`land_boundaries_total_text`	land_boundaries_total_text	string	0%	1	0 km
`coastline_text`	coastline_text	string	0%	1	193 km
`maritime_claims_territorial_sea_text`	maritime_claims_territorial_sea_text	string	0%	1	3 nm
`maritime_claims_territorial_sea_numeric`	maritime_claims_territorial_sea_numeric	float	0%	1	3.0
`maritime_claims_exclusive_fishing_zone_text`	maritime_claims_exclusive_fishing_zone_text	string	0%	1	within and beyond territorial sea, as defined in...
`climate_text`	climate_text	string	0%	1	tropical; hot, humid, rainy; two distinct monsoon...
`terrain_text`	terrain_text	string	0%	1	lowlying, gently undulating central plateau
`elevation_highest_point_text`	elevation_highest_point_text	string	0%	1	Bukit Timah 166 m
`elevation_lowest_point_text`	elevation_lowest_point_text	string	0%	1	Singapore Strait 0 m
`natural_resources_text`	natural_resources_text	string	0%	1	fish, deepwater ports
`land_use_agricultural_land_text`	land_use_agricultural_land_text	string	0%	1	0.9% (2023 est.)
`land_use_agricultural_land_arable_land_text`	land_use_agricultural_land_arable_land_text	string	0%	1	arable land: 0.8% (2023 est.)
`land_use_agricultural_land_arable_land_numeric`	land_use_agricultural_land_arable_land_numeric	float	0%	1	0.8
`land_use_agricultural_land_permanent_crops_text`	land_use_agricultural_land_permanent_crops_text	string	0%	1	permanent crops: 0.1% (2023 est.)
`land_use_agricultural_land_permanent_crops_numeric`	land_use_agricultural_land_permanent_crops_numeric	float	0%	1	0.1
`land_use_agricultural_land_permanent_pasture_text`	land_use_agricultural_land_permanent_pasture_text	string	0%	1	permanent pasture: 0% (2022 est.)
`land_use_agricultural_land_permanent_pasture_numeric`	land_use_agricultural_land_permanent_pasture_numeric	float	0%	1	0.0
`land_use_forest_text`	land_use_forest_text	string	0%	1	22% (2023 est.)
`land_use_other_text`	land_use_other_text	string	0%	1	77.1% (2023 est.)
`land_use_other_numeric`	land_use_other_numeric	float	0%	1	77.1
`irrigated_land_text`	irrigated_land_text	string	0%	1	0 sq km (2022)
+6 more extension fields — download the CSV/Parquet to see them all.

SGP OpenFactBook - Government — 1 rows, 78 columns

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Field details — 106 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	SGP
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (104) — 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 Singapore
`country_name_conventional_short_form_text`	country_name_conventional_short_form_text	string	0%	1	Singapore
`country_name_local_long_form_text`	country_name_local_long_form_text	string	0%	1	Republic of Singapore
`country_name_local_short_form_text`	country_name_local_short_form_text	string	0%	1	Singapore
`country_name_etymology_text`	country_name_etymology_text	string	0%	1	name derives from the Sanskrit words simha (lion) and...
`country_name_etymology_numeric`	country_name_etymology_numeric	float	0%	1	7.0
`government_type_text`	government_type_text	string	0%	1	parliamentary republic
`capital_name_text`	capital_name_text	string	0%	1	Singapore
`capital_geographic_coordinates_text`	capital_geographic_coordinates_text	string	0%	1	1 17 N, 103 51 E
`capital_geographic_coordinates_numeric`	capital_geographic_coordinates_numeric	float	0%	1	1.0
`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	name derives from the Sanskrit words simha (lion) and...
`capital_etymology_numeric`	capital_etymology_numeric	float	0%	1	7.0
`administrative_divisions_text`	administrative_divisions_text	string	0%	1	no first-order administrative divisions; five community...
`administrative_divisions_numeric`	administrative_divisions_numeric	float	0%	1	2019.0
`legal_system_text`	legal_system_text	string	0%	1	English common law
`constitution_history_text`	constitution_history_text	string	0%	1	several previous; latest adopted 22 December 1965
`constitution_history_numeric`	constitution_history_numeric	float	0%	1	22.0
`constitution_amendment_process_text`	constitution_amendment_process_text	string	0%	1	proposed by Parliament; passage requires two-thirds...
`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 Singapore
`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	21 years of age; universal and compulsory
`suffrage_numeric`	suffrage_numeric	float	0%	1	21.0
`executive_branch_chief_of_state_text`	executive_branch_chief_of_state_text	string	0%	1	President THARMAN Shanmugaratnam (since 14 September 2023)
`executive_branch_chief_of_state_numeric`	executive_branch_chief_of_state_numeric	float	0%	1	14.0
+74 more extension fields — download the CSV/Parquet to see them all.

SGP 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	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`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	A Malay trading port known as Temasek existed on the...
`background_numeric`	background_numeric	float	0%	1	14.0
`source_section`	source_section	string	0%	1	Introduction
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/sn.json

SGP OpenFactBook - Languages — 1 rows, 8 columns

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`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	English (official) 48.3%, Mandarin (official) 29.9%,...
`languages_languages_numeric`	Languages (numeric)	float	0%	1	48.3
`languages_major_language_sample_s_text`	languages_major_language_sample_s_text	string	0%	1	The World Factbook, the indispensable source for basic...
`languages_note`	languages_note	string	0%	1	note: data represent language most frequently spoken at home
`source_section`	source_section	string	0%	1	People and Society:languages
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/sn.json

SGP OpenFactBook - Migration — 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	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`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
`refugees_and_internally_displaced_persons_stateless_persons_text`	refugees_and_internally_displaced_persons_stateless_persons_text	string	0%	1	1,109 (2024 est.)
`refugees_and_internally_displaced_persons_stateless_persons_numeric`	refugees_and_internally_displaced_persons_stateless_persons_numeric	float	0%	1	1109.0
`source_section`	source_section	string	0%	1	Transnational Issues:migration
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/sn.json

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

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

Standards-Aligned Fields (3)

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`military_and_security_forces_text`	military_and_security_forces_text	string	0%	1	Singapore Armed Forces (SAF; aka Singapore Defense...
`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	3% of GDP (2024 est.)
`military_expenditures_military_expenditures_2024_numeric`	Military expenditures 2024 (numeric)	float	0%	1	3.0
`military_expenditures_military_expenditures_2023_text`	Military expenditures 2023 (text)	string	0%	1	3% of GDP (2023 est.)
`military_expenditures_military_expenditures_2023_numeric`	Military expenditures 2023 (numeric)	float	0%	1	3.0
`military_expenditures_military_expenditures_2022_text`	Military expenditures 2022 (text)	string	0%	1	3% of GDP (2022 est.)
`military_expenditures_military_expenditures_2022_numeric`	Military expenditures 2022 (numeric)	float	0%	1	3.0
`military_expenditures_military_expenditures_2021_text`	Military expenditures 2021 (text)	string	0%	1	3% of GDP (2021 est.)
`military_expenditures_military_expenditures_2021_numeric`	Military expenditures 2021 (numeric)	float	0%	1	3.0
`military_expenditures_military_expenditures_2020_text`	Military expenditures 2020 (text)	string	0%	1	3% of GDP (2020 est.)
`military_expenditures_military_expenditures_2020_numeric`	Military expenditures 2020 (numeric)	float	0%	1	3.0
`military_and_security_service_personnel_strengths_text`	military_and_security_service_personnel_strengths_text	string	0%	1	information varies; approximately 55,000 active-duty...
`military_and_security_service_personnel_strengths_numeric`	military_and_security_service_personnel_strengths_numeric	float	0%	1	55000.0
`military_equipment_inventories_and_acquisitions_text`	military_equipment_inventories_and_acquisitions_text	string	0%	1	the SAF has a diverse and modern mix of domestically...
`military_equipment_inventories_and_acquisitions_numeric`	military_equipment_inventories_and_acquisitions_numeric	float	0%	1	2025.0
`military_service_age_and_obligation_text`	military_service_age_and_obligation_text	string	0%	1	18 years of age for voluntary enlistment for men and...
`military_service_age_and_obligation_numeric`	military_service_age_and_obligation_numeric	float	0%	1	18.0
`military_deployments_text`	military_deployments_text	string	0%	1	maintains permanent training detachments of military...
`military_deployments_numeric`	military_deployments_numeric	float	0%	1	2025.0
`military_note_text`	military_note_text	string	0%	1	the SAF’s primary responsibility is external defense,...
`military_note_numeric`	military_note_numeric	float	0%	1	1971.0
`source_section`	source_section	string	0%	1	Military and Security
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/sn.json

SGP OpenFactBook - People And Society — 1 rows, 128 columns

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Field details — 140 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	6080545.0
`population_male_numeric`	Population male	float	SEL	0%	1	3040862.0
`population_female_numeric`	Population female	float	SEL	0%	1	3039683.0
`age_structure_0_14_years_numeric`	Population 0 14 percent	float	SEL	0%	1	14.6
`age_structure_15_64_years_numeric`	Population 15 64 percent	float	SEL	0%	1	71.1
`age_structure_65_years_and_over_numeric`	Population 65 plus percent	float	SEL	0%	1	14.3
`dependency_ratios_total_dependency_ratio_numeric`	Total dependency ratio	float	SEL	0%	1	41.6
`dependency_ratios_youth_dependency_ratio_numeric`	Youth dependency ratio	float	SEL	0%	1	20.5
`dependency_ratios_elderly_dependency_ratio_numeric`	Elderly dependency ratio	float	SEL	0%	1	21.2
`median_age_total_numeric`	Median age	float	SEL	0%	1	39.8
`population_growth_rate_numeric`	Population growth rate percent	float	SEL	0%	1	0.85
`birth_rate_numeric`	Birth rate per 1000	float	SEL	0%	1	8.77
`death_rate_numeric`	Death rate per 1000	float	SEL	0%	1	4.38
`net_migration_rate_numeric`	Net migration per 1000	float	SEL	0%	1	4.11
`urbanization_urban_population_numeric`	Urban population percent	float	SEL	0%	1	100.0
`urbanization_rate_of_urbanization_numeric`	Urban growth rate percent	float	SEL	0%	1	0.74
`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	6.0
`infant_mortality_rate_total_numeric`	Infant mortality per 1000	float	SEL	0%	1	1.5
`life_expectancy_at_birth_total_population_numeric`	Life expectancy	float	SEL	0%	1	86.7
`total_fertility_rate_numeric`	Fertility rate	float	SEL	0%	1	1.18
`gross_reproduction_rate_numeric`	Gross reproduction rate	float	SEL	0%	1	0.58
`physician_density_numeric`	Physicians per 1000	float	SEL	0%	1	2.83
`hospital_bed_density_numeric`	Hospital beds per 1000	float	SEL	0%	1	2.6
`literacy_total_population_numeric`	Literacy rate percent	float	SEL	0%	1	97.7
`country_code`	Country code	string	SEL	0%	1	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`admin_level`	Admin level	string	SEL	0%	1	national

Extension Fields (111) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`population_total_text`	population_total_text	string	0%	1	6,080,545 (2025 est.)
`population_male_text`	population_male_text	string	0%	1	3,040,862
`population_female_text`	population_female_text	string	0%	1	3,039,683
`age_structure_0_14_years_text`	age_structure_0_14_years_text	string	0%	1	14.6% (male 455,536/female 424,969)
`age_structure_15_64_years_text`	age_structure_15_64_years_text	string	0%	1	71.1% (male 2,157,441/female 2,126,799)
`age_structure_65_years_and_over_text`	age_structure_65_years_and_over_text	string	0%	1	14.3% (2024 est.) (male 400,653/female 463,061)
`dependency_ratios_total_dependency_ratio_text`	dependency_ratios_total_dependency_ratio_text	string	0%	1	41.6 (2025 est.)
`dependency_ratios_youth_dependency_ratio_text`	dependency_ratios_youth_dependency_ratio_text	string	0%	1	20.5 (2025 est.)
`dependency_ratios_elderly_dependency_ratio_text`	dependency_ratios_elderly_dependency_ratio_text	string	0%	1	21.2 (2025 est.)
`dependency_ratios_potential_support_ratio_text`	dependency_ratios_potential_support_ratio_text	string	0%	1	4.7 (2025 est.)
`dependency_ratios_potential_support_ratio_numeric`	dependency_ratios_potential_support_ratio_numeric	float	0%	1	4.7
`median_age_total_text`	median_age_total_text	string	0%	1	39.8 years (2025 est.)
`median_age_male_text`	median_age_male_text	string	0%	1	38 years
`median_age_male_numeric`	median_age_male_numeric	float	0%	1	38.0
`median_age_female_text`	median_age_female_text	string	0%	1	40.6 years
`median_age_female_numeric`	median_age_female_numeric	float	0%	1	40.6
`population_growth_rate_text`	population_growth_rate_text	string	0%	1	0.85% (2025 est.)
`birth_rate_text`	birth_rate_text	string	0%	1	8.77 births/1,000 population (2025 est.)
`death_rate_text`	death_rate_text	string	0%	1	4.38 deaths/1,000 population (2025 est.)
`net_migration_rate_text`	net_migration_rate_text	string	0%	1	4.11 migrant(s)/1,000 population (2025 est.)
`population_distribution_text`	population_distribution_text	string	0%	1	most of the urbanization is along the southern coast,...
`urbanization_urban_population_text`	urbanization_urban_population_text	string	0%	1	100% of total population (2023)
`urbanization_rate_of_urbanization_text`	urbanization_rate_of_urbanization_text	string	0%	1	0.74% annual rate of change (2020-25 est.)
`major_urban_areas_population_text`	major_urban_areas_population_text	string	0%	1	6.081 million SINGAPORE (capital) (2023)
`major_urban_areas_population_numeric`	major_urban_areas_population_numeric	float	0%	1	6.081
`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	1.07 male(s)/female
`sex_ratio_0_14_years_numeric`	sex_ratio_0_14_years_numeric	float	0%	1	1.07
`sex_ratio_15_64_years_text`	sex_ratio_15_64_years_text	string	0%	1	1.01 male(s)/female
`sex_ratio_15_64_years_numeric`	sex_ratio_15_64_years_numeric	float	0%	1	1.01
+81 more extension fields — download the CSV/Parquet to see them all.

SGP OpenFactBook - Religions — 1 rows, 6 columns

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Field details — 20 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	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`admin_level`	Admin level	string	SEL	0%	1	national
`composition_religion_buddhist_pct_synth`	Buddhist	numeric	CCL	0%	-	31.1
`composition_religion_christian_pct_synth`	Christian	numeric	CCL	0%	-	18.9
`composition_religion_muslim_pct_synth`	Muslim	numeric	CCL	0%	-	15.6
`composition_religion_hindu_pct_synth`	Hindu	numeric	CCL	0%	-	5.0
`composition_religion_other_pct_synth`	other	numeric	CCL	0%	-	0.6
`composition_ethnicity_primary_label_synth`	Chinese	string	CCL	0%	-	Chinese

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

Field Name	Label	Type	Nulls	Unique	Samples
`religions_text`	religions_text	string	0%	1	Buddhist 31.1%, Christian 18.9%, Muslim 15.6%, Taoist...
`religions_numeric`	religions_numeric	float	0%	1	31.1
`source_section`	source_section	string	0%	1	People and Society:religions
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/sn.json

Pending (7) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`composition_religion_taoist_pct_synth`	Taoist	numeric	0%	-	8.8
`composition_religion_none_pct_synth`	none	numeric	0%	-	20.0
`composition_ethnicity_chinese_pct_synth`	Chinese	numeric	0%	-	74.2
`composition_ethnicity_malay_pct_synth`	Malay	numeric	0%	-	13.7
`composition_ethnicity_indian_pct_synth`	Indian	numeric	0%	-	8.9
`composition_ethnicity_other_pct_synth`	other	numeric	0%	-	3.2
`composition_ethnicity_primary_share_pct_synth`	Chinese	numeric	0%	-	74.2

SGP OpenFactBook - Terrorism — 1 rows, 5 columns

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Field details — 5 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	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`admin_level`	Admin level	string	SEL	0%	1	national

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

Field Name	Label	Type	Nulls	Unique	Samples
`source_section`	source_section	string	0%	1	Terrorism
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/sn.json

SGP OpenFactBook - Transportation — 1 rows, 27 columns

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

Standards-Aligned Fields (4)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`airports_numeric`	Airports count	float	SEL	0%	1	9.0
`country_code`	Country code	string	SEL	0%	1	SGP
`country_name`	Country name	string	SEL	0%	1	Singapore
`admin_level`	Admin level	string	SEL	0%	1	national

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

Field Name	Label	Type	Nulls	Unique	Samples
`civil_aircraft_registration_country_code_prefix_text`	Civil aircraft registration country code prefix text	string	0%	1	9V
`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	9 (2025)
`heliports_text`	heliports_text	string	0%	1	1 (2025)
`heliports_numeric`	heliports_numeric	float	0%	1	1.0
`merchant_marine_total_text`	merchant_marine_total_text	string	0%	1	3,202 (2023)
`merchant_marine_total_numeric`	merchant_marine_total_numeric	float	0%	1	3202.0
`merchant_marine_by_type_text`	merchant_marine_by_type_text	string	0%	1	bulk carrier 591, container ship 604, general cargo 107,...
`merchant_marine_by_type_numeric`	merchant_marine_by_type_numeric	float	0%	1	591.0
`ports_total_ports_text`	ports_total_ports_text	string	0%	1	5 (2024)
`ports_total_ports_numeric`	ports_total_ports_numeric	float	0%	1	5.0
`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	1
`ports_medium_numeric`	ports_medium_numeric	float	0%	1	1.0
`ports_small_text`	ports_small_text	float	0%	1	1
`ports_small_numeric`	ports_small_numeric	float	0%	1	1.0
`ports_very_small_text`	ports_very_small_text	float	0%	1	1
`ports_very_small_numeric`	ports_very_small_numeric	float	0%	1	1.0
`ports_ports_with_oil_terminals_text`	Ports with oil terminals (text)	float	0%	1	3
`ports_ports_with_oil_terminals_numeric`	Ports with oil terminals (numeric)	float	0%	1	3.0
`ports_key_ports_text`	ports_key_ports_text	string	0%	1	Jurong Island, Keppel - (East Singapore), Pulau Bukom,...
`source_section`	source_section	string	0%	1	Transportation
`source_profile_path`	source_profile_path	string	0%	1	east-n-southeast-asia/sn.json

SGP Glottolog Language Catalog SGP-GLOTTOLOG Language

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

SGP Glottolog - Languages — 8 rows, 16 columns

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

Standards-Aligned Fields (12)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`glottocode`	Glottocode	string	CCL	0%	8	amer1248, baba1267, coco1260, indo1316, mala1479
`name`	Name	string	CCL	0%	8	American Sign Language, Baba Malay, Cocos Islands Malay,...
`iso639_3`	Iso639 3	string	CCL	0%	8	ase, mbf, coa, ind, zlm
`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%	3	sign1238, aust1307, aust1307, aust1307, aust1307
`parent_name`	Parent name	string	CCL	100%	-	-
`parent_glottocode`	Parent glottocode	string	CCL	0%	6	amer1258, vehi1234, beta1260, stan1327, sing1270
`endangerment_status`	Endangerment status	string	CCL	100%	-	-
`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%	4	2, 0, 0, 3, 13

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

Field Name	Label	Type	Nulls	Unique	Samples
`latitude`	latitude	float	0%	8	33.8117, 1.75414, -12.193342, -7.33458, 1.85856
`longitude`	longitude	float	0%	8	-81.6121, 103.076, 96.833679, 109.716, 103.0
`country_codes`	Country codes	string	0%	7	['BB', 'BF', 'BJ', 'BO', 'CA', 'CD', 'CF', 'CI', 'CN',...
`classification`	classification	string	0%	1	[], [], [], [], []

SGP LandScan Global (ORNL) SGP-LANDSCAN Modeled Population

8 rows · 3 tables · 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)

SGP 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	SGP
`admin_level`	Admin level	string	SEL	0%	1	admin_0
`admin_name`	Admin name	string	SEL	0%	1	Singapore
`admin_code`	Admin code	string	SEL	0%	1	21272760B53444952688840
`area_sqkm`	Area sqkm	float	SEL	0%	1	722.939
`pop_2024`	Population count	integer	SEL	0%	1	5996748
`pop_density_2024`	Population density	float	SEL	0%	1	8294.96

1 Admin 1 — 1 table(s)

SGP LandScan - Population Admin1 (admin_1) — 5 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	SGP, SGP, SGP, SGP, SGP
`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%	5	CENTRAL REGION, NORTH-EAST REGION, WEST REGION, EAST...
`admin_code`	Admin code	string	SEL	0%	5	49756563B71725710252082, 49756563B55738899153180,...
`area_sqkm`	Area sqkm	float	SEL	0%	5	136.1565, 135.304, 256.3948, 113.0779, 138.5992
`pop_2024`	Population count	integer	SEL	0%	5	1400997, 1368675, 1351713, 1019729, 859512
`pop_density_2024`	Population density	float	SEL	0%	5	10289.61, 10115.55, 5272.0, 9017.93, 6201.42

Locality Locality — 1 table(s)

SGP LandScan - Cities (locality) — 2 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	SGP, SGP
`admin_level`	Admin level	string	SEL	0%	1	locality, locality
`admin_name`	Admin name	string	SEL	0%	2	Singapore, Sembawang
`admin_code`	Admin code	integer	SEL	0%	2	178, 345
`area_sqkm`	Area sqkm	float	SEL	0%	2	435.0684, 65.5594
`pop_2024`	Population count	integer	SEL	0%	2	5097847, 771900
`pop_density_2024`	Population density	float	SEL	0%	2	11717.35, 11774.06

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%	2	5117759, 960308
`landscan_vs_ghs_ratio`	landscan_vs_ghs_ratio	float	0%	2	0.996, 0.804

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

6 rows · 2 tables · 2026 NGA GEOnet Names Server (GNS) 0 1 2 3 4 SEL 12 CCL 20 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)

SGP NGA GNS - Language — 5 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	SGP, SGP, SGP, SGP, SGP
`gns_language_code`	gns_language_code	string	CCL	0%	5	eng, msa, ind, tgl, por
`gns_language_name`	gns_language_name	string	CCL	0%	5	English, Malay (generic), Indonesian, Tagalog, Portuguese
`gns_toponym_count`	gns_toponym_count	integer	CCL	0%	4	7, 4, 2, 1, 1
`gns_toponym_share_pct`	gns_toponym_share_pct	float	CCL	0%	4	46.6667, 26.6667, 13.3333, 6.6667, 6.6667
`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

SGP NGA GNS - Summary — 1 rows, 27 columns

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

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	country_code	string	SEL	0%	1	SGP
`admin_level`	admin_level	integer	SEL	0%	1	0
`gns_country_name`	gns_country_name	string	SEL	0%	1	Singapore
`gns_language_count`	gns_language_count	integer	CCL	0%	1	5
`gns_script_count`	gns_script_count	integer	CCL	0%	1	0
`gns_endonym_share_pct`	gns_endonym_share_pct	float	CCL	0%	1	99.9404
`gns_non_roman_name_count`	gns_non_roman_name_count	integer	CCL	0%	1	0

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

Field Name	Label	Type	Nulls	Unique	Samples
`gns_name_count`	gns_name_count	integer	0%	1	1677
`gns_feature_count`	gns_feature_count	integer	0%	1	1348
`gns_endonym_count`	gns_endonym_count	integer	0%	1	1676
`gns_exonym_count`	gns_exonym_count	integer	0%	1	1
`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_hypsographic`	gns_name_count_hypsographic	integer	0%	1	331
`gns_feature_count_hypsographic`	gns_feature_count_hypsographic	integer	0%	1	232
`gns_name_count_hydrographic`	gns_name_count_hydrographic	integer	0%	1	457
`gns_feature_count_hydrographic`	gns_feature_count_hydrographic	integer	0%	1	384
`gns_name_count_populated_places`	gns_name_count_populated_places	integer	0%	1	461
`gns_feature_count_populated_places`	gns_feature_count_populated_places	integer	0%	1	354
`gns_name_count_spot_features`	gns_name_count_spot_features	integer	0%	1	227
`gns_feature_count_spot_features`	gns_feature_count_spot_features	integer	0%	1	208
`gns_name_count_areas_localities`	gns_name_count_areas_localities	integer	0%	1	188
`gns_feature_count_areas_localities`	gns_feature_count_areas_localities	integer	0%	1	163
`gns_name_count_administrative_regions`	gns_name_count_administrative_regions	integer	0%	1	12
`gns_feature_count_administrative_regions`	gns_feature_count_administrative_regions	integer	0%	1	6
`gns_name_count_transportation_networks`	gns_name_count_transportation_networks	integer	0%	1	1
`gns_feature_count_transportation_networks`	gns_feature_count_transportation_networks	integer	0%	1	1

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

2 rows · 1 table · 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)

SGP GHS-UCDB - Cities (locality) — 2 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%	2	Singapore, Sembawang
`country_code`	Country code	string	SEL	0%	1	SGP, SGP
`population`	Population count	integer	SEL	0%	2	5117759, 960308

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

Field Name	Label	Type	Nulls	Unique	Samples
`city_id`	city_id	integer	0%	2	178, 345
`name_alternates`	name_alternates	string	100%	-	-
`country_name`	country_name	string	0%	1	Singapore, Singapore
`population_year`	population_year	integer	0%	1	2025, 2025
`latitude`	latitude	string	100%	-	-
`longitude`	longitude	string	100%	-	-
`region`	region	string	100%	-	-

SGP INFORM Risk Index (EC-JRC) SGP-INFORM Risk Index

1 row · 1 table · 2026 INFORM Risk Index (EC-JRC) 0 1 2 3 ▶

1 rows × 249 columns ingested. Field-level inventory in progress — contact us for the full export.

0 Admin 0 — 1 table(s)

SGP Inform - Risk Index — 1 rows, 249 columns

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Field details — 249 fields (type, nulls, unique, samples)

Pending (249) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	Country code (ISO 3166-1 alpha-3)	string	0%	1	SGP
`inform_aff_dr`	People affected by drought (absolute) - raw	float	0%	1	0.0
`inform_aff_dr_freq`	Frequency of Droughts events	float	0%	1	0.0
`inform_aff_dr_rel`	People affected by droughts (relative) - raw	float	0%	1	0.0
`inform_ag_lnd_totl_k2`	Land area (sq. km)	float	0%	1	700.0
`inform_asi`	Agriculture Stress Index Probability	float	0%	1	0.25
`inform_bx_trf_pwkr`	Personal remittances, received (% of GDP)	float	0%	1	0.0
`inform_lack_of_coping_capacity`	Lack of Coping Capacity Index	float	0%	1	0.8
`inform_infrastructure_capacity`	Infrastructure	float	0%	1	0.6
`inform_cc_inf_ahc`	Access to Health Care	float	0%	1	1.0
`inform_cc_inf_ahc_health_exp`	Health expenditure per capita [CC.INF.AHC.HEALTH-EXP]	float	0%	1	0.0
`inform_cc_inf_ahc_imm`	Immunization coverage	float	0%	1	0.9
`inform_cc_inf_ahc_imm_dtp3`	Diphtheria-Tetanus-Pertussis	float	0%	1	0.3
`inform_cc_inf_ahc_imm_mcv2`	Measles	float	0%	1	1.0
`inform_cc_inf_ahc_imm_pcv3`	Pneumococcal	float	0%	1	1.4
`inform_cc_inf_ahc_mmr`	Maternal Mortality Ratio [CC.INF.AHC.MMR]	float	0%	1	0.1
`inform_cc_inf_ahc_phys`	Physicians density [CC.INF.AHC.PHYS]	float	0%	1	2.9
`inform_cc_inf_com`	Communication	float	0%	1	0.7
`inform_cc_inf_com_cel`	Mobile cellular subscriptions [CC.INF.COM.CEL]	float	0%	1	1.5
`inform_cc_inf_com_elaccs`	Access to electricity [CC.INF.COM.ELACCS]	float	0%	1	0.0
`inform_cc_inf_com_litr`	Adult literacy rate	float	0%	1	0.5
`inform_cc_inf_com_netus`	Internet users [CC.INF.COM.NETUS]	float	0%	1	0.6
`inform_cc_inf_phy`	Physical Infrastructure	float	0%	1	0.0
`inform_cc_inf_phy_h2o`	Access to improved water source	float	0%	1	0.0
`inform_cc_inf_phy_rod`	Road density [CC.INF.PHY.ROD]	float	0%	1	0.0
`inform_cc_inf_phy_sta`	Access to improved sanitation facilities	float	0%	1	0.0
`inform_institutional_capacity`	Institutional	float	0%	1	1.0
`inform_cc_ins_gov`	Governance	float	0%	1	1.0
`inform_cc_ins_gov_cpi`	Corruption Perception Index [CC.INS.GOV.CPI]	float	0%	1	1.6
`inform_cc_ins_gov_ge`	Government Effectiveness [CC.INS.GOV.GE]	float	0%	1	0.4
+219 more pending fields — download the CSV/Parquet to see them all.

HERA · Human Entity Reference Atlas by Masego Inc

Build a download

Language	Place names	Share*	Script
English (eng)	7	46.7%	—
Malay (generic) (msa)	4	26.7%	—
Indonesian (ind)	2	13.3%	—
Tagalog (tgl)	1	6.7%	—
Portuguese (por)	1	6.7%	—

Source	Type	Access
Department of Statistics Singapore (SingStat)	official_api	api
HDX (Humanitarian Data Exchange)	international_organization	bulk_download
INFORM Risk Index (EC-JRC)	international_organization	api
Glottolog Language Catalog	academic	bulk_download
World Bank Open Data	international_organization	api
UNHCR Refugee Data Finder (UN High Commissioner for Refugees)	international_organization	api
NGA GEOnet Names Server (GNS)	official_government	bulk_download
GHS Urban Centre Database (Global Human Settlement · EU Joint Research Centre)	international_organization	bulk_download
LandScan Global (ORNL — Oak Ridge National Laboratory)	research_institution	earth_engine
OpenFactBook	community_compilation	bulk_download