Singapore

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

228 rows · 3 table(s) · 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(s) · 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 — 1966 fields (type, nulls, unique, samples)

Extension Fields (1966) — 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
+1936 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(s) · 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(s) · 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 — 869 fields (type, nulls, unique, samples)

Extension Fields (869) — 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
+839 more extension fields — download the CSV/Parquet to see them all.

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

4,164 rows · 1 table(s) · 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 — 155 fields (type, nulls, unique, samples)

Extension Fields (155) — 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
+125 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(s) · 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 — 91 fields (type, nulls, unique, samples)

Extension Fields (91) — 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
+61 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(s) · 2024 HDX 0 1 2 3 ▶

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

0 Admin 0 — 1 table(s)

SGP Singapore - Human Development Indicators — 958 rows, 36 columns

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Field details — 36 fields (type, nulls, unique, samples)

Extension Fields (36) — 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
+6 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(s) · 2024 HDX 0 1 2 3 ▶

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

0 Admin 0 — 1 table(s)

SGP Singapore - Urban Development — 642 rows, 18 columns

Loading data…

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

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

Field Name	Label	Type	Nulls	Unique	Samples
`country_code`	country_code	string	0%	1	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

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

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

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

0 Admin 0 — 1 table(s)

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

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)

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

Loading data…

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

Standards-Aligned Fields (12)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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 UNHCR Refugee Data Finder SGP-UNHCR Migration

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

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

0 Admin 0 — 2 table(s)

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

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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%	-	-

SGP Global Data Lab SGP-GDL Development Indices

34 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)

SGP GDL - Subnational Indices — 34 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	SGP, SGP, SGP, SGP, SGP
`region_code`	Admin code	string	SEL	100%	-	-
`region_name`	Admin name	string	SEL	0%	1	Total, Total, Total, Total, Total
`human_development_index`	Human development index	float	SEL	0%	30	0.892, 0.896, 0.901, 0.905, 0.911
`health_index`	Health index	float	SEL	0%	32	0.84, 0.847, 0.851, 0.854, 0.856
`education_index`	Education index	float	SEL	0%	29	0.912, 0.914, 0.916, 0.918, 0.92
`income_index`	Income index	float	SEL	0%	15	0.925, 0.93, 0.938, 0.946, 0.961
`life_expectancy`	Life expectancy	float	SEL	0%	33	74.6, 75.06, 75.33, 75.53, 75.63
`mean_years_schooling`	Mean years schooling	float	SEL	0%	28	13.67, 13.71, 13.74, 13.77, 13.8

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

Field Name	Label	Type	Nulls	Unique	Samples
`year`	year	integer	0%	34	1990, 1991, 1992, 1993, 1994
`level`	level	string	0%	1	national, national, national, national, national

SGP OpenFactBook SGP-OPENFACTBOOK Country Profile

15 rows · 15 table(s) · 2024 OpenFactBook 0 1 2 3 95 SEL 6 CCL 550 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 (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	33.0
`telephones_mobile_cellular_subscriptions_per_100_inhabitants_numeric`	Mobile subscriptions per 100	float	SEL	0%	1	171.0
`internet_country_code_text`	Internet country code text	string	SEL+	0%	1	.sg
`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 (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	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_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 (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	9V
`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 (23) — 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	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(s) · 2024 Glottolog Language Catalog 0 1 2 3 1 SEL 12 CCL 3 ext ▶

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

0 Admin 0 — 1 table(s)

SGP Glottolog - Languages — 8 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%	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%	-	-
`country_codes`	Country codes	string	SEL+	0%	7	['BB', 'BF', 'BJ', 'BO', 'CA', 'CD', 'CF', 'CI', 'CN',...
`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 (3) — 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
`classification`	classification	string	0%	1	[], [], [], [], []

SGP LandScan Global (ORNL) SGP-LANDSCAN Modeled Population

8 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)

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

Loading data…

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

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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

Loading data…

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

Standards-Aligned Fields (7)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	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 table(s) · 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

Loading data…

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

Loading data…

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 Ethnic Power Relations Dataset SGP-EPR Political Ethnicity

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

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

0 Admin 0 — 1 table(s)

SGP EPR - Groups — 4 rows, 8 columns

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

Standards-Aligned Fields (6)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	SGP, SGP, SGP, SGP
`ethnic_group_name`	Ethnic group name	string	CCL	0%	4	Chinese, Malays, Indians, Eurasians and Others
`ethnic_power_status`	Ethnic power status	string	CCL	0%	2	SENIOR PARTNER, JUNIOR PARTNER, JUNIOR PARTNER, JUNIOR PARTNER
`ethnic_population_share`	Ethnic population share	float	CCL	0%	4	0.48, 0.095, 0.046, 0.009
`ethnic_group_id`	Ethnic group id	float	CCL	0%	4	83001000, 83002000, 83003000, 83004000
`regional_autonomy`	Regional autonomy	string	CCL	0%	1	false, false, false, false

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

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

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

2 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)

SGP GHS-UCDB - Cities (locality) — 2 rows, 10 columns

Loading data…

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

Standards-Aligned Fields (3)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`city_name`	Admin name	string	SEL	0%	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 Global Organized Crime Index SGP-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)

SGP Organized Crime Scores 2025 — 1 rows, 35 columns

Loading data…

Field details — 139 fields (type, nulls, unique, samples)

Standards-Aligned Fields (13)

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

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

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

Pending (104) — awaiting mapping

Field Name	Label	Type	Nulls	Unique	Samples
`iso3`	iso3	string	0%	1	SGP
`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	7
`oc_anti_money_laundering_2023`	oc_anti_money_laundering_2023	float	0%	1	7.5
`oc_anti_money_laundering_2021`	oc_anti_money_laundering_2021	integer	0%	1	7
`oc_arms_trafficking_rank`	oc_arms_trafficking_rank	integer	0%	1	161
`oc_arms_trafficking_2023`	oc_arms_trafficking_2023	float	0%	1	2.5
`oc_arms_trafficking_2021`	oc_arms_trafficking_2021	integer	0%	1	2
`oc_cannabis_trade_rank`	oc_cannabis_trade_rank	integer	0%	1	159
`oc_cannabis_trade_2023`	oc_cannabis_trade_2023	float	0%	1	3.5
`oc_cannabis_trade_2021`	oc_cannabis_trade_2021	integer	0%	1	2
`oc_cocaine_trade_rank`	oc_cocaine_trade_rank	integer	0%	1	164
`oc_cocaine_trade_2023`	oc_cocaine_trade_2023	integer	0%	1	3
`oc_cocaine_trade_2021`	oc_cocaine_trade_2021	integer	0%	1	3
`oc_criminal_actors_rank`	oc_criminal_actors_rank	integer	0%	1	171
`oc_criminal_actors_2023`	oc_criminal_actors_2023	integer	0%	1	3
`oc_criminal_actors_2021`	oc_criminal_actors_2021	integer	0%	1	3
`oc_criminal_markets_rank`	oc_criminal_markets_rank	integer	0%	1	146
`oc_criminal_markets_2023`	oc_criminal_markets_2023	float	0%	1	3.93
`oc_criminal_markets_2021`	oc_criminal_markets_2021	float	0%	1	3.25
`oc_criminal_networks_rank`	oc_criminal_networks_rank	integer	0%	1	120
`oc_criminal_networks_2023`	oc_criminal_networks_2023	integer	0%	1	4
`oc_criminal_networks_2021`	oc_criminal_networks_2021	float	0%	1	3.5
`oc_criminality_rank`	oc_criminality_rank	integer	0%	1	163
`oc_criminality_2023`	oc_criminality_2023	float	0%	1	3.47
`oc_criminality_2021`	oc_criminality_2021	float	0%	1	3.13
`oc_cyber_dependent_crimes_rank`	oc_cyber_dependent_crimes_rank	integer	0%	1	23
+74 more pending fields — download the CSV/Parquet to see them all.

SGP World Values Survey SGP-WVS Attitudes Values

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

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

0 Admin 0 — 1 table(s)

SGP WVS - Country Aggregates — 1 rows, 26 columns

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Field details — 26 fields (type, nulls, unique, samples)

Standards-Aligned Fields (1)

Field Name	Label	Type	Schema	Nulls	Unique	Samples
`country_code`	Country code	string	SEL	0%	1	SGP

Extension Fields (25) — supplemental data preserved outside core SEL/CCL schema

Field Name	Label	Type	Nulls	Unique	Samples
`wave`	wave	integer	0%	1	7
`wave_years`	wave_years	string	0%	1	2017-2022
`source`	source	string	0%	1	World Values Survey
`importance_religion`	importance_religion	integer	0%	1	1
`importance_family`	importance_family	integer	0%	1	1
`importance_friends`	importance_friends	integer	0%	1	1
`trust_people`	trust_people	integer	0%	1	1
`trust_family`	trust_family	integer	0%	1	1
`life_satisfaction`	life_satisfaction	integer	0%	1	1
`happiness`	happiness	integer	0%	1	1
`freedom_choice`	freedom_choice	integer	0%	1	1
`gender_jobs_scarce`	gender_jobs_scarce	integer	0%	1	1
`gender_political_leaders`	gender_political_leaders	integer	0%	1	1
`gender_university`	gender_university	integer	0%	1	1
`justifiable_divorce`	justifiable_divorce	integer	0%	1	1
`justifiable_homosexuality`	justifiable_homosexuality	integer	0%	1	1
`immigration_policy`	immigration_policy	integer	0%	1	1
`immigrants_jobs`	immigrants_jobs	integer	0%	1	1
`immigrants_culture`	immigrants_culture	integer	0%	1	1
`confidence_government`	confidence_government	integer	0%	1	1
`confidence_parliament`	confidence_parliament	integer	0%	1	1
`confidence_police`	confidence_police	integer	0%	1	1
`confidence_courts`	confidence_courts	integer	0%	1	1
`confidence_press`	confidence_press	integer	0%	1	1
`democracy_importance`	democracy_importance	integer	0%	1	1

HERA · Human Entity Reference Atlas by Masego Inc

Build a download

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
GI-TOC / ENACT (Global Initiative Against Transnational Organized Crime · ENACT)	academic	bulk_download
World Values Survey	academic	metadata_catalog
Ethnic Power Relations Dataset	academic	bulk_download
NGA GEOnet Names Server (GNS)	official_government	bulk_download
Global Data Lab	academic	api
World Bank Open Data	international_organization	api
UNHCR Refugee Data Finder (UN High Commissioner for Refugees)	international_organization	api
Glottolog Language Catalog	academic	bulk_download
GHS Urban Centre Database (Global Human Settlement · EU Joint Research Centre)	international_organization	bulk_download
LandScan Global (ORNL — Oak Ridge National Laboratory)	research_institution	earth_engine
OpenFactBook	community_compilation	bulk_download