Resident Population by Planning Area/Subzone of Residence, Age Group and Sex (Census of Population 2020)

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Data explorer

ResidentPopulationbyPlanningAreaSubzoneofResidenceAgeGroupandSexCensusofPopulation2020.csv (388 rows, 130.3 KB)

Number Text	(Total) Total Text	(Total) 0 - 4 Text	(Total) 5 - 9 Text	(Total) 10 - 14 Text	(Total) 15 - 19 Text	(Total) 20 - 24 Text	(Total) 25 - 29 Text	(Total) 30 - 34 Text	(Total) 35 - 39 Text	(Total) 40 - 44 Text	(Total) 45 - 49 Text	(Total) 50 - 54 Text	(Total) 55 - 59 Text	(Total) 60 - 64 Text	(Total) 65 - 69 Text	(Total) 70 - 74 Text	(Total) 75 - 79 Text	(Total) 80 - 84 Text	(Total) 85 - 89 Text	(Total) 90 & Over Text	(Males) Total Text	(Males) 0 - 4 Text	(Males) 5 - 9 Text	(Males) 10 - 14 Text	(Males) 15 - 19 Text	(Males) 20 - 24 Text	(Males) 25 - 29 Text	(Males) 30 - 34 Text	(Males) 35 - 39 Text	(Males) 40 - 44 Text	(Males) 45 - 49 Text	(Males) 50 - 54 Text	(Males) 55 - 59 Text	(Males) 60 - 64 Text	(Males) 65 - 69 Text	(Males) 70 - 74 Text	(Males) 75 - 79 Text	(Males) 80 - 84 Text	(Males) 85 - 89 Text	(Males) 90 & Over Text	(Females) Total Text	(Females) 0 - 4 Text	(Females) 5 - 9 Text	(Females) 10 - 14 Text	(Females) 15 - 19 Text	(Females) 20 - 24 Text	(Females) 25 - 29 Text	(Females) 30 - 34 Text	(Females) 35 - 39 Text	(Females) 40 - 44 Text	(Females) 45 - 49 Text	(Females) 50 - 54 Text	(Females) 55 - 59 Text	(Females) 60 - 64 Text	(Females) 65 - 69 Text	(Females) 70 - 74 Text	(Females) 75 - 79 Text	(Females) 80 - 84 Text	(Females) 85 - 89 Text	(Females) 90 & Over Text
(Null)0.0%	(Null)13.4%	(Null)30.7%	(Null)30.7%	(Null)30.4%	(Null)30.4%	(Null)29.6%	(Null)28.9%	(Null)29.9%	(Null)28.9%	(Null)29.4%	(Null)29.1%	(Null)29.1%	(Null)29.1%	(Null)29.4%	(Null)29.6%	(Null)30.4%	(Null)33.5%	(Null)34.3%	(Null)36.3% 106.2% 203.1% 402.8% 1202.6%	(Null)36.6% 107.0% 204.4% 303.6% 603.9%	(Null)28.6%	(Null)33.2%	(Null)32.2%	(Null)32.5%	(Null)33.0%	(Null)32.5%	(Null)32.2%	(Null)30.9%	(Null)30.2%	(Null)29.9%	(Null)29.1%	(Null)30.4%	(Null)29.9%	(Null)30.7%	(Null)30.9%	(Null)32.2%	(Null)35.6%	(Null)37.1% 105.4% 204.1% 403.4% 1303.1%	(Null)39.9% 108.0% 205.2% 405.4% 605.4%	(Null)43.0% 1012.1% 209.5% 3010.3% 405.7%	(Null)28.6%	(Null)32.5%	(Null)33.0%	(Null)32.2%	(Null)31.4%	(Null)30.9%	(Null)31.2%	(Null)30.9%	(Null)30.2%	(Null)30.4%	(Null)30.2%	(Null)29.9%	(Null)29.6%	(Null)31.2%	(Null)32.2%	(Null)32.2%	(Null)35.6%	(Null)36.1%	(Null)38.7% 107.0% 203.4% 803.4% 1104.1%	(Null)39.7% 108.2% 204.6% 504.9% 605.2%
Total	4044210	183080	198740	206390	215230	244540	287000	297800	299520	299290	311740	296070	305830	284630	229400	170010	90990	66510	36590	20880	1977560	93390	101730	104970	109870	124620	142380	143020	141360	142800	151690	145380	152960	141470	112610	80820	40770	27890	13520	6310	2066650	89690	97010	101430	105370	119920	144620	154780	158160	156490	160050	150690	152870	143160	116790	89190	50220	38630	23060	14560
Ang Mo Kio - Total	162280	5280	6100	7030	7600	8680	10320	10490	10420	11350	12410	11860	12780	12730	11960	9930	5770	4150	2280	1130	77570	2710	3020	3590	3870	4410	5100	5030	4890	5270	5910	5720	6330	6090	5480	4570	2570	1800	890	320	84700	2570	3080	3440	3730	4280	5220	5460	5530	6070	6500	6140	6450	6650	6480	5350	3200	2350	1390	810
Ang Mo Kio Town Centre	4810	170	240	280	320	270	280	290	330	400	470	370	320	300	250	230	140	100	40	20	2260	90	130	120	160	130	140	130	140	180	230	190	160	140	110	100	60	40	10	10	2550	80	110	160	160	140	140	170	190	230	250	180	150	160	140	130	80	60	30	20
Cheng San	28070	1060	1040	1040	1160	1330	1710	2000	2150	2070	2200	2050	2120	2120	2170	1730	960	640	350	180	13480	570	540	570	600	710	850	920	1000	980	1060	1000	1060	960	960	820	420	290	130	50	14600	490	510	470	560	620	860	1080	1140	1090	1140	1050	1060	1170	1210	920	540	360	210	130
Chong Boon	26500	860	840	1010	1060	1310	1610	1890	1730	1800	1820	1900	2090	2140	2100	1800	1130	780	430	200	12860	450	450	550	590	700	790	920	830	840	880	910	1050	1040	970	820	520	340	180	60	13640	420	400	470	470	610	820	980	910	960	940	990	1040	1110	1130	990	610	440	250	140
Kebun Bahru	22620	660	810	950	1010	1170	1420	1410	1450	1620	1790	1710	1800	1750	1690	1430	840	620	340	160	10660	310	340	460	480	600	670	660	660	770	850	830	930	830	790	640	370	280	150	50	11970	350	470	490	530	570	740	740	780	860	940	890	870	920	910	790	470	350	190	110
Sembawang Hills	6850	210	310	400	460	500	500	350	310	370	550	540	550	480	410	370	230	150	100	60	3210	110	130	180	220	240	240	170	130	170	260	270	260	250	190	170	100	70	40	30	3650	100	190	220	240	260	260	190	180	210	290	270	300	220	220	200	130	80	60	40
Shangri-La	15960	550	560	640	710	860	980	1020	990	1010	1210	1200	1390	1270	1180	960	620	430	250	130	7780	300	290	330	390	430	500	500	490	490	590	580	730	630	570	410	250	180	90	30	8180	260	270	310	320	430	480	520	500	530	620	620	660	640	610	550	370	250	170	100
Tagore	7950	210	310	400	450	580	670	490	340	440	580	580	670	730	550	380	210	190	120	60	3790	100	140	210	210	270	350	260	160	180	250	270	300	350	280	200	100	90	50	20	4160	110	170	190	250	310	320	240	180	250	330	310	360	380	270	180	110	100	70	50
Townsville	21140	660	860	930	820	890	1310	1400	1410	1650	1560	1360	1580	1660	1530	1420	880	680	360	190	9930	320	470	490	430	440	640	700	640	770	750	650	760	780	660	620	370	280	130	50	11210	340	400	430	390	450	670	710	770	880	810	710	820	880	860	810	510	400	230	140

Column legend

Title	Column name	Data type	Unit of measure	Description
Number	Number	Text	Number	-
(Total) Total	Total_Total	Text	Number	-
(Total) 0 - 4	Total_0_4	Text	Number	-
(Total) 5 - 9	Total_5_9	Text	Number	-
(Total) 10 - 14	Total_10_14	Text	Number	-
(Total) 15 - 19	Total_15_19	Text	Number	-
(Total) 20 - 24	Total_20_24	Text	Number	-
(Total) 25 - 29	Total_25_29	Text	Number	-
(Total) 30 - 34	Total_30_34	Text	Number	-
(Total) 35 - 39	Total_35_39	Text	Number	-

Sample OpenAPI query

This code can be used to test a sample API query. It retrieves the data catalogue of this dataset. For a complete guide on query parameters and syntax, please refer to the API documentation. Try it out on your browser to see the response schema.

import requests
          
dataset_id = "d_d95ae740c0f8961a0b10435836660ce0"
url = "https://data.gov.sg/api/action/datastore_search?resource_id="  + dataset_id 
        
response = requests.get(url)
print(response.json())

Citation

This dataset can be reused and cited in research publications.

Singapore Department of Statistics. (2024). Resident Population by Planning Area/Subzone of Residence, Age Group and Sex (Census of Population 2020) (2025) [Dataset]. data.gov.sg. Retrieved July 22, 2025 from https://data.gov.sg/datasets/d_d95ae740c0f8961a0b10435836660ce0/view

Data explorer

ResidentPopulationbyPlanningAreaSubzoneofResidenceAgeGroupandSexCensusofPopulation2020.csv (388 rows, 130.3 KB)

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Sample OpenAPI query

Citation

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