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

Official website links end with .gov.sg

Government agencies communicate via .gov.sg websites (e.g. go.gov.sg/open). Trusted websites

Secure websites use HTTPS

Look for a lock () or https:// as an added precaution. Share sensitive information only on official, secure websites.

Scam alert

Government officers will never ask you to send money or share your details over the phone. When unsure, hang up and call Scamshield at 1799.

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%
Dover	11080	350	540	650	630	650	670	550	690	890	950	910	820	700	610	620	370	310	130	60	5260	200	280	340	310	310	350	260	310	420	430	440	410	320	270	260	160	140	50	20	5820	160	270	310	320	340	320	300	380	470	520	470	410	380	330	360	210	170	90	50
Ghim Moh	13850	850	660	560	500	590	790	1310	1110	910	890	800	860	820	800	910	590	470	290	130	6470	470	340	270	250	300	350	580	580	420	440	380	430	350	340	370	240	200	120	40	7380	380	320	290	250	290	440	730	530	490	450	420	430	470	460	550	350	280	170	90
Holland Drive	12680	350	350	360	470	540	800	830	730	910	1070	970	950	850	860	910	670	570	300	180	5760	180	200	180	250	250	410	390	330	410	520	450	430	390	350	370	250	220	130	70	6920	180	160	190	220	290	390	440	390	500	550	520	520	470	510	540	420	350	170	110
Kent Ridge	80	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
Margaret Drive	16090	1120	1200	800	570	590	860	1260	1990	1570	1130	890	850	790	740	690	380	330	210	130	7710	560	650	420	300	300	410	540	940	770	590	430	430	380	310	300	170	140	60	30	8380	560	550	380	270	290	450	720	1060	800	540	470	420	410	430	390	210	200	140	100
Mei Chin	15570	460	540	700	800	920	1120	960	870	980	1190	1250	1300	1220	1030	780	510	480	300	170	7350	250	270	360	400	470	540	450	390	430	580	580	640	600	520	360	190	190	110	50	8210	210	270	350	400	450	580	510	480	550	610	670	660	620	510	430	320	290	190	120
National University Of S'pore	240	-	10	10	10	120	30	20	10	10	20	10	10	-	-	-	-	-	-	-	70	-	-	-	-	10	10	10	-	-	10	-	10	-	-	-	-	-	-	-	170	-	-	-	10	110	20	10	-	10	10	-	10	-	-	-	-	-	-	-
One North	720	40	60	50	30	20	30	40	100	80	100	80	40	20	20	10	-	-	-	-	350	20	30	20	10	10	10	20	50	40	50	50	30	10	10	10	-	-	-	-	370	20	30	30	20	20	20	30	50	40	50	30	10	10	10	10	-	-	-	-
Pasir Panjang 1	4510	160	190	240	260	270	350	310	340	410	410	350	340	280	240	180	80	60	40	10	2200	80	100	120	130	130	180	160	160	190	200	160	180	140	120	100	40	30	20	-	2300	80	90	120	140	150	170	150	180	220	200	190	160	150	120	90	40	30	20	10
Pasir Panjang 2	3060	90	130	140	160	200	250	180	180	210	210	240	250	230	280	160	70	50	10	20	1490	50	60	60	80	90	130	90	90	100	100	120	120	100	150	90	40	20	10	10	1570	40	70	80	80	110	120	90	90	110	110	120	130	130	130	80	30	30	10	10

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) (2026) [Dataset]. data.gov.sg. Retrieved June 18, 2026 from https://data.gov.sg/datasets/d_d95ae740c0f8961a0b10435836660ce0/view

Data explorer

ResidentPopulationbyPlanningAreaSubzoneofResidenceAgeGroupandSexCensusofPopulation2020.csv (388 rows, 130.3 KB)

Column legend

Analyse this dataset with Colab Notebook

Sample OpenAPI query

Citation

About this dataset

Contact

Created on

Licence

Agency

Column legend