Resident Labour Force Aged 15 Years and Over by Age Group, Marital Status, Sex and Ethnic Group (Census of Population 2020)
What this data shows
Published by Singapore Department of Statistics. 13 records. Fields include Number, [Total] (Total) Total, [Total] (Total) Males, [Total] (Total) Females (76 columns in total). Last updated 2026-09-06.
Description
Census of Population 2020 resident labour force aged 15 and over cross-classified by age group, marital status, sex, and ethnic group in CSV from the Singapore Department of Statistics. Labour demographers study participation patterns across marriage and ethnicity.
Official description
Source: SINGAPORE DEPARTMENT OF STATISTICS Data Last Updated: 18/06/2021 Update Frequency: 10 years Survey period: Census of Population 2020 Adapted from: https://tablebuilder.singstat.gov.sg/table/CT/17542
- Last updated
- Rows
- 13
- Columns
- 76
Chart
Values are summed where multiple rows share the same category.
Data
| Number | [Total] (Total) Total | [Total] (Total) Males | [Total] (Total) Females | [Total] (Single) Total | [Total] (Single) Males | [Total] (Single) Females | [Total] (Married) Total | [Total] (Married) Males | [Total] (Married) Females | [Total] (Widowed) Total | [Total] (Widowed) Males |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Total | 2343485.000000 | 1246136.000000 | 1097349.000000 | 700470.000000 | 355360.000000 | 345110.000000 | 1483614.000000 | 835423.000000 | 648190.000000 | 44614 | 10958 |
| 15 - 19 | 31862.000000 | 19493.000000 | 12369.000000 | 31745.000000 | 19472.000000 | 12273.000000 | 117.000000 | 22.000000 | 96.000000 | - | - |
| 20 - 24 | 135781.000000 | 69583.000000 | 66198.000000 | 130595.000000 | 67739.000000 | 62856.000000 | 4753.000000 | 1772.000000 | 2981.000000 | - | - |
| 25 - 29 | 257407.000000 | 125827.000000 | 131580.000000 | 193629.000000 | 100483.000000 | 93147.000000 | 61555.000000 | 24639.000000 | 36916.000000 | 57 | 12 |
| 30 - 34 | 275450.000000 | 136187.000000 | 139263.000000 | 104040.000000 | 55303.000000 | 48737.000000 | 165260.000000 | 78750.000000 | 86509.000000 | 156 | 61 |
| 35 - 39 | 269204.000000 | 135110.000000 | 134094.000000 | 57977.000000 | 29328.000000 | 28649.000000 | 198785.000000 | 101091.000000 | 97695.000000 | 658 | 113 |
| 40 - 44 | 264607.000000 | 134519.000000 | 130088.000000 | 45486.000000 | 21106.000000 | 24380.000000 | 202773.000000 | 107631.000000 | 95142.000000 | 1158 | 219 |
| 45 - 49 | 270198.000000 | 144148.000000 | 126050.000000 | 40492.000000 | 18659.000000 | 21833.000000 | 208302.000000 | 117905.000000 | 90397.000000 | 2590 | 447 |
| 50 - 54 | 241146.000000 | 132845.000000 | 108301.000000 | 31380.000000 | 14787.000000 | 16593.000000 | 187099.000000 | 109902.000000 | 77196.000000 | 3697 | 829 |
| 55 - 59 | 228725.000000 | 128961.000000 | 99764.000000 | 27912.000000 | 12678.000000 | 15235.000000 | 176196.000000 | 107745.000000 | 68451.000000 | 6950 | 1482 |
Preview shows 10 rows and 12 columns. Use the table search or download the CSV for the full data.
Columns
| Column | Type | Categorical |
|---|---|---|
| Number | Text | No |
| [Total] (Total) Total | Numeric | No |
| [Total] (Total) Males | Numeric | No |
| [Total] (Total) Females | Numeric | No |
| [Total] (Single) Total | Numeric | No |
| [Total] (Single) Males | Numeric | No |
| [Total] (Single) Females | Numeric | No |
| [Total] (Married) Total | Numeric | No |
| [Total] (Married) Males | Numeric | No |
| [Total] (Married) Females | Numeric | No |
| [Total] (Widowed) Total | Text | No |
| [Total] (Widowed) Males | Text | No |
| [Total] (Widowed) Females | Text | No |
| [Total] (Divorced/Separated) Total | Text | No |
| [Total] (Divorced/Separated) Males | Text | No |
| [Total] (Divorced/Separated) Females | Text | No |
| [Chinese] (Total) Total | Numeric | No |
| [Chinese] (Total) Males | Numeric | No |
| [Chinese] (Total) Females | Numeric | No |
| [Chinese] (Single) Total | Numeric | No |
| [Chinese] (Single) Males | Numeric | No |
| [Chinese] (Single) Females | Numeric | No |
| [Chinese] (Married) Total | Numeric | No |
| [Chinese] (Married) Males | Numeric | No |
| [Chinese] (Married) Females | Numeric | No |
| [Chinese] (Widowed) Total | Text | No |
| [Chinese] (Widowed) Males | Text | No |
| [Chinese] (Widowed) Females | Text | No |
| [Chinese] (Divorced/Separated) Total | Text | No |
| [Chinese] (Divorced/Separated) Males | Text | No |
| [Chinese] (Divorced/Separated) Females | Text | No |
| [Malays] (Total) Total | Numeric | No |
| [Malays] (Total) Males | Numeric | No |
| [Malays] (Total) Females | Numeric | No |
| [Malays] (Single) Total | Numeric | No |
| [Malays] (Single) Males | Numeric | No |
| [Malays] (Single) Females | Numeric | No |
| [Malays] (Married) Total | Numeric | No |
| [Malays] (Married) Males | Text | No |
| [Malays] (Married) Females | Numeric | No |
| [Malays] (Widowed) Total | Text | No |
| [Malays] (Widowed) Males | Text | No |
| [Malays] (Widowed) Females | Text | No |
| [Malays] (Divorced/Separated) Total | Text | No |
| [Malays] (Divorced/Separated) Males | Text | No |
| [Malays] (Divorced/Separated) Females | Text | No |
| [Indians] (Total) Total | Numeric | No |
| [Indians] (Total) Males | Numeric | No |
| [Indians] (Total) Females | Numeric | No |
| [Indians] (Single) Total | Numeric | No |
| [Indians] (Single) Males | Numeric | No |
| [Indians] (Single) Females | Numeric | No |
| [Indians] (Married) Total | Numeric | No |
| [Indians] (Married) Males | Numeric | No |
| [Indians] (Married) Females | Text | No |
| [Indians] (Widowed) Total | Text | No |
| [Indians] (Widowed) Males | Text | No |
| [Indians] (Widowed) Females | Text | No |
| [Indians] (Divorced/Separated) Total | Text | No |
| [Indians] (Divorced/Separated) Males | Text | No |
Showing the first 60 of 76 columns. Download the CSV for the full schema.