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Updated 24 days ago
SINGSTAT (Singapore Department of Statistics)Source: SINGAPORE DEPARTMENT OF STATISTICS
Data Last Updated: 09/03/2016
Update Frequency: 10 years
Survey period: General Household Survey 2015
Footnotes: Notes:Data exclude working persons who were overseas for more than 6 months.Income from work includes employer CPF contributions.
Adapted from: https://tablebuilder.singstat.gov.sg/table/CT/8343
Thousands Text | (Total) Total Numeric | (Total) Males Numeric | (Total) Females Numeric | (Below $1,000) Total Numeric | (Below $1,000) Males Numeric | (Below $1,000) Females Numeric | ($1,000 - $1,999) Total Numeric | ($1,000 - $1,999) Males Numeric | ($1,000 - $1,999) Females Numeric | ($2,000 - $2,999) Total Numeric | ($2,000 - $2,999) Males Numeric | ($2,000 - $2,999) Females Numeric | ($3,000 - $3,999) Total Numeric | ($3,000 - $3,999) Males Numeric | ($3,000 - $3,999) Females Numeric | ($4,000 - $4,999) Total Numeric | ($4,000 - $4,999) Males Numeric | ($4,000 - $4,999) Females Numeric | ($5,000 - $5,999) Total Numeric | ($5,000 - $5,999) Males Numeric | ($5,000 - $5,999) Females Numeric | ($6,000 - $6,999) Total Numeric | ($6,000 - $6,999) Males Numeric | ($6,000 - $6,999) Females Numeric | ($7,000 - $7,999) Total Numeric | ($7,000 - $7,999) Males Numeric | ($7,000 - $7,999) Females Numeric | ($8,000 - $8,999) Total Numeric | ($8,000 - $8,999) Males Numeric | ($8,000 - $8,999) Females Numeric | ($9,000 - $9,999) Total Numeric | ($9,000 - $9,999) Males Numeric | ($9,000 - $9,999) Females Numeric | ($10,000 - $10,999) Total Numeric | ($10,000 - $10,999) Males Numeric | ($10,000 - $10,999) Females Numeric | ($11,000 - $11,999) Total Numeric | ($11,000 - $11,999) Males Numeric | ($11,000 - $11,999) Females Numeric | ($12,000 - $12,999) Total Numeric | ($12,000 - $12,999) Males Numeric | ($12,000 - $12,999) Females Numeric | ($13,000 - $13,999) Total Numeric | ($13,000 - $13,999) Males Numeric | ($13,000 - $13,999) Females Numeric | ($14,000 - $14,999) Total Numeric | ($14,000 - $14,999) Males Numeric | ($14,000 - $14,999) Females Numeric | ($15,000 - $17,499) Total Numeric | ($15,000 - $17,499) Males Numeric | ($15,000 - $17,499) Females Numeric | ($17,500 - $19,999) Total Numeric | ($17,500 - $19,999) Males Numeric | ($17,500 - $19,999) Females Numeric | (20,000 & Over) Total Numeric | (20,000 & Over) Males Numeric | (20,000 & Over) Females Numeric |
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(Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% | (Null)0.0% |
Total | 2147.8 | 1171.8 | 976 | 25.2 | 12.3 | 12.9 | 79.1 | 45.9 | 33.2 | 94.9 | 54.3 | 40.6 | 100.7 | 57 | 43.7 | 119.9 | 67.5 | 52.4 | 123.7 | 67.8 | 55.9 | 137.7 | 75.9 | 61.8 | 132.4 | 73.9 | 58.6 | 135 | 72.8 | 62.3 | 125.5 | 66.5 | 59 | 113.6 | 62.1 | 51.6 | 107 | 57.1 | 49.9 | 97.9 | 52.3 | 45.6 | 85.1 | 45.1 | 40 | 79.2 | 43 | 36.1 | 149.2 | 79.8 | 69.4 | 111.5 | 59.6 | 51.9 | 330.3 | 179 | 151.2 |
Public Bus Only | 353.6 | 155.3 | 198.4 | 7 | 2.8 | 4.2 | 24.3 | 12.3 | 12 | 24 | 11 | 13 | 23.1 | 10.8 | 12.3 | 25.1 | 11.6 | 13.5 | 24.4 | 10.8 | 13.6 | 27.8 | 12.5 | 15.3 | 27.3 | 12.5 | 14.8 | 23.1 | 9.1 | 14 | 20.1 | 8.3 | 11.8 | 17 | 7 | 10 | 18.3 | 8.1 | 10.2 | 13.2 | 5.8 | 7.3 | 12.5 | 4.7 | 7.8 | 10.6 | 4.5 | 6.1 | 16.9 | 6.8 | 10.2 | 12.4 | 5.3 | 7.1 | 26.6 | 11.4 | 15.1 |
MRT Only | 257.7 | 110.4 | 147.3 | 2.4 | 1.1 | 1.3 | 6.8 | 3.1 | 3.7 | 8.8 | 4.7 | 4.1 | 11.7 | 5.6 | 6.1 | 13.2 | 6.4 | 6.8 | 14 | 6.2 | 7.9 | 16.8 | 7.3 | 9.5 | 14.7 | 6.8 | 7.9 | 17.6 | 7.1 | 10.5 | 15.9 | 6 | 9.9 | 16.1 | 7.4 | 8.7 | 13 | 4.9 | 8.1 | 10.9 | 3.9 | 6.9 | 10.7 | 4.9 | 5.8 | 10.2 | 3.8 | 6.4 | 20.1 | 8 | 12.2 | 16 | 7 | 9 | 39 | 16.3 | 22.7 |
MRT & Public Bus Only | 533.4 | 252.2 | 281.2 | 6.4 | 3 | 3.4 | 15.2 | 8.5 | 6.7 | 22.3 | 11.5 | 10.8 | 27 | 13.7 | 13.2 | 31.7 | 15.3 | 16.4 | 34 | 16.4 | 17.6 | 36.3 | 17.2 | 19.1 | 35.5 | 16.9 | 18.6 | 38.1 | 18.6 | 19.5 | 36.3 | 17.4 | 18.9 | 30.2 | 14.1 | 16.1 | 31 | 14.9 | 16 | 26 | 11.8 | 14.2 | 22.1 | 10.2 | 11.9 | 20.2 | 9.6 | 10.6 | 37.3 | 17 | 20.4 | 26.5 | 11.9 | 14.6 | 57.3 | 24.3 | 33 |
Other Combinations Of MRT Or Public Bus | 115.5 | 58.2 | 57.3 | 0.4 | 0.2 | 0.2 | 2.5 | 1.4 | 1.1 | 3.1 | 1.5 | 1.5 | 3.9 | 2.4 | 1.6 | 5.9 | 3 | 3 | 5.1 | 2.9 | 2.2 | 7.2 | 4.3 | 2.8 | 6.6 | 3.5 | 3.1 | 7.6 | 3.8 | 3.8 | 6.8 | 3.2 | 3.6 | 7.2 | 3.7 | 3.4 | 5.2 | 2.5 | 2.7 | 6.1 | 3 | 3.1 | 5.8 | 2.9 | 2.9 | 5.2 | 2.8 | 2.4 | 10.2 | 4.6 | 5.6 | 7.6 | 3.5 | 4.1 | 19.1 | 9 | 10.1 |
Taxi Only | 28.4 | 15 | 13.4 | 0.1 | 0.1 | 0 | 0.7 | 0.4 | 0.4 | 1 | 0.7 | 0.4 | 1.1 | 0.5 | 0.5 | 0.9 | 0.4 | 0.5 | 1.8 | 1 | 0.7 | 1.6 | 1.2 | 0.5 | 1.6 | 1 | 0.6 | 2 | 0.9 | 1.1 | 1.2 | 0.5 | 0.7 | 1.2 | 0.5 | 0.7 | 1.8 | 0.8 | 1.1 | 1.2 | 0.6 | 0.7 | 1.1 | 0.6 | 0.5 | 1.1 | 0.6 | 0.5 | 1.8 | 1 | 0.8 | 1.9 | 0.8 | 1.1 | 6 | 3.4 | 2.6 |
Car Only | 470 | 319.5 | 150.5 | 1.2 | 0.8 | 0.4 | 3.6 | 2.3 | 1.3 | 6.5 | 4.3 | 2.2 | 8.6 | 5.9 | 2.8 | 12.6 | 9 | 3.7 | 14.8 | 10.8 | 4 | 18.2 | 13.1 | 5.1 | 19.6 | 14.4 | 5.2 | 20.7 | 14.8 | 5.9 | 22.8 | 16.3 | 6.5 | 23.2 | 16.2 | 6.9 | 21.8 | 15.3 | 6.5 | 25.5 | 17.5 | 8.1 | 20 | 13.8 | 6.2 | 20.8 | 14.4 | 6.4 | 44.5 | 30.3 | 14.2 | 34.3 | 22.5 | 11.9 | 151.2 | 97.9 | 53.3 |
Private Chartered Bus/Van Only | 58.3 | 37 | 21.3 | 0.5 | 0.4 | 0.1 | 1.8 | 1.2 | 0.7 | 3.4 | 2.4 | 0.9 | 3.6 | 2.7 | 0.9 | 4 | 3.1 | 0.9 | 4.5 | 3 | 1.5 | 5.5 | 3.8 | 1.7 | 3.9 | 2.4 | 1.6 | 4.3 | 2.8 | 1.5 | 3.4 | 2.1 | 1.3 | 3 | 1.9 | 1.1 | 3.4 | 2.1 | 1.3 | 2.6 | 1.3 | 1.3 | 2.4 | 1.2 | 1.2 | 1.9 | 0.9 | 0.9 | 3.6 | 2.5 | 1.2 | 2.1 | 1.5 | 0.6 | 4.3 | 1.7 | 2.5 |
Lorry/Pickup Only | 42.8 | 38.4 | 4.4 | 0.5 | 0.4 | 0.1 | 2 | 1.7 | 0.3 | 3.8 | 3.3 | 0.5 | 3.5 | 3.3 | 0.3 | 4.1 | 3.7 | 0.4 | 3.5 | 3.3 | 0.2 | 3.9 | 3.4 | 0.6 | 3.9 | 3.4 | 0.4 | 3.6 | 3.5 | 0.1 | 2.3 | 2.1 | 0.2 | 2.6 | 2.4 | 0.3 | 2.3 | 1.9 | 0.4 | 1.3 | 1.2 | 0.1 | 0.8 | 0.7 | 0.1 | 0.9 | 0.7 | 0.2 | 1.8 | 1.6 | 0.2 | 0.8 | 0.7 | 0 | 1.3 | 1.2 | 0 |
Motorcycle/Scooter Only | 73.2 | 68.7 | 4.5 | 0.6 | 0.5 | 0.1 | 2.9 | 2.8 | 0.1 | 3.6 | 3.5 | 0.2 | 4.3 | 4.2 | 0.1 | 5.9 | 5.7 | 0.2 | 6 | 5.5 | 0.5 | 5.7 | 5.2 | 0.4 | 5.7 | 5.5 | 0.2 | 6.3 | 5.8 | 0.5 | 5.3 | 5 | 0.3 | 4.2 | 4 | 0.2 | 3.6 | 3.2 | 0.4 | 3.4 | 3.2 | 0.2 | 3.2 | 3 | 0.2 | 2.3 | 2.2 | 0.1 | 3.7 | 3.5 | 0.2 | 2.7 | 2.4 | 0.3 | 3.9 | 3.7 | 0.3 |
No results found
Title | Column name | Data type | Unit of measure | Description |
---|---|---|---|---|
Thousands | Thousands | Text | Thousands | - |
(Total) Total | Total_Total | Numeric | Thousands | - |
(Total) Males | Total_Males | Numeric | Thousands | - |
(Total) Females | Total_Females | Numeric | Thousands | - |
(Below $1,000) Total | Below_1_000_Total | Numeric | Thousands | - |
(Below $1,000) Males | Below_1_000_Males | Numeric | Thousands | - |
(Below $1,000) Females | Below_1_000_Females | Numeric | Thousands | - |
($1,000 - $1,999) Total | 1_000_1_999_Total | Numeric | Thousands | - |
($1,000 - $1,999) Males | 1_000_1_999_Males | Numeric | Thousands | - |
($1,000 - $1,999) Females | 1_000_1_999_Females | Numeric | Thousands | - |
($2,000 - $2,999) Total | 2_000_2_999_Total | Numeric | Thousands | - |
($2,000 - $2,999) Males | 2_000_2_999_Males | Numeric | Thousands | - |
($2,000 - $2,999) Females | 2_000_2_999_Females | Numeric | Thousands | - |
($3,000 - $3,999) Total | 3_000_3_999_Total | Numeric | Thousands | - |
($3,000 - $3,999) Males | 3_000_3_999_Males | Numeric | Thousands | - |
($3,000 - $3,999) Females | 3_000_3_999_Females | Numeric | Thousands | - |
($4,000 - $4,999) Total | 4_000_4_999_Total | Numeric | Thousands | - |
($4,000 - $4,999) Males | 4_000_4_999_Males | Numeric | Thousands | - |
($4,000 - $4,999) Females | 4_000_4_999_Females | Numeric | Thousands | - |
($5,000 - $5,999) Total | 5_000_5_999_Total | Numeric | Thousands | - |
($5,000 - $5,999) Males | 5_000_5_999_Males | Numeric | Thousands | - |
($5,000 - $5,999) Females | 5_000_5_999_Females | Numeric | Thousands | - |
($6,000 - $6,999) Total | 6_000_6_999_Total | Numeric | Thousands | - |
($6,000 - $6,999) Males | 6_000_6_999_Males | Numeric | Thousands | - |
($6,000 - $6,999) Females | 6_000_6_999_Females | Numeric | Thousands | - |
($7,000 - $7,999) Total | 7_000_7_999_Total | Numeric | Thousands | - |
($7,000 - $7,999) Males | 7_000_7_999_Males | Numeric | Thousands | - |
($7,000 - $7,999) Females | 7_000_7_999_Females | Numeric | Thousands | - |
($8,000 - $8,999) Total | 8_000_8_999_Total | Numeric | Thousands | - |
($8,000 - $8,999) Males | 8_000_8_999_Males | Numeric | Thousands | - |
($8,000 - $8,999) Females | 8_000_8_999_Females | Numeric | Thousands | - |
($9,000 - $9,999) Total | 9_000_9_999_Total | Numeric | Thousands | - |
($9,000 - $9,999) Males | 9_000_9_999_Males | Numeric | Thousands | - |
($9,000 - $9,999) Females | 9_000_9_999_Females | Numeric | Thousands | - |
($10,000 - $10,999) Total | 10_000_10_999_Total | Numeric | Thousands | - |
($10,000 - $10,999) Males | 10_000_10_999_Males | Numeric | Thousands | - |
($10,000 - $10,999) Females | 10_000_10_999_Females | Numeric | Thousands | - |
($11,000 - $11,999) Total | 11_000_11_999_Total | Numeric | Thousands | - |
($11,000 - $11,999) Males | 11_000_11_999_Males | Numeric | Thousands | - |
($11,000 - $11,999) Females | 11_000_11_999_Females | Numeric | Thousands | - |
($12,000 - $12,999) Total | 12_000_12_999_Total | Numeric | Thousands | - |
($12,000 - $12,999) Males | 12_000_12_999_Males | Numeric | Thousands | - |
($12,000 - $12,999) Females | 12_000_12_999_Females | Numeric | Thousands | - |
($13,000 - $13,999) Total | 13_000_13_999_Total | Numeric | Thousands | - |
($13,000 - $13,999) Males | 13_000_13_999_Males | Numeric | Thousands | - |
($13,000 - $13,999) Females | 13_000_13_999_Females | Numeric | Thousands | - |
($14,000 - $14,999) Total | 14_000_14_999_Total | Numeric | Thousands | - |
($14,000 - $14,999) Males | 14_000_14_999_Males | Numeric | Thousands | - |
($14,000 - $14,999) Females | 14_000_14_999_Females | Numeric | Thousands | - |
($15,000 - $17,499) Total | 15_000_17_499_Total | Numeric | Thousands | - |
($15,000 - $17,499) Males | 15_000_17_499_Males | Numeric | Thousands | - |
($15,000 - $17,499) Females | 15_000_17_499_Females | Numeric | Thousands | - |
($17,500 - $19,999) Total | 17_500_19_999_Total | Numeric | Thousands | - |
($17,500 - $19,999) Males | 17_500_19_999_Males | Numeric | Thousands | - |
($17,500 - $19,999) Females | 17_500_19_999_Females | Numeric | Thousands | - |
(20,000 & Over) Total | 20_000andOver_Total | Numeric | Thousands | - |
(20,000 & Over) Males | 20_000andOver_Males | Numeric | Thousands | - |
(20,000 & Over) Females | 20_000andOver_Females | Numeric | Thousands | - |
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_661c632b9ee301ddf915bf4f0f73b704"
url = "https://data.gov.sg/api/action/datastore_search?resource_id=" + dataset_id
response = requests.get(url)
print(response.json())
This dataset can be reused and cited in research publications.
24 Nov 2023
Free forever for personal or commercial use, under the Open Data Licence.