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Social

Number of residents admitted into Transitional Shelters by type of cases

Data from Jan 2019 to Feb 2023

Last updated: 06 Jun 2024, 14:25 SGT

MSF (Ministry of Social and Family Development)

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_1c25a8e53f8092448c98cb686739db30"
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.

Ministry of Social and Family Development. (2023). Number of residents admitted into Transitional Shelters by type of cases (2024) [Dataset]. data.gov.sg. Retrieved December 30, 2025 from https://data.gov.sg/datasets/d_1c25a8e53f8092448c98cb686739db30/view

About this dataset

Contact

feedback@data.gov.sg

Created on

06 Jun 2023

Licence

Free forever for personal or commercial use, under the Open Data Licence.

Agency

MSF (Ministry of Social and Family Development)

‌

Social

Number of residents admitted into Transitional Shelters by type of cases

Data from Jan 2019 to Feb 2023

Last updated: 06 Jun 2024, 14:25 SGT

MSF (Ministry of Social and Family Development)

‌

Data explorer

NumberofresidentsadmittedintoTransitionalSheltersbytypeofcases.csv (50 rows, 994 B)

Year Year (YYYY)	Month Text	Individuals Numeric	Families Numeric
(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%
2019	January	49	59
2019	February	50	65
2019	March	56	66
2019	April	60	59
2019	May	70	59
2019	June	77	62
2019	July	73	69
2019	August	79	61
2019	September	73	59
2019	October	77	61

Column legend

Title	Column name	Data type	Unit of measure	Description
Year	year	Year (YYYY)	-	-
Month	mm	Text	-	-
Individuals	individuals	Numeric	No of Indivduals	-
Families	families	Numeric	No of Families	-

Analyse this dataset with Colab Notebook

1. Copy this dataset ID: d_1c25a8e53f8092448c98cb686739db30
2. Click on the button below