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Collection: Online Shoppers

Dataset: Online Shoppers by Value of Purchase

Social

Online Shoppers by Value of Purchase

Data from Jan 2006 to Dec 2015

Last updated: 06 Jun 2024, 14:43 SGT

IMDA (Info-communications Media Development Authority)

To track the adoption of online shopping by value of purchase in Singapore

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_79958154e6f9d9a30c5655ddd41d83c5"
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.

Info-communications Media Development Authority. (2016). Online Shoppers by Value of Purchase (2024) [Dataset]. data.gov.sg. Retrieved April 1, 2026 from https://data.gov.sg/datasets/d_79958154e6f9d9a30c5655ddd41d83c5/view

About this dataset

Contact

info@imda.gov.sg

Created on

04 May 2016

Licence

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

Agency

IMDA (Info-communications Media Development Authority)

‌

Social

Online Shoppers by Value of Purchase

Data from Jan 2006 to Dec 2015

Last updated: 06 Jun 2024, 14:43 SGT

IMDA (Info-communications Media Development Authority)

To track the adoption of online shopping by value of purchase in Singapore

‌

Data explorer

OnlineShoppersbyValueofPurchase.csv (78 rows, 1.7 KB)


(Null)0.0%	(Null)0.0%	(Null)0.0%
2006	less than $100	26
2006	$100 to $199	21
2006	$200 to $499	21
2006	$500 to $999	10
2006	$1000 to $1999	12
2006	$2000 or more	10
2007	less than $100	28
2007	$100 to $199	22
2007	$200 to $499	17
2007	$500 to $999	12

Column legend

Title	Column name	Data type	Unit of measure	Description
-	year	-	-	-
-	value_of_purchase	-	-	-
-	percentage	-	-	-

Analyse this dataset with Colab Notebook

1. Copy this dataset ID: d_79958154e6f9d9a30c5655ddd41d83c5
2. Click on the button below