PriceCatcher: 2023/08

Data as of 31 Aug 2023, 23:59

The table below provides a preview of the full dataset, which contains over a million prices. We recommend that you download and work with the data in a coding environment. This data should be used in conjuction with the Item Lookup and Premise Lookup tables.

2023

2023

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How is this data produced?

Prices are collected and verified by groundstaff on a daily basis, with over 2 million prices collected every month.

What caveats I should bear in mind when using this data?

This data is collected for the purpose of price surveillance, and is excellent for high-frequency analysis of specific items in specific locations. Inflation surveillance requires a different approach, in particular to ensure proper representativeness. Inflation analysis should be conducted using DOSM's CPI data.

Publication(s) using this data

Metadata

Dataset description

PriceCatcher is a mobile app developed by the Ministry of Domestic Trade and Cost of Living (KPDN, formerly KPDNHEP) to help users compare the prices of key items in their area. Prices are collected and verified by groundstaff on a daily basis, with over 2 million prices collected every month. This dataset makes that wealth of data available to you for analysis.

Variable definitions
Last updated:

01 Sept 2023, 09:00

Next update

N/A

Data source(s)
  • KPDN
  • DOSM
License

This data is made open under the Creative Commons Attribution 4.0 International License (CC BY 4.0). A human-readable copy of the license is available Here.

Download

Data
Full Dataset (CSV)

Full Dataset (CSV)

Recommended for individuals seeking an Excel-friendly format.

0

Full Dataset (Parquet)

Full Dataset (Parquet)

Recommended for data scientists seeking to work with data via code.

0

Code

Connect directly to the data with Python.

# If not already installed, do: pip install pandas fastparquet import pandas as pd URL_DATA = 'https://storage.data.gov.my/pricecatcher/pricecatcher_2023-08.parquet' df = pd.read_parquet(URL_DATA) if 'date' in df.columns: df['date'] = pd.to_datetime(df['date']) print(df)

Sample OpenAPI query

This data catalog is not available through OpenAPI as the nature of the data makes it unsuitable for API access. For the full dataset, please use the provided download link as shown in the above section.

jata negara
Government of Malaysia

© 2023 Public Sector Open Data