PriceCatcher: Transactional Records

Data as of 20 Feb 2025, 23:59

The table below provides a preview of the full dataset, which contains over a million price records per month. We recommend that you download and work with the data in your preferred coding environment - Microsoft Excel will likely be insufficient due to the size of the dataset. This data should be used in conjuction with the Item Lookup and Premise Lookup tables.

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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. Therefore, PriceCatcher data should be used as a complement rather than a replacement to CPI data.

Publication(s) using this data

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Metadata

Dataset description

The table below provides a preview of the full dataset, which contains over a million price records per month. We recommend that you download and work with the data in your preferred coding environment - Microsoft Excel will likely be insufficient due to the size of the dataset. This data should be used in conjuction with the Item Lookup and Premise Lookup tables.

Variable definitions
Last updated:

21 Feb 2025, 12:00

Next update:

22 Feb 2025, 12:00

Data source(s)
  • Ministry of Domestic Trade
  • Department of Statistics Malaysia
License

This data is made open under the Creative Commons Attribution 4.0 International License (CC BY 4.0). A 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_2025-02.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.