Premise Lookup

Data as of 16 Jun 2024, 23:59

Lookup table, to be left-joined against premise code in the main PriceCatcher data.

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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


Dataset description

Lookup table, to be left-joined against premise code in the main PriceCatcher data.

Variable definitions
  • Premise Code
  • Premise
  • Address
  • Premise Type
  • State
  • District
Last updated:

17 Jun 2024, 12:00

Next update:


Data source(s)
  • KPDN

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.


Full Dataset (CSV)

Full Dataset (CSV)

Recommended for individuals seeking an Excel-friendly format.


Full Dataset (Parquet)

Full Dataset (Parquet)

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



Connect directly to the data with Python.

# If not already installed, do: pip install pandas fastparquet import pandas as pd URL_DATA = '' 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

Department of Statistics Malaysia

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