Industrial Production Index

Data as of Dec 2023

Output of the three main industrial sectors namely mining, manufacturing and electricity.

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How is this data produced?

The Industrial Production Index (IPI) in Malaysia measures the rate of change in production of industrial commodities in the Mining, Manufacturing, and Electricity sectors in real terms over time. For a full description of the methodology, please refer to the Technical Notes.

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

The IPI is a base year-weighted arithmetic average of quantity relatives calculated using the Laspeyres formula, with the base year of 1968 (1968=100) being the first year of its construction. The IPI pertains to Malaysia, with the exception of the base years 1968 and 1981, which pertain to Peninsular Malaysia. Data for December 2022 is provisional; it will be updated and subsequently published in the January 2023 publication.

Publication(s) using this data

Index of Industrial Production, Dec 2023, the latest edition of the monthly industrial production statistics published by DOSM. OpenDOSM also features a dashboard on industrial production.


Dataset description

Output of the three main industrial sectors namely mining, manufacturing and electricity.

Variable definitions
  • Date
  • IPI (Industrial Production Index)
  • Mining
  • Manufacturing
  • Electricity
Last updated:

08 Feb 2024, 12:00

Next update:

11 Mar 2024, 12:00

Data source(s)
  • DOSM

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.


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

The following code is an example of how to make an API query to retrieve the data catalogue mentioned above. You can use different programming languages by switching the code accordingly. For a complete guide on possible query parameters and syntax, please refer to the official Open API documentation.
import requests import pprint url = "" response_json = requests.get(url=url).json() pprint.pprint(response_json)
jata negara

Department of Statistics Malaysia

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