Annual Principal Labour Force Statistics

Data as of 2023

Annual principal labour force statistics, including unemployment and participation rates.

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Table

Unemployment Rate

Participation Rate

Employment-Population Ratio

Labour Force Size

Employed

Unemployed

Outside Labour Force

How is this data produced?

This data is produced based on the Labour Force Survey (LFS), which is designed to collect representative data on the labour force at national and state level. Consistency in methodology has been maintained to ensure that the data is comparable over time. Survey findings are a monthly, quarterly and annual basis. For a full description of the methodology, please refer to the Technical Notes.

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

Data for 1991 and 1994 are not available due to limitations in the sample data from those years. Furthermore, the sum of each category may not always equal to the totals shown in related tables because of independent rounding to one decimal place. However, the differences are not obvious.

Publication(s) using this data

The Labour Force Report, Dec 2023, the latest edition of the monthly labour force statistics published by DOSM. OpenDOSM also features a dashboard on the labour force.

Metadata

Dataset description

Annual principal labour force statistics, including unemployment and participation rates.

Variable definitions
  • Date
  • Labour Force Size
  • Employed Persons
  • Unemployed Persons
  • Persons outside Labour Force
  • Unemployment Rate
  • Participation Rate
  • Employment-Population Ratio
Last updated:

09 Feb 2024, 12:00

Next update:

09 Feb 2025, 12:00

Data source(s)
  • 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.

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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.dosm.gov.my/labour/lfs_year.parquet' 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 = "https://api.data.gov.my/data-catalogue?id=lfs_year&limit=3" response_json = requests.get(url=url).json() pprint.pprint(response_json)
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Department of Statistics Malaysia

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