Number and proportion of working individuals who worked less than 30 hours per week even though they were willing to work more, i.e. due to unavailability of work.
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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.
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.
The Labour Force Report, 3Q 2024, the latest edition of the monthly labour force statistics published by DOSM. OpenDOSM also features a dashboard on the labour force.
Number and proportion of working individuals who worked less than 30 hours per week even though they were willing to work more, i.e. due to unavailability of work.
Name in Dataset | Variable | Definition |
---|---|---|
date (Date) | Date | The date in YYYY-MM-DD format, with DD set to 01 since the data is at quarterly frequency |
variable (Categorical) | Variable | Rate (%) or persons ('000) |
age (Categorical) | Age Group | 10-year age groups, or overall |
tru (Float) | Time-Related Underemployment | Number or proportion of working individuals who worked less than 30 hours per week even though they were willing to work more, i.e. due to unavailability of work |
08 Nov 2024, 12:00
10 Feb 2025, 12:00
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)
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Full Dataset (Parquet)
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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_qtr_tru_age.parquet'
df = pd.read_parquet(URL_DATA)
if 'date' in df.columns: df['date'] = pd.to_datetime(df['date'])
print(df)
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_qtr_tru_age&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
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