Quarterly Skills-Related Underemployment by Age
Data as of 2Q 2024Number and proportion of working individuals with tertiary education working in a semi-skilled or low-skilled job, broken down by age group.
0 views·0 downloads
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?
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, 2Q 2024, the latest edition of the monthly labour force statistics published by DOSM. OpenDOSM also features a dashboard on the labour force.
Metadata
Dataset description
Number and proportion of working individuals with tertiary education working in a semi-skilled or low-skilled job, broken down by age group.
Variable definitions
- Date
- Variable
- Age Group
- Skills-Related Underemployment
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 |
sru (Float) | Skills-Related Underemployment | The number or proportion of employed individuals with tertiary education but who were working in a semi-skilled or low-skilled job as classified under MASCO |
Last updated:
09 Aug 2024, 12:00
Next update:
08 Nov 2024, 12:00
Data source(s)
- Department of Statistics Malaysia
URLs to dataset
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)
Recommended for individuals seeking an Excel-friendly format.
0
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.dosm.gov.my/labour/lfs_qtr_sru_age.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_qtr_sru_age&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
© 2024 Public Sector Open Data