Population at district level from 2020 to 2024, by sex, age group and ethnicity. The preview table shows data for the latest year only, but you may download the data in full.
0 views·0 downloads
Values for 2020 are based on adjusted data from the Population Censuses conducted in that year. Values for all other years are intercensal mid-year population estimates. The intercensal estimates were generated using the cohort-component method, which estimates the latest year's population by taking the previous year's value, then adding births, subtracting deaths, and adding net migration. For a deeper understanding of the methodology, please refer to the Technical Notes.
Values for breakdowns may be slightly different to totals when summed, due to rounding to one decimal place.
OpenDOSM features a dashboard on the population of Malaysia.
Population at district level from 2020 to 2024, by sex, age group and ethnicity. The preview table shows data for the latest year only, but you may download the data in full.
Name in Dataset | Variable | Definition |
---|---|---|
date (Date) | Date | The date in YYYY-MM-DD format, with MM-DD set to 01-01 as this is annual data |
state (Categorical) | State | One of 16 states |
district (Categorical) | District | One of 160 administrative districts, including the 4 states (Perlis and the 3 Federal Territories) which do not have subdivisions |
sex (Categorical) | Sex | Either both sexes ('both'), male ('male') or female ('female') |
age (Categorical) | Age Group | Either all age groups ('overall') or five-year age groups e.g. 0-4, 5-9, 10-14, etc. 85+ is the oldest category. |
ethnicity (Categorical) | Ethnicity | All ethnic groups ('overall'), Malay ('bumi_malay'), other Bumiputera ('bumi_other'), Chinese ('chinese'), Indian ('indian'), other citizens ('other_citizen'), or non-citizen residents ('other_noncitizen'). |
population (Float) | Population ('000) | Thousands of people ('000 people) |
31 Aug 2024, 12:00
31 Aug 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)
Recommended for individuals seeking an Excel-friendly format.
0
Full Dataset (Parquet)
Recommended for data scientists seeking to work with data via code.
0
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/population/population_district.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=population_district&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
© 2024 Public Sector Open Data