Number of households and living quarters by state from 1970 to 2024.
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Values for 1970, 1980, 1991, 2000, 2010 and 2020 are based on adjusted data from the Population Censuses conducted in those years. Values for all other years are intercensal mid-year population estimates. 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.
Number of households and living quarters by state from 1970 to 2024.
Name in Dataset | Variable | Definition |
---|---|---|
date (Date) | Date | The date in YYYY-MM-DD format, with MM-DD set to 01-01 as the data is at annual frequency |
state (Categorical) | State | One of 16 states, including the 3 Federal Territories |
households (Numeric) | Number of Households | The total number of households for the given year and state |
living_quarters (Numeric) | Number of Living Quarters | The total number of living quarters for the given year and state; note that this also includes empty dwellings. |
31 Jul 2024, 12:00
31 Jul 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/demography/hh_lq_state.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=hh_profile_state&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
Department of Statistics Malaysia
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