Gini coefficient by administrative district from 2019 to 2022.
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The primary Gini coefficient at state-level is computed based on the distribution of households' gross monthly income, where:
Because the computation of the Gini coefficient relies on household income data, Malaysia's Gini coefficient statistics are produced and published together with statistics on household income derived from the Household Income and Expenditure Survey (HIES), which is conducted at least twice within any 5-year period. For full details on the methodology, especially the computation of the PLI and its evolution and nuances, please refer to the technical notes.
District-level data is only published from 2019 (relative to state-level data which is available from 1970) as prior HIES samples were not sufficient to support district-level granularity.
The Household Income Survey Report, 2022, the latest edition of the household income statistics published by DOSM. OpenDOSM also features a dashboard on household income which enables you to explore Malaysia's household income data interactively.
Gini coefficient by administrative district from 2019 to 2022.
Name in Dataset | Variable | Definition |
---|---|---|
state (Categorical) | State | One of 16 states, including the 3 Federal Territories |
district (Categorical) | District | One of 160 administrative districts, including the 4 states (Perlis and the 3 Federal Territories) which do not have subdivisions |
date (Date) | Date | The date in YYYY-MM-DD format, with MM-DD set to 01-01 as the data is at annual frequency |
gini (Float) | Gini Coefficient | The Gini coefficient based on the distribution of households' gross monthly income |
28 Jul 2023, 12:00
N/A
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)
Recommended for data scientists seeking to work with data via code.
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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/hies/hh_inequality_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=hh_inequality_district&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
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