Daily healthcare screenings conducted under the PeKaB40 program, at state level. The table provides a preview of the dataset using the most recent year of data.
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This dataset is produced from the transactional database operated by Protect Health Corporation to administer the PeKaB40 program. PeKa B40 is a MoH initiative which aims to sustain the healthcare needs of low income groups by focusing on non-communicable diseases (NCDs). Recipients of government cash assistance and their spouses aged 40 and above are automatically eligible for free health screenings.
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Daily healthcare screenings conducted under the PeKaB40 program, at state level. The table provides a preview of the dataset using the most recent year of data.
Name in Dataset | Variable | Definition |
---|---|---|
date (Date) | Date | Date in YYYY-MM-DD format |
state (Categorical) | State | One of 16 states |
screenings (Integer) | Screenings | Number of health screenings conducted on that date |
06 Dec 2024, 10:00
07 Dec 2024, 10:00
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.
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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.data.gov.my/healthcare/pekab40_screenings_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=pekab40_screenings_state&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
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