Lookup table, to be left-joined against other GDP datasets if specified.
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This lookup table is not part of any standardised data dictionary; it was custom-made to serve the GDP datasets made available via data.gov.my and OpenDOSM only. Furthermore, the coding employed here is similar to (but not the same as) the coding used in DOSM's GDP publications, because it has been calibrated to ensure consistency across annual and quarterly GDP publications, as well as national and state GDP publications.
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Lookup table, to be left-joined against other GDP datasets if specified.
Name in Dataset | Variable | Definition |
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method (Categorical) | Method | Either the production approach ('production'), expenditure approach ('expenditure'), or income approach ('income') |
code (String) | Code | Reference for the variable as contained within the dataset |
variable_en (String) | Variable Definition (EN) | Definition of the variable in English |
variable_bm (String) | Variable Definition (MS) | Definition of the variable in Malay |
17 May 2024, 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)
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.dosm.gov.my/gdp/gdp_lookup.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=gdp_lookup&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
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