This table provides a complete lookup for the classification of stage of processing, as applied and used by publications in Malaysia, primarily by DOSM.
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The classification of stage of processing is consistent with the Standard International Trade Classification (SITC) Revision 4 published by the United Nations Statistics Division, which is used as a global reference in the classification of international merchandise trade.
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This table provides a complete lookup for the classification of stage of processing, as applied and used by publications in Malaysia, primarily by DOSM.
Name in Dataset | Variable | Definition |
---|---|---|
digits (Integer) | Digits | Number of digits; this column can be used as a filter if you only want to keep 1 digit codes, for example |
code (String) | Code | 1-4 digit codes; please ensure that you read this column as a string. |
desc_en (String) | Description (EN) | Description for the code, in English |
desc_bm (String) | Description (BM) | Description for the code, in Malay |
09 Mar 2024, 00:00
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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/dictionaries/sitc_sop.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=sitc_sop&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
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