Lookup table, to be left-joined against premise code in the main PriceCatcher data.
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Prices are collected and verified by groundstaff on a daily basis, with over 2 million prices collected every month.
This data is collected for the purpose of price surveillance, and is excellent for high-frequency analysis of specific items in specific locations. Inflation surveillance requires a different approach, in particular to ensure proper representativeness. Inflation analysis should be conducted using DOSM's CPI data.
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Lookup table, to be left-joined against premise code in the main PriceCatcher data.
Name in Dataset | Variable | Definition |
---|---|---|
premise_code (Integer) | Premise Code | Column for left-join |
premise (Categorical) | Premise | Name of premise |
address (String) | Address | Full address |
premise_type (Categorical) | Premise Type | Type of premise |
state (Categorical) | State | Name of state |
district (Categorical) | District | Name of district |
30 Sept 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.data.gov.my/pricecatcher/lookup_premise.parquet'
df = pd.read_parquet(URL_DATA)
if 'date' in df.columns: df['date'] = pd.to_datetime(df['date'])
print(df)
This data catalog is not available through OpenAPI as the nature of the data makes it unsuitable for API access. For the full dataset, please use the provided download link as shown in the above section.
Department of Statistics Malaysia
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data.gov.my