Intraday Timeseries (1 line)
Data as of 03 Apr 2023, 23:59A precise, succinct description of this chart
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How is this data produced?
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
What caveats I should bear in mind when using this data?
Contrary to popular belief, Lorem Ipsum is not simply random text. It has roots in a piece of classical Latin literature from 45 BC, making it over 2000 years old. Richard McClintock, a Latin professor at Hampden-Sydney College in Virginia, looked up one of the more obscure Latin words, consectetur, from a Lorem Ipsum passage, and going through the cites of the word in classical literature, discovered the undoubtable source.
Publication(s) using this data
Lorem Ipsum comes from sections 1.10.32 and 1.10.33 of 'de Finibus Bonorum et Malorum' (The Extremes of Good and Evil) by Cicero, written in 45 BC. This book is a treatise on the theory of ethics, very popular during the Renaissance. The first line of Lorem Ipsum, 'Lorem ipsum dolor sit amet..'', comes from a line in section 1.10.32.
Metadata
Dataset description
Lorem ipsum.
Variable definitions
- timestamp
- origin
- destination
Last updated:
04 Apr 2023, 06:00
Next update
05 Apr 2023, 06:00
Data source(s)
- MAMPU
URLs to dataset
License
This data is made open under the Creative Commons Attribution 4.0 International License (CC BY 4.0). A human-readable copy of the license is available Here.
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Chart
Image (PNG)
Suitable for general digital use.
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Vector Graphic (SVG)
Suitable for high quality prints or further image editing.
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Data
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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Code
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/transportation/ridership_sample_truncated.parquet'
df = pd.read_parquet(URL_DATA)
if 'date' in df.columns: df['date'] = pd.to_datetime(df['date'])
print(df)Sample OpenAPI query
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.
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