Timeseries (1 line)

Data as of 03 Apr 2023, 23:59

A 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.

  1. First item
  2. Second item
  3. Third item

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
  • Date
  • State
  • Variable 1
Last updated:

04 Apr 2023, 06:00

Next update

05 Apr 2023, 06:00

Data source(s)
  • MAMPU
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
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Image (PNG)

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Vector Graphic (SVG)

Vector Graphic (SVG)

Suitable for high quality prints or further image editing.

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Data
Full Dataset (CSV)

Full Dataset (CSV)

Recommended for individuals seeking an Excel-friendly format.

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Full Dataset (Parquet)

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://dgmy-public-mwe.s3.ap-southeast-1.amazonaws.com/mwe_timeseries.parquet' df = pd.read_parquet(URL_DATA) if 'date' in df.columns: df['date'] = pd.to_datetime(df['date']) print(df)

Sample OpenAPI query

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=dgmy-public-mwe_mwe_timeseries_1&limit=3" response_json = requests.get(url=url).json() pprint.pprint(response_json)
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