A suite of PySpark, Pandas, and general pipeline utils for Reproducible Data Science and Analysis (RDSA) projects.
Project description
🧰 rdsa-utils
A suite of PySpark, Pandas, and general pipeline utils for Reproducible Data Science and Analysis (RDSA) projects.
The RDSA team sits within the Economic Statistics Change Directorate, and uses cutting-edge data science and engineering skills to produce the next generation of economic statistics. Current priorities include overhauling legacy systems and developing new systems for key statistics. More information about work at RDSA can be found here: Using Data Science for Next-Gen Statistics.
rdsa-utils
is a Python codebase built with Python 3.8 and higher, and uses setup.py
, setup.cfg
, and pyproject.toml
for dependency management and packaging.
📋 Prerequisites
- Python 3.8 or higher
💾 Installation
rdsa-utils
is available for installation via PyPI and can also be found on GitHub Releases for direct downloads and version history.
To install via pip
, simply run:
pip install rdsa-utils
📖 Documentation and Further Information
Our documentation is automatically generated using GitHub Actions and MkDocs. For an in-depth understanding of rdsa-utils
, how to contribute to rdsa-utils
, and more, please refer to our MkDocs-generated documentation.
🛡️ Licence
Unless stated otherwise, the codebase is released under the MIT License. This covers both the codebase and any sample code in the documentation.
The documentation is © Crown copyright and available under the terms of the Open Government 3.0 licence.
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