skrub

.. image:: https://skrub-data.github.io/stable/_static/skrub.svg :align: center :width: 50 % :alt: skrub logo

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skrub is a Python library that facilitates machine learning with dataframes.

If you like the package, spread the word and ⭐ this repository! You can also join the Discord server <https://discord.gg/ABaPnm7fDC>_.

Website: https://skrub-data.org/

See our examples <https://skrub-data.org/stable/auto_examples>, or check out the learning materials <https://skrub-data.org/skrub-materials/index.html>.

Documentation and examples are bundled with the package itself, in skrub/_docs. After installing, you can find it at:

.. code-block:: python

import skrub
print(skrub.__docs_dir__)

Installation

skrub can easily be installed via pip or conda. For more installation information, see the installation instructions <https://skrub-data.org/stable/install.html>_.

Contributing

The best way to support the development of skrub is to spread the word!

Also, if you already are a skrub user, we would love to hear about your use cases and challenges in the Discussions <https://github.com/skrub-data/skrub/discussions>_ section.

To report a bug or suggest enhancements, please open an issue <https://docs.github.com/en/issues/tracking-your-work-with-issues/creating-an-issue>_.

If you want to contribute directly to the library, then check the how to contribute <https://skrub-data.org/stable/CONTRIBUTING.html>_ page on the website for more information.

Citing skrub

If you use skrub in a scientific publication, please cite it via the Zenodo record.