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Jupyter Widget for Intelligent Data Discovery

Project description

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Lux is a library designed to make data science easier and facilitate fast experimentation with data. You can learn more about Lux by referring to the core Lux API in Python. This is the Jupyter widget frontend for Lux, written in Typescript and React.

Here is an example of the Lux widget in action.

Basic recommendations in Lux

You can find the full demo example in this live notebook.


Lux can be installed through PyPI:

    pip install lux-api

Setup in Jupyter Notebook, VSCode

To use Lux in Jupyter notebook or VSCode, activate the notebook extension:

    jupyter nbextension install --py luxwidget
    jupyter nbextension enable --py luxwidget

If the installation happens correctly, you should see two - Validating: OK after executing the two lines above.

Setup in Jupyter Lab

To use Lux in Jupyter Lab, activate the lab extension:

    jupyter labextension install @jupyter-widgets/jupyterlab-manager
    jupyter labextension install luxwidget

If you encounter issues with the installation, please refer to this page to troubleshoot the installation. Follow these instructions to set up Lux for development purposes.

Documentation and Support

For detailed reference, please refer to the documentation page. Please report any bugs, issues, or requests through Github Issues or post on the #help channel in the Lux Slack org.

Lux has only been tested with Jupyter notebook and Chrome - there have been issues with other browsers and we advise using Chrome.

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