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Installation

Using pip

You can install using the pip package manager by running:

    pip install -U ydata-profiling
If you are in a notebook (locally, LambdaLabs, Google Colab or Kaggle), you can run:

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    import sys
    !{sys.executable} -m pip install -U ydata-profiling[notebook]
    !jupyter nbextension enable --py widgetsnbextension

You may have to restart the kernel or runtime for the package to work.

Using conda

ydata-profiling through Conda

A new conda environment containing the module can be created via: 

    conda env create -n ydata-profiling
    conda activate ydata-profiling
    conda install -c conda-forge ydata-profiling

Tip

Don't forget to specify the ``conda-forge`` channel.       
Omitting it **will not** lead to an error, as an outdated package lives on the ``main`` channel and will be installed. See :doc:`../support_contrib/common_issues` for details.

Widgets in Jupyter Notebook/Lab

For the Jupyter widgets extension (used for progress bars and the interactive widget-based report) to work, you might need to install and activate the corresponding extensions. This can be done via pip: 

  pip install ydata-profiling[notebook]
  jupyter nbextension enable --py widgetsnbextension

Or via conda: 

  conda install -c conda-forge ipywidgets

In most cases, this will also automatically configure Jupyter Notebook and Jupyter Lab (>=3.0). For older versions of both or in more complex environment configurations, refer to the official ipywidgets documentation.

From source

Download the source code by cloning the repository or by clicking on Download ZIP. Install it by navigating to the uncompressed directory and running:

   python setup.py install

This can also be done via the following one-liner: 

  pip install https://github.com/ydataai/ydata-profiling/archive/master.zip

Extras

The package declares some "extras", sets of additional dependencies.

  • [notebook]: support for rendering the report in Jupyter notebook widgets.
  • [unicode]: support for more detailed Unicode analysis, at the expense of additional disk space.
  • [pyspark]: support for pyspark engine to run the profile on big datasets

Install these with e.g. 

  pip install -U ydata-profiling[notebook,unicode, pyspark]