index.rst

Seaborn: statistical data visualization

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Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.

For a brief introduction to the ideas behind the package, you can read the :ref:`introductory notes <introduction>`. More practical information is on the :ref:`installation page <installing>`. You may also want to browse the :ref:`example gallery <example_gallery>` to get a sense for what you can do with seaborn and then check out the :ref:`tutorial <tutorial>` and :ref:`API reference <api_ref>` to find out how.

To see the code or report a bug, please visit the github repository. General support issues are most at home on stackoverflow, where there is a seaborn tag.

Documentation

.. toctree::
   :maxdepth: 1

   introduction
   whatsnew
   installing
   examples/index
   api
   tutorial

Features

• Style functions: :ref:`API <style_api>` | :ref:`Tutorial <aesthetics_tutorial>`
• Color palettes: :ref:`API <palette_api>` | :ref:`Tutorial <palette_tutorial>`
• Distribution plots: :ref:`API <distribution_api>` | :ref:`Tutorial <distribution_tutorial>`
• Regression plots: :ref:`API <regression_api>` | :ref:`Tutorial <regression_tutorial>`
• Categorical plots: :ref:`API <categorical_api>` | :ref:`Tutorial <categorical_tutorial>`
• Axis grid objects: :ref:`API <grid_api>` | :ref:`Tutorial <grid_tutorial>`