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seaborn: statistical data visualization
=======================================

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Seaborn is a Python data visualization library based on `matplotlib
<https://matplotlib.org>`_. It provides a high-level interface for drawing
attractive and informative statistical graphics.

For a brief introduction to the ideas behind the library, you can read the
:ref:`introductory notes <introduction>`. Visit the :ref:`installation page
<installing>` to see how you can download the package. You can browse the
:ref:`example gallery <example_gallery>` to see 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
<https://github.com/mwaskom/seaborn>`_. General support issues are most at home on `stackoverflow <https://stackoverflow.com/>`_, where there is a seaborn tag.
   

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.. toctree::
   :maxdepth: 1

   Introduction <introduction>
   Release notes <whatsnew>
   Installing <installing>
   Example gallery <examples/index>
   Tutorial <tutorial>
   API reference <api>

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* Relational: :ref:`API <relational_api>` | :ref:`Tutorial <relational_tutorial>`
* Categorical: :ref:`API <categorical_api>` | :ref:`Tutorial <categorical_tutorial>`
* Distributions: :ref:`API <distribution_api>` | :ref:`Tutorial <distribution_tutorial>`
* Regressions: :ref:`API <regression_api>` | :ref:`Tutorial <regression_tutorial>`
* Multiples: :ref:`API <grid_api>` | :ref:`Tutorial <grid_tutorial>`
* Style: :ref:`API <style_api>` | :ref:`Tutorial <aesthetics_tutorial>`
* Color: :ref:`API <palette_api>` | :ref:`Tutorial <palette_tutorial>`
 
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