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Improved description of seaborn #18495

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21 changes: 12 additions & 9 deletions doc/source/ecosystem.rst
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Expand Up @@ -53,6 +53,18 @@ the latest web technologies. Its goal is to provide elegant, concise constructio
graphics in the style of Protovis/D3, while delivering high-performance interactivity over
large data to thin clients.

`seaborn <https://seaborn.pydata.org>`__
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Seaborn is a Python visualization library based on `matplotlib
<http://matplotlib.org>`__. It provides a high-level, dataset-oriented
interface for creating attractive statistical graphics. The plotting functions
in seaborn understand pandas objects and leverage pandas grouping operations
internally to support concise specification of complex visualizations. Seaborn
also goes beyond matplotlib and pandas with the option to perform statistical
estimation while plotting, aggregating across observations and visualizing the
fit of statistical models to emphasize patterns in a dataset.

`yhat/ggplot <https://github.com/yhat/ggplot>`__
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Expand All @@ -64,15 +76,6 @@ but a faithful implementation for python users has long been missing. Although s
(as of Jan-2014), the `yhat/ggplot <https://github.com/yhat/ggplot>`__ project has been
progressing quickly in that direction.

`Seaborn <https://github.com/mwaskom/seaborn>`__
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Although pandas has quite a bit of "just plot it" functionality built-in, visualization and
in particular statistical graphics is a vast field with a long tradition and lots of ground
to cover. The `Seaborn <https://github.com/mwaskom/seaborn>`__ project builds on top of pandas
and `matplotlib <http://matplotlib.org>`__ to provide easy plotting of data which extends to
more advanced types of plots then those offered by pandas.

`Vincent <https://github.com/wrobstory/vincent>`__
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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