Improved description of seaborn (#18495)

Author: mwaskom

doc/source/ecosystem.rst

@@ -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>`__
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
@@ -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>`__
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~