@@ -53,6 +53,18 @@ the latest web technologies. Its goal is to provide elegant, concise constructio
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graphics in the style of Protovis/D3, while delivering high-performance interactivity over
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large data to thin clients.
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+ `seaborn <https://seaborn.pydata.org >`__
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+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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+
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+ Seaborn is a Python visualization library based on `matplotlib
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+ <http://matplotlib.org> `__. It provides a high-level, dataset-oriented
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+ interface for creating attractive statistical graphics. The plotting functions
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+ in seaborn understand pandas objects and leverage pandas grouping operations
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+ internally to support concise specification of complex visualizations. Seaborn
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+ also goes beyond matplotlib and pandas with the option to perform statistical
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+ estimation while plotting, aggregating across observations and visualizing the
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+ fit of statistical models to emphasize patterns in a dataset.
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+
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`yhat/ggplot <https://github.com/yhat/ggplot >`__
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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@@ -64,15 +76,6 @@ but a faithful implementation for python users has long been missing. Although s
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(as of Jan-2014), the `yhat/ggplot <https://github.com/yhat/ggplot >`__ project has been
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progressing quickly in that direction.
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- `Seaborn <https://github.com/mwaskom/seaborn >`__
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- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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-
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- Although pandas has quite a bit of "just plot it" functionality built-in, visualization and
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- in particular statistical graphics is a vast field with a long tradition and lots of ground
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- to cover. The `Seaborn <https://github.com/mwaskom/seaborn >`__ project builds on top of pandas
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- and `matplotlib <http://matplotlib.org >`__ to provide easy plotting of data which extends to
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- more advanced types of plots then those offered by pandas.
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-
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`Vincent <https://github.com/wrobstory/vincent >`__
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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