Metadata-Version: 2.4
Name: ggplot
Version: 0.11.5
Summary: ggplot for python
Home-page: https://github.com/yhat/ggplot/
Author: Greg Lamp
Author-email: greg@yhathq.com
License: BSD
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Requires-Dist: six
Requires-Dist: statsmodels
Requires-Dist: brewer2mpl
Requires-Dist: matplotlib
Requires-Dist: scipy
Requires-Dist: patsy>=0.4
Requires-Dist: pandas
Requires-Dist: cycler
Requires-Dist: numpy
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: home-page
Dynamic: license
Dynamic: requires-dist
Dynamic: summary

ggplot
======

What is it?
~~~~~~~~~~~

``ggplot`` is a Python implementation of the grammar of graphics. It is
not intended to be a feature-for-feature port of
```ggplot2 for R`` <https://github.com/hadley/ggplot2>`__--though there
is much greatness in ``ggplot2``, the Python world could stand to
benefit from it. So there **will be feature overlap**, but not
neccessarily mimicry (after all, R is a little weird).

You can do cool things like this:

.. code:: python

    ggplot(diamonds, aes(x='price', color='clarity')) + \
        geom_density() + \
        scale_color_brewer(type='div', palette=7) + \
        facet_wrap('cut')

.. figure:: ./docs/example.png
   :alt: 

Installation
~~~~~~~~~~~~

.. code:: bash

    $ pip install -U ggplot
    # or 
    $ conda install -c conda-forge ggplot
    # or
    pip install git+https://github.com/yhat/ggplot.git

Examples
~~~~~~~~

Examples are the best way to learn. There is a Jupyter Notebook full of
them. There are also notebooks that show how to do particular things
with ggplot (i.e. `make a scatter
plot <./docs/how-to/Making%20a%20Scatter%20Plot.ipynb>`__ or `make a
histogram <./docs/how-to/Making%20a%20Scatter%20Plot.ipynb>`__).

-  `docs <./docs>`__
-  `gallery <./docs/Gallery.ipynb>`__
-  `various examples <./examples.md>`__

What happened to the old version that didn't work?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

It's gone--the windows, the doors,
`everything <https://www.youtube.com/watch?v=YuxCKv_0GZc>`__. Just
kidding, `you can find it
here <https://github.com/yhat/ggplot/tree/v0.6.6>`__, though I'm not
sure why you'd want to look at it. The data grouping and manipulation
bits were re-written (so they actually worked) with things like facets
in mind.

Contributing
~~~~~~~~~~~~

Thanks to all of the ggplot
`contributors <./contributors.md#contributors>`__! See
*`contributing.md <./contributing.md>`__*.
