Metadata-Version: 1.1
Name: ggplot
Version: 0.5.8
Summary: ggplot for python
Home-page: https://github.com/yhat/ggplot/
Author: Greg Lamp
Author-email: greg@yhathq.com
License: BSD
Description: |image|
        
        {ggplot} from `Yhat <http://yhathq.com>`__
        ==========================================
        
        read more on our
        `blog <http://blog.yhathq.com/posts/ggplot-for-python.html>`__
        
        ::
        
            from ggplot import *
        
            ggplot(aes(x='date', y='beef'), data=meat) + \
                geom_point(color='lightblue') + \
                stat_smooth(span=.15, color='black', se=True) + \
                ggtitle("Beef: It's What's for Dinner") + \
                xlab("Date") + \
                ylab("Head of Cattle Slaughtered")
        
        .. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/ggplot_demo_beef.png
           :alt: image
        
           image
        What is it?
        -----------
        
        Yes, it's another port of
        `ggplot2 <https://github.com/hadley/ggplot2>`__. One of the biggest
        reasons why I continue to reach for ``R`` instead of ``Python`` for data
        analysis is the lack of an easy to use, high level plotting package like
        ``ggplot2``. I've tried other libraries like
        `bokeh <https://github.com/continuumio/bokeh>`__ and
        `d3py <https://github.com/mikedewar/d3py>`__ but what I really want is
        ``ggplot2``.
        
        ``ggplot`` is just that. It's an extremely un-pythonic package for doing
        exactly what ``ggplot2`` does. The goal of the package is to mimic the
        ``ggplot2`` API. This makes it super easy for people coming over from
        ``R`` to use, and prevents you from having to re-learn how to plot
        stuff.
        
        Goals
        -----
        
        -  same API as ``ggplot2`` for ``R``
        -  never use matplotlib again
        -  ability to use both American and British English spellings of
           aesthetics
        -  tight integration with `pandas <https://github.com/pydata/pandas>`__
        -  pip installable
        
        Getting Started
        ---------------
        
        Dependencies
        ~~~~~~~~~~~~
        
        This package depends on the following packages, although they should be
        automatically installed if you use ``pip``:
        
        -  ``matplotlib``
        -  ``pandas``
        -  ``numpy``
        -  ``scipy``
        -  ``statsmodels``
        -  ``patsy``
        
        Installation
        ~~~~~~~~~~~~
        
        Installing ``ggplot`` is really easy. Just use ``pip``!
        
        ::
        
            $ pip install ggplot
        
        Loading ``ggplot``
        ~~~~~~~~~~~~~~~~~~
        
        ::
        
            # run an IPython shell (or don't)
            $ ipython
            In [1]: from ggplot import *
        
        That's it! You're ready to go!
        
        Examples
        --------
        
        ::
        
            meat_lng = pd.melt(meat[['date', 'beef', 'pork', 'broilers']], id_vars='date')
            ggplot(aes(x='date', y='value', colour='variable'), data=meat_lng) + \
                geom_point() + \
                stat_smooth(color='red')
        
        .. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/ggplot_meat.png
           :alt: image
        
           image
        ``geom_point``
        ~~~~~~~~~~~~~~
        
        ::
        
            from ggplot import *
            ggplot(diamonds, aes('carat', 'price')) + \
                geom_point(alpha=1/20.) + \
                ylim(0, 20000)
        
        .. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/diamonds_geom_point_alpha.png
           :alt: image
        
           image
        ``geom_histogram``
        ~~~~~~~~~~~~~~~~~~
        
        ::
        
            p = ggplot(aes(x='carat'), data=diamonds)
            p + geom_histogram() + ggtitle("Histogram of Diamond Carats") + labs("Carats", "Freq")
        
        .. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/diamonds_carat_hist.png
           :alt: image
        
           image
        ``geom_density``
        ~~~~~~~~~~~~~~~~
        
        ::
        
            ggplot(diamonds, aes(x='price', color='cut')) + \
                geom_density()
        
        .. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/geom_density_example.png
           :alt: image
        
           image
        ::
        
            meat_lng = pd.melt(meat[['date', 'beef', 'broilers', 'pork']], id_vars=['date'])
            p = ggplot(aes(x='value', colour='variable', fill=True, alpha=0.3), data=meat_lng)
            p + geom_density()
        
        .. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/density_with_fill.png
           :alt: image
        
           image
        ``geom_bar``
        ~~~~~~~~~~~~
        
        ::
        
            p = ggplot(mtcars, aes('factor(cyl)'))
            p + geom_bar()
        
        .. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/mtcars_geom_bar_cyl.png
           :alt: image
        
           image
        TODO
        ----
        
        `The list is long, but
        distinguished. <https://github.com/yhat/ggplot/blob/master/TODO.md>`__
        We're looking for contributors! Email greg at yhathq.com for more info.
        For getting started with contributing, check out `these
        docs <https://github.com/yhat/ggplot/blob/master/docs/contributing.md>`__
        
        |image|
        
        .. |image| image:: https://secure.travis-ci.org/yhat/ggplot.png?branch=master
           :target: http://travis-ci.org/yhat/ggplot
        .. |image| image:: https://ga-beacon.appspot.com/UA-46996803-1/ggplot/README.md
           :target: https://github.com/yhat/ggplot
        
Platform: UNKNOWN
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
