Metadata-Version: 1.0
Name: ggplot
Version: 0.1.3
Summary: ggplot for python
Home-page: https://github.com/yhat/ggplot/
Author: Greg Lamp
Author-email: greg@yhathq.com
License: BSD
Description: {ggplot}
        ========
        
        ::
        
            from ggplot import *
            from pandasql import load_meat
            meat = load_meat()
        
            ggplot(aes(x='date', y='beef'), data=meat) + \
                geom_point() + \
                geom_line(color='lightblue') + \
                ggtitle("Beef: It's What's for Dinner") + \
                xlab("Date") + \
                ylab("Head of Cattle Slaughtered")
        
        What is it?
        ~~~~~~~~~~~
        
        Yes, it's another implementation 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
        ``ggplot``. I've tried other libraries like ``Bockah`` and ``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``
        -  tight integration with
           ```pandas`` <https://github.com/pydata/pandas>`__
        -  pip installable
        
        Getting Started
        ~~~~~~~~~~~~~~~
        
        Dependencies
        ^^^^^^^^^^^^
        
        -  ``matplotlib``
        -  ``pandas``
        -  ``numpy``
        -  ``scipy``
        
           unzip the matplotlibrc
           ======================
        
           $ unzip matplotlibrc.zip ~/ $ pip install ggplot
        
        Examples
        ~~~~~~~~
        
        ``geom_point``
        ^^^^^^^^^^^^^^
        
        ::
        
            from ggplot import *
            ggplot(diamonds, aes('carat', 'price')) + \
                geom_point(alpha=1/20.)
        
        ``geom_hist``
        ^^^^^^^^^^^^^
        
        ::
        
            p = ggplot(aes(x='carat'), data=diamonds)
            p + geom_hist() + ggtitle("Histogram of Diamond Carats") + labs("Carats", "Freq") 
        
        ``geom_bar``
        ^^^^^^^^^^^^
        
        ::
        
            p = ggplot(mtcars, aes('cyl'))
            p + geom_bar()
        
        TODO
        ~~~~
        
        -  finish README
        -  add matplotlibrc to build script
        -  distribute on PyPi
        -  come up with better name
        -  handle NAs gracefully
        -  make ``aes`` guess what the user actually means (DONE)
        -  aes:
        
           -  size
           -  se for stat\_smooth
           -  fix fill/colour
        
        -  geoms:
        
           -  geom\_abline (DONE)
           -  geom\_area (DONE)
           -  geom\_bar (IN PROGRESS)
           -  geom\_boxplot
           -  geom\_hline (DONE)
           -  geom\_ribbon (same as geom\_ribbon?)
           -  geom\_vline (DONE)
           -  stat\_bin2d (DONE)
           -  geom\_jitter
           -  stat\_smooth (bug)
        
        -  scales:
        
           -  scale\_colour\_brewer
           -  scale\_colour\_gradient
           -  scale\_colour\_gradient2
           -  scale\_x\_continuous
           -  scale\_x\_discrete
           -  scale\_y\_continuous
        
        -  facets:
        
           -  facet\_grid (DONE)
        
        
        
Platform: UNKNOWN
