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ggplot for python

Project description

{ggplot} from Yhat

read more on our blog

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")

What is it?

Yes, it’s another port of 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 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.


  • 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
  • pip installable

Getting Started


This package depends on the following packages, although they should be automatically installed if you use pip:

  • matplotlib
  • pandas
  • numpy
  • scipy
  • statsmodels
  • patsy


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!


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() + \


from ggplot import *
ggplot(diamonds, aes('carat', 'price')) + \
    geom_point(alpha=1/20.) + \
    ylim(0, 20000)


p = ggplot(aes(x='carat'), data=diamonds)
p + geom_histogram() + ggtitle("Histogram of Diamond Carats") + labs("Carats", "Freq")


ggplot(diamonds, aes(x='price', color='cut')) + \
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()


p = ggplot(mtcars, aes('factor(cyl)'))
p + geom_bar()


The list is long, but distinguished. We’re looking for contributors! Email greg at for more info. For getting started with contributing, check out these docs

Project details

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ggplot-0.4.7-py2.7.egg (4.0 MB) Copy SHA256 hash SHA256 Egg 2.7
ggplot-0.4.7.tar.gz (3.8 MB) Copy SHA256 hash SHA256 Source None

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