A Pythonic wrapper around R's ggplot

pip install pyggplot==27



pyggplot is a Pythonic wrapper around the R ggplot2 library.

It is based on a a straightforward take Pandas data frames and shove them into R via rpy2 approach.


Please visit


The easiest installation is via PyPI.

$ pip install pyggplot

You may be required to update pandas, rpy2, so you may be required to run

$ pip install --upgrade pyggplot 


import pandas as pd
import numpy as np
import ggplot

df = pd.DataFrame({'x': np.random.rand(100),
                   'y': np.random.randn(100),
                   'group': ['A','B'] * 50})

p = pyggplot.Plot(df)
p.add_scatter('x','y', color='group')
## or if you want to use it in IPython Notebook
# p.render_notebook()

Further usage

Takes a pandas.DataFrame object, then add layers with the various add_xyz functions (e.g. add_scatter).

Refer to the ggplot documentation about the layers (geoms), and simply replace geom_* with add_*. See:

You do not need to separate aesthetics from values - the wrapper will treat a parameter as value if and only if it is not a column name. (so y = 0 is a value, color = 'blue' is a value - except if you have a column 'blue', then it is a column!. And y = 'value' does not work, but that seems to be a ggplot issue).

When the DataFrame is passed to R:

  • row indices are turned into columns with 'reset_index',
  • multi level column indices are flattened by concatenating them with ' ', that is (X, 'mean') becomes 'x mean'.

Error messages are not great - most of them translate to 'one or more columns were not found', but they can appear as a lot of different actual messages such as

  • argument "env" is missing, with no default
  • object 'y' not found
  • object 'dat_0' not found
  • requires the following missing aesthetics: x
  • non numeric argument to binary operator

without actually quite pointing at what is strictly the offending value. Also, the error appears when rendering (or printing in the IPython Notebook), not when adding the layer.

Open questions

  • the stat support is not great - it doesn't easily map into pythonic objects. For now, do your stats in pandas - more powerful anyhow!
  • how could error messages be improved?

Other ggplots' for python