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.. currentmodule:: pandas.rpy

rpy2 / R interface

Note

This is all highly experimental. I would like to get more people involved with building a nice RPy2 interface for pandas

If your computer has R and rpy2 (> 2.2) installed (which will be left to the reader), you will be able to leverage the below functionality. On Windows, doing this is quite an ordeal at the moment, but users on Unix-like systems should find it quite easy. rpy2 evolves in time, and is currently reaching its release 2.3, while the current interface is designed for the 2.2.x series. We recommend to use 2.2.x over other series unless you are prepared to fix parts of the code, yet the rpy2-2.3.0 introduces improvements such as a better R-Python bridge memory management layer so I might be a good idea to bite the bullet and submit patches for the few minor differences that need to be fixed.

# if installing for the first time
hg clone http://bitbucket.org/lgautier/rpy2

cd rpy2
hg pull
hg update version_2.2.x
sudo python setup.py install

Note

To use R packages with this interface, you will need to install them inside R yourself. At the moment it cannot install them for you.

Once you have done installed R and rpy2, you should be able to import pandas.rpy.common without a hitch.

Transferring R data sets into Python

The load_data function retrieves an R data set and converts it to the appropriate pandas object (most likely a DataFrame):

.. ipython:: python

   import pandas.rpy.common as com
   infert = com.load_data('infert')

   infert.head()


Converting DataFrames into R objects

.. versionadded:: 0.8

Starting from pandas 0.8, there is experimental support to convert DataFrames into the equivalent R object (that is, data.frame):

.. ipython:: python

   from pandas import DataFrame

   df = DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C':[7,8,9]},
                  index=["one", "two", "three"])
   r_dataframe = com.convert_to_r_dataframe(df)

   print type(r_dataframe)
   print r_dataframe


The DataFrame's index is stored as the rownames attribute of the data.frame instance.

You can also use convert_to_r_matrix to obtain a Matrix instance, but bear in mind that it will only work with homogeneously-typed DataFrames (as R matrices bear no information on the data type):

.. ipython:: python

   r_matrix = com.convert_to_r_matrix(df)

   print type(r_matrix)
   print r_matrix


Calling R functions with pandas objects

High-level interface to R estimators