rpy2 / R interface

Warning

Up to pandas 0.19, a pandas.rpy module existed with functionality to convert between pandas and rpy2 objects. This functionality now lives in the rpy2 project itself. See the updating section of the previous documentation for a guide to port your code from the removed pandas.rpy to rpy2 functions.

rpy2 is an interface to R running embedded in a Python process, and also includes functionality to deal with pandas DataFrames. Converting data frames back and forth between rpy2 and pandas should be largely automated (no need to convert explicitly, it will be done on the fly in most rpy2 functions). To convert explicitly, the functions are pandas2ri.py2ri() and pandas2ri.ri2py().

See also the documentation of the rpy2 project: https://rpy2.readthedocs.io.

In the remainder of this page, a few examples of explicit conversion is given. The pandas conversion of rpy2 needs first to be activated:

In [1]: from rpy2.robjects import pandas2ri
   ...: pandas2ri.activate()
   ...: 

Transferring R data sets into Python

Once the pandas conversion is activated (pandas2ri.activate()), many conversions of R to pandas objects will be done automatically. For example, to obtain the ‘iris’ dataset as a pandas DataFrame:

In [2]: from rpy2.robjects import r

In [3]: r.data('iris')

In [4]: r['iris'].head()
Out[4]: 
    Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species
0           5.1          3.5           1.4          0.2  setosa
1           4.9          3.0           1.4          0.2  setosa
2           4.7          3.2           1.3          0.2  setosa
3           4.6          3.1           1.5          0.2  setosa
4           5.0          3.6           1.4          0.2  setosa

If the pandas conversion was not activated, the above could also be accomplished by explicitly converting it with the pandas2ri.ri2py function (pandas2ri.ri2py(r['iris'])).

Converting DataFrames into R objects

The pandas2ri.py2ri function support the reverse operation to convert DataFrames into the equivalent R object (that is, data.frame):

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

In [6]: r_dataframe = pandas2ri.py2ri(df)

In [7]: print(type(r_dataframe))
Out[7]: <class 'rpy2.robjects.vectors.DataFrame'>

In [8]: print(r_dataframe)
Out[8]: 
      A B C
one   1 4 7
two   2 5 8
three 3 6 9

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