How can I import R dataframes into Pandas?

Question

I am using R off and on as a "backend" to Python and thus need to occassionaly import dataframes from R into Python; but I can't figure out how to import an R data.frame as a Pandas DataFrame .

For example if I create a dataframe in R

rdf = data.frame(a=c(2, 3, 5), b=c("aa", "bb", "cc"), c=c(TRUE, FALSE, TRUE))

and then pull it into Python using rmagic with

%Rpull -d rdf

I get

array([(2.0, 1, 1), (3.0, 2, 0), (5.0, 3, 1)], 
      dtype=[('a', '<f8'), ('b', '<i4'), ('c', '<i4')])

I don't know what this is, and it's certainly not the

pd.DataFrame({'a': [2, 3, 5], 'b': ['aa', 'bb', 'cc'], 'c': [True, False, True]})

that I would expect.

The only thing that comes close to working for me is to use use a file to transfer the dataframe by writing in R

write.csv(data.frame(a=c(2, 3, 5), b=c("aa", "bb", "cc"), c=c(TRUE, FALSE, TRUE)), file="TEST.csv")

and then reading in Python

pd.read_csv("TEST.csv")

though even this approach produces an additional column: "Unnamed: 0".

What is the idiom for importing an R dataframe into Python as a Pandas dataframe?

Answer 1

First: array([(2.0, 1, 1), (3.0, 2, 0), (5.0, 3, 1)], dtype=[('a', '<f8'), ('b', '<i4'), ('c', '<i4')]) . That is a numpy structured array . http://docs.scipy.org/doc/numpy/user/basics.rec.html/ . You can easily convert it to pandas DF by using pd.DataFrame :

In [65]:

from numpy import *
print pd.DataFrame(array([(2.0, 1, 1), (3.0, 2, 0), (5.0, 3, 1)], dtype=[('a', '<f8'), ('b', '<i4'), ('c', '<i4')]))
   a  b  c
0  2  1  1
1  3  2  0
2  5  3  1

b column is coded (as if factor() 'ed in R ), c column was converted from boolean to int . a was converted from int to float ( '<f8' , actually I found that unexpected)

2nd, I think pandas.rpy.common is the most convenient way of fetching data from R : http://pandas.pydata.org/pandas-docs/stable/r_interface.html (It is probably too brief, so I will add another example here):

In [71]:

import pandas.rpy.common as com
DF=pd.DataFrame({'val':[1,1,1,2,2,3,3]})
r_DF = com.convert_to_r_dataframe(DF)
print pd.DataFrame(com.convert_robj(r_DF))
   val
0    1
1    1
2    1
3    2
4    2
5    3
6    3

Finally, the Unnamed: 0 column is the index column. You can avoid it by providing index_col=0 to pd.read_csv()

Answer 2

What about this ( see pandas 0.13.1 documentation ):

%load_ext rmagic
%R rdf = data.frame(a=c(2, 3, 5), b=c("aa", "bb", "cc"), c=c(TRUE, FALSE, TRUE))

import pandas.rpy.common as com

print com.load_data('rdf')
   a   b      c
1  2  aa   True
2  3  bb  False
3  5  cc   True