Can I Use Rpy2 To Save A Pandas Dataframe To An .Rdata File?

I never used rpy2 before, but I am just wondering if I could use it to save a python object (a pandas DataFrame) in an R-readable file. I am having trouble to move objects between

Solution 1:

Here is how you write/read .RData files with rpy2 (since accepted solution is deprecated and doesn't show how to save to .RData file):

import rpy2
from rpy2 import robjects
from rpy2.robjects import pandas2ri
pandas2ri.activate()

# read .RData file as a pandas dataframe
def load_rdata_file(filename):
    r_data = robjects.r['get'](robjects.r['load'](filename))
    df = pandas2ri.ri2py(r_data)
    return df

# write pandas dataframe to an .RData file
def save_rdata_file(df, filename):
    r_data = pandas2ri.py2ri(df)
    robjects.r.assign("my_df", r_data)
    robjects.r("save(my_df, file='{}')".format(filename))

Solution 2:

You can use rpy2 to do this. Once you have the data in a panda, you have to transmit it to R. This link provides an experimental interface between Python Pandas and R data.frames. A code example copied from the website:

from pandas import DataFrame
import pandas.rpy.common as com

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)
 <class 'rpy2.robjects.vectors.DataFrame'>

print r_dataframe
      A B C
one   1 4 7
two   2 5 8
three 3 6 9

Solution 3:

Using the most recent version of rpy2, version 3.3.2, I was unable to get the other answers to work. It appears that conversion works a bit differently now.

import pandas
p_df = pandas.DataFrame(data={'col1': [1, 2], 'col2': [3, 4]})

The following code will convert the above pandas dataframe to an R dataframe and save the R dataframe as an R .rds file.

from rpy2 import robjects
from rpy2.robjects import pandas2ri
from rpy2.robjects.conversion import localconverter

# Convert pandas dataframe to R dataframe
with localconverter(robjects.default_converter + pandas2ri.converter):
    r_df = robjects.conversion.py2rpy(p_df)

# Save R dataframe as .rds file
r_file = "file.rds"
robjects.r.assign("my_df_tosave", r_df)
robjects.r(f"saveRDS(my_df_tosave, file='{r_file}')")

The following code will load the .rds file and convert it back to a pandas dataframe.

# Load as R dataframe from .rds file
r_file = "file.rds"
robjects.r(f"df_to_load <- readRDS('{r_file}')") 
r_df = robjects.r["df_to_load"]

# Convert R dataframe to pandas dataframe
with localconverter(robjects.default_converter + pandas2ri.converter):
    p_df = robjects.conversion.rpy2py(r_df)