Loading .RData files into Python

Question

I have a bunch of .RData time-series files and would like to load them directly into Python without first converting the files to some other extension (such as .csv). Any id

Answer 1

Jupyter Notebook Users

If you are using Jupyter notebook, you need to do 2 steps:

Step 1: go to http://www.lfd.uci.edu/~gohlke/pythonlibs/#rpy2 and download Python interface to the R language (embedded R) in my case I will use rpy2-2.8.6-cp36-cp36m-win_amd64.whl

Put this file in the same working directory you are currently in.

Step 2: Go to your Jupyter notebook and write the following commands

# This is to install rpy2 library in Anaconda
!pip install rpy2-2.8.6-cp36-cp36m-win_amd64.whl

and then

# This is important if you will be using rpy2
import os
os.environ['R_USER'] = 'D:\Anaconda3\Lib\site-packages\rpy2'

and then

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

This should allow you to use R functions in python. Now you have to import the readRDS as follow

readRDS = robjects.r['readRDS']
df = readRDS('Data1.rds')
df = pandas2ri.ri2py(df)
df.head()

Congratulations! now you have the Dataframe you wanted

However, I advise you to save it in pickle file for later time usage in python as

 df.to_pickle('Data1') 

So next time you may simply use it by

df1=pd.read_pickle('Data1')