How to Use R with Python

Working with data often involves using multiple tools together to achieve desired results. If you’re a data scientist or an analyst, you’ve probably used both Python and R for your tasks. This tutorial will guide you on how to use R within Python to get the best from both languages. We’ll be using a library called rpy2 to carry out this operation.

Step 1: Installing rpy2

Before we can use rpy2, we need to install it in our Python environment. Use the following command to install:

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pip install rpy2

Step 2: Loading R packages

After installation, we can proceed to load our required packages. For this tutorial, we will load the base package from R.

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import rpy2.robjects.packages as rpackages
base_package = rpackages.importr('base')
 
base_package._libPaths()

Step 3: Running R scripts

We can run R scripts using the robjects.r function after it’s imported

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from rpy2 import robjects
 
robjects.r('''
       variable <- c(1, 2, 3)
       print(variable)
    ''')

Step 4: Accessing variables

Variables can be accessed from the R environment

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variable = robjects.r['variable']
print(variable)

Now, let’s look at the entire code:

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import rpy2.robjects.packages as rpackages
from rpy2 import robjects
 
base_package = rpackages.importr('base')
 
base_package._libPaths()
 
robjects.r('''
variable <- c(1, 2, 3)
print(variable)
''')
 
variable = robjects.r['variable']
print(variable)
 
[1] 1 2 3
[1] 1 2 3

Conclusion

In this tutorial, we’ve learned how to use R with Python using the rpy2 library. We saw how we could install this library, run R scripts, and even access R variables from Python. This interaction opens a world of possibilities where both languages can complement each other in data analysis tasks, making your work easier and more efficient.