If you run print(my_python_array) in R, you get an error that my_python_array doesn’t exist.īut if you run a Python print command inside the py_run_string() function such as py_run_string ( 'for item in my_python_array: print(item)' ) Nothing shows up in your RStudio environment pane, and no value is returned. If you run that code in R, it may look like nothing happened.

The py_run_string() function executes whatever Python code is within the parentheses and quotation marks. array ()Īnd here’s one way to do that right in an R script: py_run_string ( 'import numpy as np' ) py_run_string ( 'my_python_array = np.array()' ) The Python code looks like this: import numpy as np my_python_array = np. To keep things simple, let’s start with just two lines of Python code to import the NumPy package for basic scientific computing and create an array of four numbers. If you’d like to follow along, install and load reticulate with install.packages('reticulate') and library(reticulate). You also need any Python modules, packages, and files your Python code depends on. In addition to reticulate, you need Python installed on your system. | Stay up to date on analytics and big data with the InfoWorld Big Data Report newsletter. R data manipulation tricks at your fingertips.| Read the InfoWorld tutorials: Learn to crunch big data with R. [ Get Sharon Machlis’s R tips in our how-to video series. Thanks to the R reticulate package, you can run Python code right within an R script-and pass data back and forth between Python and R. Or an API you want to access that has sample code in Python but not R. Maybe it’s a great library that doesn’t have an R equivalent (yet). And there can be good reasons an R user would want to do some things in Python. Learn how to run Python code inside an R script using the reticulate R packageĪs much as I love R, it’s clear that Python is also a great language-both for data science and general-purpose computing.

Run python in rstudio