![]() (If you don’t specify, it’ll use your system default.) ``` my_python_array2 = r.my_r_vector print(my_python_array2) ``` It loads the reticulate package and then you specify the version of Python you want to use. This first chunk is for R code-you can see that with the r after the opening bracket. You can create a new R Markdown document in RStudio by choosing File > New File > R Markdown.Ĭode chunks start with three backticks ( ```) and end with three backticks, and they have a gray background by default in RStudio. R Markdown lets you combine text, code, code results, and visualizations in a single document. ![]() Another way I like is to use an R Markdown document. py file, and use the py_run_file() function. One is to put all the Python code in a regular. So there are a few other ways to run Python in R and reticulate. It’s going to get annoying running Python code line by line like this, though, if you have more than a couple of lines of code. 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. The Python code looks like this: import numpy as np my_python_array = np.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()") 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).
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