# Warning: package 'reticulate' was built under R version 4.0.5 We are assigning these to some common nicknames for these packages so they are easier to reference later on. Open a new R script and import these packages using the import command. We can now load our newly installed Python libraries in R. We are going to install three different packages here, cartopy (for making maps), matplotlib (a common plotting package), and xarray (to import data). We specify "r-reticulate" because that is the Python environment we want to install the packages into. The conda_install function uses Miniconda to install Python packages. Next, we need to install some Python packages: conda_install("r-reticulate", "cartopy", forge = TRUE)Ĭonda_install("r-reticulate", "matplotlib") # If you have a named environment you want to use you can load it by name Use_python("/Users/smurphy/opt/anaconda3/envs/r-reticulate/bin/python") # Load the Python installation you want to use # I can see all my available Python versions and environments If you’ve used Python and have a environment with packages loaded that you’d like to use, you can load that using the following commands. Using repl_python() will open the r-reticulate Python environment by default. You’ll notice that when you’re using Python > is displayed in the console. # Type this in the console to open an interactive environment To do this, we will use the repl_python() command. We can use Python interactively within the console in R studio. Python code blocks will run as Python code when you knit your document. Once you have a code block you can code using typical Python syntax. When in an RMarkdown document you can either manually create a code block or click on the insert dropdown list in R Studio and select Python. R Markdown can contain both Python and R code blocks. More information about Python environments can be found here. You do not need to use this environment but I will be using it for the rest of this post. This will create a new Python environment on your machine called r-reticulate. When you install reticulate you are also installing Miniconda, a lightweight package manager for Python. Installationįirst, install the reticulate package: install.packages("reticulate") All data types will be converted to their equivalent type when being handed off between Python and R. You can also load Python packages and use them within your R script using a mix of Python and R syntax. Reticulate is a library that allows you to open a Python environment within R. Importing Python scripts and using user-defined functions within your R scriptsĪll of these require reticulate.Importing Python packages and using the commands within your R scripts.There are four ways to use Python code in your R workflow: Download all code used below from the GitHub repository!
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