Quick start guide to using R, Rstudio and Python together on University-managed computers including installation without administrator credentials, utilization of unique conda environments for each project, adding additional channels for packages, adding R and Python packages to the environment, launching Rstudio, utilizing the reticulate R package and backing up configurations for portability and reproducibility.
How to get Python and R talking to each other by using the reticulate package by embedding a Python session within your R session, allowing seamless, bidirectional communication.
Export a Conda Environment to Share Across OS Platforms
Integrating R and Python on Windows can be notoriously finicky. The rpy2 library bridges this gap beautifully, but installing it via traditional methods often triggers a cascade of compilation headaches. Using Conda eliminates this friction by managing pre-compiled binaries and dependencies smoothly.
Using VS Code as Integrated Development Environment (IDE) in Conda Environment for Python and R Development - Mac
Using VS Code as Integrated Development Environment (IDE) in Conda Environment for Python and R Development - Windows
Index of R/RStudio guides
Index of Articles for Managed Virtual Conda Environments
Index of Miniconda How-To Articles for Virtual Conda Environments
Best Practices for Managing Integrated R & Python Projects with Conda