How do I quickly get started using R/Rstudio and Python together on a University-managed computer?
1. Install Miniconda. For most usage cases a default installation as performed as your non-administrative user will work best.
How-To: Install Miniconda Without Administrator Privileges in Windows.
How-To: Install Miniconda Without Administrator Privileges on a Mac.
2. Install R.
How-To: Install R From Company Portal
3. Install Rstudio.
How-To: Install Rstudio From Company Portal
4. Create a unique conda environment for each project to avoid dependency conflicts and ensure portablility
How-To: Rstudio: Create Conda Environment for Using Rstudio
5. Add channels to increase the number of available packages and versions.
How-To: Add Channel to Top of List in a Virtual Conda Environment via Command Line Interface.
How-To: Add Channel to Bottom of List in a Virtual Conda Environment via Command Line Interface.
6. Add R and Python packages to the conda environment as needed.
How-To: Using Anaconda - Install an R Package in a Virtual Conda Environment via Command Line Interface
How-To: Install a Package in a Virtual Conda Environment via Command Line Interface.
7. Launch Rstudio in an activated conda environment from the command line.
How-To: Rstudio: Launch Rstudio in Conda Environment From Command Line
8. Use reticulate and rpy2 packages for cross language object utilization.
R projects with embeded Python code:
How-To: Rstudio: Use Reticulate Package to Manage R-Python Integration
Python projects with embedded R code:
How-To: Use rpy2 Package to Manage Python-R Integration
9. Create backups to keep your work reproducible.
How-To: Backup a Virtual Conda Environment Configuration via Command Line Interface.
Informational: Best Practices for Managing Integrated R & Python Projects with Conda