Most R users probably just run RStudio Desktop from Posit on their local computers. This involves manually installing R, RStudio and all other packages.
However it is often the case that users are operating in a restricted computing environment, such as in a corporate or government setting. Alternatively you may wish to create a custom development environment to test or replicate some other specific setup. This is a good case to move away from locally managed software to containerization, such as Docker.
I have set up a Github repository that sets up a local data science development environment in the browser.
It builds a docker container including:
- Ubuntu 20.04 LTS
- R version 4.2
- RStudio Server 2022.02.3+492
- All tidyverse packages and devtools
- tex & publishing-related package
The image builds on the rocker/verse image from Rocker Project.
Some other enhanced configuration options are included in the Dockerfile, such as preloading you RStudio preferences to get the same look and feel you have locally, the option to install other CRAN packages & mounting local volumes to persist your work locally.
Go here for Step by step instructions: