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Getting Started with R in JupyterLite

The process for getting started with R follows the same general workflow as Getting Started with Python, with one key difference: you'll need the xeus-r kernel and R-specific packages in your environment.

Using the Default R Environment​

The steps for selecting an environment and creating a project are identical to the Python setup process:

  1. Select the default R environment
  2. Create your project
  3. Launch and use your notebook

Creating a Custom R Environment​

To create a custom R environment, follow the same steps as for Python. The video below demonstrates:

  • Adding the xeus-r kernel (required for R execution)
  • Installing R packages (example: ggplot2)
  • Real-time environment resolution process

Important: Remember to save your new environment after package resolution completes.

warning

When adding R packages, prefix them with r-. For example:

  • ggplot2 becomes r-ggplot2
  • dplyr becomes r-dplyr