Available through JupyterLab
R is a programming language for statistical computing, data analysis, and visualization. In EOxHub Workspaces, R notebooks can run alongside Python notebooks in JupyterLab, using the same Workspace storage and computational resources.
What is the R kernel?¶
A notebook kernel runs the code in notebook cells. The R environment uses IRkernel to execute R code and display results, tables, and plots directly in JupyterLab.
The provided environment includes packages for:
filtering, transforming, and summarizing tables with
dplyrcreating plots with
ggplot2reading and processing vector data with
sfworking with raster data with
terra
Using R in EOxHub¶
Start JupyterLab in your Workspace.
Open the Launcher and select the R kernel under Notebook.
Write R code in a cell and run it with
Shift+Enter.
For an existing notebook, use Kernel → Change Kernel to select the R environment.
R notebooks use the same .ipynb file format as other Jupyter notebooks. Select the R kernel when opening an R example.
Examples and learning resources¶
The EOxHub Example Notebooks include an R example covering table operations, plotting, vector data, raster calculations, and file export.
The example uses data bundled with R and its packages, so no external downloads or credentials are required.
For additional packages or custom environments, see Conda Store.
Additional resources: