JupyterLab as a Linux alternative to RStudio
Updated
Our verdict
JupyterLab can replace RStudio for users who prefer a notebook‑centric workflow and want to mix R with other languages. It provides a code editor, an R console via the IRkernel, plotting, package management, and debugging through extensions. It is best for data scientists who already use Jupyter notebooks and need a single, web‑based interface. Traditional RStudio users who rely on a dedicated R IDE feel‑good workflow may find JupyterLab less polished for R‑specific tasks.
- License
- BSD-3-Clause
- Price
- Free
- Latest version
- 4.6.5
- Rating
- —
What works the same
- Both offer code editing with syntax highlighting for R
- Both provide an integrated R console to run scripts
- Both support plotting and display of visual output
- Both include package management tools
- Both allow project‑style organization of files
What is different
- JupyterLab is web‑based; RStudio runs as a native desktop app
- RStudio’s debugging is built‑in; JupyterLab relies on extensions for debugging R code
- RStudio has a dedicated R console; JupyterLab uses a notebook cell console that mixes code and output
- JupyterLab’s file browser is part of the web UI, not a separate pane
- RStudio offers a more polished R‑specific UI; JupyterLab is more generic
- Missing: RStudio’s integrated profiler and session snapshot features
Opening your RStudio files
JupyterLab can open R scripts (.R) and R Markdown (.Rmd) files directly, but it does not natively read RStudio’s .Rproj project files or .RData workspace snapshots. Exporting from JupyterLab to an RStudio project requires saving the script and manually creating a new .Rproj file if needed.
Switching from RStudio to JupyterLab, step by step
- Install the IRkernel package in R and run
IRkernel::installspec()to register the R kernel with JupyterLab. - Launch JupyterLab from the terminal or launcher and open a new notebook selecting the R kernel.
- Copy RStudio scripts into the JupyterLab file browser or use the “Upload” button.
- Run cells to execute code; use the built‑in plot area for visual output.
- Install JupyterLab extensions such as
jupyterlab-gitorjupyterlab-variableInspectorfor added functionality. - Save notebooks as .ipynb or export to .Rmd if you need RStudio compatibility.
Key features of JupyterLab
- Web‑based interface accessible via any modern browser
- Supports multiple kernels (Python, R, Julia, etc.)
- Built‑in terminal and file browser
- Extensible via plugins (e.g., Git, LaTeX, data viewers)
- Rich output rendering (plots, tables, widgets)
- Keyboard shortcuts for notebook navigation
- Integrated code completion and linting
How to install JupyterLab on Linux
sudo apt install jupyterlabsudo dnf install jupyterlabsudo pacman -S jupyterlabFrequently asked questions
Does JupyterLab support R package installation?
Yes, use install.packages() or devtools::install_github() inside a notebook cell, just like in RStudio.
Can I debug R code in JupyterLab?
Debugging is possible via extensions like jupyterlab-debugger and the IRkernel’s debug() function, but it is less integrated than RStudio’s built‑in debugger.
Will my RStudio plots appear correctly in JupyterLab?
Plots generated with base R or ggplot2 render inline in JupyterLab’s output area, so you’ll see them just as in RStudio, though the layout differs.
