How to Uninstall R on Mac: Clean Removal Without Lingering Files Left Behind

To uninstall R on Mac completely, you’ll need more than just dragging the app to the trash—lingering files can haunt your system later. ✨ I’ve cleaned up enough half-uninstalled packages to know the right way: Terminal commands, hidden library folders, and a final sweep for stragglers.

The process takes about 10 minutes but saves hours of frustration when R keeps reappearing in your scripts.

Start by quitting RStudio and any active R sessions, then open Terminal for the heavy lifting. The brew uninstall r command handles the main package, but you’ll also need to manually delete files from /Library/Frameworks/ and ~/Library/R/.

Here’s where most tutorials drop the ball—skipping these steps leaves behind configuration files that can break future installs or cause permission errors.

You’ll end up with a completely clean slate, ready for a fresh R installation or another language entirely. The Terminal commands are straightforward, but the real trick is knowing which hidden folders to check afterward.

I’ve included a checklist of common leftover paths so you don’t miss anything—trust me, you’ll thank yourself later when R --version returns nothing.

If you’re reinstalling R later, back up your scripts and packages first. The cleanup process wipes everything, but a quick brew list before uninstalling helps you remember what you’ll need to reinstall.

For those who prefer GUI methods, I’ll cover the Finder route too—though it’s slower and less thorough. Let’s get started with the full removal steps.

What you need

Step-by-step instructions for removing R completely from your Mac

Here’s how to scrub R from your system—no leftover libraries, no hidden caches.

Before touching anything, close every R-related process. Open Activity Monitor (Applications > Utilities), search for "R," and force-quit any running instances. This prevents file locks that could corrupt your uninstall.

Next, check for lingering RStudio sessions. Open Force Quit Applications (Command+Shift+Esc), select RStudio if it’s running, and confirm the quit. If you skip this, you might encounter permission errors later when deleting files.

Locate the R application in Launchpad or Applications folder. Drag it to the Trash—don’t just delete it from Finder, as this can leave behind preference files. Repeat for RStudio if installed.

Empty the Trash immediately to finalize deletion. This removes the main executables, but hidden files remain in your system directories. We’ll tackle those next.

Open Terminal (Applications > Utilities) and run these commands one by one to purge all traces of R:

sudo rm -rf ~/Library/R (removes user-specific R libraries)
sudo rm -rf /Library/Frameworks/R.framework (removes system-wide R framework)
sudo rm -rf ~/Library/Preferences/org.r-project.R.plist (removes R preferences)
sudo rm -rf ~/Library/Application\ Support/RStudio (removes RStudio support files)

Enter your admin password when prompted. Verify each command completes without errors—if you see "No such file or directory", those files were already gone. This ensures no leftover caches or configurations interfere with future installs.

For a truly clean slate, run these additional Terminal commands to scrub deeper:

sudo rm -rf /Library/LaunchDaemons/org.r-project.R.plist
sudo rm -rf /Library/LaunchAgents/org.r-project.R.plist
sudo rm -rf /usr/local/bin/R (if R was installed via Homebrew or manually)

These commands target system-level files that might persist after a basic uninstall. If you’re reinstalling R soon, this step saves headaches later. Double-check with ls /usr/local/bin to confirm R isn’t lingering.

Open Terminal again and run which R. If you see "No such file or directory", R is fully removed. For RStudio, check Applications—it should no longer appear.

Reboot your Mac to ensure all processes are fully terminated. This step flushes any cached references to R in memory. After reboot, you can safely reinstall R or RStudio without conflicts.

Tips & tricks for perfect R removal on Mac

Between us, I've helped countless users completely purge R from their systems—here's what nobody tells you about getting it right the first time.

Process Isolation: The most critical step is Step 1—don't rush through quitting processes. I've seen users skip this and encounter permission errors during deletion. Open Activity Monitor and look for any process containing "R" in its name, not just "R.app". Also check for hidden processes by sorting by CPU usage—sometimes R sessions linger in the background even when you think they're closed.

Terminal Command Strategy: When running those sudo rm -rf commands in Step 3, type them carefully—one typo can delete critical system files. I recommend copying each command directly from reliable sources rather than retyping. Also, verify each path exists by running ls before deletion (e.g., ls ~/Library/R). If you see "No such file or directory", those files were already removed and you can skip that command.

Hidden File Rescue: Step 4's optional commands target system-level files that often persist. If you're reinstalling R soon, absolutely run these—they'll save you hours of debugging later. But if you're completely done with R, you can skip them. Just remember, these commands require admin privileges, so have your password ready before starting.

Verification Protocol: After running which R in Step 5, don't stop there. Also check for lingering RStudio components by running ls /Applications and ls ~/Applications. Sometimes RStudio's uninstaller leaves behind support files that can cause conflicts. A full reboot is non-negotiable—it flushes all cached references and ensures clean system state.

Frequently asked questions

Wrapping up and next steps

Uninstalling R from your Mac doesn’t have to be a hassle—with the right steps, you can completely remove it and free up space without leaving behind any lingering files. Whether you’re switching to another tool or simply decluttering, you now know how to cleanly wipe R from your system. 🎉

Ready to take the next step? Explore lightweight alternatives like Python or Julia, or dive into other data tools that might better fit your workflow. Your Mac (and future projects) will thank you!