RStudio and choosing a Linux distribution

Hi Folks!
After many years of annual vows to switch from MS-Windows to Linux (which I usually describe to myself as as switching "to a real operating system") and hesitating out of fear of the learning curve, I am now planning to set up my computer for a dual boot to Windows or Linux as insurance. The main thing I am now planning to do under Linux, besides learning how to use Linux, is running R and RStudio. (I note that for an R package to be shared on Cran it must be tested under at least two operating systems). Given that this is my use case, is there any Linux distribution that offers any special advantage in working with RStudio or R? Or with RStudio Server, maybe? I don't run RStudio Server now, but I'd like to eventually, in the short term as the easiest route to running it on my Android tablets (via browser). Alternatively, is there any distribution that has caused problems with R or RStudio?

In the event that multiple distributions are equally good for my stated purpose, I would welcome thoughts from experienced Linux users about distributions that are more advantageous to a new user. Directly to me at, as I think such comments are off-topic on this list.

I have a philosophic preference for commands and controls and options that are visible on-screen, so it is possible to find them rather than remember them).
“I consider that a man's brain originally is like a little empty attic, and you have to stock it with such furniture as you choose. A fool takes in all the lumber of every sort that he comes across, so that the knowledge which might be useful to him gets crowded out, or at best is jumbled up with a lot of other things, so that he has a difficulty in laying his hands upon it. Now the skillful workman is very careful indeed as to what he takes into his brain-attic. He will have nothing but the tools which may help him in doing his work, but of these he has a large assortment, and all in the most perfect order. It is a mistake to think that that little room has elastic walls and can distend to any extent.". —Sherlock Holmes

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If you are new to Linux then you should probably start with a Ubuntu derivative (not necessarily Ubuntu itself), e.g. Linux Mint, PopOS!, KDE neon, etc. Check which look and feel you like best.

I've used R/RStudio on a Linux server for many years, but only a few days ago did I switch to Linux on a new laptop. Installing R and RStudio Desktop was very straightforward as long as you know how to install some Linux packages via the command line, e.g. sudo apt install packagename.


I'm actually using a Windows-Ubuntu dualboot and I can recommend Ubuntu from my exprience. Installing updates and other packages is quite straightforward.

I wouldn't dual boot at all until you've tried a few distros -- get virtualbox and you can try them and delete them as much as you like with no commitment.

You dont need to dual boot any more with WSL(2). Follow the excellent guide at Using RStudio Server in Windows WSL2 – Posit Support. This guide covers Ubuntu nicely. When it comes to config, you can save yourself a lot of pain by using CRAN as Ubuntu Binaries - r2u (

I definitely agree that you should try a Debian based Linux distribution like Ubuntu. Dirk Eddelbuettel has done a tremendous work of making R on (Debian) Linux easy to use, not even requiring that you compile your packages from source.
Also there is a special interest mailing group for Debian users of R among the mailing groups maintained by the R project.
BTW, I am not aware of any requirement that CRAN packages have to be tested under at least two operating systems. I am aware of at least one package that works only under one operating system.

The distinction between a “package” and a “library” can be hard to keep straight. I find it helps me to refer to a “library” in R only this way


If I have to install or update in R, then it’s

install.packages(“dplyr”, ask = FALSE)

For system dependencies that get installed and updated in a terminal session (not the R console or an IDE) with the apt command line utility, I think of those all as “libraries.”

This helps me keep straight the difference and blundering around trying to install R packages in the terminal and system dependencies in an R sessions.

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