Installing R and RStudio on OpenSUSE Leap 42.1

Installing R

To install R we should open software manager: “Main menu -> System -> YaST -> Software -> Software Management”, type R-base in the search field, then click on the “Search” button, mark checkboxes for R-base and R-base-devel packages and click on the “Accept” button:


For correct installation of additional packages we should previously install the GNU C and C++ compilers, in our case 4.8-8.4 version:


If we will work with XML documents we should also install libxml2-devel package:


Installing RStudio

Open RStudio download page and choose appropriate installer, for example RStudio 0.99.489 – Fedora 19+/RedHat 7+/openSUSE 13.1+ (64-bit), then download file rstudio-0.99.489-x86_64.rpm, in our case. When file will be downloaded, open Konsole (or Terminal) go to the directory with that file and type a command

sudo zypper install rstudio-0.99.489-x86_64.rpm


When the installation process will be finished we can open RStudio IDE with “Main menu -> Development -> RStudio”:


After running the RStudio main window should look like one:



4 thoughts on “Installing R and RStudio on OpenSUSE Leap 42.1

  1. Hi,
    as I know, we need to install gcc because some R packages are extended with C++ code. During the installation in R these packages are compiled with gcc. An error of package installation will appear if the gcc didn’t install in the system.
    Good luck,

    1. Thank you for your reply,

      I was just curious, I had the impression that the packages would come precompiled. I also find out that adding extra packages will compile them from source.

      Have a good day

      — flanaras

  2. Now to have a smooth experience in R in Opensuse Leap 42.1 it is also worth installing all these packages
    zypper install gcc gcc-c++ gcc-fortran libpng16-devel libgnutls-devel gnutls libxml2-devel libcurl-devel libopenssl-devel xorg-x11-devel makeinfo make texinfo openblas-devel-static openblas-devel libopenblas_pthreads0

    this will enable most packages to build properly and faster analysis using R. Enjoy!!

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