How to Install and Uninstall R-core.x86_64 Package on Fedora 38
Last updated: November 28,2024
1. Install "R-core.x86_64" package
In this section, we are going to explain the necessary steps to install R-core.x86_64 on Fedora 38
$
sudo dnf update
Copied
$
sudo dnf install
R-core.x86_64
Copied
2. Uninstall "R-core.x86_64" package
Learn how to uninstall R-core.x86_64 on Fedora 38:
$
sudo dnf remove
R-core.x86_64
Copied
$
sudo dnf autoremove
Copied
3. Information about the R-core.x86_64 package on Fedora 38
Last metadata expiration check: 4:01:41 ago on Sat Mar 16 16:59:57 2024.
Available Packages
Name : R-core
Version : 4.3.3
Release : 1.fc38
Architecture : x86_64
Size : 64 M
Source : R-4.3.3-1.fc38.src.rpm
Repository : updates
Summary : The minimal R components necessary for a functional runtime
URL : https://www.r-project.org
License : GPL-2.0-or-later
Description : A language and environment for statistical computing and graphics.
: R is similar to the award-winning S system, which was developed at
: Bell Laboratories by John Chambers et al. It provides a wide
: variety of statistical and graphical techniques (linear and
: nonlinear modelling, statistical tests, time series analysis,
: classification, clustering, ...).
:
: R is designed as a true computer language with control-flow
: constructions for iteration and alternation, and it allows users to
: add additional functionality by defining new functions. For
: computationally intensive tasks, C, C++ and Fortran code can be linked
: and called at run time.
Available Packages
Name : R-core
Version : 4.3.3
Release : 1.fc38
Architecture : x86_64
Size : 64 M
Source : R-4.3.3-1.fc38.src.rpm
Repository : updates
Summary : The minimal R components necessary for a functional runtime
URL : https://www.r-project.org
License : GPL-2.0-or-later
Description : A language and environment for statistical computing and graphics.
: R is similar to the award-winning S system, which was developed at
: Bell Laboratories by John Chambers et al. It provides a wide
: variety of statistical and graphical techniques (linear and
: nonlinear modelling, statistical tests, time series analysis,
: classification, clustering, ...).
:
: R is designed as a true computer language with control-flow
: constructions for iteration and alternation, and it allows users to
: add additional functionality by defining new functions. For
: computationally intensive tasks, C, C++ and Fortran code can be linked
: and called at run time.