How to Install R and RStudio on Fedora 40 or 39

R is a powerful programming language widely used for statistical computing, data analysis, and visualization. It offers extensive libraries and tools for statistical techniques and graphical modeling, making it a popular choice in data science, research, and academia. RStudio is an integrated development environment (IDE) for R that enhances the user experience with features like syntax highlighting, debugging, and project management tools, all within a user-friendly interface.

On Fedora 40 or 39, both R and RStudio are readily available in the Fedora repositories, making their installation straightforward. This guide will demonstrate how to install R and RStudio using Fedora’s package manager, along with tips on managing R packages via CRAN (The Comprehensive R Archive Network) or using the alternative cran2copr repository.

Update Fedora Before R Lang Installation

Before the R language installation, ensure your Fedora system is up to date. Execute the following command in the terminal to refresh and upgrade your system packages:

sudo dnf upgrade --refresh

This command ensures all existing packages are updated, and any available system improvements are applied, paving the way for a smoother installation of new software.

Method 1: Install R Lang via DNF Command

Fedora Linux provides a convenient method to install the R programming language through its default package manager, DNF.

Option 1: Basic R Language Installation

For a standard installation of R, which includes the core components sufficient for most use cases, use the command:

sudo dnf install R

This installation includes the primary R language functionalities required for statistical computations and graphics.

Option 2: Install R Programming Language with Dependencies

To include all dependencies that enhance R’s functionality, especially for development purposes, use the command:

sudo dnf install -y R-core R-core-devel R-java R-java-devel libRmath libRmath-devel

Here’s what each package comprises:

• R-core: Contains the fundamental R language components, essential libraries, and datasets.
• R-core-devel: Provides necessary headers and development tools for building R packages.
• R-java: Integrates Java support in R, which is useful when working with Java libraries or applications.
• R-java-devel: Supplies headers and tools for building R packages that require Java.
• libRmath: Includes the mathematical functions used within R for advanced calculations.
• libRmath-devel: Offers development resources for R packages relying on mathematical functions.

For specific compilation scenarios, additional libraries may be needed to ensure full functionality:

sudo dnf install libcurl-devel openssl-devel harfbuzz-devel fribidi-devel freetype-devel libpng-devel libjpeg-turbo-devel

These libraries address specific requirements such as secure data transfer, text rendering, and image processing, which are crucial for R packages that depend on these capabilities.

Method 2: Install R Lang with RStudio

The following two installation methods will install R Lang, but this time with the RStudio Desktop.

Installing R with RStudio IDE

For users who require an Integrated Development Environment (IDE) along with the R language, installing RStudio Desktop is the optimal route. First, ensure R is installed:

sudo dnf install R

Following R installation, proceed to install RStudio Desktop:

sudo dnf install rstudio-desktop

RStudio Desktop provides an extensive environment for R development, making it more straightforward to write, debug, and visualize your R code. This setup is ideal for developers seeking a cohesive statistical computing and graphics workspace.

Option 4: Install R Programming Language with RStudio and Dependencies

To facilitate a full development setup with RStudio and R language dependencies:

sudo dnf install -y R-core R-core-devel R-java R-java-devel libRmath libRmath-devel rstudio-desktop

This command installs R and RStudio and all essential components for robust development activities, such as package development and integration with Java-based applications.

Including R-core-devel, R-java-devel, and libRmath-devel ensures that all the necessary development headers and tools are available for compiling complex R projects. This comprehensive installation supports advanced R functionalities, which can benefit developers working on intricate statistical models or integrating R with other software.

Verifying R Language Installation on Fedora

Step 1: Confirming R Installation

Once you have completed the installation of R and its related packages, ensuring the setup was successful is crucial. Open the terminal and initiate the R environment with the following command:

R

Step 2: Exit R Console

If the installation is correct, the R console will appear. You can execute R commands, explore datasets, and perform statistical analysis here. To conclude the R session and return to the terminal, enter:

q()

When prompted to save the workspace image, you can type ‘n’ to exit without saving or ‘y’ to save the current R workspace for future sessions. This verification step confirms that R is properly installed and functional on your Fedora system and ready for data exploration and analytical tasks.

Launching RStudio Desktop

Starting RStudio from the Terminal

To open RStudio directly using the command-line interface, enter the following command in your terminal:

rstudio

Opening RStudio via the GUI

Alternatively, you can launch RStudio using the Fedora graphical user interface. Navigate through the following path:

Activities > Show Applications > RStudio

How to Install R Packages from CRAN

Step 1: Locating R Packages on CRAN

To enhance your data analysis with R, you might need additional packages from the Comprehensive R Archive Network (CRAN), the primary repository for R packages.

Begin by launching the R environment on your Fedora system with the following command:

R

Within the R console, locate a desired package by utilizing what is available.packages() function lists all packages available for installation from CRAN. For instance:

available.packages(pattern = "ggplot2")

Replace “ggplot2” with the relevant package name to check for availability.

Step 2: Installing R Packages

After identifying the necessary package, you can install it directly from the R console. Execute the following:

install.packages("package_name")

Replace “package_name” with the actual name of the package, such as “ggplot2” to install it. This command fetches the package from CRAN and installs it and its dependencies.

Step 3: Updating R Packages

It is crucial to keep your packages up to date. To update a specific R package to its latest version on CRAN, use:

update.packages("<package name>")

Again, replace “package_name” with the actual name of the package you wish to update.

Step 4: Remove R Packages

Should you need to remove an R package from your system, the following command in the R console will suffice:

remove.packages("<package name>")

Substitute “package_name” with the package name you want to uninstall. This command will safely remove the selected package and its dependencies from your Fedora installation.

This will remove the package and its dependencies from your system.

Alternative Method: Install R Packages from cran2copr

Step 1: Enable CRAN2Copr Repository

For Fedora users seeking the latest R packages, CRAN2Copr is an invaluable third-party repository. Begin by adding the repository to your system. Execute the command to install the copr plugin:

sudo dnf install 'dnf-command(copr)

After installing the plugin, enable CRAN2Copr with:

sudo dnf copr enable iucar/cran

Following the repository activation, install the Copr Manager tool, which facilitates package management from this repository:

sudo dnf install R-CoprManager

Step 2: Installing R Packages from CRAN2Copr

With CRAN2Copr enabled, you can install R packages directly. Use the following syntax:

sudo dnf install R-<package name>

For example, to install the ggplot2 package from CRAN2Copr, run:

sudo dnf install R-ggplot2

This command retrieves the specified package and any required dependencies from the CRAN2Copr repository, ensuring you have the latest version compatible with Fedora.

Conclusion

With R and RStudio installed on your Fedora system, you’re equipped to dive into statistical analysis and data visualization projects with powerful tools at your disposal. Leveraging Fedora’s repositories ensures you have a stable setup, while CRAN and cran2copr provide access to a wide range of packages that extend R’s functionality. Regularly update your environment to stay current with the latest developments in R and RStudio, and enjoy the robust capabilities they bring to your data science workflows.