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If you’re new to Ubuntu, installing R may seem overwhelming. However, with the right guidance, it can be a simple process. R is a widely used language for statistical analysis and data visualization, making it a crucial tool for both data professionals and enthusiasts. Regardless of your level of expertise, this guide offers a straightforward approach to installing R on your Ubuntu system.
R is a programming language and free software environment tailored for statistical computing and graphics. Renowned for its rich ecosystem and versatile applications, R offers the following common features:
In essence, R serves as a comprehensive toolkit for data analysis, visualization, and software development. In the next section, let’s take a look at how to set it up on Ubuntu.
Installing R on Ubuntu is a straightforward process, especially with the help of the command line. Here’s a step-by-step guide:
Before starting, it’s a good idea to update your system packages to their latest versions.
sudo apt update sudo apt upgrade
The output will be a list of packages will be upgraded. After confirmation, ubuntu will upgrade the packages.
To ensure you get the latest version of R, add the CRAN repository to your sources list.
sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9 sudo add-apt-repository "deb https://cloud.r-project.org/bin/linux/ubuntu $(lsb_release -cs)-cran40/"
Press Enter to continue. Then, ubuntu will add the CRAN repository to its list of repositories. Here’s a sample output below:
With the repository added, you can install R.
sudo apt update sudo apt install r-base
A list of packages that will be installed. Ubuntu will proceed to install R once you give confirmation.
To check if R was installed successfully, enter the R environment.
You will see an introduction message, followed by the R prompt. Exit the R environment by typing q() and pressing Enter.
For many, RStudio provides a more user-friendly interface for working with R. To install:
sudo apt install gdebi-core wget https://download1.rstudio.org/desktop/bionic/amd64/rstudio-x.x.x-amd64.deb sudo gdebi rstudio-x.x.x-amd64.deb
Ubuntu will install the gdebi-core package first, then download and install RStudio. The version number x.x.x should be replaced with the latest version number from the RStudio website.
CRAN, which stands for the Comprehensive R Archive Network, is a network of servers around the world that store identical, up-to-date versions of code and documentation for R, as well as many extensions and related software.
Here’s a step-by-step guide on how to install an R package from CRAN:
First, you need to start R. You can do this by typing R in your terminal (for Linux/Unix/Mac) or by opening the R GUI if you’re on Windows.
Once inside the R environment, use the install.packages function to install your desired package. For example, to install a package named “package_name1”, you’d use:
Once you run this command, you’ll likely see a series of messages indicating the download and installation progress. This includes the download location, the unpacking of the package, and any additional dependencies that might also be installed.
After installation, you can use the library function to load the package and start using its functions. Using our earlier example:
By default, install.packages might ask you to choose a CRAN mirror. This is essentially a server location from where the package will be downloaded. You can manually specify a mirror by using the repos argument:
Choosing the cloud based CRAN mirror as shown above usually provides good speed and reliability.
To ensure the package has been successfully installed, you can list all installed packages and check if your package is in the list:
That’s it, you have successfully installed R on Ubuntu. This powerful tool will enable you to perform statistical analysis and visualize data. With its vast libraries and packages, you can explore data in depth, making it a valuable asset whether you are conducting academic research, professional analysis, or personal projects. Kudos and happy coding!
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