R is widely used by data scientists and researchers to retrieve, analyze and visualize data. The R programming language is mostly used in institutions such as Manufacturing, e-Commerce, healthcare, and financial institutions such as Banks to perform risk analysis such as credit risk analysis.
Here at LinuxAPT, we shall look into how to install the R programming language on Fedora 34/35.
Notable companies that use R include:
- Google – For economic forecasting and ensuring advertising effectiveness.
- Facebook – For behavioral analysis in relation to status updates, reactions, profile pictures, etc.
- Twitter – Semantic clustering and data visualization.
- Uber – Statical modeling and analysis.
- ANZ Banking group – Risk analysis.
Steps to install the R programming language on Fedora
1. Perform System Update
To begin, launch your terminal and update the system packages:
$ sudo dnf update
2. Install dependencies on the system
Now, run the command below to install dependencies:
$ sudo dnf install dnf-utils dnf-plugin-config-manager dnf-plugins-core
3. Install R programming language on your system
Installing R is quite a straightforward task since R is already available in Fedora repositories. To install R, simply run the command:
$ sudo dnf install R
During the installation, hit Y to continue installing R alongside all its dependencies and some additional packages.
Once installed confirm the version of R:
$ R --version
The installation also installs other additional components which include:
- Minimal R components: R-core.
- File for the development of R packages without Java: R-core-devel.
- Java development package for R components: R-java-devel.
- Java Runtime Environment provided by Fedora: R-java.
- Headers from the standalone Math library: libRmath-devel.
- Standalone math Library for R project: libRmath.
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This article covers how you can install the R programming language on Fedora 35. In fact, R is a programming language and programming software that is utilized for analyzing statistics, data modeling, graphical portrayal, and detailing. It involves the algorithms from machine learning, linear regression, time series, etc. R is the best software tool for programming developers, analysts, and data miners who are anticipating and trying to present the data in convincing manners.