R Programming Language 2025

The R Core Team and the R Foundation for Statistical Computation promote R, a programming language for statistical computing and graphics.

R is a language and environment for statistical computation and graphics that was created by the same people who created S at Bell Laboratories. It offers a wide range of graphical and statistical tools and is quite expandable. R offers an Open Source path to involvement in that activity and is frequently the tool of choice for statistical methods research. Under the rules of the GNU General Public License issued by the Free Software Foundation, R is accessible as Free Software in source code format. It may be built and run on a number of UNIX systems, as well as Windows and MacOS.

The difference between R and Python is that R is a statistical programming language. This indicates that Python is more flexible and useful for a variety of activities, including web development, data manipulation, and machine learning.

Due to its unique syntax from other programming languages like Python and its large command set, R is regarded as one of the most challenging computer languages to master. Most people who have no prior coding knowledge learn R in between four and six weeks.

To install R on Windows OS: 

• Please visit the CRAN website.
• Click “R for Windows Download.”
• The R executable (.exe) file can be downloaded by clicking the link labeled “setup R for the first time.”
• Run the R executable file to launch the installation process and give the program permission to modify your device.
• The installation language should be chosen.

The ideal way to learn R may be determined by conducting a self-evaluation of your abilities. Enroll in a course for beginners if you have limited expertise with coding or data science. Enroll in a higher-level course if you’ve done some programming and have a basic understanding of computer science. Although they are flexible, online courses can nevertheless be sufficiently structured for you to retain your academic discipline. In general, starting courses last four to six weeks, whereas experienced students just need two weeks. In order to learn R, use supplementary materials. Join a group of people who are studying R together, and you’ll get help from other people. Having completed a project will give you an edge throughout the employment process and will test your abilities. To demonstrate your abilities to companies, save it for your professional portfolio.

R programming is a potent language used for general-purpose programming, data visualization, and statistical research. To do statistical analyses, data visualization, machine learning, data manipulation, and reproducible research, it has built-in functions and packages. Additionally, it offers a complete collection of tools and frameworks for transforming and manipulating data. Due to its extensive ecosystem of packages, versatility, and vibrant community, R is a useful programming language for data analysis, statistical modeling, and visualization. It is the best option for anybody working with data because it supports web scraping, package creation, and data science procedures.

R is a functional programming language at its core. But there is some support for object-oriented programming in the R system (OOP).

Although it offers several advantages over other programming languages like Python, its popularity among users has been declining.

The majority of people believe that learning the programming language R is pretty challenging. The overwhelming quantity of commands that R users must master is one element that makes this challenge.

A good environment for statistical computation and design is provided by R, which offers a large range of statistics-related libraries. A lot of quantitative analysts also utilize the R programming language as a programming tool since it is effective for importing and cleaning data.

A statistical computing and graphics system is called R. The R language itself—what most people understand when they refer to R—and a run-time environment are the two components that make up this system. Because R is an interpreted language, users access its features via a command-line interpreter. R is not a general-purpose programming language, in contrast to Python and Java. It is instead regarded as a domain-specific language (DSL), which means that its uses and features are tailored to a certain field or domain. For R, that entails statistical computation and analysis. R is therefore often employed for a wide range of data science activities. Users may examine data, model it as needed, and then produce visuals using R’s extensive collection of functions for data visualization. There are several add-ons or modules that help with this in addition to the language’s built-in graphical features.

R is a command-line interpreter-based interpreted language that users may use to access.

The R programming language was created in 1993 by two statisticians, Robert Gentleman, and Ross Ihaka, at the University of Auckland.

• Accenture
• Amazon
• Deloitte Consulting
• Cognizant
• Google
• Novartis
• Infosys
• Meta Platforms
• Snapdeal
• HCL Technologies
• Novartis

Developed by the statisticians Ross Ihaka and Robert Gentleman.

R is utilized by data miners, bioinformaticians, and statisticians for data analysis and software development.

R is ideally suited for machine learning tasks such as regression and classification. It also includes a variety of features and tools for developing artificial neural networks. Data manipulation is possible using R. R provides a variety of programs that assist data analysts in transforming unstructured, jumbled data into an organized manner.

Click File – New File – R Script to develop a new R script in RStudio. Shortcut On a Mac, the command–shift–N shortcut may also generate a new R script.