R is an interpreted programming language (so it is also called a scripting language), which means that your code will not be compiled before running it. R is a high-level language in which you do not have access to the inner workings of the computer where you are running your code; everything is leaning toward helping you analyze data, which is beneficial.

R provides a mixture of programming paradigms. On its internals/foundations, it is a mandatory type of language where you can write a script that performs calculations (one at a time) one after another. Nevertheless, it also supports object-oriented features where data and functions are encapsulated inside classes, and there is also functional programming in which the functions are first-class objects. You treat them like any other variable. This mixture of programming paradigms tells that R code can bear a lot of resemblance to several different languages. The curly braces mean - you can code imperative code, which will look like C.

Uses of R

  • Weather Service uses R to predict severe flooding.
  • Social networking companies are using R to monitor their user experience.
  • Newspapers companies are using R to create infographics and interactive data journalism applications.

The major companies adopt r because their data scientists prefer to use it.

Features of R

As described earlier, the R programming language is versatile and can be used for a software development environment for statistical analysis or graphics representation and reporting purposes.

The below mentioned are the significant features of the R language:

  • R is a simple and effective programming language that has been well-developed, as well as R is data analysis software.
  • R is a well - designed, easy, and effective language that has the concepts of conditionals, looping, user-defined recursive procedures, and various I/O facilities.
  • R has a large, consistent, and incorporated set of tools used for data analysis.
  • R contains a suite of operators for different types of calculations on arrays, lists, and vectors.
  • R provides highly extensible graphical techniques.
  • R graphical techniques for data analysis output either directly display to the computer, or can be print on paper.
  • R has an effective data handling and storage facility.
  • R is a vibrant online community.
  • R is free, open-source, robust, and highly extensible.

Evolution of R

Most of the time, you should be clear from the context that R is being referred to. R (which is the language) was developed in the early 1990s by Ross Ihaka and Robert Gentleman when they both work at the Department of Statistics at the University of Auckland, New Zealand. R made its first appearance in the year 1993. This programming language is based upon the S language, which was developed in the 1970s at Bell Laboratories, mainly by John Chambers. R (which is the software) is a GNU based project that reflects its status as important free along with open-source software. Both the language, along with the software, is now developed by a group of 20 people approx. Known as R Core Team.

R is the most widely used statistical programming language because of various reasons.

  • R is a free and open-source software project.
  • R allows integrating with other languages, like C/C++, Java, Python, etc.
  • R has an online vibrant, growing community of users.
  • The CRAN (The Comprehensive R Archive Network) package repository features have more than 8270 available packages.
  • R is platform-independent so that you can use it on any operating system.

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