R is a statistical computing and graphics programming language supported by the R Core Team and the R Foundation for Statistical Computing. R, developed by statisticians Ross Ihaka and Robert Gentleman, is used by data miners and statisticians for data analysis and statistical software development. Users have written packages to extend the capabilities of the R language.

R is one of the most often used programming languages in data mining, according to user surveys and examinations of scholarly literature databases. R is ranked 11th in the TIOBE index, a measure of programming language popularity, as of March 2022. The official R software environment is an open-source free software environment included in the GNU package that is distributed under the GNU General Public License. It is mostly written in C, Fortran, and R. (partially self-hosting). For several operating systems, precompiled executables are supplied. R includes a command-line interface. Third-party graphical user interfaces, such as RStudio, an integrated programming environment, and Jupyter, a notebook interface, are also available. R is a computer language and software environment that can be used for statistical analysis, visual representation, and reporting.

R was founded at the University of Auckland in New Zealand by Ross Ihaka and Robert Gentleman, and it is now being developed by the R Development Core Team.

The mean, mode, and median are the most commonly used words in basic statistics. "Measures of Central Tendency" is the name given to all of these. As a result, we can simply measure central tendency using the R programming language.

R has a lot of tools for making and developing cool static graphics. Many plot kinds are supported by R, including graphic maps, mosaic plots, biplots, and the list goes on.

Probability distributions are important in statistics, and we can easily handle many different types of probability distributions with R, including the Binomial Distribution, Normal Distribution, Chi-squared Distribution, and many others.

It offers a comprehensive, well-coordinated, and well-integrated set of tools for data analysis.

One of the most appealing aspects of R is the abundance of libraries available. CRAN (Comprehensive R Archive Network) is a repository for R that contains over 10,000 packages.

Distributed computing is a model in which components of a software system are shared among numerous computers in order to increase efficiency and performance. In November 2015, two new R packages for distributed programming, ddR and multidplyr, were released.

There are many advantages of using R language, both for developers and for users. Here are a few of the most important reasons:

R is powerful and versatile.

R has a lot of features that make it perfect for interactive data analysis and machine learning. It's also easy to use and easy to learn.

R is fast and efficient.

R is one of the fastest languages around, and it can quickly process large amounts of data.

R is very versatile, and it can be used to create a wide range of applications.

R is an open source language, which means that it is free to use and share. This makes it a great choice for development and research.

The Disadvantages of R Language are:-

R is not as versatile as other languages when it comes to data analysis and data management.

Some packages in the R programming language have a less-than-ideal standard.

R instructions, on the other hand, put little strain on memory management. As a result, the R programming language may use up all of the available RAM.

R's applications include:

For data science, we utilise R. It provides us with a wide range of statistics-related libraries. It also serves as a platform for statistical computation and design.

Many quantitative analysts utilise R as their programming language. As a result, it aids in data import and cleansing.

R is the most widely used programming language. It's used by a lot of data analysts and research programmers. As a result, it is employed as a basic financial tool.

R is now used by tech giants like as Google, Facebook, Bing, Twitter, Accenture, Wipro, and many others.

We used to write all of our code in print(), but now we don't know how to address them in order to execute additional operations. This difficulty can be handled by employing variables, which are the names given to reserved memory addresses that can store any type of data in any programming language.

** The assignment can be written in three different ways in R:**

= (Simple Assignment)

<- (Leftward Assignment)

-> (Rightward Assignment)

Comments are a technique to improve the readability of your code. They are solely intended for the user, thus the interpreter ignores them. In R, we can only use single-line comments, however we can utilise multiline comments with a simple method given below. # at the beginning of the sentence can be used to write single-line comments.