R Language

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.

What are the features of R Language?

Basic Statistics:

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.

Static graphics:

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:

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.

Data analysis:

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

What are the Programming Features of R ?

R Packages:

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 :

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.

What are Advantages of R Language?

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

What are the Disadvantages of R Language?

The Disadvantages of R Language are:-

What are the Applications of R Language?

R's applications include:

What are Variables?

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:

What are Comments?

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.