Data Science Tutorial for You

Data Science Using R Programming

Why R Programming for Data Science :

R is free and open source software for statistical computations and graphics. It is free to all. R's compiler is freely available online. So The programmer can compile, interpret and execute R code online.

Wikipedia explain that, R is a programming language and free software for statistical computing and graphics. It is used for data analysis, statistical analysis and data mining.

It is designed in 1993 by Ross Ihaka and Robert Gentleman.

It is named R by the first names of its designers Ross and Robert.

The source code of R is published under GNU General Public Licence Versions 2.0.

Move towards the next step to understand various features of R programming language in data science.

Features of R Programming:

Due to extensive features r is most popular programming language from last few years. It's popularity is ranked among top five programming languages. Most of the data scientist prefer this language for statistical analysis and graphics.

R is open source programming language freely available for everyone.

It is used for statistical computations.

Strong graphical capabilities help in data visualization.

It is extremely compatible and easily run on every platform.

Compiler is not required to run R code because R program are not compiled but it is interpreted.

R is object oriented and also support for the distributed computations.

R studio is available for programmers to interpret R code online. Even though you have not installed R studio software.

R has active community who contribute continuously on evolving of R's environment.

Offering wide range of packages and libraries apeal to functionality of different fields and dealing with data.

How to Install R software:

RStudio IDE (Integrated Development Environment) is an integrated set of tools. It comes in the form of console, syntax highlighting editor that helps to direct the code execution and variety of tools that helps for plotting, viewing, debugging.