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Step by Step Guide for Installation of R language for Data Science & Machine/Deep Learning

Introduction to R

R is a programming language and free software for graphics and statistical computing supported by R Foundation. Data Miners and Statisticians widely use R language for Data Analysis and for developing Statistical Software. As of July 2019, R is ranked as the 20th most popular programming language by TIOBE index. Also, data mining surveys, polls and studies have shown substantial increase in popularity of R. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, but now it is developed by the R Development Core Team.


Implementation of a wide variety of graphical and statistical techniques including time-series analysis, classification & clustering is made possible and easy with the help of wide variety of R libraries. With the help of vast majority of functions and extensions, R has been made easily extensible for its users. In terms of packages, R community is noted for its active contributions. C and C++ is used by R to perform computationally intensive tasks. As compared to other statistical computing languages R has much stronger Object-Oriented facilities for programming.


With the help of various additional packages, R becomes quite good as static, dynamic and interactive graphics. It can also produce publication quality graphics. Like many other programming languages such as MATLAB (Matrix Laboratory), R also supports variety of matrix operations.


The major data structures supported in R are:

1) Vectors.

2) Matrices.

3) Arrays.

4) Data Frames (similar to Tables in Databases).

5) Lists.


Scalars cannot be represented in R as a scalar data type, rather it is represented as a vector with length one.


Although R has a command line interface, there are several Graphical User Interfaces (GUI’s). The most specialized Integrated Development Environment (IDE) for R language is R studio. A similar integrated development environment is R Tools for Visual Studio. Some generic IDE’s such as Eclipse also provide facility to work with various R packages.

As RStudio Incorporation has no formal connection to the R Foundation (an organization which is responsible for overseeing development of R environment for statistical computing) so we have to separately install R language and RStudio.


First, we will install R language in this tutorial, and then we will install R studio in the tutorial available at this link.


The following is the step by step guide to install R language.


Step by Step Installation Guide for R language


Step No. 1:

Go to R language website. This link redirects you to the official site of R language.



Step No. 2:

Click on the link highlighted in the image given below:



Step No. 3:

Wait for a few minutes because depending upon the speed of your internet it will take a bit to download.



Step No. 4:

After the completion of download simply double-click the following icon.




Step No. 5:

Select the language in which you want to proceed.



Step No. 6:

After selecting the language click “ Ok ”.



Step No. 7:

Carefully read all the instructions in License Agreement.



Step No. 8:

Click “ Next ” to proceed with installation.



Step No. 9:

Click “ Browse ” button to select the directory in which you want to install the R language.



Step No. 10:

Click “ Next ” to proceed with installation.



Step No. 11:

Select the components you want to install by selecting the check boxes. It is recommended to install all the components.



Step No. 12:

Click “ Next ” to proceed installation.



Step No. 13:

Select the startup options the from the given options. Simply go for the recommended option if you are unaware of the details.



Step No. 14:

Click “ Next ” to proceed with installation.



Step No. 15:

By using the “ Browse ” Button select the directory or folder in which you want to create the shortcuts for the program.



Step No. 16:

Click “ Next ” to proceed with installation.





Step No. 17:

Select the additional options such as additional shortcuts and registry entries.



Step No. 18:

Click “ Next ” to proceed with installation.



Step No. 19:

Wait for installation to complete.



Step No. 20:

Congrats, you have successfully completed the installation of R language. Click the link for step by step guide to install RStudio; an integrated development environment (IDE) for R language so that you can run your programs on R language.

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