Understanding 'R' Programming Language.
                     Understanding 'R' 
Programming 
Language
Introduction to 
R
R is a language and environment for 
statistical computing and graphics. It 
is a GNU project which is similar to 
the S language and environment 
which was developed at Bell 
Laboratories (formerly AT&T, now 
Lucent Technologies) by John 
Chambers and colleagues. 
Source: www.r-project.org 2
History of R
 Basically, R programing language is 
an implementation of the S 
programming Language. 
Also combines with lexical scoping 
semantics inspired by Scheme. 
Although, R was named partly after 
the first names of two R 
programming language authors. 
Moreover, the project conceives in 
1992, with an initial version released 
in 1995 and a stable beta version in 
2000.
Source: www.guru99.com 3
Statistical 
Technique
R provides a wide variety of 
statistical (linear and nonlinear 
modelling, classical statistical tests, 
time-series analysis, classification, 
clustering, …) and graphical 
techniques, and is highly extensible. 
Source: www.r-project.org 4
Well-designed 
publication-quality
One of R’s strengths is the ease with 
which well-designed publication-
quality plots can be produced, 
including mathematical symbols and 
formulae where needed. Great care 
has been taken over the defaults for 
the minor design choices in graphics, 
but the user retains full control.
Source: www.r-project.org 5
Free Software
R is available as Free Software under 
the terms of the Free Software 
Foundation’s GNU General Public 
License in source code form. It 
compiles and runs on a wide variety 
of UNIX platforms and similar 
systems (including FreeBSD and 
Linux), Windows and MacOS.
Source: www.r-project.org 6
Integrated suite of 
software
R is an integrated suite of software 
facilities for data manipulation, 
calculation and graphical display. It 
includes
1. an effective data handling and storage 
facility,
2. a suite of operators for calculations on 
arrays, in particular matrices,
3. a large, coherent, integrated collection of 
intermediate tools for data analysis,
4. graphical facilities for data analysis and 
display either on-screen or on hardcopy, 
and
Source: www.r-project.org 7
What is R used 
for?
1. Statistical inference
2. Data analysis
3. Machine learning algorithm
Source: www.guru99.com 8
R package
The primary uses of R is and will 
always be, statistic, visualization, 
and machine learning. The R package 
got the most questions in Stack 
Overflow. In the top 10, most of them 
are related to the workflow of a data 
scientist: data preparation and 
communicate the results.
Source: www.guru99.com 9
Install R 
Programming 
Language & R Studio
We have to follow three basic steps 
in the same order to run R 
programming language and R Studio 
on your system.
• R Installation
• Installation of R Studio
• Install R Packages.
Source: www.guru99.com 10
R For Business
R is best for business because it’s an 
open source. Also, it's great for 
visualization. Moreover, the R 
programming language has far more 
capabilities as compared to earlier 
tools. Also, companies are using R 
programming as their platform and 
recruit trained users of R.
Source: towardsdatascience.com 11