R programming

R Programming
Pooja Sharma
ME CSE Regular
162413
NITTTR Chandigarh

Contents
 History of R
 Introduction to R Programming
 Why learn R
 Installation steps
 R Programming IDE
 R Packages
 What R does
 What R does not
 Features
 Basic Concepts of R
 Advantages & Disadvantages
 Applications
 Future of R Programming

History of R
 Origin in the Bell Labs in the 1970’s.
 R has developed from the S language.
 1990’s : R developed concurrently with S.
 1993: R made public
 Stable released on October 31st,2014 by R
Development Core Team under GNU GPL.

INTRODUCTION TO R
PROGRAMMING
 R is a programming language and software
environment for statistical analysis, graphics
representation and reporting.
 R was created by Ross Ihaka and Robert
Gentleman at the University of Auckland, New
Zealand.
 R is freely available under the GNU General
Public License, and pre-compiled binary
versions are provided for various operating
systems like Linux, Windows and Mac.

Contd..
 R is free software distributed under a GNU-style
copy left, and an official part of the GNU project
called GNU S.
 The core of R is an interpreted computer
language which allows branching and looping as
well as modular programming using functions. R
allows integration with the procedures written in
the C, C++, .Net, Python or FORTRAN languages
for efficiency.

Getting Started with R
 To install R GUI go to http://www.r-
project.org/
 To install R Studio go to
http://www.rstudio.com/

Select CRAN Mirrors
(Click on India CRAN Mirror)

Select OS Version which you want
to download and install

After downloading run the
setup

R PROGRAMMING IDE
 There are two Integrated Development
Environments for R Programming:-
i) R GUI (Graphical User Interface)
ii) R Studio

R Packages
 A package is a collection of functions with
comprehensive documents.
 A package includes: R functions, Data Example,
Help Files, Namespace and Description.
 The default installation is kept as minimum.
 The function of R could be extent by loading R
packages.

Installing Packages
(First select the HTTPS CRAN Mirror)

Installing Packages
(Then select package which you
want to install)

What R does
o data handling and storage: numeric, textual
o matrix algebra
o hash tables
o high-level data analytic and statistical functions
o classes (“Object Oriented”)
o graphics
o programming language: loops, branching, subroutines

What R does not
o is not a database, but connects to DBMSs
o has no graphical user interfaces, but connects to
Java
o language interpreter can be very slow, but allows
to call own C/C++ code
o no spreadsheet view of data, but connects to
Excel/MsOffice
o no professional /commercial support

Features of R Programming
 R is a well-developed, simple and effective
programming language .
 R has an effective data handling and storage
facility.
 R provides a suite of operators for calculations on
arrays, lists, vectors and matrices.
 R provides a large, coherent and integrated collection
of tools for data analysis.
 R provides graphical facilities for data analysis and
display either directly at the computer or printing at
the papers.

Advantages of R
 R is free and open source software.
 R has no license restrictions.
 R has over 4800 packages available from multiple
repositories specializing in topics like econometrics,
data mining, spatial analysis, and bio-informatics.
 R is cross-platform.
 R plays well with many other tools, importing data, for
example, from CSV les, SAS, and SPSS, or directly
from Microsoft Excel, Microsoft Access, Oracle,
MySQL, and SQLite.
 It can also produce graphics output in PDF, JPG,
PNG, and SVG formats, and table output for LATEX
and HTML.

Disadvantages of R
i) Average memory performance:
 Poor management of large data sets
 Complicated structure of packages in R
ii) Average computing performance
 No default parallel execution
iii) Difficult data visualization and management
 Difficult to inspect data sets
iv) Relatively difficult to learn
 Very complex data structures

How R Programming Is Applied To
Real World
R Programming has turned into the most prevalent language
for data science and a fundamental tool for Finance and
analytics-driven organizations, for example, Google,
Facebook, and LinkedIn.

Future of R Programming
 R Programming is good and powerful because R
is one of the most demanded scripting language
developed by and for statisticians.
 With its unparalleled advantages, we predict the
present and future of Business Analysts with R.

R programming

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