Introduction to R programming

R is a programming language that is used for statistical computing and graphics. R programming is similar to S programming. It is considered a different style of S language implementation. S language code runs unaltered under R language but there are also some differences.

R programming provides statistical linear and non-linear modeling, time series forecasting, classification, clustering, and many classical statistical tests. It also provides many graphical techniques which are very extensible. R language provides an open-source route for research in statistical methodology. The quality of producing well-designed publication plots including mathematical formulas and symbols where required is the main strength of R language. R language allows us to do modular programming using functions and also allows for branching and looping.

R is available as open-source software under the terms of GNU General Public License. R is the most important tool in the current time which is used by statisticians, researchers, data analysts, and marketers. currently, R programming and Python are the most popular languages for data science.

History of R language

history of R programming
History of R programming

The R language release date, version, and description are shown in the following table: 

VersionRelease DateDescription
0.491997-04-23The First R source was released
0.601997-12-05R gets the GNU license officially
0.65.11999-10-07install.package and update.packages included
1.02000-02-29Release of the first production version
1.42001-12-19The first version for Mac OS is made available.
2.12005-04-18UTF-8 encoding, localization, and internationalization support was added
2.112010-04-22Windows 64-bit support
2.132011-04-14Code to byte conversion function was added
2.142011-10-31Addition of new packages.
2.152012-03-30Long vectors improved serialization speed
3.02013-04-03Larger numeric values support 64-bit systems
3.42017-04-21By default just-in-time compilation (JIT) is enabled
3.52018-04-23  Addition of compact internal representation of integer sequences, serialization format
History of R programming

Features of R programming language

R language has many unique features that make it powerful. Following are some important features of the R language:

  • It is open-source highly extensible and powerful software.
  • It is well developed simple and effective programming language.
  • It is an interpreted language.
  • It provides high range of graphic techniques.
  • It is used for data analysis.
  • It has a concept of user-defined input/output facilities, conditioning, and looping facilities.
  • It provides us many types of calculations on arrays, lists, and vectors.
  • It has an incorporated set of tools that are used for data analysis.
  • It contains a suite of operators.
  • It provides effective storage and data handling facilities.

Why use R programming language?

  • It is open-source and free
  • It has large support of the community
  • It provides the facility to work on different platforms like Linux, Mac, and Windows
  • It provides a wide range of statistical techniques
  • It has a variety of graphs like histograms, pie charts, scatter plots, etc.
  • It is used for data analysis and visualization, machine learning, and data science
  • It has a variety of packages to solve different problems.

Applications of R programming language

Some popular real-time applications of the R language are as follows:

  • Google
  • Facebook
  • Twitter
  • Real climate
  • NDAA
  • FDA
  • Sunlight Foundation
  • ANZ

Advantages of R programming language

  • It is open source language
  • It is platform independent
  • It provides data wrangling features
  • It supports quality plotting and graphing
  • It is continuously growing programming language

Disadvantages of R programming language

  • It has weak origin
  • It is not ideal when dealing with big data
  • It lacks basic security
  • It is slower than other programming languages