R Language Tutorial
This tutorial introduces a set of the very fundamental concepts that you need to know to be a confident user of R.
R is a programming language for data analysis and graphics as it provides facility for reading, manipulating and computing data, conducting statistical analysis and displaying the results. It is a command line driven program, which means the commands evaluate and execute in the console. R is an open source programming language, it is continually being reviewed and improved. It is the best language for representing data statistic. In addition to providing statistical operations, it is also a general-purpose programming language. This is a platform-independent language available for the Windows, Mac, and Linux operating systems.
This is one of the best language for data science in 2018. The top tier companies using R are Facebook, Google, Twitter, Microsoft.
R Language History
R programming language was created in the early 1990s by Ross Ihaka and Robert Gentleman of the Statistics Department of the University of Auckland, and it is currently maintained by the R core-development team.
It is an implementation of the S language, a language for manipulating objects, developed at AT&T Bell Laboratories in 1988 and used to manipulate data and perform statistical analysis of data.
R Language Features
- R is a powerful tool for performing any statistical data analysis.
- By using this, we can perform multiple calculations with vectors.
- It is both procedural and object-oriented language. The procedural programming provides records, modules and procedural calls, while the object-oriented programming provides classes, objects and generic functions.
- It provides database input, data handling, storage facilities.
- This language supports matrix, vector arithmetic.
- It is an interpreted language, which means it doesn't need to compile the code before execution.
- The biggest strength of R is that it has inbuilt functions to create more sophisticated plots to represent complex data, such as contour lines, density curves, and many other things.
- R can carry out important analyses that are difficult or impossible in many other packages.