Overview of the R Programming language for data science
R Programming language is programming language and software environment used for statistical computing and graphics. R Programming language is open source, interpreted programming language used for variety of data analysis and data research. R programming language which is based on 'S' programming language and it was created by Ross Ihaka and Robert Gentleman, at the University of Auckland in year 1993. This programming language gets its name from the name of its creator. This programming language is currently being developed by R Core Team.
This software is distributed as R distribution, packages, extensions, documents and binaries through Comprehensive R Archive Network (CRAN). Software is open source and its source can be downloaded compiled.
R Software is available for various operation systems including Linux, Mac OS Classic, Mac OS X and Microsoft Windows. In Ubuntu you can use the apt tool for installing it and its very easy to install in Ubuntu.
Features of R
- R Programming language is well designed, interpreted programming
language with a support for conditions, looping, user defined functions and
various pre-defined data types which can be used for statistical computing.
- R Programming language is very efficient in data handling and storage.
- It supports arrays, vectors, lists and matrices.
- It provides large set of tools/functions for data analysis.
- It provides features of generating various types data visualization
charts and graphs.
- R Programming language provides large set of packages.
- It comes with cutting edge technologies.
- R programming language comes with excellent graphics capabilities.
- R is open source programming language.
- R Programming language comes with over 9000 packages with huge set of functionality.
R programming language is getting very popular among data scientists and for statistical computing. R Programming language is most used programming language for statistical programming.
R is most preferred programming language among data scientists and R programmers are high in demand in job market.
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