In this post you will know what is R programming language and why this language everyone recommended for analysis purpose. 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, and is currently developed by the R Development Core Team. 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. This programming language was named R, based on the first letter of first name of the two R authors, Robert Gentleman and Ross Ihaka, at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. 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. This language is most suitable for software programmers, statisticians and data miners who are looking forward for developing statistical software using R programming. 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. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. 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. R is available as Free Software and runs on a wide variety of UNIX platforms and similar systems Windows and MacOS. R has its own LaTeX-like documentation format, which is used to supply comprehensive documentation, both on-line in a number of formats and in hard copy. It has the following features:
- R is a well-developed, simple and effective programming language which includes conditionals, loops, user defined recursive functions and input and output facilities.
- 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
R programming widely used for analysis because of the statistical features of R
R has some topical relevance
- It is free, open source software.
- R is available under free software Foundation.
- R has some statistical features
Basic Statistics – Mean, variance, median.
Static graphics – Basic plots, graphic maps.
Probability distributions – Beta, Binomial
Advantages of R Programming:
- R is the most comprehensive statistical analysis package as new technology and ideas often appear first in R.
- R is open-source software. Hence anyone can use and change it.
- R is an open source. We can run R anywhere and at any time, and even sell it under conditions of the license.
- R is good for GNU/Linux and Microsoft Windows. R is cross-platform which runs on many operating systems.
- In R, anyone is welcome to provide bug fixes, code enhancements, and new packages.
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