R has become a very popular programming language and development environment used for statistical computation and graphics. It started off as a GNU project that was similar to the language S but had many other features. It can be used to compute a wide variety of statistical tests that include the classic tests like Student’s Test and Correlation test. It has a powerful user base and strong community support. It is freely available to all.
The R programming language consists of a huge variety of statistical and graphical methods. It contains regression analysis algorithms, machine learning, time series and many more. Most of its packages or libraries are written in R.
To increase its efficiency, the procedures written in C, C++, FORTRAN, Python, and .NET can be integrated. The language has become popular among academic institutions as well as large corporations such as Uber, Google, and Facebook.
The core of the language is actually an interpreted programming language that supports modular programming, looping, and branching. It is heavily used in data analysis that is performed through the following steps:
The R language programming environment is based on a command line interface.
The R programming language was developed at the University of Auckland, by Ross Ihaka and Robert Gentleman. It was named R based on the initials of the founders Ross and Robert. It is currently maintained and developed by the R Development Core Team. The project was started in 1992, and the initial version was launched in 1995. In the year 2000, the stable beta version 1.0.0 was launched for the everyone.
R is an implementation of S, another statistical programming language that was developed in Bell Labs, dating back to the 1970s. After the initial release of R, many people decided to join in and work on it in order to improve its features.
By 1995, the language had become open sourced and anyone could modify and enhance it. This was because Martin Mächler had convinced the creators of the language to use the GNU license to make R free for all.
Around the middle of 1997, a small team called the R Core Team was developed to modify the source code of R; which is operational until today.
The different features of the R programming language are as follows:
The different applications of R are as follows:
R is currently the most popular analytic tool used by programmers around the world. It has around 2 million users across the globe. It has more number of blogs, discussion forums, and email lists than any other analytics tool including SAS. At present, all major corporations such as Google, Apple, Accenture, TechCrunch, Mozilla, Bing, The New York Times and Thomas Cook are adopting R as the primary language for data analytics.
Based on a study conducted recently, the R programming language is used mostly in the field of academics. This industry is followed by healthcare, government, consulting, insurance and energy. The language is very important if anyone wants to build a career in data science or data analytics.
The different job roles for candidates having R programming knowledge are:
The R programming language has a lot of promise and is expected to dominate the analytics and statistical modelling fields in the future. Having features like clustering, data reduction and correlation are easily performed through R. It does not have a very steep learning curve, so the programming community is expanding so quickly. Implementing artificial intelligence operations is efficient though R.