The Benefits of Using R
Of the many attractive benefits of R programming language, a few are easy to recognize. It’s actively maintained, it has good connectivity to various types of data and other systems, and it’s versatile enough to solve problems in many domains. Possibly best of all, it’s available for free.
R is free, open-source code
R is available under an open-source license, which means that anyone can download and modify the code. This freedom is often referred to as “free as in speech.” R is also available free of charge — a second kind of freedom, sometimes referred to as “free as in beer.” In practical terms, this means that you can download and use R free of charge.
Another benefit, albeit slightly more indirect, is that anybody can access the source code, modify it, and improve it. As a result, many excellent programmers have contributed improvements and fixes to the R code. For this reason, R is very stable and reliable.
Any freedom also has associated obligations. In the case of R, these obligations are described in the conditions of the license under which it is released: GNU General Public License (GPL), Version 2.
It’s important to stress that the GPL does not pertain to your usage of R. There are no obligations for using the software — the obligations just apply to redistribution. In short, if you change or redistribute the R source code, you have to make those changes available for anybody else to use.
R runs anywhere
The R Development Core Team has put a lot of effort into making R available for different types of hardware and software. This means that R is available for Windows, Unix systems (such as Linux), and the Mac.
R supports extensions
R performs a wide variety of functions, such as data manipulation, statistical modeling, and graphics. One really big advantage of R, however, is its extensibility. Developers can easily write their own software and distribute it in the form of add-on packages.
Because of the relative ease of creating these packages, literally thousands of them exist. In fact, many new statistical methods are published with an R package attached.
R provides an engaged community
Many people who use R eventually start helping new users and advocating the use of R in their workplaces and professional circles. They also become active on the R mailing lists or question-and-answer (Q&A) websites such as Stack Overflow, a programming Q&A website and CrossValidated, a statistics Q&A website. In addition to these mailing lists and Q&A websites, R users participate in social networks such as Twitter and regional R conferences.
R connects with other languages
As more and more people moved to R for their analyses, they started trying to combine R with their previous workflows, which led to a whole set of packages for linking R to file systems, databases, and other applications. Many of these packages have since been incorporated into the base installation of R.
Several add-on packages exist to connect R to database systems, such as the RODBC package, to read from databases using the Open Database Connectivity protocol (ODBC) and the ROracle package, to read Oracle data bases.
Initially, most of R was based on Fortran and C. Code from these two languages easily could be called from within R. As the community grew, C++, Java, Python, and other popular programming languages got more and more connected with R.
Because many statisticians also worked with commercial programs, the R Development Core Team wrote tools to read data from those programs, including SAS Institute’s SAS and IBM’s SPSS.
Many of the big commercial packages have add-ons to connect with R. Notably, SPSS has incorporated a link to R for its users, and SAS has numerous protocols that show you how to move data and graphics between the two packages.