R is an open-source programming language designed for statistical analysis. In the late 1970s at Bell Laboratories, R was developed from the commercial S language. R is now licensed under freely available under the GNU General Public License by researchers at the University of Auckland, New Zealand.
R is very popular in the academic community, even I learned and used R for my PhD in finance. R has wonderful graphing functionality. The demand for R has grown to a new level in recent years. Not just in academics, large companies have started to use R for big data analysis.
The main advantage of R is also extremely customizable. There are thousands of extensions for R, up from about 16081 by the time I am writing this post now in August 2019. Extension packages incorporate everything from time series analysis, to genomic science, to text mining. You can find these extensions in CRAN, a free repository maintained by R.
R also boasts impressive graphics, free and polished integrated development environments (IDEs), programmatic access to and from many general‐purpose languages, interfaces with popular proprietary analytics solutions including MATLAB and SAS, and even commercial support from Revolution Analytics.