Big Data Craze Bolsters R Programming Language Popularity
As industry scrambles to overcome the shortage of developers with Big Data skills, the R statistical programming language is gaining in popularity.
"Thanks to the Big Data hype, computational statistics is gaining attention nowadays," said the November TIOBE Index ranking of the popularity of programming languages. The TIOBE Index includes the statistical languages Julia, LabView, Mathematica, MATLAB, S, SAS, SPSS and Stata, but R is garnering the most attention. In fact, TIOBE said the language is "on its way to the top 10."
"The clear winner of the pack is the open source programming language R," the most recent TIOBE ranking report stated. "This month it jumped to position 12, while being at position 15 last month."
The ascendance of R was noted months earlier by another language popularity ranking, this one by RedMonk. "Advocates of R will be pleased by the language's fourth consecutive gain in the rankings," Redmonk said in its July report that listed R as No. 13, right ahead of Scala. "From 18 in January of 2013 to 13 in this run, the R language continues to rise."
Fast Company Labs last spring noted the dominance of R in the Big Data arena.
"It has been kicking around since 1997 as a free alternative to pricey statistical software, such as MATLAB or SAS," Fast Company said. "But over the past few years, it's become the golden child of data science -- now a household name not only among nerdy statisticians, but also Wall Street traders, biologists and Silicon Valley developers. Companies as diverse as Google, Facebook, Bank of America and The New York Times all use R, as its commercial utility continues to spread."
In fact, Big Data analytics site KDnuggets.com more than a year ago noted R was the most popular programming language among its readers, listed by about 61 percent of respondents to a reader poll. That 61 percent respondent rate compared to about 53 percent in 2012 and 45 percent in 2011.
Silicon Angle this July noted that "R has become a go-to skill for Big Data scientists and developers, with its popularity soaring amid languages and skills."
The site said the language is popular among Big Data developers because it "provides a deep statistical handle for large data sets, conducting statistical analysis and rendering data-driven visualization. R is particularly widely used in the industries of finance, pharmaceuticals, media and marketing, where it can be used to help guide data-driven business decisions."
That utility led R to breaking the top 10 on yet another popularity gauge, this one published as an interactive mobile app in July by IEEE Spectrum. That placed it just one step ahead of MATLAB.
According to its Web site, the R environment includes:
- An effective data handling and storage facility.
- A suite of operators for calculations on arrays, in particular matrices.
- A large, coherent, integrated collection of intermediate tools for data analysis.
- Graphical facilities for data analysis and display either on-screen or on hardcopy.
- A well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.
David Ramel is an editor and writer for Converge360.