Using R for data science

Being arguably the oldest and consequently the most mature language for statistical operations, R has been used by statisticians all over the world for over 20 years. The precursor to R was the S programming language, written by John Chambers in 1976 in Bell Labs. R, named after the initials of its developers, Ross Ihaka and Robert Gentleman, was implemented as an open source equivalent to S while they were at the University of Auckland.

The language has gained immensely in popularity since the early 2000s, averaging between 20% to 30% growth on a year-on-year basis:

In 2018, there were more than 12,000 R packages, up from about 7,500 just 3 years before, in 2015.

A few key features of R makes it not only very easy to learn, but also very versatile due to the number of available packages.