The new PYPL Popularity of Programming Languages (June 2018) index ranks Python at #1 and R at #7.
Like the similar TIOBE language index, the PYPL index uses Google search activity to rank language popularity. PYPL, however, fcouses on people searching for tutorials in the respective languages as a proxy for popularity. By that measure, Python has always been more popular than R (as you'd expect from a more general-purpose language), but both have been growing at similar rates. The chart below includes the three data-oriented languages tracked by the index (and note the vertical scale is logarithmic).
Another language ranking was also released recently: the annual KDnuggets Analytics, Data Science and Machine Learning Poll. These rankings, however, are derived not from search trends but by self-selected poll respondents, which perhaps explains the presence of Rapidminer at the #2 spot.
I dislike these search based metrics for popularity. When I use python, I end up doing a lot more searches, because its a much more fragmented environment . . what version of python, what OS, . . . matplotlib, sns . . . I typically have to try a few tries to get something to work. In contrast with R, you can get a base R solution from a newsgroup that is 10 years old and it works. I think blindly looking at total searches or posts on stackoverflow is not the best metric for measuring the popularity of a language.
Posted by: Rajcs4 | June 20, 2018 at 17:36
^ I second that opinion. R just works. With py.x*, you'll have to make it work.
Posted by: Charles Choe | June 20, 2018 at 20:30
Interested in the academic perspective on systems for (visual) data analysis? Check out the 2018 #CommercialVASystems state-of-the-art report at http://commercialtools.dbvis.de. @HarvardVCG @dbvis
Posted by: Michael Behrisch | June 21, 2018 at 05:37