Yeah but jupyter leaves bad taste in the mouth. Very frustrating to debug, binary file (no git/diff), much harder to layout than RMarkdown, no variable explorer. Additionally, the kernel idea is kind of lame/not implemented well. And you are getting nowhere in the data world without proper R support.

There wasn't migration to python because there's a total lack of anything to migrate to in python. It has only textbook examples as far as statistical models go. That's around 10% coverage and pretty much 0 coverage for all the abstractions and utility packages in R. Pretty much the same with machine learning (minus neural networks where it is strong). Python took some share from matlab and data processing tools but I don't see it retaining that. IMO it will lose it to Julia for the engineering & science people and to Scala for the data processing people.

The "second best language for everything" doesn't really work too well in the "data science" world.