[EmlynC]

While it doesn't have an inherent advantage, it has the mindshare and momentum of a community that has these tools now.

R could be just as capable as Python, but I think Python has largely won the race to be the most popular language for data analysis which in turn encourage more developers to commit to it, cementing Python's advantage.

R still has solid lead in statistics and a good mindshare amongst academics.

[baldfat]

> R could be just as capable as Python, but I think Python has largely won the race to be the most popular language for data analysis which in turn encourage more developers to commit to it, cementing Python's advantage.

Your comparing Apples and Oranges. R is a domain specific language and will never be a general purpose language.

It is not true that Python won any race in statistics. http://www.kdnuggets.com/2015/05/r-vs-python-data-science.ht...

Let alone in industry investment coming from Microsoft and other major players.

R is above Python in Statistics in momentum and numbers. Python is a good choice but Python is still playing catch up to R due to the speed at which R is developing. R with data.table and Hadleyverse (https://www.r-bloggers.com/welcome-to-the-hadleyverse/) and RStudio the momentum has been clearly on the side of R.

R just 5 years ago was a fraction of the users it has today.

Python and R are both good choices with equal speed but the difference is that R is a domain specific language that has a lot of positive ecco system.

[robertk]

R is a LISP. I would disagree heavily with it being domain-specific. It is as capable and Turing complete as any language. The only argument you can create is about performance and the judiciousness of putting stats functions in the base library, as opposed to Common Lisp which ships with even less. Not only "will" it be a general purpose programming language, it already is.