Fixed that for you. IME, in academia (outside of CS), Python is not especially loved at all: it's just there, with Java, R & Perl, and is more seen as a fact of life to deal with rather than anything else.
Because with Java you have to write inflated Fugu, R is too specific and it lacks the vast ecosystem of Python, and Perl causes eye cancer.
That's the first time I've ever heard this criticism of R: most staunch R critics will acknowledge R's vast breadth and depth of statistical libraries outclasses Python. Python has far more general use programming libraries (so deploying models is easier) and used to have a slight advantage in ML specific libraries, but there aren't major differences nowadays between the two ecosystems.
I admit, that R has an advantage in bleeding edge statistics, e.g. from papers. But that is nothing >99% of statistics users need.
Tell me you know nothing about academia without telling me you know nothing about academia.
R is a staple of anything statistics, Java is immensely used, and Perl is the backbone of half of bioinformatics.