Python also got heavyweight libraries such as Numpy and Pandas which put it in the front. Perl do not have have such well known libraries as far as I know.
Amen to this point. I am currently the single engineer in a small software biz and after the last engineer left I thought to myself "well, at least I won't have to decipher his code anymore"...needless to say, I've been shocked by how much time I can spend on a system only to revisit it within a year and have little to no memory of how or why I did something a certain way!
Looking now (it's open source) there's two keywords I have forgotten. It's a Perl binding to a C library using an old version of Swig. There's lots of Perl or C helper code to smooth out the bumps. It also looks like it hasn't been updated (bummer).
This. For the kind of tasks data science involves, you either write C++ or you need the equivalent of Numpy. No Numpy means no Pandas, which means no sane way to wrangle datasets.
For all the hate it gets, Numpy is a world-class library.