If you're doing data science things, it's hard to beat pandas/numpy. I get that those are popular in that community because the barrier to entry with Python is low. People who are just looking for a tool to solve immediate problems would do well to reach for Python.
The problems start when you try to write more complex things. Then you run into the weaknesses in tooling, testing, and performance. People would do well to skip Python and go right to another solution.
I say this having spent half of the last decade working on Python projects. If not for data science and academia keeping it alive, it'd be disappearing along with Perl.