Numpy is certainly amazing, but there are tons of competitors in the data/scientific space, which pure "A-type" data scientists tend to prefer: R, SSPS, Matlab...
The difference is that Python doesn't entirely suck as a general-purpose language. Sure, you might have better options, but it's still reasonable to write almost anything in Python.
Other scripting languages like Ruby, JS and Lua are probably a little bit better when evaluated strictly on their merits as programming languages, but they lack the ecosystem.
In other words, it might be inelegant, slow, a mess, whatever, but the concept behind it is basically correct.
The difference is that Python doesn't entirely suck as a general-purpose language. Sure, you might have better options, but it's still reasonable to write almost anything in Python.
Other scripting languages like Ruby, JS and Lua are probably a little bit better when evaluated strictly on their merits as programming languages, but they lack the ecosystem.
In other words, it might be inelegant, slow, a mess, whatever, but the concept behind it is basically correct.