Do you mean a real world example in 2018 or 2002? NumPy started as an extension to Python, not as part of the core library. So that's why it is the way it is, not because of any performance tradeoffs.
https://scipy.github.io/old-wiki/pages/History_of_SciPy.html
You seem to be asking a specific version of a more general question. Perhaps if you thought about it more generally, you'd see that your question might not be very useful. Specific modules exist to offer features not available in the core language. There is no surprise if they are more optimized, have more features, or even if they are used more.
It doesn't mean you have to use them, nor is it (much) of a problem to leave them in.
I guess I don't understand why you're asking this question, it would help us try to provide you a better answer.
