> And what about Python for data analysis? The one language that is known to be 10x slower than C becomes the de-facto standard for a field where what matters most is code performance.
Almost everything done in Python for data analysis is just a thin wrapper on top of a fast C/C++ library: Numpy, scikit, Pandas, Tensorflow, etc
That's a good point. You can get away with quite a bit of non-performant user code if the majority of the actual code execution is in the "inner bits" and not the user code. The user code ends up being the "driver" and the heavy lifting is all done by code that is able to provide the required performance. It's also a good reason why PHP has been able to become so pervasive.
Almost everything done in Python for data analysis is just a thin wrapper on top of a fast C/C++ library: Numpy, scikit, Pandas, Tensorflow, etc