Well that could have been said (and was said) about Numpy/Scipy when it started, "oh R has so many more packages, what numpy can do I can do in MATLAB ...", yet here we are.
It depends on the definition of 'people'. There were many who adopted numpy much before the ecosystem had had time to catchup. But I would readily concede that Dr. Jones @national_lab didnt at that time, in fact he probably hasnt even now.
I do disagree strongly with the opinion that Numpy is no better than MATLAB :). MATLAB has adopted some Numpy features after Numpy came out (broadcasting for example) but Numpy offered some genuine and unique advantages, both technical (broadcasting, no need for a MEX compiler that I have to pay through my nose for, not restricted to weird naming conventions, nature of parameter passing, ...) and legal.
I just don't like the BASIC derived syntax of Julia (and Ruby.) I wish there was a language that was typed, had python like classes, subroutines and lambdas but JS like anonymous functions that was fast like Julia or at least close to numpy in number crunching without needing a module written in C.
Have a look at Nim, I was presently surprised when I recently tried it out. Now if there was just a better way of integrating with numpy it would be my goto language for writing computation intensive modules for python.