Earlier quoted context omitted.
I've been working with Matlab for years and have been quite intrigued by claims that SciPy is the new, better, Matlab. But every time I tried it, it felt like a cheap knockoff. For example, let's say I want to apply DCT to a matrix. In Matlab it's simply dct(A). How do you do that in Python? Well, there's scipy.fftpack.dct, but when I try it, it turns out it operates on the rows of A, instead of the columns. So I sta…
So, basically, you're panning the massive open collaborative effort behind SciPy/NumPy/Pandas because you can't be bothered to learn a slightly different and more flexible syntax? Because that's what it sounds like.
Scipy/Numpy/Pandas are, at the moment, not the comprehensive, well documented and consistent platform that Matlab is. Simple things like a less than painless install process and numpy examples like "a*b" can be element wise multiplication or matrix multiplication pending if "a" is array or matrix are enough to put of my coworkers off for at least a year or two before contemplating a switch again.