It can do lots of things, but in my experience, it's been easier to get what I want in other tools. That’s for my stuff (mostly atomic-scale modelling and quantum chemistry in materials science), it might be different for other use cases. I really dislike Matplotlib, so rendering is done in something else, usually gnuplot. I also use it to prepare datasets from large numbers of calculations where the useful results need to be gathered from dozens/hundreds of files in a more or less complex file structure, often on different computers, with the occasional pass with some post-processing tools. Once the pipeline is set, Python is for scripts that need to be run more than about a dozen times, or need to be run on several datasets, or for things that need to be reproduced exactly (like stuff that goes into a paper). On the other hand, Matlab is terrible to write scripts, with its inconsistencies and its almost-Fortran-but-weirder syntax. This does not matter much in a script, but is a pain for interactive use. Also, the general-purpose nature of Python gets in the way, whereas the Matlab-like syntax is very focused and much less cumbersome. I hate having to set up the whole machinery when doing this in Python. That’s usually playing with a dataset, test some analysis techniques, quick regressions, solving linear equations systems, this sort of things. I use Matlab-likes (actually Scilab rather than Octave) for one offs and interactive use.
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