a) Having "beautiful code" helps keep focus where it matters: the "difficult" sutff (be data data science, machine learning, math problems, physics simulations, etc).
b) True, there are beautiful libraries all around, and easy to use. In particular to data science, I think NumPy+SciPy+matplotlib are comparable to MATLAB. With beautiful code, portability and no need to pay an expensive license.
c) Totally agree. Though there are small nitpicks in different platforms, most of the times they can be overcome.
d) Totally agree.
Also: the Anaconda distribution solves most of the problems that anyone could have with (b), (c) and (d).
b) True, there are beautiful libraries all around, and easy to use. In particular to data science, I think NumPy+SciPy+matplotlib are comparable to MATLAB. With beautiful code, portability and no need to pay an expensive license.
c) Totally agree. Though there are small nitpicks in different platforms, most of the times they can be overcome.
d) Totally agree.
Also: the Anaconda distribution solves most of the problems that anyone could have with (b), (c) and (d).