One of the things most noobs will install first is pandas. Pandas needs numpy. Numpy needs lapack, blas etc, even if they're not aware it. Yes, there's wheels, but that's limited to python-only stuff.
Then they're reading on some blog about protobuf, or hdf5, or arrow or whatever, and want to use it - but using either from Python needs installed C libraries. On linux/macos you'll need to dig into your package managers and then hope things are compatible, on Windows it's a complete pain. In conda, they can just 'conda install h5py' or whatever, and get proper hdf5 installed without having to figure out the nitty gritty details.
Well, already I can tell you're disconnected from what "most noobs" are actually like. Presumably you think "most noobs" are data scientists, which just isn't the case in my experience.
> Presumably you think "most noobs" are data scientists, which just isn't the case in my experience
It is the case in my personal experience though. I don't think I'm disconnected from what 'noobs' are as I've taught a lot of them through my line of work.
Assume you're a noob and are exploring Python package universe, fire a new private tab and google 'most popular python packages'; in my case the first 3 links are:
Then they're reading on some blog about protobuf, or hdf5, or arrow or whatever, and want to use it - but using either from Python needs installed C libraries. On linux/macos you'll need to dig into your package managers and then hope things are compatible, on Windows it's a complete pain. In conda, they can just 'conda install h5py' or whatever, and get proper hdf5 installed without having to figure out the nitty gritty details.