[aldanor]

I use both PyCharm and JupyterLab on daily basis, typically dealing with multi-gb datasets.

If I'm writing a library or adding new features to one, or writing tests I'll use PyCharm sure thing, otherwise the notebook is a quicker way to sketch prototypes and always have a kernel with preloaded datasets and pre-imported stuff ready at hand. I don't want to wait 10 minutes to just load the data every time I want to check if my new function works well on it at big scale. That's one of the most important bits.

PyCharm is a clear winner at actually writing code that you won't throw in the bin 10 min later, and once you know what to write.

Debugging? Don't remember ever using PyCharm despite the fact it exists... either pudb or python-devtools or something else. I'd just write tests and things start working in the process. And btw you have pdb debugger (some weak version of it) in jupyter if you really need it. Docstrings? Press tab twice in the notebook. Or keep PyCharm open on the side so you can cmd-b. Profiling? Never a pycharm builtin, maybe something like flamegraph but an external tool anyway.