The notebook loads a couple of Pandas dataframes, each with 5-10M rows, filters each them down to 3-5M rows, samples 10% of them, and plots various charts. Unsure whether to allocate more resources, make my notebook more resource efficient, or something else. I can provide the stacktrace if helpful.
The stacktracr would be helpful. If you could make a notebook that reproduces the issue (using synthetic data if your data is private) that would be very helpful
