I don’t know if it’s still true but Wes McKinney’s (Pandas author) rule of thumb for Pandas was “have 5 to 10 times as much as RAM as your dataset”. But he wrote this in 2017 so things may have changed.
That said, this is a 2023 comparison of Pandas and Polars memory usage.
Kind of like "do I really need k8s?", "does my workload dictate I need SQL OLAP (Online Analytical Processing) / data frame lazy loading data library?"
what's the general rule of thumb to know "you're missing out by not using existing library like pandas/polars" for somebody who is out of the loop on this kind of stuff