I'd second this, especially if its just for personal use!
The data world owes a lot to pandas, but it has plenty of sharp edges and using it can sometimes involve pretty close knowledge of how things like indexing/slicing/etc work under the hood.
If I get stuck in polars, its almost always just a "what's the name of the function to use?" type problem rather than needing lots of knowledge about how things are working under the hood.
Ehhh, there are still plenty of pandas idioms for which there is only a clunky polars equivalent. Sure, I like the strictness of polars, but it is missing some day-to-day functionality. Which might never change - the polars team is trying to be disciplined about having a consistent and performant API, which does mean some functionality may be left behind.
The data world owes a lot to pandas, but it has plenty of sharp edges and using it can sometimes involve pretty close knowledge of how things like indexing/slicing/etc work under the hood.
If I get stuck in polars, its almost always just a "what's the name of the function to use?" type problem rather than needing lots of knowledge about how things are working under the hood.