Polars is a lot better than pandas at maintaining valid state. Because you ideally describe everything in terms of lazy operations, it actually internally keep

Polars is a lot better than pandas at maintaining valid state. Because you ideally describe everything in terms of lazy operations, it actually internally keeps track of all your data types at every step until materialization and execution of the query plan. Because of that, you're not going to have the same kind of data type issues you might have in pandas. There are also libraries based off pydantic built for polars dataframes validation (see patito, though it's not mature yet).