I found the biggest benefit of polars is ironically the loss of the thing I thought I would miss most, the index; with pandas there are columns, indices, and multi-indices, whereas with polars, everything is a column, it’s all the same so you can delete a lot of conditionals.

However, I still find myself using pandas for the timestamps, timedeltas, and date offsets, and even still, I need a whole extra column just to hold time zones, since polars maps everything to UTC storage zone, you lose the origin / local TZ which screws up heterogeneous time zone datasets. (And I learned you really need to enforce careful manual thoughtful consideration of time zone replacement vs offsetting at the API level)

Had to write a ton of code to deal with this, I wish polars had explicit separation of local vs storage zones on the Datetime data type