Comment by xpe
1 year ago
In the early days, even as I appreciated what Pandas could do, I never found its API sane. Pandas has too many special cases and foot-guns. It is a notorious case of poor design.
My opinion is hardly uncommon. If you read over https://www.reddit.com/r/datascience/comments/c3lr9n/am_i_th... you will find many in agreement. Of those who "like" Pandas, it is often only a relative comparison to something worse.
The problems of the Pandas API were not intrinsic nor unavoidable. They were poor design choices probably caused by short-term thinking or a lack of experience.
Polars is a tremendous improvement.
Hey, I agree with you.
On eager vs lazy evaluation -- pytorch defaulting to eager seemed to be part of the reason it was popular. Adding optional lazy evaluation to improve performance later seems to have worked for them.