This is the weird thing that's happening right now, and maybe it's not a good thing. Any pipelines that have been built from the daraframe onward (datavis libr

This is the weird thing that's happening right now, and maybe it's not a good thing. Any pipelines that have been built from the daraframe onward (datavis libraries being the big ones) have been based on pandas (or rather its DataFrame API) as the de facto standard. Additionally, other libraries or wrappers have sought to replicate or be compatible with the pandas API. But, the one universal complaint about pandas was always its API! Moving on from it, I'd say, is a substantial part of the motivation behind something like polars. So we're in some unpleasant "worse is better" territory here, and to me, it feels like python really missed the mark by too much. The pandas API is "fine", but really, we could do with better. One option is to just treat the pandas DataFrame as the translation layer. If you need to dump tabular data from your library into a datavis library, then `plot(my_df.to_pandas())`. Hopefully that conversion overhead never becomes too much of a headache. If pandas gets full Arrow compatibility (last I checked, they were behind R and tidyverse on this??), then it shouldn't really be an issue anymore and Wes Mckinney can hopefully stop getting complaints about the pandas API!.