PERF: potential room for optimizing aggregation(like sum, count and mean) on df.groupby

[Alexia-I]

PERF: potential room for optimizing aggregation(like sum, count and mean) on df.groupby

[rhshadrach]

Thanks for the suggestion. We would need to check whether the groups do indeed form a contiguous sequence. In addition, it would mean the type of index in the result is dependent on the values being grouped, which can make it hard to predict for users. For these reasons, I do not think we should be swapping out the index.

[Alexia-I]

@rhshadrach Thanks for your quick response and for considering the suggestion. I believe the proposed optimization could be particularly useful when users group rows by an integer dtype column that forms a contiguous sequence. It really consumes much memory when using other index type other than rangeindex. I believe this enhancement could contribute to the overall efficiency and performance of Pandas, especially for data processing tasks involving large datasets. This is a common scenario, especially in large datasets, where the choice of index type can significantly impact memory usage. Utilizing RangeIndex in such cases could offer substantial memory savings.
Besides, most users interact with DataFrame contents rather than the index type and I think most operations do not distinguish int64index and rangeindex, and it would not affect user too much. Also, I anticipate that implementing this change could be relatively straightforward. Thus I think this might be easy and useful to fix.

[phofl]

I agree with @rhshadrach, we don't want value dependent behaviour if we can avoid it, the improvement isn't worth the hassle in this case. You can cast the Index by yourself if necessary.