Vyas Ramasubramani comments

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                                            Vyas Ramasubramani

[QST] aggregate function that operates on vector(array of numeric) data

This kind of operations is not natively supported, unfortunately. The fundamental issue is that pandas allows you to put arbitrary objects into a Series/DataFrame and it will run Python operations...

[QST] aggregate function that operates on vector(array of numeric) data

Yes, that is basically equivalent. You cannot operate on the numpy arrays directly, but assuming they are all of the same length you could split them into multiple columns if...

[QST] aggregate function that operates on vector(array of numeric) data

@Rhett-Ying does the above solution address your needs?

[QST] aggregate function that operates on vector(array of numeric) data

For more advanced operations, yes it will depend. If operators already exist in other libraries like cuVS those will almost certainly be faster than any apply-based solution you come up...

[QST] aggregate function that operates on vector(array of numeric) data

Going to close as resolved, but feel free to follow up if there are more questions.

Fix inconsistent usage of 'results' and 'records' in read-json.md

/merge

Fix inconsistent usage of 'results' and 'records' in read-json.md

/ok to test

Fix inconsistent usage of 'results' and 'records' in read-json.md

/merge

Parse (non-MultiIndex) label-based keys to structured data

@wence- did this stall out just waiting for reviews? If so, I'm very sorry I lost track of it. Please bring it up to date and I'm happy to review...

Parse (non-MultiIndex) label-based keys to structured data

I am loathe to close this PR outright given how many issues that it fixes, but I also fear that it is woefully out of sync with the current state...