DateOffset add to ndarray

[JonAnCla]

This is WIP to implement changes needed to allow DateOffset subclasses e.g. MonthEnd to be directly added to numpy.ndarray, e.g. numpy.array(['2022-01-01'], dtype='datetime64') + pandas.offsets.MonthEnd(1)

I need some guidance on:

• cython mechanism to check that passed ndarray is datetime64 dtype i.e.cython equivalent of pandas.api.types.is_datetime64_any_dtype
• how to approach adding unit tests? two ideas I have
  • somehow duplicate existing offset tests but run them on ndarray instead of Series? looks on the surface to be more difficult to implement
  • apply a set of offsets to a predefined Series and ndarray equivalent, and then check results match

Many thanks!

• closes ENH: implement DateOffset + np.datetime64 array #47014
• Tests added and passed if fixing a bug or adding a new feature
• All code checks passed.
• Added type annotations to new arguments/methods/functions.
• Added an entry in the latest doc/source/whatsnew/vX.X.X.rst file if fixing a bug or adding a new feature.

[mroeschke]

Do we need the astype here?

[JonAnCla]

I found that without this DateOffset._apply_array did not respect the dtype that was passed in

once the .astype step was added in, I could use e.g. datetime64[D] and get a datetime64[D] back

I'll do some further testing when working on unit tests

[mroeschke]

FWIW datetime64[D] is not a supported unit in pandas

[mroeschke]

This would also need tests and a whatsnew note in v3.0.0.rst

[github-actions]

This pull request is stale because it has been open for thirty days with no activity. Please update and respond to this comment if you're still interested in working on this.

[mroeschke]

Thanks for the pull request, but it appears to have gone stale. If interested in continuing, please merge in the main branch, address any review comments and/or failing tests, and we can reopen.