DEPR: Enforce deprecation of numeric_only=None in DataFrame aggregations
- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [x] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [x] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.

looks like some frame reductions tests are failing > looks like some frame reductions tests are failing

Thanks @jbrockmendel - this got a bit tricky. When the input is numeric but has object dtype, axis=1, and numeric_only=False, in 1.5.x the result is object dtype. When numeric_only=None however, the result is float. I think this behavior originated from #676. It seems odd, but I think a very rare case. I opted to go to with the 1.5.x default (numeric_only=None) behavior here and put a line in the whatsnew. If that looks good, I can open an issue on this for followup.

Also, when working on these fixes, I realized I missed generic.py / series.py for this deprecation. Went unnoticed because `None` is falsey. needs rebase, otherwise LGTM Thanks @rhshadrach  nice!