Make the conversion from dtype to subclass just a little faster
Calling `is_float_dtype` is a really "safe" way to take an array or a dtype and know if it is a subclass.

But I don't think you need to do that. Checking the `kind` should be enough. I get about 5-10% faster on the benchmarks shown. Mostly reducing 12us to 11.5 us. I think it is real.

- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [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
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) 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.

I think maybe my knowledge of "isinstance" is really outdated. I can't find a meaningful difference running the benchmarks on my computers.

oh well. feel free to close or merge, sorry for the noise. ExtensionDtype case is handled separately above.  its also a bit of a moot point since Float64Index, Int64Index, and UInt64Index are going away soon. Ah I missed that portion of the function. Okay I think I would be okay with this then thanks @hmaarrfk  👍🏾 