Add "N / A" to `STR_NA_VALUES`
This is a value that I just came across in some data that is in the spirit of the other NA value. I don't think this will be a false positive any more so than some of the other values in this list.

- [x] 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. A test here would just be duplicating the implementation.
- [ ] 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. I don't think this deserves an entry?
PS, I think it is usually bad taste for a test to exactly copy the contents of the implementation like this. Can I just make it so we reference STR_NA_VALUES directly in the test, and remove `_NA_VALUES` from that test? Thanks for the PR but its not really a feasible goal for us to track down every NA value a user could come across, and dealing with whitespace like this is not something I see of being value added to pandas. I think you may just need to handle this in your own process That is definitely true, I already have a selection of additional values I check for. This is just the most egregious one that I thought would.be applicable.for everyone.

Even if we don't get to perfection, I think this PR still improves the situation and is a good contribution. Are you worried that slowly this list will balloon to 100 different examples? Trying to figure out if there is some mitigation o can do to address your concern. Thank you, I appreciate your time and effort! Thanks for the PR, but agreed that it's probably not worth expanding these default at this point so closing