BUG/ENH: groupby quantile arraylike fails with integer columns
When columns are integers, `df.groupby(label).quantile(<arraylike>)` fails.
This PR fixes this issue by telling `MultiIndex` to only look for positional levels during an reordering operation.
Two new internal methods in `MultiIndex` class, and one new parameter for `DataFrame.reorder_levels` and `MultiIndex.reorder_levels` are added during the debugging process.

- [ ] closes #30289
- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry

> this is not the right solution as we are not adding a confusing at best parameter to a public function
> 
> this entire routine needs to be refactored to avoid the current method which is highly suspect now

hi Jeff, thanks for review.
Now that I think about it, I agree with you this solution is too rough.
The idea of `positional` parameter came from the discussions in the issue (#30289).
By "this entire routine needs to be refactored" I assume you mean `GroupBy.quantile` should not rely on `DataFrame.reorder_levels` at all? Could you let me know a bit more details about the design you are thinking of? 
Anyway, should I close this PR and start another one when ready? Or do you think maybe some of it is useful and I should keep this? group by quantile needs the refactor to avoid the need to reindex the multiindex which is causing the issue now)

you can close or push to this PR up to u Sorry I messed up the different commits and reverts in this branch. Will close this PR and open a new one. 