DEPR: ignoring missing labels when indexing on MultiIndex level
- [ ] closes #xxxx
- [ ] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry

There are a bunch of issues that boil down to this weird behavior.  I need to track down the full list (@attack68 do you have such a list handy?)
> 
> There are a bunch of issues that boil down to this weird behavior. I need to track down the full list (@attack68 do you have such a list handy?)

I haven't got a list but I have a script/notebook that tries to iterate over all possible combinations and display the results. I will try and post it later.

I hold the view that the tests for multiindex loc is quite sparse in terms of patchy parametrised tests, but I think a more robust algorithmic approach to all combinations might be worthwhile. Perhaps a routine for this might develop from the script?? https://github.com/attack68/pandas/tree/multiindex_ipynb 
file in root: `LocIndexing.ipynb`

It gathers and analyses many different combinations of `loc` slicing.

For a MultiIndex with `['a', 'b', 'c', 'd']` in each level, (i.e. `'!'` not in any level) here is a summary of some odd `series.loc` slices, when combining with different index types (duplicated vs unique, and monotonic vs unsorted).

![Screen Shot 2021-07-13 at 16 32 18](https://user-images.githubusercontent.com/24256554/125472004-4d3b204c-c4ac-453e-91ed-507c1eb1732a.png)

