IndexSlice on a datetime multindex not working, but doesn't seem different from a properly-working toy equivalent

I'm used to using IndexSlice on datetime indices. This is a toy equivalent of my multindex DataFrame and you can see the slicing works

#slicing works on a simple DateTime index
qf = pd.DataFrame(index=pd.date_range(start="1Jan2019",freq="d",periods=30))
qf.loc[idx['2019-1-15':None]]   #works


#the same slicing works on a multindex
qf.reset_index(inplace=True)
qf['foo']="bar"
qf['other']=range(len(qf))
qf['filler']="egbdf"
qf.set_index(['index','foo', 'other'], inplace=True)

qf.loc[idx['2019-1-15':'2019-1-20',:,:],:] #wrks    
qf.loc[idx['2019-1-15':None,'bar',:],:]   #works

But something is going on with a my real DataFrame. I cannot see what the difference is.

xf.loc[idx['2019-5-1':'2019-6-1',"squat",:],:]     # This works ok
xf.loc[idx['2019-5-1':None,"squat",:],:]           # This fails

The error I get when I slice with a '2019-5-1':None is

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-280-b0dce8e9e337> in <module>
      1 xf.loc[idx['2019-5-1':'2019-6-1',"squat",:],:]     # This works ok
----> 2 xf.loc[idx['2019-5-1':None,"squat",:],:]           # This fails
      3 #xf

C:\ProgramData\Anaconda3\envs\nambu\lib\site-packages\pandas\core\indexing.py in __getitem__(self, key)
   1492             except (KeyError, IndexError, AttributeError):
   1493                 pass
-> 1494             return self._getitem_tuple(key)
   1495         else:
   1496             # we by definition only have the 0th axis

C:\ProgramData\Anaconda3\envs\nambu\lib\site-packages\pandas\core\indexing.py in _getitem_tuple(self, tup)
    866     def _getitem_tuple(self, tup):
    867         try:
--> 868             return self._getitem_lowerdim(tup)
    869         except IndexingError:
    870             pass

C:\ProgramData\Anaconda3\envs\nambu\lib\site-packages\pandas\core\indexing.py in _getitem_lowerdim(self, tup)
    967         # we may have a nested tuples indexer here
    968         if self._is_nested_tuple_indexer(tup):
--> 969             return self._getitem_nested_tuple(tup)
    970 
    971         # we maybe be using a tuple to represent multiple dimensions here

C:\ProgramData\Anaconda3\envs\nambu\lib\site-packages\pandas\core\indexing.py in _getitem_nested_tuple(self, tup)
   1046 
   1047             current_ndim = obj.ndim
-> 1048             obj = getattr(obj, self.name)._getitem_axis(key, axis=axis)
   1049             axis += 1
   1050 

C:\ProgramData\Anaconda3\envs\nambu\lib\site-packages\pandas\core\indexing.py in _getitem_axis(self, key, axis)
   1904             # nested tuple slicing
   1905             if is_nested_tuple(key, labels):
-> 1906                 locs = labels.get_locs(key)
   1907                 indexer = [slice(None)] * self.ndim
   1908                 indexer[axis] = locs

C:\ProgramData\Anaconda3\envs\nambu\lib\site-packages\pandas\core\indexes\multi.py in get_locs(self, seq)
   2774                 # a slice, include BOTH of the labels
   2775                 indexer = _update_indexer(_convert_to_indexer(
-> 2776                     self._get_level_indexer(k, level=i, indexer=indexer)),
   2777                     indexer=indexer)
   2778             else:

C:\ProgramData\Anaconda3\envs\nambu\lib\site-packages\pandas\core\indexes\multi.py in _get_level_indexer(self, key, level, indexer)
   2635                 # note that the stop ALREADY includes the stopped point (if
   2636                 # it was a string sliced)
-> 2637                 return convert_indexer(start.start, stop.stop, step)
   2638 
   2639             elif level > 0 or self.lexsort_depth == 0 or step is not None:

AttributeError: 'int' object has no attribute 'stop'

I cannot see any material difference between the toy index and the real index, and I cannot see how the error message results to passing None into the slicer.

from IndexSlice on a datetime multindex not working, but doesn't seem different from a properly-working toy equivalent