issue_comments

Yes, I do think this deviation from pandas would make sense -- though it would be even better if we could convince pandas to make the same change!

We already have low-level tools for controlling how alignment works (construct the index yourself and use .reindex), but we should make the default behavior as user friendly as possible.

From a user perspective, I think it's plain weird to merge a bunch of datasets with montonically decreasing coordinates and land up with a new dataset that has monotonically increasing coordinates.

I'm not entirely sure this is a good idea -- a discrepancy in the behavior of an outer join between pandas seems non-ideal. Perhaps somebody else has opinions about whether this would be worthwhile?

If we do want to do this, let's put the change inside the _get_joiner function. Specifically, instead of python def _get_joiner(join): if join == 'outer': return functools.partial(functools.reduce, operator.or_) you could write something like: ```python def outer_join(indexes): index = functools.reduce(indexes, operator.or) # your logic for reverse sorting the result return index

def _get_joiner(join): if join == 'outer': return _outer_join ```

Note that operator.or_ on a pandas.Index is the same thing as pandas.Index.union, so this could be equivalently written (maybe more clearly) as: python def _outer_join(indexes): index = indexes[0] for other in indexes[1:] index = index.union(other) # your logic for reverse sorting the result return index