html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/6835#issuecomment-1215321340,https://api.github.com/repos/pydata/xarray/issues/6835,1215321340,IC_kwDOAMm_X85IcFT8,2448579,2022-08-15T16:35:35Z,2022-08-15T16:35:35Z,MEMBER,"I like the idea of just passing tuples through and letting the index deal with it. Just like a MultiIndex, there may be other cases where this makes sense.
For the current `PandasIndex` maybe we can raise a nicer error in `.sel`?","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1318826485
https://github.com/pydata/xarray/issues/6835#issuecomment-1199194614,https://api.github.com/repos/pydata/xarray/issues/6835,1199194614,IC_kwDOAMm_X85HekH2,4160723,2022-07-29T11:59:40Z,2022-07-29T11:59:40Z,MEMBER,"Thanks for the report @momchil-flex. That's definitely a regression.
However, I wonder what should we do: depreciate interpreting tuples as sequences and always consider them as ""scalar"" values or continue interpreting it differently depending on the cases?
For example, tuples indexer values were (and still are) assumed to be single element values when selecting on a dimension coordinate with a multi-index (although eventually the multi-index dimension coordinate might be depreciated in xarray):
```python
da = xr.DataArray(
data=range(3),
dims=""x"",
coords={""a"": (""x"", [""a"", ""a"", ""c""]), ""b"": (""x"", [0, 1, 2])},
).set_index(x=[""a"", ""b""])
da
#
# array([0, 1, 2])
# Coordinates:
# * x (x) object MultiIndex
# * a (x)
# array(1)
# Coordinates:
# x object ('a', 1)
# a