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  • Rework PandasMultiIndex.sel internals · 2 ✖

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1255524719 https://github.com/pydata/xarray/pull/7004#issuecomment-1255524719 https://api.github.com/repos/pydata/xarray/issues/7004 IC_kwDOAMm_X85K1clv mathause 10194086 2022-09-22T20:38:40Z 2022-09-22T20:38:40Z MEMBER

It would be nice to be able to preserve the MultiIndex with sel (e.g. ds.sel(one=["a"]) but if it makes the behavior inconsistent it is no good either...

 
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   Rework PandasMultiIndex.sel internals 1364798843
1240463387 https://github.com/pydata/xarray/pull/7004#issuecomment-1240463387 https://api.github.com/repos/pydata/xarray/issues/7004 IC_kwDOAMm_X85J7_gb benbovy 4160723 2022-09-08T09:28:25Z 2022-09-08T09:28:25Z MEMBER

it is now allowed to provide array-like labels.

Hmm not sure if it's a good idea... I find get_locs() a bit confusing like in the example below where a 4-labels array for level "one" returns a 3-items location integer array:

```python

is the 3rd label ("b") ignored?

midx.get_locs((np.array(["b", "a", "b", "c"]), 0))

array([4, 0, 8])

```

That differs too much from the vectorized selection based on single pandas indexes...

Fancy indexing with n-d label arrays doesn't work either:

```python midx.get_locs((np.array([["a", "a"], ["a", "a"]]), 0))

InvalidIndexError: [['a' 'a']

['a' 'a']]

```

And providing Variable or DataArray objects as labels would make things event harder, unless we ignore their dimension names and coordinates (but then it wouldn't be consistent with vectorized selection based on single pandas indexes).

Probably not worth it then?

 
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   Rework PandasMultiIndex.sel internals 1364798843

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