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Description
What happened?
From #8951
if d is a MultiIndex-ed dataset with levels (x, y, z), and m is a dataset with a single coord x
m.isel(x=d.x) builds a dataset with a MultiIndex with levels (y, z). This seems like it should work.
cc @benbovy
What did you expect to happen?
No response
Minimal Complete Verifiable Example
import pandas as pd, xarray as xr, numpy as np
xr.set_options(use_flox=True)
test = pd.DataFrame()
test["x"] = np.arange(100) % 10
test["y"] = np.arange(100)
test["z"] = np.arange(100)
test["v"] = np.arange(100)
d = xr.Dataset.from_dataframe(test)
d = d.set_index(index = ["x", "y", "z"])
print(d)
m = d.groupby("x").mean()
print(m)
print(d.xindexes)
print(m.isel(x=d.x).xindexes)
xr.align(d, m.isel(x=d.x))
#res = d.groupby("x") - m
#print(res)<xarray.Dataset>
Dimensions: (index: 100)
Coordinates:
* index (index) object MultiIndex
* x (index) int64 0 1 2 3 4 5 6 7 8 9 0 1 2 ... 8 9 0 1 2 3 4 5 6 7 8 9
* y (index) int64 0 1 2 3 4 5 6 7 8 9 ... 90 91 92 93 94 95 96 97 98 99
* z (index) int64 0 1 2 3 4 5 6 7 8 9 ... 90 91 92 93 94 95 96 97 98 99
Data variables:
v (index) int64 0 1 2 3 4 5 6 7 8 9 ... 90 91 92 93 94 95 96 97 98 99
<xarray.Dataset>
Dimensions: (x: 10)
Coordinates:
* x (x) int64 0 1 2 3 4 5 6 7 8 9
Data variables:
v (x) float64 45.0 46.0 47.0 48.0 49.0 50.0 51.0 52.0 53.0 54.0
Indexes:
┌ index PandasMultiIndex
│ x
│ y
└ z
Indexes:
┌ index PandasMultiIndex
│ y
└ z
ValueError...
MVCE confirmation
- Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- Complete example — the example is self-contained, including all data and the text of any traceback.
- Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
- New issue — a search of GitHub Issues suggests this is not a duplicate.
- Recent environment — the issue occurs with the latest version of xarray and its dependencies.
Relevant log output
No response
Anything else we need to know?
No response