What happened?

With the 2024.1 release, I am unable to write objects to netCDF after having stacked dimensions with .stack() and called .reset_index() to get rid of the multi-index

What did you expect to happen?

No response

Minimal Complete Verifiable Example

Python import numpy as np import xarray as xr da = xr.DataArray(np.zeros([2, 3]), dims=["x", "y"]) da = da.stack(point=("x", "y")) da = da.reset_index("point") da.to_netcdf("test.nc")

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.
• [X] Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

```Python 86 def ensure_not_multiindex(var: Variable, name: T_Name = None) -> None: 87 if isinstance(var._data, indexing.PandasMultiIndexingAdapter): ---> 88 raise NotImplementedError( 89 f"variable {name!r} is a MultiIndex, which cannot yet be " 90 "serialized. Instead, either use reset_index() " 91 "to convert MultiIndex levels into coordinate variables instead " 92 "or use https://cf-xarray.readthedocs.io/en/latest/coding.html." 93 )

NotImplementedError: variable 'x' is a MultiIndex, which cannot yet be serialized. Instead, either use reset_index() to convert MultiIndex levels into coordinate variables instead or use https://cf-xarray.readthedocs.io/en/latest/coding.html. ```

Anything else we need to know?

Creating the stacked object from scratch and saving it to netCDF works fine. The difference is that type(da.x.variable._data) is xarray.core.indexing.PandasMultiIndexingAdapter if it was stacked and reset and numpy.ndarray if it's created from scratch

Environment

What happened?

run the code block below with 2022.6.0 ``` midx = pd.MultiIndex.from_product([list("abc"), [0, 1]], names=("one", "two"))

mda = xr.DataArray(np.random.rand(6, 3), [("x", midx), ("y", range(3))])

mda.groupby("one").groups output: In [15]: mda.groupby("one").groups Out[15]: {('a', 0): [0], ('a', 1): [1], ('b', 0): [2], ('b', 1): [3], ('c', 0): [4], ('c', 1): [5]} ```

What did you expect to happen?

as it was with 2022.3.0 In [6]: mda.groupby("one").groups Out[6]: {'a': [0, 1], 'b': [2, 3], 'c': [4, 5]}

Minimal Complete Verifiable Example

```Python import pandas as pd import numpy as np import xarray as XR

midx = pd.MultiIndex.from_product([list("abc"), [0, 1]], names=("one", "two"))

mda = xr.DataArray(np.random.rand(6, 3), [("x", midx), ("y", range(3))])

mda.groupby("one").groups ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

Python N/A

Anything else we need to know?

N/A

Environment

What happened?

I was trying to assign coordinates on a dataset that had been created by using stack. After assigning the coordinates, the dataset was in a state where its length was coming out as less than zero, which caused all sorts of issues.

What did you expect to happen?

I think the issue is with the updating of _coord_names, perhaps in https://github.com/pydata/xarray/blob/18454c218002e48e1643ce8e25654262e5f592ad/xarray/core/coordinates.py#L389.

I expected to just be able to assign the coords and then print the array to see the result.

Minimal Complete Verifiable Example

```Python import xarray as xr

ds = xr.DataArray( [[[1, 1], [0, 0]], [[2, 2], [1, 1]]], dims=("lat", "year", "month"), coords={"lat": [-60, 60], "year": [2010, 2020], "month": [3, 6]}, name="test", ).to_dataset()

stacked = ds.stack(time=("year", "month")) stacked = stacked.assign_coords( {"time": [y + m / 12 for y, m in stacked["time"].values]} )

Both these fail with ValueError: len() should return >= 0

len(stacked) print(stacked) ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [x] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

Python Traceback (most recent call last): File "mre.py", line 17, in <module> len(stacked) File ".../xarray-tests/xarray/core/dataset.py", line 1364, in __len__ return len(self.data_vars) ValueError: __len__() should return >= 0

Anything else we need to know?

Here's a test (I put it in test_dataarray.py but maybe there is a better spot)

```python def test_assign_coords_drop_coord_names(self) -> None: ds = DataArray( [[[1, 1], [0, 0]], [[2, 2], [1, 1]]], dims=("lat", "year", "month"), coords={"lat": [-60, 60], "year": [2010, 2020], "month": [3, 6]}, name="test", ).to_dataset()

    stacked = ds.stack(time=("year", "month"))
    stacked = stacked.assign_coords(
        {"time": [y + m / 12 for y, m in stacked["time"].values]}
    )

    # this seems to be handled correctly
    assert set(stacked._variables.keys()) == {"test", "time", "lat"}
    # however, _coord_names doesn't seem to update as expected
    # the below fails
    assert set(stacked._coord_names) == {"time", "lat"}

    # the incorrect value of _coord_names means that all the below fails too
    # The failure is because the length of a dataset is calculated as (via len(data_vars))
    # len(dataset._variables) - len(dataset._coord_names). For the situation
    # above, where len(dataset._coord_names) is greater than len(dataset._variables),
    # you get a length less than zero which then fails because length must return
    # a value greater than zero

    # Both these fail with ValueError: __len__() should return >= 0
    len(stacked)
    print(stacked)

```

Environment

What happened?

Please see code below

With xarray:2022.06.0, DataArray.unstack raise an ValueError exception

```python-traceback

ValueError Traceback (most recent call last) Input In [2], in <cell line: 24>() 21 y = y.assign_coords(day=y.j + y.last_j) 22 y = y.set_index(multi=['sub_id', 'last_j']) ---> 24 y = y.unstack()

File /opt/conda/lib/python3.9/site-packages/xarray/core/dataarray.py:2402, in DataArray.unstack(self, dim, fill_value, sparse) 2342 def unstack( 2343 self, 2344 dim: Hashable | Sequence[Hashable] | None = None, 2345 fill_value: Any = dtypes.NA, 2346 sparse: bool = False, 2347 ) -> DataArray: 2348 """ 2349 Unstack existing dimensions corresponding to MultiIndexes into 2350 multiple new dimensions. (...) 2400 DataArray.stack 2401 """ -> 2402 ds = self._to_temp_dataset().unstack(dim, fill_value, sparse) 2403 return self._from_temp_dataset(ds)

File /opt/conda/lib/python3.9/site-packages/xarray/core/dataset.py:4656, in Dataset.unstack(self, dim, fill_value, sparse) 4652 result = result._unstack_full_reindex( 4653 dim, stacked_indexes[dim], fill_value, sparse 4654 ) 4655 else: -> 4656 result = result._unstack_once( 4657 dim, stacked_indexes[dim], fill_value, sparse 4658 ) 4659 return result

File /opt/conda/lib/python3.9/site-packages/xarray/core/dataset.py:4492, in Dataset.unstack_once(self, dim, index_and_vars, fill_value, sparse) 4489 else: 4490 fill_value = fill_value -> 4492 variables[name] = var.unstack_once( 4493 index=clean_index, 4494 dim=dim, 4495 fill_value=fill_value, 4496 sparse=sparse, 4497 ) 4498 else: 4499 variables[name] = var

File /opt/conda/lib/python3.9/site-packages/xarray/core/variable.py:1732, in Variable._unstack_once(self, index, dim, fill_value, sparse) 1727 # Indexer is a list of lists of locations. Each list is the locations 1728 # on the new dimension. This is robust to the data being sparse; in that 1729 # case the destinations will be NaN / zero. 1730 data[(..., *indexer)] = reordered -> 1732 return self._replace(dims=new_dims, data=data)

File /opt/conda/lib/python3.9/site-packages/xarray/core/variable.py:985, in Variable._replace(self, dims, data, attrs, encoding) 983 if encoding is _default: 984 encoding = copy.copy(self._encoding) --> 985 return type(self)(dims, data, attrs, encoding, fastpath=True)

File /opt/conda/lib/python3.9/site-packages/xarray/core/variable.py:2720, in IndexVariable.init(self, dims, data, attrs, encoding, fastpath) 2718 super().init(dims, data, attrs, encoding, fastpath) 2719 if self.ndim != 1: -> 2720 raise ValueError(f"{type(self).name} objects must be 1-dimensional") 2722 # Unlike in Variable, always eagerly load values into memory 2723 if not isinstance(self._data, PandasIndexingAdapter):

ValueError: IndexVariable objects must be 1-dimensional ```

What did you expect to happen?

Please see code below

With xarray:2022.03.0, code runs well

Minimal Complete Verifiable Example

```Python import xarray as xr import numpy as np

x = np.concatenate((np.repeat(np.nan,4), np.repeat(1,2))).reshape(3, 2).transpose() x = xr.DataArray( x, coords = { 'composite_id': ['s00', 's10'], 'sub_id': ('composite_id', ['0', '1']), 'last_j': ('composite_id', [100, 111]), 'j': [-2,-1,0] }, dims= ['composite_id', 'j'] )

y = x y = y.stack({'multi': ['composite_id', 'j']}) y = y.dropna('multi') y = y.assign_coords(day=y.j + y.last_j) y = y.set_index(multi=['sub_id', 'last_j'])

y = y.unstack() ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [x] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

Environment

Not working environment with xarray 2022.06.0

Working environment with xarray 2022.03.0

What happened?

I'm not sure my usecase is the simplest way to demonstrate the issue, but let's try anyway.

I have a DataArray with two coordinates and I stack them into a new multi-index. I want to pass the levels of that new multi-index into a function, but as dask arrays. Turns out, it is not straightforward to chunk these variables because they act like IndexVariable objects and refuse to be chunked.

Thus, I reset the multi-index, drop it, but the variables still don't want to be chunked!

What did you expect to happen?

I expected the levels to be chunkable after the sequence : stack, reset_index.

Minimal Complete Verifiable Example

```Python import xarray as xr ds = xr.tutorial.open_dataset('air_temperature')

ds = ds.stack(spatial=['lon', 'lat']) ds = ds.reset_index('spatial', drop=True) # I don't think the drop is important here. lon_chunked = ds.lon.chunk() # woups, doesn't do anything!

type(ds.lon.variable) # xarray.core.variable.IndexVariable # I assumed either the stack or the reset_index would have modified this type into a normal variable. ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

Seems kinda related to the issues around reset_index. I thinks this is related to (but not a duplicate of) #4366.

Environment

What happened?

This issue originates from this discussion where I was trying to figure out the best way to replace coordinate values in a MultiIndex level. I found that removing the level with reset_index and replacing the coordinate level with assign_coords works except when removing level leaves you with a MultIndex with only one level. In this case a ValueError is thrown.

What did you expect to happen?

I expect that removing and replacing a coordinate level would work the same independent of the number of levels in the MultiIndex.

Minimal Complete Verifiable Example

```Python import numpy as np import pandas as pd import xarray as xr

Replace the coordinates in level 'one'. This works as expected.

midx = pd.MultiIndex.from_product([[0,1,2], [3, 4], [5,6]], names=("one", "two","three")) mda = xr.DataArray(np.random.rand(12, 3), [("x", midx), ("y", range(3))])

new_coords = mda.coords['one'].values*2 mda.reset_index('one', drop=True).assign_coords(one= ('x',new_coords)).set_index(x='one',append=True) #Works

Drop the two level before had such that the intermediate state has a multindex

with only the 'three' level, this throws a ValueError

mda.reset_index('two',drop=True).reset_index('one', drop=True).assign_coords(one= ('x',new_coords)) #ValueError

We can intialize a data array with only two levels and only drop the 'one'

level, which gives the same ValueError. This shows that the problem is not

due to something with dropping the 'two' level above, but something inherent

to dropping to a state with only one multinddex level

midx = pd.MultiIndex.from_product([[0,1,2], [3, 4]], names=("one", "two")) mda = xr.DataArray(np.random.rand(6, 2), [("x", midx), ("y", range(2))])

new_coords = mda.coords['one'].values*2 mda.reset_index('one', drop=True).assign_coords(one= ('x',new_coords)).set_index(x='one',append=True) #ValueError ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

```Python

First example, starting from 3 level multiindex and dropping two levels

ValueError Traceback (most recent call last) c:\Users\aspit\Git\Learn\xarray\replace_coord_issue.py in <module> 15 # Drop the two level before had such that the intermediate state has a multindex 16 # with only the 'three' level, this throws a ValueError ---> 17 mda.reset_index('two',drop=True).reset_index('one', drop=True).assign_coords(one= ('x',new_coords))

c:\Users\aspit\anaconda3\envs\dataanalysis\lib\site-packages\xarray\core\common.py in assign_coords(self, coords, **coords_kwargs) 590 data = self.copy(deep=False) 591 results: dict[Hashable, Any] = self._calc_assign_results(coords_combined) --> 592 data.coords.update(results) 593 return data 594

c:\Users\aspit\anaconda3\envs\dataanalysis\lib\site-packages\xarray\core\coordinates.py in update(self, other) 160 other_vars = getattr(other, "variables", other) 161 self._maybe_drop_multiindex_coords(set(other_vars)) --> 162 coords, indexes = merge_coords( 163 [self.variables, other_vars], priority_arg=1, indexes=self.xindexes 164 )

c:\Users\aspit\anaconda3\envs\dataanalysis\lib\site-packages\xarray\core\merge.py in merge_coords(objects, compat, join, priority_arg, indexes, fill_value) 564 collected = collect_variables_and_indexes(aligned) 565 prioritized = _get_priority_vars_and_indexes(aligned, priority_arg, compat=compat) --> 566 variables, out_indexes = merge_collected(collected, prioritized, compat=compat) 567 return variables, out_indexes 568

c:\Users\aspit\anaconda3\envs\dataanalysis\lib\site-packages\xarray\core\merge.py in merge_collected(grouped, prioritized, compat, combine_attrs, equals) 252 253 _assert_compat_valid(compat) --> 254 _assert_prioritized_valid(grouped, prioritized) 255 256 merged_vars: dict[Hashable, Variable] = {}

c:\Users\aspit\anaconda3\envs\dataanalysis\lib\site-packages\xarray\core\merge.py in _assert_prioritized_valid(grouped, prioritized) 199 common_names_str = ", ".join(f"{k!r}" for k in common_names) 200 index_names_str = ", ".join(f"{k!r}" for k in index_coord_names) --> 201 raise ValueError( 202 f"cannot set or update variable(s) {common_names_str}, which would corrupt " 203 f"the following index built from coordinates {index_names_str}:\n"

ValueError: cannot set or update variable(s) 'one', which would corrupt the following index built from coordinates 'x', 'one', 'three': <xarray.core.indexes.PandasMultiIndex object at 0x00000225AA4B5200>

Second Example Starting from two level multindex and dropping one level

ValueError Traceback (most recent call last) c:\Users\aspit\Git\Learn\xarray\replace_coord_issue.py in <module> 11 12 new_coords = mda.coords['one'].values*2 ---> 13 mda.reset_index('one', drop=True).assign_coords(one= ('x',new_coords)).set_index(x='one',append=True)

c:\Users\aspit\anaconda3\envs\dataanalysis\lib\site-packages\xarray\core\common.py in assign_coords(self, coords, **coords_kwargs) 590 data = self.copy(deep=False) 591 results: dict[Hashable, Any] = self._calc_assign_results(coords_combined) --> 592 data.coords.update(results) 593 return data 594

c:\Users\aspit\anaconda3\envs\dataanalysis\lib\site-packages\xarray\core\coordinates.py in update(self, other) 160 other_vars = getattr(other, "variables", other) 161 self._maybe_drop_multiindex_coords(set(other_vars)) --> 162 coords, indexes = merge_coords( 163 [self.variables, other_vars], priority_arg=1, indexes=self.xindexes 164 )

c:\Users\aspit\anaconda3\envs\dataanalysis\lib\site-packages\xarray\core\merge.py in merge_coords(objects, compat, join, priority_arg, indexes, fill_value) 564 collected = collect_variables_and_indexes(aligned) 565 prioritized = _get_priority_vars_and_indexes(aligned, priority_arg, compat=compat) --> 566 variables, out_indexes = merge_collected(collected, prioritized, compat=compat) 567 return variables, out_indexes 568

c:\Users\aspit\anaconda3\envs\dataanalysis\lib\site-packages\xarray\core\merge.py in merge_collected(grouped, prioritized, compat, combine_attrs, equals) 252 253 _assert_compat_valid(compat) --> 254 _assert_prioritized_valid(grouped, prioritized) 255 256 merged_vars: dict[Hashable, Variable] = {}

c:\Users\aspit\anaconda3\envs\dataanalysis\lib\site-packages\xarray\core\merge.py in _assert_prioritized_valid(grouped, prioritized) 199 common_names_str = ", ".join(f"{k!r}" for k in common_names) 200 index_names_str = ", ".join(f"{k!r}" for k in index_coord_names) --> 201 raise ValueError( 202 f"cannot set or update variable(s) {common_names_str}, which would corrupt " 203 f"the following index built from coordinates {index_names_str}:\n"

ValueError: cannot set or update variable(s) 'one', which would corrupt the following index built from coordinates 'x', 'one', 'two': <xarray.core.indexes.PandasMultiIndex object at 0x00000225AA53C9E0> ```

Anything else we need to know?

No response

Environment

What happened?

Resetting a multi-index to a single level (i.e., a single index) does not rename the remaining level coordinate to the dimension name.

What did you expect to happen?

While it is certainly more consistent not to rename the level coordinate here (since an index can be assigned to a non-dimension coordinate now), it breaks from the old behavior. I think it's better not introduce any breaking change. As discussed elsewhere, we might eventually want to deprecate reset_index in favor of drop_indexes (#6971).

Minimal Complete Verifiable Example

```Python import pandas as pd import xarray as xr

midx = pd.MultiIndex.from_product([["a", "b"], [1, 2]], names=("foo", "bar"))

ds = xr.Dataset(coords={"x": midx})

<xarray.Dataset>

Dimensions: (x: 4)

Coordinates:

* x (x) object MultiIndex

* foo (x) object 'a' 'a' 'b' 'b'

* bar (x) int64 1 2 1 2

Data variables:

empty

rds = ds.reset_index("foo")

v2022.03.0

<xarray.Dataset>

Dimensions: (x: 4)

Coordinates:

* x (x) int64 1 2 1 2

foo (x) object 'a' 'a' 'b' 'b'

Data variables:

empty

v2022.06.0

<xarray.Dataset>

Dimensions: (x: 4)

Coordinates:

foo (x) object 'a' 'a' 'b' 'b'

* bar (x) int64 1 2 1 2

Dimensions without coordinates: x

Data variables:

empty

```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

Environment

Seen in #4103

MCVE Code Sample

```python from xarray.tests import assert_identical

coord_1 = xr.DataArray([1, 2], dims=["coord_1"], attrs={"attrs": True}) da = xr.DataArray([1, 0], [coord_1]) obj = da.reset_index("coord_1").rename({"coord_1_": "coord_1"}) assert_identical(da, obj) ```

Expected Output

Problem Description

``` AssertionErrorTraceback (most recent call last) <ipython-input-19-02ef6bd89884> in <module> ----> 1 assert_identical(da, obj)

~/work/python/xarray/xarray/tests/init.py in assert_identical(a, b) 160 xarray.testing.assert_identical(a, b) 161 xarray.testing._assert_internal_invariants(a) --> 162 xarray.testing._assert_internal_invariants(b) 163 164

~/work/python/xarray/xarray/testing.py in _assert_internal_invariants(xarray_obj) 265 _assert_variable_invariants(xarray_obj) 266 elif isinstance(xarray_obj, DataArray): --> 267 _assert_dataarray_invariants(xarray_obj) 268 elif isinstance(xarray_obj, Dataset): 269 _assert_dataset_invariants(xarray_obj)

~/work/python/xarray/xarray/testing.py in _assert_dataarray_invariants(da) 210 assert all( 211 isinstance(v, IndexVariable) for (k, v) in da._coords.items() if v.dims == (k,) --> 212 ), {k: type(v) for k, v in da._coords.items()} 213 for k, v in da._coords.items(): 214 _assert_variable_invariants(v, k)

AssertionError: {'coord_1': <class 'xarray.core.variable.Variable'>} ```

Versions

What happened?

Ok so this one is a bit weird. I'm not sure this is a bug, but code that worked before doesn't anymore, so it is some sort of regression.

I have a dataset with one dimension and one coordinate along that one, but they have different names. I want to transform this so that the coordinate name becomes the dimension name so it becomes are proper dimension-coordinate (I don't know how to call it). After renaming the dim to the coord's name, it all looks good in the repr, but the coord still is missing an index for that dimension (crd.indexes is empty, see MCVE). There was a workaround through reset_coords for this, but it doesn't work anymore.

Instead, the last line of the MCVE downgrades the variable, the final lon doesn't have coords anymore.

What did you expect to happen?

In the MCVE below, I show what the old "workaround" was. I expected lon.indexes to contain the indexes lon at the end of the procedure.

Minimal Complete Verifiable Example

```Python import xarray as xr

A dataset with a 1d variable along a dimension

ds = xr.Dataset({'lon': xr.DataArray([1, 2, 3], dims=('x',))})

Promote to coord. This still is not a proper crd-dim (different name)

ds = ds.set_coords(['lon'])

Rename dim:

ds = ds.rename(x='lon')

Now do we have a proper coord-dim ? No. not yet because:

ds.indexes # is empty

Workaround that was used up to the last release

lon = ds.lon.reset_coords(drop=True)

Because of the missing indexes the next line fails on the master

lon - lon.diff('lon') ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [x] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

My guess is that this line is causing reset_coords to drop the coordinate from itself : https://github.com/pydata/xarray/blob/c34ef8a60227720724e90aa11a6266c0026a812a/xarray/core/dataarray.py#L866

It would be nice if the renaming was sufficient for the indexes to appear.

My example is weird I know. The real use case is a script where we receive a 2d coordinate but where all lines are the same, so we take the first line and promote it to a proper coord-dim. But the current code fails on the master on the lon - lon.diff('lon') step that happens afterwards.

Environment

@benbovy I also just tested the get_unique() method that you mentioned and maybe noticed a related issue here, which I'm not sure is wanted / expected.

Taking the above dataset ds, accessing this function results in an error:

```python

ds.indexes.get_unique()

TypeError: unhashable type: 'MultiIndex' ```

However, for xindexes it works: ```python

ds.xindexes.get_unique()

[<xarray.core.indexes.PandasMultiIndex at 0x7f105bf1df20>] ```

Originally posted by @lukasbindreiter in https://github.com/pydata/xarray/issues/6752#issuecomment-1236717180

What happened: After updating xarray to v0.20.1, some of my multi-index-based selection code raises a TypeError.

What you expected to happen: Selection should work in the case I am considering.

Minimal Complete Verifiable Example:

```python import xarray as xr import pandas as pd

da = xr.DataArray(data=[0, 1, 2, 3], dims=("x",)).reindex( {"x": pd.MultiIndex.from_product((["foo", "bar"], [0, 1]), names=("str", "int"))} ) print(da.sel(x=("foo", 1))) ```

Expected output (what I get with xarray 0.19.0):

<xarray.DataArray ()> array(1) Coordinates: x object ('foo', 1)

Actual output (with xarray 0.20.1):

Traceback (most recent call last): File "playgrounds/xarray_mwe.py", line 7, in <module> da.sel(x=("foo", 1)) File "/Users/leroyv/miniforge3/envs/eradiate/lib/python3.7/site-packages/xarray/core/dataarray.py", line 1337, in sel **indexers_kwargs, File "/Users/leroyv/miniforge3/envs/eradiate/lib/python3.7/site-packages/xarray/core/dataset.py", line 2505, in sel self, indexers=indexers, method=method, tolerance=tolerance File "/Users/leroyv/miniforge3/envs/eradiate/lib/python3.7/site-packages/xarray/core/coordinates.py", line 422, in remap_label_indexers obj, v_indexers, method=method, tolerance=tolerance File "/Users/leroyv/miniforge3/envs/eradiate/lib/python3.7/site-packages/xarray/core/indexing.py", line 120, in remap_label_indexers idxr, new_idx = index.query(labels, method=method, tolerance=tolerance) File "/Users/leroyv/miniforge3/envs/eradiate/lib/python3.7/site-packages/xarray/core/indexes.py", line 235, in query label_value, method=method, tolerance=tolerance TypeError: get_loc() got an unexpected keyword argument 'tolerance'

Anything else we need to know?: Nothing I'm aware of

Environment: