id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
1445905299,I_kwDOAMm_X85WLsOT,7282,groupby and mean on a MultiIndex level raises ValueError,25231875,closed,0,,,4,2022-11-11T19:15:58Z,2023-10-30T09:18:54Z,2023-08-31T03:50:33Z,NONE,,,,"### What happened?
After using `set_index` to create a `MultiIndex`, calling `groupby` on a `MultiIndex` level and then `mean` raises an error.
### What did you expect to happen?
Apply mean to groups, no error.
### Minimal Complete Verifiable Example
```Python
d = DataArray(
data=[
[0, 1, 2, 3, 4, 5, 6],
[7, 8, 9, 10, 11, 12, 13],
[14, 15, 16, 17, 18, 19, 20]
],
coords={
""greek"": (""a"", ['alpha', 'beta', 'gamma']),
""colors"": (""a"", ['red', 'green', 'blue']),
""compass"": (""b"", ['north', 'south', 'east', 'west', 'northeast', 'southeast', 'southwest']),
""integer"": (""b"", [0, 1, 2, 3, 4, 5, 6]),
},
dims=(""a"", ""b"")
)
d = d.set_index(a=['greek', 'colors'], b=['compass', 'integer'])
g = d.groupby('greek')
m = g.mean(...)
```
### 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](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), 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 ""<stdin>"", line 1, in <module>
File ""/usr/local/lib/python3.10/site-packages/xarray/core/_aggregations.py"", line 5698, in mean
return self.reduce(
File ""/usr/local/lib/python3.10/site-packages/xarray/core/groupby.py"", line 1201, in reduce
return self.map(reduce_array, shortcut=shortcut)
File ""/usr/local/lib/python3.10/site-packages/xarray/core/groupby.py"", line 1104, in map
return self._combine(applied, shortcut=shortcut)
File ""/usr/local/lib/python3.10/site-packages/xarray/core/groupby.py"", line 1136, in _combine
index, index_vars = create_default_index_implicit(coord)
File ""/usr/local/lib/python3.10/site-packages/xarray/core/indexes.py"", line 1045, in create_default_index_implicit
index = PandasMultiIndex(array, name)
File ""/usr/local/lib/python3.10/site-packages/xarray/core/indexes.py"", line 615, in __init__
raise ValueError(
ValueError: conflicting multi-index level name 'greek' with dimension 'greek'
```
### Anything else we need to know?
_No response_
### Environment
<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.7 (main, Sep 13 2022, 14:31:33) [GCC 10.2.1 20210110]
python-bits: 64
OS: Linux
OS-release: 5.15.49-linuxkit
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: C.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: None
libnetcdf: None
xarray: 2022.11.0
pandas: 1.5.1
numpy: 1.23.4
scipy: None
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: None
cartopy: None
seaborn: None
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 63.2.0
pip: 22.2.2
conda: None
pytest: None
IPython: None
sphinx: None
</details>
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257070215,MDU6SXNzdWUyNTcwNzAyMTU=,1569,Grouping with multiple levels,25231875,closed,0,,,6,2017-09-12T14:46:12Z,2022-04-09T15:25:07Z,2022-04-09T15:25:06Z,NONE,,,,"[http://xarray.pydata.org/en/stable/groupby.html](http://xarray.pydata.org/en/stable/groupby.html) says:
> xarray supports “group by” operations with the same API as pandas
but when I supply the `level` keyword argument as described at [https://pandas.pydata.org/pandas-docs/stable/groupby.html#groupby-with-multiindex](https://pandas.pydata.org/pandas-docs/stable/groupby.html#groupby-with-multiindex), I get:
```
TypeError Traceback (most recent call last)
<ipython-input-12-566fc67c0151> in <module>()
----> 1 hvm_it_v6_obj = hvm_it_v6.groupby(level=[""category"",""obj""]).mean(dim=""presentation"")
2 hvm_it_v6_obj
TypeError: groupby() got an unexpected keyword argument 'level'
```","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1569/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
255597950,MDU6SXNzdWUyNTU1OTc5NTA=,1554,TypeError on DataArray.stack() if any of the dimensions to be stacked has a MultiIndex,25231875,open,0,,,3,2017-09-06T13:09:30Z,2019-04-05T18:35:12Z,,NONE,,,,"If I call .stack() on a DataArray, and any of the dimensions to be stacked already has a MultiIndex on it, I get an error:
``TypeError: Must pass list-like as `names`.``
Maybe it doesn't make sense for .stack() to work on an existing MultiIndex, but that should probably be documented, and perhaps throw a more informative error.
Here's the full trace:
```
Traceback (most recent call last)
<ipython-input-6-ce81ac38d71e> in <module>()
----> 1 xr_one_flat_stacked = xr_one_flat.stack(alphanumeric=(""letters"", ""numbers""))
2 xr_one_flat_stacked
/Users/jjpr/anaconda/envs/dldata/lib/python2.7/site-packages/xarray/core/dataarray.pyc in stack(self, **dimensions)
1027 DataArray.unstack
1028 """"""
-> 1029 ds = self._to_temp_dataset().stack(**dimensions)
1030 return self._from_temp_dataset(ds)
1031
/Users/jjpr/anaconda/envs/dldata/lib/python2.7/site-packages/xarray/core/dataset.pyc in stack(self, **dimensions)
1832 result = self
1833 for new_dim, dims in dimensions.items():
-> 1834 result = result._stack_once(dims, new_dim)
1835 return result
1836
/Users/jjpr/anaconda/envs/dldata/lib/python2.7/site-packages/xarray/core/dataset.pyc in _stack_once(self, dims, new_dim)
1801 else level
1802 for level in levels]
-> 1803 idx = utils.multiindex_from_product_levels(levels, names=dims)
1804 variables[new_dim] = IndexVariable(new_dim, idx)
1805
/Users/jjpr/anaconda/envs/dldata/lib/python2.7/site-packages/xarray/core/utils.pyc in multiindex_from_product_levels(levels, names)
79 indexing='ij')
80 labels = [x.ravel() for x in labels_mesh]
---> 81 return pd.MultiIndex(levels, labels, sortorder=0, names=names)
82
83
/Users/jjpr/anaconda/envs/dldata/lib/python2.7/site-packages/pandas/indexes/multi.pyc in __new__(cls, levels, labels, sortorder, names, copy, verify_integrity, _set_identity, name, **kwargs)
103 if names is not None:
104 # handles name validation
--> 105 result._set_names(names)
106
107 if sortorder is not None:
/Users/jjpr/anaconda/envs/dldata/lib/python2.7/site-packages/pandas/indexes/multi.pyc in _set_names(self, names, level, validate)
505 # set the name
506 for l, name in zip(level, names):
--> 507 self.levels[l].rename(name, inplace=True)
508
509 names = property(fset=_set_names, fget=_get_names,
/Users/jjpr/anaconda/envs/dldata/lib/python2.7/site-packages/pandas/indexes/base.pyc in set_names(self, names, level, inplace)
997
998 if not is_list_like(names) and level is None and self.nlevels > 1:
--> 999 raise TypeError(""Must pass list-like as `names`."")
1000
1001 if not is_list_like(names):
TypeError: Must pass list-like as `names`.
```","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1554/reactions"", ""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
329438885,MDU6SXNzdWUzMjk0Mzg4ODU=,2215,align() outer join returns DataArrays that are all NaNs,25231875,closed,0,,,10,2018-06-05T12:42:53Z,2018-06-13T21:02:45Z,2018-06-13T21:02:44Z,NONE,,,,"#### Code Sample, a copy-pastable example if possible
The problem occurs for me in the midst of a data-processing pipeline that starts with some ~40MB netCDF files. I've tried to create pasteable code that reproduces the behavior from scratch, but I haven't succeeded.
#### Problem description
I pass two DataArrays to `xr.align()` with `join=""outer""`. The DataArrays are dtype float64, and contain a mix of NaNs and floats. They are 2D and have MultiIndexes with some numeric and some string levels.
The tuple of DataArrays returned by `align()` have the correct shape and expected indexes, but the contents of the arrays are all NaNs. The original float values are gone. `np.nonzero(~np.isnan(da))` returns an empty array.
I've set breakpoints and delved into the code. On line 656 in `xarray.core.variable.Variable._getitem_with_mask`, `self` contains non-NaN values, but the `data` returned by `as_indexable(self._data)[actual_indexer]` evaluates as all NaNs. However, `data.array` at that point (which is `xarray.backends.netCDF4_.NetCDF4ArrayWrapper`) has non-NaNs. So it's some sort of masking caused by the indexing that makes it look like `data` is all NaNs.
#### Expected Output
A tuple of DataArrays which contain some non-NaN values.
#### Output of ``xr.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-116-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
xarray: 0.10.4
pandas: 0.22.0
numpy: 1.14.0
scipy: 1.0.0
netCDF4: 1.3.1
h5netcdf: None
h5py: None
Nio: None
zarr: None
bottleneck: None
cyordereddict: None
dask: None
distributed: None
matplotlib: 2.1.2
cartopy: None
seaborn: None
setuptools: 38.4.0
pip: 9.0.1
conda: None
pytest: 3.3.2
IPython: 6.2.1
sphinx: None
</details>
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