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
1473329967,I_kwDOAMm_X85X0Tsv,7350,Coordinate variable gains coordinate on subset,221526,closed,0,,,5,2022-12-02T19:18:14Z,2022-12-05T22:56:30Z,2022-12-05T22:56:30Z,CONTRIBUTOR,,,,"### What happened?
When subsetting a DataArray along a dimension down to a single item, the other coordinate variables gain this scalar coordinate.
### What did you expect to happen?
Coordinate variables should not have their coordinates changed.
### Minimal Complete Verifiable Example
```Python
import numpy as np
import xarray as xr
lat = np.array([25, 35, 45])
lon = np.array([-105, -95, -85, -75])
time = np.array([0, 1])
data = np.arange(lat.size * lon.size * time.size)
test_data = xr.DataArray(data.reshape((time.size, lat.size, lon.size)),
coords=dict(lat=lat, lon=lon, time=time),
dims=('time', 'lat', 'lon'))
print(test_data.lat.coords) # Only 'lat'
print(test_data.isel(time=0).lat.coords) # Has both 'lat' and 'time'
pritn(test_data.isel(time=[0, 1]).lat.coords) # Only 'lat'
```
### 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
_No response_
### Anything else we need to know?
This occurs with both the latest 2022.11.0 release and current main.
### Environment
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.8 | packaged by conda-forge | (main, Nov 22 2022, 08:31:57) [Clang 14.0.6 ]
python-bits: 64
OS: Darwin
OS-release: 21.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.2
libnetcdf: 4.8.1
xarray: 2022.11.0
pandas: 1.5.2
numpy: 1.23.5
scipy: 1.9.3
netCDF4: 1.6.2
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.6.2
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: 0.9.10.2
iris: None
bottleneck: 1.3.5
dask: 2022.6.1
distributed: 2022.6.1
matplotlib: 3.6.2
cartopy: 0.21.0
seaborn: None
numbagg: None
fsspec: 2022.11.0
cupy: None
pint: 0.20.1
sparse: None
flox: None
numpy_groupies: None
setuptools: 65.5.1
pip: 22.3.1
conda: None
pytest: 7.2.0
IPython: 8.6.0
sphinx: 5.3.0
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7350/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
667550022,MDU6SXNzdWU2Njc1NTAwMjI=,4283,Selection with datetime64[ns] fails with Pandas 1.1.0,221526,closed,0,,,2,2020-07-29T05:01:14Z,2020-09-16T01:33:30Z,2020-09-16T01:33:30Z,CONTRIBUTOR,,,,"I ran into this issue with a netCDF file with the following time variable:
```
double time1(time1) ;
time1:_FillValue = NaN ;
time1:standard_name = ""time"" ;
time1:long_name = ""time"" ;
time1:udunits = ""Hour since 2017-09-05T12:00:00Z"" ;
time1:units = ""Hour since 2017-09-05T12:00:00+00:00"" ;
time1:calendar = ""proleptic_gregorian"" ;
time1 = 0, 3, 6, 9, 12, 15, 18, 21, 24 ;
```
but we can reproduce the problem with something as simple as:
```python
import numpy as np
import xarray as xr
t = np.array(['2017-09-05T12:00:00.000000000', '2017-09-05T15:00:00.000000000'], dtype='datetime64[ns]')
da = xr.DataArray(np.ones(t.shape), dims=('time',), coords=(t,))
da.loc[{'time':t[0]}] # Works on pandas 1.0.5
```
this produces:
```pytb
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
in
----> 1 da.loc[{'time':t[0]}]
~/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/dataarray.py in __getitem__(self, key)
196 labels = indexing.expanded_indexer(key, self.data_array.ndim)
197 key = dict(zip(self.data_array.dims, labels))
--> 198 return self.data_array.sel(**key)
199
200 def __setitem__(self, key, value) -> None:
~/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/dataarray.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs)
1147
1148 """"""
-> 1149 ds = self._to_temp_dataset().sel(
1150 indexers=indexers,
1151 drop=drop,
~/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/dataset.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs)
2099 """"""
2100 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, ""sel"")
-> 2101 pos_indexers, new_indexes = remap_label_indexers(
2102 self, indexers=indexers, method=method, tolerance=tolerance
2103 )
~/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/coordinates.py in remap_label_indexers(obj, indexers, method, tolerance, **indexers_kwargs)
394 }
395
--> 396 pos_indexers, new_indexes = indexing.remap_label_indexers(
397 obj, v_indexers, method=method, tolerance=tolerance
398 )
~/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/indexing.py in remap_label_indexers(data_obj, indexers, method, tolerance)
268 coords_dtype = data_obj.coords[dim].dtype
269 label = maybe_cast_to_coords_dtype(label, coords_dtype)
--> 270 idxr, new_idx = convert_label_indexer(index, label, dim, method, tolerance)
271 pos_indexers[dim] = idxr
272 if new_idx is not None:
~/miniconda3/envs/py38/lib/python3.8/site-packages/xarray/core/indexing.py in convert_label_indexer(index, label, index_name, method, tolerance)
187 indexer = index.get_loc(label.item())
188 else:
--> 189 indexer = index.get_loc(
190 label.item(), method=method, tolerance=tolerance
191 )
~/miniconda3/envs/py38/lib/python3.8/site-packages/pandas/core/indexes/datetimes.py in get_loc(self, key, method, tolerance)
620 else:
621 # unrecognized type
--> 622 raise KeyError(key)
623
624 try:
KeyError: 1504612800000000000
```
what's interesting is changing the units of `datetime64` to `[s]` works:
```python
import numpy as np
import xarray as xr
t = np.array(['2017-09-05T12:00:00.000000000', '2017-09-05T15:00:00.000000000'], dtype='datetime64[s]')
da = xr.DataArray(np.ones(t.shape), dims=('time',), coords=(t,))
da.loc[{'time':t[0]}] # Works
```
**Environment**:
Python 3.8 from conda-forge on macOS 10.15.4
Output of xr.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.8.5 | packaged by conda-forge | (default, Jul 24 2020, 01:06:20)
[Clang 10.0.1 ]
python-bits: 64
OS: Darwin
OS-release: 19.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.6
libnetcdf: 4.7.4
xarray: 0.16.0
pandas: 1.1.0
numpy: 1.19.1
scipy: 1.5.2
netCDF4: 1.5.4
pydap: None
h5netcdf: None
h5py: 2.10.0
Nio: None
zarr: None
cftime: 1.2.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: 0.9.8.3
iris: None
bottleneck: None
dask: 2.21.0
distributed: 2.21.0
matplotlib: 3.3.0
cartopy: 0.18.0
seaborn: None
numbagg: None
pint: 0.14
setuptools: 49.2.0.post20200712
pip: 20.1.1
conda: None
pytest: 6.0.0
IPython: 7.16.1
sphinx: 2.4.4