issues: 667550022

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) <ipython-input-11-3e0afa0bd195> in <module> ----> 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 <tt>xr.show_versions()</tt>

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