`mean` returns empty DataArray for `groupby_bins` containing `datetime64`

[observingClouds]

What happened?

Applying the mean operator to an xarray dataset that has been grouped by bins, removes variables containing values of type datetime64.

What did you expect to happen?

I expect that all variables are preserved after applying the mean-operator. For min and max this works as expected. sum is not meaningful, so it makes sense that the variable is dropped in that case as well.

Minimal Complete Verifiable Example

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

times = pd.date_range('2020-01-01', '2020-02-01', freq='1H')
index = np.arange(len(times))
bins = np.arange(0,len(index),5)
ds=xr.Dataset({'time':('index', times),'float':('index', np.linspace(0,1,len(index)))},coords={'index':index})

ds.groupby_bins('index', bins).mean()
<xarray.Dataset>
Dimensions:     (index_bins: 148)
Coordinates:
  * index_bins  (index_bins) object (0, 5] (5, 10] ... (730, 735] (735, 740]
Data variables:
    float       (index_bins) float64 0.004032 0.01075 0.01747 ... 0.9852 0.9919

ds.groupby_bins('index', bins).min()
<xarray.Dataset>
Dimensions:     (index_bins: 148)
Coordinates:
  * index_bins  (index_bins) object (0, 5] (5, 10] ... (730, 735] (735, 740]
Data variables:
    time        (index_bins) datetime64[ns] 2020-01-01T01:00:00 ... 2020-01-3...
    float       (index_bins) float64 0.001344 0.008065 0.01478 ... 0.9825 0.9892

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

INSTALLED VERSIONS ------------------ commit: None python: 3.10.6 | packaged by conda-forge | (main, Aug 22 2022, 20:43:44) [Clang 13.0.1 ] python-bits: 64 OS: Darwin OS-release: 21.6.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: None LOCALE: ('en_US', 'UTF-8') libhdf5: None libnetcdf: None

xarray: 2022.6.0 pandas: 1.4.4 numpy: 1.23.2 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: 3.5.3 cartopy: None seaborn: None numbagg: None fsspec: 2022.8.2 cupy: None pint: None sparse: None flox: None numpy_groupies: None setuptools: 65.3.0 pip: 22.2.2 conda: None pytest: None IPython: 8.4.0 sphinx: None

[observingClouds]

This issue might be a duplicate of #5897 and it continues to exist in version 2022.09.0.