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
1931401581,I_kwDOAMm_X85zHtlt,8282,Resampler giving grouper error with pandas 2,51638288,closed,0,,,2,2023-10-07T15:57:12Z,2023-10-07T19:03:09Z,2023-10-07T19:03:09Z,NONE,,,,"### What happened?

I was trying to resample an xarray DataArray to get the mean values of the array at N-second intervals (I have used the value 20 in the example). My DataArray had two co-ordinates, ""time"" and ""LAT_GIN"" with one dimension: time. This failed with the error below. When I downgraded pandas from 2.1.0 to 1.5.3 (without changing the xarray version), it worked.

I was advised on [StackOverflow](https://stackoverflow.com/questions/77173874/how-to-perform-resampling-in-xarray-without-pandas-grouper-error) to report this here rather than on the pandas github.

### What did you expect to happen?

I expected a DataArray resampled every N seconds (here 5 values in the resampled array = 100/20), where the LAT_GIN co-ordinate has also been averaged over each of the sample periods. I was able to get this with pandas 1.5.3.

### Minimal Complete Verifiable Example

```Python
start_time = pd.Timestamp(""2023-09-25 12:34:56"")
time_values = pd.date_range(start_time, periods=100, freq=""1S"")
lat_values = np.random.rand(100).astype(np.float32)
da = xr.DataArray(lat_values, coords={'time': time_values}, dims=['time'])
da.coords['LAT_GIN'] = xr.Variable(('time',), lat_values)
da.resample(time='20S').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
TypeError: Grouper.__init__() got an unexpected keyword argument 'base'
```


### Anything else we need to know?

_No response_

### Environment

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.5 | packaged by conda-forge | (main, Jun 14 2022, 07:04:59) [GCC 10.3.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-1160.95.1.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.2
libnetcdf: 4.9.3-development

xarray: 2022.6.0
pandas: 2.1.0
numpy: 1.26.0
scipy: 1.11.2
netCDF4: 1.6.4
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.6.2
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: 3.7.3
cartopy: 0.22.0
seaborn: None
numbagg: None
fsspec: None
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 58.1.0
pip: 22.0.4
conda: None
pytest: None
IPython: 8.15.0
sphinx: None


</details>
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