issues: 805389572

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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
805389572 MDU6SXNzdWU4MDUzODk1NzI= 4885 Dataset.mean changes variables without specified dimension 5637662 closed 0     2 2021-02-10T10:37:07Z 2021-04-24T20:00:45Z 2021-04-24T20:00:45Z CONTRIBUTOR      

What happened: If I apply mean(dim='time') on a dataset, variables without that dimension are changed.

What you expected to happen: Variables without the dimension are not changed.

Minimal Complete Verifiable Example:

```python import xarray as xr

ds = xr.Dataset() ds["pos"] = [1, 2, 3] ds["data"] = ("pos", "time"), [[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]] ds["var"] = "pos", [2, 3, 4] print(ds.mean(dim="time")) ```

Anything else we need to know?: That makes it unnecessarily slow, as variables without that dimensions wouldn't need to be read from disk. It is easy enough to work around: python ds2 = ds.copy() for k in ds: if "time" in ds[k].dims: ds2[k] = ds[k].mean(dim="time") However I cannot see why dataset should change the variables without the specified dim.

Environment:

Output of <tt>xr.show_versions()</tt> INSTALLED VERSIONS ------------------ commit: None python: 3.9.1 (default, Jan 20 2021, 00:00:00) [GCC 10.2.1 20201125 (Red Hat 10.2.1-9)] python-bits: 64 OS: Linux OS-release: 5.10.13-200.fc33.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.6 libnetcdf: 4.7.3 xarray: 0.16.2 pandas: 1.0.5 numpy: 1.19.4 scipy: 1.5.2 netCDF4: 1.5.3 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.1.3 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.2.1 dask: None distributed: None matplotlib: 3.3.4 cartopy: None seaborn: None numbagg: None pint: 0.13 setuptools: 49.1.3 pip: 20.2.2 conda: None pytest: 6.0.2 IPython: 7.18.1 sphinx: 3.2.1 
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