Dataset.mean changes variables without specified dimension #4885
Description
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:
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:
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 xr.show_versions()
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