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  • dschwoerer · 1 ✖

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  • Dataset.mean changes variables without specified dimension · 1 ✖

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788052130 https://github.com/pydata/xarray/issues/4885#issuecomment-788052130 https://api.github.com/repos/pydata/xarray/issues/4885 MDEyOklzc3VlQ29tbWVudDc4ODA1MjEzMA== dschwoerer 5637662 2021-03-01T15:47:52Z 2021-03-01T15:47:52Z CONTRIBUTOR

I tried this: diff --- a/xarray/core/dataset.py +++ b/xarray/core/dataset.py @@ -4701,7 +4701,9 @@ class Dataset(Mapping, ImplementsDatasetReduce, DataWithCoords): if not reduce_dims: variables[name] = var else: - if ( + if not reduce_dims: + variables[name] = var + elif ( not numeric_only or np.issubdtype(var.dtype, np.number) or (var.dtype == np.bool_) which works great for mean - "var" stays an integer, as expected.

However, that breaks ds.std - which should be zero for "var", but isn't. I guess that is ok for coords - as the assumption is that on coordinates the calculation is not done, but for data variables this is probably not ok.

```diff --- a/xarray/core/duck_array_ops.py +++ b/xarray/core/duck_array_ops.py @@ -537,6 +537,11 @@ def mean(array, axis=None, skipna=None, **kwargs): dtypes""" from .common import _contains_cftime_datetimes

  • The mean over an empty axis shouldn't change the data

  • See https://github.com/pydata/xarray/issues/4885

  • if not axis:
  • return array + array = asarray(array) if array.dtype.kind in "Mm": offset = _datetime_nanmin(array) ``` I think it is best to change mean - which would work also for dataArrays. This implies that mean does not convert to float64 - as the numpy version does, but I guess that should be fine.

Should I open a PR?

 
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   Dataset.mean changes variables without specified dimension 805389572

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