issues: 325436508

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325436508 MDU6SXNzdWUzMjU0MzY1MDg= 2170 keepdims=True for xarray reductions 1217238 closed 0     3 2018-05-22T19:44:17Z 2019-06-23T09:18:33Z 2019-06-23T09:18:33Z MEMBER      

For operations where arrays are aggregated but then combined, the keepdims=True option for NumPy aggregations is convenient.

We should consider supporting this in xarray as well. Aggregating a DataArray/Dataset with keepdims=True (or maybe keep_dims=True) would remove all original coordinates along aggregated dimensions and return a result with a dimension of size 1 without any coordinates, e.g., ```

array = xr.DataArray([1, 2, 3], dims='x', coords={'x': ['a', 'b', 'c']}) array.mean(keepdims=True) <xarray.DataArray (x: 1)> array([2.]) Dimensions without coordinates: x ```

In case, array.mean(keepdims=True() is equivalent to array.mean().expand_dims('x') but in general this equivalent does not hold, because the location of the original dimension is lost.

Implementation-wise, we have two options: 1. Pass on keepdims=True to NumPy functions like numpy.mean(), or 2. Implement keepdims=True ourselves, in Variable.reduce().

I think I like option 2 a little better, because it places fewer requirements on aggregation functions. For example, functions like bottleneck.nanmean() don't accept a keepdims argument.

 
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