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  • brynpickering · 2 ✖

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  • Removing dimensions from Dataset objects · 2 ✖

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369315468 https://github.com/pydata/xarray/issues/1949#issuecomment-369315468 https://api.github.com/repos/pydata/xarray/issues/1949 MDEyOklzc3VlQ29tbWVudDM2OTMxNTQ2OA== brynpickering 17178478 2018-02-28T17:27:10Z 2018-02-28T17:27:38Z NONE

The drop technique seems reasonable, if a bit long-winded for the programmatic case (loop over all dimensions, find any that are empty -> loop over all variables, drop any that contain those empty dimensions).

As an addition, if the empty dimension also has an associated empty coordinate then it requires an extra step to get rid of it:

``` python In [21]: test_dataset = xr.Dataset(dict( ...: empty_array=xr.DataArray([], dims='a', coords={'a':[]}), ...: populated_array=xr.DataArray([1], {'b':['1']}, 'b') ...: ))

In [22]: test_dataset Out[22]: <xarray.Dataset> Dimensions: (a: 0, b: 1) Coordinates: * a (a) float64 * b (b) <U1 '1' Data variables: empty_array (a) float64 populated_array (b) int32 1

In [23]: test_dataset.drop('empty_array') Out[23]: <xarray.Dataset> Dimensions: (a: 0, b: 1) Coordinates: * a (a) float64 * b (b) <U1 '1' Data variables: populated_array (b) int32 1

In [24]: del test_dataset['a']

In [25]: test_dataset.drop('empty_array') Out[25]: <xarray.Dataset> Dimensions: (b: 1) Coordinates: * b (b) <U1 '1' Data variables: populated_array (b) int32 1 ```

Fixes seem reasonable, based on how we use xarray over at https://github.com/calliope-project/calliope/. The second one also provides more scope to remove subsets of data (all corresponding dims, coords, vars) if the dimension becomes superfluous for any reason, whether or not the dimension is empty.

 
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   Removing dimensions from Dataset objects 301031693
369247490 https://github.com/pydata/xarray/issues/1949#issuecomment-369247490 https://api.github.com/repos/pydata/xarray/issues/1949 MDEyOklzc3VlQ29tbWVudDM2OTI0NzQ5MA== brynpickering 17178478 2018-02-28T14:00:26Z 2018-02-28T14:00:26Z NONE

I don't think it's actually possible to purge a, hence why I started an issue rather than SO Q. As you can see, squeeze() removes b from the list of dimensions, but not a (as a has a length 0, not 1). 

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   Removing dimensions from Dataset objects 301031693

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