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# Create basic Datasetimportnumpyasnpimportpandasaspdimportxarrayasxrtemp=15+8*np.random.randn(2, 2, 3)
precip=10*np.random.rand(2, 2, 3)
lon= [[-99.83, -99.32], [-99.79, -99.23]]
lat= [[42.25, 42.21], [42.63, 42.59]]
# for real use cases, its good practice to supply array attributes such as# units, but we won't bother here for the sake of brevityds=xr.Dataset({'temperature': (['x', 'y', 'time'], temp),
'precipitation': (['x', 'y', 'time'], precip)},
coords={'lon': (['x', 'y'], lon),
'lat': (['x', 'y'], lat),
'time': pd.date_range('2014-09-06', periods=3),
'reference_time': pd.Timestamp('2014-09-05')})
# Both of these throw attribute errorsds.notnull()
# ds.isnull()
Problem description
The above methods throw AttributeError: 'Variable' object has no attribute '_constructor' errors when called on Datasets. It's not clear if this operation is currently supported, but if it's not then it probably shouldn't be exposed through the API.
Expected Output
Dataset of boolean DataArrays indicating null-ness.
Output of xr.show_versions()
Show_versions() doesn't seem to exist in 0.9.6, but presumably this covers it:
Code Sample, a copy-pastable example if possible
Problem description
The above methods throw
AttributeError: 'Variable' object has no attribute '_constructor'
errors when called on Datasets. It's not clear if this operation is currently supported, but if it's not then it probably shouldn't be exposed through the API.Expected Output
Dataset of boolean DataArrays indicating null-ness.
Output of
xr.show_versions()
Numpy version: 1.13.1
Pandas version: 0.21.0
XArray version: 0.9.6
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