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https://github.com/pydata/xarray/issues/2230#issuecomment-396934730 https://api.github.com/repos/pydata/xarray/issues/2230 396934730 MDEyOklzc3VlQ29tbWVudDM5NjkzNDczMA== 30219501 2018-06-13T13:21:40Z 2018-06-13T13:47:56Z NONE

I can overcome this by using In [14]: fcut.resample(dim='time',freq='M',how='mean',skipna=False) Out[14]: <xarray.Dataset> Dimensions: (bnds: 2, time: 5) Coordinates: * time (time) datetime64[ns] 2006-05-31 2006-06-30 2006-07-31 ... Dimensions without coordinates: bnds Data variables: rotated_pole (time) float64 1.0 1.0 1.0 1.0 1.0 time_bnds (time, bnds) float64 1.438e+07 1.438e+07 1.702e+07 ... TOT_PREC (time) float64 nan nan nan nan nan BUT THE PROBLEM IS:

A) that this behaviour is in contradiction to the computation of a mean. I can always compute a mean with the default option 'skipna=True' regardless I have a few NA's in the timeseries (the output is a number not considering the NA's) or only NA's in the timeseries (the output is NA). This is what i would expect.

B) that setting `skipna=False' does not allow for computations if only one value of the timeseries is NA.

I would like to have the behaviour of the mean operator also for the sum operator.

Also for the climate data operators (CDO) the developers decided to give the users two options, skipna=True and skipna=False. But skipna == TRUE should result in the same behaviour for both operators (mean and sum).

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