issue_comments: 426340226

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https://github.com/pydata/xarray/issues/2450#issuecomment-426340226 https://api.github.com/repos/pydata/xarray/issues/2450 426340226 MDEyOklzc3VlQ29tbWVudDQyNjM0MDIyNg== 6628425 2018-10-02T16:28:42Z 2018-10-02T16:28:42Z MEMBER

I'm not sure if I'm understanding the calculation correctly; is something like the following what you are looking for? ``` In [1]: import numpy as np; import pandas as pd; import xarray as xr

In [2]: times = pd.date_range('1979', periods=4, freq='12H')

In [3]: da = xr.DataArray(np.random.rand(4, 2, 3), coords={'time': times}, dims=['time', 'x', 'y'])

In [4]: threshold = 0.5

In [5]: (da > threshold).mean('time') Out[5]: <xarray.DataArray (x: 2, y: 3)> array([[ 0.25, 0.5 , 0.25], [ 0.25, 0.5 , 0.5 ]]) Dimensions without coordinates: x, y ```

 
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