issue_comments: 296274069

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https://github.com/pydata/xarray/issues/1380#issuecomment-296274069 https://api.github.com/repos/pydata/xarray/issues/1380 296274069 MDEyOklzc3VlQ29tbWVudDI5NjI3NDA2OQ== 8699967 2017-04-21T18:49:57Z 2017-04-21T19:44:00Z CONTRIBUTOR

Thank you @spencerahill and @shoyer. That was brilliant.

Here is the solution: ```python path_to_files = '*.grib2' def extract_date(ds): for var in ds.variables: if 'initial_time' in ds[var].attrs.keys(): grid_time = pd.to_datetime(ds[var].attrs['initial_time'], format="%m/%d/%Y (%H:%M)") if 'forecast_time' in ds[var].attrs.keys(): time_units = 'h' if 'forecast_time_units' in ds[var].attrs.keys(): time_units = str(ds[var].attrs['forecast_time_units'][0]) grid_time += np.timedelta64(int(ds[var].attrs['forecast_time'][0]), time_units)

        return ds.assign(time=grid_time)
raise ValueError("Time attribute missing: {0}".format(self.search_time_attr))

with xr.open_mfdataset(path_to_files, concat_dim='time', preprocess=extract_date, engine='pynio') as xd: print(xd) ```

 
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