issue_comments: 464953041

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https://github.com/pydata/xarray/issues/2191#issuecomment-464953041 https://api.github.com/repos/pydata/xarray/issues/2191 464953041 MDEyOklzc3VlQ29tbWVudDQ2NDk1MzA0MQ== 23510121 2019-02-19T02:22:22Z 2019-02-19T02:22:58Z NONE

@spencerkclark Thank you very much for your help! I will install the development version on my local machine. Currently I am using NCAR Cheyenne to manipulate the climate data. What I am doing on Cheyenne as a detour is: xarray.assign_coords(time = xarray.indexes['time'].to_datetimeindex()) xarray.resample(time="D").mean("time") I hope NCAR will support the next release of xarray. A follow-up question is that when we using xarray to manipulate the large dataset such as <xarray.DataArray (time: 14600, lat: 192, lon: 288)> and want to save the results for further machine learning applications (e.g., using sklearn or XGBoost, even deep learning), what will be a good format to store the data on server or local machine that will be easily used by sklearn or XGBoost?

 
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