issue_comments: 235641894

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https://github.com/pydata/xarray/pull/917#issuecomment-235641894 https://api.github.com/repos/pydata/xarray/issues/917 235641894 MDEyOklzc3VlQ29tbWVudDIzNTY0MTg5NA== 1217238 2016-07-27T16:29:50Z 2016-07-27T16:29:50Z MEMBER

I think the datetime issue is a numpy bug related to https://github.com/numpy/numpy/issues/7619

We can work around this by casting to datetime64[ns]:

(Pdb) ds['t'].values.tolist() [1356998400000000000, 1357084800000000000, 1357171200000000000, 1357257600000000000, 1357344000000000000, 1357430400000000000, 1357516800000000000, 1357603200000000000, 1357689600000000000, 1357776000000000000] (Pdb) ds['t'].values.astype('datetime64[us]').tolist() [datetime.datetime(2013, 1, 1, 0, 0), datetime.datetime(2013, 1, 2, 0, 0), datetime.datetime(2013, 1, 3, 0, 0), datetime.datetime(2013, 1, 4, 0, 0), datetime.datetime(2013, 1, 5, 0, 0), datetime.datetime(2013, 1, 6, 0, 0), datetime.datetime(2013, 1, 7, 0, 0), datetime.datetime(2013, 1, 8, 0, 0), datetime.datetime(2013, 1, 9, 0, 0), datetime.datetime(2013, 1, 10, 0, 0)]

The same issue holds for timedelta:

(Pdb) (ds['t'] - ds['t'][0]).values.tolist() [0, 86400000000000, 172800000000000, 259200000000000, 345600000000000, 432000000000000, 518400000000000, 604800000000000, 691200000000000, 777600000000000] (Pdb) (ds['t'] - ds['t'][0]).values.astype('timedelta64[us]').tolist() [datetime.timedelta(0), datetime.timedelta(1), datetime.timedelta(2), datetime.timedelta(3), datetime.timedelta(4), datetime.timedelta(5), datetime.timedelta(6), datetime.timedelta(7), datetime.timedelta(8), datetime.timedelta(9)]

We can work around these by checking for timedelta64 or datetime64 dtypes (use np.issubdtype(values.dtype, np.datetime64), and using astype to convert to datetime64[us]/timedelta64[us].

 
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