issue_comments: 43548881

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https://github.com/pydata/xarray/pull/134#issuecomment-43548881 https://api.github.com/repos/pydata/xarray/issues/134 43548881 MDEyOklzc3VlQ29tbWVudDQzNTQ4ODgx 1217238 2014-05-19T20:00:48Z 2014-05-19T20:00:48Z MEMBER

The reason I cast all datetime64 to datetime64[ns] is because pandas will not let you make an Index of datetime64 objects with anything other than ns precision. If you try to make it an Index with dtype=object you'll actually get an array of datetime.datetime objects:

```

pd.Index(pd.date_range('2000-01-01', periods=5).values.astype('datetime64[us]'), dtype='object').values array([datetime.datetime(2000, 1, 1, 0, 0), datetime.datetime(2000, 1, 2, 0, 0), datetime.datetime(2000, 1, 3, 0, 0), datetime.datetime(2000, 1, 4, 0, 0), datetime.datetime(2000, 1, 5, 0, 0)], dtype=object) ```

But I do agree this is not terribly consistent nor fully thought through. And it should certainly be well-documented.

 
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