issues: 300268334

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
300268334 MDExOlB1bGxSZXF1ZXN0MTcxMzk2NjUw 1942 Fix precision drop when indexing a datetime64 arrays. 6815844 closed 0     2 2018-02-26T14:53:57Z 2018-06-08T01:21:07Z 2018-02-27T01:13:45Z MEMBER   0 pydata/xarray/pulls/1942
  • [x] Closes #1932
  • [x] Tests added
  • [x] Tests passed
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

This precision drop was caused when converting pd.Timestamp to np.array python In [7]: ts = pd.Timestamp(np.datetime64('2018-02-12 06:59:59.999986560')) In [11]: np.asarray(ts, 'datetime64[ns]') Out[11]: array('2018-02-12T06:59:59.999986000', dtype='datetime64[ns]')

We need to call to_datetime64 explicitly.

 
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