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issues: 33307883

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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
33307883 MDExOlB1bGxSZXF1ZXN0MTU3NjcwMTU= 125 Only copy datetime64 data if it is using non-nanosecond precision. 514053 closed 0     7 2014-05-12T13:36:22Z 2014-05-20T19:09:40Z 2014-05-20T19:09:40Z CONTRIBUTOR   0 pydata/xarray/pulls/125

In an attempt to coerce all datetime arrays to nano second resolutoin utils.as_safe_array() was creating copies of any datetime64 array (via the astype method). This was causing unexpected behavior (bugs) for things such as concatenation over times. (see below).

``` import xray import pandas as pd

ds = xray.Dataset() ds['time'] = ('time', pd.date_range('2011-09-01', '2011-09-11')) times = [ds.indexed(time=[i]) for i in range(10)] ret = xray.Dataset.concat(times, 'time') print ret['time']

<xray.DataArray 'time' (time: 10)> array(['1970-01-02T07:04:40.718526408-0800', '1969-12-31T16:00:00.099966608-0800', '1969-12-31T16:00:00.041748384-0800', '1969-12-31T16:00:00.041748360-0800', '1969-12-31T16:00:00.041748336-0800', '1969-12-31T16:00:00.041748312-0800', '1969-12-31T16:00:00.041748288-0800', '1969-12-31T16:00:00.041748264-0800', '1969-12-31T16:00:00.041748240-0800', '1969-12-31T16:00:00.041748216-0800'], dtype='datetime64[ns]') Attributes: Empty ```

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