issue_comments: 340008407

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https://github.com/pydata/xarray/issues/1662#issuecomment-340008407 https://api.github.com/repos/pydata/xarray/issues/1662 340008407 MDEyOklzc3VlQ29tbWVudDM0MDAwODQwNw== 1956032 2017-10-27T15:44:11Z 2017-10-27T15:44:11Z CONTRIBUTOR

Note that if the xarray decode_cf is given a NaT, in a datetime64, it works:

```python attrs = {'units': 'days since 1950-01-01 00:00:00 UTC'} # Classic Argo data Julian Day reference jd = [24658.46875, 24658.46366898, 24658.47256944, np.NaN] # Sample

def dirtyfixNaNjd(ref,day): td = pd.NaT if not np.isnan(day): td = pd.Timedelta(days=day) return pd.Timestamp(ref) + td

jd = [dirtyfixNaNjd('1950-01-01',day) for day in jd] print jd python [Timestamp('2017-07-06 11:15:00'), Timestamp('2017-07-06 11:07:40.999872'), Timestamp('2017-07-06 11:20:29.999616'), NaT] then:python ds = xr.Dataset({'time': ('time', jd, {'units': 'ns'})}) # Update the units attribute appropriately ds = xr.decode_cf(ds) print ds['time'].values python ['2017-07-06T11:15:00.000000000' '2017-07-06T11:07:40.999872000' '2017-07-06T11:20:29.999616000' 'NaT'] ```

 
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