html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue 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'] ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,268725471 https://github.com/pydata/xarray/issues/1662#issuecomment-339991529,https://api.github.com/repos/pydata/xarray/issues/1662,339991529,MDEyOklzc3VlQ29tbWVudDMzOTk5MTUyOQ==,1956032,2017-10-27T14:42:56Z,2017-10-27T14:42:56Z,CONTRIBUTOR,"Hi Ryan, never been very far, following/promoting xarray around here, and congrats for Pangeo ! Ok, I get the datatype being wrong, but about the issue from pandas TimedeltaIndex: Does this means that a quick/dirty fix should be to decode value by value rather than on a vector ?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,268725471