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