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/2636#issuecomment-450458650,https://api.github.com/repos/pydata/xarray/issues/2636,450458650,MDEyOklzc3VlQ29tbWVudDQ1MDQ1ODY1MA==,30388627,2018-12-29T02:38:00Z,2018-12-29T02:39:41Z,NONE,"@dcherian It works by `netCDF4`, but not for `xarray`:
```
file = Dataset('ds1.nc')
print (file.variables['time'],'\n')

with xr.open_dataset('ds1.nc') as f:
    print (f.time.attrs)
```
Output:
```
<class 'netCDF4._netCDF4.Variable'>
int64 time(time)
    units: hours since 2015-01-01
unlimited dimensions: 
current shape = (3,)
filling on, default _FillValue of -9223372036854775806 used
 

OrderedDict()
```

What's the difference between `units` and `attrs`?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,394625579
https://github.com/pydata/xarray/issues/2636#issuecomment-450456616,https://api.github.com/repos/pydata/xarray/issues/2636,450456616,MDEyOklzc3VlQ29tbWVudDQ1MDQ1NjYxNg==,30388627,2018-12-29T02:17:49Z,2018-12-29T02:17:49Z,NONE,"@xylar Thanks! I just found [another question](https://stackoverflow.com/questions/46702600/how-to-prevent-xarray-from-converting-time-offsets-to-absolute-datetimes) similar to this one.

I've tried some operations:
```
with xr.open_dataset('merge.nc') as f:
    print (f['temperature'],'\n')
    print ('---------------------------')
    print (f.mean(dim='time'))
    print ('---------------------------')
    print (f['temperature'].loc[:,:,'2015-01-05T04:00:00',])
    print ('---------------------------')
```

It works fine:
```
<xarray.DataArray 'temperature' (x: 2, y: 2, time: 6)>
array([[[-0.022611, -1.428088, -0.655508,  0.977389, -0.428088,  0.344492],
        [ 0.430102,  0.996973, -0.882054,  1.430102,  1.996973,  0.117946]],

       [[ 0.157233, -0.230397, -0.505775,  1.157233,  0.769603,  0.494225],
        [-0.075826, -1.933904, -0.823982,  0.924174, -0.933904,  0.176018]]])
Coordinates:
    lon      (x, y) float64 ...
    lat      (x, y) float64 ...
  * time     (time) datetime64[ns] 2015-01-05T04:00:00 2015-01-05T05:00:00 ...
Dimensions without coordinates: x, y 

---------------------------
<xarray.Dataset>
Dimensions:      (x: 2, y: 2)
Coordinates:
    lon          (x, y) float64 ...
    lat          (x, y) float64 ...
Dimensions without coordinates: x, y
Data variables:
    temperature  (x, y) float64 -0.2021 0.6817 0.307 -0.4446
---------------------------
<xarray.DataArray 'temperature' (x: 2, y: 2)>
array([[-0.022611,  0.430102],
       [ 0.157233, -0.075826]])
Coordinates:
    lon      (x, y) float64 ...
    lat      (x, y) float64 ...
    time     datetime64[ns] 2015-01-05T04:00:00
Dimensions without coordinates: x, y
---------------------------
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,394625579
https://github.com/pydata/xarray/issues/2636#issuecomment-450455452,https://api.github.com/repos/pydata/xarray/issues/2636,450455452,MDEyOklzc3VlQ29tbWVudDQ1MDQ1NTQ1Mg==,4179064,2018-12-29T02:07:54Z,2018-12-29T02:07:54Z,NONE,"@zxdawn, I was able to verify that, by adding `decode_times=False` to your code, I get:
```
keys of merge:
odict_keys(['lon', 'lat', 'temperature', 'time']) 

time of merge:
<class 'netCDF4._netCDF4.Variable'>
int64 time(time)
    units: hours since 2015-01-01
unlimited dimensions: 
current shape = (6,)
filling on, default _FillValue of -9223372036854775806 used
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,394625579
https://github.com/pydata/xarray/issues/2636#issuecomment-450400275,https://api.github.com/repos/pydata/xarray/issues/2636,450400275,MDEyOklzc3VlQ29tbWVudDQ1MDQwMDI3NQ==,4179064,2018-12-28T17:54:19Z,2018-12-28T17:54:19Z,NONE,"Depending on your needs, you might be able to get away with calling `open_mfdataset` with `decode_times=False`.  This should leave your `time` coordinate as it is (i.e. integer hours since 2015-01-01) but that will limit the types of operations you can do on the `time` dimension because it will not be converted to some kind of `DateTime` object.  For example, it would be difficult to do time averaging that is aware of months, years, etc.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,394625579