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/662#issuecomment-157572531,https://api.github.com/repos/pydata/xarray/issues/662,157572531,MDEyOklzc3VlQ29tbWVudDE1NzU3MjUzMQ==,7799184,2015-11-18T02:00:07Z,2015-11-18T02:00:07Z,CONTRIBUTOR,"Awesome, works here too with netCDF4==1.2.1

Thanks!
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,117478779
https://github.com/pydata/xarray/issues/662#issuecomment-157570185,https://api.github.com/repos/pydata/xarray/issues/662,157570185,MDEyOklzc3VlQ29tbWVudDE1NzU3MDE4NQ==,7799184,2015-11-18T01:43:01Z,2015-11-18T01:43:01Z,CONTRIBUTOR,"Hum... Ok I will try that in another machine too.. The versions are:

pandas==0.17.0
netCDF4==1.1.1
scipy==0.15.1
numpy==1.10.1
xray==0.6.1-15-g5109f4f
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,117478779
https://github.com/pydata/xarray/issues/662#issuecomment-157567446,https://api.github.com/repos/pydata/xarray/issues/662,157567446,MDEyOklzc3VlQ29tbWVudDE1NzU2NzQ0Ng==,7799184,2015-11-18T01:26:01Z,2015-11-18T01:26:01Z,CONTRIBUTOR,"@shoyer I'm sending you by email (was not able to attach here) a stripped version of one of the files I was using. The code below should reproduce the issue:

```
import xray
dset = xray.open_dataset('hycom_example.nc', decode_times=False)
ncvar = 'water_u'
dset_sliced = xray.Dataset()
slice_dict = {u'lat': [-30], u'lon': [0]}
dset_sliced[ncvar] = dset[ncvar].sel(method='nearest', **slice_dict)
dset_sliced.to_netcdf()
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,117478779
https://github.com/pydata/xarray/issues/662#issuecomment-157564974,https://api.github.com/repos/pydata/xarray/issues/662,157564974,MDEyOklzc3VlQ29tbWVudDE1NzU2NDk3NA==,7799184,2015-11-18T01:09:00Z,2015-11-18T01:09:00Z,CONTRIBUTOR,"@maximilianr I have managed to reproduce this with a different file with different number of dimensions (time, latitude, longitude). So I believe the below example should give same problem if you run on some other file and change the variable / dimension names accordingly:

```
ncvar = 'hs'
dset_sliced1 = xray.Dataset()
dset_sliced2 = xray.Dataset()
dset = xray.open_dataset(filename, decode_times=False)
slice_dict1 = {u'latitude': [-30], u'longitude': [0], u'time': [2.83996800e+08, 2.84007600e+08]}
dset_sliced1[ncvar] = dset[ncvar].sel(method='nearest', **slice_dict1)
slice_dict2 = {u'latitude': [-30], u'longitude': [0], u'time': [2.84018400e+08, 2.84029200e+08]}
dset_sliced2[ncvar] = dset[ncvar].sel(method='nearest', **slice_dict2)

dset_sliced1.to_netcdf('test.nc')  # This fails
xray.concat([dset_sliced1, dset_sliced2], dim='time') # This also fails, same error

Traceback:
----> 1 xray.concat([dset_sliced1, dset_sliced2], dim='time') # This also fails

/source/xray/xray/core/combine.pyc in concat(objs, dim, data_vars, coords, compat, positions, indexers, mode, concat_over)
    113         raise TypeError('can only concatenate xray Dataset and DataArray '
    114                         'objects')
--> 115     return f(objs, dim, data_vars, coords, compat, positions)
    116 
    117 

/source/xray/xray/core/combine.pyc in _dataset_concat(datasets, dim, data_vars, coords, compat, positions)
    265     for k in concat_over:
    266         vars = ensure_common_dims([ds.variables[k] for ds in datasets])
--> 267         combined = Variable.concat(vars, dim, positions)
    268         insert_result_variable(k, combined)
    269 

/source/xray/xray/core/variable.pyc in concat(cls, variables, dim, positions, shortcut)
    711                 utils.remove_incompatible_items(attrs, var.attrs)
    712 
--> 713         return cls(dims, data, attrs)
    714 
    715     def _data_equals(self, other):

/source/xray/xray/core/variable.pyc in __init__(self, dims, data, attrs, encoding, fastpath)
    194         """"""
    195         self._data = _as_compatible_data(data, fastpath=fastpath)
--> 196         self._dims = self._parse_dimensions(dims)
    197         self._attrs = None
    198         self._encoding = None

/source/xray/xray/core/variable.pyc in _parse_dimensions(self, dims)
    302             raise ValueError('dimensions %s must have the same length as the '
    303                              'number of data dimensions, ndim=%s'
--> 304                              % (dims, self.ndim))
    305         return dims
    306 

ValueError: dimensions (u'time', u'latitude', u'longitude') must have the same length as the number of data dimensions, ndim=2
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,117478779
https://github.com/pydata/xarray/issues/662#issuecomment-157559691,https://api.github.com/repos/pydata/xarray/issues/662,157559691,MDEyOklzc3VlQ29tbWVudDE1NzU1OTY5MQ==,7799184,2015-11-18T00:43:32Z,2015-11-18T00:43:32Z,CONTRIBUTOR,"I was concatenating them as:

```
dset_concat = xray.concat([ds1, ds2], dim='time')
```

Trying to dump any of them as netcdf:

```
ds1.to_netcdf('test.nc')
```

would also yield the same problem
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,117478779