id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
89268800,MDU6SXNzdWU4OTI2ODgwMA==,438,`xray.open_mfdataset` concatenates also variables without time dimension,3404817,closed,0,,1172685,13,2015-06-18T11:34:53Z,2017-09-19T16:16:58Z,2015-07-15T21:47:11Z,CONTRIBUTOR,,,,"When opening a multi-file dataset with `xray.open_mfdataset`, also some variables are concatenated that do not have a `time` dimension.

My netCDF files contain a lot of those ""static"" variables (e.g. grid spacing etc.). `netCDF4.MFDataset` used to handle those as expected (i.e. did not concatenate them).

Is the different behaviour of `xray.open_mfdataset` intentional or due to a bug?

Note: I am using `decode_times=False`.
## Example

``` python
    with xray.open_dataset(files[0], decode_times=False) as single:
        print single['dz']
```

```
<xray.DataArray 'dz' (z_t: 60)>
array([  1000.        ,   1000.        ,   1000.        ,   1000.        ,
         1000.        ,   1000.        ,   1000.        ,   1000.        ,
         1000.        ,   1000.        ,   1000.        ,   1000.        ,
         1000.        ,   1000.        ,   1000.        ,   1000.        ,
         1019.68078613,   1056.44836426,   1105.99511719,   1167.80700684,
         1242.41333008,   1330.96777344,   1435.14099121,   1557.12585449,
         1699.67956543,   1866.21240234,   2060.90234375,   2288.85205078,
         2556.24707031,   2870.57495117,   3240.8371582 ,   3677.77246094,
         4194.03076172,   4804.22363281,   5524.75439453,   6373.19189453,
         7366.94482422,   8520.89257812,   9843.65820312,  11332.46582031,
        12967.19921875,  14705.34375   ,  16480.70898438,  18209.13476562,
        19802.234375  ,  21185.95703125,  22316.50976562,  23186.49414062,
        23819.44921875,  24257.21679688,  24546.77929688,  24731.01367188,
        24844.328125  ,  24911.97460938,  24951.29101562,  24973.59375   ,
        24985.9609375 ,  24992.67382812,  24996.24414062,  24998.109375  ])
Coordinates:
  * z_t      (z_t) float32 500.0 1500.0 2500.0 3500.0 4500.0 5500.0 6500.0 ...
Attributes:
    long_name: thickness of layer k
    units: centimeters
```

``` python
    with xray.open_mfdataset(files, decode_times=False) as multiple:
        print multiple['dz']
```

```
<xray.DataArray 'dz' (time: 12, z_t: 60)>
dask.array<concatenate-1156, shape=(12, 60), chunks=((1, 1, 1, ..., 1, 1), (60,)), dtype=float64>
Coordinates:
  * z_t      (z_t) float32 500.0 1500.0 2500.0 3500.0 4500.0 5500.0 6500.0 ...
  * time     (time) float64 3.653e+04 3.656e+04 3.659e+04 3.662e+04 ...
Attributes:
    long_name: thickness of layer k
    units: centimeters
```
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89180768,MDU6SXNzdWU4OTE4MDc2OA==,437,bit of code missing in documentation (http://xray.readthedocs.org/en/latest/io.html#combining-multiple-files),2539828,closed,0,,1172685,1,2015-06-18T02:34:08Z,2015-06-22T15:44:59Z,2015-06-22T15:44:59Z,NONE,,,,"in [http://xray.readthedocs.org/en/latest/io.html#combining-multiple-files](http://xray.readthedocs.org/en/latest/io.html#combining-multiple-files) there is a bit of code missing in the function `read_netcdfs`: instead of: 

```
def read_netcdfs(files, dim, transform_func=None):
    def process_one_path(path):
        # use a context manager, to ensure the file gets closed after use
        with xray.open_dataset(path) as ds:
            # transform_func should do some sort of selection or
            # aggregation
            if transform_func is not None:
                ds = transform_func(ds)
            # load all data from the transformed dataset, to ensure we can
            # use it after closing each original file
            ds.load()
            return ds

    paths = sorted(glob(files))
    datasets = [process_one_path(p) for p in paths]
    xray.concat(datasets, dim)
```

it should be: 

```
def read_netcdfs(files, dim, transform_func=None):
    def process_one_path(path):
        # use a context manager, to ensure the file gets closed after use
        with xray.open_dataset(path) as ds:
            # transform_func should do some sort of selection or
            # aggregation
            if transform_func is not None:
                ds = transform_func(ds)
            # load all data from the transformed dataset, to ensure we can
            # use it after closing each original file
            ds.load()
            return ds

    paths = sorted(glob(files))
    datasets = [process_one_path(p) for p in paths]
    dset = xray.concat(datasets, dim)
    return dset
```
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