Data is mismatched with labels after stack with MultiIndex columns
```python
df = pd.DataFrame([
    ['DIM', 'A', 1, 2, 3, 4],
    ['DIM', 'B', 11, 22, 33, 44],
])
df.columns = ["dim1", "dim2", 'c', 'b', 'a', 'd']
df = df.set_index(["dim1", "dim2"])
df.columns.name = 'metrics'

print(df)
metrics     c   b   a   d
dim1 dim2                
DIM  A      1   2   3   4
     B     11  22  33  44

print(df.unstack('dim2').stack('metrics'))

dim2          A   B
dim1 metrics       
DIM  a        1  11
     b        2  22
     c        3  33
     d        4  44
```
#### Problem description

After stacking data by one level of MultiIndex columns, the output is unexpected. 'metrics' labels are sorted alphabetically, but data is show as is - without being matched with labels.

#### Expected Output

Either option shown below would be fine and expected:

```python
dim2          A   B
dim1 metrics       
DIM  a        3  33
     b        2  22
     c        1  11
     d        4  44

dim2          A   B
dim1 metrics       
DIM  c        1  11
     b        2  22
     a        3  33
     d        4  44
```
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.2.final.0
python-bits: 64
OS: Darwin
OS-release: 17.5.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.21.0
pytest: 3.2.3
pip: 9.0.1
setuptools: 38.2.3
Cython: None
numpy: 1.13.3
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: None
patsy: 0.5.0
dateutil: 2.7.2
pytz: 2018.4
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0b10
sqlalchemy: None
pymysql: 0.7.11.None
psycopg2: 2.7.3.2 (dt dec pq3 ext lo64)
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
</details>
