DataFrame.[key] and .loc[:, key] with non-unique columns returns frame if (and only if) columns are MultiIndex
#### Code Sample, a copy-pastable example if possible

```python
In [2]: flat = pd.DataFrame(-1, index=range(2), columns=[0, 1, 1, 2, 3, 4])

In [3]: flat[0].__class__
Out[3]: pandas.core.series.Series

In [4]: flat.loc[:, 0].__class__
Out[4]: pandas.core.series.Series

In [5]: multi = pd.DataFrame(-1, index=range(2), columns=pd.MultiIndex.from_product([range(2), 
   ...: [0,1,1]]))

In [6]: multi[(0, 0)].__class__
Out[6]: pandas.core.frame.DataFrame

In [7]: multi.loc[:, (0, 0)].__class__
Out[7]: pandas.core.frame.DataFrame

In [8]: unique = pd.DataFrame(-1, index=range(2), columns=pd.MultiIndex.from_product([range(2),
   ...:  range(3)]))

In [9]: unique[(0, 0)].__class__
Out[9]: pandas.core.series.Series

In [10]: unique.loc[:, (0, 0)].__class__
Out[10]: pandas.core.series.Series
```


#### Problem description

It makes a lot of sense to not lower dimensionality when an axis is non-unique (see #9519 ), but as of now the general rule (on ``Series``, and on ``DataFrame`` with flat ``columns``) is "if the specific label is not repeated, lower dimensionality", so the fact that ``MultiIndex`` is behaving differently is problematic.

This said, I'm not claiming this is worth fixing: my favourite solution - although more disruptive - is to fix #9519.

#### Expected Output

Ideally, always ``DataFrame`` (except for ``unique``), but as of now, always ``Series``.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-6-amd64
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8

pandas: 0.24.0.dev0+51.g4274b840e
pytest: 3.5.0
pip: 9.0.1
setuptools: 39.2.0
Cython: 0.25.2
numpy: 1.14.3
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.5.6
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.0dev
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.2.2.post1153+gff6786446
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 1.3.0
xlsxwriter: 0.9.6
lxml: 4.1.1
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.2.1


</details>
