GroupBy any/all Fails with Duplicate Column Names
#### Code Sample, a copy-pastable example if possible

```python
>>> df = pd.DataFrame([[True, True, True]], columns=['key', 'a', 'a'])
>>> df.groupby('key').any()

ValueError: Buffer has wrong number of dimensions (expected 1, got 2)
```
#### Problem description

This throws because of the below line:

https://github.com/pandas-dev/pandas/blob/0801b8c9090752c1342962aecd03e9a0468adbd4/pandas/core/groupby/groupby.py#L2024

Cython is expecting a one dimensional array of masks, but `self._iterate_slices()` which contains the above statement will provide a multi-dimensional array. Therefore, when the Cython function gets called with `mask` it is a multi-dimensional object and causes the `ValueError`.

I'm not sure if this is the expected behavior of `self._iterate_slices()` or not. If so, there may be implications in other parts of the module.

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

<details>

INSTALLED VERSIONS
------------------
commit: 0801b8c9090752c1342962aecd03e9a0468adbd4
python: 3.6.4.final.0
python-bits: 64
OS: Darwin
OS-release: 17.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.0.dev0+184.g0801b8c90
pytest: 3.4.1
pip: 10.0.1
setuptools: 38.5.1
Cython: 0.27.3
numpy: 1.14.1
scipy: 1.0.0
pyarrow: 0.8.0
xarray: 0.10.0
IPython: 6.2.1
sphinx: 1.7.0
patsy: 0.5.0
dateutil: 2.6.1
pytz: 2018.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: 0.4.0
matplotlib: 2.1.2
openpyxl: 2.5.0
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.5
pymysql: 0.8.0
psycopg2: 2.7.4 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: 0.1.3
fastparquet: 0.1.4
pandas_gbq: 0.4.1
pandas_datareader: None
gcsfs: None

</details>
