Are multiple callable/dict groupers allowed in groupby?
#### Problem description

The docs for ``DataFrame.groupby`` signature start with:
```
by : mapping, function, label, or list of labels
    Used to determine the groups for the groupby.
```
... but the code assumes that lists of mappings or functions can also be passed, and this is also tested, although with limited enthusiasm:
https://github.com/pandas-dev/pandas/blob/0370740034978d3a63d4b8e5e2c96ff54e7e08ba/pandas/tests/groupby/test_grouping.py#L667
... and consistency (apparently that code path _is_ used somewhere else):
https://github.com/pandas-dev/pandas/blob/0370740034978d3a63d4b8e5e2c96ff54e7e08ba/pandas/tests/groupby/test_grouping.py#L732

#### Expected Output

Either we disable/deprecate the possibility of passing lists of mappings, ore we document it.

I guess the latter is the desired outcome, since the code does not support the feature "by chance". Still I wanted to double check with @pandas-dev/pandas-core because
- it is not a killer feature, as it is really easy to pass a single lambda that does the same job of a list of mappings (and more, like applying different mappings to specific levels of the index)
- removing it would allow us to simplify the code quite a bit (e.g. #22257 wouldn't have happened)
- it is probably not much used

#### 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+437.g33d70efb5
pytest: 3.5.0
pip: 9.0.1
setuptools: 39.2.0
Cython: 0.28.4
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.post1634.dev0+ge8120cf6d
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
gcsfs: None


</details>
