`groupby` in combination with `rolling` provides unintuitve errors

I think the minimal example here is

```

In [28]: df = pd.DataFrame({"A": range(12)})

In [29]: df.rolling(3, win_type='gaussian').mean()
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-29-82bac00d4424> in <module>
----> 1 df.rolling(3, win_type='gaussian').mean()

~/sandbox/pandas/pandas/core/window.py in mean(self, *args, **kwargs)
    827     def mean(self, *args, **kwargs):
    828         nv.validate_window_func("mean", args, kwargs)
--> 829         return self._apply_window(mean=True, **kwargs)
    830
    831

~/sandbox/pandas/pandas/core/window.py in _apply_window(self, mean, **kwargs)
    711
    712         """
--> 713         window = self._prep_window(**kwargs)
    714         center = self.center
    715

~/sandbox/pandas/pandas/core/window.py in _prep_window(self, **kwargs)
    693                 return all_args
    694
--> 695             win_type = _validate_win_type(self.win_type, kwargs)
    696             # GH #15662. `False` makes symmetric window, rather than periodic.
    697             return sig.get_window(win_type, window, False).astype(float)

~/sandbox/pandas/pandas/core/window.py in _validate_win_type(win_type, kwargs)
    674
    675                 if win_type in arg_map:
--> 676                     win_args = _pop_args(win_type, arg_map[win_type], kwargs)
    677                     if win_type == "exponential":
    678                         # exponential window requires the first arg (center)

~/sandbox/pandas/pandas/core/window.py in _pop_args(win_type, arg_names, kwargs)
    689                 for n in arg_names:
    690                     if n not in kwargs:
--> 691                         raise ValueError(msg % n)
    692                     all_args.append(kwargs.pop(n))
    693                 return all_args

ValueError: gaussian window requires std


```

Can you confirm @bgruening?

Apparently, passing `std` is required.

```python

In [40]: df.rolling(3, win_type='gaussian').mean(std=1)
Out[40]:
       A
0    NaN
1    NaN
2    1.0
3    2.0
4    3.0
5    4.0
6    5.0
7    6.0
8    7.0
9    8.0
10   9.0
11  10.0

```

An example in the docs, and / or a better error message would be nice. https://github.com/pandas-dev/pandas/blob/32b47102aa95da5a68ef9939c0e9429269ced016/pandas/core/window/rolling.py#L569

*original example below*

---

#### Code Sample, a copy-pastable example if possible

```python

import pandas as pd

iris = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv')
# this one works, but should not imho
iris['gaussian'] = iris.groupby('species')['petal_width'].rolling(3, win_type='gaussian', center=False).mean().reset_index(drop=True)

# this one raises an `ValueError: gaussian window requires std`
iris['gaussian'] = iris['petal_width'].rolling(3, win_type='gaussian', center=False).mean().reset_index(drop=True)



```
#### Problem description

According to https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rolling.html the `win_type='gaussian'` needs a `std`. The above example without the groupby errors if no `std` is given and this is the expected behaviour. However, the first example with the `groupby` does not error. I'm not even sure what happens in the first case.

#### Expected Output

The groupby example should give an error.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Linux
OS-release: 5.0.0-15-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: de_DE.UTF-8
LOCALE: de_DE.UTF-8

pandas: 0.24.2
pytest: None
pip: 19.1
setuptools: 41.0.1
Cython: None
numpy: 1.16.3
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: 7.5.0
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
