Groupby iteration fails when one of the key's values is None
#### Code Sample

```python
import pandas as pd

df = pd.DataFrame({
    'a': [1, 1, 2, 3],
    'b': [None, 1, 2, 3],
    'c': [1,2,3,4],
})

grouped = df.groupby(('a', 'b'))
print('Number of groups:', len(grouped))
# Number of groups: 4

num_iterations = 0
for _ in grouped:
    num_iterations += 1

print('Number of groups iterated over:', num_iterations) 
# Number of groups iterated over: 3
```

#### Problem description

Presently, when a `GroupBy` object is iterated over, any group where one of the columns grouped by is `None` is skipped.

This is a problem because when iterating over groups, we expect to iterate over all groups. 

It is also a problem because it is not sensible to say the length of an iterable is `x` when iterating over it only performs some `y < x` number of iterations.

#### Expected Output

I'd expect iterating over a `GroupBy` object to iterate over all groups, regardless of the value in the key columns.

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

<details>
INSTALLED VERSIONS

------------------

commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 2.6.32-504.12.2.el6.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 9.0.1
setuptools: 23.0.0
Cython: 0.24
numpy: 1.11.1
scipy: 0.17.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.4.1
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: 1.1.0
tables: 3.3.0
numexpr: 2.6.0
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.2
lxml: 3.6.0
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: 2.6.2 (dt dec pq3 ext)
jinja2: 2.8
boto: 2.40.0
pandas_datareader: None
</details>
