pandas.core.groupby.GroupBy.apply fails
#### Code Sample:
```python
>>> df = pd.DataFrame({'A': 'a a b'.split(), 'B': [1,2,3], 'C': [4,6, 5]})
>>> g = df.groupby('A')
>>> g.apply(lambda x: x / x.sum())
```
#### Problem description
Applying a function to a grouped data frame fails. The code above is the example code from the official pandas documentation: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.core.groupby.GroupBy.apply.html

Output to the above code:
```python
/usr/local/lib/python2.7/dist-packages/pandas/core/computation/check.py:17: UserWarning: The installed version of numexpr 2.4.3 is not supported in pandas and will be not be used
The minimum supported version is 2.4.6

  ver=ver, min_ver=_MIN_NUMEXPR_VERSION), UserWarning)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/groupby.py", line 805, in apply
    return self._python_apply_general(f)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/groupby.py", line 809, in _python_apply_general
    self.axis)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/groupby.py", line 1969, in apply
    res = f(group)
  File "<stdin>", line 1, in <lambda>
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/ops.py", line 1262, in f
    return self._combine_series(other, na_op, fill_value, axis, level)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 3944, in _combine_series
    try_cast=try_cast)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 3958, in _combine_series_infer
    try_cast=try_cast)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 3981, in _combine_match_columns
    try_cast=try_cast)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/internals.py", line 3435, in eval
    return self.apply('eval', **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/internals.py", line 3329, in apply
    applied = getattr(b, f)(**kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/internals.py", line 1377, in eval
    result = get_result(other)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/internals.py", line 1346, in get_result
    result = func(values, other)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/ops.py", line 1216, in na_op
    yrav.fill(yrav.item())
ValueError: can only convert an array of size 1 to a Python scalar
```
The error can be 'fixed' by applying another command to the grouped object first:
```python
>>> g.sum()
   B   C
A       
a  3  10
b  3   5

>>> g.apply(lambda x: x / x.sum())
          B    C
0  0.333333  0.4
1  0.666667  0.6
2  1.000000  1.0
```

#### Expected Output
```python
>>> g.apply(lambda x: x / x.sum())
          B    C
0  0.333333  0.4
1  0.666667  0.6
2  1.000000  1.0
```
#### Output of ``pd.show_versions()``

<details>
>>> pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-122-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.utf8
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.22.0
pytest: 2.8.7
pip: 9.0.1
setuptools: 20.7.0
Cython: 0.23.4
numpy: 1.11.0
scipy: 0.17.0
pyarrow: None
xarray: None
IPython: 5.5.0
sphinx: None
patsy: 0.4.1
dateutil: 2.4.2
pytz: 2014.10
blosc: None
bottleneck: None
tables: 3.2.2
numexpr: 2.4.3
feather: None
matplotlib: 1.5.1
openpyxl: 2.3.0
xlrd: 0.9.4
xlwt: 0.7.5
xlsxwriter: None
lxml: 3.5.0
bs4: None
html5lib: 1.0.1
sqlalchemy: 1.0.11
pymysql: 0.7.2.None
psycopg2: 2.6.1 (dt dec mx pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
>>> 

</details>
