.ne fails with abiguous message if comparing a list of columns containing column name 'dtype'
#### Code Sample, a copy-pastable example if possible

```python
df = pd.DataFrame([[0,1,2,'aa'],[0,1,2,'aa'],[0,1,5,'bb'],[0,1,5,'bb'],[0,1,5,'bb'],['cc',4,4,4]], columns=['a','b','c','dtype'])

df.loc[:, ['a', 'dtype']].ne(df.loc[:, ['a', 'dtype']])

In [10]: df
Out[10]: 
    a  b  c dtype
0   0  1  2    aa
1   0  1  2    aa
2   0  1  5    bb
3   0  1  5    bb
4   0  1  5    bb
5  cc  4  4     4

```
#### Problem description
Instead of the expected output, I receive:
```python
In [8]: df.loc[:, ['a','dtype']].ne(df.loc[:, ['a', 'dtype']])
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-8-a0710f18822f> in <module>()
----> 1 df.loc[:, ['a','dtype']].ne(df.loc[:, ['a', 'dtype']])

/home/blistein/env/aan/local/lib/python2.7/site-packages/pandas/core/ops.pyc in f(self, other, axis, level)
   1588                 self, other = self.align(other, 'outer',
   1589                                          level=level, copy=False)
-> 1590             return self._compare_frame(other, na_op, str_rep)
   1591 
   1592         elif isinstance(other, ABCSeries):

/home/blistein/env/aan/local/lib/python2.7/site-packages/pandas/core/frame.pyc in _compare_frame(self, other, func, str_rep)
   4790                 return {col: func(a[col], b[col]) for col in a.columns}
   4791 
-> 4792             new_data = expressions.evaluate(_compare, str_rep, self, other)
   4793             return self._constructor(data=new_data, index=self.index,
   4794                                      columns=self.columns, copy=False)

/home/blistein/env/aan/local/lib/python2.7/site-packages/pandas/core/computation/expressions.pyc in evaluate(op, op_str, a, b, use_numexpr, **eval_kwargs)
    201         """
    202 
--> 203     use_numexpr = use_numexpr and _bool_arith_check(op_str, a, b)
    204     if use_numexpr:
    205         return _evaluate(op, op_str, a, b, **eval_kwargs)

/home/blistein/env/aan/local/lib/python2.7/site-packages/pandas/core/computation/expressions.pyc in _bool_arith_check(op_str, a, b, not_allowed, unsupported)
    173         unsupported = {'+': '|', '*': '&', '-': '^'}
    174 
--> 175     if _has_bool_dtype(a) and _has_bool_dtype(b):
    176         if op_str in unsupported:
    177             warnings.warn("evaluating in Python space because the {op!r} "

/home/blistein/env/aan/local/lib/python2.7/site-packages/pandas/core/generic.pyc in __nonzero__(self)
   1574         raise ValueError("The truth value of a {0} is ambiguous. "
   1575                          "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
-> 1576                          .format(self.__class__.__name__))
   1577 
   1578     __bool__ = __nonzero__

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
```
#### Expected Output
```
       a      c
0  False  False
1  False  False
2  False  False
3  False  False
4  False  False
5  False  False
```
Alternative: a descriptive Error Message, telling me I can't use 'dtype' as column name.

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 4.15.0-29-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.utf8
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.23.4
pytest: 2.8.7
pip: 18.0
setuptools: 40.0.0
Cython: None
numpy: 1.11.0
scipy: 0.17.0
pyarrow: None
xarray: None
IPython: 5.5.0
sphinx: None
patsy: 0.4.1
dateutil: 2.7.3
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: None
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>
