matching False to 0 in .ix
#### To reproduce follow steps below

``` python
In [226]: df_test = pd.DataFrame(np.random.randn(5,5), columns=list('ABCDE'))

In [227]: df_test
Out[227]: 
          A         B         C         D         E
0  0.609775  0.205708 -0.015081  2.096414  0.121245
1  1.223234 -1.299398  1.238649  0.216846 -0.789828
2  0.446873  1.734404 -0.675568 -1.203400  0.053905
3  0.286693 -0.080294 -0.115739 -0.195039  0.400201
4  0.519230  1.939370 -0.424466  0.102137 -0.724420

In [228]: df_test.iloc[0,1] = False

In [229]: df_test.iloc[1,1] = '0'

In [230]: df_test.iloc[2,1] = 0

In [231]: df_test.iloc[3,1] = '2'

In [232]: df_test.B == False
Out[232]: 
0     True
1    False
2     True
3    False
4    False
Name: B, dtype: bool
```
#### Expected Output

``` python
>>> df_test.B == False
0     True
1    False
2    False
3    False
4    False
Name: B, dtype: bool
```
#### output of `pd.show_versions()`

``` python
pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Darwin
OS-release: 15.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: el_GR.UTF-8

pandas: 0.18.0
nose: 1.3.7
pip: 8.1.1
setuptools: 20.3
Cython: 0.23.4
numpy: 1.10.4
scipy: 0.17.0
statsmodels: 0.6.1
xarray: None
IPython: 4.1.2
sphinx: 1.3.5
patsy: 0.4.0
dateutil: 2.5.1
pytz: 2016.2
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.5
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.6.0
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.39.0
```
