test_expressions.test_integer* fail badly while building on Debian sid amd64 python3.5
#### Code Sample, a copy-pastable example if possible

Here is a sample (full build log and all 4 failures are at http://neuro.debian.net/_files/_buildlogs/pandas/0.18.1+git25-ga7469cf/pandas_0.18.1+git25-ga7469cf-1_amd64.build )
edit 1: it is all fine with python 2.7

```
======================================================================
FAIL: test_integer_with_zeros (pandas.tests.test_expressions.TestExpressions)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/build/pandas-0.18.1+git25-ga7469cf/debian/tmp/usr/lib/python3/dist-packages/pandas/tests/test_expressions.py", line 244, in test_integer_with_zeros
    assert_frame_equal)
  File "/build/pandas-0.18.1+git25-ga7469cf/debian/tmp/usr/lib/python3/dist-packages/pandas/tests/test_expressions.py", line 100, in run_arithmetic_test
    assert_func(expected, result)
  File "/build/pandas-0.18.1+git25-ga7469cf/debian/tmp/usr/lib/python3/dist-packages/pandas/util/testing.py", line 1313, in assert_frame_equal
    obj='DataFrame.iloc[:, {0}]'.format(i))
  File "/build/pandas-0.18.1+git25-ga7469cf/debian/tmp/usr/lib/python3/dist-packages/pandas/util/testing.py", line 1181, in assert_series_equal
    obj='{0}'.format(obj))
  File "pandas/src/testing.pyx", line 59, in pandas._testing.assert_almost_equal (pandas/src/testing.c:3783)
  File "pandas/src/testing.pyx", line 173, in pandas._testing.assert_almost_equal (pandas/src/testing.c:2987)
  File "/build/pandas-0.18.1+git25-ga7469cf/debian/tmp/usr/lib/python3/dist-packages/pandas/util/testing.py", line 1018, in raise_assert_detail
    raise AssertionError(msg)
AssertionError: DataFrame.iloc[:, 0] are different


DataFrame.iloc[:, 0] values are different (0.57994 %)
[left]:  [-9223372036854775808, -9223372036854775808, 1, 1, 1, -9223372036854775808, 1, 1, -9223372036854775808, 10000000000, 1, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, 1, 1, -9223372036854775808, -9223372036854775808, 3125, 1, -9223372036854775808, 1, 1, -9223372036854775808, 1, -9223372036854775808, 4, 1, 1, 1, -9223372036854775808, 1, 1, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, 1, 1, 1, -9223372036854775808, 1, -9223372036854775808, 387420489, 1, 1, -9223372036854775808, 1, 1, 1, -9223372036854775808, 1, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, 437893890380859392, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, 1, 1, 1, -9223372036854775808, -9223372036854775808, 1, 1, -9223372036854775808, 1, 1, -9223372036854775808, 1, 1, 1, 302875106592253, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, 1, -9223372036854775808, 1, 1, 1, -9223372036854775808, 302875106592253, 1, -9223372036854775808, 1, 1, -9223372036854775808, ...]
[right]: [-9223372036854775808, -9223372036854775808, 1, 1, 1, -9223372036854775808, 1, 1, -9223372036854775808, 10000000000, 1, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, 1, 1, -9223372036854775808, -9223372036854775808, 3125, 1, -9223372036854775808, 1, 1, -9223372036854775808, 1, -9223372036854775808, 4, 1, 1, 1, -9223372036854775808, 1, 1, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, 1, 1, 1, -9223372036854775808, 1, -9223372036854775808, 387420489, 1, 1, -9223372036854775808, 1, 1, 1, -9223372036854775808, 1, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, 437893890380859375, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, 1, 1, 1, -9223372036854775808, -9223372036854775808, 1, 1, -9223372036854775808, 1, 1, -9223372036854775808, 1, 1, 1, 302875106592253, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, 1, -9223372036854775808, 1, 1, 1, -9223372036854775808, 302875106592253, 1, -9223372036854775808, 1, 1, -9223372036854775808, ...]

----------------------------------------------------------------------
Ran 10884 tests in 932.762s

FAILED (SKIP=542, failures=4)
True
WHAT THE
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 2500 entries, 0 to 2499
Data columns (total 2 columns):
int64       2500 non-null int64
category    2500 non-null category
dtypes: category(1), int64(1)
memory usage: 22.1 KB
<class 'pandas.core.frame.DataFrame'>
Int64Index: 275 entries, 0 to 2499
Data columns (total 2 columns):
int64       275 non-null int64
category    275 non-null category
dtypes: category(1), int64(1)
memory usage: 4.6 KB
zounds!
default called array('d', [1.1, 2.2, 3.3])
ext_hook called 123 b'\x9a\x99\x99\x99\x99\x99\xf1?\x9a\x99\x99\x99\x99\x99\x01@ffffff\n@'
debian/rules:100: recipe for target 'python-test3.5' failed
make[1]: *** [python-test3.5] Error 1
make[1]: Leaving directory '/build/pandas-0.18.1+git25-ga7469cf'
debian/rules:48: recipe for target 'binary' failed
make: *** [binary] Error 2
dpkg-buildpackage: error: fakeroot debian/rules binary gave error exit status 2
I: copying local configuration

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

``` shell
> PYTHONPATH=lib.linux-x86_64-3.5 python3.5  -c 'import pandas; pandas.show_versions()'

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.8.0-rc5+
machine: x86_64
processor: 
byteorder: little
LC_ALL: C
LANG: C
LOCALE: None.None

pandas: 0.18.1+git25-ga7469cf
nose: 1.3.7
pip: None
setuptools: 27.1.2
Cython: 0.24.1
numpy: 1.11.1rc1
scipy: 0.18.0
statsmodels: None
xarray: None
IPython: None
sphinx: 1.4.6
patsy: None
dateutil: 2.5.3
pytz: 2015.7
blosc: None
bottleneck: None
tables: 3.2.2
numexpr: 2.6.1
matplotlib: 1.5.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.5.1
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None
```

any clear ideas?
