Min negative integers with a NULL value implies inconsistency after the cast to float64
For negative integer values close to - 2^63, the value is dectected as NaN after cast
Pandas version : 0.17.0

``` python
import pandas
import StringIO
df1 = pandas.read_csv(StringIO.StringIO("0\t-9223372036854775295\n0\t0\n0\t9223372036854775807\n0\t\n"),names=["foo", "bar"], sep="\t")
print df1

df2 = pandas.read_csv(StringIO.StringIO("0\t-9223372036854775296\n0\t0\n0\t9223372036854775807\n0\t\n"),names=["foo", "bar"], sep="\t")
print df2
```

output : 

```
   foo           bar
0    0           NaN
1    0  0.000000e+00
2    0  9.223372e+18
3    0           NaN
float64

   foo           bar
0    0 -9.223372e+18
1    0  0.000000e+00
2    0  9.223372e+18
3    0  NaN
float64
```

```
pandas.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Linux
OS-release: 3.19.0-30-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: fr_FR.UTF-8

pandas: 0.17.0
nose: 1.3.7
pip: 1.5.4
setuptools: 3.3
Cython: None
numpy: 1.10.1
scipy: None
statsmodels: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.4.2
pytz: 2015.7
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999
httplib2: 0.8
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None

```
