unexpected behaviour of DataFrame.duplicated
At least for large datasets `DataFrame.duplicated` returns incorrect results.

Consider MovieLens10M data (this code will automatically download the data from grouplens website):

``` python
import pandas as pd
from requests import get
from StringIO import StringIO
zip_file_url = 'http://files.grouplens.org/datasets/movielens/ml-10m.zip'
zip_response = get(zip_file_url)
zip_contents = StringIO(zip_response.content)

with ZipFile(zip_contents) as zfile:
    zdata = zfile.read('ml-10M100K/ratings.dat')
    delimiter = ';'
    zdata = zdata.replace('::', delimiter) # makes data compatible with pandas c-engine
    mldata = pd.read_csv(StringIO(zdata), sep=delimiter, header=None, engine='c',
                              names=['userid', 'movieid', 'rating', 'timestamp'],
                              usecols=['userid', 'movieid', 'rating'])
```

The data (`mldata` variable) contains no duplicates, which can be verified:

``` python
(mldata.groupby(['userid', 'movieid']).size()>1).any()
False

mldata.set_index(['userid', 'movieid']).index.is_unique
True
```

However,  `DataFrame.duplicated` gives:

``` python
dups = mldata.duplicated(['userid', 'movieid'], keep=False)
print dups.any()
print dups.sum()

True
12127
```

Expected:

``` python
False
0
```

`pd.show_versions()`:
## INSTALLED VERSIONS

commit: None
python: 2.7.10.final.0
python-bits: 64
OS: Windows
OS-release: 8
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.17.0
nose: 1.3.7
pip: 7.1.2
setuptools: 18.3.2
Cython: 0.23.3
numpy: 1.10.0
scipy: 0.16.0
statsmodels: None
IPython: 3.2.1
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.6
blosc: None
bottleneck: 1.0.0
tables: 3.2.0
numexpr: 2.3.1
matplotlib: 1.4.3
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: 1.0.0
xlsxwriter: 0.7.3
lxml: 3.4.4
bs4: 4.3.2
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.0.5
pymysql: None
psycopg2: None
