BUG: Bins are unexpected for qcut when the edges are duplicated
#### Code Sample, a copy-pastable example if possible

```python
#
import pandas as pd
import numpy as np
values = np.empty(shape=10)
values[:3] = 0
values[3:5] = 1
values[5:7] = 2
values[7:9] = 3
values[9:] = 4
pd.qcut(values,5,duplicates='drop')

```
#### Problem description

The first bin contains both 0 and 1. Since I'm looking to put 20% in each bin I would expect to have the first bin to contain only 0's (for 30% of the data) rather than 0's and 1's (for 50% of the data).

#### Expected Output

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

<details>
#
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en_US
LOCALE: None.None

pandas: 0.20.1
pytest: 2.8.5
pip: 8.1.1
setuptools: 21.2.1
Cython: 0.23.4
numpy: 1.11.0
scipy: 0.17.0
xarray: None
IPython: 4.0.3
sphinx: 1.3.5
patsy: 0.4.1
dateutil: 2.4.2
pytz: 2015.7
blosc: None
bottleneck: 1.2.0
tables: 3.2.2
numexpr: 2.5.2
feather: None
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.5.0
bs4: 4.4.1
html5lib: None
sqlalchemy: 1.0.11
pymysql: None
psycopg2: None
jinja2: 2.8
s3fs: None
pandas_gbq: None
pandas_datareader: 0.2.1
</details>
