BUG: resample nunique calculation incorrect

[agtsai-i]

Summary

Passing 'nunique' to resample produces incorrect output. However, passing pd.Series.nunique works.

Code Sample, a copy-pastable example if possible

import pandas as pd
from pandas import Timestamp

time = [Timestamp('2016-06-28 09:35:35'), Timestamp('2016-06-28 16:09:30'), Timestamp('2016-06-28 16:46:28')]
data = ['1', '2', '3']
test = pd.DataFrame({'time':time, 'data':data})
display(test.set_index('time').resample('H').apply({'data':'nunique'}))
display(test.set_index('time').resample('H').apply({'data':pd.Series.nunique}))

Expected Output

(INCORRECT, in bold)
2016-06-28 09:00:00 1
2016-06-28 10:00:00 0
2016-06-28 11:00:00 0
2016-06-28 12:00:00 0
2016-06-28 13:00:00 0
2016-06-28 14:00:00 0
2016-06-28 15:00:00 0
2016-06-28 16:00:00 1

(CORRECT, in bold)
2016-06-28 09:00:00 1
2016-06-28 10:00:00 0
2016-06-28 11:00:00 0
2016-06-28 12:00:00 0
2016-06-28 13:00:00 0
2016-06-28 14:00:00 0
2016-06-28 15:00:00 0
2016-06-28 16:00:00 2

output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 2.7.10.final.0
python-bits: 64
OS: Linux
OS-release: 4.1.10-17.31.amzn1.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 20.3.1
Cython: 0.24
numpy: 1.11.1
scipy: 0.17.1
statsmodels: 0.6.1
xarray: None
IPython: 4.1.2
sphinx: None
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: None
tables: None
numexpr: 2.6.0
matplotlib: 1.5.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: 2.6.1 (dt dec pq3 ext)
jinja2: 2.8
boto: 2.40.0
pandas_datareader: None

[jreback]

looks like the same as #13453

[agtsai-i]

Wasn't quite sure, so I submitted anyways