Grouper using frequency has inconsistent behavior inside and outside a list
#### Code Sample

```python

>>> df.groupby(pd.Grouper(freq='H')).agg({'value': 'mean'})
            timestamp       delta_t
2016-06-07 00:00:00  2.729111e+11
2016-06-07 01:00:00           NaN
2016-06-07 02:00:00           NaN
2016-06-07 03:00:00           NaN
2016-06-07 04:00:00           NaN
...

>>> df.groupby([pd.Grouper(freq='H')]).agg({'value': 'mean'})
   timestamp       delta_t
2016-06-07  2.729111e+11
2016-07-07  2.509444e+11
2016-07-13  2.775778e+11
2016-07-15  2.490556e+11
2016-07-16  2.676190e+11
```
#### Problem description

This is an inconsistent behavior, and there is no mention to this on groupby or Grouper documentation. 

#### Expected Output

```python
>>> df.groupby([pd.Grouper(freq='H')]).agg({'value': 'mean'})
   timestamp       delta_t
2016-06-07 00:00:00  2.729111e+11
2016-06-07 01:00:00           NaN
2016-06-07 02:00:00           NaN
2016-06-07 03:00:00           NaN
2016-06-07 04:00:00           NaN
```
#### Output of ``pd.show_versions()``

<details>
pandas: 0.20.2
pytest: 3.1.1
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: 0.9.6
IPython: 6.1.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.8.0
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.10
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>
