Grouped result can not divide 
#### Code Sample, a copy-pastable example if possible

```python
In [2]: group = df.groupby(pd.Grouper(freq='D', key="datetime_create"))

In [3]: day_count = group[["count"]].sum()

In [4]: total_fee = group[["fee_total", "fee_real"]].sum()

In [5]: total_fee
Out[5]:
                           fee_total  fee_real
datetime_create
2017-09-15 00:00:00+08:00       4272      3975
2017-09-16 00:00:00+08:00       4272      3987
2017-09-17 00:00:00+08:00      10680      9633
2017-09-18 00:00:00+08:00       5340      5120
2017-09-19 00:00:00+08:00       2492      2317
2017-09-20 00:00:00+08:00       5340      5152
2017-09-21 00:00:00+08:00       3560      3239
.....


In [6]: total_fee.index
Out[6]:
DatetimeIndex(['2017-09-15 00:00:00+08:00', '2017-09-16 00:00:00+08:00',
               '2017-09-17 00:00:00+08:00', '2017-09-18 00:00:00+08:00',
               '2017-09-19 00:00:00+08:00', '2017-09-20 00:00:00+08:00',
               '2017-09-21 00:00:00+08:00', '2017-09-22 00:00:00+08:00',
               '2017-09-23 00:00:00+08:00', '2017-09-24 00:00:00+08:00',
               ...
               '2018-06-30 00:00:00+08:00', '2018-07-01 00:00:00+08:00',
               '2018-07-02 00:00:00+08:00', '2018-07-03 00:00:00+08:00',
               '2018-07-04 00:00:00+08:00', '2018-07-05 00:00:00+08:00',
               '2018-07-06 00:00:00+08:00', '2018-07-07 00:00:00+08:00',
               '2018-07-08 00:00:00+08:00', '2018-07-09 00:00:00+08:00'],
              dtype='datetime64[ns, Asia/Shanghai]', name='datetime_create', length=298, freq='D')

In [7]: total_fee.index == day_count.index
Out[7]:
array([ True,  True,  True,  True,  True,  True,  True,  True,  True,
        True,  True,  True,  True,  True,  True,  True,  True,  True,
        True,  True,  True,  True,  True,  True,  True,  True,  True,
        True,  True,  True,  True,  True,  True,  True,  True,  True,
        True,  True,  True,  True,  True,  True,  True,  True,  True,
        True,  True,  True,  True,  True,  True,  True,  True,  True,
       .....

In [8]: total_fee /  day_count
Out[8]:
                           count  fee_real  fee_total
datetime_create
2017-09-15 00:00:00+08:00    NaN       NaN        NaN
2017-09-16 00:00:00+08:00    NaN       NaN        NaN
2017-09-17 00:00:00+08:00    NaN       NaN        NaN
2017-09-18 00:00:00+08:00    NaN       NaN        NaN
2017-09-19 00:00:00+08:00    NaN       NaN        NaN
2017-09-20 00:00:00+08:00    NaN       NaN        NaN
2017-09-21 00:00:00+08:00    NaN       NaN        NaN
2017-09-22 00:00:00+08:00    NaN       NaN        NaN
2017-09-23 00:00:00+08:00    NaN       NaN        NaN
2017-09-24 00:00:00+08:00    NaN       NaN        NaN
........
```
#### Problem description

What I tried  :  

1 .  convert datetime index to date. 

    ```
    group = df.groupby(pd.Grouper(freq='D', key="datetime_create"))
    day_count = group[["count"]].sum()
    total_fee = group[["fee_total", "fee_real"]].sum()

    day_count .index = day_count.index.date
    total_fee.index = total_fee.index.date
    day_fee_avg =  total_fee / day_count
    ```
    result same.

2. `group[["fee_total"]].sum() / day_count`  result same
3. remove timezone by `.dt.tz_localize(None)` , result same.



#### Expected Output

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.0
pytest: 3.5.1
pip: 10.0.1
setuptools: 39.1.0
Cython: 0.28.2
numpy: 1.14.3
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.4.0
sphinx: 1.7.4
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: 3.4.3
numexpr: 2.6.5
feather: None
matplotlib: 2.2.2
openpyxl: 2.5.3
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.4
lxml: 4.2.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.7
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None


</details>
