pandas.Series.dt.round inconsistent with freq = 'H'
#### Code Sample

```python
>>> df = pd.DataFrame(data=[pd.Timestamp('2017-10-11 07:30:00'),
                        pd.Timestamp('2017-10-11 08:30:00'),
                        pd.Timestamp('2017-10-11 09:30:00')],
                  index=[0,1,2],
                  columns=['Date_time'])

>>> df.Date_time

>>> 0   2017-10-11 07:30:00
       1   2017-10-11 08:30:00
       2   2017-10-11 09:30:00
      Name: Date_time, dtype: datetime64[ns]

>>> df.Date_time.dt.round('H')

>>> 0   2017-10-11 08:00:00
       1   2017-10-11 08:00:00
       2   2017-10-11 10:00:00
       Name: Date_time, dtype: datetime64[ns]
```
#### Problem description

07:30 and 09:30 are rounded **up** to the hour. 08:30 is rounded **down** to the hour. I find this inconsistent. I think my expected output below is more consistent, where 08:30 is rounded **up** to 09:00. 

#### Expected Output
```python
>>> df.Date_time.dt.round('H')

>>> 0   2017-10-11 08:00:00
       1   2017-10-11 09:00:00
       2   2017-10-11 10:00:00
       Name: Date_time, dtype: datetime64[ns]
```        
#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.7.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-141-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_AU.UTF-8
LOCALE: en_AU.UTF-8

pandas: 0.23.4
pytest: 4.0.2
pip: 18.1
setuptools: 40.6.3
Cython: 0.29.2
numpy: 1.15.4
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 7.2.0
sphinx: 1.8.2
patsy: 0.5.1
dateutil: 2.7.5
pytz: 2018.7
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 3.0.2
openpyxl: 2.5.12
xlrd: 1.2.0
xlwt: 1.3.0
xlsxwriter: 1.1.2
lxml: 4.2.5
bs4: 4.6.3
html5lib: 1.0.1
sqlalchemy: 1.2.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
</details>
