DatetimeIndex is converted to Index upon renaming of the columns
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import pytz

df = pd.DataFrame(data={'metric': [1, 2, 3, 4, 5, 6]},
                  index=pd.DatetimeIndex(['2007-07-13 02:00', '2007-07-13 03:00', '2007-07-13 04:00',
                                          '2007-07-13 05:00', '2007-07-13 06:00', '2007-07-13 07:00'],
                                         freq='H', tz=pytz.utc))
print(f'Index before renaming:\n{df.index}') # Gives DatetimeIndex with timezone UTC and frequency H
df.rename(index=str, columns={'metric': 'metric_renamed'}, inplace=True)
print(f'Index after renaming:\n{df.index}') # Gives Index without timezone and frequency

```
#### Problem description

The class of the dataframe index changes (from DatetimeIndex to Index) and timezone and frequency information is lost, where only the names of the columns should have changed.

***HINT***: 
Caused by _transform_index in pandas/core/internals/managers.py
If the index is not a MultiIndex, an Index is returned


**Note**: Pandas is upgraded to latest version (0.24.2)

#### Expected Output
The index of the dataframe should be left untouched.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.15.0-47-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8
pandas: 0.24.2
pytest: None
pip: 19.0.1
setuptools: 40.6.2
Cython: None
numpy: 1.16.0
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: 7.4.0
sphinx: None
patsy: None
dateutil: 2.7.5
pytz: 2018.9
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.0.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
</details>