Using DataFrame.rename changes the type of an index
#### Code Sample, a copy-pastable example if possible

```python
df = pd.DataFrame({1:['a','b','c'], 2:['d','e','f']})
print(df.index)
df2 = df.rename(index=str, columns={1:'col1', 2:'col2'})
print(df2.index)

```
#### Problem description

The issue is that, while df has an index type of `RangeIndex` (as expected), df2 has an index type of `Index` in which the original integers have been converted to strings. The same also applies for `MultiIndex`

#### Expected Output

I expect the new dataframe, in which I only renamed a few columns, to have the same index.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 61 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.21.1
pytest: None
pip: 9.0.1
setuptools: 38.2.4
Cython: None
numpy: 1.13.3
scipy: None
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.0
openpyxl: 2.4.2
xlrd: 1.0.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
