BUG: dropna('rows') changes index type even when no row was dropped 

after dropna('rows'), the dataframe index changes from RangeIndex to Int64Index even when nothing changed in the dataframe.
reset_index after dropna will fix it, but it should be avoided in the first place.


#### Code Sample, a copy-pastable example

```python
df = pd.DataFrame ({'a':range(1000)})
df.info()

df = df.dropna ('rows')
print ('\nafter dropna\n')
df.info()
```

output:
```
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1000 entries, 0 to 999
Data columns (total 1 columns):
 #   Column  Non-Null Count  Dtype
---  ------  --------------  -----
 0   a       1000 non-null   int64
dtypes: int64(1)
memory usage: 7.9 KB

after dropna

<class 'pandas.core.frame.DataFrame'>
Int64Index: 1000 entries, 0 to 999
Data columns (total 1 columns):
 #   Column  Non-Null Count  Dtype
---  ------  --------------  -----
 0   a       1000 non-null   int64
dtypes: int64(1)
memory usage: 15.6 KB
```

#### Problem description

changing from RangeIndex to Int64Index increases the dataframe size, for no good reason.

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

<details>

commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.8.5.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19041
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_Israel.1252

pandas           : 1.1.3
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.4
setuptools       : 50.3.1.post20201107
Cython           : 0.29.21
pytest           : 6.1.1
hypothesis       : None
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : 1.3.7
lxml.etree       : 4.6.1
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.10.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.8.3
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.5
pandas_gbq       : None
pyarrow          : 0.15.1
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.6.2
sqlalchemy       : 1.3.20
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.51.2
</details>
