Rolling groupby should not maintain the by column in the resulting DataFrame
When performing a `rolling` operation on a `groupby` object, the index level will be incorrectly maintained in the dataframe.

```
import numpy as np
import pandas as pd

df = pd.DataFrame({'idx_L1': ['Level_1'] * 10 + ['Level_2'] * 10 + ['Level_3'] * 10,  
                   'idx_L2': ([1] * 5 + [2] * 5 + [3] * 5) * 2,  
                   'vals': np.arange(30)})

df.groupby(['idx_L1', 'idx_L2']).rolling(3).sum()
```


This issue has been discussed in #14013.

It has been closed eventhough the bug still exists in v1.01.