BUG: Resulting index from groupby.apply is different depending on whether a RollingGroupby object is created

[mroeschke]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

---

This probably happens because we change the mutated attribues:

pandas/pandas/core/window/rolling.py

Line 532 in a2f42ac

self._groupby.mutated = True

In [1]: frame = DataFrame({"A": [1] * 20 + [2] * 12 + [3] * 8, "B": np.arange(40)})

In [3]: g = frame.groupby("A")

In [4]: g.apply(lambda x: x.rolling(4).sum()).index
Out[4]:
Int64Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
            17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,
            34, 35, 36, 37, 38, 39],
           dtype='int64')

In [5]: r = g.rolling(window=4)

In [6]: g.apply(lambda x: x.rolling(4).sum()).index
Out[6]:
MultiIndex([(1,  0),
            (1,  1),
            (1,  2),
            (1,  3),
            (1,  4),
            (1,  5),
            (1,  6),
            (1,  7),
            (1,  8),
            (1,  9),
            (1, 10),
            (1, 11),
            (1, 12),
            (1, 13),
            (1, 14),
            (1, 15),
            (1, 16),
            (1, 17),
            (1, 18),
            (1, 19),
            (2, 20),
            (2, 21),
            (2, 22),
            (2, 23),
            (2, 24),
            (2, 25),
            (2, 26),
            (2, 27),
            (2, 28),
            (2, 29),
            (2, 30),
            (2, 31),
            (3, 32),
            (3, 33),
            (3, 34),
            (3, 35),
            (3, 36),
            (3, 37),
            (3, 38),
            (3, 39)],
           names=['A', None])