BUG: RecursionError using `agg` on a resampled SeriesGroupBy
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

---

When you mix `resample` with `groupby` and try to use the `agg` method to supply multiple functions to either a DataFrameGroupBy or SeriesGroupBy, Python suddently exits without even raising an error.

I first thought I was running into this because I was supplying a single column expecting a DataFrame with multiple columns, but I can confirm this happens to me whether I provide a column (variable `b`) or apply the method to the entire GroupBy (variable `c`):

#### Code Sample

```python
import pandas as pd

a = pd.DataFrame({
    'class': {
        0: 'beta', 1: 'alpha', 2: 'alpha', 3: 'gaga', 4: 'beta', 5: 'gaga',
        6: 'beta', 7: 'gaga', 8: 'beta', 9: 'gaga', 10: 'alpha', 11: 'beta',
        12: 'alpha', 13: 'gaga', 14: 'alpha'},
    'value': {
        0: 69, 1: 33, 2: 40, 3: 2, 4: 36, 5: 40, 6: 48, 7: 84, 8: 77, 9: 22,
        10: 55, 11: 82, 12: 37, 13: 88, 14: 41},
    'date': {
        0: pd.Timestamp('2021-02-28 00:00:00'),
        1: pd.Timestamp('2021-11-30 00:00:00'),
        2: pd.Timestamp('2021-02-28 00:00:00'),
        3: pd.Timestamp('2021-04-30 00:00:00'),
        4: pd.Timestamp('2021-02-28 00:00:00'),
        5: pd.Timestamp('2021-04-30 00:00:00'),
        6: pd.Timestamp('2021-07-31 00:00:00'),
        7: pd.Timestamp('2021-01-31 00:00:00'),
        8: pd.Timestamp('2021-01-31 00:00:00'),
        9: pd.Timestamp('2021-01-31 00:00:00'),
        10: pd.Timestamp('2021-04-30 00:00:00'),
        11: pd.Timestamp('2021-10-31 00:00:00'),
        12: pd.Timestamp('2021-09-30 00:00:00'),
        13: pd.Timestamp('2021-04-30 00:00:00'),
        14: pd.Timestamp('2021-05-31 00:00:00')}})

# This will exit Python
b = a\
    .set_index('date')\
    .groupby('class')\
    .resample('M')['value']\
    .agg(['sum', 'size'])

# Not informing a column will ALSO make Python exit
c = a\
    .set_index('date')\
    .groupby('class')\
    .resample('M')\
    .agg(['sum', 'size'])
```

#### Problem description

I'm not sure if this method is supported for instances of `DatetimeIndexResamplerGroupby` objects, but calling it without arguments is valid, giving:

```
<bound method Resampler.aggregate of <pandas.core.resample.DatetimeIndexResamplerGroupby object at 0x00000163B22B0100>>
```

Also, while the problem arises with either a Series or a DataFrame, given that using `agg` with multiple functions on a `SeriesGroupBy` will correctly create a DataFrame, I would expect the same to happen when resampling with timestamps:

```python
In [1]: a.groupby('class')['value'].agg(['sum', 'size'])
Out[1]:
       sum  size
class
alpha  206     5
beta   312     5
gaga   236     5
```

#### Expected Output

```
                  sum  size
class date
alpha 2021-02-28   40     1
      2021-03-31    0     0
      2021-04-30   55     1
      2021-05-31   41     1
      2021-06-30    0     0
      2021-07-31    0     0
      2021-08-31    0     0
      2021-09-30   37     1
      2021-10-31    0     0
      2021-11-30   33     1
beta  2021-01-31   77     1
      2021-02-28  105     2
      2021-03-31    0     0
      2021-04-30    0     0
      2021-05-31    0     0
      2021-06-30    0     0
      2021-07-31   48     1
      2021-08-31    0     0
      2021-09-30    0     0
      2021-10-31   82     1
gaga  2021-01-31  106     2
      2021-02-28    0     0
      2021-03-31    0     0
      2021-04-30  130     3
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : c7f7443c1bad8262358114d5e88cd9c8a308e8aa
python           : 3.9.2.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : Intel64 Family 6 Model 142 Stepping 9, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : pt_BR.cp1252

pandas           : 1.3.1
numpy            : 1.20.2
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.2.1
setuptools       : 49.2.1
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : 3.5.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.24.1
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.1
numexpr          : None
odfpy            : None
openpyxl         : 3.0.6
pandas_gbq       : None
pyarrow          : None
pyxlsb           : 1.0.8
s3fs             : None
scipy            : 1.7.0
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
