BUG: not possible to 'cumsum' Timedelta with named aggregation
- [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.

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

---

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

```python
import pandas as pd
import numpy as np
import random

# Dataset
ts = pd.DatetimeIndex([pd.Timestamp('2021/01/01 00:30'),
                       pd.Timestamp('2021/01/01 00:45'),
                       pd.Timestamp('2021/01/01 02:00'),
                       pd.Timestamp('2021/01/01 03:50'),
                       pd.Timestamp('2021/01/01 05:00')])
length = len(ts)
random.seed(1)
value = random.sample(range(1, length+1), length)
df = pd.DataFrame({'value': value, 'ts': ts})
df['td'] = df['ts'] - df['ts'].shift(1, fill_value=ts[0]-pd.Timedelta('1h'))
df['amount'] = df['value']*10
df.loc[:2,'grps'] = 'a'
df.loc[2:,'grps'] = 'b'
```
```python
In [16]: df
Out[16]: 
   value                  ts              td  amount grps
0      2 2021-01-01 00:30:00 0 days 01:00:00      20    a
1      1 2021-01-01 00:45:00 0 days 00:15:00      10    a
2      5 2021-01-01 02:00:00 0 days 01:15:00      50    b
3      4 2021-01-01 03:50:00 0 days 01:50:00      40    b
4      3 2021-01-01 05:00:00 0 days 01:10:00      30    b
```
```python
# cumsum and Timedelta work when used through pd.Series
df['td'].cumsum()

# cumsum and Timedelta do not work when used in groupby with named aggregation
agg_rules = {'td':('td', 'cumsum')}
res = df.groupby('grps').agg(**agg_rules)
```
Error message that is returned
```python
res = df.groupby('grps').agg(**agg_rules)
Traceback (most recent call last):

  File "<ipython-input-14-c0f4606d675a>", line 2, in <module>
    res = df.groupby('grps').agg(**agg_rules)

  File "/home/pierre/anaconda3/lib/python3.8/site-packages/pandas/core/groupby/generic.py", line 945, in aggregate
    result, how = aggregate(self, func, *args, **kwargs)

  File "/home/pierre/anaconda3/lib/python3.8/site-packages/pandas/core/aggregation.py", line 582, in aggregate
    return agg_dict_like(obj, arg, _axis), True

  File "/home/pierre/anaconda3/lib/python3.8/site-packages/pandas/core/aggregation.py", line 768, in agg_dict_like
    results = {key: obj._gotitem(key, ndim=1).agg(how) for key, how in arg.items()}

  File "/home/pierre/anaconda3/lib/python3.8/site-packages/pandas/core/aggregation.py", line 768, in <dictcomp>
    results = {key: obj._gotitem(key, ndim=1).agg(how) for key, how in arg.items()}

  File "/home/pierre/anaconda3/lib/python3.8/site-packages/pandas/core/groupby/generic.py", line 247, in aggregate
    ret = self._aggregate_multiple_funcs(func)

  File "/home/pierre/anaconda3/lib/python3.8/site-packages/pandas/core/groupby/generic.py", line 315, in _aggregate_multiple_funcs
    results[base.OutputKey(label=name, position=idx)] = obj.aggregate(func)

  File "/home/pierre/anaconda3/lib/python3.8/site-packages/pandas/core/groupby/generic.py", line 241, in aggregate
    return getattr(self, func)(*args, **kwargs)

  File "/home/pierre/anaconda3/lib/python3.8/site-packages/pandas/core/groupby/groupby.py", line 2497, in cumsum
    return self._cython_transform("cumsum", **kwargs)

  File "/home/pierre/anaconda3/lib/python3.8/site-packages/pandas/core/groupby/groupby.py", line 996, in _cython_transform
    raise DataError("No numeric types to aggregate")

DataError: No numeric types to aggregate
```


#### Problem description

Cumsum works with Timedelta in some workflows, but for some other workflows (groupby, named aggregation) it does not.

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

<details>

INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.8.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.8.0-53-generic
Version          : #60~20.04.1-Ubuntu SMP Thu May 6 09:52:46 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : fr_FR.UTF-8
LOCALE           : fr_FR.UTF-8

pandas           : 1.2.4
numpy            : 1.20.1
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.1.1
setuptools       : 52.0.0.post20210125
Cython           : 0.29.23
pytest           : 6.2.3
hypothesis       : None
sphinx           : 4.0.1
blosc            : None
feather          : None
xlsxwriter       : 1.3.8
lxml.etree       : 4.6.3
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 3.0.0
IPython          : 7.22.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.9.0
fastparquet      : 0.6.3
gcsfs            : None
matplotlib       : 3.3.4
numexpr          : 2.7.3
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : 2.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.6.2
sqlalchemy       : 1.4.15
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 2.0.1
xlwt             : 1.3.0
numba            : 0.51.2

</details>
