BUG: wrong output index mapping of results when groupby both scan and reduction aggregation are passed
Edit (https://github.com/pandas-dev/pandas/issues/40695#issuecomment-810574992): This issue is about `groupby(...).transform` not accepting list-likes or dict-likes.

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

```python
In [1]: import pandas as pd


In [2]: pdf = pd.DataFrame({'a' : [2, 2, 1, 1, 6], 'b' : [2, 2, 1, 1, 3]})


In [3]: pdf.groupby('a').agg(['sum'])
Out[3]: 
    b
  sum
a    
1   2
2   4
6   3

In [4]: pdf.groupby('a').agg(['cumsum'])
Out[4]: 
       b
  cumsum
0      2
1      4
2      1
3      2
4      3

In [5]: pdf.groupby('a').agg(['cumsum', 'sum'])
Out[5]: 
       b     
  cumsum  sum
0    2.0  NaN
1    4.0  2.0
2    1.0  4.0
3    2.0  NaN
4    3.0  NaN
6    NaN  3.0

```

#### Problem description

When both scan aggregrations (cumsum, cummin, cummax, cumcount) and any of reduction aggregartions (sum, min, max, prod, ...), are passed to `groupby.agg` , output value mapping to index in the result is wrong.

scan aggregations produce index as RangeIndex (0 to N-1).
reduction aggregations usually map to grouped keys. In the given example, it maps to values of keys in resulting index.


#### Expected Output
Common method to align the output should be decided and implemented.

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

<details>


INSTALLED VERSIONS
------------------
commit           : f2c8480af2f25efdbd803218b9d87980f416563e
python           : 3.7.10.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-137-generic
Version          : #141-Ubuntu SMP Fri Feb 19 13:46:27 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.3
numpy            : 1.19.2
pytz             : 2020.4
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 49.6.0.post20201009
Cython           : 0.29.22
pytest           : 6.2.2
hypothesis       : 6.8.1
sphinx           : 3.5.3
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.21.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : None
fsspec           : 0.8.7
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pyxlsb           : None
s3fs             : None
scipy            : 1.6.0
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.52.0

</details>
