BUG: inconsistent result when groupby then sum values that contain inf
- [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.

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

---

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

```python
import pandas as pd

>>> df = pd.DataFrame({'a': ['hello', 'hello', 'world', 'world'], 'b': [np.inf, 10, np.nan, 10]})
>>> gb = df.groupby('a')
>>> gb.sum()
          b
a          
hello   NaN
world  10.0
>>> gb.get_group('hello').b.sum()
inf
```

#### Problem description
while directly doing `groupby.sum`, the group with `inf` will return `np.nan`, but if we get the group and do `sum`, it returns `np.inf`
#### Expected Output
`groupby.sum` should also return `np.inf` if the values contian `np.inf`
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : c7f7443c1bad8262358114d5e88cd9c8a308e8aa
python           : 3.7.6.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.2.0
Version          : Darwin Kernel Version 18.2.0: Thu Dec 20 20:46:53 PST 2018; root:xnu-4903.241.1~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : en_US.UTF-8
pandas           : 1.3.1
numpy            : 1.21.1
pytz             : 2021.1
dateutil         : 2.8.2
pip              : 21.1.2
setuptools       : 57.0.0
Cython           : None
pytest           : 4.5.0
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : 0.7.11.None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.26.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : 2.7.3
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 3.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.1.0
sqlalchemy       : 1.3.24
tables           : 3.5.2
tabulate         : 0.7.7
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
