sum() after groupby returns different value compared to regular sum()
- [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
np.random.seed(0)
df = pd.DataFrame(np.random.rand(253, 2) * 254, columns=['a', 'b'])
df['type'] = 'test'

sum_mult_v1 = df.assign(mult=(lambda x: x.a * x.b)).groupby('type')['mult'].sum()[0]
sum_mult_v2 = (df['a'] * df['b']).sum()
print(sum_mult_v1)
print(sum_mult_v2)
print(sum_mult_v1 == sum_mult_v2)
```

#### Problem description
The output of the code is:
```
4010049.3807103755
4010049.3807103736
False
```

For some reason, the summation of values after groupby is different from the same operation done without a groupby. I understand that there is no point in grouping by a column that only has one value, but I wonder if there is something off with the summation function after groupby? 

#### Expected Output
The expected output would be having the same numbers. 
```
4010049.3807103736
4010049.3807103736
True
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.6.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.4.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0.post20200210
Cython           : 0.29.17
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.2.8
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.14.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : 1.2.8
numba            : 0.49.1

</details>
