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BUG: inconsistent result when groupby then sum values that contain inf #43292

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@jerrytim

Description

@jerrytim
  • I have checked that this issue has not already been reported.

  • 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

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()

INSTALLED VERSIONS

commit : c7f7443
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

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BugGroupbyReduction Operationssum, mean, min, max, etc.RegressionFunctionality that used to work in a prior pandas version

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