Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas
from decimal import Decimal
frame = pandas.DataFrame(
columns=["group_field", "value_field"],
data=[
[Decimal(1), Decimal(2)],
[Decimal(1), Decimal(3)],
[None, Decimal(4)],
[None, Decimal(5)],
],
)
group_by = frame.groupby("group_field", dropna=False)
sum = group_by["value_field"].sum()
print(sum)Issue Description
When trying to upgrade from pandas 1.3.0 to 2.0.3 I noticed that tests that grouped on a mixture of decimals and Nones were failing with the following error:
decimal.InvalidOperation: [<class 'decimal.InvalidOperation'>]
Even though I upgraded pandas, version of numpy stayed the same at 1.24.3.
Looking deeper it looks like the safe_sort function first tries to sort data using values.argsort(), but since that raises a decimal.InvalidOperation instead of a TypeError it fails. I was able to fix this by adding the new exception type to the except clause like this:
except (TypeError, decimal.InvalidOperation):Hopefully this is an easy 1-line fix but please let me know if you have questions or concerns. Thanks!
Expected Behavior
Sum from the print statement should be the series that looks like this:
group_field
1 5
NaN 9
Name: value_field, dtype: object
Installed Versions
INSTALLED VERSIONS
commit : 0f43794
python : 3.9.13.final.0
python-bits : 64
OS : Darwin
OS-release : 22.6.0
Version : Darwin Kernel Version 22.6.0: Wed Jul 5 22:22:05 PDT 2023; root:xnu-8796.141.3~6/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.0.3
numpy : 1.24.3
pytz : 2023.3
dateutil : 2.8.2
setuptools : 68.1.2
pip : 22.3.1
Cython : 0.29.34
pytest : 5.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.9.5
jinja2 : 3.1.2
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.7.0
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : 1.4.31
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None