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I have checked that this issue has not already been reported.
I have confirmed this bug exists on the latest version of pandas.
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
importpandasaspddf=pd.DataFrame(
{
"col1": [None, 1, 1, 0, None, 0],
"col2": [4, 5, None, 7, 4, 5],
"col3": [0, 1, 2, 3, 4, 5]
}
)
# these two are equal (note that we can't use == to compare because of nulls in the dict)print(df.groupby(['col1', 'col2'], dropna=False).groups)
print(df.groupby(['col1', 'col2'], dropna=True).groups)
Issue Description
Note that groupby.groups does seem to respect dropna for grouping by a single column with nulls, but groupbing by a single column with nulls with dropna=False raises ValueError: Categorical categories cannot be null due to #35202.
Expected Behavior
As with other groupby aggregations, dropna=True should drop any group keys where any key column is null.
Installed Versions
INSTALLED VERSIONS
commit : a671b5a
python : 3.9.18.final.0
python-bits : 64
OS : Darwin
OS-release : 23.2.0
Version : Darwin Kernel Version 23.2.0: Wed Nov 15 21:55:06 PST 2023; root:xnu-10002.61.3~2/RELEASE_ARM64_T6020
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
Pandas version checks
I have checked that this issue has not already been reported.
I have confirmed this bug exists on the latest version of pandas.
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
Issue Description
Note that groupby.groups does seem to respect
dropna
for grouping by a single column with nulls, but groupbing by a single column with nulls withdropna=False
raisesValueError: Categorical categories cannot be null
due to #35202.Expected Behavior
As with other groupby aggregations,
dropna=True
should drop any group keys where any key column is null.Installed Versions
INSTALLED VERSIONS
commit : a671b5a
python : 3.9.18.final.0
python-bits : 64
OS : Darwin
OS-release : 23.2.0
Version : Darwin Kernel Version 23.2.0: Wed Nov 15 21:55:06 PST 2023; root:xnu-10002.61.3~2/RELEASE_ARM64_T6020
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.1.4
numpy : 1.26.3
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 8.18.1
pandas_datareader : None
bs4 : None
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.4
qtpy : None
pyqt5 : None
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