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 as pd
df = pd.DataFrame(
{"A": [1, 1, 2, 2, 2], "B": [3, 3, 4, 4, 4], "C": [1, 1, 1, 1, 1]},
dtype=float
)
assert (
pd.crosstab(index=df["A"], columns=df["B"], values=df["C"], aggfunc="skew", dropna=True).shape ==
pd.crosstab(index=df["A"], columns=df["B"], values=df["C"], aggfunc="skew", dropna=False).shape
)Issue Description
When I provide dropna=True to crosstab and specify a values array to aggregate, pandas seems to drop rows and columns where all the results are NaN. In this case pandas skew gives NaN if there are fewer than 3 values in a group, so only the value for index=2, column=4 has a non-NaN value. That leaves a row of NaN and a column of NaN, so pandas drops both the all-NaN row and the all-NaN column.
Expected Behavior
The documentation says that dropna=True means, "Do not include columns whose entries are all NaN." I expect pandas to follow that rule and to keep values where the aggregation result is NaN. In the example above, I expect to see 2 rows for the 2 possible values of A, 1 and 2, an 2 columns for the 2 possible values of B, 3 and 4.
Installed Versions
INSTALLED VERSIONS
------------------
commit : 0691c5cf90477d3503834d983f69350f250a6ff7
python : 3.9.21
python-bits : 64
OS : Darwin
OS-release : 24.2.0
Version : Darwin Kernel Version 24.2.0: Fri Dec 6 18:56:34 PST 2024; root:xnu-11215.61.5~2/RELEASE_ARM64_T6020
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.2.3
numpy : 2.0.2
pytz : 2024.2
dateutil : 2.8.2
pip : 24.2
Cython : None
sphinx : None
IPython : 8.12.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : None
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : None
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.1
qtpy : None
pyqt5 : None