BUG: DataFrame.min with skipna=True raises TypeError when column contains np.nan and datetime.date

[tanjt107]

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

import pandas as pd
import numpy as np
import datetime

data = {
    "dates": [
        np.nan,
        np.nan,
        datetime.date(2025, 1, 3),
        datetime.date(2025, 1, 4),
    ],
}

df = pd.DataFrame(data)

df.min(axis=0)

Issue Description

The issue arises when calling DataFrame.min(axis=0) with skipna=True (default) on a column containing a mix of np.nan and datetime.date. This results in a TypeError because np.nan (a float) cannot be compared with datetime.date.

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\test.py", line 29, in <module>

    df.min(axis=0)

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\pandas\core\frame.py", line 11643, in min

    result = super().min(axis, skipna, numeric_only, **kwargs)

             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\pandas\core\generic.py", line 12388, in min

    return self._stat_function(

           ^^^^^^^^^^^^^^^^^^^^

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\pandas\core\generic.py", line 12377, in _stat_function

    return self._reduce(

           ^^^^^^^^^^^^^

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\pandas\core\frame.py", line 11562, in _reduce

    res = df._mgr.reduce(blk_func)

          ^^^^^^^^^^^^^^^^^^^^^^^^

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\pandas\core\internals\managers.py", line 1500, in reduce

    nbs = blk.reduce(func)

          ^^^^^^^^^^^^^^^^

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\pandas\core\internals\blocks.py", line 404, in reduce

    result = func(self.values)

             ^^^^^^^^^^^^^^^^^

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\pandas\core\frame.py", line 11481, in blk_func

    return op(values, axis=axis, skipna=skipna, **kwds)

           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\pandas\core\nanops.py", line 147, in f

    result = alt(values, axis=axis, skipna=skipna, **kwds)

             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\pandas\core\nanops.py", line 404, in new_func

    result = func(values, axis=axis, skipna=skipna, mask=mask, **kwargs)

             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\pandas\core\nanops.py", line 1098, in reduction

    result = getattr(values, meth)(axis)

             ^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "C:\Users\45217950\Downloads\GitHub\irr-cloud\.venv\Lib\site-packages\numpy\_core\_methods.py", line 48, in _amin

    return umr_minimum(a, axis, None, out, keepdims, initial, where)

           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

TypeError: '<=' not supported between instances of 'float' and 'datetime.date'

This issue is related to issue #61187, but the specific case here involves datetime.date (not datetime.datetime), which behaves differently in pandas.

Expected Behavior

dates    2025-01-03
dtype: object

Installed Versions

INSTALLED VERSIONS

---

commit : 0691c5c

python : 3.12.7

python-bits : 64

OS : Windows

OS-release : 10

Version : 10.0.19045

machine : AMD64

processor : Intel64 Family 6 Model 85 Stepping 7, GenuineIntel

byteorder : little

LC_ALL : None

LANG : en_US.UTF-8

LOCALE : English_United States.1252

pandas : 2.2.3

numpy : 2.2.3

pytz : 2025.1

dateutil : 2.9.0

pip : 24.2

Cython : None

sphinx : None

IPython : None

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 : 3.1.5

pandas_gbq : 0.28.0

psycopg2 : None

pymysql : None

pyarrow : 19.0.1

pyreadstat : None

pytest : None

python-calamine : None

pyxlsb : None

s3fs : None

scipy : 1.15.2

sqlalchemy : None

tables : None

tabulate : None

xarray : None

xlrd : None

xlsxwriter : 3.2.2

zstandard : None

tzdata : 2025.1

qtpy : None

pyqt5 : None

[rhshadrach]

Thanks for the report. This happens on any object dtype data; I am wondering if pandas should handle object blocks specially where we filter instead of fillna values. Further investigations and PRs to fix are welcome!

[MayurKishorKumar]

take