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BUG: pd.Series idxmax raises ValueError instead of returning <NA> when all values are <NA> #51276

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@hchau630

Description

@hchau630

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Reproducible Example

import pandas as pd
import numpy as np

s = pd.Series([np.nan, np.nan]).convert_dtypes()
s.idxmax(skipna=True)

Issue Description

According to documentation, when pd.Series contains all NaN values, calling idxmax with skipna=True should return NaN. However, in this case it raise "ValueError: attempt to get argmax of an empty sequence" instead. This issue only happens when I used convert_dtypes() on the Series before calling idxmax. Interestingly, the same issue does not appear for pd.DataFrame.

Expected Behavior

Should return or NaN rather than raising ValueError.

Installed Versions

INSTALLED VERSIONS

commit : 2e218d1
python : 3.9.13.final.0
python-bits : 64
OS : Darwin
OS-release : 21.3.0
Version : Darwin Kernel Version 21.3.0: Wed Jan 5 21:37:58 PST 2022; root:xnu-8019.80.24~20/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.5.3
numpy : 1.23.4
pytz : 2022.6
dateutil : 2.8.2
setuptools : 65.5.0
pip : 22.2.2
Cython : None
pytest : 7.2.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.4.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.6.2
numba : None
numexpr : 2.8.4
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.9.3
snappy : None
sqlalchemy : None
tables : 3.7.0
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None

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    BugNA - MaskedArraysRelated to pd.NA and nullable extension arraysNumeric OperationsArithmetic, Comparison, and Logical operations

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