BUG: Series containing Bool and NaN/None values returns Object dtype

[DarthKitten2130]

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Reproducible Example

import pandas as pd

ser1 = pd.Series([True,False,True,False,None])

print(ser1.dtype)

Issue Description

The dtype returned from the Series object is the 'object' dtype. This issue also persists in DataFrames.

Expected Behavior

The dtype returned should have been a 'bool' dtype.

Installed Versions

INSTALLED VERSIONS

commit : f538741
python : 3.11.3.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.2.0
numpy : 1.26.3
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 69.0.3
pip : 23.3.2
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 : None
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : 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
python-calamine : 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

[mroeschke]

bool (numpy type) cannot hold NA values, so this is the expected behavior https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html#values-considered-missing

[davetapley]

@mroeschke could it not return boolean?

The page you linked to does call it out a little later on:

pandas/doc/source/user_guide/missing_data.rst

Lines 32 to 33 in 56b5979

	:class:`NA` for :class:`StringDtype`, :class:`Int64Dtype` (and other bit widths),
	:class:`Float64Dtype`(and other bit widths), :class:`BooleanDtype` and :class:`ArrowDtype`.

[DarthKitten2130]

Actually, all 3 of us are technically correct. The doc you just referred to mentions that the dtype has to come from pyarrow, and not numpy. If you want this functionality, you would need to replace your numpy types with pyarrow types. As pandas moves away from numpy and embraces pyarrow, this will probably become more standardised. Until then however, I wish there would be a clear distinction as to how the transition from numpy to pyarrow affects legacy code.

[mroeschke]

The boolean type is explicitly opt-in still, so when dtype=None, the inferred type is np.bool_