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Reproducible Example

In [1]: import pandas as pd

In [2]: import numpy as np

In [3]: pd.__version__
Out[3]: '2.1.0.dev0+5.g8d2a4e11d1'

In [4]: s = pd.Series([1,2,3])

In [5]: s & 1
Out[5]:
0    1
1    0
2    1
dtype: int64

In [6]: s & np.array([1,2,3])
Out[6]:
0    1
1    2
2    3
dtype: int64

In [7]: s & [1, 2, 3]
Out[7]:
0    True
1    True
2    True
dtype: bool

In [8]: np.array([1,2,3]) & [1,2,3]
Out[8]: array([1, 2, 3])

Issue Description

If you have a Series of integers, and you do a bitwise operation using &, | or ^ ("and", "or", or "xor"), where the other argument is a list, you get different results than if the argument is a numpy array.

Note in the example above how s & np.array([1,2,3]) produces a Series of integers, while s & [1,2,3] produces a Series of bool

Also, note that numpy produces an array of integers, not bools.

Expected Behavior

The behavior should be consistent whether the operand is a numpy array or a list of integers.

Installed Versions

INSTALLED VERSIONS ------------------ commit : 8d2a4e11d136af439de92ef1a970a1ae0edde4dc python : 3.8.16.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19045 machine : AMD64 processor : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : English_United States.1252 pandas : 2.1.0.dev0+5.g8d2a4e11d1 numpy : 1.23.5 pytz : 2022.7.1 dateutil : 2.8.2 setuptools : 66.1.1 pip : 23.0 Cython : 0.29.32 pytest : 7.2.1 hypothesis : 6.68.1 sphinx : 4.5.0 blosc : None feather : None xlsxwriter : 3.0.8 lxml.etree : 4.9.2 html5lib : 1.1 pymysql : 1.0.2 psycopg2 : 2.9.3 jinja2 : 3.1.2 IPython : 8.10.0 pandas_datareader: None bs4 : 4.11.2 bottleneck : 1.3.6 brotli : fastparquet : 2023.2.0 fsspec : 2023.1.0 gcsfs : 2023.1.0 matplotlib : 3.6.3 numba : 0.56.4 numexpr : 2.8.3 odfpy : None openpyxl : 3.1.0 pandas_gbq : None pyarrow : 10.0.1 pyreadstat : 1.2.0 pyxlsb : 1.0.10 s3fs : 2023.1.0 scipy : 1.10.0 snappy : sqlalchemy : 2.0.3 tables : 3.7.0 tabulate : 0.9.0 xarray : 2023.1.0 xlrd : 2.0.1 zstandard : 0.19.0 tzdata : None qtpy : None pyqt5 : None

Comment From: jbrockmendel

yah this is weird. let's deprecate the heck out of it