BUG: Results of series bitwise ufunc operations are being casted to bool in pandas-2.0

[galipremsagar]

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• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

In [1]: import pandas as pd

In [2]: import numpy as np

In [3]: np.bitwise_xor
Out[3]: <ufunc 'bitwise_xor'>

In [4]: a = pd.Series([1, 2, 3], index=[10, 11, 23], name="a")

In [5]: b = pd.Series([10, 20, 30], index=[11, 10, 23], name="a")

In [9]: np.bitwise_xor(a, b)
Out[9]: 
10    True
11    True
23    True
Name: a, dtype: bool

In [10]: np.bitwise_xor(a.to_frame(), b.to_frame())
Out[10]: 
     a
10  21
11   8
23  29

Issue Description

bitwise_xor on Series & DataFrame are returning different results(i.e., bool & int respectively).

Expected Behavior

Consistent output between Series & DataFrame:

In [9]: np.bitwise_xor(a, b)
Out[9]: 
10    21
11    8
23    29
Name: a, dtype: int64

Installed Versions

INSTALLED VERSIONS

commit : c2a7f1a
python : 3.10.10.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-76-generic
Version : #86-Ubuntu SMP Fri Jan 17 17:24:28 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.0.0rc1
numpy : 1.23.5
pytz : 2023.3
dateutil : 2.8.2
setuptools : 67.6.1
pip : 23.0.1
Cython : 0.29.34
pytest : 7.2.2
hypothesis : 6.70.2
sphinx : 5.3.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.12.0
pandas_datareader: None
bs4 : 4.12.0
bottleneck : None
brotli :
fastparquet : None
fsspec : 2023.3.0
gcsfs : None
matplotlib : None
numba : 0.56.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 10.0.1
pyreadstat : None
pyxlsb : None
s3fs : 2023.3.0
scipy : 1.10.1
snappy :
sqlalchemy : 1.4.46
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : None
qtpy : None
pyqt5 : None

[mroeschke]

Looks like maybe_dispatch_ufunc_to_dunder_op is dispatching this to a ^ b which returns a boolean result. Index doesn't have this behavior

In [5]: a ^ b
Out[5]: 
10    True
11    True
23    True
Name: a, dtype: bool

In [6]: np.bitwise_xor(pd.Index(a), pd.Index(b))
Out[6]: Index([11, 22, 29], dtype='int64', name='a')

Not sure if that's intentional cc @jbrockmendel

[jbrockmendel]

Haven't looked too closely, but I expect the difference is related to the bespoke reindexing/casting logic in the Series logical op, xref #52538