BUG: `str` dtype does not return pyarrow boolean (`bool[pyarrow]`) output for elementwise checks (equality, etc.)

[mattharrison]

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

# Load a string column with pyarrow backend
make = pd.Series(["Alfa Romeo", "Ford", "Subaru"], dtype="str")

# Elementwise equality check
result = make == "Alfa Romeo"
print(result.dtype)  # Expected: boolean[pyarrow], Actual: bool

Issue Description

When using the new str dtype (backed by pyarrow) in pandas 3.x, elementwise operations such as equality checks (==) do not return a Series with pyarrow boolean dtype. Instead, the output is a Series with numpy boolean dtype. This is inconsistent with other pyarrow-backed dtypes, which return pyarrow booleans for such operations.

Expected Behavior

This works if casting to string[pyarrow]

import pandas as pd

# Load a string column with pyarrow backend
make = pd.Series(["Alfa Romeo", "Ford", "Subaru"], dtype="str")

# Elementwise equality check
result = make.astype('string[pyarrow]') == "Alfa Romeo"
print(result.dtype)  # Got: boolean[pyarrow]

Installed Versions

INSTALLED VERSIONS

commit : 1a3230d
python : 3.11.13
python-bits : 64
OS : Darwin
OS-release : 24.6.0
Version : Darwin Kernel Version 24.6.0: Mon Jul 14 11:30:40 PDT 2025; root:xnu-11417.140.69~1/RELEASE_ARM64_T6041
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8

pandas : 3.0.0rc0
numpy : 2.4.0rc1
dateutil : 2.9.0.post0
pip : None
Cython : None
sphinx : None
IPython : 9.8.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.14.3
bottleneck : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.6
lxml.etree : None
matplotlib : 3.10.7
numba : None
numexpr : None
odfpy : None
openpyxl : None
psycopg2 : None
pymysql : None
pyarrow : 22.0.0
pyiceberg : None
pyreadstat : None
pytest : None
python-calamine : None
pytz : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
qtpy : None
pyqt5 : None

[mattharrison]

Here's another related issue, let me know if I should file a separate bug:

>>> age = pd.Series(['0-10', '11-15', '11-15', '61-65', '46-50'])
>>> age.str.split('-')
0     [0, 10]
1    [11, 15]
2    [11, 15]
3    [61, 65]
4    [46, 50]
dtype: object

if we use the pd.ArrowDtype(pa.string()) type, this returns list<item: string>[pyarrow] instead of object.