BUG: Multiplying a series of strings with a boolean different for arrow vs. python

[Dr-Irv]

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
pd.Series(["a", "b", "c"], dtype="string[python]") * True  # works
pd.Series(["a", "b", "c"], dtype="string") * True  # fails

Issue Description

Multiplying a string series by a boolean doesn't work with arrow based strings
Error reported:

  File "C:\Code\pandas_dev\pandas\pandas\core\ops\common.py", line 70, in new_method
    return method(self, other)
           ^^^^^^^^^^^^^^^^^^^
  File "C:\Code\pandas_dev\pandas\pandas\core\arraylike.py", line 205, in __mul__
    return self._arith_method(other, operator.mul)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Code\pandas_dev\pandas\pandas\core\series.py", line 5924, in _arith_method
    return base.IndexOpsMixin._arith_method(self, other, op)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Code\pandas_dev\pandas\pandas\core\base.py", line 1485, in _arith_method
    result = ops.arithmetic_op(lvalues, rvalues, op)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Code\pandas_dev\pandas\pandas\core\ops\array_ops.py", line 272, in arithmetic_op
    res_values = op(left, right)
                 ^^^^^^^^^^^^^^^
  File "C:\Code\pandas_dev\pandas\pandas\core\ops\common.py", line 70, in new_method
    return method(self, other)
           ^^^^^^^^^^^^^^^^^^^
  File "C:\Code\pandas_dev\pandas\pandas\core\arraylike.py", line 205, in __mul__
    return self._arith_method(other, operator.mul)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Code\pandas_dev\pandas\pandas\core\arrays\arrow\array.py", line 1051, in _arith_method
    result = self._evaluate_op_method(other, op, ARROW_ARITHMETIC_FUNCS)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Code\pandas_dev\pandas\pandas\core\arrays\arrow\array.py", line 970, in _evaluate_op_method
    raise TypeError("Can only string multiply by an integer.")
TypeError: Can only string multiply by an integer.

Expected Behavior

No error

Installed Versions

INSTALLED VERSIONS

commit : bb10b27
python : 3.11.13
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.26100
machine : AMD64
processor : Intel64 Family 6 Model 183 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 3.0.0.dev0+2306.gbb10b27dea.dirty
numpy : 2.2.6
dateutil : 2.9.0.post0
pip : 25.2
Cython : 3.1.3
sphinx : 8.3.0
IPython : 9.5.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.14.0
bottleneck : 1.6.0
fastparquet : 2024.11.0
fsspec : 2025.9.0
html5lib : 1.1
hypothesis : 6.138.15
gcsfs : 2025.9.0
jinja2 : 3.1.6
lxml.etree : 6.0.1
matplotlib : 3.10.6
numba : 0.61.2
numexpr : 2.10.2
odfpy : None
openpyxl : 3.1.5
psycopg2 : 2.9.10
pymysql : 1.4.6
pyarrow : 19.0.1
pyiceberg : 0.9.1
pyreadstat : 1.3.1
pytest : 8.4.2
python-calamine : None
pytz : 2025.2
pyxlsb : 1.0.10
s3fs : 2025.9.0
scipy : 1.16.1
sqlalchemy : 2.0.43
tables : 3.10.2
tabulate : 0.9.0
xarray : 2025.9.0
xlrd : 2.0.2
xlsxwriter : 3.2.5
zstandard : 0.24.0
qtpy : None
pyqt5 : None

[jbrockmendel]

I’d expect both to raise

[Dr-Irv]

I’d expect both to raise

I disagree. Because with a list of strings, it works:

>>> ["a", "b", "c"] * True
['a', 'b', 'c']
>>> ["a", "b", "c"] * False
[]

And if we decide to raise, we have a change in behavior from 2.3 to 3.0

[jbrockmendel]

Perfect time to make the change

[cmp0xff]

Hi, could you confirm that pd.Series(["a", "b", "c"], dtype="string") * True will be fixed to work? It is not too clear to me from the context. Thanks!

[jbrockmendel]

Irv and I disagree on whether it should work. On Wednesday's dev call we'll ask for other opinions and get it resolved.

[mroeschke]

From a typing perspective, I get why this should work (bools, subclass int), but from a practical standpoint I agree with Brock as I'm not sure if users would intend to multiply a string array by a bool compared to just using an int

[Dr-Irv]

From a typing perspective, I get why this should work (bools, subclass int), but from a practical standpoint I agree with Brock as I'm not sure if users would intend to multiply a string array by a bool compared to just using an int.

Here's a use case: it's an easy way to create null strings based on a condition. E.g.,

pd.Series(["abc", "def", "ghi"]) * [True, False, True]
0    abc
1
2    ghi
dtype: object

I see your point, but we do have the incompatible behavior between dtype string[python] and dtype string (with the former working with pandas 2.3). So if we want to remove it, we would need to deprecate it.