BUG: .str.replace() with capture groups does not play nice with string methods

[noahblakesmith]

Pandas version checks

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• 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

Code

import pandas as pd
c = pd.Series("THE QUICK BROWN FOX JUMPS OVER THE LAZY DOG")
x, y, z = "\\b(FOX|THE)\\b", "_ABC_", "\\1_ABC_"
print(c.str.replace(x, y.lower(), regex=True))
print(c.str.replace(x, z.lower(), regex=True))

Output

0    _abc_ QUICK BROWN _abc_ JUMPS OVER _abc_ LAZY DOG
dtype: object
0    THE_abc_ QUICK BROWN FOX_abc_ JUMPS OVER THE_a...
dtype: object

Issue Description

The .lower() string method inconsistently modifies the repl argument when the latter includes a regex capture group.

Expected Behavior

I would expect .lower() to modify all characters in repl, including those in the capture group (or a warning stating otherwise).

Installed Versions

INSTALLED VERSIONS

commit : 0691c5c
python : 3.10.16
python-bits : 64
OS : Darwin
OS-release : 24.3.0
Version : Darwin Kernel Version 24.3.0: Thu Jan 2 20:24:16 PST 2025; root:xnu-11215.81.4~3/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.2.3
numpy : 2.2.2
pytz : 2025.1
dateutil : 2.9.0.post0
pip : 25.0
Cython : None
sphinx : None
IPython : 8.33.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.13.3
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2025.2.0
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.5
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.5
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 19.0.1
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
xlsxwriter : None
zstandard : None
tzdata : 2025.1
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for the report. You're calling lower on a string. There is no way for pandas to tell the difference between the following two lines.

print(c.str.replace(x, "\\1_ABC_".lower(), regex=True))
print(c.str.replace(x, "\\1_abc_", regex=True))

Closing for now. If you believe I've misunderstood the issue, please comment how here and we can reopen!