BUG: Duplicate columns allowed on merge if originating from separate dataframes (original) (raw)

Pandas version checks

Reproducible Example

import pandas as pd df1 = pd.DataFrame({"col1":[1], "col2":[2]}) df2 = pd.DataFrame({"col1":[1], "col2":[2], "col2_dup":[3]})

pd.merge(df1, df2, on="col1", suffixes=("_dup", ""))

Observe (1)

pd.merge(df1, df2, on="col1", suffixes=("", "_dup"))

Observe (2)

Issue Description

Case 1 provides the following result:

   col1  col2_dup  col2  col2_dup
0     1         2     2         3

Case 2 results in an exception:

pandas.errors.MergeError: Passing 'suffixes' which cause duplicate columns {'col2_dup'} is not allowed.

While the MergeError in this case does make sense (ideally duplicate columns should not be allowed as they might cause confusion), the same issue is observed in the first case and no exception is raised.

Expected Behavior

Since this bug is about consistency, either of the following 2 should happen:

Installed Versions

INSTALLED VERSIONS

commit : 0691c5c
python : 3.11.7
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 170 Stepping 4, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.2.3
numpy : 2.2.5
pytz : 2025.2
dateutil : 2.9.0.post0
pip : 23.2.1
Cython : None
sphinx : None
IPython : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : None
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : None
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.2
qtpy : None
pyqt5 : None