Pandas version checks

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Reproducible Example

import pandas as pd
import numpy as np

da = pd.DataFrame()
db = pd.DataFrame()
da["t"] = np.array([1721088000012322083, 1721088047408560273, 1721088047408560451], dtype=np.int64)   # Note different types here
db["t"] = np.array([1721088000012322083, 1721088047408560273, 1721088047408560451], dtype=np.uint64)  # Note different types here
da["i"] = 1
db["i"] = 1
da["p"] = [3, 6, 2]
db["q"] = [1, 2, 2]

print(pd.merge(da, db, on=["i", "t"], how="left", validate="1:1"))
print(pd.merge(da, db, on=["t"], how="left", validate="1:1"))

Issue Description

Running the example produces some very strange results: The first print returns: ---------------t-------------------i-p-q 0 1721088000012322083 1 3 1 1 1721088047408560273 1 6 2 2 1721088047408560273 1 6 2 3 1721088047408560451 1 2 2 4 1721088047408560451 1 2 2

Firstly I wouldn't expect there to be a collision of join keys despite an implicit cast between uint64 and int64. Even allowing for this, the collision doesn't trigger the validate='1:1' check.

Stranger still it seems if you drop the first trivial join key, then the merge is clean! -------------t------------------i_x-p-i_y-q 0 1721088000012322083 1 3 1 1 1 1721088047408560273 1 6 1 2 2 1721088047408560451 1 2 1 2

Expected Behavior

I would expect the output to be: -------------t------------------i_x-p-i_y-q 0 1721088000012322083 1 3 1 1 1 1721088047408560273 1 6 1 2 2 1721088047408560451 1 2 1 2

in both cases or for validate to throw in the first case.

Installed Versions

INSTALLED VERSIONS

commit : 2cc37625532045f4ac55b27176454bbbc9baf213 python : 3.12.11 python-bits : 64 OS : Linux OS-release : 6.1.0-37-amd64 Version : #1 SMP PREEMPT_DYNAMIC Debian 6.1.140-1 (2025-05-22) machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : C.UTF-8 LOCALE : C.UTF-8

pandas : 2.3.0 numpy : 2.2.6 pytz : 2025.2 dateutil : 2.9.0.post0 pip : 25.0.1 Cython : None sphinx : None IPython : 9.3.0 adbc-driver-postgresql: None adbc-driver-sqlite : None bs4 : 4.13.4 blosc : None bottleneck : None dataframe-api-compat : None fastparquet : None fsspec : 2025.5.1 html5lib : None hypothesis : None gcsfs : None jinja2 : 3.1.6 lxml.etree : None matplotlib : 3.10.3 numba : 0.61.2 numexpr : None odfpy : None openpyxl : None pandas_gbq : None psycopg2 : None pymysql : None pyarrow : 20.0.0 pyreadstat : None pytest : 8.3.5 python-calamine : None pyxlsb : None s3fs : None scipy : 1.15.3 sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlsxwriter : None zstandard : 0.23.0 tzdata : 2025.2 qtpy : None pyqt5 : None

Comment From: eicchen

take