BUG: Unknown slicing behavior for Multiindexing when passing through str for int

[renkeven]

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Reproducible Example

import pandas as pd

idx_1 = [2000, 2001]
idx_2 = ["a", "b"]
idx_3 = ["x", "y"]

pd.DataFrame(data={"value": range(8)}, index=pd.MultiIndex.from_product([idx_1, idx_2, idx_3])).loc[("2000", "a")]

Returns

   value
x      0
y      1
x      2
y      3

Issue Description

For a number of our dataframe outputs, we have unfortunately mixed the dtypes of year columns as either str or int. This ambiguity means that we get our slicing notation wrong on occasion, which runs risk of returning an incorrect dataframe instead of raising a KeyError.

Following the above example,
Using .loc[("2000", "GIBBERISH")] also returns the same output as the example. I expect KeyError to be raised here as both columns do not exist in the dataframe.
Using .loc["2000"] fails and a KeyError is raised as expected.
Using .loc[("2000",)] returns the same output as .loc[2000], however, here I would expect a KeyError to be raised for the former (the latter returns the desired and correct output).

Expected Behavior

Expect to raise a KeyError, "2000" not in axis here

Installed Versions

INSTALLED VERSIONS

commit : 0691c5c
python : 3.10.15
python-bits : 64
OS : Linux
OS-release : 6.1.100+
Version : #1 SMP PREEMPT_DYNAMIC Sat Aug 24 16:19:44 UTC 2024
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.2.3
numpy : 1.26.0
pytz : 2024.1
dateutil : 2.9.0
pip : 24.2
Cython : None
sphinx : None
IPython : 8.28.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.9.0
html5lib : None
hypothesis : None
gcsfs : 2024.9.0post1
jinja2 : 3.1.4
lxml.etree : 5.3.0
matplotlib : 3.9.2
numba : 0.60.0
numexpr : None
odfpy : None
openpyxl : 3.1.5
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 15.0.0
pyreadstat : None
pytest : 8.3.3
python-calamine : None
pyxlsb : 1.0.10
s3fs : None
scipy : 1.14.1
sqlalchemy : None
tables : None
tabulate : None
xarray : 2024.9.0
xlrd : 2.0.1
xlsxwriter : 3.2.0
zstandard : 0.23.0
tzdata : 2024.2
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for the report. Indeed, this is not intentional. The following example raises a KeyError:

idx_1 = [2001, 2000]
idx_2 = ["a", "b"]
idx_3 = ["x", "y"]

r = pd.DataFrame(data={"value": range(8)}, index=pd.MultiIndex.from_product([idx_1, idx_2, idx_3]))
r.loc[("2000", "a")])

When the index is sorted, pandas uses NumPy's searchsorted, which has what I think is a somewhat surprising result.

arr = np.array([2000, 2000, 2000, 2001, 2001, 2001, 2001])
print(arr.searchsorted("2001", side="left"))
# 3

Further investigations and PRs to fix are welcome!

[rhshadrach]

This is due to numpy/numpy#24032

[AshmitGupta]

take