BUG: regression, is_unique is incorrect since pandas 2.1.0 · Issue #57911 · pandas-dev/pandas (original) (raw)

Pandas version checks

Reproducible Example

import pandas as pd print("pandas version", pd.version)

values = [1, 1, 2, 3, 4] index = pd.Index(values)

print("===========") print(index) print("is_unique=", index.is_unique)

filtered_index = index[2:].copy()

print("===========") print(filtered_index) print("is_unique=", filtered_index.is_unique)

index = pd.Index(values) filtered_index = index[2:].copy()

print("===========") print(filtered_index) print("is_unique=", filtered_index.is_unique)

Issue Description

Hello,

We found a regression, index.is_unique is incorrect since pandas 2.1.0.

I looked for open issues but did not find any fix or existing discussion.
Having a look at the changelog, there were lots of changes in 2.1.0 to introduce copy-on-write optimizations on the index.
I think the issue could be related to that, my best guess, maybe index[2:] cached something from the original index that is no longer correct?

Attaching a simple repro, it's very easy to reproduce. :)

Thank you.

Expected Behavior

pandas version 1.5.3
===========
Int64Index([1, 1, 2, 3, 4], dtype='int64')
is_unique= False
===========
Int64Index([2, 3, 4], dtype='int64')
is_unique= True
===========
Int64Index([2, 3, 4], dtype='int64')
is_unique= True

pandas version 2.2.1
===========
Index([1, 1, 2, 3, 4], dtype='int64')
is_unique= False
===========
Index([2, 3, 4], dtype='int64')
is_unique= False    # <---------------- INCORRECT
===========
Index([2, 3, 4], dtype='int64')
is_unique= True

Installed Versions

tested on: