BUG: Intersection of multiindex returns duplicates · Issue #36915 · pandas-dev/pandas (original) (raw)

import pandas as pd

arraysA = [['val1', 'val1', 'val1', 'val1'], ['val2', 'val2', 'val2', 'val2']] arraysB = [['val1'], ['val2']]

MultiIndex([('val1', 'val2'),

('val1', 'val2'),

('val1', 'val2'),

('val1', 'val2')],

names=['idx1', 'idx2'])

indexA = pd.MultiIndex.from_arrays(arraysA, names=('idx1', 'idx2'))

MultiIndex([('val1', 'val2')],

names=['idx1', 'idx2'])

indexB = pd.MultiIndex.from_arrays(arraysB, names=('idx1', 'idx2'))

res = indexA.intersection(indexB)

Problem description

Intersection of multiindexes must produce result without duplicates. According to definition the intersection of two sets A and B, denoted by A ∩ B, is the set containing all elements of A that also belong to B (or equivalently, all elements of B that also belong to A.

Version 1.0.3 gave correct output, versions 1.1.2 , 1,1,3 - not.

Output: Pandas 1.1.3

MultiIndex([('val1', 'val2'),
('val1', 'val2'),
('val1', 'val2'),
('val1', 'val2')],
names=['idx1', 'idx2'])

Output: Pandas 1.0.3

MultiIndex([('val1', 'val2')],
names=['idx1', 'idx2'])

Expected Output

I assume correct output should look like pandas 1.0.3 version:
MultiIndex([('val1', 'val2')], names=['idx1', 'idx2'])

Output of pd.show_versions()

INSTALLED VERSIONS

commit : db08276
python : 3.7.6.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.17763
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 9, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 1.1.3
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.2
setuptools : 46.0.0
Cython : None
pytest : 6.0.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.3.0
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.8.5 (dt dec pq3 ext lo64)
jinja2 : 2.11.1
IPython : 7.14.0
pandas_datareader: None
bs4 : 4.9.1
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.2.1
numexpr : None
odfpy : None
openpyxl : 3.0.4
pandas_gbq : None
pyarrow : 1.0.1
pytables : None
pyxlsb : 1.0.6
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.17
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
numba : None
None