BUG: IntervalIndex intersections are not intersections in many cases · Issue #38743 · pandas-dev/pandas (original) (raw)
- I have checked that this issue has not already been reported.
- I have confirmed this bug exists on the latest version of pandas.
- (optional) I have confirmed this bug exists on the master branch of pandas.
Code Sample, a copy-pastable example
Your code here
import pandas._testing as tm
idx_unique = tm.makeIntervalIndex(k=5) idx_non_unique = idx_unique[[0, 0, 1, 2, 3, 4]]
assert idx_unique.intersection(idx_non_unique).equals(idx_non_unique) assert idx_non_unique.intersection(idx_unique).equals(idx_non_unique)
As an implementation note:
assert idx_non_unique._intersection_non_unique(idx_unique).equals(idx_non_unique)
All of these should probably fail
Problem description
Intersections on IntervalIndexes should not repeat duplicated elements, similar to all other Index types.
I came across this while writing tests for #38654
For example, if we defined a test:
def check_intersection_commutative(left, right): assert left.intersection(right).equals(right.intersection(left))
@pytest.mark.parametrize("index_maker", tm.index_subclass_makers_generator()) def test_intersection_uniqueness(index_maker): if index_make is tm.makeMultiIndex: pytest.pass() # This index maker is bugged ind_unique = index_maker(k=5) ind_non_unique = idx_unique[[0, 0, 1, 2, 3, 4]]
check_intersection_commutative(ind_unique, ind_non_unique)
assert idx_unique.intersection(idx_non_unique).is_uniqueOnly IntervalIndex would fail (not including the bugged makeMultiIndex).
Expected Output
All of the assertions in the original example should fail.
Output of pd.show_versions()
dev environment
INSTALLED VERSIONS
------------------
commit : 9f1a41dee0e9167361d9f435b4c3d499d01e415a
python : 3.8.5.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Tue Nov 10 00:10:30 PST 2020; root:xnu-6153.141.10~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.0.dev0+210.g9f1a41dee0.dirty
numpy : 1.18.5
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 49.2.0.post20200712
Cython : 0.29.21
pytest : 5.4.3
hypothesis : 5.20.3
sphinx : 3.1.1
blosc : None
feather : None
xlsxwriter : 1.2.9
lxml.etree : 4.5.2
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: None
bs4 : 4.9.1
bottleneck : 1.3.2
fsspec : 0.7.4
fastparquet : 0.4.1
gcsfs : 0.6.2
matplotlib : 3.2.2
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.4
pandas_gbq : None
pyarrow : 0.17.1
pyxlsb : None
s3fs : 0.4.2
scipy : 1.5.1
sqlalchemy : 1.3.18
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.16.0
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.50.1
1.1.5
INSTALLED VERSIONS
------------------
commit : b5958ee1999e9aead1938c0bba2b674378807b3d
python : 3.8.6.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Tue Nov 10 00:10:30 PST 2020; root:xnu-6153.141.10~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.5
numpy : 1.19.4
pytz : 2020.1
dateutil : 2.8.1
pip : 20.3.3
setuptools : 51.0.0
Cython : 0.29.21
pytest : 6.2.1
hypothesis : None
sphinx : 3.3.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.19.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.5
fastparquet : 0.4.1
gcsfs : None
matplotlib : 3.3.3
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 2.0.0
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.5.4
sqlalchemy : 1.3.18
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.16.2
xlrd : 1.2.0
xlwt : None
numba : 0.52.0