Description
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the master branch of pandas.
Reproducible Example
import pandas as pd
import numpy as np
interval_index = pd.IntervalIndex.from_tuples([(1.0, np.inf), (-np.inf, 0.0), (0.0, 1.)], name='interval')
foo_index = pd.Index([1, 2, 3], name='foo')
multi_index = pd.MultiIndex.from_product([foo_index, interval_index])
print(multi_index.get_level_values('foo').get_indexer_for([2]))
print(multi_index.get_level_values('interval').get_indexer_for([pd.Interval(-np.inf, 0.0)]))
multi_index = pd.MultiIndex.from_product([interval_index, foo_index])
print(multi_index.get_level_values('foo').get_indexer_for([2]))
print(multi_index.get_level_values('interval').get_indexer_for([pd.Interval(-np.inf, 0.0)]))Issue Description
get_indexer_for() does not return a list of indeces as described in the docs but a mask like list under some circumstances.
As far as I have investigated, the behavior occurs if all of the following conditions are met:
- the index is a
MultiIndex - the level in question is a
IntervalIndex - the level in question is not the first level of the
MultiIndex
The script above outputs
[3 4 5]
[0 1 0 0 1 0 0 1 0]
[1 4 7]
[3 4 5]
Expected Behavior
Expected output
[3 4 5]
[1 4 7]
[1 4 7]
[3 4 5]
Installed Versions
INSTALLED VERSIONS
commit : 3a6d4cd
python : 3.9.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-88-lowlatency
Version : #99-Ubuntu SMP PREEMPT Thu Sep 23 18:30:52 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : de_DE.UTF-8
LOCALE : de_DE.UTF-8
pandas : 1.4.0.dev0+933.g3a6d4cd01d
numpy : 1.21.2
pytz : 2021.3
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : None
pytest : 6.2.5
hypothesis : 6.23.3
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None