BUG: slicing a MultiIndex does not preserve the sequence of the index since pandas 1.2.0rc0 · Issue #40978 · pandas-dev/pandas (original) (raw)
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Between 1.1.5 and 1.2.0rc2 the behavior of slicing MultiIndexes has changed. Up to 1.1.5 slicing a MultiIndex like df.loc[(slice(None), somel_items), :]
preserved the sequence of the sliced DataFrame
. From 1.2.0rc0 the sequence is changed.
Code Sample
import pandas as pd
print("pandas version %s" % pd.version)
index = pd.MultiIndex.from_tuples([(1, 1), (1, 2), (1, 7), (1, 6), (2, 2), (2, 3), (2, 8), (2, 7)])
all_items = index.get_level_values(1) # all items from level 1
df = pd.DataFrame({'x': range(8)}, index=index)
df_sliced = df.loc[(slice(None), all_items), :]
df_sliced, should be identical with df, as all_items contains all items from level 1
print(df_sliced)
pd.testing.assert_frame_equal(df, df_sliced)
works if and only if pd.version < 1.2.0rc0
print("Success")
Problem description
Running the sample code in 1.1.5 gives the following output:
pandas version 1.1.5
x
1 1 0
2 1
7 2
6 3
2 2 4
3 5
8 6
7 7
Success
whereas in 1.2.4 it gives
pandas version 1.2.4
x
1 1 0
6 3
2 1
2 2 4
3 5
8 6
1 7 2
2 7 7
Traceback (most recent call last):
File "tmp/pandas_demo.py", line 19, in <module>
pd.testing.assert_frame_equal(df, df_sliced)
File "/home/jmu3si/Devel/pylife/.venv/lib/python3.8/site-packages/pandas/_testing.py", line 1657, in assert_frame_equal
assert_index_equal(
File "/home/jmu3si/Devel/pylife/.venv/lib/python3.8/site-packages/pandas/_testing.py", line 805, in assert_index_equal
assert_index_equal(
File "/home/jmu3si/Devel/pylife/.venv/lib/python3.8/site-packages/pandas/_testing.py", line 825, in assert_index_equal
_testing.assert_almost_equal(
File "pandas/_libs/testing.pyx", line 46, in pandas._libs.testing.assert_almost_equal
File "pandas/_libs/testing.pyx", line 161, in pandas._libs.testing.assert_almost_equal
File "/home/jmu3si/Devel/pylife/.venv/lib/python3.8/site-packages/pandas/_testing.py", line 1073, in raise_assert_detail
raise AssertionError(msg)
AssertionError: MultiIndex level [0] are different
MultiIndex level [0] values are different (25.0 %)
[left]: Int64Index([1, 1, 1, 1, 2, 2, 2, 2], dtype='int64')
[right]: Int64Index([1, 1, 1, 2, 2, 2, 1, 2], dtype='int64')
I am not sure if this is necessarily a problem, I stumbled across it because a test suite that used pd.testing.assert_frame_equal()
failed due to this. So either the actual sequence should be preserved when slicing a DataFrame
or pd.testing.assert_frame_equal()
should not fail if the sequence is shuffled (but the index is correct).
Expected Output
As discussed above.
Output of pd.show_versions()
INSTALLED VERSIONS
commit : 2cb9652
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-71-lowlatency
Version : #79-Ubuntu SMP PREEMPT Wed Mar 24 12:38:51 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : de_DE.UTF-8
LOCALE : de_DE.UTF-8
pandas : 1.2.4 (resp. 1.1.5)
numpy : 1.20.2
pytz : 2021.1
dateutil : 2.8.1
pip : 20.2.4
setuptools : 50.3.0.post20201006
Cython : 0.29.23
pytest : 6.2.3
hypothesis : None
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 : 3.4.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : None
tables : None
tabulate : None
xarray : 0.17.0
xlrd : None
xlwt : None
numba : None