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BUG: unstack with sort=False fails when used with the level parameter #54987

Closed
3 tasks done
m-amin-alavian opened this issue Sep 3, 2023 · 10 comments · Fixed by #56357
Closed
3 tasks done

BUG: unstack with sort=False fails when used with the level parameter #54987

m-amin-alavian opened this issue Sep 3, 2023 · 10 comments · Fixed by #56357
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Labels
Bug Reshaping Concat, Merge/Join, Stack/Unstack, Explode

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@m-amin-alavian
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Pandas version checks

  • I have checked that this issue has not already been reported.

  • I have confirmed this bug exists on the latest version of pandas.

  • I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

index = pd.MultiIndex.from_tuples(
    [
        (2020, 'Urban'),
        (2020, 'Rural',),
        (2021, 'Urban'),
        (2021, 'Rural',),
    ],
    names=["Year", "Urban_Rural"]
)
data = pd.Series(
    [21, 11, 22, 12],
    index=index
)

# sort = True:
data.unstack(0)

# | Urban_Rural   |   2020 |   2021 |
# |:--------------|-------:|-------:|
# | Rural         |     11 |     12 |
# | Urban         |     21 |     22 |


# sort = False
data.unstack(0, sort=False)

# | Urban_Rural   |   2020 |   2021 |
# |:--------------|-------:|-------:|
# | Urban         |     21 |     11 |
# | Rural         |     22 |     12 |


# sort = False without level
data.unstack(sort=False)

# |   Year |   Urban |   Rural |
# |-------:|--------:|--------:|
# |   2020 |      21 |      11 |
# |   2021 |      22 |      12 |

Issue Description

The issue occurs when using the unstack method in pandas with the sort=False parameter and a specified level. In this scenario, the values within the resulting DataFrame are not affected by the specified level and are displayed as if the level is set to its default value, -1. However, the labels are correctly applied, leading to an incorrect resulting DataFrame.

Expected Behavior

When using unstack with level and sort=False, the resulting DataFrame should correctly reflect the values from the input data.

Installed Versions

INSTALLED VERSIONS

commit : 4b456e2
python : 3.11.2.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22621
machine : AMD64
processor : Intel64 Family 6 Model 165 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.2.0dev0+171.g4b456e232
numpy : 1.25.2
pytz : 2023.3
dateutil : 2.8.2
setuptools : 65.5.0
pip : 23.2.1
Cython : None
pytest : 7.4.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.11.0
pandas_datareader : None
bs4 : None
bottleneck : 1.3.7
dataframe-api-compat: None
fastparquet : 2023.8.0
fsspec : 2023.6.0
gcsfs : None
matplotlib : 3.7.1
numba : None
numexpr : 2.8.5
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 13.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

@m-amin-alavian m-amin-alavian added Bug Needs Triage Issue that has not been reviewed by a pandas team member labels Sep 3, 2023
@rhshadrach
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rhshadrach commented Sep 9, 2023

Edit: My assessment here is incorrect; this issue is independent of the codes being sorted.

Thanks for the report! I took a look into this - it appears to me that the unstack algorithm depends on the codes being sorted. I tried implementing a method similar to our new implementation of stack (you essentially just have to replace index <--> columns everywhere), but this introduces a huge performance regression (10-100x) because unstack is cythonized.

My hope is that we can remove the assumption of sorted codes from the unstack algorithm and keep the performance, then apply this to stack as well. But I'm not sure this is doable.

In the meantime, I didn't see any quick fix to make sort=False work in unstack but I'm still looking.

cc @mroeschke

@rhshadrach rhshadrach added Reshaping Concat, Merge/Join, Stack/Unstack, Explode and removed Needs Triage Issue that has not been reviewed by a pandas team member labels Sep 9, 2023
@renanffernando
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take

@johentsch
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Hi there, it seemed to me my issue was a duplicate of #55516 but @m-amin-alavian was referred to this posting here so I'm adding my example to this issue, too.

My issue arises when doing .unstack(sort=False) on this series with 2996 items below -- but not if I do it only on the first 2990, which is why I'm posting the entire data.

Code for initializing the series

index = pd.MultiIndex.from_tuples(
[
('V', 'I'),
('V', 'i'),
('V', 'I6'),
('V', 'V7'),
('V', 'i6'),
('V', ''),
('V', 'V2'),
('V', 'V65'),
('V', 'iii6'),
('V', 'V6'),
('V', 'vi'),
('V', 'iv6(2)'),
('V', 'i(9)'),
('V', 'iv6'),
('V', 'IV6'),
('V', 'IV6(2)'),
('V', 'I(9)'),
('V', 'VI'),
('V', 'iii'),
('V', 'vi7'),
('V', 'V6/iv'),
('V', 'ii'),
('V', 'V(64)'),
('V', 'V'),
('V', 'V43'),
('V', 'iv7'),
('V', 'vi(9)'),
('V', 'ii%43'),
('V', 'i64'),
('V', 'III+6'),
('V', 'iv'),
('V', 'I64'),
('V', 'III'),
('V', 'V65/iv'),
('V', 'VI6'),
('V', 'V(6)'),
('V', 'V6/vi'),
('V', 'IV'),
('V', 'ii6'),
('V', 'ii(4)'),
('V', 'i/v'),
('V', 'ii43'),
('V', 'vi6'),
('V', 'v'),
('V', 'v6'),
('V', 'V/iv'),
('V', '#vi%7'),
('V', 'IM65'),
('V', 'V(4)/V'),
('V', 'vi2'),
('V', 'III6'),
('V', 'IVM7'),
('V', 'V6/V'),
('V', 'iio6'),
('V', 'viio7/V'),
('V', 'IM7'),
('V', 'I(2)'),
('V', '#viio/vi'),
('V', '#viio43'),
('V', 'IV65'),
('V', 'I6/V'),
('V', 'ii%65'),
('V', '#viio6'),
('V', 'iii7'),
('V', 'V65/vi'),
('V', 'V65/IV'),
('V', 'IIIM7'),
('V', 'III+M7'),
('V', 'viio64'),
('V', 'iv6(4)'),
('V', 'iv6(9)'),
('V', 'iv64'),
('V', 'iv64(2)'),
('V', 'iv65(2)'),
('V', 'vi6(2)'),
('V', 'iv7(9)'),
('V', 'I/III'),
('V', 'I(4)'),
('V', 'viio6/V'),
('V', 'iio65'),
('V', 'viio6(2)/V'),
('V', '#viio64'),
('V', 'vi7(9)'),
('V', 'v64'),
('V', '#vi%2'),
('V', 'IV(2)'),
('V', 'V(4)'),
('V', 'VI(#4)'),
('V', 'VM2'),
('V', 'V65/V'),
('V', 'i(2)'),
('V', 'i(6v5)'),
('V', 'V43/V'),
('V', 'V/vi'),
('V', 'V/V'),
('V', 'i65'),
('V', 'V/IV'),
('V', 'IVM7(9)'),
('V', 'iio/v'),
('V', 'ii(9)/V'),
('V', 'ii2/V'),
('V', 'IVM65/III'),
('V', 'IV7'),
('V', 'ii6(2)'),
('V', 'ii6(2)/III'),
('V', 'ii65/V'),
('V', 'ii7/V'),
('V', 'IV(9)'),
('V', 'V7/IV'),
('V', 'V7/iv'),
('I', ''),
('I', 'V'),
('I', 'I6'),
('I', 'V6'),
('I', 'IV'),
('I', 'V(4)'),
('I', 'vi'),
('I', 'vi6'),
('I', 'ii65'),
('I', 'V65'),
('I', 'IV6'),
('I', 'viio6'),
('I', 'V7'),
('I', 'I'),
('I', 'ii2'),
('I', 'ii(9)'),
('I', 'V43'),
('I', 'IVM65'),
('I', 'IV(9)'),
('I', 'IVM7'),
('I', 'ii6'),
('I', 'IV64'),
('I', 'ii7'),
('I', 'V(64)'),
('I', 'ii'),
('I', 'ii6(2)'),
('I', 'V2'),
('I', 'IM2'),
('I', 'V7/IV'),
('I', 'viio'),
('I', 'V43/V'),
('I', 'viio6(2)'),
('I', 'V65/IV'),
('I', 'viio(2)'),
('I', 'I(64)'),
('I', 'iv'),
('I', 'viio6/V'),
('I', 'I64'),
('I', 'i'),
('I', 'iii6'),
('I', 'vi7'),
('I', 'V7/V'),
('I', 'iii'),
('I', 'iv6'),
('I', 'V2/IV'),
('I', 'V6(4)'),
('I', 'V2/V'),
('I', 'IV7'),
('I', 'ii6/V'),
('I', 'I(6)'),
('I', 'I6/V'),
('I', 'ii(4)'),
('I', 'IM65'),
('I', 'i6/iii'),
('I', 'IV65'),
('I', 'v6'),
('I', 'V43(4)/V'),
('I', 'V6(2)'),
('I', 'V64'),
('I', 'vii%7/V'),
('I', 'viio/IV'),
('I', 'ii7/V'),
('I', 'ii7(9)'),
('I', 'iio6/vi'),
('I', 'vi6(2)'),
('I', 'ii65(2)'),
('I', 'vii%7'),
('I', 'vi65'),
('I', 'iv7'),
('I', 'V65/ii'),
('I', 'ii43'),
('I', 'ii/IV'),
('I', 'I/V'),
('I', 'I6/IV'),
('I', 'IM7'),
('I', 'IV(97)'),
('I', 'IV/IV'),
('I', 'IV6(2)/IV'),
('I', 'IV6/IV'),
('I', 'IV65/vi'),
('I', 'IVM7(9)'),
('I', 'V(4)/V'),
('I', 'V/V'),
('I', 'V/ii'),
('I', 'V2/iv'),
('I', 'V43(4)'),
('I', 'V6(6)'),
('I', 'V65/V'),
('I', 'V65/iv'),
('I', 'V65/vi'),
('I', 'V7(9)/IV'),
('I', 'VIM7'),
('I', 'ii%7'),
('I', 'ii(2)/vi'),
('I', 'ii(94)'),
('I', 'viio64'),
('i', ''),
('i', 'V'),
('i', 'i6'),
('i', 'V6'),
('i', 'V(4)'),
('i', 'v6'),
('i', 'V65'),
('i', 'iv'),
('i', 'VI6'),
('i', 'ii%65'),
('i', 'iv6'),
('i', 'VI'),
('i', 'ii%2'),
('i', 'V43'),
('i', 'ii%43'),
('i', '#viio6'),
('i', 'IV'),
('i', 'iv7'),
('i', 'V/iv'),
('i', 'v'),
('i', 'V7'),
('i', 'III'),
('i', '#viio'),
('i', 'i'),
('i', 'V2'),
('i', 'iio6(2)'),
('i', 'v(4)'),
('i', 'iv64'),
('i', 'i2'),
('i', 'iv7(9)'),
('i', 'iv(9)'),
('i', 'VIM7'),
('i', 'iv6(2)'),
('i', 'V65/iv'),
('i', '#viio(2)'),
('i', '#viio65'),
('i', 'V7/iv'),
('i', 'III6'),
('i', 'ii%7'),
('i', 'IV7'),
('i', 'V6/III'),
('i', 'iio6'),
('i', 'V6/iv'),
('i', 'bII6'),
('i', 'V(64)'),
('i', '#viio6/iv'),
('i', 'V2/iv'),
('i', 'v6(4)'),
('i', 'IV7(9)'),
('i', 'ii65'),
('i', 'ii6(2)'),
('i', 'ii%7(9)'),
('i', '#viio/iv'),
('i', 'i64'),
('i', 'III+6'),
('i', 'iio7'),
('i', 'i/v'),
('i', 'viio/IV'),
('i', 'i7'),
('i', 'ii%65(2)'),
('i', 'IV(9)'),
('i', 'IV6(2)/VI'),
('i', 'I6/III'),
('i', 'ii/III'),
('i', 'ii2'),
('i', 'ii6'),
('i', 'viio6/VII'),
('i', 'IV6'),
('i', 'IV65'),
('i', 'V6(4)'),
('i', '#vi%65'),
('i', 'vi6'),
('i', 'V43/VII'),
('i', 'V7/III'),
('i', 'ii7/III'),
('i', 'V/V'),
('i', 'V2(64)'),
('i', 'viio(2)/III'),
('i', 'viio/iv'),
('i', 'v6(+4)'),
('i', '#vi%7'),
('i', 'v(2)'),
('i', 'iio6(112)'),
('i', 'iv7(#6#4)'),
('i', 'v64'),
('i', 'v6(2)'),
('i', 'iio6(42)'),
('i', 'v7'),
('i', 'iv65'),
('i', 'vi65'),
('i', 'vi7/III'),
('i', 'iv43'),
('i', 'iio(9)'),
('i', '#vio6'),
('i', 'ii7'),
('i', 'V65(4)'),
('i', 'I/III'),
('i', 'I6'),
('i', 'IV/III'),
('i', 'IV6/III'),
('i', '#viio64'),
('i', 'V(4)/III'),
('i', 'V(5)'),
('i', 'V/III'),
('i', 'V/VII'),
('i', 'V6(+4)'),
('i', 'V6(2)'),
('i', 'V6(2)/III'),
('i', 'V6/VII'),
('i', 'V64'),
('i', 'V65/III'),
('i', 'ii65/III'),
('i', 'V65/V'),
('i', 'V65/VII'),
('i', 'V7(6)'),
('i', 'V7/IV'),
('i', '#viio43'),
('i', 'VII'),
('i', 'VII(2)'),
('i', 'VII6'),
('i', 'I'),
('i', 'bII6(2)'),
('i', 'i(6)'),
('i', '#viio(42)'),
('i', 'ii%65/v'),
('i', 'ii(4)'),
('i', 'viio64/iv'),
('I6', 'IV'),
('I6', 'ii65'),
('I6', 'I'),
('I6', 'V43'),
('I6', 'V'),
('I6', 'ii7'),
('I6', 'IV(9)'),
('I6', 'V(4)'),
('I6', 'vi'),
('I6', 'viio6'),
('I6', ''),
('I6', 'ii6'),
('I6', 'IVM7'),
('I6', 'V6'),
('I6', 'viio6(2)'),
('I6', 'ii'),
('I6', 'IV6'),
('I6', 'V65'),
('I6', 'V(64)'),
('I6', 'vi7'),
('I6', 'ii6(2)'),
('I6', 'vi6'),
('I6', 'V7/IV'),
('I6', 'IM7'),
('I6', 'I64'),
('I6', 'V(4)/V'),
('I6', 'IVM65'),
('I6', 'V65/V'),
('I6', 'I6'),
('I6', 'IV7'),
('I6', 'IVM7(9)'),
('I6', 'ii43'),
('I6', 'IVM2'),
('I6', 'ii(9)'),
('I6', 'iv7'),
('I6', 'viio'),
('I6', 'ii2'),
('I6', 'ii%7'),
('I6', 'V7'),
('I6', 'viio64'),
('I6', 'V65/IV'),
('I6', 'V6/V'),
('I6', 'IV6(2)'),
('I6', 'V7/V'),
('I6', 'IV65'),
('I6', 'viio6/V'),
('I6', 'viio6(2)/V'),
('I6', 'I7'),
('I6', 'IM65'),
('I6', 'viio(2)'),
('I6', 'IV(97)'),
('I6', 'vii6(2)'),
('I6', 'vii%7/V'),
('I6', 'vi64'),
('I6', 'IV6/IV'),
('I6', 'VI'),
('I6', 'V(64)/V'),
('I6', 'V/ii'),
('I6', 'V2'),
('I6', 'ii6(9)'),
('I6', 'ii6(42)'),
('I6', 'V43/V'),
('I6', 'ii6(112)'),
('I6', 'ii43(42)'),
('I6', 'V64'),
('I6', 'V7(4)'),
('I6', 'ii(2)'),
('I6', 'iii'),
('V7', 'I'),
('V7', 'i'),
('V7', 'vi'),
('V7', 'VI'),
('V7', 'V(64)'),
('V7', 'I(9)'),
('V7', 'i6'),
('V7', 'I6'),
('V7', 'V65'),
('V7', 'i(9)'),
('V7', 'iv7'),
('V7', 'I64'),
('V7', 'iii6'),
('V7', 'IM7'),
('V7', 'V'),
('V7', ''),
('V7', 'i64'),
('V7', 'V/iv'),
('V7', 'i(4)'),
('V7', 'IVM7'),
('V7', 'IV6'),
('V7', 'vi6(2)'),
('V7', 'iv6'),
('V7', 'viio7/V'),
('V7', 'VI(64)'),
('V7', 'vi64'),
('V7', 'I(2)'),
('V7', 'I(4)'),
('V7', '#vi%7'),
('V7', 'III+6'),
('V7', 'iv6(2)'),
('V7', 'bVI'),
('V7', 'iM7'),
('V7', 'vi(9)'),
('V7', 'ii43'),
('V7', 'iii'),
('V7', 'iv7(9)'),
('V7', 'iv(2)'),
('V7', 'V64'),
('V7', 'VM7/IV'),
('V7', 'IV'),
('V7', '#viio'),
('V7', '#viio7'),
('V7', '#viio7/vi'),
('V7', 'I(7)'),
('V7', 'I7'),
('V7', 'III+M7(9)'),
('V7', 'IIIM7(9)'),
('V7', 'IVM7(9)'),
('V7', 'VI(+6)'),
('V7', 'V(4)'),
('V7', 'V(6)'),
('V7', 'V/IV'),
('V7', 'V2'),
('V7', 'V43'),
('V7', 'V7'),
('V7', 'V7(9)'),
('V7', 'viio7/vi'),
('i6', 'ii%65'),
('i6', 'i'),
('i6', 'V43'),
('i6', 'iv'),
('i6', 'V65'),
('i6', 'V'),
('i6', 'ii%7'),
('i6', 'IV'),
('i6', 'V(4)'),
('i6', 'iv7'),
('i6', ''),
('i6', '#viio6'),
('i6', 'V6'),
('i6', 'iv(9)'),
('i6', 'IV(9)'),
('i6', 'ii65'),
('i6', 'VI'),
('i6', 'iio6'),
('i6', 'iv6'),
('i6', 'VIM7'),
('i6', '#viio65'),
('i6', 'V(64)'),
('i6', 'i7'),
('i6', 'ii7'),
('i6', 'IV7(9)'),
('i6', 'VII6'),
('i6', '#vi%7'),
('i6', 'bII6'),
('i6', 'ii%43'),
('i6', 'VI6'),
('i6', 'v(4)'),
('i6', '#viio6(2)'),
('i6', 'ii6'),
('i6', 'i64'),
('i6', 'IV2'),
('i6', '#viio43'),
('i6', '#viio/iv'),
('i6', 'i65'),
('i6', 'iv7(9)'),
('i6', 'viio6'),
('i6', 'III'),
('i6', 'V7'),
('i6', 'IV6(2)/VI'),
('i6', 'V2'),
('i6', 'iv2'),
('i6', 'iio65'),
('i6', 'V/v'),
('i6', 'iv%7'),
('i6', 'iv(6)'),
('i6', 'V/iv'),
('i6', 'iv(97)'),
('i6', 'iv6(2)'),
('i6', 'V/III'),
('i6', 'iio6(24)'),
('i6', 'iv65'),
('i6', '#vii6(2)'),
('i6', 'iv7(#6#4)'),
('i6', 'iv7(^6#4)'),
('i6', 'IV7'),
('i6', 'vi65'),
('i6', 'iio6(94)'),
('i6', 'iio6(112)'),
('i6', 'iio6(2)'),
('i6', 'IVM65/III'),
('i6', 'bII6(2)'),
('i6', 'I65'),
('i6', 'i(6)'),
('i6', 'V65/iv'),
('i6', 'V65/III'),
('i6', 'ii%2'),
('i6', 'III+(6)'),
('i6', 'ii%65(9)'),
('i6', 'V7/iv'),
('i6', '#vio6'),
('i6', 'V64'),
('i6', 'ii6(2)'),
('i6', 'III+6'),
('i6', 'iio'),
('i6', 'iio(9)'),
('i6', '#viio64'),
('i6', '#vio64'),
('IV', 'V7'),
('IV', 'ii6'),
('IV', 'ii'),
('IV', 'I6'),
('IV', 'V'),
('IV', 'I'),
('IV', 'V(4)'),
('IV', 'IV6'),
('IV', 'V43'),
('IV', ''),
('IV', 'V2'),
('IV', 'ii7'),
('IV', 'I(4)'),
('IV', 'V6/V'),
('IV', 'viio6'),
('IV', 'V65'),
('IV', 'V/V'),
('IV', 'ii65'),
('IV', 'i'),
('IV', 'V65/V'),
('IV', 'vi'),
('IV', 'IV2'),
('IV', '#viio6'),
('IV', 'viio64'),
('IV', 'V(64)'),
('IV', 'vii%7'),
('IV', 'vii%65'),
('IV', 'IV(6)'),
('IV', 'IVM2'),
('IV', 'iio'),
('IV', 'V(9)'),
('IV', 'iio6'),
('IV', 'viio/V'),
('IV', 'IVM7'),
('IV', 'I64'),
('IV', 'iv65'),
('IV', 'iv'),
('IV', 'V/IV'),
('IV', 'iv7'),
('IV', 'iii6(2)'),
('IV', 'vi6'),
('IV', 'viio'),
('IV', 'IV7'),
('IV', 'vi(b6)'),
('IV', 'ii7(9)'),
('IV', 'iii(2)'),
('IV', 'ii7/vi'),
('IV', 'V6'),
('IV', '#vii64'),
('IV', 'ii43'),
('IV', 'ii%65/vi'),
('IV', 'V(+4)'),
('IV', 'V(2)'),
('IV', 'VII'),
('IV', 'V7/V'),
('IV', 'V7/III'),
('IV', '#vi'),
('IV', 'I(64)'),
('IV', 'V65/IV'),
('IV', 'i6/vi'),
('V(4)', 'V'),
('V(4)', 'V7'),
('V(4)', ''),
('V(4)', 'V6'),
('V(4)', 'iv7'),
('V(4)', 'v'),
('V(4)', '#viio/vi'),
('V(4)', 'V65/vi'),
('V(4)', 'I6'),
('V(4)', 'I'),
('V(4)', 'V2'),
('V(4)', 'V6/V'),
('V(4)', 'V65'),
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('i(6)', 'v6(2)'),
('i(4)/iv', 'i/iv'),
('iii%43', 'IV6(2)'),
('iii%43', 'vi7'),
('IV6(72)', 'IV6'),
('V65(2)', 'V65'),
('iio6/iv', 'V(9)/iv'),
('iio6/iv', 'V/iv'),
('bVI', 'i6'),
('ii6(9)', 'ii6'),
('IVM7/III', 'V(4)/III'),
('IVM7/V', 'V(4)/V'),
('IVM7/V', 'viio64/V'),
('V7/VI', ''),
('V7/VI', 'I(7)/VI'),
('ii65(2)', 'V(4)'),
('V(#64)', 'V7'),
('V(#64)', 'i'),
('iv7(#6#4)', 'iv7'),
('iio6(24)', 'iio6'),
('iii7(9)', 'I6'),
('iio6(2)/v', 'iio6/v'),
('iio/vi', 'V7/vi'),
('iio64(72)', 'iio6'),
('iio6(94)', 'iio6'),
('iio64(42)', 'iio64'),
('iio6/V', 'iv'),
('iio/v', 'V43'),
('iio6/vi', 'iv7/vi'),
('iio6(b2)/v', 'iio6/V'),
('#vi', 'V65/V'),
('iv%7', 'ii'),
('vii%43/IV', 'vi7'),
('vi(94)', 'vi'),
('vi/VI', 'ii7/VI'),
('vi/v', 'ii%65/v'),
('vi6(2)/vi', 'vi6/vi'),
('vi6/vi', 'V/vi'),
('vi64/III', 'ii7/III'),
('vi7(9)', 'IV'),
('vi7/III', 'viio/III'),
('vi7/iv', 'V65/iv'),
('vi7/v', 'iv6/v'),
('vii%7/VI', 'I(4)/VI'),
('iv(9)/iv', 'iv/iv'),
('vii2', 'iii6'),
('vii6(2)', 'viio6'),
('viio/V/iv', 'V(9)/iv'),
('viio/VII', 'v6'),
('viio6(2)/III', 'viio6/III'),
('viio6/IV', 'IV'),
('viio64/IV', 'IV'),
('viio64/iv', 'iv6'),
('viio7(2)/V', 'viio7/V'),
('viio7/IV', 'IV(4)'),
('vi(11)', 'vi'),
('vi%7/V', 'ii7/V'),
('vi%43/V', 'ii7/V'),
('v7(9)', 'III6'),
('iv(9)/vi', 'iv/vi'),
('iv(94)', 'ii7'),
('iv/ii', 'VI/ii'),
('iv43', 'VII7'),
('iv6(2)/iii', 'iv6/iii'),
('iv6(2)/v', 'iv6/v'),
('iv6(2)/vi', 'iio/vi'),
('iv6(4)', 'iv6'),
('iv6/iii', 'V7/iii'),
('iv64(2)', 'iv64'),
('iv64(72)', 'iv6'),
('iv65(2)', 'ii%43'),
('iv7(^6#4)', 'iv7'),
('iv7(^6^#4)', 'iv7'),
('v/iv', 'ii6(2)/VI'),
('v2', 'I6'),
('v6(+4)', 'VI'),
('v6(b2)', 'v6'),
('v6/iv', 'v/iv'),
('v6/vi', 'iv6/vi'),
('v65', 'i64(72)'),
('vi(64)', 'vi'),
('VII6(2)', 'VII(6)'),
('iii6(72)/V', 'iii6/V'),
('V7(9)/IV', ''),
('V(97)', 'i64'),
('V(7)', 'V(64)'),
('V(64)/v', 'VI(7)/v'),
('V(64)/iv', 'V(4)/iv'),
('V(64)/I', 'V'),
('V(6)/V', 'V7/V'),
('V(5)', 'V'),
('V(4)/iii', 'V/iii'),
('IV65/vi', 'V65/vi'),
('IV6/iv', 'V65/iv'),
('IV6(94)', 'IV6'),
('IV6(72)/V', 'IV6/V'),
('IV6(62)', 'IV6'),
('IV6(2)/IV', 'IV6/IV'),
('IV43', 'V65'),
('V2/III', ''),
('V2/v', 'i6/v'),
('V43(4)', 'V43'),
('V65(2)/III', 'V65/III'),
('V7(6)', 'V7'),
('V7(4)/III', 'V7/III'),
('V7(-3)', 'i'),
('V65(9)', 'V65'),
('V65(4)', 'V65'),
('V65(2)/V', 'V65/V'),
('V64/V', 'V'),
('V43/V/V', 'V/V'),
('V6/V/V', 'V/V'),
('V6(9)', 'V6'),
('V6(6)', 'vi'),
('V6(2)/III', 'V6/III'),
('V6(+4)', 'i'),
('V6(#72)', 'V6'),
('IV/IV', 'viio/IV'),
('IV(b4)', 'IV'),
('IV(+9)', 'I6'),
('#viio64/ii', 'V/ii'),
('I(94)', 'I6'),
('I(9)/IV', 'V7'),
('I(7)/VI', 'iv6'),
('I(7)', 'I'),
('I(4)/VI', 'I/VI'),
('#viio64/vii', 'VII6'),
('#viio(42)', '#viio'),
('I6(2)/III', 'I6/III'),
('#viio(4)', '#viio'),
('#viio(2)/iv', 'V6/iv'),
('#vii64', 'i6'),
('#vii6(2)', '#viio6'),
('#vii%7', 'i6'),
('#vi%43', 'V43'),
('I/VI', 'i6'),
('I6(2)/VI', 'vi/VI'),
('IM43(42)', 'IM43'),
('III+(6)', 'V65'),
('III65', 'i6'),
('III64(72)', 'III6'),
('III/vi', 'iv6(2)/vi'),
('III/v', 'i6/v'),
('III+7(9)', 'i6'),
('III+65', 'VI'),
('III(6)', 'IV'),
('I6(42)', 'I6'),
('II', 'III+M7(9)'),
('I65', 'iv(97)'),
('I64(7)', 'I'),
('I64(4)/III', 'vi64/III'),
('I6/IV', 'ii7/IV'),
('I6(9)', 'I6'),
('V7(9)', 'i'),
('V7/VII', 'V/III'),
('iii6(72)', 'iii6'),
('V7/vii', 'vii'),
('ii6(2)/V', 'ii6/V'),
('ii6(2)/III', 'ii6/III'),
('ii6(112)', 'ii6'),
('ii43(42)', 'ii43'),
('ii2/III', 'V6/III'),
('ii/vi', 'V65/vi'),
('ii/V', 'iii6(72)/V'),
('ii/IV', 'IV6/IV'),
('ii(97)', 'V'),
('ii(94)', 'ii'),
('ii(9)/V', 'V65/V'),
('ii(9)/III', 'V7/III'),
('ii(62)', 'ii6'),
('ii(6)', 'iv7'),
('ii(2)/vi', 'ii/vi'),
('ii6(2)/VI', 'ii6/VI'),
('ii6(42)', 'ii'),
('ii6(72)/V', 'ii6/V'),
('ii7/vi', 'V/vi'),
('iii6(7)', 'iii6'),
('iii6(2)/V', 'iii6/V'),
('iii/V', 'IV6(72)/V'),
('iii(64)', 'iii'),
('iii(6)', 'iii7'),
('iii(2)', 'iii'),
('ii7/iv', 'V65/iv'),
('ii6(b2)', 'ii6'),
('ii7/VI', 'V7/VI'),
('ii65/ii', 'V/ii'),
('ii65/IV', 'V2/IV'),
('ii64(2)', 'ii64'),
('ii6/VI', 'I6(2)/VI'),
('ii6/III', 'I6(2)/III'),
('ii%7/iv', 'V7/iv'),
('ii%65/ii', 'V/ii'),
('ii%65(9)', 'ii%65'),
('VI6/vi', 'v6/vi'),
('VIM7(9)', 'iv6'),
('VII64', 'V2/VII'),
('VII43', 'III64(72)'),
('VII(9)', 'v'),
('VII(6)', 'v6'),
('VII(2)', 'v6'),
('VI6/v', 'III/v'),
('VM2', 'iii(6)'),
('VI/ii', 'ii65/ii'),
('VI(b4)', 'VI'),
('VI(7)/v', 'iio6/v'),
('VI(2)', 'iv6'),
('VI(+6)', 'V7'),
('VI(#4)', 'i6'),
('VIM7/vi', 'ii%7/vi'),
('VM7/IV', 'IVM7'),
('ii%43(42)', 'ii%43'),
('i6(4)', 'III6'),
('iM7(9)', 'i6'),
('iM7', 'IV7'),
('i64(72)', 'i6'),
('i64(7)', 'i'),
('i64(42)', 'i64'),
('i64(2)', 'i6'),
('i6(11)', 'i6'),
('bII6/vi', 'iv/vi'),
('i(6v5)/iv', 'i(64)/iv'),
('i(6v5)', 'i(64)'),
('i(64)/iv', 'V/iv'),
('i(64)', 'i(4)'),
('bii6/vi', 'iv/vi'),
('bIII+M7(9)', 'i6'),
('viio7/vi', 'vi'),
], 
names=["antecedent", "consequent"])
s = pd.Series(
[
720,
650,
205,
164,
152,
138,
91,
58,
53,
46,
40,
38,
31,
31,
30,
27,
25,
19,
18,
17,
15,
14,
14,
14,
11,
11,
10,
9,
8,
8,
7,
7,
7,
7,
7,
6,
6,
6,
6,
6,
6,
6,
5,
5,
5,
5,
5,
5,
5,
5,
4,
4,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
456,
267,
214,
179,
128,
125,
73,
70,
54,
49,
41,
35,
34,
28,
26,
25,
25,
23,
22,
20,
19,
18,
15,
14,
14,
11,
9,
9,
9,
8,
8,
7,
7,
6,
6,
5,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
391,
273,
138,
107,
103,
83,
64,
57,
54,
52,
31,
31,
27,
25,
22,
20,
20,
17,
15,
14,
14,
12,
12,
12,
11,
11,
10,
10,
9,
9,
9,
8,
7,
7,
6,
6,
6,
6,
6,
5,
5,
5,
5,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
201,
197,
138,
63,
55,
48,
45,
26,
24,
23,
21,
20,
18,
16,
16,
12,
11,
10,
10,
9,
8,
7,
6,
6,
5,
4,
4,
4,
4,
4,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
336,
210,
90,
66,
53,
28,
24,
20,
10,
8,
8,
7,
6,
6,
6,
5,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
134,
84,
81,
67,
44,
39,
32,
24,
23,
23,
22,
21,
19,
17,
16,
11,
10,
9,
8,
8,
8,
7,
7,
7,
6,
4,
4,
4,
4,
4,
4,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
84,
75,
68,
55,
51,
50,
36,
26,
25,
25,
18,
18,
13,
12,
11,
9,
7,
6,
6,
6,
5,
4,
4,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
557,
39,
10,
6,
6,
5,
3,
3,
3,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
195,
163,
114,
22,
19,
18,
16,
15,
9,
9,
6,
4,
3,
3,
3,
3,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
145,
99,
68,
36,
27,
21,
20,
16,
15,
13,
12,
12,
11,
11,
7,
7,
6,
5,
4,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
70,
70,
47,
31,
30,
12,
12,
12,
11,
10,
10,
10,
8,
8,
6,
5,
4,
4,
4,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
65,
28,
28,
25,
18,
18,
18,
15,
14,
14,
14,
12,
9,
9,
8,
7,
7,
6,
6,
6,
6,
5,
5,
5,
4,
4,
4,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
212,
47,
34,
17,
11,
10,
8,
8,
7,
6,
3,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
210,
66,
28,
15,
11,
10,
8,
7,
7,
4,
3,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
79,
30,
30,
21,
18,
18,
18,
17,
17,
16,
13,
11,
8,
8,
7,
5,
4,
4,
3,
3,
3,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
127,
39,
21,
21,
13,
11,
8,
8,
7,
6,
4,
4,
4,
4,
4,
3,
3,
3,
3,
3,
3,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
86,
58,
43,
26,
26,
11,
10,
9,
7,
6,
6,
6,
3,
3,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
90,
85,
45,
32,
27,
6,
4,
3,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
121,
117,
7,
6,
4,
4,
3,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
61,
42,
27,
13,
9,
8,
7,
6,
5,
5,
5,
5,
5,
4,
4,
3,
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
119,
50,
22,
5,
4,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
65,
39,
13,
12,
11,
10,
10,
6,
5,
4,
3,
3,
3,
3,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
60,
41,
13,
10,
9,
9,
6,
6,
5,
4,
3,
3,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
75,
51,
6,
6,
5,
4,
3,
3,
3,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
36,
29,
22,
10,
9,
8,
7,
5,
4,
4,
3,
3,
3,
3,
3,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
55,
39,
9,
8,
4,
3,
3,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
19,
16,
14,
10,
9,
6,
5,
5,
4,
3,
3,
3,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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1,
1,
1,
1,
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1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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1,
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1,
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1,
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1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
],
index=index)

Demonstration of the bug:

sorted_unstack = s.unstack()
sorted_unstack.loc["V", "i"] # second value of the Series, correctly yields 650.0
unsorted_unstack = s.unstack(sort=False)
unsorted_unstack.loc["V", "i"] # incorrectly yields nan
# narrowing down the error
s.iloc[:2990].unstack(sort=False).loc["V", "i"] # correct: 650.0
s.iloc[:2991].unstack(sort=False).loc["V", "i"] # incorrect: nan

@rhshadrach
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rhshadrach commented Dec 5, 2023

Thanks @johentsch - can you edit your example of the issue to be as minimal as possible? I know you mentioned it not occurring if you only include the first 2990, but what if you only include the tail or middle section? As is, I think your example is too much to be helpful.

@johentsch
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I had tried for quite a while but I didn't manage, sorry. Maybe, when @renanffernando solves the root of the issue, this will work, too. If not, I could try and spend some more time for creating a MWE for a new issue if the scope falls out of this one here, would that be alright?

@rhshadrach
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Sure - makes sense to wait and see if the resolution for the OP resolved this. I've taken a couple of cracks at this issue and it doesn't look easy. Planning on trying again toward the end of this month.

@renanffernando
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Ah, thanks @johentsch for the new test case. I thought I had resolved this bug on my machine by using a strategy for sorted=False analogous to that used for sort=True. But your test broke my solution.

I'll try to find out what's going on here.

renanffernando added a commit to renanffernando/pandas that referenced this issue Dec 6, 2023
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
@renanffernando
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renanffernando commented Dec 6, 2023

I think I fixed the bug. I just need to think about how to write the changes in a cleaner way.

renanffernando added a commit to renanffernando/pandas that referenced this issue Dec 8, 2023
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
renanffernando added a commit to renanffernando/pandas that referenced this issue Dec 8, 2023
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
renanffernando added a commit to renanffernando/pandas that referenced this issue Dec 8, 2023
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
renanffernando added a commit to renanffernando/pandas that referenced this issue Dec 8, 2023
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
renanffernando added a commit to renanffernando/pandas that referenced this issue Dec 8, 2023
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
renanffernando added a commit to renanffernando/pandas that referenced this issue Dec 21, 2023
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
renanffernando added a commit to renanffernando/pandas that referenced this issue Dec 21, 2023
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
renanffernando added a commit to renanffernando/pandas that referenced this issue Dec 21, 2023
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
renanffernando added a commit to renanffernando/pandas that referenced this issue Dec 21, 2023
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
renanffernando added a commit to renanffernando/pandas that referenced this issue Jan 24, 2024
…pandas-dev#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.
@annie-maria
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Question, when would this be in a stable pandas release? An estimated range is fine. I've encountered the issue too :/

@rhshadrach
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Assuming we get it into 3.0 (PR should be ready now), when 3.0 is released. We were originally targeting April, but I'd guess it's looking more like June now.

mroeschke added a commit that referenced this issue May 21, 2024
#56357)

* BUG: unstack with sort=False fails when used with the level parameter (#54987)

Assign new codes to labels when sort=False. This is done so that the data appears to be already sorted,
fixing the bug.

* Minor refactor and cleanup

* Cleanup & remove test

* whatsnew

* Revert test removal

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Co-authored-by: richard <[email protected]>
Co-authored-by: Richard Shadrach <[email protected]>
Co-authored-by: Matthew Roeschke <[email protected]>
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