Skip to content

BUG: Discrepency between documentation and output for outer merge on index when left and right indices match and are unique #55992

Closed
@wence-

Description

@wence-

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
left = pd.DataFrame({"key": [2, 3, 1]})
right = pd.DataFrame({"key": [2, 3, 1]})
lefti = left.set_index("key")
righti = right.set_index("key")

for sort in [False, True]:
    result_key = left.merge(right, on="key", how="outer", sort=sort)
    result_index = lefti.merge(righti, left_index=True, right_index=True, how="outer", sort=sort).reset_index()

    print(f"{sort=!s:<5} {result_key.equals(result_index)=!s:<5}")

# sort=False result_key.equals(result_index)=False
# sort=True  result_key.equals(result_index)=False

Issue Description

Since #54611, merging dataframes produces a result that almost always matches the documented behaviour. The only exception appears to be an outer merge on an index when the left and right indexes are equal and unique. In this case, irrespective of sort=True/False, the returned result has the order of the input index.

Expected Behavior

Since there isn't a carve-out in the documentation for this specific corner-case, I would expect that pd.merge(..., how="outer") always sorts the output lexicographically according to the join key(s).

Installed Versions

INSTALLED VERSIONS
------------------
commit              : b864b8eb54605124827e6af84aa7fbc816cfc1e0
python              : 3.10.12.final.0
python-bits         : 64
OS                  : Linux
OS-release          : 6.2.0-36-generic
Version             : #37~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon Oct  9 15:34:04 UTC 2
machine             : x86_64
processor           : x86_64
byteorder           : little
LC_ALL              : None
LANG                : en_GB.UTF-8
LOCALE              : en_GB.UTF-8

pandas              : 2.1.0.dev0+1414.gb864b8eb54
numpy               : 1.24.4
pytz                : 2023.3
dateutil            : 2.8.2
setuptools          : 67.7.2
pip                 : 23.2.1
Cython              : 3.0.0
pytest              : 7.4.0
hypothesis          : 6.82.2
sphinx              : 6.2.1
blosc               : None
feather             : None
xlsxwriter          : 3.1.2
lxml.etree          : 4.9.3
html5lib            : 1.1
pymysql             : 1.4.6
psycopg2            : 2.9.6
jinja2              : 3.1.2
IPython             : 8.14.0
pandas_datareader   : None
bs4                 : 4.12.2
bottleneck          : 1.3.7
dataframe-api-compat: None
fastparquet         : 2023.7.0
fsspec              : 2023.6.0
gcsfs               : 2023.6.0
matplotlib          : 3.7.2
numba               : 0.57.1
numexpr             : 2.8.4
odfpy               : None
openpyxl            : 3.1.2
pandas_gbq          : None
pyarrow             : 12.0.1
pyreadstat          : 1.2.2
python-calamine     : None
pyxlsb              : 1.0.10
s3fs                : 2023.6.0
scipy               : 1.11.1
sqlalchemy          : 2.0.19
tables              : 3.8.0
tabulate            : 0.9.0
xarray              : 2023.7.0
xlrd                : 2.0.1
zstandard           : 0.19.0
tzdata              : 2023.3
qtpy                : 2.4.0
pyqt5               : None

Metadata

Metadata

Assignees

No one assigned

    Labels

    BugReshapingConcat, Merge/Join, Stack/Unstack, Explode

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions