TST: Add test for col names during groupby().agg()

[calvh]

Column names should consistently be retained when using df.groupby().agg()

• closes BUG: groupby().agg() loses column names for an empty dataframe with 'idxmax' as an aggregation function #42332
• tests added / passed
• Ensure all linting tests pass, see here for how to run them
• whatsnew entry

Whats new:
Add a test to pandas/tests/groupby/aggregate/test_aggregate.py

The issue appears to be fixed now:

Tested on 1.4.0.dev0+508.g5fe02971f8

Output of pd.show_versions()

INSTALLED VERSIONS

commit : 5fe0297
python : 3.9.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.11.0-31-generic
Version : #33-Ubuntu SMP Wed Aug 11 13:19:04 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_CA.UTF-8
LOCALE : en_CA.UTF-8

pandas : 1.4.0.dev0+508.g5fe02971f8
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.2
pip : 20.3.4
setuptools : 57.4.0
Cython : 0.29.24
pytest : 6.2.4
hypothesis : 6.14.9
sphinx : 4.1.2
blosc : 1.10.4
feather : None
xlsxwriter : 3.0.1
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.26.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fsspec : 2021.05.0
fastparquet : 0.7.1
gcsfs : 2021.05.0
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : 2021.05.0
scipy : 1.7.1
sqlalchemy : 1.4.23
tables : 3.6.1
tabulate : 0.8.9
xarray : 0.18.2
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.54.0

[phofl]

Thanks for the tests. Could you please check the whole DataFrame? Additionally it would be good, if you could parametrize here

[calvh]

@phofl sorry for the delay

After some experimenting, here is what I came up with to parametrize the test. I'm unsure of how to parametrize the sum function.

Also, I am sorry but could you elaborate on the meaning of the "whole dataframe" as I am not sure what you meant.

Thank you.

@pytest.mark.parametrize(
    "agg_params",
    [
            {"start": pd.NamedAgg(column="time", aggfunc="min")},
            {
                "start": pd.NamedAgg(column="time", aggfunc="min"),
                "peak_time": pd.NamedAgg(column="values", aggfunc="idxmax"),
            },
            {"peak_time": pd.NamedAgg(column="values", aggfunc="idxmax")},
    ],
)
def test_groupby_agg_column_names(agg_params):
    # GH42332
    grouped = (
        DataFrame(columns=["id1", "id2", "time", "values"], dtype="int")
        .groupby(["id1", "id2"])
    )

    aggregated = grouped.agg(**agg_params)

    assert (
        grouped.sum().index.names == aggregated.index.names == ["id1", "id2"]
    )

[jreback]

use tm.assert_frame_equal and construct the actual expected value.

[github-actions]

This pull request is stale because it has been open for thirty days with no activity. Please update or respond to this comment if you're still interested in working on this.

[calvh]

This pull request is stale because it has been open for thirty days with no activity. Please update or respond to this comment if you're still interested in working on this.

Sorry, yes I am still interested in working on this

[mroeschke]

Appears this PR has been dormant for a while and still needs updates so closing. If interested in continuing, please merge master, address related comments and we can reopen.