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TST: Add test for col names during groupby().agg() #43244

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TST: Add test for col names during groupby().agg() #43244

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32 changes: 32 additions & 0 deletions pandas/tests/groupby/aggregate/test_aggregate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1274,3 +1274,35 @@ def func(ser):

expected = DataFrame([[1.0]], index=[1])
tm.assert_frame_equal(res, expected)


def test_groupby_agg_column_names():
# GH42332

df = DataFrame(columns=["id1", "id2", "time", "values"], dtype="int").groupby(
["id1", "id2"]
)

df_sum_idx = df.sum().index.names
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@phofl phofl Aug 27, 2021

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Thanks for the tests. Could you please check the whole DataFrame? Additionally it would be good, if you could parametrize here
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@calvh calvh Aug 31, 2021

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@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"] )

df_agg1_idx = df.agg(
**{"start": pd.NamedAgg(column="time", aggfunc="min")}
).index.names

df_agg2_idx = df.agg(
**{
"start": pd.NamedAgg(column="time", aggfunc="min"),
"peak_time": pd.NamedAgg(column="values", aggfunc="idxmax"),
}
).index.names

df_agg3_idx = df.agg(
**{"peak_time": pd.NamedAgg(column="values", aggfunc="idxmax")}
).index.names

expected = ["id1", "id2"]

assert df_sum_idx == expected
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@jreback jreback Aug 31, 2021

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use tm.assert_frame_equal and construct the actual expected value.
assert df_agg1_idx == expected
assert df_agg2_idx == expected
assert df_agg3_idx == expected