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ensure consistent structure for groupby on index and column #29357

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ensure consistent structure for groupby on index and column #29357

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22 changes: 22 additions & 0 deletions pandas/tests/groupby/test_grouping.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@
date_range,
)
from pandas.core.groupby.grouper import Grouping
from pandas.core.indexes.frozen import FrozenList
import pandas.util.testing as tm

# selection
Expand Down Expand Up @@ -641,6 +642,27 @@ def test_groupby_level_index_value_all_na(self):
)
tm.assert_frame_equal(result, expected)

@pytest.mark.parametrize(
"df",
[
pd.DataFrame([[1, 2, 3]], columns=["a", "b", "c"]).set_index("a"),
pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns=["a", "b", "c"]).set_index(
"a"
),
pd.DataFrame(
[[1, 2, 3], [4, 5, 6], [7, 8, 9]], columns=["a", "b", "c"]
).set_index("a"),
],
)
@pytest.mark.parametrize(
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can you use the fixture all_numeric_reductions (you can simply replace method with this)

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I've just checked, if I remove the second pytest parametrisation and use all_numeric_reductions (from pandas.conftest) as the second parameter the test will throw an error of AttributeError: 'DataFrameGroupBy' object has no attribute 'kurt'.

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I think can also use reduction_func from the groupby contest. Might need to consolidate those fixtures at a later point

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In that case tests fail for ngroup and nth reductions: AssertionError: assert FrozenList(['a']) == FrozenList(['a', 'c']) and TypeError: nth() missing 1 required positional argument: 'n' respectively.

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So the test in #29124 is already doing this with all of the groupby funcs though with a different intent (duplicate column labels). Maybe after that gets merged we come back to this and see if this makes sense to fit into that test as well via some sort of parametrization; not sure it's worth doing as a one-off

"method", ["mean", "median", "prod", "min", "max", "sum", "std", "var"]
)
def test_groupby_on_index_and_column_consistent_structure(self, df, method):
# https://github.com/pandas-dev/pandas/issues/17681
df_gb = df.groupby(["a", "c"])
result = getattr(df_gb, method)()
assert result.index.names == FrozenList(["a", "c"])


# get_group
# --------------------------------
Expand Down