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Fix pivot index bug #37771

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Nov 14, 2020
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.2.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -553,6 +553,7 @@ Reshaping
- Bug in :meth:`DataFrame.agg` with ``func={'name':<FUNC>}`` incorrectly raising ``TypeError`` when ``DataFrame.columns==['Name']`` (:issue:`36212`)
- Bug in :meth:`Series.transform` would give incorrect results or raise when the argument ``func`` was dictionary (:issue:`35811`)
- Bug in :meth:`DataFrame.pivot` did not preserve :class:`MultiIndex` level names for columns when rows and columns both multiindexed (:issue:`36360`)
- Bug in :meth:`DataFrame.pivot` modified ``index`` argument when ``columns`` was passed but ``values`` was not (:issue:`37635`)
- Bug in :func:`join` returned a non deterministic level-order for the resulting :class:`MultiIndex` (:issue:`36910`)
- Bug in :meth:`DataFrame.combine_first()` caused wrong alignment with dtype ``string`` and one level of ``MultiIndex`` containing only ``NA`` (:issue:`37591`)
- Fixed regression in :func:`merge` on merging DatetimeIndex with empty DataFrame (:issue:`36895`)
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3 changes: 1 addition & 2 deletions pandas/core/reshape/pivot.py
Original file line number Diff line number Diff line change
Expand Up @@ -450,10 +450,9 @@ def pivot(
cols = com.convert_to_list_like(index)
else:
cols = []
cols.extend(columns)

append = index is None
indexed = data.set_index(cols, append=append)
indexed = data.set_index(cols + columns, append=append)
else:
if index is None:
index = [Series(data.index, name=data.index.name)]
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38 changes: 38 additions & 0 deletions pandas/tests/reshape/test_pivot.py
Original file line number Diff line number Diff line change
Expand Up @@ -2153,3 +2153,41 @@ def test_pivot_index_none(self):

expected.columns.name = "columns"
tm.assert_frame_equal(result, expected)

def test_pivot_index_list_values_none_immutable_args(self):
# GH37635
df = DataFrame(
{
"lev1": [1, 1, 1, 2, 2, 2],
"lev2": [1, 1, 2, 1, 1, 2],
"lev3": [1, 2, 1, 2, 1, 2],
"lev4": [1, 2, 3, 4, 5, 6],
"values": [0, 1, 2, 3, 4, 5],
}
)
index = ["lev1", "lev2"]
columns = ["lev3"]
result = df.pivot(index=index, columns=columns, values=None)

expected = DataFrame(
np.array(
[
[1.0, 2.0, 0.0, 1.0],
[3.0, np.nan, 2.0, np.nan],
[5.0, 4.0, 4.0, 3.0],
[np.nan, 6.0, np.nan, 5.0],
]
),
index=MultiIndex.from_arrays(
[(1, 1, 2, 2), (1, 2, 1, 2)], names=["lev1", "lev2"]
),
columns=MultiIndex.from_arrays(
[("lev4", "lev4", "values", "values"), (1, 2, 1, 2)],
names=[None, "lev3"],
),
)

tm.assert_frame_equal(result, expected)

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check here that you got the correct result from the pivot (might need to hard-code)

assert index == ["lev1", "lev2"]
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can you also assert that columns is the same as original, ping on green.

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Done but not green; new comment below.

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I'd say it's green, LGTM

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@Jacob-Stevens-Haas Jacob-Stevens-Haas Nov 13, 2020

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Gotcha, thanks! @jreback?

assert columns == ["lev3"]