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REGR: Fix regression when grouping over a Series #57323

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Feb 10, 2024
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REGR: Fix regression when grouping over a Series #57323

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REGR: Fix regression when grouping over a Series
phofl Feb 9, 2024
12eca90
Merge branch 'main' into 57276
phofl Feb 10, 2024
e72dc6b
Merge branch 'main' into 57276
phofl Feb 10, 2024
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v2.2.1.rst
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Expand Up @@ -21,6 +21,7 @@ Fixed regressions
- Fixed regression in :meth:`.DataFrameGroupBy.idxmin`, :meth:`.DataFrameGroupBy.idxmax`, :meth:`.SeriesGroupBy.idxmin`, :meth:`.SeriesGroupBy.idxmax` ignoring the ``skipna`` argument (:issue:`57040`)
- Fixed regression in :meth:`.DataFrameGroupBy.idxmin`, :meth:`.DataFrameGroupBy.idxmax`, :meth:`.SeriesGroupBy.idxmin`, :meth:`.SeriesGroupBy.idxmax` where values containing the minimum or maximum value for the dtype could produce incorrect results (:issue:`57040`)
- Fixed regression in :meth:`CategoricalIndex.difference` raising ``KeyError`` when other contains null values other than NaN (:issue:`57318`)
- Fixed regression in :meth:`DataFrame.groupby` raising ``ValueError`` when grouping by a :class:`Series` in some cases (:issue:`57276`)
- Fixed regression in :meth:`DataFrame.loc` raising ``IndexError`` for non-unique, masked dtype indexes where result has more than 10,000 rows (:issue:`57027`)
- Fixed regression in :meth:`DataFrame.merge` raising ``ValueError`` for certain types of 3rd-party extension arrays (:issue:`57316`)
- Fixed regression in :meth:`DataFrame.sort_index` not producing a stable sort for a index with duplicates (:issue:`57151`)
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5 changes: 2 additions & 3 deletions pandas/core/internals/managers.py
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Expand Up @@ -15,7 +15,6 @@
final,
)
import warnings
import weakref

import numpy as np

Expand Down Expand Up @@ -337,8 +336,8 @@ def references_same_values(self, mgr: BaseBlockManager, blkno: int) -> bool:
Checks if two blocks from two different block managers reference the
same underlying values.
"""
ref = weakref.ref(self.blocks[blkno])
return ref in mgr.blocks[blkno].refs.referenced_blocks
blk = self.blocks[blkno]
return any(blk is ref() for ref in mgr.blocks[blkno].refs.referenced_blocks)
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At the point where df["col"].index is df.index is no longer true, we will have to update this, but I assume we can handle that at that point

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That should work anyway though, since df.col.index will also be in the references since it still shares values with df.index. All shallow copies of the original values should be in there, that’s the elegant think about the tracking mechanism

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Actually index checks will never get there since it's defined on the manager


def get_dtypes(self) -> npt.NDArray[np.object_]:
dtypes = np.array([blk.dtype for blk in self.blocks], dtype=object)
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11 changes: 11 additions & 0 deletions pandas/tests/copy_view/test_methods.py
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Expand Up @@ -273,6 +273,17 @@ def test_reset_index_series_drop(using_copy_on_write, index):
tm.assert_series_equal(ser, ser_orig)


def test_groupby_column_index_in_references():
df = DataFrame(
{"A": ["a", "b", "c", "d"], "B": [1, 2, 3, 4], "C": ["a", "a", "b", "b"]}
)
df = df.set_index("A")
key = df["C"]
result = df.groupby(key, observed=True).sum()
expected = df.groupby("C", observed=True).sum()
tm.assert_frame_equal(result, expected)


def test_rename_columns(using_copy_on_write):
# Case: renaming columns returns a new dataframe
# + afterwards modifying the result
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