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BUG: loc.setitem raising ValueError when df has duplicate columns #39278

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Merged
merged 4 commits into from
Jan 21, 2021
Merged

BUG: loc.setitem raising ValueError when df has duplicate columns #39278

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64101f8
BUG: loc.setitem raising ValueError when df has duplicate columns
phofl Jan 19, 2021
6c9f245
Use is_scalar instead of unique
phofl Jan 19, 2021
9bc5fc9
Change condition
phofl Jan 19, 2021
74c1dd0
Make nested condition
phofl Jan 20, 2021
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.3.0.rst
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Expand Up @@ -276,6 +276,7 @@ Indexing
- Bug in :meth:`DataFrame.loc`, :meth:`Series.loc`, :meth:`DataFrame.__getitem__` and :meth:`Series.__getitem__` returning incorrect elements for non-monotonic :class:`DatetimeIndex` for string slices (:issue:`33146`)
- Bug in :meth:`DataFrame.reindex` and :meth:`Series.reindex` with timezone aware indexes raising ``TypeError`` for ``method="ffill"`` and ``method="bfill"`` and specified ``tolerance`` (:issue:`38566`)
- Bug in :meth:`DataFrame.__setitem__` raising ``ValueError`` with empty :class:`DataFrame` and specified columns for string indexer and non empty :class:`DataFrame` to set (:issue:`38831`)
- Bug in :meth:`DataFrame.loc.__setitem__` raising ValueError when expanding unique column for :class:`DataFrame` with duplicate columns (:issue:`38521`)
- Bug in :meth:`DataFrame.iloc.__setitem__` and :meth:`DataFrame.loc.__setitem__` with mixed dtypes when setting with a dictionary value (:issue:`38335`)
- Bug in :meth:`DataFrame.loc` dropping levels of :class:`MultiIndex` when :class:`DataFrame` used as input has only one row (:issue:`10521`)
- Bug in setting ``timedelta64`` values into numeric :class:`Series` failing to cast to object dtype (:issue:`39086`)
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3 changes: 2 additions & 1 deletion pandas/core/indexing.py
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Expand Up @@ -1850,7 +1850,8 @@ def _setitem_single_block(self, indexer, value, name: str):
for i, idx in enumerate(indexer)
if i != info_axis
)
and item_labels.is_unique
and len(item_labels.get_indexer_for([item_labels[indexer[info_axis]]]))
== 1
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lets separate this out into a nested condition and define item_labels[indexer[info_axis]] once, then reuse it on L1856

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Done

):
self.obj[item_labels[indexer[info_axis]]] = value
return
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9 changes: 9 additions & 0 deletions pandas/tests/frame/indexing/test_setitem.py
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Expand Up @@ -373,6 +373,15 @@ def test_setitem_string_column_numpy_dtype_raising(self):
expected = DataFrame([[1, 2, 5], [3, 4, 6]], columns=[0, 1, "0 - Name"])
tm.assert_frame_equal(df, expected)

def test_setitem_empty_df_duplicate_columns(self):
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do we need tests for Series?

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Don't think so, indexer has to be a tuple to land there, which is only valid for dataframes I think?

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its weird, but you could do series.loc[("foo",)]

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Yep, definitely weird :)

But this is already converted before reaching that point.

df = Series(index=["a", "b", "b"], dtype="float64")
df.loc[("a", )] = 1

This results in indexer=0. Tested the same with a MultiIndex Series, also 0 there

# GH#38521
df = DataFrame(columns=["a", "b", "b"], dtype="float64")
df.loc[:, "a"] = list(range(2))
expected = DataFrame(
[[0, np.nan, np.nan], [1, np.nan, np.nan]], columns=["a", "b", "b"]
)
tm.assert_frame_equal(df, expected)


class TestDataFrameSetItemSlicing:
def test_setitem_slice_position(self):
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