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Bug in melt raising Error with dup columns as value vars #41964

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Jun 15, 2021
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.3.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -1148,6 +1148,7 @@ Reshaping
- Bug in :func:`to_datetime` raising an error when the input sequence contained unhashable items (:issue:`39756`)
- Bug in :meth:`Series.explode` preserving the index when ``ignore_index`` was ``True`` and values were scalars (:issue:`40487`)
- Bug in :func:`to_datetime` raising a ``ValueError`` when :class:`Series` contains ``None`` and ``NaT`` and has more than 50 elements (:issue:`39882`)
- Bug in :meth:`DataFrame.melt` raising ``InvalidIndexError`` when :class:`DataFrame` has duplicate columns used as ``value_vars`` (:issue:`41951`)

Sparse
^^^^^^
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3 changes: 2 additions & 1 deletion pandas/core/reshape/melt.py
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@
from pandas.core.dtypes.concat import concat_compat
from pandas.core.dtypes.missing import notna

import pandas.core.algorithms as algos
from pandas.core.arrays import Categorical
import pandas.core.common as com
from pandas.core.indexes.api import (
Expand Down Expand Up @@ -106,7 +107,7 @@ def melt(
id_vars + value_vars
)
else:
idx = frame.columns.get_indexer(id_vars + value_vars)
idx = algos.unique(frame.columns.get_indexer_for(id_vars + value_vars))
frame = frame.iloc[:, idx]
else:
frame = frame.copy()
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9 changes: 9 additions & 0 deletions pandas/tests/reshape/test_melt.py
Original file line number Diff line number Diff line change
Expand Up @@ -403,6 +403,15 @@ def test_ignore_index_name_and_type(self):

tm.assert_frame_equal(result, expected)

def test_melt_with_duplicate_columns(self):
# GH#41951
df = DataFrame([["id", 2, 3]], columns=["a", "b", "b"])
result = df.melt(id_vars=["a"], value_vars=["b"])
expected = DataFrame(
[["id", "b", 2], ["id", "b", 3]], columns=["a", "variable", "value"]
)
tm.assert_frame_equal(result, expected)


class TestLreshape:
def test_pairs(self):
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