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Error with .drop([]) on non-unique index #16428

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Merged
merged 4 commits into from
May 24, 2017
Merged

Error with .drop([]) on non-unique index #16428

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8d0285a
BUG: ensure that labels are objects, if they are empty they default t…
lkirk May 22, 2017
0bdc8ed
BUG: fix-drop-on-non-unique-index
lkirk May 22, 2017
eb3ee0e
fix note in whatsnew
lkirk May 23, 2017
1973925
adds test to drop blank list
lkirk May 23, 2017
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2 changes: 2 additions & 0 deletions doc/source/whatsnew/v0.20.2.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -93,3 +93,5 @@ Categorical

Other
^^^^^

- Bug in ``pd.drop([])`` for DataFrame with non-unique indices (:issue:`16270`)
3 changes: 2 additions & 1 deletion pandas/core/generic.py
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Expand Up @@ -12,6 +12,7 @@
from pandas._libs import tslib, lib
from pandas.core.dtypes.common import (
_ensure_int64,
_ensure_object,
needs_i8_conversion,
is_scalar,
is_number,
Expand Down Expand Up @@ -2076,7 +2077,7 @@ def drop(self, labels, axis=0, level=None, inplace=False, errors='raise'):
result = dropped

else:
labels = com._index_labels_to_array(labels)
labels = _ensure_object(com._index_labels_to_array(labels))
if level is not None:
if not isinstance(axis, MultiIndex):
raise AssertionError('axis must be a MultiIndex')
Expand Down
6 changes: 6 additions & 0 deletions pandas/tests/frame/test_axis_select_reindex.py
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Expand Up @@ -61,6 +61,11 @@ def test_drop_names(self):
expected = Index(['e', 'f'], name='second')
tm.assert_index_equal(dropped.columns, expected)

# GH 16398
dropped = df.drop([], errors='ignore')
expected = Index(['a', 'b', 'c'], name='first')
tm.assert_index_equal(dropped.index, expected)

def test_drop_col_still_multiindex(self):
arrays = [['a', 'b', 'c', 'top'],
['', '', '', 'OD'],
Expand Down Expand Up @@ -100,6 +105,7 @@ def test_drop(self):
columns=['a', 'a', 'b'])
assert_frame_equal(nu_df.drop('a', axis=1), nu_df[['b']])
assert_frame_equal(nu_df.drop('b', axis='columns'), nu_df['a'])
assert_frame_equal(nu_df.drop([]), nu_df) # GH 16398

nu_df = nu_df.set_index(pd.Index(['X', 'Y', 'X']))
nu_df.columns = list('abc')
Expand Down