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BUG: bug in setitem with multi-index and a 0-dim ndarray (GH7218) #7219

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Merged
merged 1 commit into from
May 23, 2014
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BUG: bug in setitem with multi-index and a 0-dim ndarray (GH7218) #7219

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2 changes: 1 addition & 1 deletion doc/source/release.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -522,7 +522,7 @@ Bug Fixes
- Bug in ``query``/``eval`` where global constants were not looked up correctly
(:issue:`7178`)
- Bug in recognizing out-of-bounds positional list indexers with ``iloc`` and a multi-axis tuple indexer (:issue:`7189`)
- Bug in setitem with a single value, multi-index and integer indices (:issue:`7190`)
- Bug in setitem with a single value, multi-index and integer indices (:issue:`7190`, :issue:`7218`)
- Bug in expressions evaluation with reversed ops, showing in series-dataframe ops (:issue:`7198`, :issue:`7192`)
- Bug in multi-axis indexing with > 2 ndim and a multi-index (:issue:`7199`)

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4 changes: 2 additions & 2 deletions pandas/core/indexing.py
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Expand Up @@ -339,7 +339,7 @@ def _setitem_with_indexer(self, indexer, value):

# require that we are setting the right number of values that
# we are indexing
if is_list_like(value) and lplane_indexer != len(value):
if is_list_like(value) and np.iterable(value) and lplane_indexer != len(value):

if len(obj[idx]) != len(value):
raise ValueError(
Expand Down Expand Up @@ -386,7 +386,7 @@ def setter(item, v):

def can_do_equal_len():
""" return True if we have an equal len settable """
if not len(labels) == 1:
if not len(labels) == 1 or not np.iterable(value):
return False

l = len(value)
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14 changes: 10 additions & 4 deletions pandas/tests/test_indexing.py
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Expand Up @@ -619,14 +619,20 @@ def test_loc_setitem_multiindex(self):
self.assertEqual(result, 0)

df = DataFrame(-999,columns=['A', 'w', 'l', 'a', 'x', 'X', 'd', 'profit'], index=index)
df.loc[(t,n),'X'] = 0
df.loc[(t,n),'X'] = 1
result = df.loc[(t,n),'X']
self.assertEqual(result, 0)
self.assertEqual(result, 1)

df = DataFrame(columns=['A', 'w', 'l', 'a', 'x', 'X', 'd', 'profit'], index=index)
df.loc[(t,n),'X'] = 0
df.loc[(t,n),'X'] = 2
result = df.loc[(t,n),'X']
self.assertEqual(result, 0)
self.assertEqual(result, 2)

# GH 7218, assinging with 0-dim arrays
df = DataFrame(-999,columns=['A', 'w', 'l', 'a', 'x', 'X', 'd', 'profit'], index=index)
df.loc[(t,n), 'X'] = np.array(3)
result = df.loc[(t,n),'X']
self.assertEqual(result,3)

def test_loc_setitem_dups(self):

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