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BUG: closes bug in stack when index is not unique #10433

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Aug 8, 2015
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.17.0.txt
Original file line number Diff line number Diff line change
Expand Up @@ -561,6 +561,7 @@ Bug Fixes
- Bug in ``Table.select_column`` where name is not preserved (:issue:`10392`)
- Bug in ``offsets.generate_range`` where ``start`` and ``end`` have finer precision than ``offset`` (:issue:`9907`)
- Bug in ``pd.rolling_*`` where ``Series.name`` would be lost in the output (:issue:`10565`)
- Bug in ``stack`` when index or columns are not unique. (:issue:`10417`)



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22 changes: 15 additions & 7 deletions pandas/core/reshape.py
Original file line number Diff line number Diff line change
Expand Up @@ -461,6 +461,12 @@ def stack(frame, level=-1, dropna=True):
-------
stacked : Series
"""
def factorize(index):
if index.is_unique:
return index, np.arange(len(index))
cat = Categorical(index, ordered=True)
return cat.categories, cat.codes

N, K = frame.shape
if isinstance(frame.columns, MultiIndex):
if frame.columns._reference_duplicate_name(level):
Expand All @@ -475,20 +481,22 @@ def stack(frame, level=-1, dropna=True):
return _stack_multi_columns(frame, level_num=level_num, dropna=dropna)
elif isinstance(frame.index, MultiIndex):
new_levels = list(frame.index.levels)
new_levels.append(frame.columns)

new_labels = [lab.repeat(K) for lab in frame.index.labels]
new_labels.append(np.tile(np.arange(K), N).ravel())

clev, clab = factorize(frame.columns)
new_levels.append(clev)
new_labels.append(np.tile(clab, N).ravel())

new_names = list(frame.index.names)
new_names.append(frame.columns.name)
new_index = MultiIndex(levels=new_levels, labels=new_labels,
names=new_names, verify_integrity=False)
else:
ilabels = np.arange(N).repeat(K)
clabels = np.tile(np.arange(K), N).ravel()
new_index = MultiIndex(levels=[frame.index, frame.columns],
labels=[ilabels, clabels],
levels, (ilab, clab) = \
zip(*map(factorize, (frame.index, frame.columns)))
labels = ilab.repeat(K), np.tile(clab, N).ravel()
new_index = MultiIndex(levels=levels,
labels=labels,
names=[frame.index.name, frame.columns.name],
verify_integrity=False)

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38 changes: 38 additions & 0 deletions pandas/tests/test_multilevel.py
Original file line number Diff line number Diff line change
Expand Up @@ -964,6 +964,44 @@ def test_stack(self):
result = self.ymd.unstack(0).stack(-2)
expected = self.ymd.unstack(0).stack(0)

# GH10417
def check(left, right):
assert_series_equal(left, right)
self.assertFalse(left.index.is_unique)
li, ri = left.index, right.index
for i in range(ri.nlevels):
tm.assert_numpy_array_equal(li.levels[i], ri.levels[i])
tm.assert_numpy_array_equal(li.labels[i], ri.labels[i])

df = DataFrame(np.arange(12).reshape(4, 3),
index=list('abab'),
columns=['1st', '2nd', '3rd'])

mi = MultiIndex(levels=[['a', 'b'], ['1st', '2nd', '3rd']],
labels=[np.tile(np.arange(2).repeat(3), 2),
np.tile(np.arange(3), 4)])

left, right = df.stack(), Series(np.arange(12), index=mi)
check(left, right)

df.columns = ['1st', '2nd', '1st']
mi = MultiIndex(levels=[['a', 'b'], ['1st', '2nd']],
labels=[np.tile(np.arange(2).repeat(3), 2),
np.tile([0, 1, 0], 4)])

left, right = df.stack(), Series(np.arange(12), index=mi)
check(left, right)

tpls = ('a', 2), ('b', 1), ('a', 1), ('b', 2)
df.index = MultiIndex.from_tuples(tpls)
mi = MultiIndex(levels=[['a', 'b'], [1, 2], ['1st', '2nd']],
labels=[np.tile(np.arange(2).repeat(3), 2),
np.repeat([1, 0, 1], [3, 6, 3]),
np.tile([0, 1, 0], 4)])

left, right = df.stack(), Series(np.arange(12), index=mi)
check(left, right)

def test_unstack_odd_failure(self):
data = """day,time,smoker,sum,len
Fri,Dinner,No,8.25,3.
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