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BUG: do not fail when stack()ing unsortable level #18363

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Dec 1, 2017
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BUG: do not fail when stack()ing unsortable level #18363

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3 changes: 2 additions & 1 deletion doc/source/whatsnew/v0.22.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -142,7 +142,8 @@ Sparse
Reshaping
^^^^^^^^^

-
- Bug in :func:`DataFrame.stack` which fails trying to sort mixed type levels under Python 3 (:issue:`18310`)

-
-

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24 changes: 12 additions & 12 deletions pandas/core/indexes/multi.py
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Expand Up @@ -1292,19 +1292,19 @@ def _sort_levels_monotonic(self):

for lev, lab in zip(self.levels, self.labels):

if lev.is_monotonic:
new_levels.append(lev)
new_labels.append(lab)
continue

# indexer to reorder the levels
indexer = lev.argsort()
lev = lev.take(indexer)
if not lev.is_monotonic:
try:
# indexer to reorder the levels
indexer = lev.argsort()
except TypeError:
pass
else:
lev = lev.take(indexer)

# indexer to reorder the labels
indexer = _ensure_int64(indexer)
ri = lib.get_reverse_indexer(indexer, len(indexer))
lab = algos.take_1d(ri, lab)
# indexer to reorder the labels
indexer = _ensure_int64(indexer)
ri = lib.get_reverse_indexer(indexer, len(indexer))
lab = algos.take_1d(ri, lab)

new_levels.append(lev)
new_labels.append(lab)
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24 changes: 24 additions & 0 deletions pandas/tests/frame/test_reshape.py
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Expand Up @@ -133,6 +133,30 @@ def test_stack_unstack(self):
assert_frame_equal(unstacked_cols.T, df)
assert_frame_equal(unstacked_cols_df['bar'].T, df)

def test_stack_mixed_level(self):
# GH 18310
levels = [range(3), [3, 'a', 'b'], [1, 2]]

# flat columns:
df = DataFrame(1, index=levels[0], columns=levels[1])
result = df.stack()
expected = Series(1, index=MultiIndex.from_product(levels[:2]))
assert_series_equal(result, expected)

# MultiIndex columns:
df = DataFrame(1, index=levels[0],
columns=MultiIndex.from_product(levels[1:]))
result = df.stack(1)
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can you add the 2nd example you had in the issue as well, e.g. df[['a', 'b']].stack(0) (though different starting frame as well i think.

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(done)
ping

expected = DataFrame(1, index=MultiIndex.from_product([levels[0],
levels[2]]),
columns=levels[1])
assert_frame_equal(result, expected)

# as above, but used labels in level are actually of homogeneous type
result = df[['a', 'b']].stack(1)
expected = expected[['a', 'b']]
assert_frame_equal(result, expected)

def test_unstack_fill(self):

# GH #9746: fill_value keyword argument for Series
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