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Preserve Alignment Between Index and Values for Non-Monotonic Stack #20980

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Preserve Alignment Between Index and Values for Non-Monotonic Stack #20980

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13ec238
Added test for issue
WillAyd May 8, 2018
a79eaf7
Fixed misalignment on frame reconstruction
WillAyd May 8, 2018
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8 changes: 7 additions & 1 deletion pandas/core/reshape/reshape.py
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Original file line number Diff line number Diff line change
Expand Up @@ -653,7 +653,13 @@ def _convert_level_number(level_num, columns):
# time to ravel the values
new_data = {}
level_vals = this.columns.levels[-1]
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we have a sort_monotonic function in a MI to do this

level_labels = sorted(set(this.columns.labels[-1]))
level_labels = list()
for label in this.columns.labels[-1]:
# GH 20945 if labels are not monotonic we were mangling
# alignment when moving to index; ensure we preserve order
if label not in level_labels:
level_labels.append(label)

level_vals_used = level_vals[level_labels]
levsize = len(level_labels)
drop_cols = []
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19 changes: 19 additions & 0 deletions pandas/tests/frame/test_reshape.py
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Expand Up @@ -414,6 +414,25 @@ def test_stack_mixed_levels(self):
assert_frame_equal(df3.stack(level=['animal', 0]),
animal_hair_stacked, check_names=False)

def test_stack_retains_index_order_non_monotonic(self):
# GH 20945
df = pd.DataFrame([
['DIM', 'A', 1, 2, 3, 4],
['DIM', 'B', 11, 22, 33, 44],
])
df.columns = ["dim1", "dim2", 'c', 'b', 'a', 'd']
df.columns.name = 'foo'
df = df.set_index(["dim1", "dim2"])

expected_mi = pd.MultiIndex.from_product([['DIM'], ['c', 'b', 'a', 'd']])
expected_mi.names = ['dim1', 'foo']
expected = pd.DataFrame([[1, 11], [2, 22], [3, 33], [4, 44]],
index=expected_mi, columns=['A', 'B'])
expected.columns.name = 'dim2'

result = df.unstack('dim2').stack(level=0)
tm.assert_frame_equal(result, expected)

def test_stack_int_level_names(self):
columns = MultiIndex.from_tuples(
[('A', 'cat', 'long'), ('B', 'cat', 'long'),
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