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BUG: Let MultiIndex.set_levels accept any iterable (#23273) #23291

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Oct 25, 2018
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BUG: Let MultiIndex.set_levels accept any iterable (#23273) #23291

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.24.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -1004,6 +1004,7 @@ Indexing
- Bug in :meth:`DataFrame.loc` when indexing with an :class:`IntervalIndex` (:issue:`19977`)
- :class:`Index` no longer mangles ``None``, ``NaN`` and ``NaT``, i.e. they are treated as three different keys. However, for numeric Index all three are still coerced to a ``NaN`` (:issue:`22332`)
- Bug in `scalar in Index` if scalar is a float while the ``Index`` is of integer dtype (:issue:`22085`)
- Bug in `MultiIndex.set_levels` when levels value is not subscriptable (:issue:`23273`)

Missing
^^^^^^^
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3 changes: 3 additions & 0 deletions pandas/core/indexes/multi.py
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Expand Up @@ -389,6 +389,9 @@ def set_levels(self, levels, level=None, inplace=False,
labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
names=[u'foo', u'bar'])
"""
if is_list_like(levels) and not isinstance(levels, Index):
levels = list(levels)

if level is not None and not is_list_like(level):
if not is_list_like(levels):
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you can just add

elif is_list_like(levels):
   levels = list(levels)

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Tried this approach, but unfortunately, it breaks functionality where one passes to set_levels CategoricalIndex (or in general, something else which is more complex than a list).

Specifically, this turns

index.set_levels(CategoricalIndex(list("bac")), 0)

into

index.set_levels(list("bac"), 0)

and breaks test_set_levels_categorical

I can add change this with

if is_list_like(levels) and not isinstance(levels, Index):

but I'm not sure what's better

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the 2nd would be fine, we don't need/want any more api checkers)

raise TypeError("Levels must be list-like")
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14 changes: 14 additions & 0 deletions pandas/tests/indexes/multi/test_get_set.py
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Expand Up @@ -414,3 +414,17 @@ def test_set_value_keeps_names():
df.at[('grethe', '4'), 'one'] = 99.34
assert df._is_copy is None
assert df.index.names == ('Name', 'Number')


def test_set_levels_with_iterable():
# GH23273
sizes = [1, 2, 3]
colors = ['black'] * 3
index = pd.MultiIndex.from_arrays([sizes, colors], names=['size', 'color'])

result = index.set_levels(map(int, ['3', '2', '1']), level='size')

expected_sizes = [3, 2, 1]
expected = pd.MultiIndex.from_arrays([expected_sizes, colors],
names=['size', 'color'])
tm.assert_index_equal(result, expected)