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BUG: GH11847 Unstack with mixed dtypes coerces everything to object #14053

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BUG: GH11847 Unstack with mixed dtypes coerces everything to object #14053

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2 changes: 2 additions & 0 deletions doc/source/whatsnew/v0.19.2.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -68,3 +68,5 @@ Bug Fixes


- Explicit check in ``to_stata`` and ``StataWriter`` for out-of-range values when writing doubles (:issue:`14618`)

- Bug in ``unstack()`` if called with a list of column(s) as an argument, regardless of the dtypes of all columns, they get coerced to ``object`` (:issue:`11847`)
6 changes: 4 additions & 2 deletions pandas/core/reshape.py
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Expand Up @@ -277,7 +277,8 @@ def _unstack_multiple(data, clocs):
verify_integrity=False)

if isinstance(data, Series):
dummy = Series(data.values, index=dummy_index)
dummy = data.copy()
dummy.index = dummy_index
unstacked = dummy.unstack('__placeholder__')
new_levels = clevels
new_names = cnames
Expand All @@ -292,7 +293,8 @@ def _unstack_multiple(data, clocs):

return result

dummy = DataFrame(data.values, index=dummy_index, columns=data.columns)
dummy = data.copy()
dummy.index = dummy_index

unstacked = dummy.unstack('__placeholder__')
if isinstance(unstacked, Series):
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40 changes: 40 additions & 0 deletions pandas/tests/frame/test_reshape.py
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Expand Up @@ -282,6 +282,46 @@ def test_unstack_fill_frame_categorical(self):
index=list('xyz'))
assert_frame_equal(result, expected)

def test_unstack_preserve_dtypes(self):
# Checks fix for #11847
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test with more dtypes

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use more types as the index

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can you write a 1-liner that this is checking for a list of unstacks is the same as as repeated unstacking.

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@jreback the test examples are not repeated unstacking, just comparing 'index' with ['index']

df = pd.DataFrame(dict(state=['IL', 'MI', 'NC'],
index=['a', 'b', 'c'],
some_categories=pd.Series(['a', 'b', 'c']
).astype('category'),
A=np.random.rand(3),
B=1,
C='foo',
D=pd.Timestamp('20010102'),
E=pd.Series([1.0, 50.0, 100.0]
).astype('float32'),
F=pd.Series([3.0, 4.0, 5.0]).astype('float64'),
G=False,
H=pd.Series([1, 200, 923442], dtype='int8')))

def unstack_and_compare(df, column_name):
unstacked1 = df.unstack([column_name])
unstacked2 = df.unstack(column_name)
assert_frame_equal(unstacked1, unstacked2)

df1 = df.set_index(['state', 'index'])
unstack_and_compare(df1, 'index')

df1 = df.set_index(['state', 'some_categories'])
unstack_and_compare(df1, 'some_categories')

df1 = df.set_index(['F', 'C'])
unstack_and_compare(df1, 'F')

df1 = df.set_index(['G', 'B', 'state'])
unstack_and_compare(df1, 'B')

df1 = df.set_index(['E', 'A'])
unstack_and_compare(df1, 'E')

df1 = df.set_index(['state', 'index'])
s = df1['A']
unstack_and_compare(s, 'index')

def test_stack_ints(self):
columns = MultiIndex.from_tuples(list(itertools.product(range(3),
repeat=3)))
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