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API/BUG: .apply will correctly infer output shape when axis=1 #18577

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merged 12 commits into from
Feb 7, 2018
Merged

API/BUG: .apply will correctly infer output shape when axis=1 #18577

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970d3a3
API/BUG: .apply will correctly infer output shape when axis=1
jreback Nov 30, 2017
534e65d
tests for dicts and result_type='infer'
jreback Jan 28, 2018
24c1b6e
clean up broadcast tests
jreback Feb 4, 2018
4789970
rename infer to expand
jreback Feb 4, 2018
914e136
deprecate reduce
jreback Feb 4, 2018
ad9cbd9
validate result_type kwarg
jreback Feb 5, 2018
6e1819a
docs
jreback Feb 5, 2018
1363c03
doc
jreback Feb 6, 2018
dc6ed74
broadcast should preserve like-columns
jreback Feb 6, 2018
69084ea
update doc-string
jreback Feb 6, 2018
8a1837c
test for Series with broadcast=True, raises when passed incorrect shape
jreback Feb 6, 2018
1d93380
broadcast always returns original column names
jreback Feb 7, 2018
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validate result_type kwarg
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@jreback
jreback committed Feb 7, 2018
commit ad9cbd95e7ba8866dcb81a7cdf50f88c682d1eac
4 changes: 4 additions & 0 deletions pandas/core/apply.py
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Expand Up @@ -39,6 +39,10 @@ def __init__(self, obj, func, broadcast, raw, reduce, result_type,
self.args = args or ()
self.kwds = kwds or {}

if result_type not in [None, 'reduce', 'broadcast', 'expand']:
raise ValueError("invalid value for result_type, must be one "
"of {None, 'reduce', 'broadcast', 'expand'}")

if broadcast is not None:
warnings.warn("The broadcast argument is deprecated and will "
"be removed in a future version. You can specify "
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2 changes: 1 addition & 1 deletion pandas/io/formats/style.py
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Expand Up @@ -510,7 +510,7 @@ def _apply(self, func, axis=0, subset=None, **kwargs):
data = self.data.loc[subset]
if axis is not None:
result = data.apply(func, axis=axis,
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@TomAugspurger I had to do this work-around here to push a list-like result into a frame (which we are breaking generally in this patch, but here style is relying on this, so kind of ok with this behavior, I have to add some more tests); this is from pandas/tests/io/formats/test_style.test_apply_axis

. e.g.

In [5]:         df = pd.DataFrame({'A': [0, 0], 'B': [1, 1]})
   ...:         f = lambda x: ['val: {max}'.format(max=x.max()) for v in x]
   ...: 

In [6]: df
Out[6]: 
   A  B
0  0  1
1  0  1

In [7]: df.apply(f, axis=1)
Out[7]: 
0    [val: 1, val: 1]
1    [val: 1, val: 1]
dtype: object

In [8]: df.apply(f, axis=1, result_type='infer')
Out[8]: 
        A       B
0  val: 1  val: 1
1  val: 1  val: 1

I am not entirely sure why you need this this way.

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The above snippet is no longer correct (I mean: in the meantime we have chosen to not preserve the original columns names when a list is returned, so this will have column names [0, 1]).

This has no impact on the style code?

result_type='infer', **kwargs)
result_type='expand', **kwargs)
result.columns = data.columns
else:
result = func(data, **kwargs)
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12 changes: 12 additions & 0 deletions pandas/tests/frame/test_apply.py
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Expand Up @@ -750,6 +750,18 @@ def test_result_type(self):
expected.columns = columns
assert_frame_equal(result, expected)

@pytest.mark.parametrize("result_type", ['foo', 1])
def test_result_type_error(self, result_type):
# allowed result_type
df = DataFrame(
np.tile(np.arange(3, dtype='int64'), 6).reshape(6, -1) + 1,
columns=['A', 'B', 'C'])

with pytest.raises(ValueError):
df.apply(lambda x: [1, 2, 3],
axis=1,
result_type=result_type)

@pytest.mark.parametrize(
"box",
[lambda x: list(x),
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