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Fixes groupby.apply() error when no returns #9684 #9685

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Fixes groupby.apply() error when no returns #9684 #9685

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3 changes: 1 addition & 2 deletions doc/source/whatsnew/v0.16.1.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -99,11 +99,10 @@ Bug Fixes


- Bug in ``transform`` causing length mismatch when null entries were present and a fast aggregator was being used (:issue:`9697`)

- Bug in ``equals`` causing false negatives when block order differed (:issue:`9330`)

- Bug in ``DataFrame`` slicing may not retain metadata (:issue:`9776`)
- Bug where ``TimdeltaIndex`` were not properly serialized in fixed ``HDFStore`` (:issue:`9635`)
- Fixed bug in ``groupby.apply()`` that would raise an error the user passed function either returned nothing or only returned values of ``None``. (:issue:`9685`)

- Bug in plotting continuously using ``secondary_y`` may not show legend properly. (:issue:`9610`, :issue:`9779`)

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7 changes: 6 additions & 1 deletion pandas/core/groupby.py
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Expand Up @@ -2808,7 +2808,12 @@ def _wrap_applied_output(self, keys, values, not_indexed_same=False):

# make Nones an empty object
if com._count_not_none(*values) != len(values):
v = next(v for v in values if v is not None)
try:
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v = [ v for v in values if v is not None ]
if not v:
    return DataFrame()

v = next(v for v in values if v is not None)
except StopIteration:
# If all values are None, then this will throw an error.
# We'd prefer it return an empty dataframe.
return DataFrame()
if v is None:
return DataFrame()
elif isinstance(v, NDFrame):
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11 changes: 11 additions & 0 deletions pandas/tests/test_groupby.py
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Expand Up @@ -5053,6 +5053,17 @@ def test_groupby_categorical_two_columns(self):
"C3":[nan,nan,nan,nan, 10,100,nan,nan, nan,nan,200,34]}, index=idx)
tm.assert_frame_equal(res, exp)

def test_groupby_apply_all_none(self):
# Tests to make sure no errors if apply function returns all None
# values. Issue 9684.
test_df = DataFrame({'groups': [0,0,1,1], 'random_vars': [8,7,4,5]})

def test_func(x):
pass
result = test_df.groupby('groups').apply(test_func)
expected = DataFrame()
tm.assert_frame_equal(result, expected)


def assert_fp_equal(a, b):
assert (np.abs(a - b) < 1e-12).all()
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