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Bug 29764 groupby loses index name sometimes #33111

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Bug 29764 groupby loses index name sometimes #33111

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94b3bdb
BUG: GroupBy Doesn't Always Maintain Column Index Name #29764
phofl Mar 29, 2020
4b20125
BUG: Add whats new entry #29764
phofl Mar 29, 2020
39825cc
BUG: Modify whats new entry and shorten pop onto dict
Mar 29, 2020
d61ac2b
BUG: Modify whats new entry
phofl Mar 29, 2020
85ff9c8
BUG: Avoid runtime import
phofl Mar 29, 2020
1b765b3
BUG: Add new test and change getattr
phofl Mar 29, 2020
1c3b16c
Parametrize unittests
phofl Apr 12, 2020
303e10c
Merge branch 'master' of https://github.com/pandas-dev/pandas into 29764
phofl Apr 12, 2020
cc5dca3
Merge branch 'master' of https://github.com/pandas-dev/pandas into 29764
phofl Apr 19, 2020
2d8026f
Change type hint
phofl Apr 19, 2020
ffe4f2e
Merge branch 'master' of https://github.com/pandas-dev/pandas into 29764
phofl Jun 15, 2020
bdf9293
Merge branch 'master' of https://github.com/pandas-dev/pandas into 29764
phofl Aug 4, 2020
b750394
Move whats new entry to 1.2
phofl Aug 4, 2020
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v1.1.0.rst
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Expand Up @@ -403,6 +403,7 @@ Groupby/resample/rolling
- Bug in :meth:`GroupBy.apply` raises ``ValueError`` when the ``by`` axis is not sorted and has duplicates and the applied ``func`` does not mutate passed in objects (:issue:`30667`)
- Bug in :meth:`DataFrameGroupby.transform` produces incorrect result with transformation functions (:issue:`30918`)
- Bug in :meth:`DataFrame.groupby` and :meth:`Series.groupby` produces inconsistent type when aggregating Boolean series (:issue:`32894`)
- Bug in :meth:`DataFrame.groupby` does not always maintain column index name for ``any``, ``all``, ``bfill``, ``ffill``, ``shift`` (:issue:`29764`)


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6 changes: 4 additions & 2 deletions pandas/core/groupby/generic.py
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Expand Up @@ -1687,8 +1687,9 @@ def _wrap_aggregated_output(
-------
DataFrame
"""
idx_name = output.pop("idx_name", None)
indexed_output = {key.position: val for key, val in output.items()}
columns = Index(key.label for key in output)
columns = Index([key.label for key in output], name=idx_name)

result = DataFrame(indexed_output)
result.columns = columns
Expand Down Expand Up @@ -1720,8 +1721,9 @@ def _wrap_transformed_output(
-------
DataFrame
"""
idx_name = output.pop("idx_name", None)
indexed_output = {key.position: val for key, val in output.items()}
columns = Index(key.label for key in output)
columns = Index([key.label for key in output], name=idx_name)

result = DataFrame(indexed_output)
result.columns = columns
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5 changes: 4 additions & 1 deletion pandas/core/groupby/groupby.py
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Expand Up @@ -2235,8 +2235,11 @@ def _get_cythonized_result(
grouper = self.grouper

labels, _, ngroups = grouper.group_info
output: Dict[base.OutputKey, np.ndarray] = {}
output: Dict[base.OutputKey, np.ndarray, str:str] = {}
base_func = getattr(libgroupby, how)
obj = self._selected_obj
if isinstance(obj, DataFrame):
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what are you doing here? this is very odd

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@phofl phofl Apr 7, 2020 •
edited
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The function call self._wrap_aggregated_output or self._wrap_transformed_output(output) convert the array containing the results in a DataFrame (or Series, but not important in our case). This is below the marked section. The name of the index is already lost at this point, so I added the name to the output dictionary, which is given as input for this functions. This is not relevant, if the result is a Series, so I check, if we have a DataFrame.

My first idea was to check if the original object was from the type DataFrameGroupBy, but I could not perform this check without importing DataFrameGroupBy during runtime. To avoid this, I used the method you see above.

Does this answer your question?

output["idx_name"] = getattr(getattr(obj, "columns"), "name")

for idx, obj in enumerate(self._iterate_slices()):
name = obj.name
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16 changes: 16 additions & 0 deletions pandas/tests/groupby/test_groupby.py
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Expand Up @@ -2057,3 +2057,19 @@ def test_groups_repr_truncates(max_seq_items, expected):

result = df.groupby(np.array(df.a)).groups.__repr__()
assert result == expected


def test_groupby_column_index_name_lost():
# GH: 29764 groupby loses index sometimes
df = pd.DataFrame([[1]], columns=pd.Index(["a"], name="idx"))
result = df.groupby([1]).sum()
expected = pd.DataFrame([1], columns=pd.Index(["a"], name="idx"), index=[1])
tm.assert_frame_equal(result, expected)

result = df.groupby([1]).any()
expected = pd.DataFrame([True], columns=pd.Index(["a"], name="idx"), index=[1])
tm.assert_frame_equal(result, expected)

result = df.groupby([1]).shift()
expected = pd.DataFrame([np.nan], columns=pd.Index(["a"], name="idx"), index=[0])
tm.assert_frame_equal(result, expected)