8000 BUG: Groupby selection context not being properly reset by christopherzimmerman · Pull Request #28541 · pandas-dev/pandas · GitHub
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BUG: Groupby selection context not being properly reset #28541

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BUG: Groupby selection context not being properly reset #28541

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b5f01b7
Added failing test for groupby mutation
christopherzimmerman Sep 19, 2019
1dbb12d
Switched implementation to use _group_selection_context
christopherzimmerman Sep 19, 2019
bcab4a0
added whatsnew entry
christopherzimmerman Sep 19, 2019
ca26b64
updated test, removed last instance of not using context manager to f…
christopherzimmerman Sep 20, 2019
c4b0a53
Merge branch 'master' of https://github.com/christopherzimmerman/pand…
christopherzimmerman Oct 21, 2019
7a9e1d1
Rebase from master
christopherzimmerman Oct 21, 2019
f24c05c
Missed a merge
christopherzimmerman Oct 21, 2019
5cc3cb1
Fixed two tests
christopherzimmerman Oct 21, 2019
3050963
Another context needed to be set
christopherzimmerman Oct 21, 2019
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Fixed two tests
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@christopherzimmerman
christopherzimmerman committed Oct 21, 2019
commit 5cc3cb17bc88664d09b098d22e83532896d7519b
4 changes: 2 additions & 2 deletions pandas/tests/groupby/aggregate/test_other.py
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Original file line number Diff line number Diff line change
Expand Up @@ -482,13 +482,13 @@ def test_agg_timezone_round_trip():
assert ts == grouped.first()["B"].iloc[0]

# GH#27110 applying iloc should return a DataFrame
assert ts == grouped.apply(lambda x: x.iloc[0]).iloc[0, 0]
assert ts == grouped.apply(lambda x: x.iloc[0]).drop("A", 1).iloc[0, 0]

ts = df["B"].iloc[2]
assert ts == grouped.last()["B"].iloc[0]

# GH#27110 applying iloc should return a DataFrame
assert ts == grouped.apply(lambda x: x.iloc[-1]).iloc[0, 0]
assert ts == grouped.apply(lambda x: x.iloc[-1]).drop("A", 1).iloc[0, 0]


def test_sum_uint64_overflow():
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2 changes: 1 addition & 1 deletion pandas/tests/groupby/test_grouping.py
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Expand Up @@ -172,7 +172,7 @@ def test_grouper_creation_bug(self):
result = g.sum()
assert_frame_equal(result, expected)

result = g.apply(lambda x: x.sum())
result = g.apply(lambda x: x.sum()).drop("A", 1)
assert_frame_equal(result, expected)

g = df.groupby(pd.Grouper(key="A", axis=0))
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