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TST: Add tests for groupby categorical values with axis=1 #27788

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merged 8 commits into from
Aug 7, 2019
Merged

TST: Add tests for groupby categorical values with axis=1 #27788

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7e461a1
remove \n from docstring
charlesdong1991 Dec 3, 2018
1314059
fix conflicts
charlesdong1991 Jan 19, 2019
8bcb313
Merge remote-tracking branch 'upstream/master'
charlesdong1991 Jul 30, 2019
9e3ff00
Merge remote-tracking branch 'upstream/master' into add_test_21127
charlesdong1991 Aug 5, 2019
ecd9542
Add test for issue 13420
charlesdong1991 Aug 6, 2019
6ff0dfc
Resolve linting error
charlesdong1991 Aug 6, 2019
e63c2d8
Change name
charlesdong1991 Aug 7, 2019
e12da5b
Merge remote-tracking branch 'upstream/master' into add_test_21127
charlesdong1991 Aug 7, 2019
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10 changes: 10 additions & 0 deletions pandas/tests/groupby/test_categorical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1165,3 +1165,13 @@ def test_seriesgroupby_observed_apply_dict(df_cat, observed, index, data):
lambda x: OrderedDict([("min", x.min()), ("max", x.max())])
)
assert_series_equal(result, expected)


@pytest.mark.parametrize("code", [([1, 0, 0]), ([0, 0, 0])])
def test_groupby_categorical_axis_1(code):
# GH 13420
df = DataFrame({"a": [1, 2, 3, 4], "b": [-1, -2, -3, -4], "c": [5, 6, 7, 8]})
grp = pd.Categorical.from_codes(code, categories=list("abc"))
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Can you call this cat instead of grp? The latter is typically the result of an actual groupby

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ok, changed! @WillAyd and thanks for taking a look!

result = df.groupby(grp, axis=1).mean()
expected = df.T.groupby(grp, axis=0).mean().T
assert_frame_equal(result, expected)