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add more ignores
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pandas/tests/groupby/test_categorical.py

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@@ -67,6 +67,7 @@ def f(a):
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}
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@pytest.mark.filterwarnings("ignore:invalid value encountered in cast:RuntimeWarning")
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def test_apply_use_categorical_name(df):
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cats = qcut(df.C, 4)
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@@ -338,6 +339,7 @@ def test_apply(ordered):
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tm.assert_series_equal(result, expected)
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@pytest.mark.filterwarnings("ignore:invalid value encountered in cast:RuntimeWarning")
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def test_observed(request, using_infer_string, observed):
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# multiple groupers, don't re-expand the output space
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# of the grouper
@@ -1556,6 +1558,7 @@ def test_dataframe_groupby_on_2_categoricals_when_observed_is_false(
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assert (res.loc[unobserved_cats] == expected).all().all()
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@pytest.mark.filterwarnings("ignore:invalid value encountered in cast:RuntimeWarning")
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def test_series_groupby_categorical_aggregation_getitem():
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# GH 8870
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d = {"foo": [10, 8, 4, 1], "bar": [10, 20, 30, 40], "baz": ["d", "c", "d", "c"]}

pandas/tests/groupby/test_groupby.py

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@@ -3118,6 +3118,7 @@ def test_groupby_numeric_only_std_no_result(numeric_only):
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dfgb.std(numeric_only=numeric_only)
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@pytest.mark.filterwarnings("ignore:invalid value encountered in cast:RuntimeWarning")
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def test_grouping_with_categorical_interval_columns():
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# GH#34164
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df = DataFrame({"x": [0.1, 0.2, 0.3, -0.4, 0.5], "w": ["a", "b", "a", "c", "a"]})

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