Backport PR #60553: TST: filter possible RuntimeWarning in tests (#60555)

* Backport PR #60553: TST: filter possible RuntimeWarning in tests

* add more ignores

Author: mroeschke

pandas/tests/extension/test_interval.py

@@ -90,6 +90,31 @@ def _supports_reduction(self, ser: pd.Series, op_name: str) -> bool:
     def test_fillna_length_mismatch(self, data_missing):
         super().test_fillna_length_mismatch(data_missing)
 
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
+    def test_hash_pandas_object(self, data):
+        super().test_hash_pandas_object(data)
+
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
+    def test_hash_pandas_object_works(self, data, as_frame):
+        super().test_hash_pandas_object_works(data, as_frame)
+
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
+    @pytest.mark.parametrize("engine", ["c", "python"])
+    def test_EA_types(self, engine, data, request):
+        super().test_EA_types(engine, data, request)
+
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
+    def test_astype_str(self, data):
+        super().test_astype_str(data)
+
 
 # TODO: either belongs in tests.arrays.interval or move into base tests.
 def test_fillna_non_scalar_raises(data_missing):

pandas/tests/frame/methods/test_to_numpy.py

@@ -1,4 +1,5 @@
 import numpy as np
+import pytest
 
 import pandas.util._test_decorators as td
 
@@ -41,6 +42,9 @@ def test_to_numpy_copy(self, using_copy_on_write):
         else:
             assert df.to_numpy(copy=False, na_value=np.nan).base is arr
 
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
     def test_to_numpy_mixed_dtype_to_str(self):
         # https://github.com/pandas-dev/pandas/issues/35455
         df = DataFrame([[Timestamp("2020-01-01 00:00:00"), 100.0]])

pandas/tests/frame/test_constructors.py

@@ -2450,6 +2450,9 @@ def test_construct_with_two_categoricalindex_series(self):
         )
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
     def test_constructor_series_nonexact_categoricalindex(self):
         # GH 42424
         ser = Series(range(100))

pandas/tests/groupby/test_categorical.py

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

pandas/tests/groupby/test_groupby.py

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

pandas/tests/indexes/interval/test_astype.py

@@ -186,6 +186,12 @@ def test_subtype_datetimelike(self, index, subtype):
         with pytest.raises(TypeError, match=msg):
             index.astype(dtype)
 
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
+    def test_astype_category(self, index):
+        super().test_astype_category(index)
+
 
 class TestDatetimelikeSubtype(AstypeTests):
     """Tests specific to IntervalIndex with datetime-like subtype"""

pandas/tests/indexes/interval/test_formats.py

@@ -59,6 +59,9 @@ def test_repr_floats(self):
         expected = "(329.973, 345.137]    1\n(345.137, 360.191]    2\ndtype: int64"
         assert result == expected
 
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
     @pytest.mark.parametrize(
         "tuples, closed, expected_data",
         [

pandas/tests/indexes/interval/test_indexing.py

@@ -341,6 +341,9 @@ def test_get_indexer_categorical(self, target, ordered):
         expected = index.get_indexer(target)
         tm.assert_numpy_array_equal(result, expected)
 
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
     def test_get_indexer_categorical_with_nans(self):
         # GH#41934 nans in both index and in target
         ii = IntervalIndex.from_breaks(range(5))

pandas/tests/indexes/test_setops.py

@@ -519,6 +519,7 @@ def test_intersection_difference_match_empty(self, index, sort):
         tm.assert_index_equal(inter, diff, exact=True)
 
 
+@pytest.mark.filterwarnings("ignore:invalid value encountered in cast:RuntimeWarning")
 @pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
 @pytest.mark.parametrize(
     "method", ["intersection", "union", "difference", "symmetric_difference"]

pandas/tests/io/excel/test_writers.py

@@ -755,6 +755,9 @@ def test_excel_date_datetime_format(self, ext, path):
         # we need to use df_expected to check the result.
         tm.assert_frame_equal(rs2, df_expected)
 
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
     def test_to_excel_interval_no_labels(self, path, using_infer_string):
         # see gh-19242
         #