Just filter warnings instead

Author: mroeschke

pandas/tests/arrays/interval/test_astype.py

@@ -5,6 +5,7 @@
     CategoricalDtype,
     Index,
     IntervalIndex,
+    Series,
 )
 import pandas._testing as tm
 
@@ -26,3 +27,11 @@ def test_astype_categorical_retains_ordered(self, ordered):
         result = index.astype(dtype)
         expected = Index(expected)
         tm.assert_index_equal(result, expected)
+
+    @pytest.mark.filterwarnings(
+        "ignore:invalid value encountered in cast:RuntimeWarning"
+    )
+    def test_astype_str(self, data):
+        result = Series(data[:2]).astype(str)
+        expected = Series([str(x) for x in data[:2]], dtype=str)
+        tm.assert_series_equal(result, expected)

pandas/tests/extension/test_interval.py

@@ -101,6 +101,31 @@ def test_fillna_limit_series(self, data_missing):
     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_fillna_length_mismatch(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
 
 from pandas import (
     DataFrame,
@@ -31,6 +32,9 @@ def test_to_numpy_copy(self):
         #  and that can be respected because we are already numpy-float
         assert df.to_numpy(copy=False).base is df.values.base
 
+    @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

@@ -2404,6 +2404,9 @@ 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/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

@@ -340,6 +340,9 @@ 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

@@ -525,6 +525,7 @@ 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

@@ -800,6 +800,9 @@ def test_excel_date_datetime_format(self, ext, tmp_excel, tmp_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, tmp_excel, using_infer_string):
         # see gh-19242
         #

pandas/tests/reshape/test_cut.py

@@ -733,6 +733,7 @@ def test_cut_with_duplicated_index_lowest_included():
     tm.assert_series_equal(result, expected)
 
 
+@pytest.mark.filterwarnings("ignore:invalid value encountered in cast:RuntimeWarning")
 def test_cut_with_nonexact_categorical_indices():
     # GH 42424