TST: check_stacklevel=True in various tests (#44449)

Author: rhshadrach

pandas/tests/apply/test_frame_apply.py

@@ -1198,9 +1198,7 @@ def test_nuiscance_columns():
     )
     tm.assert_frame_equal(result, expected)
 
-    with tm.assert_produces_warning(
-        FutureWarning, match="Select only valid", check_stacklevel=False
-    ):
+    with tm.assert_produces_warning(FutureWarning, match="Select only valid"):
         result = df.agg("sum")
     expected = Series([6, 6.0, "foobarbaz"], index=["A", "B", "C"])
     tm.assert_series_equal(result, expected)

pandas/tests/arrays/test_datetimelike.py

@@ -783,9 +783,7 @@ def test_to_perioddelta(self, datetime_index, freqstr):
         with tm.assert_produces_warning(FutureWarning, match=msg):
             # Deprecation GH#34853
             expected = dti.to_perioddelta(freq=freqstr)
-        with tm.assert_produces_warning(
-            FutureWarning, match=msg, check_stacklevel=False
-        ):
+        with tm.assert_produces_warning(FutureWarning, match=msg):
             # stacklevel is chosen to be "correct" for DatetimeIndex, not
             #  DatetimeArray
             result = arr.to_perioddelta(freq=freqstr)

pandas/tests/dtypes/cast/test_promote.py

@@ -411,7 +411,7 @@ def test_maybe_promote_any_with_datetime64(
         # Casting date to dt64 is deprecated
         warn = FutureWarning
 
-    with tm.assert_produces_warning(warn, match=msg, check_stacklevel=False):
+    with tm.assert_produces_warning(warn, match=msg):
         # stacklevel is chosen to make sense when called from higher-level functions
         _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
 

pandas/tests/frame/indexing/test_setitem.py

@@ -949,7 +949,7 @@ def test_setitem_mask_categorical(self):
         df = DataFrame({"cats": catsf, "values": valuesf}, index=idxf)
 
         exp_fancy = exp_multi_row.copy()
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             # issue #37643 inplace kwarg deprecated
             return_value = exp_fancy["cats"].cat.set_categories(
                 ["a", "b", "c"], inplace=True

pandas/tests/frame/methods/test_join.py

@@ -344,9 +344,7 @@ def test_merge_join_different_levels(self):
         columns = ["a", "b", ("a", ""), ("c", "c1")]
         expected = DataFrame(columns=columns, data=[[1, 11, 0, 44], [0, 22, 1, 33]])
         msg = "merging between different levels is deprecated"
-        with tm.assert_produces_warning(
-            FutureWarning, match=msg, check_stacklevel=False
-        ):
+        with tm.assert_produces_warning(FutureWarning, match=msg):
             # stacklevel is chosen to be correct for pd.merge, not DataFrame.join
             result = df1.join(df2, on="a")
         tm.assert_frame_equal(result, expected)

pandas/tests/frame/test_constructors.py

@@ -2664,27 +2664,27 @@ def test_constructor_data_aware_dtype_naive(self, tz_aware_fixture, pydt):
         expected = DataFrame({0: [ts_naive]})
         tm.assert_frame_equal(result, expected)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = DataFrame({0: ts}, index=[0], dtype="datetime64[ns]")
         tm.assert_frame_equal(result, expected)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = DataFrame([ts], dtype="datetime64[ns]")
         tm.assert_frame_equal(result, expected)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = DataFrame(np.array([ts], dtype=object), dtype="datetime64[ns]")
         tm.assert_frame_equal(result, expected)
 
         with tm.assert_produces_warning(FutureWarning):
             result = DataFrame(ts, index=[0], columns=[0], dtype="datetime64[ns]")
         tm.assert_frame_equal(result, expected)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             df = DataFrame([Series([ts])], dtype="datetime64[ns]")
         tm.assert_frame_equal(result, expected)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             df = DataFrame([[ts]], columns=[0], dtype="datetime64[ns]")
         tm.assert_equal(df, expected)
 
@@ -2946,9 +2946,7 @@ def test_tzaware_data_tznaive_dtype(self, constructor):
         ts = Timestamp("2019", tz=tz)
         ts_naive = Timestamp("2019")
 
-        with tm.assert_produces_warning(
-            FutureWarning, match="Data is timezone-aware", check_stacklevel=False
-        ):
+        with tm.assert_produces_warning(FutureWarning, match="Data is timezone-aware"):
             result = constructor(ts, dtype="M8[ns]")
 
         assert np.all(result.dtypes == "M8[ns]")

pandas/tests/groupby/aggregate/test_cython.py

@@ -97,7 +97,7 @@ def test_cython_agg_nothing_to_agg():
 
     frame = DataFrame({"a": np.random.randint(0, 5, 50), "b": ["foo", "bar"] * 25})
 
-    with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+    with tm.assert_produces_warning(FutureWarning):
         result = frame[["b"]].groupby(frame["a"]).mean()
     expected = DataFrame([], index=frame["a"].sort_values().drop_duplicates())
     tm.assert_frame_equal(result, expected)

pandas/tests/groupby/test_function.py

@@ -154,9 +154,7 @@ def test_averages(self, df, method):
             ],
         )
 
-        with tm.assert_produces_warning(
-            FutureWarning, match="Dropping invalid", check_stacklevel=False
-        ):
+        with tm.assert_produces_warning(FutureWarning, match="Dropping invalid"):
             result = getattr(gb, method)(numeric_only=False)
         tm.assert_frame_equal(result.reindex_like(expected), expected)
 

pandas/tests/groupby/test_groupby.py

@@ -904,9 +904,7 @@ def test_omit_nuisance_agg(df, agg_function):
 
 def test_omit_nuisance_warnings(df):
     # GH 38815
-    with tm.assert_produces_warning(
-        FutureWarning, filter_level="always", check_stacklevel=False
-    ):
+    with tm.assert_produces_warning(FutureWarning, filter_level="always"):
         grouped = df.groupby("A")
         result = grouped.skew()
         expected = df.loc[:, ["A", "C", "D"]].groupby("A").skew()

pandas/tests/indexes/datetimes/test_indexing.py

@@ -516,9 +516,7 @@ def test_get_loc_tz_aware(self):
             freq="5s",
         )
         key = Timestamp("2019-12-12 10:19:25", tz="US/Eastern")
-        with tm.assert_produces_warning(
-            FutureWarning, match="deprecated", check_stacklevel=False
-        ):
+        with tm.assert_produces_warning(FutureWarning, match="deprecated"):
             result = dti.get_loc(key, method="nearest")
         assert result == 7433
 

pandas/tests/indexes/datetimes/test_misc.py

@@ -142,9 +142,7 @@ def test_datetimeindex_accessors4(self):
         assert dti.is_month_start[0] == 1
 
     def test_datetimeindex_accessors5(self):
-        with tm.assert_produces_warning(
-            FutureWarning, match="The 'freq' argument", check_stacklevel=False
-        ):
+        with tm.assert_produces_warning(FutureWarning, match="The 'freq' argument"):
             tests = [
                 (Timestamp("2013-06-01", freq="M").is_month_start, 1),
                 (Timestamp("2013-06-01", freq="BM").is_month_start, 0),

pandas/tests/indexes/datetimes/test_scalar_compat.py

@@ -65,9 +65,7 @@ def test_dti_timestamp_fields(self, field):
         expected = getattr(idx, field)[-1]
 
         warn = FutureWarning if field.startswith("is_") else None
-        with tm.assert_produces_warning(
-            warn, match="Timestamp.freq is deprecated", check_stacklevel=False
-        ):
+        with tm.assert_produces_warning(warn, match="Timestamp.freq is deprecated"):
             result = getattr(Timestamp(idx[-1]), field)
         assert result == expected
 

pandas/tests/indexing/test_loc.py

@@ -2630,7 +2630,7 @@ def test_loc_slice_disallows_positional():
     with pytest.raises(TypeError, match=msg):
         df.loc[1:3, 1]
 
-    with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+    with tm.assert_produces_warning(FutureWarning):
         # GH#31840 deprecated incorrect behavior
         df.loc[1:3, 1] = 2
 

pandas/tests/io/formats/style/test_style.py

@@ -749,7 +749,7 @@ def test_applymap_subset_multiindex(self, slice_):
         col = MultiIndex.from_product([["x", "y"], ["A", "B"]])
         df = DataFrame(np.random.rand(4, 4), columns=col, index=idx)
 
-        with tm.assert_produces_warning(warn, match=msg, check_stacklevel=False):
+        with tm.assert_produces_warning(warn, match=msg):
             df.style.applymap(lambda x: "color: red;", subset=slice_).to_html()
 
     def test_applymap_subset_multiindex_code(self):

pandas/tests/resample/test_deprecated.py

@@ -63,12 +63,12 @@ def test_deprecating_on_loffset_and_base():
     # not checking the stacklevel for .groupby().resample() because it's complicated to
     # reconcile it with the stacklevel for Series.resample() and DataFrame.resample();
     # see GH #37603
-    with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+    with tm.assert_produces_warning(FutureWarning):
         df.groupby("a").resample("3T", base=0).sum()
-    with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+    with tm.assert_produces_warning(FutureWarning):
         df.groupby("a").resample("3T", loffset="0s").sum()
     msg = "'offset' and 'base' cannot be present at the same time"
-    with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+    with tm.assert_produces_warning(FutureWarning):
         with pytest.raises(ValueError, match=msg):
             df.groupby("a").resample("3T", base=0, offset=0).sum()
 

pandas/tests/reshape/merge/test_join.py

@@ -630,7 +630,7 @@ def test_join_dups(self):
         dta = x.merge(y, left_index=True, right_index=True).merge(
             z, left_index=True, right_index=True, how="outer"
         )
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             dta = dta.merge(w, left_index=True, right_index=True)
         expected = concat([x, y, z, w], axis=1)
         expected.columns = ["x_x", "y_x", "x_y", "y_y", "x_x", "y_x", "x_y", "y_y"]

pandas/tests/series/accessors/test_cat_accessor.py

@@ -51,7 +51,7 @@ def test_cat_accessor(self):
 
         exp = Categorical(["a", "b", np.nan, "a"], categories=["b", "a"])
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             # issue #37643 inplace kwarg deprecated
             return_value = ser.cat.set_categories(["b", "a"], inplace=True)
 
@@ -88,7 +88,7 @@ def test_cat_accessor_updates_on_inplace(self):
         return_value = ser.drop(0, inplace=True)
         assert return_value is None
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             return_value = ser.cat.remove_unused_categories(inplace=True)
 
         assert return_value is None

pandas/tests/series/test_arithmetic.py

@@ -790,7 +790,7 @@ def test_series_ops_name_retention(
             # GH#37374 logical ops behaving as set ops deprecated
             warn = FutureWarning if is_rlogical and box is Index else None
             msg = "operating as a set operation is deprecated"
-            with tm.assert_produces_warning(warn, match=msg, check_stacklevel=False):
+            with tm.assert_produces_warning(warn, match=msg):
                 # stacklevel is correct for Index op, not reversed op
                 result = op(left, right)
 

pandas/tests/series/test_constructors.py

@@ -1645,12 +1645,12 @@ def test_constructor_data_aware_dtype_naive(self, tz_aware_fixture, pydt):
             ts = ts.to_pydatetime()
         ts_naive = Timestamp("2019")
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = Series([ts], dtype="datetime64[ns]")
         expected = Series([ts_naive])
         tm.assert_series_equal(result, expected)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             result = Series(np.array([ts], dtype=object), dtype="datetime64[ns]")
         tm.assert_series_equal(result, expected)
 

pandas/tests/series/test_logical_ops.py

@@ -279,9 +279,7 @@ def test_reversed_xor_with_index_returns_index(self):
         tm.assert_index_equal(result, expected)
 
         expected = Index.symmetric_difference(idx2, ser)
-        with tm.assert_produces_warning(
-            FutureWarning, match=msg, check_stacklevel=False
-        ):
+        with tm.assert_produces_warning(FutureWarning, match=msg):
             result = idx2 ^ ser
         tm.assert_index_equal(result, expected)
 
@@ -337,9 +335,7 @@ def test_reverse_ops_with_index(self, op, expected):
         idx = Index([False, True])
 
         msg = "operating as a set operation"
-        with tm.assert_produces_warning(
-            FutureWarning, match=msg, check_stacklevel=False
-        ):
+        with tm.assert_produces_warning(FutureWarning, match=msg):
             # behaving as set ops is deprecated, will become logical ops
             result = op(ser, idx)
         tm.assert_index_equal(result, expected)

pandas/tests/test_expressions.py

@@ -287,32 +287,32 @@ def test_bool_ops_warn_on_arithmetic(self, op_str, opname):
             return
 
         with tm.use_numexpr(True, min_elements=5):
-            with tm.assert_produces_warning(check_stacklevel=False):
+            with tm.assert_produces_warning():
                 r = f(df, df)
                 e = fe(df, df)
                 tm.assert_frame_equal(r, e)
 
-            with tm.assert_produces_warning(check_stacklevel=False):
+            with tm.assert_produces_warning():
                 r = f(df.a, df.b)
                 e = fe(df.a, df.b)
                 tm.assert_series_equal(r, e)
 
-            with tm.assert_produces_warning(check_stacklevel=False):
+            with tm.assert_produces_warning():
                 r = f(df.a, True)
                 e = fe(df.a, True)
                 tm.assert_series_equal(r, e)
 
-            with tm.assert_produces_warning(check_stacklevel=False):
+            with tm.assert_produces_warning():
                 r = f(False, df.a)
                 e = fe(False, df.a)
                 tm.assert_series_equal(r, e)
 
-            with tm.assert_produces_warning(check_stacklevel=False):
+            with tm.assert_produces_warning():
                 r = f(False, df)
                 e = fe(False, df)
                 tm.assert_frame_equal(r, e)
 
-            with tm.assert_produces_warning(check_stacklevel=False):
+            with tm.assert_produces_warning():
                 r = f(df, True)
                 e = fe(df, True)
                 tm.assert_frame_equal(r, e)

pandas/tests/window/test_rolling.py

@@ -697,7 +697,7 @@ def test_rolling_count_default_min_periods_with_null_values(frame_or_series):
     expected_counts = [1.0, 2.0, 3.0, 2.0, 2.0, 2.0, 3.0]
 
     # GH 31302
-    with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+    with tm.assert_produces_warning(FutureWarning):
         result = frame_or_series(values).rolling(3).count()
     expected = frame_or_series(expected_counts)
     tm.assert_equal(result, expected)