Fixup tests

pandas/_testing/__init__.py

@@ -15,6 +15,7 @@
     ContextManager,
     cast,
 )
+import warnings
 
 import numpy as np
 
@@ -306,11 +307,17 @@ def box_expected(expected, box_cls, transpose: bool = True):
         else:
             expected = pd.array(expected, copy=False)
     elif box_cls is Index:
-        expected = Index(expected)
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", "Dtype inference", category=FutureWarning)
+            expected = Index(expected)
     elif box_cls is Series:
-        expected = Series(expected)
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", "Dtype inference", category=FutureWarning)
+            expected = Series(expected)
     elif box_cls is DataFrame:
-        expected = Series(expected).to_frame()
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", "Dtype inference", category=FutureWarning)
+            expected = Series(expected).to_frame()
         if transpose:
             # for vector operations, we need a DataFrame to be a single-row,
             #  not a single-column, in order to operate against non-DataFrame

pandas/tests/tseries/frequencies/test_inference.py

@@ -23,6 +23,7 @@
     date_range,
     period_range,
 )
+import pandas._testing as tm
 from pandas.core.arrays import (
     DatetimeArray,
     TimedeltaArray,
@@ -206,7 +207,8 @@ def test_infer_freq_custom(base_delta_code_pair, constructor):
 )
 def test_infer_freq_index(freq, expected):
     rng = period_range("1959Q2", "2009Q3", freq=freq)
-    rng = Index(rng.to_timestamp("D", how="e").astype(object))
+    with tm.assert_produces_warning(FutureWarning, match="Dtype inference"):
+        rng = Index(rng.to_timestamp("D", how="e").astype(object))
 
     assert rng.inferred_freq == expected