BUG: df.replace over pd.Period columns (#34871)

doc/source/whatsnew/v1.2.0.rst

@@ -434,6 +434,8 @@ Strings
 
 Interval
 ^^^^^^^^
+
+- Bug in :meth:`DataFrame.replace` and :meth:`Series.replace` where :class:`Interval` dtypes would be converted to object dtypes (:issue:34871)
 - Bug in :meth:`IntervalIndex.take` with negative indices and ``fill_value=None`` (:issue:`37330`)
 -
 -
@@ -488,6 +490,11 @@ I/O
 - Bug in :class:`HDFStore` threw a ``TypeError`` when exporting an empty :class:`DataFrame` with ``datetime64[ns, tz]`` dtypes with a fixed HDF5 store (:issue:`20594`)
 - Bug in :class:`HDFStore` was dropping timezone information when exporting :class:`Series` with ``datetime64[ns, tz]`` dtypes with a fixed HDF5 store (:issue:`20594`)
 
+Period
+^^^^^^
+
+- Bug in :meth:`DataFrame.replace` and :meth:`Series.replace` where :class:`Period` dtypes would be converted to object dytpes (:issue:34871)
+
 Plotting
 ^^^^^^^^
 

pandas/core/internals/blocks.py

@@ -2002,6 +2002,18 @@ class ObjectValuesExtensionBlock(ExtensionBlock):
     def external_values(self):
         return self.values.astype(object)
 
+    def _can_hold_element(self, element: Any) -> bool:
+        if is_valid_nat_for_dtype(element, self.dtype):
+            return True
+        if element is NaT:
+            return True
+        if isinstance(element, list) and len(element) == 0:
+            return True
+        tipo = maybe_infer_dtype_type(element)
+        if tipo is not None:
+            return issubclass(tipo.type, self.dtype.type)
+        return isinstance(element, self.dtype.type)
+
 
 class NumericBlock(Block):
     __slots__ = ()

pandas/tests/frame/methods/test_replace.py

@@ -1517,17 +1517,15 @@ def test_replace_with_duplicate_columns(self, replacement):
 
         tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.xfail(
-        reason="replace() changes dtype from period to object, see GH34871", strict=True
-    )
-    def test_replace_period_ignore_float(self):
+    @pytest.mark.parametrize("value", [pd.Period("2020-01"), pd.Interval(0, 5)])
+    def test_replace_ea_ignore_float(self, value):
         """
         Regression test for GH#34871: if df.replace(1.0, 0.0) is called on a df
-        with a Period column the old, faulty behavior is to raise TypeError.
+        with a Period/Interval column the old, faulty behavior is to raise TypeError.
         """
-        df = DataFrame({"Per": [pd.Period("2020-01")] * 3})
+        df = DataFrame({"Per": [value] * 3})
         result = df.replace(1.0, 0.0)
-        expected = DataFrame({"Per": [pd.Period("2020-01")] * 3})
+        expected = DataFrame({"Per": [value] * 3})
         tm.assert_frame_equal(expected, result)
 
     def test_replace_value_category_type(self):

pandas/tests/series/methods/test_replace.py

@@ -450,6 +450,18 @@ def test_replace_with_compiled_regex(self):
         expected = pd.Series(["z", "b", "c"])
         tm.assert_series_equal(result, expected)
 
+    @pytest.mark.parametrize("value", [pd.Period("2020-01"), pd.Interval(0, 5)])
+    def test_replace_ea_ignore_float(self, value):
+        """
+        Regression test for corrolary to GH#34871: if series.replace(1.0, 0.0)
+        is called on a Period/Interval Series, the old, faulty behavior
+        is to raise TypeError.
+        """
+        series = pd.Series([value] * 3)
+        result = series.replace(1.0, 0.0)
+        expected = pd.Series([value] * 3)
+        tm.assert_series_equal(expected, result)
+
     @pytest.mark.parametrize("pattern", ["^.$", "."])
     def test_str_replace_regex_default_raises_warning(self, pattern):
         # https://github.com/pandas-dev/pandas/pull/24809