diff --git a/doc/source/user_guide/io.rst b/doc/source/user_guide/io.rst
index cf153ddd2cbbd..3b7a6037a9715 100644
--- a/doc/source/user_guide/io.rst
+++ b/doc/source/user_guide/io.rst
@@ -5240,6 +5240,7 @@ Write to a feather file.
 Read from a feather file.
 
 .. ipython:: python
+   :okwarning:
 
    result = pd.read_feather("example.feather")
    result
@@ -5323,6 +5324,7 @@ Write to a parquet file.
 Read from a parquet file.
 
 .. ipython:: python
+   :okwarning:
 
    result = pd.read_parquet("example_fp.parquet", engine="fastparquet")
    result = pd.read_parquet("example_pa.parquet", engine="pyarrow")
diff --git a/pandas/core/internals/array_manager.py b/pandas/core/internals/array_manager.py
index 34b3d83c066c2..acadfcbbdf302 100644
--- a/pandas/core/internals/array_manager.py
+++ b/pandas/core/internals/array_manager.py
@@ -61,9 +61,7 @@
 from pandas.core.arrays import (
     DatetimeArray,
     ExtensionArray,
-    IntervalArray,
     PandasArray,
-    PeriodArray,
     TimedeltaArray,
 )
 from pandas.core.arrays.sparse import SparseDtype
@@ -87,6 +85,7 @@
 )
 from pandas.core.internals.blocks import (
     ensure_block_shape,
+    external_values,
     new_block,
     to_native_types,
 )
@@ -1203,12 +1202,7 @@ def dtype(self):
 
     def external_values(self):
         """The array that Series.values returns"""
-        if isinstance(self.array, (PeriodArray, IntervalArray)):
-            return self.array.astype(object)
-        elif isinstance(self.array, (DatetimeArray, TimedeltaArray)):
-            return self.array._data
-        else:
-            return self.array
+        return external_values(self.array)
 
     def internal_values(self):
         """The array that Series._values returns"""
diff --git a/pandas/core/internals/blocks.py b/pandas/core/internals/blocks.py
index 174ea8760b0db..01660e34300ce 100644
--- a/pandas/core/internals/blocks.py
+++ b/pandas/core/internals/blocks.py
@@ -96,7 +96,9 @@
     ExtensionArray,
     FloatingArray,
     IntegerArray,
+    IntervalArray,
     PandasArray,
+    PeriodArray,
     TimedeltaArray,
 )
 from pandas.core.base import PandasObject
@@ -217,16 +219,9 @@ def is_view(self) -> bool:
     def is_categorical(self) -> bool:
         return self._holder is Categorical
 
+    @final
     def external_values(self):
-        """
-        The array that Series.values returns (public attribute).
-
-        This has some historical constraints, and is overridden in block
-        subclasses to return the correct array (e.g. period returns
-        object ndarray and datetimetz a datetime64[ns] ndarray instead of
-        proper extension array).
-        """
-        return self.values
+        return external_values(self.values)
 
     def internal_values(self):
         """
@@ -1770,8 +1765,7 @@ class ObjectValuesExtensionBlock(HybridMixin, ExtensionBlock):
     Series[T].values is an ndarray of objects.
     """
 
-    def external_values(self):
-        return self.values.astype(object)
+    pass
 
 
 class NumericBlock(Block):
@@ -1956,12 +1950,6 @@ def is_view(self) -> bool:
         # check the ndarray values of the DatetimeIndex values
         return self.values._data.base is not None
 
-    def external_values(self):
-        # NB: this is different from np.asarray(self.values), since that
-        #  return an object-dtype ndarray of Timestamps.
-        # Avoid FutureWarning in .astype in casting from dt64tz to dt64
-        return self.values._data
-
 
 class TimeDeltaBlock(DatetimeLikeBlockMixin):
     __slots__ = ()
@@ -2296,3 +2284,23 @@ def to_native_types(
         values[mask] = na_rep
         values = values.astype(object, copy=False)
         return values
+
+
+def external_values(values: ArrayLike) -> ArrayLike:
+    """
+    The array that Series.values returns (public attribute).
+
+    This has some historical constraints, and is overridden in block
+    subclasses to return the correct array (e.g. period returns
+    object ndarray and datetimetz a datetime64[ns] ndarray instead of
+    proper extension array).
+    """
+    if isinstance(values, (PeriodArray, IntervalArray)):
+        return values.astype(object)
+    elif isinstance(values, (DatetimeArray, TimedeltaArray)):
+        # NB: for datetime64tz this is different from np.asarray(values), since
+        #  that returns an object-dtype ndarray of Timestamps.
+        # Avoid FutureWarning in .astype in casting from dt64tz to dt64
+        return values._data
+    else:
+        return values