BUG: pivot_table raising TypeError with ea dtype and dropna True

doc/source/whatsnew/v1.5.0.rst

@@ -1027,6 +1027,7 @@ Reshaping
 - Bug in :func:`concat` losing dtype of columns when ``join="outer"`` and ``sort=True`` (:issue:`47329`)
 - Bug in :func:`concat` not sorting the column names when ``None`` is included (:issue:`47331`)
 - Bug in :func:`concat` with identical key leads to error when indexing :class:`MultiIndex` (:issue:`46519`)
+- Bug in :func:`pivot_table` raising ``TypeError`` when ``dropna=True`` and aggregation column has extension array dtype (:issue:`47477`)
 - Bug in :meth:`DataFrame.join` with a list when using suffixes to join DataFrames with duplicate column names (:issue:`46396`)
 - Bug in :meth:`DataFrame.pivot_table` with ``sort=False`` results in sorted index (:issue:`17041`)
 - Bug in :meth:`concat` when ``axis=1`` and ``sort=False`` where the resulting Index was a :class:`Int64Index` instead of a :class:`RangeIndex` (:issue:`46675`)

pandas/core/reshape/pivot.py

@@ -178,7 +178,9 @@ def __internal_pivot_table(
                 and v in agged
                 and not is_integer_dtype(agged[v])
             ):
-                if not isinstance(agged[v], ABCDataFrame):
+                if not isinstance(agged[v], ABCDataFrame) and isinstance(
+                    data[v].dtype, np.dtype
+                ):
                     # exclude DataFrame case bc maybe_downcast_to_dtype expects
                     #  ArrayLike
                     # e.g. test_pivot_table_multiindex_columns_doctest_case

pandas/tests/reshape/test_pivot.py

@@ -2223,6 +2223,21 @@ def test_pivot_table_with_margins_and_numeric_columns(self):
 
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize("dropna", [True, False])
+    def test_pivot_ea_dtype_dropna(self, dropna):
+        # GH#47477
+        df = DataFrame({"x": "a", "y": "b", "age": Series([20, 40], dtype="Int64")})
+        result = df.pivot_table(
+            index="x", columns="y", values="age", aggfunc="mean", dropna=dropna
+        )
+        expected = DataFrame(
+            [[30]],
+            index=Index(["a"], name="x"),
+            columns=Index(["b"], name="y"),
+            dtype="Float64",
+        )
+        tm.assert_frame_equal(result, expected)
+
 
 class TestPivot:
     def test_pivot(self):