BUG: fix IntervalIndex for pivot table raise type error

doc/source/whatsnew/v0.24.2.rst

@@ -59,6 +59,7 @@ Bug Fixes
 
 - Bug in :meth:`~pandas.core.groupby.GroupBy.transform` where applying a function to a timezone aware column would return a timezone naive result (:issue:`24198`)
 - Bug in :func:`DataFrame.join` when joining on a timezone aware :class:`DatetimeIndex` (:issue:`23931`)
+- Bug in :func:`DataFrame.pivot_table` where use :class:`IntervalIndex` as pivot index would raise TypeError (:issue:`25814`)
 
 **Visualization**
 

pandas/core/arrays/categorical.py

@@ -181,7 +181,7 @@ def contains(cat, key, container):
     #  can't be in container either.
     try:
         loc = cat.categories.get_loc(key)
-    except KeyError:
+    except (KeyError, TypeError):
         return False
 
     # loc is the location of key in categories, but also the *value*

pandas/tests/reshape/test_pivot.py

@@ -19,6 +19,18 @@ def dropna(request):
     return request.param
 
 
+@pytest.fixture(
+    params=[
+        pd.Categorical([pd.Interval(0, 1, 'right')] * 4),
+        pd.Categorical([pd.Interval(0, 1, 'left')] * 4),
+        pd.Categorical([pd.Interval(low, high, 'right')
+                        for low, high in zip(range(0, 3), range(1, 4))]),
+        pd.Categorical([pd.Interval(low, high, 'left')
+                        for low, high in zip(range(0, 3), range(1, 4))])])
+def interval_values(request):
+    return request.param
+
+
 class TestPivotTable:
 
     def setup_method(self, method):
@@ -198,6 +210,18 @@ def test_pivot_with_non_observable_dropna(self, dropna):
 
         tm.assert_frame_equal(result, expected)
 
+    def test_pivot_with_interval_index(self, interval_values, dropna):
+        # GH 25814
+        df = pd.DataFrame(
+            {'A': interval_values,
+             'B': [1] * interval_values.size})
+        result = df.pivot_table(index='A', values='B', dropna=dropna)
+        expected = pd.DataFrame(
+            {'B': [1]},
+            index=pd.Index(interval_values.unique(),
+                           name='A'))
+        tm.assert_frame_equal(result, expected)
+
     def test_pass_array(self):
         result = self.data.pivot_table(
             'D', index=self.data.A, columns=self.data.C)