BUG: pivot table bug with Categorical indexes, #10993

doc/source/whatsnew/v0.17.1.txt

@@ -87,7 +87,7 @@ Bug Fixes
 
 - Bug in list-like indexing with a mixed-integer Index (:issue:`11320`)
 
-
+- Bug in ``pivot_table`` with ``margins=True`` when indexes are of ``Categorical`` dtype (:issue:`10993`)
 - Bug in ``DataFrame.plot`` cannot use hex strings colors (:issue:`10299`)
 
 

pandas/core/index.py

@@ -627,6 +627,10 @@ def astype(self, dtype):
         return Index(self.values.astype(dtype), name=self.name,
                      dtype=dtype)
 
+    def _to_safe_for_reshape(self):
+        """ convert to object if we are a categorical """
+        return self
+
     def to_datetime(self, dayfirst=False):
         """
         For an Index containing strings or datetime.datetime objects, attempt
@@ -3190,6 +3194,10 @@ def duplicated(self, keep='first'):
         from pandas.hashtable import duplicated_int64
         return duplicated_int64(self.codes.astype('i8'), keep)
 
+    def _to_safe_for_reshape(self):
+        """ convert to object if we are a categorical """
+        return self.astype('object')
+
     def get_loc(self, key, method=None):
         """
         Get integer location for requested label
@@ -4529,6 +4537,10 @@ def format(self, space=2, sparsify=None, adjoin=True, names=False,
         else:
             return result_levels
 
+    def _to_safe_for_reshape(self):
+        """ convert to object if we are a categorical """
+        return self.set_levels([ i._to_safe_for_reshape() for i in self.levels ])
+
     def to_hierarchical(self, n_repeat, n_shuffle=1):
         """
         Return a MultiIndex reshaped to conform to the

pandas/core/internals.py

@@ -3427,6 +3427,9 @@ def insert(self, loc, item, value, allow_duplicates=False):
         if not isinstance(loc, int):
             raise TypeError("loc must be int")
 
+        # insert to the axis; this could possibly raise a TypeError
+        new_axis = self.items.insert(loc, item)
+
         block = make_block(values=value,
                            ndim=self.ndim,
                            placement=slice(loc, loc+1))
@@ -3449,8 +3452,7 @@ def insert(self, loc, item, value, allow_duplicates=False):
             self._blklocs = np.insert(self._blklocs, loc, 0)
             self._blknos = np.insert(self._blknos, loc, len(self.blocks))
 
-        self.axes[0] = self.items.insert(loc, item)
-
+        self.axes[0] = new_axis
         self.blocks += (block,)
         self._shape = None
 

pandas/tools/pivot.py

@@ -189,7 +189,13 @@ def _add_margins(table, data, values, rows, cols, aggfunc):
     margin_dummy = DataFrame(row_margin, columns=[key]).T
 
     row_names = result.index.names
-    result = result.append(margin_dummy)
+    try:
+        result = result.append(margin_dummy)
+    except TypeError:
+
+        # we cannot reshape, so coerce the axis
+        result.index = result.index._to_safe_for_reshape()
+        result = result.append(margin_dummy)
     result.index.names = row_names
 
     return result
@@ -218,6 +224,7 @@ def _compute_grand_margin(data, values, aggfunc):
 
 
 def _generate_marginal_results(table, data, values, rows, cols, aggfunc, grand_margin):
+
     if len(cols) > 0:
         # need to "interleave" the margins
         table_pieces = []
@@ -235,7 +242,13 @@ def _all_key(key):
 
                 # we are going to mutate this, so need to copy!
                 piece = piece.copy()
-                piece[all_key] = margin[key]
+                try:
+                    piece[all_key] = margin[key]
+                except TypeError:
+
+                    # we cannot reshape, so coerce the axis
+                    piece.set_axis(cat_axis, piece._get_axis(cat_axis)._to_safe_for_reshape())
+                    piece[all_key] = margin[key]
 
                 table_pieces.append(piece)
                 margin_keys.append(all_key)

pandas/tools/tests/test_pivot.py

@@ -719,6 +719,26 @@ def test_crosstab_dropna(self):
                                     ('two', 'dull'), ('two', 'shiny')])
         assert_equal(res.columns.values, m.values)
 
+    def test_categorical_margins(self):
+        # GH 10989
+        df = pd.DataFrame({'x': np.arange(8),
+                           'y': np.arange(8) // 4,
+                           'z': np.arange(8) % 2})
+
+        expected = pd.DataFrame([[1.0, 2.0, 1.5],[5, 6, 5.5],[3, 4, 3.5]])
+        expected.index = Index([0,1,'All'],name='y')
+        expected.columns = Index([0,1,'All'],name='z')
+
+        data = df.copy()
+        table = data.pivot_table('x', 'y', 'z', margins=True)
+        tm.assert_frame_equal(table, expected)
+
+        data = df.copy()
+        data.y = data.y.astype('category')
+        data.z = data.z.astype('category')
+        table = data.pivot_table('x', 'y', 'z', margins=True)
+        tm.assert_frame_equal(table, expected)
+
 if __name__ == '__main__':
     import nose
     nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],