diff --git a/datascience/tables.py b/datascience/tables.py
index 3c3001ac7..828e9794b 100644
--- a/datascience/tables.py
+++ b/datascience/tables.py
@@ -1041,10 +1041,10 @@ def pivot(self, columns, rows, values=None, collect=None, zero=None):
         the values that match both row and column based on ``collect``.
 
         Args:
-            ``columns`` -- a single column label, (``str``), in table, used to
-                create new columns, based on its unique values.
-            ``rows`` -- row labels, as (``str``) or array of strings, used to
-                create new rows based on it's unique values.
+            ``columns`` -- a single column label or index, (``str`` or ``int``),
+                used to create new columns, based on its unique values.
+            ``rows`` -- row labels or indices, (``str`` or ``int`` or list),
+                used to create new rows based on it's unique values.
             ``values`` -- column label in table for use in aggregation.
                 Default None.
             ``collect`` -- aggregation function, used to group ``values``
@@ -1106,6 +1106,7 @@ def pivot(self, columns, rows, values=None, collect=None, zero=None):
             raise TypeError('collect requires values to be specified')
         if values is not None and collect is None:
             raise TypeError('values requires collect to be specified')
+        columns = self._as_label(columns)
         rows = self._as_labels(rows)
         if values is None:
             selected = self.select([columns] + rows)
diff --git a/tests/test_tables.py b/tests/test_tables.py
index 9d36d5dbe..15756619b 100644
--- a/tests/test_tables.py
+++ b/tests/test_tables.py
@@ -423,6 +423,16 @@ def test_pivot_counts(t):
     True  | 1 | 2 | 0
     """)
 
+def test_pivot_counts_with_indices(t):
+    t = t.copy()
+    t.append(('e', 12, 1, 12))
+    t['early'] = t['letter'] < 'd'
+    test = t.pivot(2, 4)
+    assert_equal(test, """
+    early | 1 | 2 | 10
+    False | 1 | 0 | 1
+    True  | 1 | 2 | 0
+    """)
 
 def test_pivot_values(t):
     t = t.copy()