Validate that 'name' attribute is set only if hashable

pandas/core/series.py

@@ -17,6 +17,7 @@
                                 _default_index, _maybe_upcast,
                                 _asarray_tuplesafe, _infer_dtype_from_scalar,
                                 is_list_like, _values_from_object,
+                                is_hashable,
                                 _possibly_cast_to_datetime, _possibly_castable,
                                 _possibly_convert_platform, _try_sort,
                                 ABCSparseArray, _maybe_match_name, _coerce_to_dtype,
@@ -105,6 +106,8 @@ class Series(base.IndexOpsMixin, generic.NDFrame):
         dict.
     dtype : numpy.dtype or None
         If None, dtype will be inferred
+    name :  used to attach metadata to a Series, e.g., as str or namedtuple. 
+            Must be hashable, defaults to None.
     copy : boolean, default False
         Copy input data
     """
@@ -272,6 +275,20 @@ def _update_inplace(self, result, **kwargs):
         # we want to call the generic version and not the IndexOpsMixin
         return generic.NDFrame._update_inplace(self, result, **kwargs)
 
+    # Validate that name is hashable
+    @property
+    def name(self):
+        return self._name
+
+    @name.setter
+    def name(self, value):
+        if is_hashable(value):
+            object.__setattr__(self, '_name', value)
+        else: 
+            raise TypeError('Series.name must be hashable, got %s.' 
+                              % value.__class__.__name__)
+
+
     # ndarray compatibility
     @property
     def dtype(self):

pandas/tests/test_series.py

@@ -644,6 +644,13 @@ def test_constructor_map(self):
         result = Series(m, index=lrange(10, 20))
         exp.index = lrange(10, 20)
         assert_series_equal(result, exp)
+
+    def test_constructor_unhashable_name(self):
+        def set_to_unhashable(s_):
+            s_.name = {}
+        s = Series([1,3], name = 'test')
+        self.assertRaises(TypeError, set_to_unhashable, s)
+        self.assertEqual(s.name, 'test')
 
     def test_constructor_categorical(self):
         cat = pd.Categorical([0, 1, 2, 0, 1, 2], ['a', 'b', 'c'], fastpath=True)
@@ -1980,7 +1987,7 @@ def test_repr(self):
         rep_str = repr(ser)
         self.assertIn("Name: 0", rep_str)
 
-        ser = Series(["a\n\r\tb"], name=["a\n\r\td"], index=["a\n\r\tf"])
+        ser = Series(["a\n\r\tb"], name="a\n\r\td", index=["a\n\r\tf"])
         self.assertFalse("\t" in repr(ser))
         self.assertFalse("\r" in repr(ser))
         self.assertFalse("a\n" in repr(ser))