Merge pull request #559 from ioam/gridcolumns_fixes

Various small fixes for GridColumns

holoviews/core/data.py

@@ -1386,13 +1386,13 @@ def init(cls, eltype, data, kdims, vdims):
 
         kdim_names = [d.name if isinstance(d, Dimension) else d for d in kdims]
         vdim_names = [d.name if isinstance(d, Dimension) else d for d in vdims]
-        expected = [len(data[kd]) for kd in kdim_names]
+        expected = tuple([len(data[kd]) for kd in kdim_names])
         for vdim in vdim_names:
             shape = data[vdim].shape
-            if shape != tuple(expected):
-                raise ValueError('Key dimension values and value array %s'
+            if shape != expected and not (not expected and shape == (1,)):
+                raise ValueError('Key dimension values and value array %s '
                                  'shape do not match. Expected shape %s, '
-                                 'actual shape: %s' % (expected, vdim, shape))
+                                 'actual shape: %s' % (vdim, expected, shape))
         return data, kdims, vdims
 
 
@@ -1456,10 +1456,15 @@ def groupby(cls, columns, dim_names, container_type, group_type, **kwargs):
 
         # Iterate over the unique entries applying selection masks
         grouped_data = []
-        for unique_key in zip(util.cartesian_product(keys)):
+        for unique_key in zip(*util.cartesian_product(keys)):
             group_data = cls.select(columns, **dict(zip(dim_names, unique_key)))
-            for vdim in columns.vdims:
-                group_data[vdim.name] = np.squeeze(group_data[vdim.name])
+            if np.isscalar(group_data):
+                group_data = {columns.vdims[0].name: np.atleast_1d(group_data)}
+                for dim, v in zip(dim_names, unique_key):
+                    group_data[dim] = np.atleast_1d(v)
+            else:
+                for vdim in columns.vdims:
+                    group_data[vdim.name] = np.squeeze(group_data[vdim.name])
             group_data = group_type(group_data, **group_kwargs)
             grouped_data.append((tuple(unique_key), group_data))
 

tests/testcolumns.py

@@ -475,3 +475,6 @@ def test_columns_sort_vdim_hm(self):
         with self.assertRaisesRegexp(Exception, exception):
             self.columns_hm.sort('y')
 
+
+    def test_columns_groupby(self):
+        self.assertEqual(self.columns_hm.groupby('x').keys(), list(self.xs))