--- a/ckanext/ga_report/controller.py
+++ b/ckanext/ga_report/controller.py
@@ -192,24 +192,17 @@
                 filter(GA_Stat.stat_name==k).\
                 order_by(GA_Stat.period_name)
             # Run the query on all months to gather graph data
-            series = {}
-            x_axis = set()
+            graph = {}
             for stat in q:
-                x_val = _get_unix_epoch(stat.period_name)
-                series[ stat.key ] = series.get(stat.key,{})
-                series[ stat.key ][x_val] = float(stat.value)
-                x_axis.add(x_val)
-            # Common x-axis for all series. Exclude this month (incomplete data)
-            x_axis = sorted(list(x_axis))[:-1]
-            # Buffer a rickshaw dataset from the series
-            def create_graph(series_name, series_data):
-                return { 
-                    'name':series_name, 
-                    'data':[ {'x':x,'y':series_data.get(x,0)} for x in x_axis ]
-                    }
-            rickshaw = [ create_graph(name,data) for name, data in series.items() ]
-            rickshaw = sorted(rickshaw,key=lambda x:x['data'][-1]['y'])
-            setattr(c, v+'_graph', json.dumps(rickshaw))
+                graph[ stat.key ] = graph.get(stat.key,{
+                    'name':stat.key, 
+                    'data': []
+                    })
+                graph[ stat.key ]['data'].append({
+                    'x':_get_unix_epoch(stat.period_name),
+                    'y':float(stat.value)
+                    })
+            setattr(c, v+'_graph', json.dumps( _to_rickshaw(graph.values(),percentageMode=True) ))
 
             # Buffer the tabular data
             if c.month:
@@ -409,22 +402,63 @@
                 'x':_get_unix_epoch(entry.period_name),
                 'y':int(entry.pageviews),
                 })
-
+                    
         c.graph_data = json.dumps( _to_rickshaw(graph_data.values()) )
 
         return render('ga_report/publisher/read.html')
 
-def _to_rickshaw(data):
-    num_points = []    
-    for package in data:
-        package['data'] = sorted( package['data'], key=lambda x:x['x'] )
-        num_points.append( len(package['data']) )
-    if len(set(num_points))>1:
-        example = num_points[ num_points.index(max(num_points)) ]
-        for package in data:
-            while len(package['data'])<example:
-                package['data'].insert(0, package['data'][0])
+def _to_rickshaw(data, percentageMode=False):
+    if data==[]:
+        return data
+    # Create a consistent x-axis
+    num_points = [ len(series['data']) for series in data ]
+    ideal_index = num_points.index( max(num_points) )
+    x_axis = [ point['x'] for point in data[ideal_index]['data'] ]
+    for series in data:
+        xs = [ point['x'] for point in series['data'] ]
+        assert set(xs).issubset( set(x_axis) ), (xs, x_axis)
+        # Zero pad any missing values
+        for x in set(x_axis).difference(set(xs)):
+            series['data'].append( {'x':x, 'y':0} )
+        assert len(series['data'])==len(x_axis), (len(series['data']),len(x_axis),series['data'],x_axis,set(x_axis).difference(set(xs)))
+    if percentageMode:
+        def get_totals(series_list):
+            totals = {}
+            for series in series_list:
+                for point in series['data']:
+                    totals[point['x']] = totals.get(point['x'],0) + point['y']
+            lengths = [ len(series['data']) for series in series_list ]
+            assert len(set(lengths))==1
+            assert lengths[0] == len(totals)
+            return totals
+        # Transform data into percentage stacks
+        totals = get_totals(data)
+        # Roll insignificant series into a catch-all
+        THRESHOLD = 0.01
+        raw_data = data
+        data = []
+        for series in raw_data:
+            for point in series['data']:
+                fraction = float(point['y']) / totals[point['x']]
+                if not (series in data) and fraction>THRESHOLD:
+                    data.append(series)
+        # Overwrite data with a set of intereting series
+        others = [ x for x in raw_data if not (x in data) ]
+        data.append({ 
+            'name':'Other',
+            'data': [ {'x':x,'y':y} for x,y in get_totals(others).items() ] 
+            })
+        # Turn each point into a percentage
+        for series in data:
+            for point in series['data']:
+                point['y'] = (point['y']*100) / totals[point['x']]
+    # Sort the points
+    for series in data:
+        series['data'] = sorted( series['data'], key=lambda x:x['x'] )
+        # Strip the latest month's incomplete analytics
+        series['data'] = series['data'][:-1]
     return data
+
 
 def _get_top_publishers(limit=20):
     '''