--- a/ckanext/ga_report/controller.py
+++ b/ckanext/ga_report/controller.py
@@ -1,6 +1,7 @@
 import re
 import csv
 import sys
+import json
 import logging
 import operator
 import collections
@@ -21,6 +22,10 @@
     d = strptime(strdate, '%Y-%m')
     return '%s %s' % (calendar.month_name[d.tm_mon], d.tm_year)
 
+def _get_unix_epoch(strdate):
+    from time import strptime,mktime
+    d = strptime(strdate, '%Y-%m')
+    return int(mktime(d))
 
 def _month_details(cls, stat_key=None):
     '''
@@ -107,11 +112,26 @@
 
             return key, val
 
+        # Query historic values for sparkline rendering
+        graph_query = model.Session.query(GA_Stat)\
+                .filter(GA_Stat.stat_name=='Totals')\
+                .order_by(GA_Stat.period_name)
+        graph_data = {}
+        for x in graph_query:
+            graph_data[x.key] = graph_data.get(x.key,[])
+            key, val = clean_key(x.key,float(x.value))
+            tooltip = '%s: %s' % (_get_month_name(x.period_name), val)
+            graph_data[x.key].append( (tooltip,x.value) )
+        # Trim the latest month, as it looks like a huge dropoff
+        for key in graph_data:
+            graph_data[key] = graph_data[key][:-1]
+
         c.global_totals = []
         if c.month:
             for e in entries:
                 key, val = clean_key(e.key, e.value)
-                c.global_totals.append((key, val))
+                sparkline = graph_data[e.key]
+                c.global_totals.append((key, val, sparkline))
         else:
             d = collections.defaultdict(list)
             for e in entries:
@@ -121,9 +141,10 @@
                     v = sum(v)
                 else:
                     v = float(sum(v))/float(len(v))
+                sparkline = graph_data[k]
                 key, val = clean_key(k,v)
 
-                c.global_totals.append((key, val))
+                c.global_totals.append((key, val, sparkline))
                 c.global_totals = sorted(c.global_totals, key=operator.itemgetter(0))
 
         keys = {
@@ -161,7 +182,29 @@
 
         for k, v in keys.iteritems():
             q = model.Session.query(GA_Stat).\
-                filter(GA_Stat.stat_name==k)
+                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()
+            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))
+
+            # Buffer the tabular data
             if c.month:
                 entries = []
                 q = q.filter(GA_Stat.period_name==c.month).\
@@ -178,7 +221,7 @@
             # Get the total for each set of values and then set the value as
             # a percentage of the total
             if k == 'Social sources':
-                total = sum([x for n,x in c.global_totals if n == 'Total visits'])
+                total = sum([x for n,x,graph in c.global_totals if n == 'Total visits'])
             else:
                 total = sum([num for _,num in entries])
             setattr(c, v, [(k,_percent(v,total)) for k,v in entries ])