diff --git a/panoramix/forms.py b/panoramix/forms.py
index aff476699b..814fc0e972 100644
--- a/panoramix/forms.py
+++ b/panoramix/forms.py
@@ -116,6 +116,14 @@ class FormFactory(object):
                     'black_white']),
                 default='fire',
                 description=""),
+            'normalize_across': SelectField(
+                'Normalize Across', choices=self.choicify([
+                    'heatmap', 'x', 'y']),
+                default='heatmap',
+                description=(
+                    "Color will be rendered based on a ratio "
+                    "of the cell against the sum of across this "
+                    "criteria")),
             'canvas_image_rendering': SelectField(
                 'Rendering', choices=(
                     ('pixelated', 'pixelated (Sharp)'),
diff --git a/panoramix/static/panoramix.js b/panoramix/static/panoramix.js
index be0f71da6a..019ceacf39 100644
--- a/panoramix/static/panoramix.js
+++ b/panoramix/static/panoramix.js
@@ -25,7 +25,11 @@ var color = function(){
     // Returns a linear scaler our of an array of color
     if(!Array.isArray(colors))
       colors = spectrums[colors];
-    var ext = d3.extent(data, accessor);
+    if(data !== undefined)
+      var ext = d3.extent(data, accessor);
+    else
+      var ext = [0,1];
+
     var points = [];
     var chunkSize = (ext[1] - ext[0]) / colors.length;
     $.each(colors, function(i, c){
diff --git a/panoramix/static/widgets/viz_heatmap.js b/panoramix/static/widgets/viz_heatmap.js
index 7c81477652..8a04ab0581 100644
--- a/panoramix/static/widgets/viz_heatmap.js
+++ b/panoramix/static/widgets/viz_heatmap.js
@@ -7,6 +7,7 @@ px.registerViz('heatmap', function(slice) {
     var height = slice.height();
     var hmWidth = width - (margins.l + margins.r)
     var hmHeight = height - (margins.b + margins.t)
+    var fp = d3.format('.3p');
     d3.json(slice.jsonEndpoint(), function(error, payload) {
       var matrix = {};
       if (error){
@@ -39,9 +40,7 @@ px.registerViz('heatmap', function(slice) {
       var X = 0, Y = 1;
       var heatmapDim = [xRbScale.domain().length, yRbScale.domain().length];
 
-      var color = px.color.colorScalerFactory(
-        fd.linear_color_scheme, data, function(d){return d.v});
-
+      var color = px.color.colorScalerFactory(fd.linear_color_scheme);
 
       var scale = [
         d3.scale.linear()
@@ -99,6 +98,7 @@ px.registerViz('heatmap', function(slice) {
                 s += "<div><b>" + fd.all_columns_x + ": </b>" + obj.x + "<div>"
                 s += "<div><b>" + fd.all_columns_y +": </b>" + obj.y + "<div>"
                 s += "<div><b>" + fd.metric + ": </b>" + obj.v + "<div>"
+                s += "<div><b>%: </b>" + fp(obj.perc) + "<div>"
                 return s;
               }
           })
@@ -146,7 +146,7 @@ px.registerViz('heatmap', function(slice) {
         image = context.createImageData(heatmapDim[0], heatmapDim[1]);
         var pixs = {};
         $.each(data, function(i, d) {
-            var c = d3.rgb(color(d.v));
+            var c = d3.rgb(color(d.perc));
             var x = xScale(d.x);
             var y = yScale(d.y);
             pixs[x + (y*xScale.domain().length)] = c;
diff --git a/panoramix/viz.py b/panoramix/viz.py
index bfeb15584f..6fd7702f30 100644
--- a/panoramix/viz.py
+++ b/panoramix/viz.py
@@ -1213,6 +1213,7 @@ class HeatmapViz(BaseViz):
             'linear_color_scheme',
             ('xscale_interval', 'yscale_interval'),
             'canvas_image_rendering',
+            'normalize_across',
         )
     },)
     def query_obj(self):
@@ -1233,6 +1234,23 @@ class HeatmapViz(BaseViz):
         else:
             df = df[[x, y, v]]
             df.columns = ['x', 'y', 'v']
+        norm = fd.get('normalize_across')
+        overall = False
+        if norm == 'heatmap':
+            overall = True
+        else:
+            gb = df.groupby(norm, group_keys=False)
+            if len(gb) <= 1:
+                overall = True
+            else:
+                df['perc'] = (
+                    gb.apply(
+                        lambda x: (x.v - x.v.min()) / (x.v.max() - x.v.min()))
+                )
+        if overall:
+            v = df.v
+            min_ = v.min()
+            df['perc'] = (v - min_) / (v.max() - min_)
         return df.to_json(orient="records")