Ability to aggregate over any point property

This needed a change in the supercluster npm module, a PR was placed here:
mapbox/supercluster#12

caravel/assets/package.json

@@ -74,7 +74,7 @@
     "select2": "3.5",
     "select2-bootstrap-css": "^1.4.6",
     "style-loader": "^0.13.0",
-    "supercluster": "^2.1.0",
+    "supercluster": "https://github.com/georgeke/supercluster/tarball/ac3492737e7ce98e07af679623aad452373bbc40",
     "topojson": "^1.6.22",
     "transform-loader": "^0.2.3",
     "viewport-mercator-project": "^2.1.0",

caravel/assets/visualizations/mapbox.jsx

@@ -47,7 +47,7 @@ class ScatterPlotGlowOverlay extends ScatterPlotOverlay {
           ctx.beginPath();
 
           if (location.get("properties").get("cluster")) {
-            var scaledRadius = d3.round(
+            var scaledRadius = maxCount === minCount ? radius : d3.round(
                   (location.get("properties").get("point_count") - minCount) /
                   (maxCount - minCount) * radius + radius / 2, 1
                 ),
@@ -69,7 +69,9 @@ class ScatterPlotGlowOverlay extends ScatterPlotOverlay {
 
             ctx.textAlign = "center";
             ctx.fillText(
-              location.get("properties").get("point_count_abbreviated"),
+              location.get("properties").get("metric")
+                ? location.get("properties").get("metric")
+                : location.get("properties").get("point_count_abbreviated"),
               pixelRounded[0],
               pixelRounded[1] + d3.round((scaledRadius - fontHeight) / 2, 1)
             );
@@ -136,6 +138,7 @@ class MapboxViz extends React.Component {
           locations={Immutable.fromJS(clusters)}
           dotRadius={this.props.clusterRadius * 0.6}
           globalOpacity={1}
+          metricKey={this.props.metricKey}
           compositeOperation="screen"
           renderWhileDragging={true}
           lngLatAccessor={function (location) {
@@ -148,11 +151,13 @@ class MapboxViz extends React.Component {
 }
 
 function mapbox(slice) {
-  const clusterRadius = 60;
+  const clusterRadius = 60,
+        metricKey = "metric";
   var div = d3.select(slice.selector),
       clusterer = supercluster({
         radius: clusterRadius,
-        maxZoom: 16
+        maxZoom: 16,
+        metricKey: metricKey
       });
 
   var render = function () {
@@ -171,7 +176,8 @@ function mapbox(slice) {
           sliceWidth={slice.width()}
           clusterer={clusterer}
           mapStyle={json.data.mapStyle}
-          clusterRadius={clusterRadius}/>,
+          clusterRadius={clusterRadius}
+          metricKey={metricKey}/>,
         div.node()
       );
 

caravel/data/__init__.py

@@ -950,6 +950,7 @@ def load_long_lat_data():
     with gzip.open(os.path.join(DATA_FOLDER, 'san_francisco.csv.gz')) as f:
         pdf = pd.read_csv(f, encoding="utf-8")
     pdf['date'] = datetime.datetime.now().date()
+    pdf['value'] = [random.randint(-100, -1) for _ in range(len(pdf))]
     pdf.to_sql(
         'long_lat',
         db.engine,
@@ -967,6 +968,7 @@ def load_long_lat_data():
             'postcode': Float(),
             'id': String(100),
             'date': Date(),
+            'value': Float(),
         },
         index=False)
     print("Done loading table!")

caravel/viz.py

@@ -1672,34 +1672,60 @@ class MapboxViz(BaseViz):
         'label': None,
         'fields': (
             ('longitude', 'latitude'),
+            'all_columns',
             'mapbox_style',
         )
     },)
 
+    form_overrides = {
+        'all_columns': {
+            'label': 'Column for numbers on clusters',
+            'description': ("Column that defines the way the number on each cluster "
+                "is counted. Leave empty to just display the number of points"),
+        },
+    }
+
     def query_obj(self):
         d = super(MapboxViz, self).query_obj()
         fd = self.form_data
+        all_columns = fd.get('all_columns')
         d['columns'] = [fd.get('longitude'), fd.get('latitude')]
+        if len(all_columns) >= 1:
+            if (all_columns[0] != fd.get('longitude') and
+                all_columns[0] != fd.get('latitude')):
+                d['columns'].append(fd.get('all_columns')[0])
         d['groupby'] = []
         return d
 
     def get_data(self):
         df = self.get_df()
         fd = self.form_data
+        all_columns = fd.get('all_columns')
+        metric_col = [None] * len(df.index)
+        if (len(all_columns)) >= 1:
+            if all_columns[0] == fd.get('longitude'):
+                metric_col = df[fd.get('longitude')]
+            elif all_columns[0] == fd.get('latitude'):
+                metric_col = df[fd.get('latitude')]
+            else:
+                metric_col = df[fd.get('all_columns')[0]]
 
         # using geoJSON formatting
         geo_json = {
           "type": "FeatureCollection",
           "features": [
             {
               "type": "Feature",
-              "properties": {},
+              "properties": {
+                "metric": metric
+              },
               "geometry": {
                 "type": "Point",
                 "coordinates": [lon, lat]
               }
             }
-            for lon, lat in zip(df[fd.get('longitude')], df[fd.get('latitude')])
+            for lon, lat, metric
+            in zip(df[fd.get('longitude')], df[fd.get('latitude')], metric_col)
           ]
         }