title: Heatmap with value instead of count on ggmap (contour & geom_hex)
body: <p>For the visualization of my predictive models on electric vehicle charging demand I would like to create heatmaps showing the hotspots of charging demand across multiple cities. I would like to use two different types of heatmaps - contour heatmaps and density heatmaps spread over the map in hexagons (I split my data into hexagonal cells for prediction). </p>
  
  <p>Unfortunately I only managed to create heatmaps with counts but not the actual (charging demand) values. I tried spitting/cutting the data, made sure that only observations > 0 were used and tried to limit the x/y axis - nothing has worked so far. I hope someone here has a nifty idea on how to do this. Below a piece of sample data and both heatmap codes that now produce count-heatmaps instead of value-heatmaps (lon/lat are the centroids of my hexagonal cells into which the data is aggregated):</p>
  
  <pre><code>+---+------------+-------------+----------------+
  |   |     lon    |      lat    |charging_demand |
  +---+------------+-------------+----------------+
  | 1 | 12.65783   | 55.58421    |     653.7      |
  | 2 | 12.67671   | 55.59255    |     24.1       |
  | 3 | 12.66813   | 55.59422    |     376.2      |
  +---+------------+-------------+----------------+
  </code></pre>
  
  <p>For quick replication:</p>
  
  <pre><code> df.data &lt;- data.frame(lon = c(12.64753, 12.64924, 12.55998, 12.51878, 12.52221, 12.58401, 12.55655, 12.57371, 12.59088, 12.58058),
                        lat = c(55.63091, 55.62924, 55.67594, 55.78267, 55.78601, 55.68261, 55.66593, 55.67927, 55.67927, 55.70596),
                        charging_demand = c(663.7, 627.4, 597.4, 14.5, 396.3, 300.0, 0.00, 256.9, 228.5, 0.2))
  </code></pre>
  
  <p>Hexagonal heatmap (count) example:</p>
  
  <pre><code> map &lt;- get_map(location = "Copenhagen", zoom = 12)
  
   ggmap(map) + 
    coord_cartesian() + 
    geom_hex(data = df.data, aes(x = lon, y = lat, colour = charging_demand), 
             alpha = 0.6, color = "black", show.legend = TRUE, stat = "binhex") +
    guides(fill = FALSE, alpha = FALSE) +
    scale_fill_gradientn (colours = c("green","red"))
  </code></pre>
  
  <p>Contour heatmap (count) example:</p>
  
  <pre><code> ggmap(map, extent = "device") + 
    geom_density2d(data = df.data, aes(x = lon, y = lat), size = 0.3) + 
    stat_density2d(data = df.data, aes(x = lon, y = lat, fill = ..level.., alpha = ..level..), 
                   size = 0.01, bins = 10, geom = "polygon") + 
    scale_fill_gradient(low = "green", high = "red") + 
    scale_alpha(range = c(0, 0.3), guide = FALSE)
  </code></pre>
  
  <p>Cutting the data even into 1000 pieces didn't help either:</p>
  
  <pre><code> df.data$demand_cut &lt;- cut(df.data$charging_demand, breaks = 1000)
  </code></pre>