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  3. Visualizing Geospatial Data in R

Exercise

Choropleth map

Now that you understand drawing polygons, let's get your polygons on a map. Remember, you replace your ggplot() call with a ggmap() call and the original ggplot() call moves to the base_layer() argument, then you add your polygon layer as usual:

ggmap(corvallis_map_bw,
      base_layer = ggplot(ward_sales,
                          aes(lon, lat))) +
  geom_polygon(aes(group = group, fill = ward))

Try it out in the console now!

Uh oh, things don't look right. Wards 1, 3 and 8 look jaggardy and wrong. What's happened? Part of the ward boundaries are beyond the map boundary. Due to the default settings in ggmap(), any data off the map is dropped before plotting, so some polygon boundaries are dropped and when the remaining points are joined up you get the wrong shapes.

Don't worry, there is a solution: ggmap() provides some arguments to control this behaviour. Arguments extent = "normal" along with maprange = FALSE force the plot to use the data range rather than the map range to define the plotting boundaries.

Instructions 1/3

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  • 1
    • Update the ggmap() call to fix the polygon cropping.
      • Set extent to "normal" and maprange to FALSE.
  • 2
    • Update the plot, swapping the polygon fill color from ward to num_sales.
  • 3
    • Update the plot again, mapping fill to avg_price. Also, set alpha to 0.8 in your call to geom_polygon() to allow the map to show through.