Thematic Polygon renderings, also known as Choropleth maps, use binning methods to determine how to color the polygons. Each shape is placed into a certain color “bin” that represents a range of values with a goal of allowing you to see similarities and differences of some attribute of your data as it relates to location. SpatialKey provides several binning methods (or algorithms) to automatically place your data into one of five bins. Alternatively, you can manually set set the ranges of each bin to values that you specify or change the number of bins altogether. Whichever method you chose, you can also select a predefined color scheme for the bins or select an individual color for each bin.
When using an automatic binning method, binning is done based on the values associated with only the polygons that are in the current visible extent of the map. This means as you pan or zoom the map, the color an any specific polygon may change as the overall set of visible polygons has changed. For example, if you were looking at a dataset of average real estate sale prices by county, the value for a specific county might be relatively low when looking at the data nationwide (and placed in a “low” bin), but relatively high when looking at just a portion of a state (and placed in a “high” bin). This dynamic binning based on the visible extent of the map is generally a huge advantage over traditional static tile maps because this allows you to make better visual comparisons of the locations you are viewing. However, you can always “lock” the bin ranges to prevent this behavior by switching to manual binning mode.
Automatic Binning Methods
SpatialKey employs three binning methods to create bins. Depending on your specific data, one might be more appropriate than another. By default SpatialKey uses the Natural Breaks binning method. The other binning methods that SpatialKey offers are the Quantile and Equal Intervals methods.
Natural Breaks uses an algorithm (referred to as the Jenks Optimization) to automatically determine logical breaks in your data. The Quantile method divides the polygons so that an equal number of polygons fall into each of the 5 bins. And the Equal Interval method divides the range into equal ranges that go from the minimum to the maximum
Here is a comparison of the same data, showing the average home price in Sacramento by zip code. Each map uses a different binning method, but the underlying data is exactly the same. You can see that different binning methods will produce maps that look different. The legend shows the distribution of polygons based on their value, and you can see how many polygons fall into each distinct color break.
You can use manual binning to lock the ranges that have been set using an automatic binning method so that they don’t get re-computed based on changes the range of values visible on the map. Ranges for the bins can also be overwritten manually. With manual binning selected, the ranges for these bins won’t change as you pan and zoom the map, or change data in your filters.