Everything happens somewhere. That’s why the location of an object can be just as important as its nonspatial attributes for the purposes of data analysis. In fact, spatial and nonspatial data often go hand in hand.
As an example, consider a ride-sharing app. Once you’ve ordered a ride, you might want to track the location of the car on a map in real time while it’s heading to you. You might also want know some basic nonspatial information about the car and driver assigned to your order: the make and model of the car, the driver’s rating, and so on.
In the last chapter, you saw how to work with location data to ...
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