In my last post I showed some of the features of JMP's Bubble Plot platform using the US crime rate data (How to Make Bubble Charts) to create a static bubble plot, and the 1973 to 1999 US crime rate data to generate a dynamic bubble plot. Describing the dynamic bubble plot i wrote
Around 1976 Nevada starts to move away from the rest of the states, with both a high burglary and murder rates, reaching a maximum around 1980, and returning to California and Florida levels by 1984. Around 1989 the murder rate in Louisiana starts to increase reaching 20 per 100,000 by 1993, staying between 15 and 20 per 100,00 all the way up to 1997, with a fairly constant burglary rate. We can also see that the crime rates for North Dakota are consistently low
You can see these stories unfold in the animation, but after it is over our brains tend to forget the path a bubble took; the sequence of steps that led to its final position. Fortunately for us, the Bubble Plot platform has an option, Trail Lines, that can help our brains visualize motion. This option can be accessed from the bubble plot contextual menu:
Let's select the bubbles for Nevada, Louisiana, and North Dakota. If you run the animation a trail follows the motion of each of these bubbles. By the end of the sequence, 1999, the plot shows the paths taken by these 3 states.
Now we can clearly see Nevada, the green trail, shooting up to the upper right (high burglary and murder rates), and then coming back. Note how Louisiana (blue line) moves horizontally to the right (higher murder rate), without changing too much in the vertical direction (burglary rate). North Dakota's path (yellow line) is a short zigzag motion, keeping itself around a burglary rate of 435 per 100,000, and a murder rate of 1.18 per 100,000.
In Visualizing Change, data visualization expert Stephen Few discusses four meaningful characteristics of change through time: magnitude, shape, velocity and direction. These four characteristics are easier to visualize by using Trail Bubbles in addition to Trail Lines. The plot below shows the Trail Lines and Trail Bubbles for Louisiana, Nevada, and North Dakota. To help the eye, I've added labels for the starting year of 1973.
The magnitude of change can be assessed by looking at the difference between bubble locations. For Nevada, between 1973 and 1980, you can see big changes in the burglary rate, from about 2000 to 3000 per 100,000, and the murder rate, from 12 to 20 per 100,000. By 1999 Nevada's burglary rate have been cut in half to 1000 per 100,000. The shape of change is given by the overall shape of the bubbles, while the direction and velocity of change can be visualized by the trend of the trails and the rate at which a bubble moves from one place to the next. For Nevada, the shape of change is somewhat concave, with rapid changes (big jumps from one bubble to the next), trending upward and downward in the 45° diagonal.
Louisiana's burglary rate did not change much (vertical changes), but its murder rate went up to 20 per 100,000, ending at 10 per 1000,000, lower than where it started (horizontal changes). The changes did not seem to occur rapidly, because the distance between the bubbles is small. As we saw before, not a lot of changes in North Dakota. Its shape is a circle with a small radius; i.e., neither big, nor rapid changes in either murder or burglary rates (the last bubble is almost where started).
A JMP bubble plot, with line and bubbles trails, can really change the way you visualize change. Go ahead, give it a try.
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