Scatterplots allow us to analyze data based on multiple variables and determine the presence and nature of relationships among them. For example, you can compare product sales in terms of quantity, cost, and total revenue.
In Figure 20-1, we can observe the distribution of the product portfolio. Among the quantity of units sold, bottle holders lead the way, represented by the far-right point. However, in terms of sales volume, they fall in the middle. The highest dollar sales volume is attributed to helmets, which is the topmost point. The size of the bubble represents the price (the larger the bubble, the higher the price). Mountain bikes have larger bubbles compared to their neighboring road bikes, demonstrating the relationship between revenue and price.
Figure 20-1. Product portfolio on the scatterplot
Pay attention to the fact that on this chart we’ve included labels for both axes, even in a vertical orientation! We’ve done this because we have two sets of values to compare. Furthermore, you’ll see some handy scale sliders next to these labels. They’re quite useful when it’s hard to distinguish smaller categories when they’re displayed alongside much larger ones. In Figure 20-2, we’ve zoomed in on the range of values for quantity, focusing on a range from 0 to 700 units, and for revenue, from 0 to 140K. With this zoomed-in view, we can better compare ...
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