While logarithmic scales are a useful tool for visualizing metrics that change significantly over time, how can you translate multiple metrics that are on vastly different scales to make them easier to understand? For example, let us try to compare the following two metrics:
It’s very hard to see any kind of relationship between those metrics, because the magnitude of their values is so different. Your first thought might be to use different axes for each series (one on the left and one on the right):
But there are a lot of problems with this approach, which we’ve gone into some depth previously in our series on Data Visualization. Generally speaking, dual-axes plots are a bad idea and should be avoided.
But, even if dual-axes plots were a good idea (which they are not), what would you do if you have more than two metrics? If you are primarily interested in how the metrics are changing you can use the relative change to visualize the relationship. For example, given these three metrics:
Instead of charting the actual value of all metrics, we can chart the percentage change of each metric, relative to itself, from a point in time. This translates all metrics from real values into percentages (change since the chosen point in time) and makes it easy to see how they are changing together:
From this you can see that the changes in Metric 1 are significant, while the changes for Metric 3 and Metric 2 are smaller. This significant difference is not visible in the raw data.
Again, if the reader does not understand these are relative changes and not actual metric values there can be a lot of misunderstanding. However, with the appropriate context to avoid that confusion, you can use relative change charts to convey a variety of very interesting insights.
Tomorrow we’ll go a step farther and discuss how we can use residuals to emphasize the most interesting aspects of our data.
Quote of the Day: “There is not a fragment in all nature, for every relative fragment of one thing is a full harmonious unit in itself.” ― John Muir