 Another variation of time and flow visualizations is something called the bump chart, which is actually based on interactive visualizations from the New York Times. The bomb chart is right up here, top middle. I'm going to click on that. We need a data set. I'm going to use the same music data set that I used previously. And I come down and you'll see that we have the same places to put our variables. So again, I'm going to take a media for group, drag that over here. And there's my canvas, but it hasn't filled in with the title yet. Then I'm going to get year and put it right there. By the way, you'll notice it doesn't give an error anymore, which it did in our first example of small multiples. But we have these charts that are all uniform across time, nice rainbow colors. I'm going to take market share, which is our main outcome variable, the thing we're looking for, and drag that over to size. And then here, you get kind of a crazy looking graph. It's similar to some of the other ones we had in that it shows the relative proportion of music purchases made in each medium over time, sort of like adding up to 100%. Now you've got a few choices, but most of them don't really do much of anything. So we can normalize it. But you know, nothing happens there. A curve basis is nice, because it's it's nice and smooth curves, you do linear, you get kind of a choppy looking one. And I just don't think it looks as good. So we'll leave it at basis. And so this is another option, another way of looking at the relative changes over time, just like we had with the stream graphs and the small multiples. None of these constitutes a single correct answer. One of the important principles of data visualization is use whatever method gives you insight into your data. And so that's going to depend on both the data that you have, and the way that you and your audience make sense of things. So that one is best left to your own judgment.