This tutorial covers stack plots. First, we'll define what stack plots are, and then we'll look at several examples.
Stack plots are a composite chart. And so that means that we're putting more than one data set together, and typically two or more. So with a stack plot, it's going to help us to draw comparisons and make that easier to do for us.
So in this first example, we have a stacked bar chart. And there's many kinds of stack plots that you can do. So this one, we're taking a bar chart and instead of just having one set of bars, we've added other layers to it. So the coloring here is helping us to show the difference between what kind of data we're including.
So at the top here in the green, we have waste. The purple is showing industrial processes. The gray is agriculture, the orange industrial transport, and the blue is the energy. And the way of telling that is from this chart over here. So this chart is what lets me know what each of the colors stands for.
Now, what the rest of the chart is looking at, I still need to use my typical kind of stack plot-- my bar chart skills. And on the y-axis, we have emissions. And across the x-axis, we have years. So each chip bar is representing a different year. So we have 1990, ' 95, 2000, 2005.
Now from looking at this, we can see right away that between 1990 and 2005, there's been an increase in emissions. And then what the stack chart is going to let us do is kind of see where that increase is coming from. And if we look across, we can see that the purple stays pretty stable at first, and then increases a bit. The orange, so the International transport, increases a bit at the very end. But the bigger increases seem to be coming from this blue, from energy. The green, also, the waste, staying pretty consistent across.
So by stacking the different bar charts together, we can see where the overall increase in emissions is coming from. It's coming a little bit from industrial processes, perhaps a little bit from agriculture, and a little bit from international transport, but mostly from energy. That's kind of one disadvantage to a stacked bar chart is you can't tell exactly how much this increases, because it's pretty hard to read with the scale over here being so spread out and our differences here being so small.
We'll take another look at a different type of stack plot. Here we have a stacked line plot. And again, it's a stack plot made using line charts. So this is going to help us to compare different data sets. And then this one, the title is letting us know, is oil consumption, thousands of barrels per day. And we have time again on the x-axis and the thousands of barrels per day on the y-axis.
And then the different lines here have been shaded in in between. So here, we have US down on the bottom. And then you can imagine that there was a line up here for Canada and Mexico, but then we shaded in this region in between in order to make it clear exactly what Canada and Mexico had.
So again, you can see that in 1980, the overall trend there was a lot of oil consumption. It went down a little bit and then has increased pretty steadily over time, up to the maximum here.
And then again, you can see where this change is largely driving from. And most of these smaller bars are pretty consistent in size, and that the US seems to be counting for a big increase, as well as Asia and Oceania is the one that kind of spreads out the most. It's pretty narrow down here, back in the early 80s, and then the area spreads out up here. So this was a stacked line plot.
Again on the stacked plots, you have many different kinds, using to compare different types, different data sets in one chart. This one's a line plot, but we also saw a bar chart example. This has been your tutorial on stack plots.