This lecture is going to be about plotting and color in R. It's kind of an adjunct lecture to the lectures that we've already had in plotting in both base graphics and the lattice graphics system. I just want to talk a little bit about how you specify different types of colors using different palates in R. You might think that the specification of color in a plot is maybe kind of a secondary decision and in some sense it is it's definitely secondary to something like the data, but of course, but the judicious and appropriate use of colors, I think in plots can help to describe the relationships that you're trying to demonstrate and can help various dimensions of the data come out more effectively than if you just choose an arbitrary set of colors. So, there are a couple of things, functions, and things that I want to cover in this lu, lecture, but the basic point that I'm, is that the default color schemes for most of the plots in R, are pretty bad. And you don't have to be an expert in design or anything to really kind of see this. But the kind, the natural color schemes that you kind of gravitate towards when you use the plotting functions are not particularly well suited for different kinds of data. But there have been a number of developments in R, via packages and also in the core R system that can help with the handling of specification of colors and, and various types of plots. And so we're going to, I'm going to talk about one of these packages and some of the functions in this lecture. So, the basic problem that typically comes out in most plots. This is a pretty standard plot in R that you might see in a presentation or a paper there's some points on the plot and I'm just plotting random points here. And you see that there are, the points are in three different colors. The first is black. The open circles are in black. Then there's a couple of points that are in red and a couple of points that are in green. So why does this happen? Because in most plotting functions there will be a col argument, col. When you say col equals one, you get black. When you say col equals two, you get red and when you say col equals three, you get green. And so, if you have a plot and you want three different colors in it. It's very easy to say, okay, well, just give me col equals one, two, three. and, and so, you get black, red, and green. Col equals four, would have been something like cyan, and then, col equals five is magenta. So, those are the kind of standard colors that you just get stuck with, when you, when you set col equal to be one, two, three, four or five. And so if you go this route the red and the green don't, are not particularly meaningful in this, in this case. Of course, you don't know what the data are about. So it's it's possible that they are, but in most cases, they're not the, the most suitable colors for the type of data that you're going to show. And, and also, just from a design point if you use this color scheme all the time, then all of your plots will look like they belong in some Christmas show or Christmas presentation. So, if the question is whether or not we can choose a better set of colors that better communicates the idea that we're trying to get across. Another standard set of colors is shown here. This is the volcano data set that comes with R. And it's basically a data set that shows different elevations of a volcano. And, there two, the color, set of colors on the left is called, is comes from the heat colors palette. And so, this is a palette of colors that, goes from kind of a reddish to, to indicate low, to a yellow or white, to indicate high. And then, on the right side here, we've got a palette of colors called the topo colors or topographical colors and this goes from a kind of blue, which indicates low to a a brown or a white which indicates high. So for the heat colors it, if you know what fire is, it may be reasonable to, to kind of see that picture and know that kind of what is low and what is high. For the topographical colors, it's not, maybe not immediately clear to some people wha, what is low and what is high, it's not so the fact that blue is low and green is higher than blue it may not be particularly obvious. It's not particularly obvious to me.
