Next one is angle and slope. Angle and slope. So here, we have again, one of the super common graphs that we have seen before is the line chart. In a line chart you have dots that are connected by lines and the slope of these lines is meaningful. Is very meaningful, actually, if the x-axis represents time, the slope represents the rate of change. Another very common chart that you can see around that uses angle is the pie chart. In a pie chart, the segments of the pie chart represent the proportion and the angle is typically mapped to the proportion to these associated to the value of the segment. So, this is an example of using angle. Next one is color. So, color is a bit more complicated. So, color is actually made of a number of different channels. So, it's important for you to know that color is not one single channel. When we think about how to encode information using color, how to encode attributes using color, it's important to note that color is numerous as a certain number of channels. Here we're going to talk about exclusively two channels, but actually, color can be described by three channels. I'm not going in details why and how this happens, but for the purpose of introducing the channels here, the color channel, I'm going to talk about two main color channels. The first one is color HUE. So, what is HUE? HUE is basically the name of the color. So if I say red, green, yellow, blue, these are the color names. That's what we mean when we say color HUE. Color HUE is very good to encode categorical information. Then we have color intensity. So, the color intensity can be described in many ways. One way to talk about intensity is about the brightness of the color. So, the color intensity or brightness of the color is a property of color that you can use to encode quantitative information. Let me try to give you an example here. It's possible by drawing a few squares of the same color, HUE but with different intensities. So, this is one square then I need another square with a slightly different intensity, and another one that is even brighter. Then another one that is even brighter than that, and another one that is even better than that one. So, let's see if I can line them a little. So that's an example, you see that all these squares have exactly the same HUE, the same color name. It's like blue, bluish, but they have different intensity, they go from darker to brighter. This type of channel can be used to encode quantitative information. So, in what charts or graphs is color used? Virtually everywhere you see color applied to points, to lines, to areas, to bars, it's almost everywhere. This doesn't mean that you always have to use color, but color is a very powerful visual channel. You also have to be very careful because it's very often misused. The last channel that I want to introduce is texture. So, texture and shape. Let me give you examples of texture and shape. I'm going to start with shape. For this, I'm using again scatter plots. As you may have learned from now, I am a big fan of scatter plots. In a scatter plot, you can have actually different shapes for the points. Imagine something like this. So, I can use triangles to identify one type of point and the circles to represent another type of point. So, that would be an example of using the shaped channel to encode categorical information. In this case actually binary information. There are only two categories. Let me give you an example of texture once again using bars. If I have three bars here, I can actually use different texture to identify them. We can also use texture with bubbles again. So, let's say that we have again our scatter plot with a certain number of bubbles, and here I can have some that have the vertical texture, and some have the audits on top. Texture and again, it can be used to identify categorical information. Again here, we have all the vertical ones representing one category and all the horizontal ones representing another category.