The next set of graphical components I'm going to describe is channels. Okay, we have a number of channels here. These are the most common channels, it doesn't mean that you cannot identify other types of channels but this cover very, very large proportion of the cases you're going to find around. So, we have position, size which is made of length, width and area, angle and slope, color which is made of intensity and hue going to explain in a moment what this means, and shape and texture. Okay. Let me try to draw some of these channels so that hopefully, it's going to be much more clear what kind of elements and visual structures they identify. Let's start with position. Okay, position. So, this is an incredibly common component, incredibly common channel. Literally, every single visualization out there uses position. Okay, let me show you a few examples of using position. So, for instance in a scatter plot as we have seen many times by now, the dots are positioned on the screen in a way that position is meaningful. It's encoding important information, right? So, let's take for instance this dot here, the x position and the y position are actually identifying the value of two attributes. Another common one that we have seen multiple times by now is the bar chart. The bar chart is interesting because every bar is horizontally located in a position that typically identifies a category A, B and C. But position is also used in a network diagram. So, let me show you how this looks like. So, in a network diagram, you have several nodes, right? And the position of the nodes and the position of the edges, the links, the lines that connect the nodes is also meaningful, okay? So, position is one of the most important visual channels if not the most important visual channels. Basically identifies the position of the graphical marks. Now, let's move on to the next one. The next one is size. Okay, size. Size is also very common. One important thing to do here is to distinguish between one-dimensional size and two-dimensional size. Let me give you a few examples. Once again in a bar chart when we use bars, the size of the bar is actually encoding quantitative information. The information associated to the categories that you have associated to the bars, okay? So, more in detail, more precisely, the kind of size that is used in a bar chart is length. Okay, but you can imagine other situations where size that is one-dimensional is used to encode information. Another one is when we have lines of different width or thickness. Okay, so, in this case, we have width which is encoding information about something. So, what is a chart when, what is a graph that uses sometimes this kind of encoding strategy? Once again, in network diagrams, you can see sometimes networks where the connections between the nodes have different widths. Some lines are thicker than others. For instance, in a visualization that shows, I don't know, volume of something flowing from one region of the world to another region same either low like in goods or in our flight data set, how many flights go from one city to another, okay? Those that are thicker have more connection between the two cities. Okay. But we can also have two dimensional size. So, a typical example that we have seen before is when we have bubbles in a bubble chart. Okay? The bubbles can have different sizes and the size encodes some quantitative information coming from the data. Note that the same can be done with different shapes. For instance, if we use a square, right? Square of different sizes. Okay, so this is regarding size, we have 1D, 2D. Within 1D we have length and width and in 2D, we have different types of area size.
