At the beginning of this lesson, I described the fact that time data as a very interesting type of structure because you can consider time as linear, but you can also consider time as cyclic. Now, I want to dig a little deeper into how to visualize a cyclic data. A different ways of saying that is how do you visualize periodic phenomena. This is very important because it's very common in data analysis and presentation and visualization to focus on temporal phenomena that actually have some cyclical patterns. So, what does it mean to be cyclic? Well, it means that you can analyze the temporal structure of an event by focusing on certain cyclic patterns. For an instance, yearly patterns, or seasonal patterns, or weekly patterns, or daily patterns, and so on. So, that's very, very common and very, very useful. So, how do you visualize cyclical or periodic patterns? Well, I have already shown you an example in one of the previous videos. With line charts, it's pretty straightforward to do that. So, you can use lines to represent something that changes over time, in this case, over the days of a week. But then, you can also show how this changes according to different years. Now, line charts are perfectly good solution, but there are situations where you may want to use a different visual representation. One that I personally like very much because it's very compact, very useful, and very intuitive is calendar-like visualizations. The basic idea here is to use a structure for your visualization in the positioning of the elements that resembles what we normally do with calendars. What do we do with calendars? Well, we have rows and columns. Sometimes, we may also repeat these sets of rows and columns multiple times in a small multiples fashion, similarly to what we have seen before with other types of visualizations. So, here is a practical example of a calendar-like visualization. In this case, we have every single rectangle. Big rectangle represents one year, and rows of these rectangles represent days of the week, and columns represent different months. So, this is data coming from bicycle usage in Chicago. I think it's called DV. What you see here is that the volume of bicycle usage across different times. Again, you can see cyclical patterns over different months and different years. As you can see, as expected over summer, people use bikes much, much more often. A very similar visual representation is this one where we are visualizing vehicle collisions in New York City. But in this case, we have a different arrangement. In columns, we have time of the day. In rows, we have different months and different years. As you can see, this cyclic pattern is consistent across many years. So, I think it's very useful for you to remember that that's another tool that you can use and have in your toolbox. Using line charts for periodic data is totally fine, but sometimes, if you want to compress a lot of data in a small visualization, then calendar-likes visualizations are a really good option. As I said, another good aspect of calendar-like visualization is that they tend to be very intuitive the same way line charts are.
