Join Bill Shander for an in-depth discussion in this video Change over time, part of Data Visualization: Storytelling.
- [Voiceover] It's often said that there are only seven plots in literature. People have written books about. And, there are alternative approaches to the same idea. As we discussed at the beginning of this course, stories serve the purpose of allowing us to understand and experience the world around us, and through that experience we learn how to survive and thrive. Since the human experience is entirely about putting one foot in front of the other in a linear way, and experiencing all that we experience through that lens of time, it makes sense that stories are linear, and time-dependent, and time-driven.
So, one of the most common data stories is about data changing over time. Right? First this happened, and then this, and then that, etc. So, when you're looking a your data, it often makes sense to find these time-driven story lines, in telling these linear time-driven stories to your audience. As they say, it ain't a visualization discussion until someone breaks out the Minard. For those of you who don't know this one, this is an info-graphic by a guy named Charles Minard. It was created in the 1800s, and it's telling the story of Napoleon's march on Moscow.
And, Edward Tufte, the grandfather of modern data visualization and information visualization, used this, and sort of held this up. It is one of the great examples of info-graphics of all time. Essentially, the basic idea here is you're looking at Napoleon's march on Moscow. It starts on the left-hand side. The thickness of the brown line shows you the size of the army, 400 and something thousand men. And, as he marches Eastward, you can see the army shrinking and shrinking. They're fighting the Russians all along the way here, and losing and losing a lot of men.
And essentially, they finally get to Moscow, their army's a quarter of the size as it was, they're there for a good long time, by the way, and finally they decide to turn around and go home, and they're losing more men, and more men, and more men. There's a lot of data here, more than you would think. And essentially, there's geographic information, where they were, starting in Lafayette, ending in Moscow, and then returning. There's the size of the army in the thickness of the line, and we also have temperature information down below. And so, you see really interesting stories, such as, when they crossed that river . About a third of the way from the left hand edge, you can see the black line sort of cuts in half, yet again 'cause it was so cold and they were crossing that river, you know, on foot.
Right? This is the early 1800s. So essentially, you have a lot of information here, and what's interesting is that this is a story of change over time, even though time is never mentioned. Right? We don't see the dates, we don't see the months listed out here. Essentially, this is a story of change over time without a lot of discussion of change over time. You can imagine the grueling months of combat, and how difficult of a time this was for people. It's a central component to the story. Stories really in the end, are almost always about change over time, even when it's implied rather than explicit.
So, data stories themselves are also often about that. This is a go to mechanism for data story telling. Of course, you don't always have data about things changing over time, which would clearly push you to one of the other story mechanisms.
Join data visualization expert Bill Shander as he guides you through the process of turning "facts and figures" into "story" to engage and fulfill our human expectation for information. This course is intended for anyone who works with data and has to communicate it to others, whether a researcher, a data analyst, a consultant, a marketer, or a journalist. Bill shows you how to think about, and craft, stories from data by examining many compelling stories in detail.
- Creating a narrative structure for data
- Applying narrative to data
- Identifying what you want to say with the data
- Analyzing what your data is saying
- Determining what your audience needs to hear
- Leveraging tables, charts, and visuals
- Ensuring your narrative provides context and direction