Skip to 0 minutes and 1 second The first maps we know of, that have survived, were about 5,000 years old. You know, on clay tablets. But it was only a few hundred years ago that there was sufficient data and statistical understanding to go beyond just simple maps and actually create data maps. Maps that contained information about differences between different places. So that was in the 1600’s, where that came together. You know, in the 17th century and 18th century, with the rise of printing and the rise of some more modern mathematics and basic statistics, there was an expansion of graphics. Most of it, almost all of it, were either maps or simple time series. So those were the most widespread graphics.
Skip to 0 minutes and 46 seconds And they remain, probably, the most widespread graphics in newspapers today. Just basic maps, maybe basic data maps, and time series plots. This is where Tufte gets into sort of research design issues. But he says, “There’s something fundamentally unsatisfying about most time series plots, in that the passage of time alone doesn’t tell us what’s happening.” So yes, things changed over time, but we don’t really know why without additional information. Now, sometimes a time series is useful if there are important events that took place at a certain point. The French revolution happened, and there was a big change that year. Well, you know, that’s plausibly related to the French revolution.
Skip to 1 minute and 26 seconds So, it could be that a time series can get us closer to causal explanation if we enhance the time series with other pieces of data. So, that could be useful. But, in general, the real progress in data visualization happened when there this kind of combination of distinct variables and the relationship between them that was independent of a simple time series. And that’s really what happened a bit later, mainly in the mid-late 1700’s. I mean, he has a lot of figures by these sort of pioneers in data visualization and graphics; Lombaire, Swiss Mathematician and then William Playfair. Great name. Playfair, actually, there’s a ton of stuff by Playfair in the book. So what does Playfair do?
Skip to 2 minutes and 14 seconds He basically made time series plots “mainstream.” He really started using them widely and made them mainstream for the presentation of economic data. In a way, they were kind of used in a scattered way before then. He made them widespread. Apparently, according to Tufte, he invented the bar chat, invented the pie chart and was the first person to use area to depict quantity. So he would, you know, present various types of economic data, political data and basically size observations by quantity. Like trade quantity, or something like that, trade volumes. So he was really an innovator. And this 1786 book was very important. So, within a very short amount of time, a lot of these tools became widespread.
Skip to 3 minutes and 4 seconds And these are still what Excel use. Like if you go to Excel, graph plotting types, it’s still kind of like Playfair’s “playlist.” You know? It’s still kind of the same stuff. So, what are some of the things that he did? These are some of the early time series. This is trade data, you can see the imports into England and then the exports out of England. So, you can basically see the trade balance here over time. Once thing that Playfair always did is, he really integrated words, into his graphics all the time. And a lot of the early figures do this. And then for a long time, figures and scientific research stopped doing it, but their sort of words are back.
Skip to 3 minutes and 46 seconds I think that’s the kind of feeling of a lot of recent work. So this is the trade balance over time. This is one of the first bar charts, where the dark line, he says, at the bottom denotes the black lines are exports, and the ribbed lines are imports. So again, he’s sort of distinguishing between exports and imports here into different countries. So, he’s presenting data in various ways.
Skip to 4 minutes and 17 seconds So, what Minard is doing here is, he has a graphic on the fate of Napoleon’s army when he tried to invade Russia. So for people who aren’t familiar or forgot this episode or blocked it out, Napoleon conquered most of Europe. Decided to keep going east, he should have stayed Poland, he never should have gone to Russia. It was a huge mistake for him. He decided he was going to go conquer Russia. He left with this massive army. And between the Russians sort of burning every town before he could get there and destroying food supplies in a brutally cold winter, his whole army was annihilated. Shortly after that, you know, he was removed from power.
Skip to 4 minutes and 55 seconds So, this is a pretty interesting figure. It’s a combination of a time series and a data map, to begin with. There’s very effective use of color. Let me explain the figure. This is a map. So, this is Poland and he was going east into Ukraine, or something, and then into Russia. This is Moscow. Up here, the orange line is the army he started with, going to Moscow. The thickness of the orange line is how many soldiers he had. You can see every place he goes he losing soldiers to disease, to battles, etc.
Skip to 5 minutes and 32 seconds So by the time he gets to Moscow, which the Russians had burnt to the ground – so there was nothing to eat, there was nothing to do – he had already lost, you can see visually, the majority of his army. Then he had to return. That’s the black line. And what’s in this bottom aspect of the figure, and this is actually very nice, because the bottom aspect panel of the figure links up to the black line in terms of dates. So at this date, this has the temperature. At this date over here this is the temperature. And what ends up happening is, it was a brutally cold winter with minus however many degrees.
Skip to 6 minutes and 7 seconds So basically as his army retreated, it was getting colder and colder and colder. So he basically gets back to a starting point with like him, his horse and his cook or something. So this is a time series in different directions. It’s a map. You can see the link to temperature, which has causal explanatory power. It’s kind of an amazing figure. And when you think about it, this must have taken a long time to conceive of. There are a lot of different pieces of data. It’s driven by a real substantive understanding of the historical episode. It’s driven by the sophisticated use of data and it’s beautiful. The colors are beautiful.
Skip to 6 minutes and 46 seconds The other thing to notice, the different panels are kind of lined up. We’ll come back to this later on. In a way that makes them both more effective. Like, if these were side to side, it would be much less powerful to see that as they kept going the temperature just kept falling. So I don’t know if Tufte is right that it is the greatest figure ever made. Or something like that. It’s like the Mohammed Ali of, you know, figures, or something. It’s a pretty nice figure.
A brief history of maps, time-series, and charts
Though the practice of mapmaking is thousands of years old, modern enhanced data visualization, particularly through the use of time-series and data maps, really began in the 18th century with Johann H. Lambert, a Swiss mathematician, and William Playfair, a Scottish engineer and political economist, both of whom are featured in Tufte’s book as pioneers in visualization. In this video, we also learn about what Tufte considered one of the greatest graphics of all time – Charles Joseph Minard’s visualization of how the size of Napoleon’s army changed as it marched east towards Moscow and then returned during a brutally cold winter.
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