Hey folks, I can’t tell you how much I’ve enjoyed recreating the “data portraits” from the collection of visualizations that WEB DuBois and his colleagues presented at the 1900 Paris Exposition. You can find the entire collection of “data portraits” in a book assembled by Whitney Battle-Baptiste and Britt Rusert (here) or as a collection of plates through the Library of Congress (here). Perhaps this isn’t so obvious to my non-US readers and viewers, but February is Black History month. In December or January, I had the idea to do a couple visuals for February to honor DuBois, his colleagues, and other great Black scientists of yesterday and today. When Executive Orders from the Trump Administration started going off the rails, I doubled down on the DuBois recreation videos. When all is said and done, I’ll have recreated 8 of the ~60 visuals on YouTube. I’m grateful to Battle-Baptiste and Rusert, Anthony Starks and Jason Forrest who have helped popularize efforts to recreate these visuals with modern tooling. I really hope I’ve done the visualizations justice. Please make sure you watch the great presentation by Starks and Forrest that was posted to YouTube in 2021. Frankly, I’m pretty amazed that I’ve been able to recreate these visuals using only the functions loaded with the Recreating fans, bullseyes, spirals, and other odd shapes in R has really taken a lot out of me! This week, I wanted to cover something I thought would be a little “simpler”. Check out this bar plot, which is Plate 9 from the collection. Part of DuBois and his colleagues’ goal in going to Paris was to provide context to his European audience for the situation of Black Georgians and Americans in general. This visual shows the age distribution among Black Georgians relative to the French population. The French population was older than the Black Georgian population. Beyond the story there are a few interesting things about this plot First, this is clearly a bar plot with the categories on the y-axis, the percent of the population on the x-axis, and the race/nationality used to set the color of the bars. This bar plot can be created using Second, instead of including an x-axis, the percentages are embedded in the bars. This can be done with Third, instead of having the legend on the right as we are accustomed to with ggplot2, this legend is directly below the title. We can pull this off with the Finally, the hard part of this figure is the inclusion of the “{“ to group the pairs of bars for each age group. We might be tempted to use A number of DuBois’s other visualizations also use these braces, so I think it is worth learning how to use them. Of course, there’s a package that will do this for us, but where’s the adventure in that!? If you want some data to practice with here you go…
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Hey folks! As I’m writing this newsletter the US government is in shutdown mode with no clear signs that things will get going anytime soon. I’ll withhold my own political take except to say that my family has been running without an official budget for about 25 years. I don’t recommend it, but we know basically how much money goes to our mortgage, insurance, groceries, charities, etc. and how much money we generally have left over. Somehow we still are able to spend money on living a pretty...
Hey folks! This week I have a figure for you from the New York Times based on a poll they did with Siena that describes Americans’ sentiments concerning Israel’s actions in their war with Gaza. What does it say to me? This plot is saying that more Americans think that Israel is intentionally killing civilians than they did in December 2023. The change in percentage of people in the other categories seems to decrease accordingly. What do you like? I love slope plots! I think they’re a great...
Hey folks, This week I have an interesting figure for you from the Financial Times from an e-mail newsletter they distribute each week describing some visualization related to climate change. Before reading further, go ahead and spend a few minutes with the image. What does it say to you? What do you like? What don’t you like about it? How do you think you would go about making it in R? I’d encourage you to write down any of your answers to these questions before reading what I have to say....