This month’s challenge was to re-brand a storytelling with data style graph in the style of your choosing. Fifty-eight readers submitted their re-designs with everything from McDonald’s to Vogue to Harry Potter and much, much more! Click to see the entire post and how effective brand can be when it’s thoughtfully incorporated into data storytelling.Read More
Wow, tons of variation in the ways people chose to display variability! Check out 41 visualizations of variability in data—featuring box plots, histograms, violins, reference bands and more—with topics ranging from weather to sports to love. Click to see the recap post that includes all the submissions.Read More
Over the past few days, I've been undertaking the (painstaking) process of updating and redirecting every single link for every single blog post (part of the growing pain of revamping my site, which is mostly complete now). One of the benefits of this is that it forced me to look back at my blog posts over the years. I was reminded of something I haven't done in a while: a data visualization challenge.
One of the first posts in my Feedly summary today seems like the perfect inspiration for resurrecting the data viz challenge. The post, by the Economist, is titled "Global population forecasts." It's featured within their Graphic Detail section (there may be a full article that goes with it, but the short version should work for our purposes here). I was looking through the visuals and thinking abut how they could be revamped to more quickly and clearly tell the story. But then I paused and thought, why not let you do that?
My challenge to you is this: take the following set of visuals and improve them. Use whatever tools and methods you want. Think about not only how to best show the data, but also how to tell a story with it. Email your remake and any relevant thoughts you want to share to me at email@example.com by midnight PST Wednesday, August 12th. I'll feature the submissions in a future blog post. I'll also pick my fave and invite the creator to write a guest post.
Big thanks to Max, who made a sharable dataset with the numbers you need from the original (massive) file which you can view (and save for your own use) here.