#SWDchallenge: area graphs
“Area graph” results from Google image search
There is a single graph that is probably more well known than any other graph in recent history—and it is an area graph. I can simply say the words “flatten the curve” and you are likely able to picture a version of it in your head.
Just in case not, here is what it looks like:
Why is it effective? Both axes and curves are labeled directly, so there’s no question of what we’re looking at. The transparency allows us to see the overlap. A point of reference is drawn and labeled on the graph directly (Healthcare system capacity), giving us an immediate comparison point. Colors are used thoughtfully: red to signal danger and what we’d like to avoid, a kind blue to represent what we would like to happen (making evident the tension between the two). Also note here, that while there are likely numbers underlying it, none of those numbers are included here, because they would complicate things in unnecessary ways. All in all, this is a great graph that has been used for a pretty effective and critically important call to action: do what you can to help flatten the curve so we can get the number of COVID-19 cases below our healthcare system capacity and have the ability to care for those in need.
We don’t use a lot of area graphs at SWD. As a point of evidence, if we look at the hundreds of examples across our books, there is only a single one each in storytelling with data and Let’s Practice! (and in the latter case, one of the reviewers thought I shouldn’t include it; both examples are included in resources shared below). One challenge that often arises with area graphs where series are stacked on top of each other is that it’s unclear whether segments further up the stack are meant to be read from the axis up, or from the prior series up. Sure, that can often be addressed through titles and labels, but adding more to an already-dense visual is rarely the ideal solution. Perhaps the bigger issue is that most area graphs I encounter would work better as simple lines. This makes for a less ink-heavy graph, allowing you more free space to potentially annotate points of interest.
That said, there are situations where area graphs work beautifully. The “flatten the curve” graph at the onset of this post is a great illustration of this. Area graphs work well when there is something about the area itself that is important to convey. For example, in the aforementioned example, it helps us understand that the area under each curve is the same, they just take on different shapes depending on how we act, which will put us either over or under that critical healthcare capacity line.
the challenge
Find some data of interest that will lend itself well and create and share an area graph. Any type of area graph is welcome: standard area, stacked area, 100% stacked area, etc.
NOTE: While I used a graph depicting it in the context above, I’d like to kindly recommend against the visualization of COVID-19 data for this challenge. Our monthly challenges are meant to be a space to have fun and try new things, so is probably not the best venue given the serious and rapidly changing nature of this particular dataset. I’ve also seen too many examples lately where people are graphing data they don’t fully understand or seem to be forgetting that it is disease and death—things that are impacting real people in very real ways—that they are plotting, sharing, and picking apart in public online forums. Now, while I’m sure that you, reading this, wouldn’t do either of these things, let’s just please avoid it all together within the confines of our friendly monthly challenge, take a break from COVID-19, and point our graphing powers at other topics.
If you need help finding data, check out this list of publicly available data sources.
Share your creation in the SWD community by April 30th at 4PM PST. If there is any specific feedback or input that you would find helpful, include that detail in your commentary. Take some time also to check out others' submissions and share your thoughts via comments and datapoints over the course of the month. I look forward to seeing some awesome area graphs!
related resources
Here are a few examples and resources to point you to related to area graphs (not a comprehensive list). If you are aware of others, please share in your submission commentary.
Horizon graphs, with a food pricing example (Nathan Yau)
How to improve your area charts (Steve Wexler)
Making sense of streamgraphs (Andy Kirk)
Most unisex names in the US (Nathan Yau)
Peak Break-up Times According to Facebook Status Updates (David McCandless)
