Living
142 posts
In the last post, I looked at the overall employment situation in the U.S. Here is the trend of the "official" unemployment rate since 1990. I was talking about the missing 100 million. These are people who are neither employed nor unemployed in the eyes of the Bureau of Labor Statistics (BLS). They are simply unrepresented in the numbers shown in the chart above. This group is visualized in my...
Been busy with an exciting project, which I might talk about one day. But I promised some people I'll follow up on Covid symptoms data visualization, so here it is. After I posted about the Venn diagram used to depict self-reported Covid-19 symptoms by users of the Covid Symptom Tracker app (reported by Nature), Xan and a few others alerted me to Twitter discussion about alternative visualizations that people have...
A twitter follower did not appeciate this chart from Nature showing the collection of flu-like symptoms that people reported they have to an UK tracking app. It's a super-complicated Venn diagram. I have written about this type of chart before (see here); it appears to be somewhat popular in the medicine/biology field. A Venn diagram is not a data visualization because it doesn't plot the data. Notice that the different...
DC sent me the following chart over Twitter. It supposedly showcases one sector that has bucked the economic collapse, and has conversely been boosted by the stay-at-home orders around the world. At first glance, I was drawn to the yellow line and the axis title on the right side. I understood the line to depict the growth rate in traffic "vs a normal day". The trend is clear as day....
The pie chart about COVID-19 worries illustrates why we should follow a basic rule of constructing color legends: order the categories in the way you expect readers to encounter them. Here is the chart that I discussed the other day, with the data removed since they are not of concern in this post. (link) First look at the pie chart. Like me, you probably looked at the orange or the...
The pressure of the coronavirus news cycle has gotten the better of some graphics designers. Via Twitter, Mark B sent me the following chart: I applied the self-sufficiency test to this pie chart. That's why you can't see the data which were also printed on the chart. The idea of self-sufficiency is to test how much work the visual elements of the graphic are doing to convey its message. Look...
Another day, another Twitter user sent a sloppy chart featured on TV news. This CNN graphic comes from Hugo K. by way of Kevin T. And it's another opportunity to apply the self-sufficiency test. Like before, I removed the data printed on the graphic. In reading this chart, we like to know the number of U.S. reported cases of coronavirus relative to China, and Italy relative to the U.S. So,...
As we move into the next phase of the dataviz bonanza arising from the coronavirus pandemic, we will see a shift from simple descriptive graphics of infections and deaths to bivariate explanatory graphics claiming (usually spurious) correlations. The FT is leading the way with this effort, and I hope all those who follow will make a note of several wise decisions they made. They source their data. Most of the...
My friend Ray Vella at The Conference Board has a few charts up on their coronavirus website. TCB is a trusted advisor and consultant to large businesses and thus is a good place to learn how the business community is thinking about this crisis. I particularly like the following chart: This puts the turmoil in the stock market in perspective. We are roughly tracking the decline of the Great Recession...
Reader Lucia G. sent me this chart, from Ars Technica's FAQ about the coronavirus: She notices something wrong with the axis. The designer took the advice not to make a dual axis, but didn't realize that the two metrics are not measured on the same scale even though both are expressed as percentages. The blue bars, labeled "cases", is a distribution of cases by age group. The sum of the...