Living

119 posts
Everything in Texas is big, but not this BIG

Long-time reader John forwarded the following chart via Twitter. The chart shows the recent explosive growth in deaths due to Covid-19 in Texas. John flagged this graphic as yet another example in which the data are encoded to the lengths of the squares, not their areas. Fixing this chart just requires fixing the length of one side of the square. I also flipped it to make a conventional column chart....

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On data volume, reliability, uncertainty and confidence bands

This chart from the Economist caught my eye because of the unusual use of color-coded hexagonal tiles. The basic design of the chart is easy to grasp: It relates people's "happiness" to national wealth. The thick black line shows that the average citizen of wealthier countries tends to rate their current life situation better. For readers alert to graphical details, things can get a little confusing. The horizontal "wealth" axis...

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Working with multiple dimensions, an example from Germany

An anonymous reader submitted this mirrored bar chart about violent acts by extremists in the 16 German states. At first glance, this looks like a standard design. On a second look, you might notice what the reader discovered- the chart used two different scales, one for each side. The left side (red) depicting left-wing extremism is artificially compressed relative to the right side (blue). Not sure if this reflects the...

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Presented without comment

Weekend assignment - which of these tells the story better? Or: The cop-out answer is to say both. If you must pick one, which one? *** When designing a data visualization as a living product (not static), you'd want a design that adapts as the data change.

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Designs of two variables: map, dot plot, line chart, table

The New York Times found evidence that the richest segments of New Yorkers, presumably those with second or multiple homes, have exited the Big Apple during the early months of the pandemic. The article (link) is amply assisted by a variety of data graphics. The first few charts represent different attempts to express the headline message. Their appearance in the same article allows us to assess the relative merits of...

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How the pandemic affected employment of men and women

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...

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Twitter people UpSet with that Covid symptoms diagram

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...

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This exercise plan for your lock-down work-out is inspired by Venn

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...

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The hidden bad assumption behind most dual-axis time-series charts

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....

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Make your color legend better with one simple rule

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...

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