scale

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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Comparing U.S. coronavirus case rates to other hot spots

The numbers are high here in the United States, and at this point, they look bad on their own. But compare it to other countries that are currently hit hard, the U.S. looks even worse. For The New York Times, Lauren Leatherby makes the comparisons. Tags: coronavirus, Lauren Letherby, New York Times, scale, scrollytelling

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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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A million dollars vs. a billion visualized with a road trip

A million dollars. A billion dollars. The latter is 1,000 times more than the former. Just add a few zeros, right? Tom Scott used a road trip to visualize the actual difference in scale. Scott starts by setting the baseline of a million dollars with a short, one-minute walk. Stack one million dollar bills after the other and it’s about the length of a football field. Stack one billion, and...

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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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Cornell must remove the logs before it reopens the campus in the fall

Against all logic, Cornell announced last week it would re-open in the fall because a mathematical model under development by several faculty members and grad students predicts that a "full re-opening" would lead to 80 percent fewer infections than a scenario of full virtual instruction. That's what was reported by the media. The model is complicated, with loads of assumptions, and the report is over 50 pages long. I will...

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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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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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Reviewing the charts in the Oxford Covid-19 study

On my sister (book) blog, I published a mega-post that examines the Oxford study that was cited two weeks ago as a counterpoint to the "doomsday" Imperial College model. These studies bring attention to the art of statistical modeling, and those six posts together are designed to give you a primer, and you don't need math to get a feel. One aspect that didn't make it to the mega-post is...

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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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