Axis

51 posts
The time has arrived for cumulative charts

Long-time reader Scott S. asked me about this Washington Post chart that shows the disappearance of pediatric flu deaths in the U.S. this season: The dataset behind this chart is highly favorable to the designer, because the signal in the data is so strong. This is a good chart. The key point is shown clearly right at the top, with an informative title. Gridlines are very restrained. I'd draw attention...

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Vaccine researchers discard the start-at-zero rule

I struggled to decide on which blog to put this post. The reality is it bridges the graphical and analytical sides of me. But I ultimately placed it on the dataviz blog because that's where today's story starts. Data visualization has few set-in-stone rules. If pressed for one, I'd likely cite the "start-at-zero" rule, which has featured regularly on Junk Charts (here, here, and here, for example). This rule only...

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A note to science journal editors: require better visuals

In reviewing a new small-scale study of the Moderna vaccine, I found this chart: This style of charts is quite common in scientific papers. And they are horrible. It irks me to think that some authors are forced to adopt such styles. The study's main goal is to compare two half doses to two full doses of the Moderna vaccine. (To understand the science, read the post on my book...

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These are the top posts of 2020

It's always very interesting as a writer to look back at a year's of posts and find out which ones were most popular with my readers. Here are the top posts on Junk Charts from 2020: How to read this chart about coronavirus risk This post about a New York Times scatter plot dates from February, a time when many Americans were debating whether Covid-19 was just the flu. Proportions...

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Atypical time order and bubble labeling

This chart appeared in a Charles Schwab magazine in Summer, 2019. This bubble chart does not print any data labels. The bubbles take our attention but the designer realizes that the actual values of the volatility are not intuitive numbers. The same is true of any standard deviation numbers. If you're told SD of a data series is 3, it doesn't tell you much by itself. I first transformed this...

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Is this an example of good or bad dataviz?

This chart is giving me feelings: I first saw it on TV and then a reader submitted it. Let's apply a Trifecta Checkup to the chart. Starting at the Q corner, I can say the question it's addressing is clear and relevant. It's the relationship between Trump and McConnell's re-election. The designer's intended message comes through strongly - the chart offers evidence that McConnell owes his re-election to Trump. Visually,...

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Aligning the visual and the data

The Washington Post reported a surge in donations to the Democrats after the death of Justice Ruth Ginsberg (link). A secondary effect, perhaps unexpected, was that donors decided to spread the money around; the proportion of donors who gave to six or more candidates jumped to 65%, where normally it is at 5%. The text tells us what to look for, and the axis labels are commendably restrained. The color...

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Locating the political center

I mentioned the September special edition of Bloomberg Businessweek on the election in this prior post. Today, I'm featuring another data visualization from the magazine. *** Here are the rightmost two charts. Time runs from top to bottom, spanning four decades. Each chart covers a political issue. These two charts concern abortion and marijuana. The marijuana question (far right) has only two answers, legalize or don't legalize. The underlying data...

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Deaths as percent neither of cases nor of population. Deaths as percent of normal.

Yesterday, I posted a note about excess deaths on the book blog (link). The post was inspired by a nice data visualization by the New York Times (link). This is a great example of data journalism. Excess deaths is a superior metric for measuring the effect of Covid-19 on public health. It's better than deaths as percent of cases. Also better than percent of the population.What excess deaths measure is...

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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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