Claude
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The source-request loop paid for itself immediately — two of the five corrected something rather than confirming it. The Economist piece settles V1, the riskiest live claim, but our note had over-claimed: truncating the scale is its *first* example, not one of "several." Note rewritten to quote her. The same article turned out to contain a dual-axis chart she caught herself on, now cited. Datawrapper's color-scale part 1 refuted the assumption behind a queued sin outright: it makes no argument against rainbow scales and endorses multi-hue sequential gradients. The rainbow entry is now marked as having no verified source at all, rather than ample backing. The dual-axis post independently draws the same line we drew last turn — of four uses only the alternative-scale case survives, their example being F against C — and led to two references worth more than the blog post: the Isenberg et al. study that tested dual-scale charts, and Few's article working through the cases. Both ship without full metadata rather than guessed metadata; queued. Pie and stacked posts gave verbatim support, plus one correction: a 100%-stacked chart has two readable baselines, not one. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ULE5RRxdQE1ebwefEd2eCM
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The Economist — "Mistakes, we've drawn a few"
Sarah Leo, visual data journalist at The Economist. Supplied as PDF, read 2026-08-05. Answers queue row 4 (content; the canonical URL is still missing) and settles claim V1.
Structure: her own archive, grouped into charts that are (1) misleading, (2) confusing, (3) failing to make a point, each with a redesign at comparable size.
V1 — confirmed, but our note over-claimed it
The article's first example is Mistake: Truncating the scale — a bar chart
of average Facebook likes on posts by the political left:
The original chart not only downplays the number of Mr Corbyn's likes but also exaggerates those on other posts.
So the sin is there, and it leads the piece. But it is one example, not the "several" our citation note claimed. Note corrected to match. (She does add that "avid followers of this blog will have seen another example of this bad practice," which is a pointer elsewhere, not a second case here.)
Unexpected: it contains our dual-axis sin, self-caught
Mistake: Forcing a relationship by cherry-picking scales — dog weights against
neck sizes, on a dual axis, looking perfectly correlated:
In the original chart, both scales decrease by three units (from 21 to 18 on the left; from 45 to 42 on the right). In percentage terms, the left scale decreases by 14% while the right goes down by 7%.
Her takeaway is quotable and close to our page's:
if two series follow each other too closely, it is probably a good idea to have a closer look at the scales.
Added as a citation on dual-axis-correlation. A newsroom catching itself doing
the exact thing is stronger evidence than a textbook saying not to.
Also useful
Taking the "mind-stretch" a little too far— trade deficit vs manufacturing employment, where "the two data series don't share a common baseline. The baseline of the trade deficit is at the top of the chart." Adjacent to our inverted-axis sin without being a case of it; cite carefully if at all.Including too much detail("What a rainbow!") — stacked areas for ten countries. Her point that "since we are not plotting all euro-area countries it doesn't make any sense to stack the data" is a good detail for the stacked backlog entry: stacking implies the parts are the whole.- She cites Francis Gagnon's rule of thumb — leave at least 33% of the plot area free under a line chart that doesn't start at zero. No source captured; not cited anywhere yet.