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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Datawrapper — pie charts, and stacked column charts
Two "Data vis do's & don'ts" posts by Lisa Charlotte Muth, supplied as PDFs and read 2026-08-05. Answers queue rows 1 and 6.
"What to consider when creating pie charts" (3 Jan 2018)
blog.datawrapper.de/pie-charts/
Opening line, which is the useful one for us:
Pie charts are great to show how 100% divide up into a few shares.
And the positive case, which we should keep quoting when people accuse us of banning the form:
Pie charts work best for values around 25%, 50% or 75%. It's easier for readers to spot these percentages in a pie chart than in a stacked bar or column chart.
Then the limits, both of which are our published sin:
Pie charts are not the best choice if you want readers to compare the size of shares. That's especially true if the differences between the shares are small.
Pie charts work best if you only have a few values – five max.
Our sample pie has eight. Cited on too-many-pie-slices.
Caveat for backlog entries 2 and 3. This post does not say in so many words that a pie's parts must be mutually exclusive and sum to 100% — so it can't be cited for the multi-select survey case as I'd hoped. What it does give is the premise those sins rest on:
One pie chart can only show one total and its shares.
That's enough to support "there must be a whole," and nothing more. The backlog notes now say exactly that rather than implying a stronger claim.
Also flags Robert Kosara's "Understanding Pie Charts" as a "great research-based
explanation of how people read pie charts" — independent support for our
eagereyes note (claim V7). URL not captured; queued.
"What to consider when creating stacked column charts" (13 Feb 2018)
blog.datawrapper.de/stacked-column-charts/
The sentence backlog entry 6 is built on:
It's hard for readers to compare columns that don't start at the same baseline.
And the design guidance:
Bring the most important value to the bottom of the chart and use color to make it stand out. Your readers can compare values easier with each other if they have the same baseline.
Useful nuance I hadn't accounted for: a 100%-stacked chart has two usable baselines, not one —
You will gain a second baseline at the top of your chart where you can place the second most important category in your data.
So the sin is sharper than "only the bottom is readable": everything between the two baselines floats. Worth writing the page that way.
Also: "Make sure that you include all parts of the total in your charts – and only parts of the total." Pairs with the Economist's rainbow-stack example, where a partial selection of countries was stacked as if it were the whole.