Work the five delivered sources into the pages

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.