chart-sins/docs/content-backlog.md

Content backlog — what to write next

Working document. Ranked by what is worth writing — the sins people actually commit, and the pages most worth sending someone.

Sourcing is a constraint on that list, not the thing that generates it: a sin earns a slot because it's worth a page, and then we go find the sources that make the case. Never the reverse. What we don't do is invent authority, or stretch a source into saying something it doesn't.

The list deliberately mixes registers. Some sins are subtle enough that a competent analyst commits them by accident; others are arithmetically void and indefensible on sight. Both belong — the egregious ones are the most sendable pages we can write, because there's nothing to argue about, and the subtle ones are what keep the site useful to people who already know the basics. Severity runs 2–5 on purpose.

Sources in play

src/lib/references.ts currently holds 22 entries, 18 of them cited by the five published sins. This table is a convenience, not a scoreboard — it's here so you can spot a source that fits a sin you're drafting, not so we can drive the right-hand column to zero blanks. An uncited reference is not a debt.

Adding new references is the normal way to strengthen a page. If a sin deserves seven sources, give it seven and add whatever's missing to the file.

Reference	Cited by
ftvisvocab	—
healy	—
munzner	—
schwabish	—
datawrapper	dual-axis-correlation
fewpies	too-many-pie-slices
huff	truncated-y-axis
shapeparameter	aspect-ratio
showmenumbers	too-many-pie-slices
spurious	dual-axis-correlation
swd	dual-axis-correlation
tufte	truncated-y-axis
vizwtf	inverted-y-axis
callingbullshit	inverted-y-axis, truncated-y-axis
datatoviz	dual-axis-correlation, too-many-pie-slices
eagereyes	aspect-ratio, too-many-pie-slices
economistmistakes	inverted-y-axis, truncated-y-axis
junkcharts	inverted-y-axis, too-many-pie-slices
truthfulart	aspect-ratio, dual-axis-correlation
wilke	too-many-pie-slices, truncated-y-axis
clevelandmcgill	aspect-ratio, too-many-pie-slices, truncated-y-axis
howchartslie	aspect-ratio, dual-axis-correlation, inverted-y-axis, truncated-y-axis

The citation lists in each entry below are starting points, not budgets — add to them while drafting.

Ranked backlog

1. A Cherry-Picked Time Range — Deceptive Framing, severity 5

Poke: "You started the clock exactly where the story got good."

The trend runs one way over five years and the other way over five months, so the chart shows the five months. Nothing about the chart is technically false — the axis starts at zero, the labels are honest — which is what makes it the nastiest sin on this list.

Charts: one series, two views. Bad = the flattering slice. Fixed = the full record with the slice shaded in place. Literally the same dataset filtered, so the "same numbers, both charts" rule holds by construction — the strongest proof we can build.

Citations: huff (the original con), callingbullshit, howchartslie, junkcharts.

2. Pie Slices That Sum to More Than 100% — Impossible Wholes, severity 5

Poke: "Your slices add up to 180%. A pie has one job — dividing a whole — and this data has no whole to divide."

The multi-select survey is the classic source: "which of these tools do you use?", respondents tick three each, and the results get poured into a pie. The wedges are now sized as fractions of a total that doesn't exist, so every one of them is drawn wrong, and the "share" each appears to hold is pure artifact.

Unlike most of this list, there's no judgment call — the chart is arithmetically void. That's the appeal: nothing to argue about, and no way to defend it in a meeting.

Charts: bad = pie of multi-select response counts, wedges summing past the circle. Fixed = bar chart, one bar per option, each labelled "% of respondents" with the base stated. Same counts.

Citations: fewpies, datawrapper (their pie-chart guidance covers when the form applies at all), datatoviz, junkcharts.

3. A Pie Chart of Rates or Averages — Impossible Wholes, severity 5

Poke: "You made a pie out of averages. Adding them together produces a number that means nothing, and that number is your denominator."

The other half of the same mistake, and the one people defend for longer. Average deal size by region, conversion rate by channel, satisfaction score by team — relative metrics, each with its own denominator, stacked into wedges as if they were parts of a shared total. A region with a high average takes a big slice regardless of how many deals it actually did.

Worth its own page rather than folding into the entry above: the tell is different (these numbers can sum to 100% by coincidence), and the person who needs sending here is making a different error — a category mistake about what their metric is, not a counting mistake.

Charts: bad = pie of average order value by region. Fixed = bar chart of the same averages, plus the volume behind each one so the weighting is visible.

Citations: fewpies, munzner (part-to-whole is a composition of a whole, or it is nothing), schwabish, ftvisvocab.

4. Group Averages Shown Without the Distribution — Hiding the Data, severity 4

Poke: "Four bars, four averages, and no idea whether the difference is real."

The bar-of-means: every group collapsed to one number, so wildly different distributions draw identical bars. Wilke devotes a section to exactly this and Healy makes the perceptual case.

Charts: bad = grouped bar of means. Fixed = strip/box plot over the same observations, means still marked.

Citations: wilke, healy, schwabish, datatoviz.

5. Bubbles Sized by Radius Instead of Area — Perceptual Traps, severity 4

Poke: "You doubled the number and quadrupled the ink."

Scaling a circle's radius by the value instead of its area squares the apparent difference. This is Tufte's Lie Factor with an actual number attached, and Munzner's channel ranking — already underwriting the pie and truncated-axis sins — applies directly.

Charts: bad = radius ∝ value (a calculate transform squaring the size encoding). Fixed = area ∝ value, or better, the same values as a dot plot where position does the work.

Citations: munzner, clevelandmcgill, tufte, howchartslie.

6. Stacked Segments Without a Shared Baseline — Perceptual Traps, severity 3

Poke: "Only the bottom band of a stacked chart has a straight edge to measure against. The rest are guesses."

In a stacked column chart, every segment except the bottom one starts at a baseline that moves from column to column, so readers can compare the total and the bottom series — and nothing else. The series you actually care about is usually floating somewhere in the middle. Datawrapper's guidance is blunt about it: bring the most important value to the bottom, because readers can only compare values that share a baseline.

Ubiquitous in business dashboards, which is what earns it a slot despite the milder severity.

Charts: bad = stacked columns with the interesting series stranded in the middle. Fixed = the same numbers as small multiples (or the key series pulled out to its own zero baseline), totals preserved.

Citations: datawrapper, wilke, munzner, ftvisvocab.

7. Categories Sorted Alphabetically Instead of by Value — Sloppy Craft, severity 2

Poke: "Your categories are sorted by name. Nobody wants to know which region starts with A."

Venial, universal, and the single most useful page to fire at a colleague — which is the whole product thesis. Low severity is a feature: the gallery needs a range.

Charts: bad = categorical bars in alphabetical order. Fixed = same bars sorted by value.

Citations: schwabish, ftvisvocab, swd, fewpies.

Not yet buildable

Real sins, but our pipeline can't prove them honestly today. Recorded so we stop rediscovering them:

• 3D bars / gratuitous perspective and chartjunk (Tufte, Few) — Vega-Lite won't render the sin, and a screenshot violates the same-pipeline rule that makes the before/after credible.
• Counts on a choropleth instead of rates (Cairo's set-piece) — needs TopoJSON geometry and a build-time data dependency we don't have yet. Strong candidate the moment we take that on.
• Rainbow color scales for continuous data (Wilke, Munzner, and Datawrapper's four-part color-scale series — the best free treatment of this anywhere) — sourcing is not the constraint. What still blocks it is ours: the fixed chart needs a sequential ramp validated on --chart-canvas in both themes. Do the palette work first (dataviz skill + its validator), then this is ready to write.

Conventions reminder

Note what the two pie entries above do and don't say. Neither condemns the pie chart — both condemn feeding one data that has no whole to divide. Same for a second y-axis: the form is fine, the manufactured correlation is not. We don't ban chart types here, and a backlog entry that reads like a blanket ban has been written wrong. See the severity rubric in CLAUDE.md — a form with legitimate uses caps out at 4.

Anything picked up from this list still follows CLAUDE.md: the title names the problem plainly and leaves the wit to the poke, the poke names the general sin and never our sample's numbers, both charts share one dataset, and the fixed chart obeys every rule the site preaches.

The headings above are working titles written to that rule — they say what the sin is, so they can be taken as-is or rephrased without having to first decode a pun.