Darker cells mean a higher score for this topic on that metric.
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Quick answers
When should I pick Choropleth story maps?
When the story is: regional comparisons, civics assignments, territory KPIs.
When should I avoid Choropleth story maps?
Skip it in cases like: raw counts without normalizing by population or area.
Who invented or popularised it?
Baron Charles Dupin (1826); modern TopoJSON + D3 geo pipelines
What does it encode?
color of administrative regions mapped to a quantitative rate
Is it OK in ads?
Yes if one claim is visible at a glance in Meta, Google and retail print; otherwise link to a full figure.
Will a teacher accept it?
Yes for lab reports and poster boards if axes, units and a source line are present.
Choropleth story maps encodes values as color of administrative regions mapped to a quantitative rate. Baron Charles Dupin (1826); modern TopoJSON + D3 geo pipelines.
In reports, ads and assignments it fits regional comparisons, civics assignments, territory KPIs. Skip it when raw counts without normalizing by population or area.
Rules
- Rules 1 — Use color of administrative regions mapped to a quantitative rate as one channel, not two.
- Rules 2 — Direct labels beat a distant legend.
- Rules 3 — Do not hide zero. If you break the axis, say so.
- Rules 4 — Colour encodes category or magnitude, not both.
- Rules 5 — Put the claim in the title, not just "Choropleth story maps".
- Rules 6 — Source and period, even in small type.
Palette
- Palette 1 — Categories: distinct hues. Sequences: one hue, changing value.
- Palette 2 — Diverging: a neutral centre, emphasis at both ends.
- Palette 3 — One brand colour plus greys beats a rainbow.
- Palette 4 — Check contrast on a projector and in greyscale print.
Type
- Type 1 — Tabular figures for numbers. Do not pour body copy into the chart.
- Type 2 — Titles as sentences; axes as short nouns.
- Type 3 — For CJK, drop weight one step and leave tracking.
Choropleth story maps: honour color of administrative regions mapped to a quantitative rate, and switch when raw counts without normalizing by population or area.