Guidelines
Suggest edit

Use lightness shades of one hue when totals matter more than parts

For part-whole charts with many categories, use color-lightness variation within one hue on category parts to improve readability and address overly confetti-like palettes for readers who should notice totals before parts.

  • purpose:refine
  • basis:heuristic
  • lever:encoding
  • channel:color-lightness:use
  • operator:part-whole
  • group-cardinality:many
  • quality:readability:use
  • polish:palette

advice

Simplify the palette with lightness

Replace many hues with darker and lighter shades of one hue when you want totals to dominate. For example, use shaded segments in a stacked bar chart instead of a many-hue palette so the total bars read first and the parts stay visible.

reason

Shift attention from parts to totals

A one-hue lightness scale reduces color variety while preserving separation between categories. It also changes emphasis: readers notice the overall total more readily, while the individual parts recede compared with a multi-hue palette.

Mechanism: Lightness variation keeps categories distinguishable enough to read, but it weakens part-to-part contrast and makes the full bar or total more visually prominent.

Evidence: The post recommends darker and lighter versions of one hue to make charts less confetti-like, and it explicitly notes that this shifts focus toward totals and away from parts, especially in stacked bar charts (Muth, 2022).

context

Use when totals should read first

  • User Goal: Reduce palette complexity while keeping parts visible.
  • Task: Show totals and their parts, with totals carrying more weight.
  • Data: Many categorical parts are shown inside larger totals.
  • Chart Setting: A part-whole chart such as a stacked bar chart.
  • Audience: Readers who should grasp the overall total quickly.
  • Success Criterion: Totals stand out without making all parts identical.

exceptions

Do not use when parts are as important as totals

Break it when: Readers need the parts to be as important as or more important than the totals. Why: Shades are harder to tell apart than different hues and will push attention away from the parts.

costs

Accept weaker part separation

Sacrifice: You give up some part-to-part distinctness. Risk: Readers may struggle to compare individual categories closely. Mitigation: Keep different hues when the parts themselves are the main story.

mistakes

Avoid using shades for part-heavy reading

Mistake: Switching to same-hue shades when the main job is to compare the parts against each other. Why it fails: The palette reduces the contrast that those comparisons need.

check

Compare focus before and after the palette change

Failure Sign: The chart still feels confetti-like even though totals should be the main read. Quick Check: Compare a many-hue version with a one-hue shaded version and see whether totals become more prominent. Stronger Test: Ask whether the palette change has made the parts harder to tell apart than the task allows.

fix

Edit the palette toward one hue

  • Replace multiple category hues with darker and lighter versions of a single hue.
  • Review whether the totals now read first.
  • Return to different hues if the parts need stronger visual separation.

References

Muth, L. C. (2022). 10 ways to use fewer colors in your data visualizations. https://www.datawrapper.de/blog/10-ways-to-use-fewer-colors-in-your-data-visualizations