# Datawrapper — "Which color scale to use when visualizing data" (part 1 of 4)

Lisa Charlotte Muth, `blog.datawrapper.de/which-color-scale-to-use-in-data-vis/`,
**16 March 2021**. Supplied as PDF, read 2026-08-05. Partly answers queue row 3.

## This does not say what I assumed it said

I had queued this expecting it to condemn rainbow/spectral scales, and wrote in
the backlog that the series was "the best free treatment of this anywhere" for
that purpose. **Part 1 makes no such argument.** It is a taxonomy — categorical
vs sequential vs diverging, classed vs unclassed — and its closing section is
called "It's not as clear-cut as it seems."

Worse for my assumption, it actively softens the single-hue rule:

> You can use only one hue in your sequential gradients (e.g., light blue to
> dark blue) – but almost all examples I show here use multiple hues (e.g.,
> light yellow to dark blue). Using two or even more hues increases the color
> contrast between segments of your gradient, making it easier for readers to
> distinguish between them.

So "sequential must be one hue" is **not** a rule we can attribute here, and a
future rainbow sin must not be written as though multi-hue gradients are the
problem. The problem with rainbow scales is non-monotonic lightness and implied
banding, which is a different claim needing a different source.

## What it is good for

- Clean definitions of categorical / sequential / diverging, and classed vs
  unclassed, if a future sin needs to explain the vocabulary.
- The framing that a color scale is a *mapping* to data, same as any axis.
- Its own reference list points at Robert Simmon's *Subtleties of Color* (2013)
  and Wilke's color-scales chapter — both plausible homes for the actual
  rainbow argument.

## Still needed for the rainbow sin

Parts 2, 3 and 4 of this series, and Kosara's "How The Rainbow Color Map
Misleads" (referenced by search results, never read). Re-queued. Until one of
those is in hand, the rainbow sin has **no** verified source and should not be
drafted.