color for data visualization

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COLOR FOR DATA VISUALIZATION

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Page 1: Color for Data Visualization

COLOR FOR

DATA VISUALIZATION

Page 2: Color for Data Visualization

The fundamental uses of color in information

design (are): to label, to measure, to represent

or imitate reality, to enliven or decorate.

COLOR

Page 3: Color for Data Visualization

Is this a good or bad use of color?

Page 4: Color for Data Visualization

Particularly avoid Roy G. Biv (red, orange,

yellow, green, blue, indigo, violet), the color

spectrum of the rainbow.

THE FIRST RULE

Page 5: Color for Data Visualization

BASIC COLOR THEORY

How humans think about color How computers process color

Page 6: Color for Data Visualization

COLOR PERCEPTION

A constant increase in brightness is not perceived as linear,

and this response is different for red, green, and blue. Look

for tools and color palettes that describe colors in a

perceptual color space, like CIE L*C*h or Munsell.

Page 7: Color for Data Visualization

A color scale should vary consistently across the entire range of values, so

that each step is equivalent, regardless of its position on the scale.

A palette should also minimize errors from the color shifts introduced by

nearby areas of differing color or lightness, a phenomenon known as

simultaneous contrast.

Page 8: Color for Data Visualization

Combine a linear, proportional change in lightness with a simultaneous

change in hue and saturation to achieve the perfect palette for

sequential data.

SEQUENTIAL DATA

Page 9: Color for Data Visualization

For divergent data, use palettes that are composed of two sequential

palettes merged with a neutral color.

This type of palette works because it takes advantage of pre attentive

processing: our visual systems can discriminate the different colors quickly

and without conscious thought.

DIVERGENT DATA

Page 10: Color for Data Visualization

A sequential palette that varies uniformly in lightness will still be readable by

someone with color deficient vision (or a black and white print), regardless

of the hue. But a divergent palette with matched lightness can be difficult or

impossible to parse if the viewer can’t distinguish the hues.

COLOR DEFICIENCY CAUTION

Page 11: Color for Data Visualization

Instead of representing proportional relationships, color is used to separate

areas into distinct categories. The palette should consist of colors as distinct

from one another as possible. Due to the limits of perception, especially

simultaneous contrast, the maximum number of categories that can be

displayed is about 12

CATEGORICAL/QUALITATIVE DATA

Page 12: Color for Data Visualization

If you need to display double-digit categories, it’s best to group similar

classes together.

>12 CATEGORIES

A grouped color scheme allows the USGS to simultaneously show 16 different

land cover classes in a single map of the area surrounding Portland, Oregon.

Page 13: Color for Data Visualization

RESOURCES FOR SELECTING COLORS

Page 14: Color for Data Visualization

Pros: Very easy to use, all palettes here are “safe”, available on D3

Cons: Limited color palettes to choose from

COLOR BREWER

Page 15: Color for Data Visualization

NASA AMES COLOR TOOL

Page 16: Color for Data Visualization

CHROMA.JS

Page 17: Color for Data Visualization

HCL PICKER BY TRISTEN BROWN

Page 19: Color for Data Visualization

I WANT HUE

For categorical palettes

Page 20: Color for Data Visualization

COLOR GUIDELINES FROM TUFTE

Page 21: Color for Data Visualization

Color spots against a light gray or muted field

highlight and italicize data.

A magnetogram is a map of magnetic fields, in this case on the surface of the

Sun. A divergent palette suits this data because the north polarity (red) and

south polarity (blue) are both measurements of the same quantity (magnetism), just with opposite signs.

SDO HMI image adapted from the Solar Data Analysis Center.

Page 22: Color for Data Visualization

Use colors found in nature, especially those on the

lighter side.

The subtle colors in this bathymetric map of Crater Lake are a direct descendent of

the palettes created by Eduard Imhof. Map courtesy National Park Service

Harper’s Ferry Center.

Page 23: Color for Data Visualization

The unnatural colors of the rainbow palette (left) are often difficult for novice viewers to interpret. A more naturalistic palette for phytoplankton(more or less a type of ocean vegetation) trends from dark

blue for barren ocean, through turquoise, green, and yellow for increasing concentrations of the tiny plants and algae.

Page 24: Color for Data Visualization

Pure, bright or very strong colors have loud, unbearable effects when

they stand unrelieved over large areas adjacent to each other, but

extraordinary effects can be achieved when they are used sparingly on

or between dull background tones.

Screenshot from the BBC’s traffic accident visualization

http://www.bbc.co.uk/news/uk-15975724

Page 25: Color for Data Visualization

Large area background or base-colors should

do their work most quietly, allowing the smaller,

bright areas to stand out most vividly, if the

former are muted, grayish or neutral.

DO NOT DO THIS

Page 26: Color for Data Visualization