Color scales
Claus O. Wilke
last updated: 2024-02-05

Uses of color in data visualization

1. Distinguish categories (qualitative)

Qualitative scale example

Palette name: Okabe-Ito

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Qualitative scale example

Palette name: ColorBrewer Set1

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Qualitative scale example

Palette name: ColorBrewer Set3

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Uses of color in data visualization

1. Distinguish categories (qualitative)
2. Represent numeric values (sequential)

Sequential scale example

Palette name: Viridis

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Sequential scale example

Palette name: Inferno

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Sequential scale example

Palette name: Cividis

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Uses of color in data visualization

1. Distinguish categories (qualitative)
2. Represent numeric values (sequential)
3. Represent numeric values (diverging)

Diverging scale example

Palette name: ColorBrewer PiYG

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Diverging scale example

Palette name: Carto Earth

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Diverging scale example

Palette name: Blue-Red

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Uses of color in data visualization

1. Distinguish categories (qualitative)
2. Represent numeric values (sequential)
3. Represent numeric values (diverging)
4. Highlight

Highlight example

Palette name: Grays with accents

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Highlight example

Palette name: Okabe-Ito accent

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Highlight example

Palette name: ColorBrewer accent

Figure redrawn from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

Uses of color in data visualization

1. Distinguish categories (qualitative)
2. Represent numeric values (sequential)
3. Represent numeric values (diverging)
4. Highlight

Color scales in ggplot2

Getting the data

The temps_months dataset:

temps_months <- read_csv("https://wilkelab.org/SDS375/datasets/tempnormals.csv") %>%
  group_by(location, month_name) %>%
  summarize(mean = mean(temperature)) %>%
  mutate(
    month = factor(
      month_name,
      levels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun",
                 "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")
    ),
    location = factor(
      location, levels = c("Death Valley", "Houston", "San Diego", "Chicago")
    )
  ) %>%
  select(-month_name)

Getting the data

The popgrowth dataset:

US_census <- read_csv("https://wilkelab.org/SDS375/datasets/US_census.csv")
US_regions <- read_csv("https://wilkelab.org/SDS375/datasets/US_regions.csv")
popgrowth <- left_join(US_census, US_regions) %>%
    group_by(region, division, state) %>%
    summarize(
      pop2000 = sum(pop2000, na.rm = TRUE),
      pop2010 = sum(pop2010, na.rm = TRUE),
      popgrowth = (pop2010-pop2000)/pop2000,
      .groups = "drop"
    ) %>%
    mutate(region = factor(region, levels = c("West", "South", "Midwest", "Northeast")))

ggplot2 color scale functions are a bit of a mess

ggplot2 color scale functions are a bit of a mess

Scale function
Aesthetic    
Data type
Palette type


scale_color_hue()                    
color
discrete         
qualitative                                                  

ggplot2 color scale functions are a bit of a mess

Scale function
Aesthetic    
Data type
Palette type


scale_color_hue()                    
color
discrete         
qualitative                                                  

scale_fill_hue()
fill
discrete
qualitative

ggplot2 color scale functions are a bit of a mess

Scale function
Aesthetic    
Data type
Palette type


scale_color_hue()                    
color
discrete         
qualitative                                                  

scale_fill_hue()
fill
discrete
qualitative

scale_color_gradient()
color
continuous
sequential

ggplot2 color scale functions are a bit of a mess

Scale function
Aesthetic    
Data type
Palette type


scale_color_hue()                    
color
discrete         
qualitative                                                  

scale_fill_hue()
fill
discrete
qualitative

scale_color_gradient()
color
continuous
sequential

scale_color_gradient2()
color
continuous
diverging

ggplot2 color scale functions are a bit of a mess

Scale function	Aesthetic	Data type	Palette type
`scale_color_hue()`	`color`	discrete	qualitative
`scale_fill_hue()`	`fill`	discrete	qualitative
`scale_color_gradient()`	`color`	continuous	sequential
`scale_color_gradient2()`	`color`	continuous	diverging
`scale_fill_viridis_c()`	`color`	continuous	sequential
`scale_fill_viridis_d()`	`fill`	discrete	sequential
`scale_color_brewer()`	`color`	discrete	qualitative, diverging, sequential
`scale_fill_brewer()`	`fill`	discrete	qualitative, diverging, sequential
`scale_color_distiller()`	`color`	continuous	qualitative, diverging, sequential

... and there are many many more

Examples

ggplot(temps_months, aes(x = month, y = location, fill = mean)) + 
  geom_tile(width = 0.95, height = 0.95) + 
  coord_fixed(expand = FALSE) +
  theme_classic()
  # no fill scale defined, default is scale_fill_gradient()

Examples

ggplot(temps_months, aes(x = month, y = location, fill = mean)) + 
  geom_tile(width = 0.95, height = 0.95) + 
  coord_fixed(expand = FALSE) +
  theme_classic() +
  scale_fill_gradient()

Examples

ggplot(temps_months, aes(x = month, y = location, fill = mean)) + 
  geom_tile(width = 0.95, height = 0.95) + 
  coord_fixed(expand = FALSE) +
  theme_classic() +
  scale_fill_viridis_c()

Examples

ggplot(temps_months, aes(x = month, y = location, fill = mean)) + 
  geom_tile(width = 0.95, height = 0.95) + 
  coord_fixed(expand = FALSE) +
  theme_classic() +
  scale_fill_viridis_c(option = "B", begin = 0.15)

Examples

ggplot(temps_months, aes(x = month, y = location, fill = mean)) + 
  geom_tile(width = 0.95, height = 0.95) + 
  coord_fixed(expand = FALSE) +
  theme_classic() +
  scale_fill_distiller(palette = "YlGnBu")

The colorspace package creates some order

Scale name: scale_<aesthetic>_<datatype>_<colorscale>()

The colorspace package creates some order

Scale name: scale_<aesthetic>_<datatype>_<colorscale>()

<aesthetic>: name of the aesthetic (fill, color, colour)
<datatype>: type of variable plotted (discrete, continuous, binned)
<colorscale>: type of the color scale (qualitative, sequential, diverging, divergingx)

The colorspace package creates some order

Scale name: scale_<aesthetic>_<datatype>_<colorscale>()

<aesthetic>: name of the aesthetic (fill, color, colour)
<datatype>: type of variable plotted (discrete, continuous, binned)
<colorscale>: type of the color scale (qualitative, sequential, diverging, divergingx)

Scale function	Aesthetic	Data type	Palette type
`scale_color_discrete_qualitative()`	`color`	discrete	qualitative
`scale_fill_continuous_sequential()`	`fill`	continuous	sequential
`scale_colour_continous_divergingx()`	`colour`	continuous	diverging

Examples

ggplot(temps_months, aes(x = month, y = location, fill = mean)) + 
  geom_tile(width = 0.95, height = 0.95) + 
  coord_fixed(expand = FALSE) +
  theme_classic() +
  scale_fill_continuous_sequential(palette = "YlGnBu", rev = FALSE)

Examples

ggplot(temps_months, aes(x = month, y = location, fill = mean)) + 
  geom_tile(width = 0.95, height = 0.95) + 
  coord_fixed(expand = FALSE) +
  theme_classic() +
  scale_fill_continuous_sequential(palette = "Viridis", rev = FALSE)

Examples

ggplot(temps_months, aes(x = month, y = location, fill = mean)) + 
  geom_tile(width = 0.95, height = 0.95) + 
  coord_fixed(expand = FALSE) +
  theme_classic() +
  scale_fill_continuous_sequential(palette = "Inferno", begin = 0.15, rev = FALSE)

colorspace::hcl_palettes(type = "sequential", plot = TRUE) # all sequential palettes

colorspace::hcl_palettes(type = "diverging", plot = TRUE, n = 9) # all diverging palettes

colorspace::divergingx_palettes(plot = TRUE, n = 9) # all divergingx palettes

Setting colors manually for discrete, qualitative scales

Discrete, qualitative scales are best set manually

ggplot(popgrowth, aes(x = pop2000, y = popgrowth, color = region)) +
  geom_point() +
  scale_x_log10()
  # no color scale defined, default is scale_color_hue()

Discrete, qualitative scales are best set manually

ggplot(popgrowth, aes(x = pop2000, y = popgrowth, color = region)) +
  geom_point() +
  scale_x_log10() +
  scale_color_hue()

Discrete, qualitative scales are best set manually

library(ggthemes)  # for scale_color_colorblind()
ggplot(popgrowth, aes(x = pop2000, y = popgrowth, color = region)) +
  geom_point() +
  scale_x_log10() +
  scale_color_colorblind()  # uses Okabe-Ito colors

Discrete, qualitative scales are best set manually

ggplot(popgrowth, aes(x = pop2000, y = popgrowth, color = region)) +
  geom_point() +
  scale_x_log10() +
  scale_color_manual(
    values = c(West = "#E69F00", South = "#56B4E9", Midwest = "#009E73", Northeast = "#F0E442")
  )

Okabe-Ito RGB codes

Name	Hex code	R, G, B (0-255)
orange	#E69F00	230, 159, 0
sky blue	#56B4E9	86, 180, 233
bluish green	#009E73	0, 158, 115
yellow	#F0E442	240, 228, 66
blue	#0072B2	0, 114, 178
vermilion	#D55E00	213, 94, 0
reddish purple	#CC79A7	204, 121, 167
black	#000000	0, 0, 0

Figure from Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.

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Color scales

Claus O. Wilke

last updated: 2024-02-05

Uses of color in data visualization

Uses of color in data visualization

Qualitative scale example

Qualitative scale example

Qualitative scale example

Uses of color in data visualization

Sequential scale example

Sequential scale example

Sequential scale example

Uses of color in data visualization

Diverging scale example

Diverging scale example

Diverging scale example

Uses of color in data visualization

Highlight example

Highlight example

Highlight example

Uses of color in data visualization

Color scales in ggplot2

Getting the data

Getting the data

ggplot2 color scale functions are a bit of a mess

ggplot2 color scale functions are a bit of a mess

ggplot2 color scale functions are a bit of a mess

ggplot2 color scale functions are a bit of a mess

ggplot2 color scale functions are a bit of a mess

ggplot2 color scale functions are a bit of a mess

Examples

Examples

Examples

Examples

Examples

The colorspace package creates some order

The colorspace package creates some order

The colorspace package creates some order

Examples

Examples

Examples

Setting colors manually for discrete, qualitative scales

Discrete, qualitative scales are best set manually

Discrete, qualitative scales are best set manually

Discrete, qualitative scales are best set manually

Discrete, qualitative scales are best set manually

Okabe-Ito RGB codes

Further reading

Uses of color in data visualization

Help