Setting color and fill Scales

This lesson is called Setting color and fill Scales, part of the R in 3 Months (Fall 2026) course. This lesson is called Setting color and fill Scales, part of the R in 3 Months (Fall 2026) course.

Transcript

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View code shown in video

# Load Packages -----------------------------------------------------------

library(tidyverse)

# Import Data -------------------------------------------------------------

penguins <- read_csv("penguins.csv")

penguin_bill_length_by_island <-
  penguins |>
  group_by(island) |>
  summarize(mean_bill_length = mean(bill_length_mm, na.rm = TRUE)) |>
  arrange(mean_bill_length)

# Setting color and fill Scales -------------------------------------------

# We can change the color or fill scale using a scale function.

# The function scale_color_manual() allows us to manually specify colors to use.

ggplot(
  data = penguins,
  mapping = aes(
    x = bill_length_mm,
    y = bill_depth_mm,
    color = island
  )
) +
  geom_point() +
  scale_color_manual(
    values = c(
      "orange",
      "dodgerblue",
      "green"
    )
  )

# We can also use built-in palettes.

# The scale_color_viridis_d() function (the d means it works with discrete data)
# is a great way to get colorblind-friendly palettes.

ggplot(
  data = penguins,
  mapping = aes(
    x = bill_length_mm,
    y = bill_depth_mm,
    color = island
  )
) +
  geom_point() +
  scale_color_viridis_d()

# The scale_color_viridis_d() function also has several built-in palettes.
# You can use them as follows.

ggplot(
  data = penguins,
  mapping = aes(
    x = bill_length_mm,
    y = bill_depth_mm,
    color = island
  )
) +
  geom_point() +
  scale_color_viridis_d(option = "H")

# We can use scale_fill_viridis_d() for the fill aesthetic property.

ggplot(
  data = penguin_bill_length_by_island,
  mapping = aes(
    x = island,
    y = mean_bill_length,
    fill = island
  )
) +
  geom_col() +
  scale_fill_viridis_d()

ggplot(
  data = penguin_bill_length_by_island,
  mapping = aes(
    x = island,
    y = mean_bill_length,
    fill = mean_bill_length
  )
) +
  geom_col() +
  scale_fill_viridis_c()

ggplot(
  data = penguins,
  mapping = aes(
    x = bill_length_mm,
    y = bill_depth_mm,
    color = bill_depth_mm
  )
) +
  geom_point() +
  scale_color_viridis_c()

Your Turn

Solution

# Load Packages -----------------------------------------------------------

library(tidyverse)

# Import Data -------------------------------------------------------------

penguins <- read_csv("penguins.csv")

penguins_by_species <-
  penguins |>
  count(species)

# Setting color and fill Scales -------------------------------------------

# Take your scatterplot that you just made and add a scale using scale_color_manual().
# You can find a list of all colors you can use here:
# https://www.datanovia.com/en/blog/awesome-list-of-657-r-color-names/

ggplot(
  data = penguins,
  mapping = aes(
    x = flipper_length_mm,
    y = body_mass_g,
    color = island
  )
) +
  geom_point() +
  scale_color_manual(
    values = c(
      "red",
      "blue",
      "green"
    )
  )

# Now update the last bar chart you made by manually specifying colors of the bars

ggplot(
  data = penguins_by_species,
  mapping = aes(
    x = species,
    y = n,
    fill = species
  )
) +
  geom_col() +
  scale_fill_manual(
    values = c(
      "red",
      "blue",
      "green"
    )
  )

# Update your bar chart using the scale_fill_viridis_d() function instead of
# scale_fill_manual()

ggplot(
  data = penguins_by_species,
  mapping = aes(
    x = species,
    y = n,
    fill = species
  )
) +
  geom_col() +
  scale_fill_viridis_d()

# Load Packages -----------------------------------------------------------

library(tidyverse)

# Import Data -------------------------------------------------------------

penguins <- read_csv("penguins.csv")
			
# Setting color and fill Scales -------------------------------------------

# Take your scatterplot that you just made and add a scale using scale_color_manual(). 
# You can find a list of all colors you can use here:
# https://www.datanovia.com/en/blog/awesome-list-of-657-r-color-names/

# YOUR CODE HERE

# Now update the last bar chart you made by manually specifying colors of the bars

# YOUR CODE HERE

# Update your bar chart using the scale_fill_viridis_d() function instead of
# scale_fill_manual()

# YOUR CODE HERE

Learn More

You can see a list of all named colors here.

There are a lot of other packages that give you color/fill palettes you can work with. See especially the paleteer package, which is a meta palette package, give you access to palettes from many other packages.

Have any questions? Put them below and we will help you out!

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Mallik Janthak • October 19, 2026

Don't know why this code is not showing any color. Please advice.

# Now update the last bar chart you made by manually specifying colors of the bars

ggplot(
  data = penguins,
  mapping = aes(x = species)
) +
  geom_bar(stat = "count") +
  scale_color_manual(
    values = c(
      "beige",
      "darkkhaki",
      "darkbrown"
    )
  )



# Update your bar chart using the scale_fill_viridis_d() function instead of
# scale_fill_manual()

ggplot(
  data = penguins,
  mapping = aes(x = species)
) +
  geom_bar(stat = "count") +
  scale_color_viridis_c()

Gracielle Higino Coach • October 19, 2026

Hi Mallik! Your code is missing a color or fill argument in the aesthetic layer. This is needed to tell R where it should apply the colors you're listing in the scale_color layers.