Setting color and fill Aesthetic Properties

This lesson is called Setting color and fill Aesthetic Properties, part of the Fundamentals of R course. This lesson is called Setting color and fill Aesthetic Properties, part of the Fundamentals of R course.

Transcript

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

library(tidyverse)

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

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

# We add the color argument within aes() so that 
# the data in that variable is mapped to those aesthetic properties.

# With this code, the island variable is mapped to the aesthetic property color

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

# Let's try the same thing with our bar chart

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

# That didn't work! Let's try fill instead.

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

Your Turn

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

library(tidyverse)

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

penguins <- read_csv("penguins.csv")

# Setting color and fill Aesthetic Properties -----------------------------

# Take your graph that uses geom_col() and make the inside of each bar a different color.

# YOUR CODE HERE

# Make your scatterplot from before with flipper length on the x axis and body mass on the y axis
# but make the points different colors based on the island variable

# YOUR CODE HERE

Learn More

You may want to review Chapter 11 from R for Data Science , which includes a section on mapping data to color and fill aesthetics. Chapter 2 of Fundamentals of Data Visualization has a similar discussion. So does Chapter 3 of Data Visualization: A Practical Introduction.

Chapter 11 of ggplot2: Elegant Graphics for Data Analysis is also a good place to learn about color and fill scales.

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

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Tony Yu • March 19, 2025

Why is it that the color= option is treated differently by geom_point and geom_col? The logic seems inconsistent here since "color=" is used as if it is "fill =" by geom_point. What if I want the scatter plot to have black dots with outline color different by island?

Gracielle Higino Coach • March 21, 2025

Hi Tony! That's a great observation! Different geoms have different geometric properties - some are solid points and lines, others can be filled in. The default for geom_point is to use a kind of shape that does not have a filling, but you can change that using the argument shape inside your geom_point() layer. The shape argument has some options that are not "fillable" and others that are. This figure shows the different options of "point shapes".

Play with the code below to explore these options:

ggplot(data = penguins,
       mapping = aes(x = flipper_length_mm,
                     y = body_mass_g,
                     fill = body_mass_g,
                     color = species)) +
  geom_point(shape = 21, size = 5, stroke = 2)

In the code above I specified a filling color and a contour color in the aes layer, determined the shape of the point that I wanted (shape = 21), the size of each point and the contour line width.

Let me know if that's clearer now!