Themes
This lesson is called Themes, part of the R in 3 Months (Spring 2025) course. This lesson is called Themes, part of the R in 3 Months (Spring 2025) course.
Transcript
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# Load Packages -----------------------------------------------------------
library(tidyverse)
# Import Data -------------------------------------------------------------
penguins <- read_csv("penguins.csv")
# Themes ------------------------------------------------------------------
# To add a theme to a plot, we use the theme_ set of functions.
# There are several built-in themes. For instance, theme_minimal().
ggplot(data = penguin_bill_length_by_island_and_sex,
mapping = aes(x = island,
y = mean_bill_length,
fill = sex)) +
geom_col(position = "dodge") +
labs(title = "Males have longer bills than females",
subtitle = "But they're all good penguins",
caption = "Data from the palmerpenguins R package",
x = NULL,
y = "Mean Bill Length in Millimeters",
fill = NULL) +
theme_minimal()
# There's also theme_light().
ggplot(data = penguin_bill_length_by_island_and_sex,
mapping = aes(x = island,
y = mean_bill_length,
fill = sex)) +
geom_col(position = "dodge") +
labs(title = "Males have longer bills than females",
subtitle = "But they're all good penguins",
caption = "Data from the palmerpenguins R package",
x = NULL,
y = "Mean Bill Length in Millimeters",
fill = NULL) +
theme_light()
# There are also packages that give you themes you can apply to your plots.
# Let's load the ggthemes() package
# Install it if necessary using install.packages("ggthemes")
library(ggthemes)
# We can then use a theme from this package called theme_economist()
# to make our plots look like those in the Economist.
ggplot(data = penguin_bill_length_by_island_and_sex,
mapping = aes(x = island,
y = mean_bill_length,
fill = sex)) +
geom_col(position = "dodge") +
labs(title = "Males have longer bills than females",
subtitle = "But they're all good penguins",
caption = "Data from the palmerpenguins R package",
x = NULL,
y = "Mean Bill Length in Millimeters",
fill = NULL) +
theme_economist()
# You can see a number of other themes from this package at
# https://yutannihilation.github.io/allYourFigureAreBelongToUs/ggthemes/
Your Turn
# Load Packages -----------------------------------------------------------
library(tidyverse)
# Import Data -------------------------------------------------------------
penguins <- read_csv("penguins.csv")
# Themes ------------------------------------------------------------------
# Use one of the built-in ggplot2 themes to change the look and feel of your last plot
# https://ggplot2.tidyverse.org/reference/index.html#themes
# YOUR CODE HERE
# Install the ggthemes package
# Load the ggthemes package
# Use one of themes from the package to update your last plot
# The themes can be found here:
# https://yutannihilation.github.io/allYourFigureAreBelongToUs/ggthemes/
# YOUR CODE HERE
Learn More
Data Visualization: A Practical Introduction has a section on themes in Chapter 8.
If you’re looking for packages that give you extra themes, check out this roundup.
Note that theme packages often include code that changes to overall look and feel as well as palettes that you can apply to the color and fill scales.
Have any questions? Put them below and we will help you out!
Course Content
127 Lessons
1
Welcome to Getting Started with R
00:57
2
Install R
02:05
3
Install RStudio
02:14
4
Files in R
04:33
5
Projects
07:54
6
Packages
02:38
7
Import Data
05:24
8
Objects and Functions
03:16
9
Examine our Data
12:50
10
Import Our Data Again
07:11
11
Getting Help
07:46
12
Week 1 Live Session (Spring 2025)
1:03:11
1
Welcome to Fundamentals of R
01:36
2
Update Everything
02:45
3
Start a New Project
02:16
4
The Tidyverse
03:34
5
Pipes
04:15
6
select()
07:25
7
mutate()
04:25
8
filter()
10:05
9
summarize()
05:59
10
group_by() and summarize()
05:54
11
arrange()
02:07
12
Create a New Data Frame
03:58
13
Bring it All Together (Data Wrangling)
07:29
14
Week 2 Project Assignment
09:39
15
Week 2 Coworking Session (Spring 2025)
16
Week 2 Live Session (Spring 2025)
1:03:24
1
The Grammar of Graphics
04:39
2
Scatterplots
03:46
3
Histograms
05:47
4
Bar Charts
06:37
5
Setting color and fill Aesthetic Properties
02:39
6
Setting color and fill Scales
05:40
7
Setting x and y Scales
03:09
8
Adding Text to Plots
07:32
9
Plot Labels
03:57
10
Themes
02:19
11
Facets
03:12
12
Save Plots
02:57
13
Bring it All Together (Data Visualization)
06:42
14
Week 3 Project Assignment
03:30
15
Week 3 Coworking Session (Spring 2025)
16
Week 3 Live Session (Spring 2025)
1:02:31
1
Downloading and Importing Data
10:32
2
Overview of Tidy Data
05:50
3
Tidy Data Rule #1: Every Column is a Variable
07:43
4
Tidy Data Rule #3: Every Cell is a Single Value
10:04
5
Tidy Data Rule #2: Every Row is an Observation
04:42
6
Week 6 Coworking Session (Spring 2025)
7
Week 6 Live Session (Spring 2025)
1:02:38
1
Best Practices in Data Visualization
03:44
2
Tidy Data
02:25
3
Pipe Data into ggplot
09:54
4
Reorder Plots to Highlight Findings
03:37
5
Line Charts
04:17
6
Use Color to Highlight Findings
09:16
7
Declutter
08:29
8
Add Descriptive Labels to Your Plots
09:10
9
Use Titles to Highlight Findings
08:14
10
Use Annotations to Explain
07:09
11
Week 9 Coworking Session (Spring 2025)
12
Week 9 Live Session (Spring 2025)
59:09
1
Advanced Markdown
06:43
2
Tables
18:36
3
Advanced YAML and Code Chunk Options
05:53
4
Inline R Code
04:42
5
Making Your Reports Shine: Word Edition
04:30
6
Making Your Reports Shine: PDF Edition
06:11
7
Making Your Reports Shine: HTML Edition
06:06
8
Presentations
10:12
9
Dashboards
05:38
10
Websites
06:43
11
Publishing Your Work
04:38
12
Quarto Extensions
05:50
13
Parameterized Reporting, Part 1
10:57
14
Parameterized Reporting, Part 2
05:11
15
Parameterized Reporting, Part 3
07:47
16
Week 12 Coworking Session (Spring 2025)
17
Week 12 Live Session (Spring 2025)
57:01
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Maria Montenegro • April 9, 2024
This is super helpful! I'm assuming we can create our own themes? Would you be able to show us how to go about this?
David Keyes Founder • April 9, 2024
Yes! In the Going Deeper Advanced Data Visualization section, there are lessons that show you how to make your own custom ggplot theme.