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R in 3 Months (Fall 2021)

Customize Your Theme

This lesson is called Customize Your Theme, part of the R in 3 Months (Fall 2021) course. This lesson is called Customize Your Theme, part of the R in 3 Months (Fall 2021) course.

Transcript

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Your Turn

Solution

theme_student <- function() {
  theme_minimal() +
    theme(axis.title = element_blank(),
          panel.grid.minor.y = element_blank(),
          plot.title = element_markdown(face = "bold"))
}

enrollment_by_race_ethnicity %>% 
  filter(race_ethnicity == "Hispanic/Latino") %>% 
  ggplot(aes(x = year,
             y = percent_of_total_at_school,
             group = district)) +
  geom_line(color = "lightgray",
            alpha = 0.5) +
  geom_line(data = highlight_district,
            inherit.aes = TRUE,
            color = "blue") +
  geom_text(data = highlight_district,
            inherit.aes = TRUE,
            aes(label = percent_display),
            hjust = c(1, 0),
            color = "blue") +
  scale_y_continuous(labels = percent_format()) +
  labs(title = "<span style = 'color: blue'>Douglas ESD</span> saw a large growth in its Latino student population from 2017-2018 to 2018-2019") +
  annotate("text",
           x = 2.02,
           y = .825,
           hjust = 0,
           color = "gray",
           label = "Woodburn has the highest\npercentage of Latino students\nof any district") +
  scale_x_discrete(expand = expansion(add = c(0.1, 0.5))) +
  theme_student()

Make your own theme by combining elements of the theme() function and/or themes from other packages (e.g. theme_ipsum())
Add this theme to your plot, removing any code that is now redundant

Learn More

If you want to see a bunch of complete themes ready for your use, I've written a blog post that may be of interest to you. If you want to dive deep on creating custom themes, Andrew Heiss has some great materials here.

If you have trouble, as I do, remembering the various theme elements, this blog post from Henry Wang has a nice overview to help you.

ggplot2 Theme Elements Demonstration.

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

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Catherine Roller White • May 15, 2021

This is great. What's the best way to store and retrieve code for your customized themes? Do you have some sort of generic .R file that you'd retrieve it from for each project?

Course Content

134 Lessons

Welcome to Getting Started with R

Install RStudio

Objects and Functions

Examine our Data

Import Our Data Again

R in 3 Months Fall 2021 Week 1 Live Session

Welcome to Fundamentals of R

RMarkdown Overview

R in 3 Months Fall 2021 Week 2 Project Assignment

R in 3 Months Fall 2021 Week 2 Office Hours

R in 3 Months Fall 2021 Week 2 Live Session

Getting Started

Create a New Data Frame

R in 3 Months Fall 2021 Week 3 Project Assignment

R in 3 Months Fall 2021 Week 3 Office Hours

R in 3 Months Fall 2021 Week 3 Live Session

An Important Workflow Tip

The Grammar of Graphics

Text and Labels

R in 3 Months Fall 2021 Week 4 Project Assignment

R in 3 Months Week 4 Office Hours

R in 3 Months Fall 2021 Week 4 Live Session

R in 3 Months Fall 2021 Week 5 Office Hours

What is Git? What is GitHub?

Why Should You Learn to Use Git and GitHub?

Update Everything

Create a Local Git Repository

GitHub Repositories

Connect RStudio and GitHub

Push an RStudio Project to a GitHub Repository

Pull a GitHub Repository to an RStudio Project

Keep RStudio and GitHub in Sync

R in 3 Months Week 6 Office Hours

R in 3 Months Fall 2021 Week 6 Project Assignment

R in 3 Months Fall 2021 Week 6 Live Session

Dealing with Missing Data

Changing Variable Types

Advanced Variable Creation

Advanced Summarizing

Binding Data Frames

R in 3 Months Fall 2021 Week 7 Project Assignment

R in 3 Months Fall 2021 Week 7 Live Session

R in 3 Months Week 7 Office Hours

Renaming Variables

Quick Interlude to Reorganize our Code

R in 3 Months Fall 2021 Week 8 Project Assignment

R in 3 Months Fall 2021 Week 8 Office Hours

R in 3 Months Fall 2021 Week 8 Live Session

R in 3 Months Fall 2021 Week 9 Office Hours

Data Visualization Best Practices

Pipe Data Into ggplot

Reorder Plots to Highlight Findings

Use Color to Highlight Findings

Use the scales Package for Nicely Formatted Values

Use Direct Labeling

R in 3 Months Fall 2021 Week 10 Project Assignment

R in 3 Months Week 10 Office Hours

R in 3 Months Fall 2021 Week 10 Live Session

Use Axis Text Wisely

Use Titles to Highlight Findings

Use Color in Titles to Highlight Findings

Use Annotations to Explain

Customize Your Theme

Customize Your Fonts

Try New Plot Types

R in 3 Months Fall 2021 Week 11 Project Assignment

R in 3 Months Week 11 Office Hours

R in 3 Months Fall 2021 Week 11 Live Session

Advanced Markdown Text Formatting

Making Your Reports Shine: Word Edition

Making Your Reports Shine: HTML Edition

Making Your Reports Shine: PDF Edition

R in 3 Months Week 12 Project Assignment

R in 3 Months Week 12 Office Hours

R in 3 Months Week 12 Live Session

R in 3 Months Fall 2021 Final Project Assignment

R in 3 Months Fall 2021 Week 13 Live Session

R in 3 Months Fall 2021 Week 14 Office Hours

R in 3 Months Fall 2021 Week 14 Live Session