Chapter 27 Advanced ggplot2

What You’ll Learn:

Scales and coordinate systems
Advanced themes
Annotations and labels
Multiple plots
Statistical transformations

Key Errors Covered: 18+ advanced ggplot2 errors

Difficulty: ⭐⭐⭐ Advanced

27.1 Introduction

Advanced ggplot2 enables publication-quality graphics:

library(ggplot2)
library(dplyr)

# Advanced plot
ggplot(mtcars, aes(x = mpg, y = hp, color = wt)) +
  geom_point(size = 3) +
  scale_color_gradient(low = "blue", high = "red") +
  scale_x_continuous(breaks = seq(10, 35, 5)) +
  coord_cartesian(ylim = c(50, 350)) +
  theme_minimal() +
  labs(title = "Horsepower vs MPG")

27.2 Scales

💡 Key Insight: Scale Functions

# Continuous scales
ggplot(mtcars, aes(x = mpg, y = hp, color = wt)) +
  geom_point() +
  scale_color_gradient(low = "blue", high = "red")

# Discrete scales
ggplot(mtcars, aes(x = factor(cyl), y = mpg, fill = factor(cyl))) +
  geom_boxplot() +
  scale_fill_manual(values = c("4" = "green", "6" = "blue", "8" = "red"))

# Log scales
ggplot(mtcars, aes(x = mpg, y = hp)) +
  geom_point() +
  scale_y_log10()

27.3 Error #1: `Discrete value supplied to continuous scale`

⭐⭐ INTERMEDIATE 🔢 TYPE

27.3.1 The Error

ggplot(mtcars, aes(x = mpg, y = hp, color = cyl)) +
  geom_point() +
  scale_color_gradient(low = "blue", high = "red")

🔴 ERROR

Error: Discrete value supplied to continuous scale

27.3.2 Solutions

✅ SOLUTION: Match Scale to Data Type

# For discrete: use discrete scale
ggplot(mtcars, aes(x = mpg, y = hp, color = factor(cyl))) +
  geom_point() +
  scale_color_manual(values = c("4" = "green", "6" = "blue", "8" = "red"))

# For continuous: ensure numeric
ggplot(mtcars, aes(x = mpg, y = hp, color = wt)) +
  geom_point() +
  scale_color_gradient(low = "blue", high = "red")

27.4 Themes

🎯 Best Practice: Custom Themes

custom_theme <- theme_minimal() +
  theme(
    plot.title = element_text(size = 16, face = "bold"),
    axis.title = element_text(size = 12, face = "bold"),
    legend.position = "right",
    panel.grid.minor = element_blank()
  )

ggplot(mtcars, aes(x = mpg, y = hp, color = factor(cyl))) +
  geom_point(size = 3) +
  custom_theme +
  labs(title = "Custom Themed Plot")

27.5 Annotations

💡 Key Insight: Adding Annotations

ggplot(mtcars, aes(x = mpg, y = hp)) +
  geom_point() +
  annotate("text", x = 30, y = 250, label = "High HP", color = "red") +
  geom_hline(yintercept = mean(mtcars$hp), linetype = "dashed")

27.6 Summary

Key Takeaways:

Match scales to data types
Customize with themes
Add annotations for context
Use appropriate coordinates

Quick Reference:

# Scales
scale_x_continuous()
scale_color_manual()
scale_fill_brewer()

# Themes
theme_minimal()
theme()

# Annotations
annotate()
geom_hline/vline()