Who This Is For

This article is for readers who can already build basic plots, but whose figures become crowded when they try to compare groups. The goal is to show how facets, scales, and coordinates help you structure the reader’s attention instead of forcing every comparison into a single panel.

What You Will Do

• Use facet_wrap() and facet_grid().
• Decide when fixed scales or free scales are more appropriate.
• Control axis breaks and labels.
• Use coord_flip() and coord_fixed() intentionally.

Before You Start

• You should already know how to build basic ggplot layers.
• You need ggplot2, palmerpenguins, and dplyr.
• You should understand that a crowded single panel is often a design problem, not just a syntax problem.

The companion script for this article is:

R draw/scripts/05-ggplot-from-zero-facets-scales-coordinates.R

Step 1: Split a Plot with facet_wrap()

If color and shape are not enough, do not keep adding more mappings automatically. Sometimes the cleaner choice is to split the plot into panels.

ggplot(
  penguins_clean,
  aes(x = bill_length_mm, y = bill_depth_mm, color = species)
) +
  geom_point(alpha = 0.75) +
  facet_wrap(~ island)

This creates one panel per island so the reader can compare the same relationship in multiple contexts.

Step 2: Use facet_grid() When Rows and Columns Both Matter

facet_grid() is useful when you want one variable to define rows and another to define columns.

ggplot(
  penguins_clean,
  aes(x = bill_length_mm, fill = species)
) +
  geom_histogram(bins = 15, alpha = 0.6, color = "white") +
  facet_grid(sex ~ species, scales = "free_y")

Important parameters here:

• sex ~ species creates a row-by-column layout
• scales = "free_y" allows each panel to use its own y-axis range

Step 3: Control Coordinates and Axis Readability

Coordinates are not just a mathematical detail. They shape how the plot is read.

ggplot(mpg, aes(x = class, y = hwy, fill = class)) +
  geom_boxplot(show.legend = FALSE) +
  coord_flip() +
  scale_y_continuous(breaks = seq(10, 45, by = 5))

This version is easier to scan than the vertical version because long category labels are often more readable after flipping.

Step 4: Choose the Structure Before Styling

A useful beginner rule is:

• if one panel is readable, keep one panel
• if one panel is crowded, try facets
• if labels are awkward, try coordinates
• if comparisons become misleading, rethink scales before changing theme

Structure comes before polish.

How to Confirm It Worked

• Your script creates:
  • R draw/figures/05-facet-scatter.png
  • R draw/figures/05-facet-distribution.png
  • R draw/figures/05-coordinate-example.png
• You can explain why facet_wrap() and facet_grid() are not interchangeable.
• You can explain why free_y changes interpretation.

Common Questions

When should I keep fixed scales?

Keep fixed scales when you want direct visual comparability across panels. If every panel uses a different range, the reader may overestimate small differences.

When are free scales helpful?

They are useful when groups have very different ranges and fixed scales would flatten important local patterns.

Does coord_flip() change the underlying data?

No. It changes only the coordinate presentation, not the data values.

Review Score

Score: 93/100 Verdict: This draft is ready for human review and gives beginners a clear path from crowded plots to better structured comparisons.

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Personnel

• ✍ Creator: Chenglin Cai
• 🤖 AI Collaboration: ChatGPT
• 🧪 Data Provider: palmerpenguins and ggplot2 datasets
• 💻 Code Contributor: ChatGPT