Advanced Visualizations with ggplot2

ggplot2 is R's most celebrated visualization package, based on the "Grammar of Graphics" — a layered approach where you build charts piece by piece: data, aesthetics, geometries, and themes.

1. The Grammar of Graphics — Core Structure

library(ggplot2)

ggplot(data = df, aes(x = age, y = salary)) +
  geom_point()

Every ggplot2 chart follows this pattern: ggplot(data, aes(...)) + geom_*() — data, aesthetic mappings, and one or more geometry layers, joined with +.

2. Aesthetics (aes) — Mapping Data to Visuals

ggplot(df, aes(x = age, y = salary, color = department, size = experience)) +
  geom_point(alpha = 0.7)

Aesthetics map data columns to visual properties: x/y position, color, size, shape, and transparency (alpha).

3. Common Geometry Layers

ggplot(df, aes(x = department, y = salary)) +
  geom_boxplot(fill = "lightblue") +
  labs(title = "Salary Distribution by Department")

4. Adding Layers

ggplot(df, aes(x = age, y = salary)) +
  geom_point(color = "steelblue") +
  geom_smooth(method = "lm", se = TRUE, color = "red") +
  labs(title = "Age vs Salary with Trend Line",
       x = "Age", y = "Salary ($)")

5. Themes — Controlling the Overall Look

ggplot(df, aes(x = department, fill = department)) +
  geom_bar() +
  theme_minimal() +
  theme(legend.position = "none",
        plot.title = element_text(face = "bold", size = 14)) +
  labs(title = "Employee Count by Department")

6. Faceting — Small Multiples

facet_wrap() and facet_grid() split a single chart into a grid of subplots by category — extremely powerful for comparisons:

ggplot(df, aes(x = age, y = salary)) +
  geom_point() +
  facet_wrap(~ department) +
  labs(title = "Age vs Salary by Department")

7. Saving ggplot2 Charts

ggsave("output/salary_by_dept.png", width = 8, height = 5, dpi = 300)

8. Production-Ready Checklist

• ✅ Understand the layered grammar — data + aes + geoms + theme.
• ✅ Choose the right geom — for the story your data tells.
• ✅ Use facet_wrap() for comparisons — across categories in one figure.
• ✅ Apply a consistent theme — for publication-ready output.