How do I create a heatmap in R with ggplot2?

Use geom_tile() from the ggplot2 package. Variables needed: 2 categorical + 1 numerical.

What data types work with a heatmap?

A heatmap works best with categorical, numerical data. It requires 2 categorical + 1 numerical.

RelationshipComparison CategoricalNumerical

Heatmap

ggplot2: geom_tile() · Package: ggplot2 · Variables: 2 categorical + 1 numerical

WHAT IS A HEATMAP?

A heatmap displays values in a matrix grid where each cell is colored according to its value. It reveals patterns across two dimensions simultaneously — like which day of the week and time of day sees the most website traffic, or which variables in a dataset are most correlated. Heatmaps are particularly powerful for correlation matrices, user activity patterns, and any data that can be arranged in a rows-by-columns format. Use a diverging color scale (e.g., blue-white-red) for data with a meaningful center point. In ggplot2, use geom_tile() with scale_fill_gradient2().

BEST FOR

· Correlation matrices
· Two-dimensional patterns
· Time-of-day/day-of-week patterns
· Large numeric tables

AVOID WHEN

· Precise values needed
· Few data points
· Color-blind accessibility concerns

R + GGPLOT2 CODE EXAMPLE

ggplot2

cor_mat <- reshape2::melt(cor(mtcars[, 1:7]))
ggplot(cor_mat, aes(x = Var1, y = Var2, fill = value)) +
  geom_tile() +
  scale_fill_gradient2(low = "blue", mid = "white", high = "#ff6a00") +
  labs(title = "Correlation Matrix")