ggplot2 Heatmap Exercises in R: 20 Practice Problems
Twenty practice problems on heatmaps in ggplot2: geom_tile, geom_raster, color scales, reordering, labels, correlation matrices.
RRun this once before any exercise
library(ggplot2)
library(dplyr)
library(tidyr)
library(tibble)
Exercise 1: Basic geom_tile
Difficulty: Beginner.
Show solution
RInteractive R
df <- expand.grid(x = 1:5, y = 1:5)
df$z <- runif(25)
ggplot(df, aes(x, y, fill = z)) + geom_tile()
Exercise 2: geom_raster (faster)
Difficulty: Intermediate.
Show solution
RInteractive R
df <- expand.grid(x = 1:50, y = 1:50)
df$z <- runif(nrow(df))
ggplot(df, aes(x, y, fill = z)) + geom_raster()
Exercise 3: Two-color gradient
Difficulty: Intermediate.
Show solution
RInteractive R
df <- expand.grid(x = 1:5, y = 1:5); df$z <- runif(25)
ggplot(df, aes(x, y, fill = z)) + geom_tile() +
scale_fill_gradient(low = "white", high = "red")
Exercise 4: Diverging gradient
Difficulty: Intermediate.
Show solution
RInteractive R
df <- expand.grid(x = 1:5, y = 1:5); df$z <- df$x - df$y
ggplot(df, aes(x, y, fill = z)) + geom_tile() +
scale_fill_gradient2(low = "blue", mid = "white", high = "red", midpoint = 0)
Exercise 5: Viridis fill
Difficulty: Intermediate.
Show solution
RInteractive R
df <- expand.grid(x = 1:5, y = 1:5); df$z <- runif(25)
ggplot(df, aes(x, y, fill = z)) + geom_tile() + scale_fill_viridis_c()
Exercise 6: Correlation matrix heatmap
Difficulty: Advanced.
Show solution
RInteractive R
cor_mat <- cor(mtcars)
cor_df <- as.data.frame(cor_mat) |>
tibble::rownames_to_column("v1") |>
pivot_longer(-v1, names_to = "v2", values_to = "cor")
ggplot(cor_df, aes(v1, v2, fill = cor)) + geom_tile() +
scale_fill_gradient2(low = "blue", mid = "white", high = "red", midpoint = 0)
Exercise 7: Add cell value labels
Difficulty: Intermediate.
Show solution
RInteractive R
df <- expand.grid(x = 1:3, y = 1:3); df$z <- 1:9
ggplot(df, aes(x, y, fill = z)) + geom_tile() +
geom_text(aes(label = z), color = "white")
Exercise 8: Reverse y axis
Difficulty: Intermediate.
Show solution
RInteractive R
df <- expand.grid(x = 1:5, y = 1:5); df$z <- runif(25)
ggplot(df, aes(x, y, fill = z)) + geom_tile() + scale_y_reverse()
Exercise 9: Square aspect ratio
Difficulty: Intermediate.
Show solution
RInteractive R
df <- expand.grid(x = 1:5, y = 1:5); df$z <- runif(25)
ggplot(df, aes(x, y, fill = z)) + geom_tile() + coord_equal()
Exercise 10: Order rows/cols by hierarchical clustering
Difficulty: Advanced.
Show solution
RInteractive R
m <- cor(mtcars)
order <- hclust(dist(m))$order
m_ord <- m[order, order]
m_long <- as.data.frame(m_ord) |>
tibble::rownames_to_column("v1") |>
pivot_longer(-v1, names_to = "v2", values_to = "cor") |>
mutate(v1 = factor(v1, levels = rownames(m_ord)),
v2 = factor(v2, levels = colnames(m_ord)))
ggplot(m_long, aes(v1, v2, fill = cor)) + geom_tile() +
scale_fill_gradient2(low = "blue", mid = "white", high = "red")
Exercise 11: Tile with white grid
Difficulty: Intermediate.
Show solution
RInteractive R
df <- expand.grid(x = 1:5, y = 1:5); df$z <- runif(25)
ggplot(df, aes(x, y, fill = z)) + geom_tile(color = "white", linewidth = 1)
Exercise 12: Tile from a count table
Difficulty: Advanced.
Show solution
RInteractive R
diamonds |>
count(cut, color) |>
ggplot(aes(cut, color, fill = n)) + geom_tile() +
scale_fill_viridis_c()
Exercise 13: Mask diagonal
Difficulty: Advanced.
Show solution
RInteractive R
m <- cor(mtcars[, 1:5])
m[lower.tri(m, diag = FALSE)] <- NA
df <- as.data.frame(m) |>
tibble::rownames_to_column("v1") |>
pivot_longer(-v1, names_to = "v2", values_to = "cor") |>
na.omit()
ggplot(df, aes(v1, v2, fill = cor)) + geom_tile() +
scale_fill_gradient2(low = "blue", high = "red")
Exercise 14: Limit color range
Difficulty: Advanced.
Show solution
RInteractive R
df <- expand.grid(x = 1:5, y = 1:5); df$z <- runif(25)
ggplot(df, aes(x, y, fill = z)) + geom_tile() +
scale_fill_gradient(low = "white", high = "red", limits = c(0, 1))
Exercise 15: Annotate cells with formatted numbers
Difficulty: Advanced.
Show solution
RInteractive R
m <- cor(mtcars[, 1:5])
df <- as.data.frame(m) |>
tibble::rownames_to_column("v1") |>
pivot_longer(-v1, names_to = "v2", values_to = "cor")
ggplot(df, aes(v1, v2, fill = cor)) + geom_tile() +
geom_text(aes(label = sprintf("%.2f", cor)), color = "black", size = 3) +
scale_fill_gradient2(low = "blue", high = "red")
Exercise 16: Faceted heatmap
Difficulty: Advanced.
Show solution
RInteractive R
df <- expand.grid(x = 1:3, y = 1:3, group = c("A","B"))
df$z <- runif(nrow(df))
ggplot(df, aes(x, y, fill = z)) + geom_tile() + facet_wrap(~ group)
Exercise 17: Time-vs-day calendar heatmap
Difficulty: Advanced.
Show solution
RInteractive R
df <- expand.grid(day = 1:7, hour = 0:23)
df$count <- sample(0:50, nrow(df), replace = TRUE)
ggplot(df, aes(hour, day, fill = count)) + geom_tile() +
scale_fill_viridis_c() +
scale_y_reverse()
Exercise 18: Theme cleanup
Difficulty: Advanced.
Show solution
RInteractive R
df <- expand.grid(x = 1:5, y = 1:5); df$z <- runif(25)
ggplot(df, aes(x, y, fill = z)) + geom_tile() +
theme_minimal() + theme(panel.grid = element_blank())
Exercise 19: Combine with text and color
Difficulty: Advanced.
Show solution
RInteractive R
df <- data.frame(team = rep(c("A","B","C"), each = 3),
metric = rep(c("M1","M2","M3"), 3),
val = round(runif(9), 2))
ggplot(df, aes(metric, team, fill = val)) + geom_tile(color = "white") +
geom_text(aes(label = val), color = "black") +
scale_fill_viridis_c() + theme_minimal()
Exercise 20: Custom legend position
Difficulty: Intermediate.
Show solution
RInteractive R
df <- expand.grid(x = 1:5, y = 1:5); df$z <- runif(25)
ggplot(df, aes(x, y, fill = z)) + geom_tile() +
theme(legend.position = "top")
What to do next
- ggplot2-Exercises (shipped), broader practice.
- ggplot2-Color-Scales-Exercises (shipped), palette focus.