Code accompanying blog post at https://blog.stephenturner.us/p/plot-titles

plot-titles.R

# https://blog.stephenturner.us/p/plot-titles

library(dplyr)
library(ggplot2)

ggplot(diamonds, aes(x = carat)) +
  geom_histogram(binwidth = 0.1) +
  labs(
    title = "Most diamonds are under 1 carat; larger stones are rare",
    subtitle = "Histogram of ~54k diamonds in ggplot2::diamonds (binwidth = 0.1)",
    x = "Carat",
    y = "Count"
  ) +
  theme_minimal()

ggplot(diamonds, aes(x = carat, y = price)) +
  geom_point(alpha = 0.08) +
  scale_y_continuous(labels = scales::dollar) +
  labs(
    title = "Carat strongly predicts price, but the spread is huge at any given size",
    subtitle = "Same carat, very different prices: quality and other attributes dominate within-size variation",
    x = "Carat",
    y = "Price (USD)"
  ) +
  theme_minimal()

ggplot(penguins, aes(x = flipper_len, y = bill_len, color = species)) +
  geom_point(alpha = 0.8, na.rm = TRUE) +
  labs(
    title = "Species are mostly separable with two simple measurements",
    subtitle = "Adelie, Chinstrap, and Gentoo form distinct clusters (some overlap remains)",
    x = "Flipper length (mm)",
    y = "Bill length (mm)",
    color = "Species"
  ) +
  theme_minimal()

dplyr::starwars |>
  filter(!is.na(height), !is.na(mass), mass < 500) |> 
  ggplot(aes(x = height, y = mass)) +
  geom_point(alpha = 0.7) +
  geom_smooth(se = FALSE) +
  labs(
    title = "Taller characters tend to be heavier, but the outliers are the story",
    subtitle = "Filtered to mass < 500 for readability; trend line summarizes the overall pattern",
    x = "Height (cm)",
    y = "Mass (kg)"
  ) +
  theme_minimal()