Gallery

library(ggswim)
library(ggplot2)
library(dplyr)

Random Data Sets

In this example, we’ll set up some random data for reproducibility by defining dataframes for our lanes and our markers.

set.seed(123)
lane_data <- tibble(
  x = 0,
  xend = sample(5:20, 30, replace = TRUE),
  y = factor(rep(1:15, each = 2)),
  colour = sample(c("red", "blue", "green", "yellow", "purple"), 30, replace = TRUE)
)

set.seed(123)
marker_data <- tibble(
  x = sample(5:20, 30, replace = TRUE),
  y = factor(rep(1:15, each = 2)),
  label = sample(c("A", "B", "C", "D", "E"), 30, replace = TRUE),
  glyph = sample(c("😊", "🎉", "✅", "💥", "✨"), 30, replace = TRUE)
) |>
  mutate(
    glyph = dplyr::case_when(
      label == "A" ~ "😊",
      label == "B" ~ "🎉",
      label == "C" ~ "✅",
      label == "D" ~ "💥",
      label == "E" ~ "✨",
      .default = NA
    )
  )

And then we’ll call those dataframes into their appropriate swim and marker geom functions:

ggplot() +
  geom_swim_lane(
    data = lane_data,
    aes(x = x, xend = xend, y = y, colour = colour),
    linewidth = 3
  ) +
  geom_swim_marker(
    data = marker_data,
    aes(x = x, y = y, marker = label),
    size = 8
  ) +
  scale_colour_brewer(name = "Lanes", palette = "Set1") +
  with(
    marker_data,
    scale_marker_discrete(glyphs = glyph, limits = label, name = "Markers")
  ) +
  labs(
    title = "Sample Swimmer Plot",
    x = "Time", y = "Record ID"
  ) +
  theme_ggswim()

Themeing with ggswim

Here we’ll demonstrate some of the theme functions available with ggswim. These examples will use the same plot setup from the README, starting with the original output:

p

theme_ggswim()

p + theme_ggswim()

theme_ggswim_dark()

p + theme_ggswim_dark()