Combining and arranging multiple plots in a grid

Wrapper around patchwork::wrap_plots() that returns a combined grid of plots with annotations. It is mostly useful with {ggstatsplot} plots and is exported only for backward compatibility; to create a grid of plots, it is highly recommended that you use {patchwork} directly.

Usage

combine_plots(
  plotlist,
  plotgrid.args = list(),
  annotation.args = list(),
  guides = "collect",
  ...
)

Arguments

plotlist

A list containing ggplot objects.

plotgrid.args

A list of additional arguments passed to patchwork::wrap_plots(), except for guides, which has its own argument.

annotation.args

A list of additional arguments passed to patchwork::plot_annotation().

guides

A string specifying how guides should be treated in the layout. 'collect' will collect guides below to the given nesting level, removing duplicates. 'keep' will stop collection at this level and let guides be placed alongside their plot. auto will allow guides to be collected if a upper level tries, but place them alongside the plot if not. If you modify default guide "position" with theme(legend.position=...) while also collecting guides you must apply that change to the overall patchwork (see example).

...

Currently ignored.

Value

A patchwork object: a combined plot with annotation labels.

Examples

library(ggplot2)

p1 <- ggplot(
  data = subset(iris, Species == "setosa"),
  aes(x = Sepal.Length, y = Sepal.Width)
) +
  geom_point() +
  labs(title = "setosa")

p2 <- ggplot(
  data = subset(iris, Species == "versicolor"),
  aes(x = Sepal.Length, y = Sepal.Width)
) +
  geom_point() +
  labs(title = "versicolor")

# combining the plot with a title and a caption
combine_plots(
  plotlist = list(p1, p2),
  plotgrid.args = list(nrow = 1),
  annotation.args = list(
    tag_levels = "a",
    title = "Dataset: Iris Flower dataset",
    subtitle = "Edgar Anderson collected this data",
    caption = "Note: Only two species of flower are displayed",
    theme = theme(
      plot.subtitle = element_text(size = 20),
      plot.title = element_text(size = 30)
    )
  )
)