Add a ggplot2 component to a plot

Escape hatch for advanced ggplot2 usage: add_ggplot(p, ggplot2::annotate(...)), add_ggplot(p, ggplot2::guides(...)), add_ggplot(p, ggplot2::labs(...)) etc. modify the underlying ggplot and return the plotit object so the pipeline continues. Prefer the verb API (mark_*, scale_*, label_*, style) for reproducible, well-validated plots.

Usage

add_ggplot(plot, component)

Arguments

plot

A plotit object (or a plotit_composite).

component

Any object ggplot2's + accepts (layer, scale, coord, facet, theme, labs, or a ggplot2 object).

Value

A modified plotit (or plotit_composite) object.

Stability

Extension surface (contract tier: extensible). The signature is stable as documented; it is the supported replacement for the former S3 + operator on plotit objects, which is intentionally not defined so that ggplot2 components are only added through this single explicit entry point.

ggplot2 4.0's ggplot2::stat_manual() slots in here as a custom data-transformation layer without a dedicated plotit verb: add_ggplot(p, ggplot2::stat_manual(fun = function(d) ...)).

Examples

p <- plotit(iris, encode(x = Sepal.Width, y = Sepal.Length)) |>
  mark_point() |>
  add_ggplot(ggplot2::annotate("text", x = 2.5, y = 7.9, label = "high", size = 3))