Create interactive reference lines

These geometries are based on geom_abline(), geom_hline() and geom_vline().

Usage

geom_abline_interactive(...)

geom_hline_interactive(...)

geom_vline_interactive(...)

Arguments

...: arguments passed to base function, plus any of the interactive_parameters.

Details for interactive geom functions

The interactive parameters can be supplied with two ways:

As aesthetics with the mapping argument (via aes()). In this way they can be mapped to data columns and apply to a set of geometries.
As plain arguments into the geom_*_interactive function. In this way they can be set to a scalar value.

Examples

# add diagonal interactive reference lines to a ggplot -------
library(ggplot2)
library(ggiraph)

p <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
g <- p + geom_abline_interactive(intercept = 20, tooltip = 20)
x <- girafe(ggobj = g)
if (interactive())
  print(x)

l <- coef(lm(mpg ~ wt, data = mtcars))
g <- p + geom_abline_interactive(
  intercept = l[[1]],
  slope = l[[2]],
  tooltip = paste("intercept:", l[[1]], "\nslope:", l[[2]]),
  data_id="abline"
)
x <- girafe(ggobj = g)
x <- girafe_options(x = x,
                    opts_hover(css = "cursor:pointer;fill:orange;stroke:orange;"))
if (interactive())
  print(x)

# add horizontal interactive reference lines to a ggplot -------
library(ggplot2)
library(ggiraph)

if( requireNamespace("dplyr", quietly = TRUE)){
  g1 <- ggplot(economics, aes(x = date, y = unemploy)) +
    geom_point() + geom_line()

  gg_hline1 <- g1 + geom_hline_interactive(
    aes(yintercept = mean(unemploy),
        tooltip = round(mean(unemploy), 2)), size = 3)
  x <- girafe(ggobj = gg_hline1)
  if( interactive() ) print(x)
}

dataset <- data.frame(
  x = c(1, 2, 5, 6, 8),
  y = c(3, 6, 2, 8, 7),
  vx = c(1, 1.5, 0.8, 0.5, 1.3),
  vy = c(0.2, 1.3, 1.7, 0.8, 1.4),
  year = c(2014, 2015, 2016, 2017, 2018)
)

dataset$clickjs <- rep(paste0("alert(\"", mean(dataset$y), "\")"), 5)


g2 <- ggplot(dataset, aes(x = year, y = y)) +
  geom_point() + geom_line()

gg_hline2 <- g2 + geom_hline_interactive(
  aes(yintercept = mean(y),
      tooltip = round(mean(y), 2),
      data_id = y, onclick = clickjs))

x <- girafe(ggobj = gg_hline2)
if( interactive() ) print(x)

# add vertical interactive reference lines to a ggplot -------
library(ggplot2)
library(ggiraph)

if (requireNamespace("dplyr", quietly = TRUE)) {
  g1 <- ggplot(diamonds, aes(carat)) +
    geom_histogram()

  gg_vline1 <- g1 + geom_vline_interactive(
    aes(xintercept = mean(carat),
        tooltip = round(mean(carat), 2),
        data_id = carat), size = 3)
  x <- girafe(ggobj = gg_vline1)
  if( interactive() ) print(x)
}
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

dataset <- data.frame(x = rnorm(100))

dataset$clickjs <- rep(paste0("alert(\"",
                              round(mean(dataset$x), 2), "\")"), 100)

g2 <- ggplot(dataset, aes(x)) +
  geom_density(fill = "#000000", alpha = 0.7)
gg_vline2 <- g2 + geom_vline_interactive(
  aes(xintercept = mean(x), tooltip = round(mean(x), 2),
      data_id = x, onclick = clickjs), color = "white")

x <- girafe(ggobj = gg_vline2)
x <- girafe_options(x = x,
                    opts_hover(css = "cursor:pointer;fill:orange;stroke:orange;") )
if( interactive() ) print(x)

Usage

Arguments

Details for interactive geom functions

See also

Examples