Create interactive observations connections

These geometries are based on geom_path(), geom_line() and geom_step(). See the documentation for those functions for more details.

Usage

geom_path_interactive(...)

geom_line_interactive(...)

geom_step_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 interactive paths to a ggplot -------
library(ggplot2)
library(ggiraph)

# geom_line_interactive example -----
if( requireNamespace("dplyr", quietly = TRUE)){
  gg <- ggplot(economics_long,
    aes(date, value01, colour = variable, tooltip = variable, data_id = variable,
        hover_css = "fill:none;")) +
    geom_line_interactive(size = .75)
  x <- girafe(ggobj = gg)
  x <- girafe_options(x = x,
                      opts_hover(css = "stroke:red;fill:orange") )
  if( interactive() ) print(x)

}

# geom_step_interactive example -----
if( requireNamespace("dplyr", quietly = TRUE)){
  recent <- economics[economics$date > as.Date("2013-01-01"), ]
  gg = ggplot(recent, aes(date, unemploy)) +
    geom_step_interactive(aes(tooltip = "Unemployement stairstep line", data_id = 1))
  x <- girafe(ggobj = gg)
  x <- girafe_options(x = x,
                      opts_hover(css = "stroke:red;") )
  if( interactive() ) print(x)
}

# create datasets -----
id = paste0("id", 1:10)
data = expand.grid(list(
  variable = c("2000", "2005", "2010", "2015"),
  id = id
  )
)
groups = sample(LETTERS[1:3], size = length(id), replace = TRUE)
data$group = groups[match(data$id, id)]
data$value = runif(n = nrow(data))
data$tooltip = paste0('line ', data$id )
data$onclick = paste0("alert(\"", data$id, "\")" )

cols = c("orange", "orange1", "orange2", "navajowhite4", "navy")
dataset2 <- data.frame(x = rep(1:20, 5),
    y = rnorm(100, 5, .2) + rep(1:5, each=20),
    z = rep(1:20, 5),
    grp = factor(rep(1:5, each=20)),
    color = factor(rep(1:5, each=20)),
    label = rep(paste0( "id ", 1:5 ), each=20),
    onclick = paste0(
      "alert(\"",
      sample(letters, 100, replace = TRUE),
      "\")" )
)


# plots ---
gg_path_1 = ggplot(data, aes(variable, value, group = id,
    colour = group, tooltip = tooltip, onclick = onclick, data_id = id)) +
  geom_path_interactive(alpha = 0.5)

gg_path_2 = ggplot(data, aes(variable, value, group = id, data_id = id,
    tooltip = tooltip)) +
  geom_path_interactive(alpha = 0.5) +
  facet_wrap( ~ group )

gg_path_3 = ggplot(dataset2) +
  geom_path_interactive(aes(x, y, group=grp, data_id = label,
    color = color, tooltip = label, onclick = onclick), size = 1 )

# ggiraph widgets ---
x <- girafe(ggobj = gg_path_1)
x <- girafe_options(x = x,
                    opts_hover(css = "stroke-width:3px;") )
if( interactive() ) print(x)

x <- girafe(ggobj = gg_path_2)
x <- girafe_options(x = x,
                    opts_hover(css = "stroke:orange;stroke-width:3px;") )
if( interactive() ) print(x)

x <- girafe(ggobj = gg_path_3)
x <- girafe_options(x = x,
                    opts_hover(css = "stroke-width:10px;") )
if( interactive() ) print(x)

m <- ggplot(economics, aes(unemploy/pop, psavert))
p <- m + geom_path_interactive(aes(colour = as.numeric(date), tooltip=date))
x <- girafe(ggobj = p)
if( interactive() ) print(x)

Usage

Arguments

Details for interactive geom functions

See also

Examples