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

geom_path_interactive(...)

geom_line_interactive(...)

geom_step_interactive(...)

Arguments

...

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

Details for geom_*_interactive 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.

See also

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)