View source: R/geom_path_interactive.R
geom_path_interactive | R Documentation |
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 passed to base function, plus any of the interactive_parameters. |
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.
girafe()
# 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)
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