ggiraph: geom_rect_interactive – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

geom_rect_interactive

Create interactive rectangles

Description

These geometries are based on geom_rect() and geom_tile(). See the documentation for those functions for more details.

Usage

geom_rect_interactive(...)

geom_tile_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.

Note

Converting a raster to svg elements could inflate dramatically the size of the svg and make it unreadable in a browser. Function geom_tile_interactive should be used with caution, total number of rectangles should be small.

Examples

# add interactive polygons to a ggplot -------
library(ggplot2)
library(ggiraph)

dataset = data.frame( x1 = c(1, 3, 1, 5, 4),
	x2 = c(2, 4, 3, 6, 6),
	y1 = c( 1, 1, 4, 1, 3),
	y2 = c( 2, 2, 5, 3, 5),
	t = c( 'a', 'a', 'a', 'b', 'b'),
	r = c( 1, 2, 3, 4, 5),
	tooltip = c("ID 1", "ID 2", "ID 3", "ID 4", "ID 5"),
	uid = c("ID 1", "ID 2", "ID 3", "ID 4", "ID 5"),
	oc = rep("alert(this.getAttribute(\"data-id\"))", 5)
)

gg_rect = ggplot() +
	scale_x_continuous(name="x") +
	scale_y_continuous(name="y") +
	geom_rect_interactive(data=dataset,
		mapping = aes(xmin = x1, xmax = x2,
			ymin = y1, ymax = y2, fill = t,
			tooltip = tooltip, onclick = oc, data_id = uid ),
		color="black", alpha=0.5) +
	geom_text(data=dataset,
			aes(x = x1 + ( x2 - x1 ) / 2, y = y1 + ( y2 - y1 ) / 2,
					label = r ),
		size = 4 )

x <- girafe(ggobj = gg_rect)
if( interactive() ) print(x)
# add interactive tiles to a ggplot -------
library(ggplot2)
library(ggiraph)

df <- data.frame(
  id = rep(c("a", "b", "c", "d", "e"), 2),
  x = rep(c(2, 5, 7, 9, 12), 2),
  y = rep(c(1, 2), each = 5),
  z = factor(rep(1:5, each = 2)),
  w = rep(diff(c(0, 4, 6, 8, 10, 14)), 2)
)

p <- ggplot(df, aes(x, y, tooltip = id)) + geom_tile_interactive(aes(fill = z))
x <- girafe(ggobj = p)
if( interactive() ) print(x)


# correlation dataset ----
cor_mat <- cor(mtcars)
diag( cor_mat ) <- NA
var1 <- rep( row.names(cor_mat), ncol(cor_mat) )
var2 <- rep( colnames(cor_mat), each = nrow(cor_mat) )
cor <- as.numeric(cor_mat)
cor_mat <- data.frame( var1 = var1, var2 = var2,
  cor = cor, stringsAsFactors = FALSE )
cor_mat[["tooltip"]] <-
  sprintf("<i>`%s`</i> vs <i>`%s`</i>:</br><code>%.03f</code>",
  var1, var2, cor)

p <- ggplot(data = cor_mat, aes(x = var1, y = var2) ) +
  geom_tile_interactive(aes(fill = cor, tooltip = tooltip), colour = "white") +
  scale_fill_gradient2_interactive(low = "#BC120A", mid = "white", high = "#BC120A",
                                   limits = c(-1, 1), data_id = "cormat", tooltip = "cormat") +
  coord_equal()
x <- girafe(ggobj = p)
if( interactive() ) print(x)

ggiraph

Make 'ggplot2' Graphics Interactive

v0.7.10

GPL-3

Authors

David Gohel [aut, cre], Panagiotis Skintzos [aut], Mike Bostock [cph] (d3.js), Speros Kokenes [cph] (d3-lasso), Eric Shull [cph] (saveSvgAsPng js library), Eric Book [ctb] (hline and vline geoms)

Initial release