ggiraph (version 0.9.0)

geom_rect_interactive: Create interactive rectangles

Description

These geometries are based on ggplot2::geom_rect() and ggplot2::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 interactive geom functions

The interactive parameters can be supplied with two ways:

• As aesthetics with the mapping argument (via ggplot2::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

girafe()

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,
    linejoin = "bevel",
    lineend = "round"
  ) +
  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("`%s` vs `%s`:%.03f", 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)
}