Aliases: aes_position x y xmin xmax ymin ymax xend yend
Keywords:
### ** Examples # Generate data: means and standard errors of means for prices # for each type of cut dmod <- lm(price ~ cut, data = diamonds) cut <- unique(diamonds$cut) cuts_df <- data.frame( cut, predict(dmod, data.frame(cut), se = TRUE)[c("fit", "se.fit")] ) ggplot(cuts_df) + aes( x = cut, y = fit, ymin = fit - se.fit, ymax = fit + se.fit, colour = cut ) + geom_pointrange()
# Using annotate p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point() p
p + annotate( "rect", xmin = 2, xmax = 3.5, ymin = 2, ymax = 25, fill = "dark grey", alpha = .5 )
# Geom_segment examples p + geom_segment( aes(x = 2, y = 15, xend = 2, yend = 25), arrow = arrow(length = unit(0.5, "cm")) )
p + geom_segment( aes(x = 2, y = 15, xend = 3, yend = 15), arrow = arrow(length = unit(0.5, "cm")) )
p + geom_segment( aes(x = 5, y = 30, xend = 3.5, yend = 25), arrow = arrow(length = unit(0.5, "cm")) )
# You can also use geom_segment() to recreate plot(type = "h") # from base R: counts <- as.data.frame(table(x = rpois(100, 5))) counts$x <- as.numeric(as.character(counts$x)) with(counts, plot(x, Freq, type = "h", lwd = 10))
ggplot(counts, aes(x = x, y = Freq)) + geom_segment(aes(yend = 0, xend = x), size = 10)