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 \name{aes_position} \alias{aes_position} \alias{x} \alias{xend} \alias{xmax} \alias{xmin} \alias{y} \alias{yend} \alias{ymax} \alias{ymin} \title{Position related aesthetics: x, y, xmin, xmax, ymin, ymax, xend, yend} \description{ This page demonstrates the usage of a sub-group of aesthetics; x, y, xmin, xmax, ymin, ymax, xend, and yend. } \examples{ # Generate data: means and standard errors of means for prices # for each type of cut dmod <- lm(price ~ cut, data = diamonds) cuts <- data.frame(cut = unique(diamonds\$cut), predict(dmod, data.frame(cut = unique(diamonds\$cut)), se = TRUE)[c("fit", "se.fit")]) se <- ggplot(cuts, aes(x = cut, y = fit, ymin = fit - se.fit, ymax = fit + se.fit, colour = cut)) se + geom_pointrange() # Boxplot with precomputed statistics # generate sample data library(plyr) abc <- adply(matrix(rnorm(100), ncol = 5), 2, quantile, c(0, .25, .5, .75, 1)) b <- ggplot(abc, aes(x = X1, ymin = "0\%", lower = "25\%", middle = "50\%", upper = "75\%", ymax = "100\%")) b + geom_boxplot(stat = "identity") # Using annotate p <- ggplot(mtcars, aes(wt, mpg)) + geom_point() p + annotate("rect", xmin = 2, xmax = 3.5, ymin = 2, ymax = 25, fill = "dark grey", alpha = .5) # Geom_segment examples library(grid) 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") : 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)) qplot(x, Freq, data = counts, geom = "segment", yend = 0, xend = x, size = I(10)) }
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