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使用ggplot基于x值应用透明背景划分打印区域

tidyverse scatter-plot background ggplot2 r

Krantz · 技术社区 · 6 年前

如果您能将下面的透明背景色应用于根据x值将绘图区域分为两部分,如下图所示(垂直分割)。

以下是我的示例数据和代码:

mtcars$cyl <- as.factor(mtcars$cyl)
ggplot(mtcars, aes(x=wt, y=mpg, color=cyl)) +
  geom_point() + 
  theme(legend.position="none")+
  geom_smooth(method=lm, se=FALSE, fullrange=TRUE)

下面是我想要复制的图,图例说明了我想要实现的更改:

1 回复 | 直到 5 年前

Anonymous coward 6 年前

geom_ribbon ,并设置 ymin 和 ymax 随你的便。

library(tidyverse)
    mtcars$group <- ifelse(mtcars$wt <= 3.5, "<= 3.5", "> 3.5")
mtcars <- arrange(mtcars, wt)
mtcars$group2 <- rleid(mtcars$group)
mtcars_plot <- head(do.call(rbind, by(mtcars, mtcars$group2, rbind, NA)), -1)
mtcars_plot[,c("group2","group")] <- lapply(mtcars_plot[,c("group2","group")], na.locf)
mtcars_plot[] <- lapply(mtcars_plot, na.locf, fromLast = TRUE)

ggplot(mtcars_plot, aes(x = wt, y = mpg)) +
  geom_point() +
  geom_smooth(aes(), method=lm, se=F, fullrange=TRUE) +
  geom_ribbon(aes(ymin = mpg *.75, ymax = mpg * 1.25, fill = group), alpha = .25) +
  labs(fill = "Weight Class")

使用你必须事先用计算机计算它们 lm 和 predict .

mtmodel <- lm(mpg ~ wt, data = mtcars)
mtcars$Low <- predict(mtmodel, newdata = mtcars, interval = "confidence")[,2]
mtcars$High <- predict(mtmodel, newdata = mtcars, interval = "confidence")[,3]

mtcars . 然后用计算出的边界绘制。

ggplot(mtcars_plot, aes(x = wt, y = mpg)) +
  geom_point() +
  geom_smooth(aes(), method=lm, se=F, fullrange=TRUE) +
  geom_ribbon(aes(ymin = Low, ymax = High, fill = group), alpha = .25) +
  labs(fill = "Weight Class") +
  scale_fill_manual(values = c("red", "orange"), name = "fill")