首页 > 解决方案 > ggplot 扩展函数在散点图中绘制叠加均值

问题描述

我正在尝试创建一个扩展 ggplot2 的自定义函数。该函数的目标是将平均值与水平和垂直标准误差叠加。下面的代码完成了整个事情。

library(plyr)
library(tidyverse)

summ <- ddply(mtcars,.(),summarise,
              dratSE = sqrt(var(drat))/length(drat),
              mpgSE = sqrt(var(mpg))/length(mpg),
              drat = mean(drat),
              mpg = mean(mpg))

ggplot(data = mtcars, mapping = aes(x = drat, y = mpg)) +
  geom_point(shape = 21, fill = 'black', color = 'white', size = 3) + 
  geom_errorbarh(data = summ, aes(xmin = drat - dratSE, xmax = drat + dratSE)) +
  geom_errorbar(data = summ, aes(ymin = mpg - mpgSE, ymax = mpg+mpgSE), width = .1) +
  geom_point(data = summ, color='red',size=4) 

理想情况下,它只需要一个函数geom_scattermeans()来完成整个事情。但我不确定美学是如何geomggplot().

此外,我在制作一个接收列名作为参数的函数并使其与ddply(). 在此处输入图像描述

标签: rggplot2plyrggproto

解决方案


我认为plyr在这一点上已经不复存在了。我会推荐这个dplyr包。与您一起编程时,dplyr可以使用{{(curly-curly,或文档中所说的 embracing )来正确引用表达式。

library(ggplot2)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

geom_point_error <- function(data, x, y, color = 'red', size = 4) {
  
  data <- dplyr::summarise(
    data,
    x_se = sqrt(var({{x}}))/length({{x}}),
    y_se = sqrt(var({{y}}))/length({{y}}),
    x = mean({{x}}),
    y = mean({{y}})
  )
  
  list(
    geom_errorbarh(data = data,
                   mapping = aes(y = y,
                                 xmin = x - x_se, xmax = x + x_se), inherit.aes = F),
    geom_errorbar(data = data,
                  mapping = aes(x = x,
                                ymin = y - y_se, ymax = y + y_se), width = .1,inherit.aes = F),
    geom_point(data = data,
               mapping = aes(x = x, y = y),
               color = color, size = size)
  )
}

ggplot(data = mtcars, mapping = aes(x = drat, y = mpg)) +
  geom_point(shape = 21, fill = 'black', color = 'white', size = 3) + 
  geom_point_error(mtcars, x = drat, y = mpg)

reprex 包于 2021-05-17 创建(v1.0.0)

第二种选择是构建您自己的ggproto Geom内部来处理这些计算ggplot2,但目前这有点多。


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