r - 同一图中的多个分布——使用 ggplot2 中的 geom_density 函数

Question

我想我已经非常接近完成这段代码了，但我在这里遗漏了一些东西。我想像这样将两个图“组合”成一个:

第一个情节有这段代码:

  ggplot(test, aes(y=key,x=value)) + 
  geom_path()+
  coord_flip()

第二个有下面这个:

  ggplot(test, aes(x=value, fill=key)) +
  geom_density() +
  coord_flip()

当我们阅读有关正态分布的统计书籍时，经常会看到这种多重分布图。到目前为止，我得到的最有用的链接是这个 here .

请使用此代码重现我的问题:

library(tidyverse)
test <- data.frame(key = c("communication","gross_motor","fine_motor"),
                   value = rnorm(n=30,mean=0, sd=1))
ggplot(test, aes(x=value, fill=key)) +
  geom_density() +
  coord_flip()

ggplot(test, aes(y=key,x=value)) + 
  geom_path(size=2)+
  coord_flip()

非常感谢

Answer 1

您可能对 ggridges 中的脊线图感兴趣包。

Ridgeline plots are partially overlapping line plots that create the impression of a mountain range. They can be quite useful for visualizing changes in distributions over time or space.

library(tidyverse)
library(ggridges)

set.seed(123)
test <- data.frame(
  key = c("communication", "gross_motor", "fine_motor"),
  value = rnorm(n = 30, mean = 0, sd = 1)
)

ggplot(test, aes(x = value, y = key)) + 
  geom_density_ridges(scale = 0.9) + 
  theme_ridges() +
  NULL
#> Picking joint bandwidth of 0.525

添加中线:

ggplot(test, aes(x = value, y = key)) +
  stat_density_ridges(quantile_lines = TRUE, quantiles = 2, scale = 0.9) +
  coord_flip() +
  theme_ridges() +
  NULL
#> Picking joint bandwidth of 0.525

模拟地毯:

ggplot(test, aes(x = value, y = key)) + 
  geom_density_ridges(
    jittered_points = TRUE,
    position = position_points_jitter(width = 0.05, height = 0),
    point_shape = '|', point_size = 3, point_alpha = 1, alpha = 0.7,
  ) +
  theme_ridges() +
  NULL
#> Picking joint bandwidth of 0.525

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