如何在分組密度圖的頂部添加中值？

如果之前有人問過這個問題，我深表歉意。我正在嘗試將中值添加到grouped密度圖的峰值（下面的示例）。

library(dplyr)
library(forcats)

Catalan_elections %>%
  mutate(YearFct = fct_rev(as.factor(Year))) %>%
  ggplot(aes(y = YearFct))  
  geom_density_ridges(
    aes(x = Percent, fill = paste(YearFct, Option)), 
    alpha = .8, color = "white", from = 0, to = 100
  )  
  labs(
    x = "Vote (%)",
    y = "Election Year",
    title = "Indy vs Unionist vote in Catalan elections",
    subtitle = "Analysis unit: municipalities (n = 949)",
    caption = "Marc Belzunces (@marcbeldata) | Source: Idescat"
  )  
  scale_y_discrete(expand = c(0, 0))  
  scale_x_continuous(expand = c(0, 0))  
  scale_fill_cyclical(
    breaks = c("1980 Indy", "1980 Unionist"),
    labels = c(`1980 Indy` = "Indy", `1980 Unionist` = "Unionist"),
    values = c("#ff0000", "#0000ff", "#ff8080", "#8080ff"),
    name = "Option", guide = "legend"
  )  
  coord_cartesian(clip = "off")  
  theme_ridges(grid = FALSE)

uj5u.com熱心網友回復：

編輯：

感謝您更新您的問題；我誤解并認為您想突出顯示中位數（直截了當），但聽起來您實際上想要峰值（更復雜）。我還認為這是您的代碼，而不是來自https://cran.r-project.org/web/packages/ggridges/vignettes/gallery.html的示例，所以我沒有意識到 Catalan_elections 資料集是公開可用的（例如來自 ggjoy 包）。

這是一個更相關的解決方案：

library(tidyverse)
library(palmerpenguins)
library(ggridges)
#install.packages("ggjoy")
library(ggjoy)

Catalan_elections_with_max_density <- Catalan_elections %>%
  group_by(Year, Option) %>%
  na.omit() %>%
  mutate(max_density = max(density(Percent, na.rm = TRUE)$y),
         which_max_density = which.max(density(Percent, na.rm = TRUE)$y)) %>%
  mutate(which_max_x_intercept = density(Percent, na.rm = TRUE)$x[which_max_density])

Catalan_elections_with_max_density %>%
  mutate(YearFct = fct_rev(as.factor(Year))) %>%
  ggplot(aes(y = YearFct))  
  geom_density_ridges(
    aes(x = Percent, fill = paste(YearFct, Option)), 
    alpha = .8, color = "white", from = 0, to = 100,
  )  
  geom_segment(aes(x = which_max_x_intercept,
                   xend = which_max_x_intercept,
                   y = as.numeric(YearFct),
                   yend = as.numeric(YearFct)   max_density * 48),
               color = "white", size = 0.75, alpha = 0.1)  
  labs(
    x = "Vote (%)",
    y = "Election Year",
    title = "Indy vs Unionist vote in Catalan elections",
    subtitle = "Analysis unit: municipalities (n = 949)",
    caption = "Marc Belzunces (@marcbeldata) | Source: Idescat"
  )  
  scale_y_discrete(expand = c(0, 0))  
  scale_x_continuous(expand = c(0, 0))  
  scale_fill_cyclical(
    breaks = c("1980 Indy", "1980 Unionist"),
    labels = c(`1980 Indy` = "Indy", `1980 Unionist` = "Unionist"),
    values = c("#ff0000", "#0000ff", "#ff8080", "#8080ff"),
    name = "Option", guide = "legend"
  )  
  coord_cartesian(clip = "off")  
  theme_ridges(grid = FALSE)
#> Picking joint bandwidth of 3.16

^{由reprex 包(v2.0.1)于 2021 年 12 月 14 日創建}

注意。我不太明白 geom_density_ridges() 中的縮放是如何作業的，所以我使用“max_density * a constant”來使其大致正確。根據您的用例，您需要調整常數或計算峰值密度與繪圖的 y 坐標之間的關系。

原答案：

我沒有你的資料集“Catalan_elections”，所以這里有一個使用palmerpenguins 資料集的例子：

library(tidyverse)
library(palmerpenguins)
library(ggridges)

penguins %>%
  na.omit() %>%
  mutate(YearFct = fct_rev(as.factor(year))) %>%
  ggplot(aes(x = bill_length_mm, y = YearFct, fill = YearFct))  
  geom_density_ridges(
    alpha = .8, color = "white", from = 0, to = 100,
    quantile_lines = TRUE, quantiles = 2
  )  
  labs(
    x = "Vote (%)",
    y = "Election Year",
    title = "Indy vs Unionist vote in Catalan elections",
    subtitle = "Analysis unit: municipalities (n = 949)",
    caption = "Marc Belzunces (@marcbeldata) | Source: Idescat"
  )  
  scale_y_discrete(expand = c(0, 0))  
  scale_x_continuous(expand = c(0, 0))  
  scale_fill_cyclical(
    breaks = c("1980 Indy", "1980 Unionist"),
    labels = c(`1980 Indy` = "Indy", `1980 Unionist` = "Unionist"),
    values = c("#ff0000", "#0000ff", "#ff8080", "#8080ff"),
    name = "Option", guide = "legend"
  )  
  coord_cartesian(clip = "off")  
  theme_ridges(grid = FALSE)
#> Picking joint bandwidth of 1.92

^{由reprex 包(v2.0.1)于 2021 年 12 月 13 日創建}

標籤：r ggplot2 密度图

上一篇：迭代子集資料幀并使用R應用于繪圖函式

下一篇：關閉時在圖例中錯誤地渲染圖例中的有條件地著色段