我制作了一个循环，每个变量输出1个固定变量（控制与PAD）的2个图形。使用plot_grid函数，我做了2行（标题为1行），虽然不是很直观，但是行得通（如图所示），但是现在我想为两个组添加代表均值和SD的值（最好是在图例）我为均值和标准差做了一个向量，但是在将它们添加到最终绘图中时我有点迷失了。也许还有一种更简便的方法。

我在下面做了一个示例代码。我还附上一张描述我喜欢它的图片。

创建数据框

rm(list=ls())
library(ggplot2)
library(purrr)
library(ggbeeswarm)
library(cowplot)
library(plotly)
library(dplyr)
library(tidyr)
library(plyr)

group <- c("Control","PAD","Control","PAD")
b <- round(runif(15,1,7)) 
c <- round(runif(15,3)) 
d <- round(runif(15,3,8)) 
e <- round(runif(15,5))
event <- c("no event","event","no event","event")

df <- data.frame(group,b,c,d,e,event)
df

rm(group,event)

将颜色定义为箱线图使用的组

df$color <- "color"
for (i in 1:dim(df)[1]){
  if (df$group[i]=="Control") {
    df$color[i] <- "Control" # in de column PAD,if the control is control give the color the string "control"
  }
}
for (i in 1:dim(df)[1]){
  if (df$group[i] == "PAD" && df$event[i] == "event") {
    df$color[i] <- "PAD with event" # in de column PAD,if the PAD has event give the color the string "event"
  }
}
for (i in 1:dim(df)[1]){
  if (df$group[i] == "PAD" && df$event[i] == "no event") {
    df$color[i] <- "PAD without event"
  }
}
rm(i)

用于循环浏览列

expl = names(df[1]) 
response = names(df[2:5]) 

response = set_names(response)
response

expl = set_names(expl)
expl

图2中使用的子集PAD和控件获取平均值和sd

PADonly <- subset(df,group == "PAD" )
Ctrlonly <- subset(df,group == "Control" )

explPAD = names(df[7]) #the explanatory value is event vs no event)
response = names(DBPAD[2:5])

运行循环

pdf("all_plots.pdf",width = 15)
 xPAD <- PADonly[,i]


xPADmean <- mean(xPAD,na.rm=TRUE)  
  xPADSD <- sd(xPAD,na.rm = TRUE)

  xctrl <- Ctrlonly[,i]
  xctrlmean <- mean(xctrl,na.rm=TRUE)  
  xctrlSD <- sd(xctrl,na.rm = TRUE)

  p1 <- ggplot(df,aes_string("group",i)) + 
    geom_boxplot(show.legend = F) + 
    geom_beeswarm(aes(color = color),size=2) +
    scale_color_manual(values= c("Control"="#107f40","PAD with event" = "#D85622","PAD without event"="#2D416D")) # color the values as as you please



  p2 <- ggplot(df,aes_string(x= i,fill="group")) + 
    geom_histogram(bins=15,aes(y=..density..),position = "identity",alpha=0.15,color="black") +
    scale_fill_manual(values= c("PAD"="#2D416D","Control" = "#D85622")) + # color the values as as you please
    scale_y_continuous(labels = scales::percent) +
    stat_density(aes_string(i,color="group"),na.rm=TRUE,bw = "nrd0",geom = "line",size=1,linetype=2) +
    geom_rug(aes_string(x=i,color="group")) +
    scale_color_manual(values= c("PAD"="#2D416D","Control" = "#D85622"))+
    geom_vline(xintercept=xPADmean,linetype=2,color="#2D416D")+
    geom_vline(xintercept=xctrlmean,color="#D85622")

  p_all <- plot_grid(p1,p2)


  # create a title vector for i
  title <- ggdraw() +
    draw_label(i,fontface = "bold",x = 0,hjust = 0,size = 25) +
    theme(
      # add margin on the left of the drawing canvas
      plot.margin = margin(0,7,))


  p_all <- plot_grid(title,p_all,ncol=1,rel_heights = c(0.1,1))
  print(p_all)
}