在ggplot2中绘制多行[关闭]

2 回答

• 1

  我喜欢使用 summarySE() 定义here作为错误栏，我希望下面会产生你想要的东西 .

  首先是摘要功能：

  summarySE <- function(data=NULL, measurevar, groupvars=NULL, na.rm=FALSE,
                        conf.interval=.95, .drop=TRUE) {
    library(plyr)
  
    # New version of length which can handle NA's: if na.rm==T, don't count them
    length2 <- function (x, na.rm=FALSE) {
      if (na.rm) sum(!is.na(x))
      else       length(x)
    }
  
    # This does the summary. For each group's data frame, return a vector with
    # N, mean, and sd
    datac <- ddply(data, groupvars, .drop=.drop,
                   .fun = function(xx, col) {
                     c(N    = length2(xx[[col]], na.rm=na.rm),
                       mean = mean   (xx[[col]], na.rm=na.rm),
                       sd   = sd     (xx[[col]], na.rm=na.rm)
                     )
                   },
                   measurevar
    )
  
    # Rename the "mean" column    
    datac <- rename(datac, c("mean" = measurevar))
  
    datac$se <- datac$sd / sqrt(datac$N)  # Calculate standard error of the mean
  
    # Confidence interval multiplier for standard error
    # Calculate t-statistic for confidence interval: 
    # e.g., if conf.interval is .95, use .975 (above/below), and use df=N-1
    ciMult <- qt(conf.interval/2 + .5, datac$N-1)
    datac$ci <- datac$se * ciMult
  
    return(datac)
  }
  

  然后插入您的数据 .

  data <- data.frame(Day =c(rep(2,9),rep(5,9),rep(9,9)),Treat = 
  rep(c("A","A","A","B","B","B","C","C","C"),3), Length = 
  c(2,4,3,5,3,3,8,3,7,3,6,7,4,7,8,8,8,8,10,7,5,7,8,9,19,20,12), Width = 
  seq(1,27,1))
  summarized <- summarySE(data, measurevar="Length", groupvars=c("Treat", "Day"))
  summarized
  

  然后是ggplot本身 .

  ggplot(summarized, aes(x=Day, y=Length, colour=Treat)) + 
    geom_errorbar(aes(ymin=Length-se, ymax=Length+se), width=.1) +
    geom_line() +
    geom_point()
  

  回复于 2024-05-17T17:11:01+08:00
• 0

  这是一个更简单的解决方案，有助于防止图形化时的重叠，并且它在错误栏中占据了更标准的95％置信区间：

  require(ggplot2)
  
  df <- data.frame(
    Day = c(rep(2,9),rep(5,9),rep(9,9)),
    Treat = rep(c("A","A","A","B","B","B","C","C","C"),3), 
    Length = c(2,4,3,5,3,3,8,3,7,3,6,7,4,7,8,8,8,8,10,7,5,7,8,9,19,20,12),
    Width = seq(1,27,1))
  
  #Use aggregate function to find mean "Length" based on "Treat" and "Day"
  plotDf <- aggregate(Length ~ Treat + Day, mean, na.rm=TRUE, data=df)
  
  #Create function that uses 95% confidence interval to make SE bars
  #Note: you can adjust CI by removing/replacing '1.96*' as needed.
  find_se <- function(x) 1.96*sd(x,na.rm=TRUE)/sqrt(length(x))
  
  #Use aggregate function to calculate SEs based on "Treat" and "Day"
  plotDf$SE <- setNames(
    aggregate(Length ~ Treat + Day,find_se, data=df)[,"Length"],"SE")
  
  #Plot (uses position_dodge to avoid overlap)
  pd <- position_dodge(.2)
  ggplot(data=plotDf, aes(x=Day,y=Length,colour=Treat)) +
         geom_line(position=pd) +
         geom_point(position=pd) +
         geom_errorbar(aes(ymin=Length-SE, ymax=Length+SE),
                       width=.3, position=pd)
  

  图形输出：

  

  回复于 2024-05-17T17:11:01+08:00