使用ggplot2的多个数据帧的geom_point和geom_errorbar

2 回答

• 1

  用 inherit.aes 你也不能吃蛋糕，你要么继承所有东西，要么指定一切 .

  在您的情况下，您的新数据具有 ymin 和 ymax 的不同列名，因此我们确实需要在新的 geom_errorbar 层中设置 inherit.aes = F ，但是我们需要指定所有的美学 .

  如果原始图中的 ymin 和 ymax 仅设置在 geom_errorbar 级别而不是顶级，我们可以省去一点麻烦：

  mGts <-
      ggplot(
          data = mean_TS_Cond_use,
          aes(
              x = week_DOY,
              y = week_mean_Cond,
              color = Leaf.age.ordered
          )
      ) +
      geom_point(size = 4) +
      geom_errorbar(
          # move these down here
          aes(ymax = week_mean_Cond + week_sd_Cond,
              ymin = week_mean_Cond - week_sd_Cond)
      )
  

  通过该更改，新的 geom_point 图层很好，但我们将设置 inherit.aes = F 并为 geom_errorbar 重新指定美学：

  mGts_situ <- mGts +
      geom_point(
          mapping = aes(
              x = week_DOY,
              y = week_mean_GS,
              color = Leaf.age.ordered
          ),
          data = mean_TS_Gs_use,
          size = 4,
          shape = 18
      ) +
      geom_errorbar(
          mapping = aes(
              ymax = week_mean_GS + week_sd_GS,
              ymin = week_mean_GS - week_sd_GS,
              x = week_DOY,
              color = Leaf.age.ordered
          ),
          data = mean_TS_Gs_use,
          inherit.aes = FALSE
      )
  mGts_situ
  

  回复于 2024-04-28T13:31:55+08:00
• 2

  我认为如果我们合并两个数据框，这个图将更容易创建：

  library(dplyr)
  library(ggplot2)
  

  重命名列，以便我们在两个数据框中具有通用名称 . 添加新列以区分源数据来自哪个数据帧 . 然后组合两个数据框：

  mean_TS_Cond_use = mean_TS_Cond_use %>% 
    rename(week_mean=week_mean_Cond, week_sd=week_sd_Cond) %>%
    mutate(Source="Cond")
  
  mean_TS_Gs_use = mean_TS_Gs_use %>% 
    rename(week_mean=week_mean_GS, week_sd=week_sd_GS) %>%
    mutate(Source="Gs")
  
  df = bind_rows(list(mean_TS_Cond_use, mean_TS_Gs_use))
  

  重置 Leaf.age.ordered 的订单：

  df$Leaf.age.ordered = factor(df$Leaf.age.ordered, levels=c("young","mature","old","old1"))
  

  将 week_DOY 转换为因子（因此躲避将正常工作）：

  df$week_DOY_f = factor(df$week_DOY, levels=min(df$week_DOY):max(df$week_DOY))
  

  躲避以避免重叠 . group 审美是为了得到正确的躲闪：

  pd = position_dodge(0.5)
  
  ggplot(df, aes(x=week_DOY_f, 
                 y=week_mean, colour=Source, fill=Source,
                 ymax=week_mean + week_sd, ymin=week_mean - week_sd)) +
    geom_errorbar(position=pd, aes(group=interaction(Leaf.age.ordered, Source)), 
                  width=0.1, alpha=0.5) +
    geom_point(position=pd, aes(group=interaction(Leaf.age.ordered, Source),
                                size=Leaf.age.ordered), 
               pch=21, color="black", stroke=0.2) +
    theme_bw() +
    scale_size_discrete(range=c(1,3)) +
    guides(size=guide_legend(override.aes=list(fill="grey30")))
  

  情节仍然非常繁忙，但希望更容易阅读：

  

  或者也许文字标签可以更好地区分年龄：

  ggplot(df, aes(x=week_DOY_f, 
                 y=week_mean, colour=Source,
                 ymax=week_mean + week_sd, ymin=week_mean - week_sd)) +
    geom_errorbar(position=pd, aes(group=interaction(Leaf.age.ordered, Source)), 
                                   width=0.1, alpha=0.5) +
    geom_label(position=pd, aes(label=toupper(substr(Leaf.age.ordered,1,1)), 
                                group=interaction(Leaf.age.ordered, Source)), 
               fontface="bold", fill="white", label.size=0, size=2.5,
               label.padding=unit(0.05,"lines"), show.legend=FALSE) +
    theme_bw() +
    guides(colour=guide_legend(override.aes=list(alpha=1,lwd=1)))
  

  

  回复于 2024-04-28T13:31:55+08:00