不幸的是，我在R语言中不是很有经验，但我需要解决一个问题，这对我来说似乎很难，但如果一个人知道如何在R语言中使用箱线图，可能很容易。
我需要在分组箱线图中添加额外的水平线或点，用于第10和第90百分位数**。除此之外，箱线图应包含常见的特征，如最小值，最大值，通常的第25百分位数，中位数和第75百分位数以及离群值。
我尝试了几个解决方案，但都不适合我的情况。一个有希望的尝试是类似于下面的解决方案，写一个函数-但我需要的是中位数而不是平均值，除此之外，我还需要显示第10和第90百分位数。此外，按变量 Col 对框进行分组很重要（参见下面的示例代码）：
如果你能给予我一些解决这个问题的方法，我将不胜感激！

dataset_stack <- structure(list(Col = c("Blue", "Blue", "Blue", "Blue", "Blue", 
                       "Blue", "Blue", "Blue", "Blue", "Blue", "Blue", "Blue", "Blue", 
                       "Green", "Green", "Green", "Green", "Green", "Green", "Green", 
                       "Green", "Green", "Green", "Green", "Green", "Green", "Green", 
                       "Green", "Red", "Red", "Red", "Red", "Red", "Red", "Red", "Red", 
                       "Red", "Red", "Red", "Red", "Red", "Red", "Red"), TTC = c(0.9, 
                                                                                 0.7, 0, 0.1, 0.1, 0.4, 0.9, 0.8, 0.1, 0, 0.7, 0.2, 0.7, 0.2, 
                                                                                 0, 0.8, 0.7, 0.8, 0.9, 0.3, 0.9, 0.8, 0.3, 1, 0.6, 0.4, 0.3, 
                                                                                 0.3, 0.3, 0.2, 0.2, 0.7, 0.9, 0.9, 0.6, 0.4, 0.1, 0.4, 0.8, 0, 
                                                                                 0.7, 0.4, 0.7)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
                                                                                                                                                          -43L))

bp.vals <- function(x, probs=c(0.1, 0.25, 0.75, .9)) {
    r <- quantile(x, probs=probs , na.rm=TRUE)
    r = c(r[1:2], exp(mean(log(x))), r[3:4])
    names(r) <- c("ymin", "lower", "middle", "upper", "ymax")
    r
  }

  # Sample usage of the function with the built-in mtcars data frame
  ggplot(dataset_stack, aes(x=factor(Col), y=TTC)) +
    stat_summary(fun.data=bp.vals, geom="boxplot")