用geom_bar和stat ="identity"在平均值上绘制hline. [英] Plot hline at mean with geom_bar and stat="identity"

问题描述

我有一个条形图，其中确切的条形高度在数据框中.

I have a barplot where the exact bar heights are in the dataframe.

df <- data.frame(x=LETTERS[1:6], y=c(1:6, 1:6 + 1), g=rep(x = c("a", "b"), each=6))

ggplot(df, aes(x=x, y=y, fill=g, group=g)) + 
  geom_bar(stat="identity", position="dodge")

现在，我想添加两个线，以显示每个组中所有条形的平均值.我所拥有的

Now I want to add two hlines displaying the mean of all bars per group. All I get with

ggplot(df, aes(x=x, y=y, fill=g, group=g)) + 
  geom_bar(stat="identity", position="dodge") +
  stat_summary(fun.y=mean, aes(yintercept=..y.., group=g), geom="hline")

是

由于我也想对任意数量的组执行此操作，因此，我希望仅使用ggplot解决方案.

As I want to do this for a arbitrary number of groups as well, I would appreciate a solution with ggplot only.

我想避免这样的解决方案，因为它不完全依赖传递给ggplot的数据集，具有冗余代码，并且在组数方面不灵活:

I want to avoid a solution like this, because it does not rely purely on the dataset passed to ggplot, has redundant code and is not flexible in the number of groups:

ggplot(df, aes(x=x, y=y, fill=g, group=g)) + 
  geom_bar(stat="identity", position="dodge") +
  geom_hline(yintercept=mean(df$y[df$g=="a"]), col="red") +
  geom_hline(yintercept=mean(df$y[df$g=="b"]), col="green")

提前谢谢！

• 添加了数据集
• 评论结果代码
• 更改了数据和图以澄清问题

推荐答案

如果我正确理解了您的问题，那么第一种方法就差不多了:

If I understand your question correctly, your first approach is almost there:

ggplot(df, aes(x = x, y = y, fill = g, group = g)) + 
  geom_col(position="dodge") + # geom_col is equivalent to geom_bar(stat = "identity")
  stat_summary(fun.y = mean, aes(x = 1, yintercept = ..y.., group = g), geom = "hline")

根据stat_summary的帮助文件:

stat_summary在唯一的x上操作； ...

stat_summary operates on unique x; ...

在这种情况下，stat_summary默认继承了x = x和group = g的顶级美学映射，因此它将计算每个x的平均y值 中的每个g值，导致出现许多水平线.在stat_summary的映射中添加x = 1会覆盖x = x(同时保留group = g)，因此对于每个g值，我们得到一个均值y值.

In this case, stat_summary has inherited the top level aesthetic mappings of x = x and group = g by default, so it would calculate the mean y value at each x for each value of g, resulting in a lot of horizontal lines. Adding x = 1 to stat_summary's mapping overrides x = x (while retaining group = g), so we get a single mean y value for each value of g instead.

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