为ggplot2中的每个面板添加一条具有不同截距的垂直线

发布于 2024-08-09 19:50:08 字数 771 浏览 3 评论 0原文

我正在使用 ggplot2 创建直方图面板，并且我希望能够在每组的平均值处添加一条垂直线。但是 geom_vline() 对每个面板使用相同的截距（即全局平均值）：

require("ggplot2")
# setup some sample data
N <- 1000
cat1 <- sample(c("a","b","c"), N, replace=T)
cat2 <- sample(c("x","y","z"), N, replace=T)
val <- rnorm(N) + as.numeric(factor(cat1)) + as.numeric(factor(cat2))
df <- data.frame(cat1, cat2, val)

# draws a single histogram with vline at mean
qplot(val, data=df, geom="histogram", binwidth=0.2) + 
  geom_vline(xintercept=mean(val), color="red")

# draws panel of histograms with vlines at global mean
qplot(val, data=df, geom="histogram", binwidth=0.2, facets=cat1~cat2) + 
  geom_vline(xintercept=mean(val), color="red")

如何让它使用每个面板的组平均值作为 x 截距？（如果您还可以在包含平均值的行旁添加文本标签，则可获得奖励积分。）

原文

I'm using ggplot2 to create panels of histograms, and I'd like to be able to add a vertical line at the mean of each group. But geom_vline() uses the same intercept for each panel (i.e. the global mean):

require("ggplot2")
# setup some sample data
N <- 1000
cat1 <- sample(c("a","b","c"), N, replace=T)
cat2 <- sample(c("x","y","z"), N, replace=T)
val <- rnorm(N) + as.numeric(factor(cat1)) + as.numeric(factor(cat2))
df <- data.frame(cat1, cat2, val)

# draws a single histogram with vline at mean
qplot(val, data=df, geom="histogram", binwidth=0.2) + 
  geom_vline(xintercept=mean(val), color="red")

# draws panel of histograms with vlines at global mean
qplot(val, data=df, geom="histogram", binwidth=0.2, facets=cat1~cat2) + 
  geom_vline(xintercept=mean(val), color="red")

How can I get it to use each panel's group mean as the x-intercept? (Bonus points if you can also add a text label by the line with the value of the mean.)

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挥剑断情 2024-08-16 19:50:08

我想这确实是 @eduardo 的重写，但只有一行。

ggplot(df) + geom_histogram(mapping=aes(x=val)) 
  + geom_vline(data=aggregate(df[3], df[c(1,2)], mean), 
      mapping=aes(xintercept=val), color="red") 
  + facet_grid(cat1~cat2)

替代文本 http://www.imagechicken.com/uploads/1264782634003683000.png

或使用 plyr< /code> （require(plyr) ggplot 作者 Hadley 的一个包）：

ggplot(df) + geom_histogram(mapping=aes(x=val)) 
  + geom_vline(data=ddply(df, cat1~cat2, numcolwise(mean)), 
      mapping=aes(xintercept=val), color="red") 
  + facet_grid(cat1~cat2)

vline 没有在切面上切割，这似乎令人不满意，我不知道为什么。

I guess this is a reworking of @eduardo's really, but in one line.

ggplot(df) + geom_histogram(mapping=aes(x=val)) 
  + geom_vline(data=aggregate(df[3], df[c(1,2)], mean), 
      mapping=aes(xintercept=val), color="red") 
  + facet_grid(cat1~cat2)

alt text http://www.imagechicken.com/uploads/1264782634003683000.png

or using plyr (require(plyr) a package by the author of ggplot, Hadley):

ggplot(df) + geom_histogram(mapping=aes(x=val)) 
  + geom_vline(data=ddply(df, cat1~cat2, numcolwise(mean)), 
      mapping=aes(xintercept=val), color="red") 
  + facet_grid(cat1~cat2)

It seems unsatisfying that vline isn't cut on the facets, I'm not sure why.

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枫林﹌晚霞¤ 2024-08-16 19:50:08

一种方法是预先使用平均值构建 data.frame。

library(reshape)
dfs <- recast(data.frame(cat1, cat2, val), cat1+cat2~variable, fun.aggregate=mean)
qplot(val, data=df, geom="histogram", binwidth=0.2, facets=cat1~cat2) + geom_vline(data=dfs, aes(xintercept=val), colour="red") + geom_text(data=dfs, aes(x=val+1, y=1, label=round(val,1)), size=4, colour="red")

One way is to construct the data.frame with the mean values before hand.

library(reshape)
dfs <- recast(data.frame(cat1, cat2, val), cat1+cat2~variable, fun.aggregate=mean)
qplot(val, data=df, geom="histogram", binwidth=0.2, facets=cat1~cat2) + geom_vline(data=dfs, aes(xintercept=val), colour="red") + geom_text(data=dfs, aes(x=val+1, y=1, label=round(val,1)), size=4, colour="red")

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