如何获得geom_vline来尊重facet_wrap？ [英] How to get geom_vline to honor facet_wrap?

问题描述

我捅了一圈，但一直无法找到答案。我想要做一个加权的geom_bar图，用垂直线覆盖，显示每个方面的总体加权平均值。我无法做到这一点。垂直线似乎适用于所有方面的单个值。

  require（'ggplot2'）
 require（' （A，A，A，A，A，A，B，B，B ，B，B，B，B，B，B，B，B，B）
 instrument <-c ， V2， V1， V1， V1， V2， V1， V1， V2， V1， V1， V2， V1， V1，V2，V1）
 cost <-c（1,4,1.5,1,4,4,1,2,1.5,1,2,1.5,2,1.5， 1,2）
灵敏度<-c（3,5,2,5,5,1,1,2,3,4,3,2,1,3,1,2）
 
＃将一个初始数据框放在一起
 mydata<  -  data.frame（panel，instrument，cost，sensitivity）
 
＃向数据添加一个贡献向量框架：每种仪器
＃对面板的加权平均敏感度的贡献。 
 MYFUNC<  - 功能（成本，灵敏度）{
返回（成本*灵敏度/总和（成本））
} 
 MYDATA<  -  ddply（MYDATA，（面板），transform，contrib = myfunc（cost，sensitivity））
 
＃每个面板加权平均的两个视图;应该是相同的编号，无论哪种方式
 ddply（MYDATA，C（ 面板），概括地说，wavg = weighted.mean（灵敏度，成本））
 ddply（MYDATA，C（ 面板），总结一下，wavg2 = sum（contrib））
 
＃plot每个面板从其总体成本加权灵敏度中获得。另外
＃将每个面板的加权平均值作为一条简单的垂直线。 
＃
＃问题！我不知道如何获得geom_vline来尊重方面的细节。它
＃似乎是计算整体数据，并在每个方面图中显示相同的
＃值。 
 ggplot（MYDATA，AES（X =灵敏度，重量=的contrib））+ 
 geom_bar（binwidth = 1）+ 
 geom_vline（xintercept =总和（的contrib））+ 
 facet_wrap （〜panel）+ 
 ylab（contrib）
  

解决方案

如果你传入了预设数据，它似乎工作：

$ $ $ $ $ $ $ $ $ ggplot（mydata，aes（x =灵敏度，重量=的contrib））+
geom_bar（binwidth = 1）+
geom_vline（数据= ddply（MYDATA， 面板，概括地说，wavg =总和（的contrib）），AES（xintercept = wavg） ）+
facet_wrap（〜panel）+
ylab（contrib）+
theme_bw（）

I've poked around, but been unable to find an answer. I want to do a weighted geom_bar plot overlaid with a vertical line that shows the overall weighted average per facet. I'm unable to make this happen. The vertical line seems to a single value applied to all facets.

require('ggplot2')
require('plyr')

# data vectors
panel <- c("A","A","A","A","A","A","B","B","B","B","B","B","B","B","B","B")
instrument <-c("V1","V2","V1","V1","V1","V2","V1","V1","V2","V1","V1","V2","V1","V1","V2","V1")
cost <- c(1,4,1.5,1,4,4,1,2,1.5,1,2,1.5,2,1.5,1,2)
sensitivity <- c(3,5,2,5,5,1,1,2,3,4,3,2,1,3,1,2)

# put an initial data frame together
mydata <- data.frame(panel, instrument, cost, sensitivity)

# add a "contribution to" vector to the data frame: contribution of each instrument
# to the panel's weighted average sensitivity.
myfunc <- function(cost, sensitivity) {
  return(cost*sensitivity/sum(cost))
}
mydata <- ddply(mydata, .(panel), transform, contrib=myfunc(cost, sensitivity))

# two views of each panels weighted average; should be the same numbers either way
ddply(mydata, c("panel"), summarize, wavg=weighted.mean(sensitivity, cost))
ddply(mydata, c("panel"), summarize, wavg2=sum(contrib))

# plot where each panel is getting its overall cost-weighted sensitivity from. Also
# put each panel's weighted average on the plot as a simple vertical line.
#
# PROBLEM! I don't know how to get geom_vline to honor the facet breakdown. It
#          seems to be computing it overall the data and showing the resulting
#          value identically in each facet plot.
ggplot(mydata, aes(x=sensitivity, weight=contrib)) +
  geom_bar(binwidth=1) +
  geom_vline(xintercept=sum(contrib)) +
  facet_wrap(~ panel) +
  ylab("contrib")

解决方案

If you pass in the presumarized data, it seems to work:

ggplot(mydata, aes(x=sensitivity, weight=contrib)) +
  geom_bar(binwidth=1) +
  geom_vline(data = ddply(mydata, "panel", summarize, wavg = sum(contrib)), aes(xintercept=wavg)) +
  facet_wrap(~ panel) +
  ylab("contrib") +
  theme_bw()

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