如何让geom_vline尊重facet_wrap？

Question

我已经四处寻找，但一直无法找到答案。我想做一个加权的geom_bar图，用垂直线覆盖，显示每个面的整体加权平均值。我无法做到这一点。垂直线似乎是应用于所有方面的单个值。

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")

Answer 1

如果传入推测数据，它似乎有效：

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()

Answer 2

使用dplyr和facet_wrap的示例，任何人都想要它。

library(dplyr)
library(ggplot2)

df1 <- mutate(iris, Big.Petal = Petal.Length > 4)
df2 <- df1 %>%
  group_by(Species, Big.Petal) %>%
  summarise(Mean.SL = mean(Sepal.Length))

ggplot() +
  geom_histogram(data = df1, aes(x = Sepal.Length, y = ..density..)) +
  geom_vline(data = df2, mapping = aes(xintercept = Mean.SL)) +
  facet_wrap(Species ~ Big.Petal) 

Answer 3

 vlines <- ddply(mydata, .(panel), summarize, sumc = sum(contrib))
 ggplot(merge(mydata, vlines), aes(sensitivity, weight = contrib)) + 
 geom_bar(binwidth = 1) + geom_vline(aes(xintercept = sumc)) + 
 facet_wrap(~panel) + ylab("contrib")