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我正在学习 R，我向你保证，我已经从高处和低处搜索过这个问题的答案。它是如此简单，但由于某种原因，我无法为我的生活弄明白！

我有一个包含一个数字向量和两个因子的数据框：

team.weight <- c(150,160,120,100) # player's weight
team.jersey <- factor(c("blue", "green", "blue", "blue")) # player's jersey color
team.sex <- factor(c("male", "female", "female", "male")) # player's sex
team <- data.frame(team.jersey, team.sex, team.weight)

我想显示一个表格（我忘记了它叫什么），它显示了两个因子表的每个级别组合的所有球员的平均体重，即 mean(team.weight)。

我可以手动执行此操作，但必须有更好的方法！

mean(team.weight[c(team.jersey[1],team.sex[1])])
mean(team.weight[c(team.jersey[1],team.sex[2])])
mean(team.weight[c(team.jersey[1],team.sex[3])])
mean(team.weight[c(team.jersey[1],team.sex[4])])

mean(team.weight[c(team.jersey[2],team.sex[1])])
mean(team.weight[c(team.jersey[2],team.sex[2])])
mean(team.weight[c(team.jersey[2],team.sex[3])])
mean(team.weight[c(team.jersey[2],team.sex[4])])

mean(team.weight[c(team.jersey[3],team.sex[1])])
mean(team.weight[c(team.jersey[3],team.sex[2])])
mean(team.weight[c(team.jersey[3],team.sex[3])])
mean(team.weight[c(team.jersey[3],team.sex[4])])

mean(team.weight[c(team.jersey[4],team.sex[1])])
mean(team.weight[c(team.jersey[4],team.sex[2])])
mean(team.weight[c(team.jersey[4],team.sex[3])])
mean(team.weight[c(team.jersey[4],team.sex[4])])

任何帮助将不胜感激。我知道答案很愚蠢，但我无法理解它是什么。

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2 回答 2

3 
tapply(team.weight, list(team$team.jersey, team$team.sex), mean)
#       female male
# blue     120  125
# green    160   NA
于 2013-08-25T14:26:21.077 回答
2

Here is a plyr example:

> library(plyr)
> ddply(team,.(team.jersey,team.sex),summarize,avgWeight=mean(team.weight))
  team.jersey team.sex avgWeight
1        blue   female       120
2        blue     male       125
3       green   female       160
于 2013-08-25T14:23:39.580 回答