R？中多因素的汇总统计？

我有每个游戏的游戏数据如下：

身份证件 销售时点情报系统 团队 目镜肺体积描记图 分数 0 A. 鸭子 青蛙 2. 1. B 鸭子 青蛙 15 2. B 鸭子 青蛙 20 3. C 鸭子 青蛙 7. 4. C 鸭子 青蛙 9.5 5. C 鸭子 青蛙 10 6. A. 青蛙 鸭子 3. 7. A. 青蛙 鸭子 0.5 8. B 青蛙 鸭子 17 9 B 青蛙 鸭子 13 10 B 青蛙 鸭子 21 11 C 青蛙 鸭子 8.5

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正如@Maurits Evers所评论的那样，您展示输出的方式没有任何意义。看起来您需要一个单独的输出，每个团队和位置的平均分数。另外，你每行只给我们一分，我想这是

团队的得分，所以我们没有对手的得分来计算平均值。我会使用
dplyr
summary
函数

以下是您的数据：

game = data.frame(id = c(0:11),
                  Pos = c("A", "B", "B", "C", "C", "C","A","A", "B", "B", "B","C"),
                  Team = c("Duck","Duck","Duck","Duck","Duck","Duck","Frog","Frog","Frog","Frog","Frog","Frog"),
                  Opp = c("Frog","Frog","Frog","Frog","Frog","Frog","Duck","Duck","Duck","Duck","Duck","Duck"),
                  Score = c(2, 15, 20, 7, 9.5, 10, 3, 0.5, 17, 13, 21, 8.5))

首先，按职位划分的平均数：

library(dplyr)
Pos_av = game%>%    #creat a new data.frame called "Pos_av" which is taking data from "game" and piping it (%>%) into different functions 
  group_by(Pos)%>%    #first into a grouping function so we chose the variable we want to find the average for
  summarise(Pos_Mean = mean(Score))    # the we pipe into summarise function where we name our new variable (Pos_Mean) and then define the function we want to use to summarise it (in this case the mean)

这给了我们：

对于团队来说，这同样意味着：

Team_av = game%>%
  group_by(Team)%>%
  summarise(Team_Mean = mean(Score))


要获得每个团队和职位的平均值，请按两个变量分组：

Both_av = game%>%
  group_by(Team, Pos)%>%
  summarise(Mean = mean(Score))

您可以通过循环数据帧和所有条件来设置每个单元格的值，具体取决于该条件和该对手/团队的平均值：

## The name of the variable holding the data.frame is "df"

## Expand the dataframe to contain your desired variables
for(t in c("Team","Opp")){
  for(p in c("A","B","C")){
    df[[paste(t,"_",p,"_","Avg",sep="")]]=NA
  }
}

## Loop through the data to compute the means
for(i in 1:dim(df)[1]){
  for(t in c("Team","Opp")){
    for(p in c("A","B","C")){
      ## For each case i, each Team t, and each Position p, compute the mean and store it:
      df[[paste(t,"_",p,"_","Avg",sep="")]][i] = mean(df$Score[df$Team==df[[t]][i] & df$Pos==p])
    }
  }
}

这将导致数据帧：

> df
   Id Pos Team  Opp Score Team_A_Avg Team_B_Avg Team_C_Avg Opp_A_Avg Opp_B_Avg Opp_C_Avg
1   0   A Duck Frog   2.0       2.00       17.5   8.833333      1.75      17.0  8.500000
2   1   B Duck Frog  15.0       2.00       17.5   8.833333      1.75      17.0  8.500000
3   2   B Duck Frog  20.0       2.00       17.5   8.833333      1.75      17.0  8.500000
4   3   C Duck Frog   7.0       2.00       17.5   8.833333      1.75      17.0  8.500000
5   4   C Duck Frog   9.5       2.00       17.5   8.833333      1.75      17.0  8.500000
6   5   C Duck Frog  10.0       2.00       17.5   8.833333      1.75      17.0  8.500000
7   6   A Frog Duck   3.0       1.75       17.0   8.500000      2.00      17.5  8.833333
8   7   A Frog Duck   0.5       1.75       17.0   8.500000      2.00      17.5  8.833333
9   8   B Frog Duck  17.0       1.75       17.0   8.500000      2.00      17.5  8.833333
10  9   B Frog Duck  13.0       1.75       17.0   8.500000      2.00      17.5  8.833333
11 10   B Frog Duck  21.0       1.75       17.0   8.500000      2.00      17.5  8.833333
12 11   C Frog Duck   8.5       1.75       17.0   8.500000      2.00      17.5  8.833333

我不明白你的预期产出；为什么
Team_A_Avg=2
即使是
Pos=B
和
Pos=C
的行也是如此？@mbenoo请您查看建议的答案，如果有人回答了您的问题，请接受+/-向上投票？谢谢