具有不同功能的聚合多个变量

Question

说我下表DataTable

Cat1 | Cat2 | Val1 | Val2 
-------------------------------------------- 
A  | A  | 1  | 2 
A  | B  | 3  | 4 
B  | A  | 5  | 6 
B  | B  | 7  | 8 
A  | A  | 2  | 4 
A  | B  | 6  | 8 
B  | A  | 10  | 12 
B  | B  | 14  | 16 

这一点我希望通过CAT1和CAT2聚集，以分别VAL1和VAL2的总和和平均过，我怎么可能达致这？

Cat1 | Cat2 | Sum Val1 | Avg Val2 
-------------------------------------------- 
A  | A  | 3  | 3 
A  | B  | 9  | 6 
B  | A  | 15  | 9 
B  | B  | 21  | 12 

我已经取得了单变量聚合，聚合函数：

aggregate(
     Val1 
    ~ Cat1 + Cat2 
    data=DataTable, 
    FUNC=sum 
) 

但尽管有cbind玩耍，不能得到我想要的行为。我24小时学习R，所以我对这些概念不够熟悉，不能完全理解我一直在做什么（总是很危险！），但是认为这一点很容易实现。 |

Answer 1

set.seed(45) 
df <- data.frame(c1=rep(c("A","A","B","B"), 2), 
       c2 = rep(c("A","B"), 4), 
       v1 = sample(8), 
       v2 = sample(1:100, 8)) 
> df 
# c1 c2 v1 v2 
# 1 A A 6 19 
# 2 A B 3 1 
# 3 B A 2 37 
# 4 B B 8 86 
# 5 A A 5 30 
# 6 A B 1 44 
# 7 B A 7 41 
# 8 B B 4 39 

v1 <- aggregate(v1 ~ c1 + c2, data = df, sum) 
v2 <- aggregate(v2 ~ c1 + c2, data = df, mean) 
out <- merge(v1, v2, by=c("c1","c2")) 
> out 
# c1 c2 v1 v2 
# 1 A A 11 24.5 
# 2 A B 4 22.5 
# 3 B A 9 39.0 
# 4 B B 12 62.5 

**Edit:**我会建议你使用data.table，因为它使事情变得非常简单：

require(data.table) 
dt <- data.table(df) 
dt.out <- dt[, list(s.v1=sum(v1), m.v2=mean(v2)), 
        by=c("c1","c2")] 
> dt.out 

# c1 c2 s.v1 m.v2 
# 1: A A 11 24.5 
# 2: A B 4 22.5 
# 3: B A 9 39.0 
# 4: B B 12 62.5 

Answer 2

这里有一个基础R解决方案：

首先，你的数据：

x <- structure(list(Cat1 = structure(c(1L, 1L, 2L, 2L, 1L, 1L, 2L, 
2L), .Label = c("A", "B"), class = "factor"), Cat2 = structure(c(1L, 
2L, 1L, 2L, 1L, 2L, 1L, 2L), .Label = c("A", "B"), class = "factor"), 
    Val1 = c(1L, 3L, 5L, 7L, 2L, 6L, 10L, 14L), Val2 = c(2L, 
    4L, 6L, 8L, 4L, 8L, 12L, 16L)), .Names = c("Cat1", "Cat2", 
"Val1", "Val2"), class = "data.frame", row.names = c(NA, -8L)) 

然后，使用ave()和unique()机智hin within()。

unique(
    within(x, { 
    sum_val1 <- ave(Val1, Cat1, Cat2, FUN = sum) 
    mean_val2 <- ave(Val2, Cat1, Cat2, FUN = mean) 
    rm(Val1, Val2) 
    }) 
) 
# Cat1 Cat2 mean_val2 sum_val1 
# 1 A A   3  3 
# 2 A B   6  9 
# 3 B A   9  15 
# 4 B B  12  21 

或者，如果您熟悉SQL，使用sqldf：

library(sqldf) 
sqldf("select Cat1, Cat2, 
     sum(Val1) `Sum_Val1`, 
     avg(Val2) `Avg_Val2` 
     from x group by Cat1, Cat2")