如何调用一个返回data.table中多个行和列的函数?

时间:2013-07-28 22:18:19

标签: r statistics data.table

我想在data.table中调用一个函数来计算一组汇总统计信息,如下所示:

summ.stats <- function(vec) {
    list(
         Min = min(vec),
         Mean = mean(vec),
         S.D. = sd(vec),
         Median = median(vec),
         Max = max(vec))
}

我希望在j的{​​{1}}中调用它:

data.table

这很好,我明白了:

DT <- data.table(a=c(1,2,3,1,2,3),b=c(1,4,3,2,1,4),c=c(2,3,4,5,2,1))

DT[, summ.stats(b), by=a]

但我有兴趣将多个变量传递给summ.stats。例如:

   a Min Mean      S.D. Median Max
1: 1   1  1.5 0.7071068    1.5   2
2: 2   1  2.5 2.1213203    2.5   4
3: 3   3  3.5 0.7071068    3.5   4

我希望得到类似的内容:

DT[, summ.stats(b, c), by=a]

最好的方法是什么?

2 个答案:

答案 0 :(得分:5)

或者您可以按如下方式修改您的功能:

summ.stats <- function(vec) {
    list(
        Var = names(vec),
         Min = sapply(vec, min),
         Mean = sapply(vec, mean),
         S.D. = sapply(vec, sd),
         Median = sapply(vec, median),
         Max = sapply(vec, max))
}

DT[, summ.stats(.SD), by=a] # no need for as.list(.SD) as Roger mentions
   a Var Min Mean      S.D. Median Max
1: 1   b   1  1.5 0.7071068    1.5   2
2: 1   c   2  3.5 2.1213203    3.5   5
3: 2   b   1  2.5 2.1213203    2.5   4
4: 2   c   2  2.5 0.7071068    2.5   3
5: 3   b   3  3.5 0.7071068    3.5   4
6: 3   c   1  2.5 2.1213203    2.5   4

答案 1 :(得分:3)

如果没有明确地重塑为长形式,您可以执行类似

的操作
rbindlist(lapply(c('b','c'), function(x) data.table(var = x, DT[,summ.stats(get(x)),by=a])))



#    var a Min Mean      S.D. Median Max
# 1:   b 1   1  1.5 0.7071068    1.5   2
# 2:   b 2   1  2.5 2.1213203    2.5   4
# 3:   b 3   3  3.5 0.7071068    3.5   4
# 4:   c 1   2  3.5 2.1213203    3.5   5
# 5:   c 2   2  2.5 0.7071068    2.5   3
# 6:   c 3   1  2.5 2.1213203    2.5   4

如果reshape数据为长篇

reshape(DT, direction = 'long', 
            varying = list(value = c('b','c')), 
            times = c('b','c'))[,summ.stats(b), by = list(a, Var = time)]

也可以。


效率较低,你可以使用plyr的ldply,稍微重新定义一下这个函数

summ.stats2 <- function(vec) {
    data.table(
         Min = min(vec),
         Mean = mean(vec),
         S.D. = sd(vec),
         Median = median(vec),
         Max = max(vec))
}
library(plyr)
DT[, ldply(lapply(.SD, summ.stats2)),by =a]