r - 按多个组计算跨多列的最大值

Question

我有一个数据文件，其中包含三列中的数值和两个分组变量(ID 和 Group)，我需要从中通过 ID 和 Group 计算单个最大值:

structure(list(ID = structure(c(1L, 1L, 1L, 2L), .Label = c("a1", 
"a2"), class = "factor"), Group = structure(c(1L, 1L, 2L, 2L), .Label = 
c("abc", 
"def"), class = "factor"), Score1 = c(10L, 0L, 0L, 5L), Score2 = c(0L, 
0L, 5L, 10L), Score3 = c(0L, 11L, 2L, 11L)), class = "data.frame", row.names = 
c(NA, 
-4L))

我试图获得的结果是:

structure(list(ID = structure(c(1L, 1L, 2L), .Label = c("a1", 
"a2"), class = "factor"), Group = structure(c(1L, 2L, 2L), .Label = c("abc", 
"def"), class = "factor"), Max = c(11L, 5L, 11L)), class = "data.frame", 
row.names = c(NA, 
-3L))

我正在 dplyr 中尝试以下操作:

SampTable<-SampDF %>% group_by(ID,Group) %>% 
summarize(max = pmax(SampDF$Score1, SampDF$Score2,SampDF$Score3))

但它会产生这个错误:

Error in summarise_impl(.data, dots) : 
Column `max` must be length 1 (a summary value), not 4

是否有一种简单的方法可以在 dplyr 中实现此目的？或 data.table ?

Answer 1

使用 data.table 的解决方案.在 3:5 上查找最大值列(分数列)来自 ID和 Group .

library(data.table)
setDT(d)
d[, .(Max = do.call(max, .SD)), .SDcols = 3:5, .(ID, Group)]

   ID Group Max
1: a1   abc  11
2: a1   def   5
3: a2   def  11

数据:

d <- structure(list(ID = structure(c(1L, 1L, 1L, 2L), .Label = c("a1", 
"a2"), class = "factor"), Group = structure(c(1L, 1L, 2L, 2L), .Label = 
c("abc", 
"def"), class = "factor"), Score1 = c(10L, 0L, 0L, 5L), Score2 = c(0L, 
0L, 5L, 10L), Score3 = c(0L, 11L, 2L, 11L)), class = "data.frame", row.names = 
c(NA, 
-4L))