使用：=在data.table中，按组分组多个列

使用data.table分配给多个列的最佳方式是什么？ 例如：

 f <- function(x) {c("hi", "hello")} x <- data.table(id = 1:10) 

我想要做这样的事情（当然这个语法是不正确的）：

 x[ , (col1, col2) := f(), by = "id] 

并扩大，我可能有很多名称在variables列（如column_names ），我想这样做：

 x[ , col_names := another_f(), by = "id", with = FALSE] 

什么是正确的方式来做这样的事情？

Answer 1

这现在在R-Forge的v1.8.3中有效。 感谢您的突出！

 x <- data.table(a = 1:3, b = 1:6) f <- function(x) {list("hi", "hello")} x[ , c("col1", "col2") := f(), by = a][] # ab col1 col2 # 1: 1 1 hi hello # 2: 2 2 hi hello # 3: 3 3 hi hello # 4: 1 4 hi hello # 5: 2 5 hi hello # 6: 3 6 hi hello x[ , c("mean", "sum") := list(mean(b), sum(b)), by = a][] # ab col1 col2 mean sum # 1: 1 1 hi hello 2.5 5 # 2: 2 2 hi hello 3.5 7 # 3: 3 3 hi hello 4.5 9 # 4: 1 4 hi hello 2.5 5 # 5: 2 5 hi hello 3.5 7 # 6: 3 6 hi hello 4.5 9 mynames = c("Name1", "Longer%") x[ , (mynames) := list(mean(b) * 4, sum(b) * 3), by = a] # ab col1 col2 mean sum Name1 Longer% # 1: 1 1 hi hello 2.5 5 10 15 # 2: 2 2 hi hello 3.5 7 14 21 # 3: 3 3 hi hello 4.5 9 18 27 # 4: 1 4 hi hello 2.5 5 10 15 # 5: 2 5 hi hello 3.5 7 14 21 # 6: 3 6 hi hello 4.5 9 18 27 

 x[ , mynames := list(mean(b) * 4, sum(b) * 3), by = a, with = FALSE][] # same # ab col1 col2 mean sum Name1 Longer% # 1: 1 1 hi hello 2.5 5 10 15 # 2: 2 2 hi hello 3.5 7 14 21 # 3: 3 3 hi hello 4.5 9 18 27 # 4: 1 4 hi hello 2.5 5 10 15 # 5: 2 5 hi hello 3.5 7 14 21 # 6: 3 6 hi hello 4.5 9 18 27 x[ , get("mynames") := list(mean(b) * 4, sum(b) * 3), by = a][] # same # ab col1 col2 mean sum Name1 Longer% # 1: 1 1 hi hello 2.5 5 10 15 # 2: 2 2 hi hello 3.5 7 14 21 # 3: 3 3 hi hello 4.5 9 18 27 # 4: 1 4 hi hello 2.5 5 10 15 # 5: 2 5 hi hello 3.5 7 14 21 # 6: 3 6 hi hello 4.5 9 18 27 x[ , eval(mynames) := list(mean(b) * 4, sum(b) * 3), by = a][] # same # ab col1 col2 mean sum Name1 Longer% # 1: 1 1 hi hello 2.5 5 10 15 # 2: 2 2 hi hello 3.5 7 14 21 # 3: 3 3 hi hello 4.5 9 18 27 # 4: 1 4 hi hello 2.5 5 10 15 # 5: 2 5 hi hello 3.5 7 14 21 # 6: 3 6 hi hello 4.5 9 18 27