将函数应用于 data.table 的每一行 [英] Applying a function to each row of a data.table

问题描述

我正在寻找一种方法来有效地将函数应用于 data.table 的每一行.让我们考虑以下数据表:

I looking for a way to efficiently apply a function to each row of data.table. Let's consider the following data table:

library(data.table)
library(stringr)

x <- data.table(a = c(1:3, 1), b = c('12 13', '14 15', '16 17', '18 19'))
> x
   a     b
1: 1 12 13
2: 2 14 15
3: 3 16 17
4: 1 18 19

假设我想按空格分割列 b 的每个元素(从而为原始数据中的每一行生成两行)并连接生成的数据表.对于上面的示例，我需要以下结果:

Let's say I want to split each element of column b by space (thus yielding two rows for each row in the original data) and join the resulting data tables. For the example above, I need the following result:

   a V1
1: 1 12
2: 1 13
3: 2 14
4: 2 15
5: 3 16
6: 3 17
7: 1 18
8: 1 19

如果列 a 仅具有唯一值，则以下方法会起作用:

The following would work if column a has only unique values:

x[, list(str_split(b, ' ')[[1]]), by = a]

下面的几乎有效(除非原始数据表中有一些相同的行)，但是当 x 有很多列并将列 b 复制到结果时很难看，我想避免.

The following almost works (unless there are some identical rows in the original data table), but is ugly when x has many columns and copies column b to the result, which I would like to avoid.

>     x[, list(str_split(b, ' ')[[1]]), by = list(a,b)]
   a     b V1
1: 1 12 13 12
2: 1 12 13 13
3: 2 14 15 14
4: 2 14 15 15
5: 3 16 17 16
6: 3 16 17 17
7: 1 18 19 18
8: 1 18 19 19

解决这个问题最有效和最惯用的方法是什么?

What would be the most efficient and idiomatic way to solve this problem?

推荐答案

怎么样:

x
   a     b
1: 1 12 13
2: 2 14 15
3: 3 16 17
4: 1 18 19

x[,list(a=rep(a,each=2), V1=unlist(strsplit(b," ")))]
   a V1
1: 1 12
2: 1 13
3: 2 14
4: 2 15
5: 3 16
6: 3 17
7: 1 18
8: 1 19

给出评论的通用解决方案:

Generalized solution given comment :

x[,{s=strsplit(b," ");list(a=rep(a,sapply(s,length)), V1=unlist(s))}]

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