将函数应用于多个并发列并输出到新列 - R.

Ok, first of all let me generate some sample data:

好的，首先让我生成一些示例数据：

A_X01 <- c(34, 65, 23, 43, 22)
A_X02 <- c(2, 4, 7, 8, 3)
B_X01 <- c(24, 45, 94, 23, 54)
B_X02 <- c(4, 2, 4, 9, 1)
C_X01 <- c(34, 65, 876, 45, 87)
C_X02 <- c(123, 543, 86, 87, 34)
Var <- c(3, 5, 7, 2, 3)
DF <- data.frame(A_X01, A_X02, B_X01, B_X02, C_X01, C_X02, Var)

What I want to do is apply an equation to the concurrent columns of A and B for both X01 and X02, with a third column "Var" used in the equation.

我想要做的是将方程应用于X01和X02的A和B的并发列，方程中使用第三列“Var”。

So far I have been doing this the following way:

到目前为止，我一直在这样做：

DF$D_X01 <- (DF$A_X01 + DF$B_X01) * DF$Var 
DF$D_X02 <- (DF$A_X02 + DF$B_X02) * DF$Var

My desired output is as follows:

我想要的输出如下：

  A_X01 A_X02 B_X01 B_X02 C_X01 C_X02 Var D_X01 D_X02
1    34     2    24     4    34   123   3   174    18
2    65     4    45     2    65   543   5   550    30
3    23     7    94     4   876    86   7   819    77
4    43     8    23     9    45    87   2   132    34
5    22     3    54     1    87    34   3   228    12

As you'll appreciate this is a lot of lines of code to do something fairly simple. Meaning at present my scripts are rather long (as I have multiple columns in the actual dataset)!

正如您所理解的那样，要做一些相当简单的事情需要很多代码。目前我的脚本相当长（因为我在实际数据集中有多个列）！

One of the apply functions must be the way to go but I can't seem to get my head around it for concurrent columns. I did think about using lapply but how would I get this to work for the two lists of columns and for the right columns to be added together?

其中一个应用函数必须是可行的方法，但我似乎无法理解并发列。我确实考虑过使用lapply，但是我如何才能将这个列用于两列列并将右列添加到一起？

I've looked around and can't seem to find a way to do this which must be a fairly common problem?

我环顾四周，似乎找不到办法做这个必须是一个相当常见的问题？

Thanks.

谢谢。

EDIT: Original question was a bit confusing so have updated with a desired output and some extra conditions.

编辑：原始问题有点令人困惑，所以更新了所需的输出和一些额外的条件。

2 个解决方案

#1

Try this

尝试这个

indx <- gsub("\\D", "", grep("A_X|B_X", names(DF), value = TRUE)) # Retrieving indexes
indx2 <- DF[grep("A_X|B_X", names(DF))] # Considering only the columns of interest
DF[paste0("D_X", unique(indx))] <- 
   sapply(unique(indx), function(x) rowSums(indx2[which(indx == x)])*DF$Var)
DF
#   A_X01 A_X02 B_X01 B_X02 C_X01 C_X02 Var D_X01 D_X02
# 1    34     2    24     4    34   123   3   174    18
# 2    65     4    45     2    65   543   5   550    30
# 3    23     7    94     4   876    86   7   819    77
# 4    43     8    23     9    45    87   2   132    34
# 5    22     3    54     1    87    34   3   228    12

#2

You may also try

你也可以试试

indxA <- grep("^A", colnames(DF))
indxB <- grep("^B", colnames(DF))
f1 <- function(x,y,z) (x+y)*z
DF[sprintf('D_X%02d', indxA)] <- Map(f1 , DF[indxA], DF[indxB], list(DF$Var))
DF
#  A_X01 A_X02 B_X01 B_X02 C_X01 C_X02 Var D_X01 D_X02
#1    34     2    24     4    34   123   3   174    18
#2    65     4    45     2    65   543   5   550    30
#3    23     7    94     4   876    86   7   819    77
#4    43     8    23     9    45    87   2   132    34
#5    22     3    54     1    87    34   3   228    12

Or you could use mapply

或者你可以使用mapply

DF[sprintf('D_X%02d', indxA)] <-  mapply(`+`, DF[indxA],DF[indxB])*DF$Var

#1