CODEWITHSUNDEEP
rapplylapply
Catchment_Jack
Catchment_Jack

Reputation: 375

Apply function to multiple concurrent columns and output to new column - R

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

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.

So far I have been doing this the following way:

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:

  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)!

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?

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

Thanks.

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

Upvotes: 0

Views: 190

Answers (2)

akrun
akrun

Reputation: 887173

You may also try

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

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

Upvotes: 0

David Arenburg
David Arenburg

Reputation: 92292

Try this

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

Upvotes: 1

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