Add variables whilst ignoring NA`s using transform function

Question

I have a data frame with a large number of variables. I am creating new variables by adding together some of the old ones. The code I am using to do so is:

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Answer 1

My first instinct was to suggest to use sum() since then you can use the na.rm argument. However, this doesn't work, since sum() reduces it arguments to a single scalar value, not a vector.

This means you need to write a parallel sum function. Let's call this psum(), similar to the base R function pmin() or pmax():

psum <- function(..., na.rm=FALSE) { 
  x <- list(...)
  rowSums(matrix(unlist(x), ncol=length(x)), na.rm=na.rm)
} 

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Now set up some data and use psum() to get the desired vector:

dat <- data.frame(
  x = c(1,2,3, NA),
  y = c(NA, 4, 5, NA))

transform(dat, new=psum(x, y, na.rm=TRUE))
   x  y new
1  1 NA   1
2  2  4   6
3  3  5   8
4 NA NA   0

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Similarly, you can define a parallel product, or pprod() like this:

pprod <- function(..., na.rm=FALSE) { 
  x <- list(...)
  m <- matrix(unlist(x), ncol=length(x))
  apply(m, 1, prod, na.rm=TRUE)
} 

transform(dat, new=pprod(x, y, na.rm=TRUE))
   x  y new
1  1 NA   1
2  2  4   8
3  3  5  15
4 NA NA   1

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This example of pprod provides a general template for what you want to do: Create a function that uses apply() to summarize a matrix of input into the desired vector.