Imputing random values sampled from non-missing values

If you want to impute random values sampled from the non-missing values of the variable, you can use the following two functions:

rand.impute <- function(a) { 
  missing <- is.na(a) 
  n.missing <- sum(missing) 
  a.obs <- a[!missing] 
  imputed <- a 
  imputed[missing] <- sample (a.obs, n.missing, replace=TRUE) 
  return (imputed) 
} 
 
random.impute.data.frame <- function(dat, cols) { 
  nms <- names(dat) 
  for(col in cols) { 
    name <- paste(nms[col],".imputed", sep = "") 
    dat[name] <- rand.impute(dat[,col]) 
  } 
  dat 
} 

With these two functions in place, you can use the following to impute random values for both Income and Phone_type:

> dat <- read.csv("missing-data.csv", na.strings="") 
> random.impute.data.frame(dat, c(1,2))