Creating a function to replace NAs from one data.frame with values from another

Question

I regularly have situations where I need to replace missing values from a data.frame with values from some other data.frame that is at a different level of aggregation. So,

Answer 1

My preference would be to pull out the code from merge that does the matching and do it myself so that I could keep the ordering of the original data frame intact, both row-wise and column-wise. I also use matrix indexing to avoid any loops, though to do so I create a new data frame with the revised fillCols and replace the columns of the original with it; I thought I could fill it in directly but apparently you can't use matrix ordering to replace parts of a data.frame, so I wouldn't be surprised if a loop over the names would be faster in some situations.

With matrix indexing:

fillNaDf <- function(naDf, fillDf, mergeCols, fillCols) {
  fillB <- do.call(paste, c(fillDf[, mergeCols, drop = FALSE], sep="\r"))
  naB <- do.call(paste, c(naDf[, mergeCols, drop = FALSE], sep="\r"))
  na.ind <- is.na(naDf[,fillCols])
  fill.ind <- cbind(match(naB, fillB)[row(na.ind)[na.ind]], col(na.ind)[na.ind])
  naX <- naDf[,fillCols]
  fillX <- fillDf[,fillCols]
  naX[na.ind] <- fillX[fill.ind]
  naDf[,colnames(naX)] <- naX
  naDf
}

With a loop:

fillNaDf2 <- function(naDf, fillDf, mergeCols, fillCols) {
  fillB <- do.call(paste, c(fillDf[, mergeCols, drop = FALSE], sep="\r"))
  naB <- do.call(paste, c(naDf[, mergeCols, drop = FALSE], sep="\r"))
  m <- match(naB, fillB)
  for(col in fillCols) {
    fix <- which(is.na(naDf[,col]))
    naDf[fix, col] <- fillDf[m[fix],col]
  }
  naDf
}