Question

After merging a dataframe with another im left with random NA’s for the occasional row. I’d like to set these NA’s to 0 so I can perform calculations with them.

Im trying to do this with:

    bothbeams.data = within(bothbeams.data, {
      bothbeams.data$x.x = ifelse(is.na(bothbeams.data$x.x) == TRUE, 0, bothbeams.data$x.x)
      bothbeams.data$x.y = ifelse(is.na(bothbeams.data$x.y) == TRUE, 0, bothbeams.data$x.y)
    })

Where $x.x is one column and $x.y is the other of course, but this doesn’t seem to work.

Answer 1

You can just use the output of is.na to replace directly with subsetting:

bothbeams.data[is.na(bothbeams.data)] <- 0

Or with a reproducible example:

dfr <- data.frame(x=c(1:3,NA),y=c(NA,4:6))
dfr[is.na(dfr)] <- 0
dfr
  x y
1 1 0
2 2 4
3 3 5
4 0 6

However, be careful using this method on a data frame containing factors that also have missing values:

> d <- data.frame(x = c(NA,2,3),y = c("a",NA,"c"))
> d[is.na(d)] <- 0
Warning message:
In `[<-.factor`(`*tmp*`, thisvar, value = 0) :
  invalid factor level, NA generated

It “works”:

> d
  x    y
1 0    a
2 2 <NA>
3 3    c

…but you likely will want to specifically alter only the numeric columns in this case, rather than the whole data frame. See, eg, the answer below using dplyr::mutate_if.