Question

I have two data.frames:

pattern <- data.frame(pattern = c("A", "B", "C", "D"), val = c(1, 1, 2, 2))

match <- data.frame(match = c("A", "C"))

I want to add to my data.frame pattern another column called new_val and assign “X” to each row where the value for column pattern is in the data.frame match otherwise assign “Y”

is.element(pattern$pattern, match$match)

[1] TRUE FALSE TRUE FALSE

So, the resulting data.frame should look like:

    pattern val new_val
1   A       1   X
2   B       1   Y
3   C       2   X
4   D       2   Y

I achieved to do it with an ugly for-loop but I am sure this can be pretty much done in a one line R command using fancy stuff 🙂

Is anyone able to help?

Many thanks!

Answer 1

I’m only really posting this since Tyler said “if you wanted a one liner data.table would likely do it” and I knew it was definitely possible with a one liner in base. I am also assuming match had been renamed to mat.

  pattern$new_val <- c("Y", "X")[(pattern$pattern %in% mat)+1]
  pattern
#  pattern val new_val
#1       A   1       X
#2       B   1       Y
#3       C   2       X
#4       D   2       Y

pattern$pattern %in% mat is finding which of the elements of pattern are in mat which returns TRUE if it’s in mat, FALSE if it’s not. Then I add 1 to make it numeric in the range of 1-2 so that it can be used for indexing. Then we use that as an index to the self defined vector c("Y", "X") and since the index we created is always 1 or 2 we’re always able to grab an element of interest. So in this case we’ll grab “Y” if pattern wasn’t in mat and “X” if it was – which is what you wanted.