Question

This is a toy example of something I always end up writing a loop for. I’m having trouble figuring out the one liner. I’m sure I’ve seen it, but it didn’t stick.

smallFrame <- data.frame(colA = c('A', 'B', 'C' ,'D'), colB = c(1,1,1,1))
someList <- list(A=20, B=30, C=40, D=50)
for(letter in names(someList)){
  smallFrame[smallFrame$colA==letter, 'newColumn'] <- someList[[letter]]
}

how do I do the loop in one line? This won’t do it.

lapply(names(someList), function(x) {smallFrame[smallFrame$colA==x, 'newColumn'] <- someList[[x]]})

Answer 1

This is a simple merge, if you reshape your smallList appropriately

# reshape2 for melt.
library(reshape2)
# slightly expanded version with duplicate colA == A
smallFrame <- data.frame(colA = c('A', 'A', 'B', 'C' ,'D'), colB = c(1,2,1,1,1))
someList <- list(A=20, B=30, C=40, D=50)
merge(smallFrame, melt(someList), by.x = 'colA', by.y = 'L1')

  colA colB value
1    A    1    20
2    A    2    20
3    B    1    30
4    C    1    40
5    D    1    50

or, if you are really keen on assigning within smallFrame and efficiently, use data.table

library(data.table)
smallDT <- data.table(smallFrame, key = 'colA')
someDT <- data.table(melt(someList), key = 'L1')

# left join smallDT and someDT, assigning the `value` column by reference
# within smallDT as the column `newColumn`
smallDT[someDT, newColumn := value]




smallDT
   colA colB newColumn
1:    A    1        20
2:    A    2        20
3:    B    1        30
4:    C    1        40
5:    D    1        50