Create new column based on 4 values in another column

You could use nested ifelse:

col2 <- ifelse(col1==1, "G",        ifelse(col1==2, "H",        ifelse(col1==3, "J",        ifelse(col1==4, "K",                        NA  )))) # all other values map to NA

In this simple case it's overkill, but for more complicated ones...

You have a special case of looking up values where the index are integer numbers 1:4. This means you can use vector indexing to solve your problem in one easy step.

First, create some sample data:

set.seed(1)dat <- data.frame(col1 = sample(1:4, 10, replace = TRUE))

Next, define the lookup values, and use [ subsetting to find the desired results:

values <- c("G", "H", "J", "K")dat$col2 <- values[dat$col1]

The results:

dat   col1 col21     2    H2     2    H3     3    J4     4    K5     1    G6     4    K7     4    K8     3    J9     3    J10    1    G

More generally, you can use [ subsetting combined with match to solve this kind of problem:

index <- c(1, 2, 3, 4)values <- c("G", "H", "J", "K")dat$col2 <- values[match(dat$col1, index)]dat   col1 col21     2    H2     2    H3     3    J4     4    K5     1    G6     4    K7     4    K8     3    J9     3    J10    1    G

There are a number of ways of doing this, but here's one.

set.seed(357)mydf <- data.frame(col1 = sample(1:4, 10, replace = TRUE))mydf$col2 <- rep(NA, nrow(mydf))mydf[mydf$col1 == 1, ][, "col2"] <- "A"mydf[mydf$col1 == 2, ][, "col2"] <- "B"mydf[mydf$col1 == 3, ][, "col2"] <- "C"mydf[mydf$col1 == 4, ][, "col2"] <- "D"   col1 col21     1    A2     1    A3     2    B4     1    A5     3    C6     2    B7     4    D8     3    C9     4    D10    4    D

Here's one using car's recode.

library(car)mydf$col3 <- recode(mydf$col1, "1" = 'A', "2" = 'B', "3" = 'C', "4" = 'D')

One more from this question:

mydf$col4 <- c("A", "B", "C", "D")[mydf$col1]