update one column twice in a data.table efficient in R

Question

I have a data table that looks like this:

DT <- data.table(Zeit = c(0.024, 0.4, 0.05),
                 Gier = c(1, 2, 3),
                 GierVZ = c(1, 0, 1),
                 Quer = c(2, 4, 6))

Now I want to update and add some columns to this data table. But I am not able to update Gier twice because it would create a duplicate and get an error.

DT[, ':='(Zeit   = round(Zeit, digits = 2),
          Gier   = replace(Gier, Gier == 163.83, NA),
          GierVZ = factor(GierVZ, levels = c(0, 1), labels = c("positiv", "negativ")),
          Quer   = Quer * 9.81,
          Gier   = ifelse(GierVZ == "negativ", Gier * -1, Gier))]

How can I avoid this in general and still create some readable fast code? I am sure there is an easy answer to this. But I am kind of a newbie to data tables and I think (at least at the moment) it is not that intuitive like dplyr, but it is much faster for my big data.

Answer 1

You could evaluate Gier in curly braces:

DT[, ':='(Zeit   = round(Zeit, digits = 2),
          Gier   = {Gier[Gier == 163.83] <- NA; ifelse(GierVZ, -Gier, Gier)},
          GierVZ = factor(GierVZ, levels = c(0, 1), labels = c("positiv", "negativ")),
          Quer   = Quer * 9.81)]