R data.table apply function to rows using columns as arguments

The best way is to write a vectorized function, but if you can't, then perhaps this will do:

x[, func.text(f1, f2), by = seq_len(nrow(x))]

The most elegant way I've found is with mapply:

x[, value := mapply(func.text, f1, f2)]
x
#    f1 f2    value
# 1:  1  3 21.08554
# 2:  2  4 56.59815
# 3:  3  5 151.4132

Or with the purrr package:

x[, value := purrr::pmap_dbl(.(f1, f2), func.text)]

We can define rows with .I function.

dt_iris <- data.table(iris)
dt_iris[, ..I := .I]

## Let's define some function
some_fun <- function(dtX) {
    print('hello')
    return(dtX[, Sepal.Length / Sepal.Width])
}

## by row
dt_iris[, some_fun(.SD), by = ..I] # or simply: dt_iris[, some_fun(.SD), by = .I]

## vectorized calculation
some_fun(dt_iris)