Evaluate expression in R data.table

Question

I have the following data.table:

> dt = data.table(expr = c("a + b", "a - b", "a * b", "a / b"), a = c(1,2,3,4), b = c(5,6,7,8))
> dt
    expr a b
1: a + b 1 5
2: a - b 2 6
3: a * b 3 7
4: a / b 4 8

My aim is to get the following data.table:

> dt
    expr a b ans
1: a + b 1 5   6
2: a - b 2 6  -4
3: a * b 3 7  21
4: a / b 4 8 0.5

I tried the following:

> dt[, ans := eval(expr)]
Error in eval(expr, envir, enclos) : object 'expr' not found

> dt[, ans := eval(parse(text = expr))]
Error in parse(text = expr) : object 'expr' not found

Any idea how can I calculate the ans column based on the expression in the expr column?

Answer 1

If your actual expressions describe calls to vectorized functions and are repeated many times each, this may be more efficient, since it only parses and evaluates each distinct expression one time:

f <- function(e, .SD) eval(parse(text=e[1]), envir=.SD)
dt[, ans:=f(expr,.SD), by=expr, .SDcols=c("a", "b")]
#     expr a b  ans
# 1: a + b 1 5  6.0
# 2: a - b 2 6 -4.0
# 3: a * b 3 7 21.0
# 4: a / b 4 8  0.5

Answer 2

Really, there are a bunch of challenges for vectorization in such a setup. eval doesn't expect to run on a vector of expressions nor is it set up to iterate over a vector of environments by default. Here I define a helper function to wrap much of the iteration

calc <- function(e, ...) {
   run<-function(x, ...) {
       eval(parse(text=x), list(...)) 
   }
   do.call("mapply", c(list(run, e), list(...)))
}

dt[, ans:=calc(expr,a=a,b=b)]

which returns

    expr a b  ans
1: a + b 1 5  6.0
2: a - b 2 6 -4.0
3: a * b 3 7 21.0
4: a / b 4 8  0.5

as desired. Note that you'll need to name the parameters in the call to calc() so it knows which column to map to which variable.