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

问题

I have the following data.table

x = structure(list(f1 = 1:3, f2 = 3:5), .Names = c(\"f1\", \"f2\"), row.names = c(NA, -3L), class = c(\"data.table\", \"data.frame\"))

I would like to apply a function to each row of the data.table. The function func.test uses args f1 and f2 and does something with it and returns a computed value. Assume (as an example)

func.text <- function(arg1,arg2){ return(arg1 + exp(arg2))}

but my real function is more complex and does loops and all, but returns a computed value. What would be the best way to accomplish this?

回答1:

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))]

回答2:

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(.(f1, f2), func.text)]

回答3:

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) 

来源：https://stackoverflow.com/questions/25431307/r-data-table-apply-function-to-rows-using-columns-as-arguments