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Luckily, you can write functions that take in more than one parameter by defining as many parameters as needed, for example: def function_name(data_1, data_2):
The apply() function lets us apply a function to the rows or columns of a matrix or data frame. This function takes matrix or data frame as an argument along with function and whether it has to be applied by row or column and returns the result in the form of a vector or array or list of values obtained.
Yes. See the Examples section of ? optim and ? integrate for some R functions that accept other functions as arguments.
Just pass var2 as an extra argument to one of the apply functions.
mylist <- list(a=1,b=2,c=3)
myfxn <- function(var1,var2){
var1*var2
}
var2 <- 2
sapply(mylist,myfxn,var2=var2)
This passes the same var2 to every call of myfxn. If instead you want each call of myfxn to get the 1st/2nd/3rd/etc. element of both mylist and var2, then you're in mapply's domain.
If your function have two vector variables and must compute itself on each value of them (as mentioned by @Ari B. Friedman) you can use mapply as follows:
vars1<-c(1,2,3)
vars2<-c(10,20,30)
mult_one<-function(var1,var2)
{
var1*var2
}
mapply(mult_one,vars1,vars2)
which gives you:
> mapply(mult_one,vars1,vars2)
[1] 10 40 90
To further generalize @Alexander's example, outer is relevant in cases where a function must compute itself on each pair of vector values:
vars1<-c(1,2,3)
vars2<-c(10,20,30)
mult_one<-function(var1,var2)
{
var1*var2
}
outer(vars1,vars2,mult_one)
gives:
> outer(vars1, vars2, mult_one)
[,1] [,2] [,3]
[1,] 10 20 30
[2,] 20 40 60
[3,] 30 60 90
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