How to assign from a function which returns more than one value?

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Still trying to get into the R logic... what is the "best" way to unpack (on LHS) the results from a function returning multiple values?

I can't do this apparently:

R> functionReturningTwoValues <- function() { return(c(1, 2)) }
R> functionReturningTwoValues()
[1] 1 2
R> a, b <- functionReturningTwoValues()
Error: unexpected ',' in "a,"
R> c(a, b) <- functionReturningTwoValues()
Error in c(a, b) <- functionReturningTwoValues() : object 'a' not found

must I really do the following?

R> r <- functionReturningTwoValues()
R> a <- r[1]; b <- r[2]

or would the R programmer write something more like this:

R> functionReturningTwoValues <- function() {return(list(first=1, second=2))}
R> r <- functionReturningTwoValues()
R> r$first
[1] 1
R> r$second
[1] 2

--- edited to answer Shane's questions ---

I don't really need giving names to the result value parts. I am applying one aggregate function to the first component and an other to the second component (min and max. if it was the same function for both components I would not need splitting them).

16 Answers

Year 2021 and this is something I frequently use.

tidyverse package has a function called lst that assigns name to the list elements when creating the list. Post which I use list2env() to assign variable or use the list directly

library(tidyverse)
fun <- function(){
  a<-1
  b<-2
  lst(a,b)
}
list2env(fun(), envir=.GlobalEnv)#unpacks list key-values to variable-values into the current environment

This is only for the sake of completeness and not because I personally prefer it. You can pipe %>% the result, evaluate it with curly braces {} and write variables to the parent environment using double-arrow <<-.

library(tidyverse)
functionReturningTwoValues() %>% {a <<- .[1]; b <<- .[2]}

UPDATE: Your can also use the multiple assignment operator from the zeallot package:: %<-%

c(a, b) %<-% list(0, 1)

I will post a function that returns multiple objects by way of vectors:

Median <- function(X){
  X_Sort <- sort(X)
  if (length(X)%%2==0){
    Median <- (X_Sort[(length(X)/2)]+X_Sort[(length(X)/2)+1])/2
  } else{
    Median <- X_Sort[(length(X)+1)/2]
  }
  return(Median)
}

That was a function I created to calculate the median. I know that there's an inbuilt function in R called median() but nonetheless I programmed it to build other function to calculate the quartiles of a numeric data-set by using the Median() function I just programmed. The Median() function works like this:

  1. If a numeric vector X has an even number of elements (i.e., length(X)%%2==0), the median is calculated by averaging the elements sort(X)[length(X)/2] and sort(X)[(length(X)/2+1)].
  2. If Xdoesn't have an even number of elements, the median is sort(X)[(length(X)+1)/2].

On to the QuartilesFunction():

QuartilesFunction <- function(X){
X_Sort <- sort(X) # Data is sorted in ascending order

if (length(X)%%2==0){
  
  # Data number is even
  
  HalfDN <- X_Sort[1:(length(X)/2)] 
  HalfUP <- X_Sort[((length(X)/2)+1):length(X)]
  
  QL <- Median(HalfDN)
  QU <- Median(HalfUP)
  
  QL1 <- QL
  QL2 <- QL
  QU1 <- QU
  QU2 <- QU
  QL3 <- QL
  QU3 <- QU
  
  Quartiles <- c(QL1,QU1,QL2,QU2,QL3,QU3)
  names(Quartiles) = c("QL (1)", "QU (1)", "QL (2)", "QU (2)","QL (3)", "QU (3)")
  
} else{ # Data number is odd
  
  # Including the median
  
  Half1DN <- X_Sort[1:((length(X)+1)/2)] 
  Half1UP <- X_Sort[(((length(X)+1)/2)):length(X)]
  
  QL1 <- Median(Half1DN)
  QU1 <- Median(Half1UP)
  
  # Not including the median
  
  Half2DN <- X_Sort[1:(((length(X)+1)/2)-1)] 
  Half2UP <- X_Sort[(((length(X)+1)/2)+1):length(X)]
  
  QL2 <- Median(Half2DN)
  QU2 <- Median(Half2UP)
  
  # Methods (1) and (2) averaged
  
  QL3 <- (QL1+QL2)/2
  QU3 <- (QU1+QU2)/2
  
  Quartiles <- c(QL1,QU1,QL2,QU2,QL3,QU3)
  names(Quartiles) = c("QL (1)", "QU (1)", "QL (2)", "QU (2)","QL (3)", "QU (3)") 
}
return(Quartiles)
}

This function returns the quartiles of a numeric vector by using three methods:

  1. Discarding the median for the calculation of the quartiles when the number of elements of the numeric vector Xis odd.
  2. Keeping the median for the calculation of the quartiles when the number of elements of the numeric vector Xis odd.
  3. Averaging the results obtained by using methods 1 and 2.

When the number of elements in the numeric vector X is even, the three methods coincide.

The result of the QuartilesFunction() is a vector that depicts the first and third quartiles calculated by using the three methods outlined.

With R 3.6.1, I can do the following

fr2v <- function() { c(5,3) }
a_b <- fr2v()
(a_b[[1]]) # prints "5"
(a_b[[2]]) # prints "3"
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