Functions in R: Returning Multiple Values Within the Same Function

In R programming language, a function is a block of code that can be executed multiple times from different parts of your program. Functions are an essential part of any program as they allow you to reuse code and make your programs more modular and maintainable.

One common question when working with functions in R is how to return multiple values within the same function. In this article, we will explore how to achieve this using a technique called returning lists in R.

The Problem

When defining a function in R, you can only return one value from that function. This can be frustrating if you want to return multiple values as output of your function.

Consider an example where you have a function calculate_statistics which calculates the mean, median, and standard deviation of a given dataset. You might want to return these statistics to use them in further calculations or print them out:

# Define a sample dataset
dog_biscuits <- c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
tail_wags <- c(0, 0, 1, 3, 8, 13, 14, 12, 15, 16, 14)

# Define a function to calculate statistics
calculate_statistics <- function(x) {
  # Calculate the mean of x
  z1 <- mean(x)
  
  # Calculate the median of x
  z2 <- median(x)
  
  # Calculate the standard deviation of x
  z3 <- sd(x)
}

# Call the function and assign output to variables outside the function
b <- calculate_statistics(tail_wags)

# Print out b which should contain all three statistics
print(b)

As you can see, b only contains one value - the standard deviation of tail_wags. However, what if we want to return multiple values as output from our function? This is where returning lists comes in.

Returning Lists

In R, a list is an object that stores a collection of values. A list can contain other lists or even other types of objects like vectors, data frames, etc.

To return multiple values as output from your function, you need to create a list and store each value within the list. Here’s how you can modify our previous example to achieve this:

# Define a sample dataset
dog_biscuits <- c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
tail_wags <- c(0, 0, 1, 3, 8, 13, 14, 12, 15, 16, 14)

# Define a function to calculate statistics
calculate_statistics <- function(x) {
  # Calculate the mean of x
  z1 <- mean(x)
  
  # Calculate the median of x
  z2 <- median(x)
  
  # Calculate the standard deviation of x
  z3 <- sd(x)
  
  # Create a list and return it as output from our function
  return(list(mean = z1, median = z2, standard_deviation = z3))
}

# Call the function and assign output to variables outside the function
b <- calculate_statistics(tail_wags)

# Print out b which should contain all three statistics
print(b)

As expected, b now contains a list of three values: the mean, median, and standard deviation of tail_wags.

Creating Lists Manually

In addition to using R’s built-in list() function, you can also create lists manually by enclosing your elements in parentheses or brackets.

Here’s an example:

# Define a sample dataset
dog_biscuits <- c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
tail_wags <- c(0, 0, 1, 3, 8, 13, 14, 12, 15, 16, 14)

# Define a function to calculate statistics
calculate_statistics <- function(x) {
  # Calculate the mean of x
  z1 <- mean(x)
  
  # Calculate the median of x
  z2 <- median(x)
  
  # Calculate the standard deviation of x
  z3 <- sd(x)
  
  # Create a list manually using parentheses or brackets
  my_statistics <- (z1, z2, z3)
  
  return(my_statistics)
}

# Call the function and assign output to variables outside the function
b <- calculate_statistics(tail_wags)

# Print out b which should contain all three statistics
print(b)

This code produces the same result as before: a list containing the mean, median, and standard deviation of tail_wags.

Best Practices for Returning Lists

When returning lists from functions in R, follow these best practices:

1. Be clear about what you’re returning: Make sure that your function’s output is well-documented to ensure other developers can understand its return values.
2. Use meaningful variable names: When creating a list, use meaningful variable names for each element to make it easier to access and manipulate the data.
3. Test thoroughly: Always test your functions with different inputs to ensure that they’re working as expected.

By following these best practices and using lists to return multiple values from your R functions, you can write more robust, efficient, and maintainable code.

Last modified on 2023-05-10