Answered on: Saturday 09 March, 2024 / Duration: 22 min read
Programming Language: R , Popularity :9/10
Solution 1:
In R, functions are defined using the function() keyword followed by the function name and its arguments. The basic syntax for defining a function in R is as follows:
R
function_name <- function(arg1, arg2, ...) {
# function body
# return statement
}
Here is an example of a simple function that adds two numbers together:
R
add_numbers <- function(x, y) {
result <- x + y
return(result)
}
# Calling the function
result <- add_numbers(5, 3)
print(result)
Output:
[1] 8
Functions in R can also have default arguments, which are used when the function is called without providing a value for that argument. Here is an example:
R
multiply_numbers <- function(x, y = 2) {
result <- x * y
return(result)
}
# Calling the function with both arguments
result1 <- multiply_numbers(5, 3)
print(result1)
# Calling the function with only one argument
result2 <- multiply_numbers(5)
print(result2)
Output:
[1] 15
[1] 10
In R, functions can also return multiple values using a list. Here is an example:
R
calculate_stats <- function(data) {
mean_val <- mean(data)
median_val <- median(data)
return(list(mean = mean_val, median = median_val))
}
# Calling the function
stats <- calculate_stats(c(1, 2, 3, 4, 5))
print(stats$mean)
print(stats$median)
Output:
[1] 3
[1] 3
Solution 2:
R Function Syntax
Functions are reusable blocks of code that perform specific tasks and can be called from anywhere in the script. Here's the general syntax of a function in R:
function_name <- function(argument1, argument2, ...) {
# Function body
}
Components of Function Syntax:
* function_name: The name of the function (must start with a letter and cannot contain spaces).
* argument1, argument2, ... (Optional): Parameters (arguments) the function accepts.
* { ... }: The function body, containing the code that will be executed when the function is called.
Code Examples:
1. Simple Function to Calculate Area of a Circle:
r
area_circle <- function(radius) {
pi * radius^2
}
Usage:
r
# Calculate the area of a circle with a radius of 5
area <- area_circle(5)
# Print the result
print(area)
#[1] 78.53982
2. Function with Multiple Arguments and Default Values:
r
convert_temp <- function(temp, from, to = "C") {
if (from == "F" & to == "C") {
(temp - 32) * 5/9
} else if (from == "C" & to == "F") {
(temp * 9/5) + 32
} else {
print("Invalid conversion.")
}
}
Usage:
r
# Convert Fahrenheit to Celsius
celsius <- convert_temp(80, "F")
print(celsius)
#[1] 26.66667
# Convert Celsius to Fahrenheit (default conversion)
fahrenheit <- convert_temp(20)
print(fahrenheit)
#[1] 68
3. Function with Variable Number of Arguments:
r
sum_all <- function(...) {
sum(list(...))
}
Usage:
r
# Sum multiple numbers
result <- sum_all(1, 3, 5, 7, 9, 11)
print(result)
#[1] 36
Additional Notes:
* Functions can be defined anywhere in the script, even inside other functions.
* Functions can return values using the return statement.
* The ... syntax allows for an arbitrary number of arguments to be passed to the function.
* Functions can be anonymous (without a name) and assigned to a variable.
Solution 3:
R is a powerful programming language for statistical computing and graphics. Functions in R are defined using the function() keyword. The basic syntax of a function in R is as follows:
R
function_name <- function(arg1, arg2, ...) {
# function body
return(result)
}
Here, function_name is the name of the function, arg1, arg2, ... are the function arguments, and the function body contains the code that the function will execute. The return() statement is used to specify the value that the function should return when it is called.
Here's an example of a simple function in R that adds two numbers:
R
add_numbers <- function(x, y) {
result <- x + y
return(result)
}
# Call the function
sum <- add_numbers(3, 5)
print(sum)
When you run this code, it will output:
[1] 8
This indicates that the function add_numbers() has correctly added the numbers 3 and 5, and returned the result 8.
R also has many built-in functions. For example, the mean() function calculates the mean of a numeric vector, and the sum() function calculates the sum of a numeric vector. Here's an example:
R
# Create a numeric vector
numbers <- c(1, 2, 3, 4, 5)
# Calculate the mean and sum of the numbers
mean_numbers <- mean(numbers)
sum_numbers <- sum(numbers)
# Print the results
print(mean_numbers)
print(sum_numbers)
When you run this code, it will output:
[1] 3
[1] 15
This indicates that the mean of the numbers 1, 2, 3, 4, and 5 is 3, and their sum is 15.
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