Exercise 03: R Functions

Creating Custom Functions

1. Write a function called fahrenheit_to_celsius that converts a temperature from Fahrenheit to Celsius.

• Formula: C = \frac{(F - 32) \times 5}{9}
• Test your function with F = 98.6.

fahrenheit_to_celsius <- function(temp_f) {
  return((temp_f - 32) * 5 / 9)
}
fahrenheit_to_celsius(temp_f = 98.6)

2. Create a function called circle_area that calculates the area of a circle given its radius.

• Formula: A = \pi \times r^2
• Use the built-in constant pi in R and test the function with r = 5.

# r is the circle radius
circle_area <- function(r){
  return(pi * r^2) 
}
circle_area(r = 5)
circle_area(5) # 5 assign to r

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Piping

1. Transform the following code into a pipe-based version:

result <- filter(mtcars, hp > 100)
result <- arrange(result, desc(mpg))
result <- select(result, hp, mpg)
result

mtcars |> 
  filter(hp > 100) |> 
  arrange(desc(mpg)) |> 
  select(hp, mpg)

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Debugging Functions

1. Identify and correct the mistake in the following code:

df |> mutate(
  a = (a - mean(a, na.rm = TRUE)) / sd(a),
  b = (b - mean(a, na.rm = TRUE)) / sd(b) # a should be changed to b
)

2. Rewrite the code by creating a custom function standardized() to avoid code repetition.

standardized <- function(x){
  return((x - mean(x, na.rm = TRUE)) / sd(x))
}
df |> mutate(
  a = standardized(a),
  b = standardized(b)
)

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Arguments in Functions

1. Create a function greet that takes two arguments, name (default = “World”) and punctuation (default = “!”). The function should return a greeting message.

• Example: greet("Alice", "?") should return "Hello, Alice?".

greet <- function(name = "World", punctuation = "!") {
  paste0("Hello, ", name, punctuation)
}
greet(name = "Alice", punctuation = "?")

2. Test the sum() function by passing named arguments (x = 3, y = 5) and explain how the function handles them.

sum(x = 3, y = 5)
sum(3, 5)
sum(c(3, 5))
# mean(x = 3, 5)
# mean(c(3, 5))

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Function Scope

1. Explain why the following code throws an error:

add <- function(x, y) {
  result <- x + y # beacuase result is in the local scope
  return(result)
}
add(5, 3)
result  # Error

2. Modify the code to make the variable result accessible outside the function.

add <- function(x, y) {
  result <<- x + y # beacuase result is in the local scope
  return(result)
}
add(6, 3)
result

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Flexible Arguments

1. Write a function multiply_all() that accepts a variable number of arguments and multiplies all the numbers together. Test your function with multiply_all(2, 3, 4).

multiply_all <- function(x, y, z) { # flexible arguments
  x * y * z
}
multiply_all(2, 3, 4)

multiply_all_flexible <- function(...) {
  prod(c(...))
}
multiply_all_flexible(1, 2, 3)
multiply_all_flexible(1, 2, 3, 5)
multiply_all_flexible(1, 2, 3, 5, 8)
multiply_all_flexible(c(1, 2, 3, 5, 8))

1. Investigate the mean() function by using the help page. Explain why it can accept additional arguments like y in the code below:

mean(x = c(1, 2, 3), y = 3) # because y is flexible argument. It is not included into calculation of mean

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Nested Functions

1. Write a function rect_prism_volume() that calculates the volume of a rectangular prism given its length, width, and height. Inside this function, create another function rect_area() to calculate the base area.

   • The formula for the volume of a rectangular prism is:

     V = A_b \times h

     A_b = l \times w

     where:

     • V = Volume of the rectangular prism,

     • A_b = base area

       • l = Length,

       • w = Width,

     • h = Height.

# the first function
rect_area <- function(l, w){
  A_base = l * w
  return(A_base)
}

# the second function that contains the first function
rect_prism_volume <- function(l, w, h){
  return(rect_area(l, w) * h)
}

1. Test your function with length = 5, width = 3, height = 4.

rect_prism_volume(l =5, w = 3, h = 4)

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Rescale Function

1. Create a custom function rescale() that rescales a numeric vector to the range 0 to 1.

• Formula: x_{\text{scaled}} = \frac{x - \min(x)}{\max(x) - \min(x)}

rescale <- function(x){
  res = (x - min(x)) / (max(x) - min(x))
  return(res)
}

2. Use your rescale() function to rescale the columns of the following data frame:

set.seed(1234)
df <- tibble(
 a = rnorm(5),
 b = rnorm(5),
 c = rnorm(5)
)
df

df |> 
  mutate(
    a = rescale(a),
    b = rescale(b),
    c = rescale(c)
  )