In a previous exercise 3.3.2 you wrote the iq_classification(score) function in a way it can handle score vectors with lengths greater than 1 using the ifelse function. This ifelse is perfect for vectorizing a very specific subset of functions (if-statements), a more uniform way could be using a for-loop:

Original function:

iq_classification <- function(score){
  if(score >= 130){
      "Very superior"
  } else {
      "Not very superior"
  }
}

Vectorized function with for-loop:

iq_classification_for <- function(scores){
  results <- c()
  for(score in scores){
    if(score >= 130){
        results <- append(results, "Very superior")
    } else {
        results <- append(results, "Not very superior")
    }
  }
  results
}

For loops are very usefull and sometimes inevitable but for most cases R has provided functions to avoid for-loops. These functions tend to be faster and shorter to write. The apply family is a widely used set of functions that can be used to replace for loops.

All these functions are meant to vectorize functions that normally can’t handle vectors with a length greater than 1. Most of these fall out of scope for this basic introduction but there is one in particular that will be very handy, the sapply() function.

Exercise

• Write a wrapper function iq_classification_wrapper that vectorizes the original iq_classification function using the sapply function (This wrapper function should accept vectors with lengts greater than 1).

  Wrapper functions

  A wrapper function is a function whose main purpose is to call a second function with little or no additional computation.

  Avoid duplication of effort

  We have written the original iq_classification(score) function for you. This function returns the corresponding IQ category for a given score.