Learning Objectives

This week, students will:

• Learn the structure of loops

Practice Objectives

• Vectorized functions
• Creating functions

Review

• Question from last class: To get all the functions within a family, we can use the function methods()

methods(is)
methods(summary)
methods(summarize)

Setup your RStudio project (5 min)

• 🎗️ Structuring your files into a project is a best practice for good data science!
• Open your RStudio project for the class; I called mine “spring2023”.
• Open a new file, name it “loops.Rmd”, and save it to your “documents” folder.

Day 1

Looping by values in an object

• The basic structure of a for loop
• For example:

  # If we have an initial vector of values
  lengths <- c(13.3, 15, 100)
  # We can run code using each value stored in a vector
  for (value in lengths) {
  mass <- 0.73 * value^2
  print(mass)
  # we can't use return() in for loops
  }
  

• Exercises 1 and 2: Basics of for loops (5 min)

Looping by index

• An index in R is the numeric position of values inside a data structure in R.
• For example:

  flowers <- c("lilacs", "daisies", "jasmins")
  flowers[2]
  

• To access an element in the vector, we need to use a number as index inside square brackets
• That returns the value that is in the position given by the number.
• We can use numbers as indices to loop over values inside a vector.

  for (i in 1:3) {
  print(i)
  print(flowers[i])
  }
  

• Exercise 3: Basics of for loops 5 min)

Storing results from loops

• So far we have just printed results from equations running inside our loops.
• Usually, we need to save the results of running a for loop, so that we can use them later.
• When we are using a function, we use an assignment to store the results from the function.

  my_results <- 0.73 * lengths^2
  

• In loops we do not have that option. We can’t do:

  my_result <- for (variable in vector) {
  }
  

• The only way to save results from each iteration of the loop is by saving them into an empty object.
• To create an empty vector, we use the function vector().
• For example, run the following loop:

  flowers <- c("lilacs", "daisies", "jasmins")
  for (i in 1:length(flowers)) {
  upper <- toupper(flowers[i])
  print(upper)
  }
  

• Then, create an empty vector to store results

  my_results <- vector(mode = "character", length = length(flowers))
  my_results
  

• Finally, use this empty vector and indices inside a loop to store results:

  for (i in 1:length(flowers)) {
  upper <- toupper(flowers[i])
  my_results[i] <- upper
  }
  my_results
  

• Exercise 4: Basics of for loops (5 min)

Looping over multiple objects

• When we have multiple vectors, we can use numeric indices to use values from all vectors at a time within a loop.
• Exercise 5: Basics of for loops (5 min)

Day 2

Looping using functions

Exercise 6: Mass of dinosaurs with loops (30 min)

Looping over files

Practical uses of for loops

Exercise 7: Automatic analysis of muliple files (30 min)