Intermediate R II: Iteration and more functions

Session 10

October 1, 2024

Learning objectives

• Write a more advanced function
• Set up an analysis with function and analysis scripts
• Use iteration to streamline workflows involving functions

When should I write my own function?

• Standardized procedures done many times
• Discrete chunks of a workflow
• Code used by multiple scripts or at multiple points in a workflow

When should I leave code in a script?

• Single-use, highly-customized code (e.g. a plot)
• Code that is changing a lot
• Code that tells the story of your analysis

Questions to ask yourself

• Do I find myself typing the same code over and over?
• Am I copy-pasting and changing a single variable/character?
• Does this code distract from the readability of a script?
• Is there an existing function I could pull from an R package?

Coding time

Important

Make sure you are in the right project and on an appropriate branch!

Coding time

• Review sample analysis to decide what could be a function
• Organize this analysis into analysis and function scripts

Iteration

Iteration

• Iteration allows you to repeat the same process many times on different objects.
• for loops:
  • Run sequentially
  • Easy to write and read
  • Slower, can be inefficient
• purrr::map:
  • Can run in parallel
  • Fairly readable
  • More efficient

Anatomy of for loops

for(<thing> in <some things>) {
  <do something with or to the thing>
}

for(i in 1:10) {
  print(i^2)
}

Storing the output of for loops

squares <- vector(length = 10)

for(i in 1:10){
  squares[i] <- i^2
}

Anatomy of purrr::map

purrr::map(<some things>, <a function>)

purrr::map(1:10, \(x) x^2)

Storing the output of purrr::map

purr_squares <- purrr::map(1:10, \(x) x^2)

Coding time

• Practice using a for loop and a map statement to apply our function to each island in turn.

Resources

• R4DS on iteration
• purrr and furrr documentation