Loop and conquer

Before you start: branches; for loops; returned list results.
Setup: Save practice in an R script; no submission. Try the eight tasks before opening hints/solutions.
Your check: Construct and compare stored vector/list results across all branches. Practise in the unit summary.

This worksheet provides practice with conditional statements and loops.

Things you need for this worksheet

  • R — the interpreter can be installed on any operating system.
  • RStudio — we recommend using RStudio for (interactive) programming with R.

Loop till you drop

This is a self-study exercise; no submission is required. Work through the tasks in R or RStudio and save your code in an R script (.R). If you already use R Markdown, you can use a .Rmd document and render it to HTML instead:

  1. Implement an if-then-else statement that prints “larger” if the number provided as variable n is larger than 1 and “equal or smaller” otherwise.
  2. Extend a copy of the above statement (i.e. copy the entire if-then-else statement and include it a second time in your script in order to preserve both versions) that prints “equal” and “smaller” separately, in addition to “larger”.
  3. Implement an if-then-else statement that prints “even” if the number provided as variable n is even and prints “odd” otherwise.
  4. Place a copy of the extended larger/equal/smaller statement in a for loop. Iterate over values of n that are less than 1, equal to 1, and greater than 1 to demonstrate all three branches.
  5. Extend a copy of the loop so that the labels (“larger”, “equal”, or “smaller”) are stored in a vector instead of being printed during each iteration. Print the vector after the loop.
  6. Extend a copy of the modified loop to store the results in a list instead of a vector. Print the list after the loop.
  7. Change the modified loop to use lapply() instead of a for loop. Save the returned results in a variable and print them after the call.
  8. Finally, add one line after the call to flatten the returned list into a vector. Leave the call itself unchanged.

Save your work in a local project folder. Run the code again to check all branches of your conditions, inspect the stored results, and compare the list and vector outputs. If you chose R Markdown, render the document to check that it runs from beginning to end.

Hints and expected results

Use values <- c(0, 1, 2) for the three-way comparisons. Expect "smaller", "equal", "larger" in that order. For the parity task, use whole numbers; a remainder of zero after division by 2 identifies an even integer. The vector/list tasks should preserve one result per input value.

Hint for tasks 1–3

An if tests one value. Compare n > 1, then n == 1 where needed. For parity, use n %% 2 == 0; the input should be an integer-valued number.

Hint for tasks 4–8

Use seq_along(values) when writing results by position. Create a character vector or list before filling it. lapply() collects returned labels in a list; unlist() flattens this simple list of single strings into a vector.

One worked solution to tasks 1–8

Tasks 1–3: branches

n <- 2
if (n > 1) print("larger") else print("equal or smaller")

n <- 1
if (n > 1) {
  print("larger")
} else if (n == 1) {
  print("equal")
} else {
  print("smaller")
}

n <- 2
if (n %% 2 == 0) print("even") else print("odd")

These calls print larger, equal and even. Also try 0 and 1 in the parity test; they give even and odd. Keep the three-way comparison at the boundary 1, not at 0.

Task 4: repeat all branches

values <- c(0, 1, 2)
for (n in values) {
  if (n > 1) print("larger") else if (n == 1) print("equal") else print("smaller")
}

Tasks 5–6: collect the results

labels <- character(length(values))
for (i in seq_along(values)) {
  n <- values[i]
  if (n > 1) labels[i] <- "larger" else if (n == 1) labels[i] <- "equal" else labels[i] <- "smaller"
}
labels
label_list <- vector("list", length(values))
for (i in seq_along(values)) {
  n <- values[i]
  if (n > 1) label_list[[i]] <- "larger" else if (n == 1) label_list[[i]] <- "equal" else label_list[[i]] <- "smaller"
}
label_list

The labels are the same, but labels is character and label_list is a list. [[i]] stores one component in the list.

Tasks 7–8: return and flatten

applied <- lapply(values, function(n) {
  if (n > 1) return("larger")
  if (n == 1) return("equal")
  return("smaller")
})
flattened <- unlist(applied)
identical(labels, flattened)
identical(label_list, applied)

Both comparisons return TRUE. The loop and lapply() are alternative ways to collect the same labels; flattening changes the structure, not the label meanings.

Practise writing a reusable function

Without copying the solution, turn the three-way comparison into a function with arguments n and threshold, defaulting to 1. For this task, n is one non-missing numeric value. Test smaller/equal/larger values and a different threshold, then call your function with lapply().

Compare a function solution 
classify_number <- function(n, threshold = 1) {
  if (n > threshold) return("larger")
  if (n == threshold) return("equal")
  return("smaller")
}
lapply(c(0, 1, 2), classify_number)
lapply(c(0, 1, 2), classify_number, threshold = 2)

The first result contains smaller/equal/larger; the second contains smaller/smaller/equal. This simple function assumes one known numeric value per call. Before extending it to missing values or empty input, decide whether to return a missing label or report an error; neither policy follows automatically from this example.

Ready to continue: run your saved script in a fresh R session and explain why its list/vector comparisons succeed. There is no submission or examination.

Updated: