Chapter 22: R For Loop

Part 1: What is a For Loop?

A for loop is a control structure that repeats a block of code for each element in a sequence or collection. It’s called a “for” loop because it runs “for” each item in a set.

The Basic Syntax

• variable: A name you choose to represent the current element

• sequence: A vector, list, or other collection to iterate over

• { }: The code block that runs for each element

A Simple Example

Output:

Let’s trace through what happens:

1. i takes the value 1, runs the code inside

2. i takes the value 2, runs the code inside

3. Continues until i takes the value 5

4. After the last iteration, the loop ends

Part 2: Different Types of Sequences

For loops can iterate over many different types of sequences:

1. Numeric Sequences

2. Character Vectors

Output:

3. Lists

4. Data Frame Columns

Part 3: Accessing Index and Value

Sometimes you need both the position (index) and the value:

Using 1:length(sequence)

Output:

Using seq_along() – The Safe Way

The seq_along() function is safer than 1:length() because it handles empty vectors correctly:

Part 4: Building Results with For Loops

A common pattern is to build a result vector or data frame inside a loop:

Building a Vector

Output:

Better Approach: Pre-allocate for Speed

For large loops, pre-allocating memory is much faster:

Building a Data Frame

Output:

Part 5: Nested For Loops

Sometimes you need loops inside loops – like processing rows and columns of a matrix:

Basic Nested Loop

Creating a Multiplication Table

Output:

More Complex Nested Example: Student Grades

Part 6: Control Statements in For Loops

Using break to Exit Early

The break statement stops the loop immediately:

Output:

Using next to Skip Iterations

The next statement skips to the next iteration:

Output:

Part 7: Real-World Examples

Example 1: Data Cleaning

Example 2: Financial Calculator – Compound Interest

Example 3: Text Analysis

Example 4: Simulation – Dice Rolling

Example 5: Stock Price Simulation

Part 8: For Loops vs. Vectorized Operations

When Vectorization is Better

R is optimized for vectorized operations, which are often much faster than loops:

When For Loops Are Necessary

Sometimes for loops are the right tool:

Part 9: Common Mistakes and How to Avoid Them

Mistake 1: Modifying the Iteration Variable

Mistake 2: Growing Objects Inefficiently

Mistake 3: Off-by-One Errors

Mistake 4: Forgetting to Initialize Results

Mistake 5: Using For Loops When Vectorized Solutions Exist

Part 10: Advanced For Loop Patterns

Pattern 1: Using Lists of Functions

Pattern 2: Parallel Processing with For Loops

Pattern 3: Recursive Directory Processing

Summary: The For Loop Philosophy

For loops are your tool for iterating over known sequences. Master these patterns:

1. Basic iteration – Loop over vectors and lists

2. Index-based access – Use indices when you need position

3. Building results – Accumulate results in pre-allocated structures

4. Nested loops – Handle multi-dimensional data

5. Control flow – Use break and next for flexible execution

When to use for loops:

• Iterating over files or external resources

• When each iteration depends on previous results

• Complex processing that can’t be vectorized

• Learning and teaching programming concepts

When NOT to use for loops:

• Simple mathematical operations on vectors (use vectorization)

• When apply functions (lapply, sapply, etc.) are more appropriate

• Performance-critical code with large datasets

Best practices:

• Always pre-allocate result vectors/data frames

• Use seq_along() instead of 1:length()

• Consider vectorized alternatives first

• Keep loop bodies simple and focused

• Comment complex logic inside loops

The for loop is like a reliable conveyor belt – it will process each item exactly once, in order, and you can trust it to do the same thing to every item. Master it, and you’ll have a fundamental tool for automating repetitive tasks in R.

Would you like me to elaborate on any specific aspect of for loops or explore more complex real-world examples?