🎒 R Arrays: Your Magic Backpack of Data!

The Story of Arrays

Imagine you have a magic backpack that can hold many things in neat little compartments. That’s exactly what an array is in R!

Think of it like this: You have a box of crayons. Each crayon has its own spot, numbered 1, 2, 3… You can grab any crayon by saying “Give me crayon number 3!” That’s how arrays work!

🎨 What is an Array?

An array is like a multi-shelf storage box.

Key Idea: Arrays store the same type of things (all numbers, all words) in organized compartments you can access by number.

🏗️ Creating Arrays

Method 1: The array() Function

This is your main tool for building arrays!

# Simple 1D array (like a row of lockers)
my_array <- array(1:6, dim = c(6))
# Result: 1 2 3 4 5 6

# 2D array (like a grid of boxes)
matrix_array <- array(1:6, dim = c(2, 3))
# Result:
#      [,1] [,2] [,3]
# [1,]    1    3    5
# [2,]    2    4    6

What’s happening?

• 1:6 = The stuff to put inside (numbers 1 through 6)
• dim = c(2, 3) = The shape: 2 rows, 3 columns

Method 2: 3D Arrays (The Magic Cube!)

# A 3D array is like stacked grids
cube <- array(1:12, dim = c(2, 3, 2))
# Creates 2 layers, each with 2 rows & 3 cols

Think of it as two sheets of paper, each with a 2×3 grid drawn on it!

graph TD
    A[3D Array] --> B[Layer 1]
    A --> C[Layer 2]
    B --> D[Row 1: 1, 3, 5]
    B --> E[Row 2: 2, 4, 6]
    C --> F[Row 1: 7, 9, 11]
    C --> G[Row 2: 8, 10, 12]

Method 3: Using dim() on a Vector

You can transform a simple list into an array!

# Start with a vector
my_vector <- c(10, 20, 30, 40, 50, 60)

# Add dimensions to make it an array
dim(my_vector) <- c(2, 3)

# Now it's a 2x3 array!

🎯 Pro Tip: R fills arrays column by column (top to bottom, then left to right), not row by row!

🔧 Array Operations

Now let’s learn how to use your magic backpack!

1. Accessing Elements (Finding Your Stuff)

# Create a 2x3 array
arr <- array(c(5, 10, 15, 20, 25, 30),
             dim = c(2, 3))

# Get one item: row 1, column 2
arr[1, 2]  # Returns: 15

# Get entire row 1
arr[1, ]   # Returns: 5 15 25

# Get entire column 2
arr[, 2]   # Returns: 15 20

Think of it like: “I want the item at Row 1, Shelf 2!”

2. Modifying Elements (Changing Things)

# Change one value
arr[1, 1] <- 100
# Now position [1,1] holds 100!

# Change an entire row
arr[2, ] <- c(7, 8, 9)
# Row 2 is now: 7, 8, 9

3. Math with Arrays (The Fun Part!)

Arrays love math! You can do operations on everything at once.

arr1 <- array(1:4, dim = c(2, 2))
arr2 <- array(5:8, dim = c(2, 2))

# Add them together
arr1 + arr2
# Each position adds up!

# Multiply everything by 2
arr1 * 2
# Every number doubles!

graph TD
    A["arr1<br>[1,3]<br>[2,4]"] --> |"+ arr2"| B["Result<br>[6,10]<br>[8,12]"]
    C["arr2<br>[5,7]<br>[6,8]"] --> B

4. Useful Array Functions

5. The apply() Magic

Want to do something to each row or column? Use apply()!

arr <- array(1:6, dim = c(2, 3))

# Sum each row (MARGIN = 1)
apply(arr, 1, sum)
# Returns: 9 12

# Sum each column (MARGIN = 2)
apply(arr, 2, sum)
# Returns: 3 7 11

Remember:

• MARGIN = 1 → Do it to ROWS
• MARGIN = 2 → Do it to COLUMNS

🌟 Quick Summary

💡 Why Arrays Matter

Arrays are the building blocks for:

• 📊 Data tables
• 🖼️ Images (pixels in a grid!)
• 🎮 Game boards
• 📈 Scientific data

You’re now ready to organize data like a pro! 🚀

🎯 Key Takeaways

1. Arrays = organized storage with numbered compartments
2. Create with array() - give it data and dimensions
3. Access with brackets - [row, column, layer]
4. R fills column-first - remember this quirk!
5. apply() is your friend for row/column operations

Now go fill those magic backpacks with data! 🎒✨