Arrays and Lists

An array (called a list in Python) is a data structure that stores multiple values under a single identifier. Arrays are essential for managing collections of data efficiently and are a key topic in GCSE Computer Science (AQA 3.2 / OCR J277 2.2).

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What Is an Array?

An array is an ordered collection of elements of the same data type, stored in contiguous memory locations. Each element is accessed by its index (position number).

Index	0	1	2	3	4
Value	"Alice"	"Bob"	"Charlie"	"Diana"	"Eve"

Key Point: In most programming languages (including Python), array indices start at 0. This is called zero-based indexing. In AQA pseudocode, indices also start at 0.

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Declaring Arrays

Pseudocode

names ← ["Alice", "Bob", "Charlie", "Diana", "Eve"]
scores ← [85, 72, 91, 64, 78]

Python

names = ["Alice", "Bob", "Charlie", "Diana", "Eve"]
scores = [85, 72, 91, 64, 78]

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Accessing Elements

Use the index to read or modify a specific element:

Pseudocode

OUTPUT names[0]       # Outputs: Alice
names[2] ← "Chris"   # Changes "Charlie" to "Chris"

Python

print(names[0])       # Output: Alice
names[2] = "Chris"    # Changes "Charlie" to "Chris"

Exam Tip: Attempting to access an index that does not exist (e.g. names[10] when the array only has 5 elements) causes an index out of bounds error.

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Array Length

To find out how many elements are in an array:

• Pseudocode: LEN(names) returns 5
• Python: len(names) returns 5

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Traversing an Array (Iterating Through Elements)

Using a FOR Loop with Index

for i in range(len(names)):
    print(names[i])

Using a FOR-EACH Loop

for name in names:
    print(name)

In pseudocode:

FOR EACH name IN names
    OUTPUT name
ENDFOR

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Array Structure Visualised

flowchart LR
    subgraph names["names array (length 5)"]
        direction LR
        I0["[0]<br/>Alice"]
        I1["[1]<br/>Bob"]
        I2["[2]<br/>Charlie"]
        I3["[3]<br/>Diana"]
        I4["[4]<br/>Eve"]
    end
    I0 --> I1 --> I2 --> I3 --> I4

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Common Array Operations

Adding Elements

names.append("Frank")     # Adds "Frank" to the end
names.insert(2, "Zara")   # Inserts "Zara" at index 2

Removing Elements

names.remove("Bob")       # Removes the first occurrence of "Bob"
names.pop(0)              # Removes and returns the element at index 0

Searching for an Element

if "Alice" in names:
    print("Found Alice")

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Working with Arrays: Practical Examples

Finding the Largest Value

scores = [85, 72, 91, 64, 78]
highest = scores[0]
for i in range(1, len(scores)):
    if scores[i] > highest:
        highest = scores[i]
print(f"Highest score: {highest}")

In pseudocode:

highest ← scores[0]
FOR i ← 1 TO LEN(scores) - 1
    IF scores[i] > highest THEN
        highest ← scores[i]
    ENDIF
ENDFOR
OUTPUT "Highest score: ", highest

Calculating the Average

total = 0
for score in scores:
    total += score
average = total / len(scores)
print(f"Average: {average}")

Linear Search

A linear search checks each element in turn until the target is found or the end of the array is reached:

def linear_search(arr, target):
    for i in range(len(arr)):
        if arr[i] == target:
            return i
    return -1  # Not found

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Two-Dimensional Arrays (2D Arrays)

A 2D array is an array of arrays — essentially a table with rows and columns.

grid = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
]
print(grid[1][2])  # Output: 6 (row 1, column 2)

In pseudocode:

grid[1][2]   # Accesses row 1, column 2

Traversing a 2D Array

for row in range(len(grid)):
    for col in range(len(grid[row])):
        print(grid[row][col], end=" ")
    print()

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Arrays vs Variables

Feature	Single Variable	Array
Stores	One value	Multiple values
Access	By name	By name and index
Use case	Single piece of data	Collection of related data
Efficiency	Fine for 1 value	Much better for many values

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Common Exam Mistakes

1. Forgetting zero-based indexing — the first element is at index 0, not 1.
2. Off-by-one errors when looping — range(len(arr)) goes from 0 to len(arr) - 1.
3. Confusing append with assignment — arr[5] = "x" fails if index 5 doesn't exist; use append instead.
4. Not handling the "not found" case in a search.

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Summary

• An array stores multiple values under one identifier, accessed by index.
• Indices start at 0 (zero-based indexing).
• Use loops to traverse arrays.
• Common operations: finding the largest/smallest, calculating totals/averages, searching.
• 2D arrays represent tables (rows and columns).

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Extended Worked Examples

Example 1: Finding the minimum value

temperatures = [12, 7, 15, -2, 9, 4, -5, 18]
lowest = temperatures[0]
for i in range(1, len(temperatures)):
    if temperatures[i] < lowest:
        lowest = temperatures[i]
print(f"Lowest temperature: {lowest}")

Trace:

i	temperatures[i]	lowest
0 (init)	—	12
1	7	7
2	15	7
3	-2	-2
4	9	-2
5	4	-2
6	-5	-5
7	18	-5

Output: Lowest temperature: -5

Example 2: Pseudocode linear search

SUBROUTINE linearSearch(arr, target)
    FOR i ← 0 TO LEN(arr) - 1
        IF arr[i] = target THEN
            RETURN i
        ENDIF
    ENDFOR
    RETURN -1
ENDSUBROUTINE

A linear search inspects each element once, giving a worst-case time complexity proportional to the length of the array. For sorted arrays, a binary search is faster — but binary search is covered in the Algorithms unit.

Example 3: Counting occurrences

votes = ["Red", "Blue", "Red", "Green", "Red", "Blue"]
target = "Red"
count = 0
for vote in votes:
    if vote == target:
        count = count + 1
print(f"{target} received {count} votes")

Output: Red received 3 votes

Example 4: Reversing an array

numbers = [1, 2, 3, 4, 5]
reversed_numbers = []
for i in range(len(numbers) - 1, -1, -1):
    reversed_numbers.append(numbers[i])
print(reversed_numbers)