2.3 Data Structures

Definition: A list is a collection that can store multiple values in order.

Purpose: To group related items together.

When used: When data needs to be ordered and changeable.

Python example:

scores = [10, 15, 20]
scores.append(25)

print(scores)
        

Definition: An array stores multiple values of the same data type.

Purpose: Efficient storage of numerical data.

When used: When working with large, fixed‑type datasets.

Python note: Python lists are commonly used, but arrays exist via libraries.

Python example:

from array import array

numbers = array('i', [1, 2, 3, 4])
numbers.append(5)

print(numbers)
        

Definition: A dictionary stores data as key–value pairs.

Purpose: Fast access to data using a key.

When used: When values must be labelled or looked up.

Python example:

student = {
    "name": "Alex",
    "age": 18,
    "grade": "B"
}

print(student["name"])
        

Interpreting code means understanding what each instruction does.

Python example:

prices = [5, 10, 15]
total = 0

for price in prices:
    total += price

print(total)
        

This code loops through the list and calculates the total.

Developing code involves writing new logic using data structures.

Python example:

names = ["Sam", "Lee", "Jordan"]

for name in names:
    print("Hello", name)
        

Debugging means finding and fixing errors in code.

Example with bug:

numbers = [1, 2, 3]

print(numbers[3])
        

Issue: Index out of range. Fix: Use a valid index (0–2).

Operators are used to process data in structures.

Python example:

numbers = [2, 4, 6]
result = numbers[0] + numbers[1]

print(result)
        

This uses the addition operator on list values.