Records, Lists & Tuples

Overview

In programming, records, lists, and tuples are data structures used to organise and store collections of data. Each serves a specific purpose and offers unique features for managing data efficiently. Understanding these structures helps in selecting the right one based on the problem requirements.

Records

Definition: A record is a data structure that groups related data of different types under one name.
Fields: Each piece of data in a record is called a field. Fields can have different data types.
Purpose: Records are useful for representing real-world objects or entities with multiple attributes.

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Example: A record for a student might contain:

name (string)
age (integer)
grade (float)

Implementation (Python example using a dictionary or class):

student = {
    "name": "Alice",
    "age": 18,
    "grade": 89.5
}

# Accessing a field
print(student["name"])  # Output: Alice

Lists

Definition: A list is an ordered collection of elements, where each element can be of any data type. Lists are mutable, meaning their contents can be changed after creation.
Purpose: Lists are used to store a sequence of related items, such as a collection of names or numbers.
Features:
- Dynamic size: Can grow or shrink.
- Elements are indexed, starting from 0.

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Example:

names = ["Alice", "Bob", "Charlie"]
print(names[1])  # Output: Bob

# Adding an element
names.append("Diana")
print(names)  # Output: ["Alice", "Bob", "Charlie", "Diana"]

Tuples

Definition: A tuple is an ordered collection of elements, similar to a list, but immutable—once created, its contents cannot be changed.
Purpose: Tuples are used when the data should remain constant throughout the program, such as coordinates or settings.
Features:
- Fixed-size after creation.
- Often used for returning multiple values from a function.

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Example:

coordinates = (10, 20)
print(coordinates[0])  # Output: 10

# Trying to modify a tuple will result in an error:
# coordinates[0] = 15  # This would raise a TypeError

When to Use Each Data Structure

Data Structure	Purpose	Key Characteristics
Records	Group related data with different types	Fixed fields, named attributes
Lists	Store sequences of similar or varying data	Mutable, dynamic size, indexed elements
Tuples	Store fixed sequences of data that won't change	Immutable, fixed size, indexed elements

Examples

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Example 1: Using a Record Create and access a record for a book.

book = {
    "title": "1984",
    "author": "George Orwell",
    "pages": 328
}

print(book["author"])  # Output: George Orwell

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Example 2: Using a List Store and modify a list of scores.

scores = [95, 88, 76, 100]
scores[2] = 80  # Change the 3rd score
print(scores)  # Output: [95, 88, 80, 100]

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Example 3: Using a Tuple Store coordinates that should not change.

coordinates = (5, 10)
print(coordinates[1])  # Output: 10

Note Summary

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Common Mistakes

Modifying Tuples:
Tuples are immutable; trying to modify them will result in errors.
Incorrect Indexing:
Lists and tuples are zero-indexed; accessing my_list[1] refers to the second element.
Confusing Lists with Records:
Use records when data has multiple named attributes, not just a sequence of values.

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Key Takeaways

Records: Store related data with different types using fields.
Lists: Store an ordered sequence of elements, with the ability to modify and resize.
Tuples: Store an ordered, immutable sequence of elements.
Each structure is suited for specific use cases, and selecting the right one helps in writing efficient and readable programs.

Records, Lists & Tuples Simplified Revision Notes for A-Level OCR Computer Science

Records, Lists & Tuples

Overview

Records

Lists

Tuples

When to Use Each Data Structure

Examples

Note Summary

Common Mistakes

Key Takeaways

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