Data Types and Records

Objective

Select and use appropriate data types for a problem solution.

Data Types

Data types define the kind of value a variable can hold. Choosing the correct data type is crucial for efficient memory usage and accurate calculations.

• Integer (int): Whole numbers (e.g., -3, 0, 100).
• Floating-point number (float): Numbers with a decimal point (e.g., 3.14, -2.5).
• Character (char): A single character (e.g., 'A', '7', '$').
• String (str): A sequence of characters (e.g., "Hello", "123").
• Boolean (bool): Represents truth values: True or False.

Why are data types important?

Using the right data type has several benefits:

• Memory Efficiency: Different data types require different amounts of memory. Using the smallest appropriate type saves memory.
• Accuracy: Using the correct type prevents data loss or unexpected results. For example, performing arithmetic on a string will lead to errors.
• Compiler Optimization: Compilers can optimize code more effectively when data types are explicitly specified.

Example: Choosing the right data type

Consider storing the age of a person. An integer data type is appropriate because age is a whole number.

age = 30 // Integer data type

If we were storing the price of an item, a floating-point data type would be more suitable to accommodate decimal values.

price = 19.99 // Floating-point data type

Records (Structures)

Records, also known as structures, allow you to group together variables of different data types under a single name. This is useful for representing real-world entities with multiple attributes.

Creating Records

In Python, records can be created using classes or named tuples. Here's an example using a class:

class Person: def __init__(self, name, age, city): self.name = name self.age = age self.city = city person1 = Person("Alice", 25, "New York") print(person1.name) # Output: Alice print(person1.age) # Output: 25

Accessing Record Members

You can access the individual variables within a record using the dot notation (.).

Example: Student Record

Let's create a record to represent a student:

Attribute	Data Type
Student Name	String (str)
Student ID	Integer (int)
Grade	String (str)
Attendance Percentage	Float (float)

A Student record could be defined as follows (in Python):

class Student: def __init__(self, name, student_id, grade, attendance): self.name = name self.student_id = student_id self.grade = grade self.attendance = attendance

Benefits of using Records

• Organization: Records provide a structured way to organize related data.
• Modularity: They allow you to group data and associated operations into a single unit.
• Code Readability: Using meaningful record names improves code readability.

Practice

Consider a scenario where you need to store information about products in an online store. How would you design a record to represent a product, including attributes like name, price, and quantity in stock?