3. Data Types

Overview

Data types refer to the categories of data that determine what kind of value can be stored and manipulated within a program. Understanding data types is crucial for ensuring that data is stored correctly and for performing accurate operations.

When to Study

Data types can be studied either in parallel with or after Data Structures. A solid understanding of data types enhances your ability to work with different kinds of data and to implement operations effectively.

Objectives

  • Ensure Correct Data Storage: Properly store and manage various types of data.
  • Perform Accurate Operations: Carry out operations on data with appropriate precision and correctness.

Key Concepts

1. Primitive Data Types

  • Description: Basic types of data built into a programming language. They represent single values and have a fixed size.
  • Examples:
  • Integer (int): Represents whole numbers. E.g., 5, -23.
  • Floating Point (float, double): Represents real numbers with decimal points. E.g., 3.14, -0.001.
  • Character (char): Represents a single character. E.g., 'A', 'z'.
  • Boolean (bool): Represents true or false values. E.g., true, false.

2. Composite Data Types

  • Description: Data types that are composed of multiple primitive types.
  • Examples:
  • String: Represents a sequence of characters. E.g., "Hello, World!".
  • Array: Represents a collection of elements of the same type. E.g., [1, 2, 3, 4].
  • Struct (C/C++), Class (Object-Oriented Languages): User-defined types that group together different data types. E.g., a Person struct with name and age fields.

3. Abstract Data Types

  • Description: Data types that are defined by their behavior (operations) rather than their implementation.
  • Examples:
  • List: An ordered collection of elements that can be dynamically sized.
  • Queue: A collection that follows the FIFO (First-In-First-Out) principle.
  • Stack: A collection that follows the LIFO (Last-In-First-Out) principle.
  • Map (or Dictionary): A collection of key-value pairs.

4. Special Data Types

  • Description: Data types used for specific purposes or with special constraints.
  • Examples:
  • Date and Time: Represents dates and times. E.g., 2024-08-29, 12:00:00.
  • Enumeration (enum): Represents a set of named values. E.g., enum Days { Sunday, Monday, Tuesday, ... }.
  • Null: Represents the absence of a value. E.g., null in Java or None in Python.

Conclusion

Understanding data types is essential for correct data handling and manipulation. By mastering data types, you can ensure that your programs store and process data accurately and efficiently.