Data Structures and Algorithms - Simplified Notes PDF

Data Structures and Algorithms - Simplified Notes 1. Introduction to Data Structures Data structures are ways to organize and store data so we can use it effectively. They help us save time and make our programs faster. Why are data structures important? - They allow us to perform operations li...

Data Structures and Algorithms - Simplified Notes 1. Introduction to Data Structures Data structures are ways to organize and store data so we can use it effectively. They help us save time and make our programs faster. Why are data structures important? - They allow us to perform operations like searching or sorting data quickly. - They help us manage large amounts of information efficiently. 2. Types of Data Structures Data structures can be grouped into: 1. Primitive Data Structures: - These are the basic types like numbers (int, float) and letters (char). 2. Non-Primitive Data Structures: - These are more complex, like: a) Linear: Arrays, Stacks, Queues, Linked Lists. b) Non-linear: Trees and Graphs. 3. User-Defined Data Structures: - These are made by programmers, like classes in Python. 4. Static and Dynamic: - Static: Fixed size, like arrays. - Dynamic: Size changes as needed, like linked lists. Page 1  Data Structures and Algorithms - Simplified Notes 3. What is an Algorithm? An algorithm is a step-by-step plan to solve a problem. Imagine it's like a recipe for cooking! Good algorithms have these features: - Clear steps (no confusion). - They end after a few steps (finite). - They can take inputs and give outputs. - They are fast and use little memory. 4. Specific Data Structures Here are some common data structures: 1. Arrays: - Store many items of the same type, like a row of lockers. - Types: One-dimensional, two-dimensional (like a grid), and multi-dimensional. 2. Stacks: - Work like a stack of plates (Last In, First Out). - Common actions: PUSH (add), POP (remove), and PEEK (look at the top). 3. Queues: - Work like a line at a store (First In, First Out). - Actions: ENQUEUE (add) and DEQUEUE (remove). 5. Pointers and Recursion Page 2  Data Structures and Algorithms - Simplified Notes 1. Pointers: - A pointer is like a treasure map-it shows where data is stored in memory. 2. Recursion: - Recursion is when a function calls itself. It's like a mirror showing another mirror! - Example: Finding the factorial of a number: Factorial(5) = 5 * Factorial(4). 6. Expression Evaluation and Conversion Expressions are math problems written in different ways: - Infix: Normal way (3 + 4). - Postfix: Operator comes after (3 4 +). - Prefix: Operator comes first (+ 3 4). Conversions: We can convert between these forms using stacks. Page 3