DSA – Data Structures and Algorithm

In the previous chapter, we discussed what DSA is and got familiar with algorithmic notations like Big O, Little o, and others. Now, let’s dive into data structures — one of the core pillars of DSA. What Are Data Structures? A data structure is a way of organizing data in a computer so that it can be used efficiently. Imagine you have a closet, and you want to keep all your clothes in an organized way — like folding shirts on one shelf and hanging jackets on another. Data structures work the same way for organizing information in a program. Each data structure has a specific purpose and is better suited for particular kinds of tasks. For example, some data structures are great for storing data in order, while others are perfect for quickly finding a specific piece of information. Types of Data Structures Data structures can be classified into two major types: Let’s start with linear data structures and go through each one in detail. Arrays An Array is the simplest and most commonly used data structure. It is a collection of elements (values or variables), each identified by an index or a key. Arrays are usually used to store multiple items of the same type together. Key Points About Arrays: Example: In the example above, arr[0] is 10, arr[1] is 20, and so on. Pros: Cons: Linked Lists A Linked List is a linear data structure where elements (called nodes) are linked using pointers. Unlike arrays, Linked Lists can grow or shrink in size dynamically, which makes them more flexible. Each node contains two parts: Types of Linked Lists: Example: Here, each Node has an integer (data) and a pointer (next) that points to the next node. Pros: Cons: Stacks A Stack is a collection of elements where you can only add or remove elements from one end, called the top. It follows the LIFO (Last In, First Out) principle. Imagine a stack of books; the last book you place on top is the first one you’ll take out. Key Operations in Stacks: Example: Pros: Cons: Queues A Queue is another linear data structure but operates under the FIFO (First In, First Out) principle. Imagine standing in a queue at a ticket counter — the first person to stand in line is the first one to be served. Key Operations in Queues: Example: Pros: Cons: Choosing the Right Data Structure When choosing a data structure, always ask yourself: Each data structure has its strengths and weaknesses, so choosing the right one depends on the problem you’re trying to solve. Wrapping Up We’ve explored some of the key linear data structures: Arrays, Linked Lists, Stacks, and Queues. These structures are foundational and are used frequently in many real-world scenarios. Understanding how they work and when to use them will make your programming much more efficient. In the next chapter, we’ll dive into non-linear data structures, such as Trees and Graphs, and see how they can be used to solve more complex problems. Stay tuned!