**What Is Data Structure? Explain Types of Data Structure With Example**

When it comes to handling and organizing data efficiently in computer science, data structures play a vital role. A data structure is a collection of data elements organized in a specific way to facilitate efficient operations on that data. It provides a way to store and organize data so that it can be easily accessed and manipulated.

## Types of Data Structures

Data structures can be categorized into two main types: __primitive__ and __non-primitive__. Let’s explore each type in detail:

### 1. Primitive Data Structures:

A primitive data structure is a basic building block provided by programming languages.

These structures are predefined and are directly operated upon by the machine instructions. The four primary primitive data structures are:

**Integer:**This data structure is used to store whole numbers (positive, negative, or zero) without any fractional or decimal parts. For example, 5, -10, and 0.**Float:**Float represents real numbers with decimal points.For example, 3.14 or -2.5.

**Character:**This data structure stores individual characters such as letters, digits, or symbols. For example, ‘a’, ‘Z’, or ‘@’.**Boolean:**Boolean represents only two values: true or false.

### 2. Non-Primitive Data Structures:

In contrast to primitive data structures, non-primitive data structures are derived from primitive ones but have more complex implementations.

These structures can hold multiple values of different types together and are built using primitive data structures. Some common examples of non-primitive data structures include:

**Arrays:**Arrays are a collection of elements of the same data type arranged in a contiguous memory block. They allow efficient random access to elements using indices.**Linked Lists:**Linked lists consist of nodes, where each node contains both the data and a reference to the next node. They are dynamic and allow efficient insertion and deletion operations at any position.**Stacks:**Stacks follow the Last-In-First-Out (LIFO) principle. They allow insertion and deletion of elements only from one end, known as the top.**Queues:**Queues follow the First-In-First-Out (FIFO) principle.They allow insertion at one end (rear) and deletion at the other end (front).

**Trees:**Trees are hierarchical structures consisting of nodes connected by edges. Each node can have zero or more child nodes, forming a branching structure.**Graphs:**Graphs consist of vertices/nodes connected by edges/links. They represent complex relationships between entities.

Data structures form an essential part of algorithms and play a crucial role in solving various computational problems efficiently. Choosing appropriate data structures for specific scenarios can significantly impact performance and memory usage.

In conclusion, understanding different types of data structures allows programmers to optimize their code and design efficient algorithms that can handle large amounts of data effectively.

Gaining proficiency in data structure concepts is essential for any aspiring programmer or computer scientist!