Introduction to Data Structures

Hello, and Welcome everyone, in this lecture, we will start to discuss the topic of data structures.

Introduction to Data Structures

In computer science, a data structure is a way of organizing and storing data in a computer so that it can be accessed and used efficiently. It is an essential concept in computer programming and plays a crucial role in the effective implementation of algorithms.

Real-Life Examples of Data Structures

Arrays: An array is a collection of elements of the same type that are stored in contiguous memory locations. It is commonly used to represent tables, lists, and vectors.
Linked Lists: A linked list is a collection of nodes that contain data and a reference to the next node in the sequence. It is commonly used to implement queues, stacks, and graphs.
Trees: A tree is a hierarchical data structure consisting of nodes that are connected by edges. It is commonly used to represent hierarchical relationships, such as the organization of files in a computer system.
Hash Tables: A hash table is a data structure that maps keys to values using a hash function. It is commonly used for efficient retrieval and storage of data, such as in database indexing.

Understanding data structures is crucial for developing efficient algorithms and software applications. By choosing the appropriate data structure for a given problem, developers can optimize performance and reduce memory usage.

Data refers to quantities, characters, or symbols that can be stored, transmitted, and recorded on magnetic, optical, or mechanical media in the form of electrical signals.

Operations can be performed on data, which may include:

Mathematical computations
Sorting and filtering
Searching and retrieving
Manipulating and transforming

Let's see an example:

We have two sets of data
We can think of them as quantities that we can perform operations on
We can store and transmit these quantities

They are satisfying the properties of data. So I can say that these are my data. Now let's try to understand when data becomes information.

There is a distinction between data and information, and it is a topic that often causes confusion. We often interchange these two terms, but let's try to understand what the difference is.

When I say just a collection of characters like this:

If I write a collection of symbols like this: ∑x, then this is just data. Because it is just a collection of characters, I won't be able to understand it properly. Right?

Could you tell me what exactly I have written over here? No, right?

Now I can read this and I can understand what is written. Here I have written:

My name is Mayank.

Now, it has become the "Information"!

So it is quite understandable.

Meaningful or processed data is commonly referred to as information. It is important to manage data effectively to produce meaningful information.

Arranging data can be accomplished through:

Proper organization and categorization
Effective storage and retrieval methods
Utilizing appropriate analytical tools

The Importance of Data Structures

The proper management of data is crucial in producing meaningful information. To achieve this, it is important to have a solid understanding of data structures. Data structures provide a framework for organizing and structuring data in a way that makes it easier to process and analyze.

To appropriately manage the data so that we can get some meaningful information from it, we need to use efficient methods. Additionally, we should store data in a way that allows us to access it whenever needed.

Why Companies Prefer Data Structures?

Data structures are crucial for efficient data usage and organization. It's the systematic way of organizing data to make it more usable. This is why many companies prefer this subject over others.

So, What is a Data Structure?

A data structure is a systematic way of organizing data so that it can be used efficiently.

Benefits of Using Data Structures:

Efficient data usage
Easy access to required data
Quick data processing
Reduced data redundancy
Improved data maintenance

Organizing data in an efficient and usable way is the essence of data structures.

We are organizing and managing data to ensure efficient use. Efficiency refers to both time and space. Below is an example of a classical data structure:

Arrays: A collection of similar data types stored in contiguous memory locations.
Linked Lists: Each element contains a pointer to the next element, forming a chain.
Stacks: A Last-in-First-Out (LIFO) data structure where the last inserted element is the first to be removed.
Queues: A First-in-First-Out (FIFO) data structure where the first inserted element is the first to be removed.
Trees: A hierarchical data structure with a root node and subtrees of children nodes.
Graphs: A non-linear data structure consisting of nodes and edges that connect them.

These are just a few examples of classical data structures that are commonly used to organize and manage data efficiently.

Arrays

An array is a sequence or collection of symbols, characters, or integers that we have used many times in programming.

Do you know what floats in programming are? You can think of an array as a data structure because it helps in managing data in a sequential manner.

Here is an example of why data structures are useful. Instead of creating multiple variables of the same type, why not create an array to store all the values? Let's say:

Variable method:

var num1 = 5;var num2 = 7;var num3 = 10;

Array method:

var nums = [5, 7, 10];

I need to generate 100 integers, and instead of creating 100 variables for each integer, I can use a single array to store all the integers. This is the power of arrays and their usefulness. Similarly, we can store strings as arrays, since strings are just sequences of characters.

A string consisting of 100 characters may seem daunting to handle with individual variables. However, instead of creating 100 variables, you can create one array to store the entire string. This simplifies the process and allows for easier manipulation of the data.

Why Arrays are Important for Data Management

Arrays are a useful data structure for managing data in an organized manner. They allow for easy access to data and efficient manipulation of information.

By using arrays, we can store and manage large amounts of data in a way that is easily accessible and organized. This is why arrays are an essential tool for data management.

Let's discuss some real life examples of data structures to help understand why we need them. Here is an example:

Did you know that the stack data structure is used in implementing the redo and undo feature? This is the famous feature which we use many times in our applications, such as Google Docs.

Implementing Redo and Undo Feature using Stack Data Structure

The redo and undo feature is popularly used in software applications like Microsoft Word, PowerPoint, and other similar tools. This feature allows users to revert their previous actions or redo them if needed. But, did you know that the stack data structure is used in implementing this feature?

How it Works

When a user performs an action, the application saves a copy of the current state of the document. This copy is added to a stack data structure, which contains all the previous states of the document. When the user clicks on the undo button, the topmost state is popped from the stack and set as the current state of the document. Similarly, when the user clicks on the redo button, the previously undone state is pushed back into the stack and set as the current state.

Benefits of Using Stack Data Structure

Efficient memory usage as only the states that are required are stored in the stack.
Easy to implement and understand.
Allows for unlimited undo and redo actions as long as the stack has available memory.

Sample Code

// Initialize StackStack undoStack = new Stack();// User performs actionDocumentState newState = document.saveState();// Add new state to stackundoStack.push(newState);// User clicks undoDocumentState previousState = undoStack.pop();document.setState(previousState);

I have utilized the interface provided by Google Docs to compose this text. For the purpose of this demonstration, I have written the following: