Data Structures

A data structures is a method of storing and organizing data so that it may be used effectively.
Our Data Structure lesson covers all Data Structure subjects, including Array, Pointer, Structure, Linked List, Stack, Queue, Graph, Searching, Sorting, and Programs.

What exactly is data structure?

This data arrangement is accomplished through the use of an array of data structures. There are more methods for organizing data in memory. Let’s look at the many forms of data structures.

The data structure is not written in any programming language, such as C, C++, or Java. It is a collection of techniques that may be used in any programming language to organize data in memory.

‘n’ methods were developed to structure the data in memory, and all of these algorithms are known as Abstract data types. The collection of rules is made up of these abstract data kinds.

 Types of data structures

There are two types of data structures:-

• Primitive
• Non-primitive

Primitive Data structure

Primitive data structures are the same as primitive data types. The primitive data structures that may contain a single value are int, char, float, double, and pointer.

Non-Primitive Data structure

The non-primitive data structure is divided into two types:

• Linear data structure
• Non-linear data structure

Linear Data Structure

A linear data structure is the arranging of data in a consecutive order. Arrays, linked lists, stacks, and queues are the data structures used for this purpose. In these data structures, one element is linearly linked to only one other element.

When an element is connected to the number of “n” elements, it is called a non-linear data structure. The best examples are trees and graphics. In this case, the elements are arranged randomly.

In the next articles, we will go through the aforementioned data structures in more detail. Now we’ll look at some of the typical operations that may be performed on these data structures.

Data structures may also be divided into the following categories:

• Static data structure: This is a sort of data structure in which the size is determined at compile time. As a result, the maximum size is fixed.
• Dynamic data structure: This is a sort of data structure in which the size is determined at run time. As a result, the maximum size is negotiable.

Significant Operations
The following are the most frequent operations that may be done on data structures:

• Searching: In a data structure, we may look for any element.
• Sorting: The elements of a data structure can be sorted in either ascending or descending order.
• Insertion: The new element can also be inserted into a data structure.
• Updating: We may also update the element by replacing it with another element.
• Deletion: To remove an element from a data structure, we can use the delete operation.

Which Data Structure?

Data structure is a way to organize data so that it can be used efficiently. Here, we use the word effectively both in space and time. For example, the stack is an ADT (abstract data type), which is implemented using an array or linked list data structure. Therefore, we come to the conclusion that we need a certain data structure to implement a specific ADT.

ADT specifies what to do and the data structure specifies how to do it. In other words, we can say that ADT gives us the blueprint, and the data structure provides the implementation part. Now comes the question: how do I know what data structure a particular ADT will use?

Since different data structures can be implemented in a specific ADT, different implementations are compared in terms of time and space. For example, stack ADT can be implemented through arrays and linked lists. Assuming that the matrix provides time efficiency and the linked list provides space efficiency, then the one that best meets the current user’s requirements will be selected.

Benefits of Data Structures

A data structure has the following advantages:

• Efficiency: If the data structure used to implement a certain ADT is chosen correctly, the programme will be highly efficient in terms of time and space.
• Reusability: The data structure is reusable, which implies that it can be used by numerous client applications.
• Abstraction: The level of abstraction is provided by the data structure described by an ADT. Because the client cannot see the internal workings of the data structure, it does not need to be concerned with implementation. Only the interface is visible to the client.