Data Structures basic concepts

                               Data Structures

A data structure is a particular way of organizing data in a computer so that it can be used effectively.

For example, we can store a list of items having the same data-type using the array data structure.

                                                              or

In computer science, a data structure is a data organization, management, and storage format that enables efficient access and modification. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data.

        Primitive and Non-primitive data structures

Primitive Data Structures

Primitive Data Structures are the basic data structures that directly operate upon the machine instructions.
hey have different representations on different computers.
Integers, Floating point numbers, Character constants, String constants and Pointers come under this category.

Non-primitive Data Structures

Non-primitive data structures are more complicated data structures and are derived from primitive data structures.
They emphasize on grouping same or different data items with relationship between each data item.

Arrays, Lists and Files come under this category.

                   Abstract Data Type in Data Structures

The Data Type is basically a type of data that can be used in different computer program. It signifies the type like integer, float etc, the space like integer will take 4-bytes, character will take 1-byte of space etc.

The abstract datatype is special kind of datatype, whose behavior is defined by a set of values and set of operations. The keyword “Abstract” is used as we can use these datatypes, we can perform different operations. But how those operations are working that is totally hidden from the user. The ADT is made of with primitive datatypes, but operation logics are hidden.

Some examples of ADT are Stack, Queue, List etc.

Let us see some operations of those mentioned ADT −

• Stack −
• isFull(), This is used to check whether stack is full or not
• isEmpry(), This is used to check whether stack is empty or not
• push(x), This is used to push x into the stack
• pop(), This is used to delete one element from top of the stack
• peek(), This is used to get the top most element of the stack
• size(), this function is used to get number of elements present into the stack
• Queue −
• isFull(), This is used to check whether queue is full or not
• isEmpry(), This is used to check whether queue is empty or not
• insert(x), This is used to add x into the queue at the rear end
• delete(), This is used to delete one element from the front end of the queue
• size(), this function is used to get number of elements present into the queue
• List −
• size(), this function is used to get number of elements present into the list
• insert(x), this function is used to insert one element into the list
• remove(x), this function is used to remove given element from the list
• get(i), this function is used to get element at position i
• replace(x, y), this function is used to replace x with y value

Linear Data Structure AND Non-linear Data Structure

Linear Data Structure:
Data structure where data elements are arranged sequentially or linearly where the elements are attached to its previous and next adjacent in what is called a linear data structure. In linear data structure, single level is involved. Therefore, we can traverse all the elements in single run only. Linear data structures are easy to implement because computer memory is arranged in a linear way. Its examples are array, stack, queue, linked list, etc.

Non-linear Data Structure:
Data structures where data elements are not arranged sequentially or linearly are called non-linear data structures. In a non-linear data structure, single level is not involved. Therefore, we can’t traverse all the elements in single run only. Non-linear data structures are not easy to implement in comparison to linear data structure. It utilizes computer memory efficiently in comparison to a linear data structure. Its examples are trees and graphs.

Difference between Linear and Non-linear Data Structures

Difference between Linear and Non-linear Data Structures:

S.NO	LINEAR DATA STRUCTURE	NON-LINEAR DATA STRUCTURE

1.	In a linear data structure, data elements are arranged in a linear order where each and every elements are attached to its previous and next adjacent.	In a non-linear data structure, data elements are attached in hierarchically manner.
2.	In linear data structure, single level is involved.	Whereas in non-linear data structure, multiple levels are involved.
3.	Its implementation is easy in comparison to non-linear data structure.	While its implementation is complex in comparison to linear data structure.
4.	In linear data structure, data elements can be traversed in a single run only.	While in non-linear data structure, data elements can’t be traversed in a single run only.
5.	In a linear data structure, memory is not utilized in an efficient way.	While in a non-linear data structure, memory is utilized in an efficient way.
6.	Its examples are: array, stack, queue, linked list, etc.	While its examples are: trees and graphs.
7.	Applications of linear data structures are mainly in application software development.	Applications of non-linear data structures are in Artificial Intelligence and image processing.