What is Data Structure?

Data Structure is a way of collecting and organizing data in such a way that we can perform operations on these data in an effective way. Data Structures is about rendering data elements in terms of some relationship, for better organization and storage. For example, we have some data which has,Instructor name "Nitesh Jain" and age 40. Here "Nitesh Jain" is of String data type and 40 is of integer data type.

We can organize this data as a record like Instructor record, which will have both Instructor name and age in it. Now we can collect and store Instructor records in a file or database as a data structure. For example: "Nitesh Jain" 40, "Amit" 39, "Ankur" 25

If you are aware of Object Oriented programming concepts, then a class also does the same thing, it collects different type of data under one single entity. The only difference being, data structures provides for techniques to access and manipulate data efficiently.

In simple language, Data Structures are structures programmed to store ordered data, so that various operations can be performed on it easily. It represents the knowledge of data to be organized in memory. It should be designed and implemented in such a way that it reduces the complexity and increases the efficiency.

Basic Terminologies

Data structures are the building blocks of any program or the software. Choosing the appropriate data structure for a program is the most difficult task for a programmer. Following terminology is used as far as data structures are concerned.

Data: Data can be defined as an elementary value or the collection of values, for example, student's name and its id are the data about the student.

Group Items: Data items which have subordinate data items are called Group item, for example, name of a student can have first name and the last name.

Record: Record can be defined as the collection of various data items, for example, if we talk about the student entity, then its name, address, course and marks can be grouped together to form the record for the student.

File: A File is a collection of various records of one type of entity, for example, if there are 60 employees in the class, then there will be 20 records in the related file where each record contains the data about each employee.

Attribute and Entity: An entity represents the class of certain objects. it contains various attributes. Each attribute represents the particular property of that entity.

Field: Field is a single elementary unit of information representing the attribute of an entity.

Data Types

(1) Linear Data Structure

(2) Non Linear Data Structure

(1) Linear Data Structures: A data structure is called linear if all of its elements are arranged in the linear order. 

Types of Linear Data Structures are given below:

Arrays: An array is a collection of similar type of data items and each data item is called an element of the array. The data type of the element may be any valid data type like char, int, float or double.

Linked List: Linked list is a linear data structure which is used to maintain a list in the memory. It can be seen as the collection of nodes stored at non-contiguous memory locations. Each node of the list contains a pointer to its adjacent node.

Stack: Stack is a linear list in which insertion and deletions are allowed only at one end, called top.

Queue: Queue is a linear list in which elements can be inserted only at one end called rear and deleted only at the other end called front.

Non Linear Data Structures: This data structure does not form a sequence i.e. each item or element is connected with two or more other items in a non-linear arrangement.

Types of Non Linear Data Structures are given below:

Trees: Trees are multilevel data structures with a hierarchical relationship among its elements known as nodes. The bottom most nodes in the hierarchy are called leaf node while the topmost node is called root node. Each node contains pointers to point adjacent nodes.

Graphs: Graphs can be defined as the pictorial representation of the set of elements (represented by vertices) connected by the links known as edges. A graph is different from tree in the sense that a graph can have cycle while the tree can not have the one.

Abstract Data Type in Data Structures (ADT)

The abstract datatype is special kind of data type, 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 logic 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