Data Structure is an approach of organizing data, storing data and managing data so that we can access and modify it efficiently.
For example
Suppose we have some data of the students of class 4. As we know that every students have name, age and roll number in general. If we consider a student whose name is “Pawan”, age is 17 and he is from class 4. Here “Pawan” name is of String data, and 17 and 1 is integer data.
If we have only one the data of single student then it is easy to manage and store. But what about if we have thousands of students data?
So for that purpose data structure concept is needed to handle the operations on that large amount of data.
Means we have to use array or linked list as per requirement to manage that much data and perform any desired operation on it efficiently.
What is Data Structure?
In simple word, we can define data Structures as it is a structure programmed to store data in ordered form so that operations are often performed on that very easily. Also, represent the data in organized form to store in memory so that it should be increase the efficiency and reduces the complexity.
You can also remember it as Data Structure, is a method to store the data in a structured way so that it can be easily created, viewed, and managed.
Types of data structures
1. Arrays
An array is a data structure that stores similar type of data in continuous memory location.
Here similar type of data means all elements have same data type.
Data is stored together in Continuous Memory Locations, the position of any element can be calculated or retrieved easily with the help of first element’s location or base location.
Each elements of an array have index value, with the help of it we can access the elements of any position.
The index value starts from the 0.
Example: Consider an array of integers [3, 5, 9, 1]. Here, 3 is at index 0, 5 is at index 1, and so on. Accessing the element at index 2 would return 9.
2. Stacks
A stacks are recursive data structures that follow the last-in-first-out (LIFO) principle or we can also say that first in last out (FILO) principle.
LIFO means the lastly pushed element in the stack pooped out first. Similarly FILO means first pushed element will pooped out at last.
Stack has two operations push and pop. Push means the item into the stack, and the pop means item out of the stack.
Elements in the stack can be added and removed only at the top.
Example: Imagine a stack of books. The last book you put on top is the first one you’ll take off.
3. Queues
A Queues is a data structures that follow the First In First Out (FIFO) principle.
FIFO means the first element that is inserted in the queue is the first element one, which will be removed first.
Elements are always added in Queues to the back, and it is removed from the front.
Example: Customers in a bank queue. The first customer in line is the first to be served.
4. Linked lists
A linked list is a linear data structure where the elements are stored at non-contiguous memory locations.
It is a node based structure and each node have two fields, data and reference (or link) to the next node in the list.
Data stores the actual value or item and link stores the base address of next node means we can say that link has a reference of next node.
If there is no any next node then link will point to NULL.
Example: A treasure hunt where each clue points to the location of the next clue, with the final clue saying “end of hunt.”
5. Trees
Tree is an abstract and non-linear data structures. It is also know as hierarchical data structures where is a single root node from which other nodes branch out. In simple word we can also say as It has a root node and child nodes. And all nodes are linked to each other with the help of edge.
Each node in a tree can have multiple children but only one parent, except for the root node, which has no parent. We can also define it as it is a collection of nodes.
Example: A family tree showing generations of family members, where each person is a node connected to their Childs.
6. Graph
A Graph is a non-linear data structure which consists nodes and edges. Nodes are also known as vertices, and the edges are known as lines or arcs. This edges or arc connects two nodes in the graph. A computer network is a real-world example of Graphs.
We can also explain graph as it consist of nodes (vertices) connected by edges (lines). They can represent complex networks like computer networks or social networks. Here the nodes represent entities and the edges represent the relationships or paths between them.
Example: A map of cities (nodes) connected by roads (edges).
7. Tries
A trie, or prefix tree, is a tree-like data structure that is based on the prefix of a string and stores strings as data items that can be can be visualized like a graph. Each node typically represents a character of a string, and the path from the root to a node spells out a prefix of keys.
Example: Autocomplete features in search engines use tries to predict the rest of a word as you type.
8. Hash tables
Hash tables is a data structure that stores data in a key/values pair. And there is a hash function that helps to generate key. This structure is highly efficient for lookup operations.
Example: A dictionary where words are keys, and their meanings are values. A hash table allows quick lookup of the meaning associated with a given word.
Why do we need Data Structures?
Data structures are important for the following reasons:
- Data structures are used in every program or software system to arrange the data.
- Data structures are essential ingredients of many efficient algorithms. It helps in the management of huge amounts of data, such as a large integrated collection of databases.
- Each Data Structure allows data/elements to be stored in a specific manner in the memory.
- Data Structure helps in efficient data search and retrieval.
- For specific problems, specific Data structures are used.
- Data Structure allows managing a large amount of data, such as large databases and indexing services such as a hash table.
- Data structures organized the storage and retrieval of data and information which is stored in both main memory and secondary memory.
Area Where Data Structure is Used
- In Numerical analysis
- In Operating System
- In Artificial intelligence
- In Compiler design
- In Statistical analysis package
- In DBMS
- In Simulation
- In Graphics Design