What is Data Type?
In computer programming, a data type is a classification of data that determines the type of values that can be stored, manipulated, and processed. It tells the computer what kind of data a particular variable or constant can hold, and what operations can be performed on that data. Common data types include integers, floating-point numbers, characters, strings, booleans, and more complex types such as arrays, structures, and classes. The choice of data type is an important consideration when designing a program, as it affects the memory usage, performance, and correctness of the code.
A data type defines the type of value that can be stored in a variable. Whenever a variable is defined, the compiler allocates some memory for that variable based on the data type with which it is declared. Every data type requires a different amount of memory.
All these data types hold different values depending on their types. Some examples are shown below:
| Data Type |
Used For |
Example |
| Integer |
Whole Numbers |
. . ., 0, 1, 2, 3, . . . N where N is any integer |
| Floating point |
Decimal Numbers |
Any Real Number |
| Boolean |
Represents Logical Values |
True or False |
| Character |
Encoding text numerically |
‘a’, ‘1’ ,or any other character
Note: Here 1 is also a character because
it is enclosed between single quotes
|
A data structure is a storage that is used to store and organize data. It is a way of arranging data on a computer so that it can be accessed and updated efficiently. A data structure is not only used for organizing the data. It is also used for processing, retrieving, and storing data. There are different basic and advanced types of data structures that are used in almost every program or software system that has been developed. So we must have good knowledge about data structures.
Some Examples of Data Structures are:
A linked list is a linear data structure in which elements are stored in a sequence, and each element is linked to its next element using a pointer. Unlike an array, which stores elements in contiguous memory locations, linked lists allow for dynamic memory allocation and efficient insertion and deletion of elements.
A linked list is made up of a series of nodes, where each node contains both the element to be stored and a pointer to the next node in the list. The first node in the list is called the head, while the last node is called the tail, and its next pointer is typically set to null.
There are two main types of linked lists: singly linked lists and doubly linked lists. In a singly linked list, each node contains a single pointer to its next node, while in a doubly linked list, each node contains two pointers – one to its next node and one to its previous node.
Linked lists are commonly used to implement other data structures, such as stacks, queues, and hash tables. They are also useful in situations where the size of the data is unknown or can change during the execution of a program, such as in streaming applications or when reading large files.
A stack is an abstract data type that represents a collection of elements with two main operations: push and pop. It follows the Last In First Out (LIFO) principle, meaning that the last element added to the stack will be the first one to be removed.
The push operation adds an element to the top of the stack, while the pop operation removes the topmost element from the stack. A stack can also provide other operations like peek, which returns the topmost element without removing it, and isEmpty, which checks if the stack is empty or not.
A stack can be implemented using an array or a linked list. In the array implementation, we use a fixed-size array to store the elements, and a variable top to keep track of the topmost element. In the linked list implementation, we use a singly or doubly linked list to store the elements, and a variable top to keep track of the topmost element.
Stacks are widely used in computer science and programming, for example, to implement the function call stack, undo-redo functionality in text editors, and in the evaluation of mathematical expressions.
A Queue is a linear data structure that follows the First In First Out (FIFO) principle. It is similar to a line of people waiting for their turn, where the person who arrives first gets served first. The elements are added at the back of the queue, and removed from the front of the queue. The insertion of an element in a queue is called enqueue, and the removal of an element is called dequeue.
A queue can be implemented using an array or a linked list. In an array implementation, we need to keep track of the front and rear indices. In a linked list implementation, we can use two pointers to keep track of the front and rear nodes.
Some common operations on a queue are:
Enqueue: adds an element to the back of the queue.
Dequeue: removes an element from the front of the queue.
Peek/front: returns the front element without removing it.
IsEmpty: checks if the queue is empty.
IsFull: checks if the queue is full (in case of a fixed-size array implementation).
In computer science, a graph is a collection of vertices (also called nodes) and edges that connect these vertices. A vertex represents a point or object, while an edge represents the relationship between two vertices.
Graphs are used to represent a wide variety of real-world systems, such as social networks, transportation networks, and computer networks. They are also used in various algorithms, such as shortest path algorithms, minimum spanning tree algorithms, and flow algorithms.
There are two main types of graphs: directed and undirected. In a directed graph, each edge has a direction, while in an undirected graph, the edges have no direction. Another classification of graphs is based on the presence or absence of cycles. A graph with no cycles is called an acyclic graph, while a graph with cycles is called a cyclic graph.
There are many different algorithms for working with graphs, including breadth-first search, depth-first search, Dijkstra’s algorithm, Bellman-Ford algorithm, Kruskal’s algorithm, and Prim’s algorithm, among others.
In computer science, a tree is a non-linear data structure consisting of nodes connected by edges. Each node in a tree has a parent node and zero or more child nodes. The topmost node in a tree is called the root node, and nodes with no children are called leaves. A tree is typically used to represent hierarchical structures such as file systems, organization charts, or family trees.
There are different types of trees such as binary trees, AVL trees, B-trees, red-black trees, and many more. In a binary tree, each node has at most two child nodes, a left child and a right child. An AVL tree is a binary search tree in which the heights of the two child subtrees of any node differ by at most one. A B-tree is a tree data structure that allows efficient insertion, deletion, and searching of data items. A red-black tree is a self-balancing binary search tree in which each node is either red or black, and the root and leaves are black.
Trees can be traversed in different ways such as pre-order traversal, in-order traversal, and post-order traversal. In pre-order traversal, we visit the root node first, then the left subtree, and then the right subtree. In in-order traversal, we visit the left subtree first, then the root node, and then the right subtree. In post-order traversal, we visit the left subtree first, then the right subtree, and then the root node. Other traversal methods include level-order traversal, depth-first search, and breadth-first search.
An array is a collection of items stored at contiguous memory locations. The idea is to store multiple items of the same type together. This makes it easier to calculate the position of each element by simply adding an offset to a base value, i.e., the memory location of the first element of the array (generally denoted by the name of the array).
Time complexity:
| Algo. |
Avg case |
worst case |
|
accessing
|
O(1)
|
O(1)
|
|
searching
|
O(n)
|
O(n)
|
| insertion |
O(n)
|
O(n)
|
| deletion |
O(n)
|
O(n)
|
Space Complexity at worst case for creating an array is O(N)
Is Array Data Type or Data Structure?
Now since we have basic information about both data types and data structures, we can thereby conclude that array is undoubtedly a Data Structure because
It can store values of any data type which we can access, delete and update the existing values also we can add on new values into it.
Hence array is a Data Structure and not a Data Type.
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