What is a data structure? What are the types of data structures?
A Data structure is a named group of different data type which can be processed as a single unit .A data structue has well defined oiperation behaviour and properties.
A data structure is a way of organizing and storing data in a computer memory or disk, so that it can be accessed and modified efficiently. Data structures are essential for designing and implementing various algorithms, applications and systems.
There are many types of data structures, each with its own advantages and disadvantages. Some of the common types of data structures are:
- Arrays: An array is a collection of elements of the same data type, stored in a contiguous block of memory. Each element can be accessed by its index, which is a numerical value that represents its position in the array. Arrays are simple and fast, but they have a fixed size and cannot be resized dynamically.
- Lists: A list is a collection of elements that can be of different data types, stored in a linear sequence. Each element has a pointer to the next element in the list, and optionally to the previous element as well. Lists are flexible and dynamic, but they require extra space for pointers and have slower access time than arrays.
- Stacks: A stack is a collection of elements that follows the last-in first-out (LIFO) principle. That means the last element added to the stack is the first one to be removed from it. Stacks are useful for implementing recursion, backtracking and undo operations.
- Queues: A queue is a collection of elements that follows the first-in first-out (FIFO) principle. That means the first element added to the queue is the first one to be removed from it. Queues are useful for implementing scheduling, buffering and synchronization.
- Trees: A tree is a collection of nodes that are connected by edges, forming a hierarchical structure. Each node can have zero or more child nodes, and at most one parent node. The node without any parent is called the root node. Trees are useful for representing hierarchical data, such as file systems, organizational charts and XML documents.
- Graphs: A graph is a collection of nodes that are connected by edges, forming a network structure. Each node can have zero or more adjacent nodes, and each edge can have a weight or direction associated with it. Graphs are useful for modeling complex relationships, such as social networks, maps and web pages.
- Hash tables: A hash table is a collection of key-value pairs that are stored in an array using a hash function. A hash function maps each key to an index in the array, where the corresponding value is stored. Hash tables are useful for implementing fast lookup, insertion and deletion operations.
- Heaps: A heap is a collection of elements that are arranged in a complete binary tree structure, such that each node is either greater than or equal to (max heap) or less than or equal to (min heap) its children. Heaps are useful for implementing priority queues, sorting algorithms and median finding algorithms.
- Data structure is a way to store and organize data so that it can be used eficiently.
- The data structure name indicate itself that organizing the data in memory.
- The data structure is not any Programming Language like C , C++ , PYTHON, JAVA etc it is a set of algorithms that we can use in ang Programming Language to structure the data in memory.
Different types of Data Structure
- Simple data structure - There data structure are normally built from primitive data type like integer , real , character.
Ex- Array, structure - Compound data structure - Simple data structure can be combined in various ways to from more complex structure called compound data structures.
compound data structures are classified into following two types.
- LINEAR DATA STRUCTURE - A data stucture is said to be linear if its elemerts from a sequence following are the example LINEAR DATA STRUCTURE stack , queue , linked list.
- NON - LINEAR DATA STRUCTURE - There are multilevel data stuctures example of NON-LINEAR DATA STRUCTURE is TREE.
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