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How Many Types of Data Structures Are There? List of DS, Best Guide

Have you ever wondered How Many Types of Data Structures Are There? Here is complete List of Data structures and short note on each one of them.

How Many Types of Data Structures Are There?

Data Structures

This document gives extensive tutorials on all DS topics. A data file is a specific mechanism for organising an application data file. This page provides useful examples of different types of data. Array Linked Lists Stack Queues – Binary Trees – Search Trees. I can store the table that has the same types of files as our database in ArrayData Format. How can the linker of lists change in relation to them? The node exchanged is the same as any other database.

Data types and Data structures

Array

  • An array is a collection of items stored at contiguous memory locations.

Types of data:

There are 4 types of Data

  • Nominal,
  • Ordinal,
  • Discrete,
  • Continuous

Hash Table:

A Hash table (hash map) is a data structure that implements an associative array abstract data type, a structure that can map keys to values.

Graphs.

A Graph is a non-linear data structure consisting of nodes and edges. The nodes are sometimes also referred to as vertices and the edges are lines or arcs that connect any two nodes in the graph

Tree

A Tree is a widely used abstract data type that simulates a hierarchical tree structure, with a root value and subtrees of children with a parent node, represented as a set of linked nodes.

Binary search tree

Binary Search Tree · The left subtree of a node contains only nodes with keys lesser than the node’s key.

Red-Black Tree

A red-black tree is a kind of self-balancing binary search tree where each node has an extra bit, and that bit is often interpreted as the color (red or black).

Data structure classification:

Data Structures are normally divided into two broad categories:
(1) Primitive Data Structures
(2) Non-Primitive Data Structures

Operations on data structure:

Operations on Data Structures are

  • Traversal,
  • Insertion,
  • Deletion,
  • Searching,
  • Sorting and
  • Merging.

B-tree

B Tree is a specialized m-way tree that can be widely used for disk access. A B-Tree of order m can have at most m-1 keys and m children.

Linear Probing

Linear probing is a scheme in computer programming for resolving collisions in hash tables, data structures for maintaining a collection of key–value pairs and looking up the value associated with a given key

Need of Data Structures

The need of Data Structure includes efficiency and reusability. Data structure provides a way of organizing, managing, and storing data efficiently. With the help of data structure, the data items can be traversed easily.

Advantages of Data Structures

  • Data structure helps in efficient storage of data in the storage device.
  • Data structure usage provides convenience while retrieving the data from storage device.
  • Data structure provides effective and efficient processing of small as well as large amount of data.
  • Usage of proper data structure, can help programmer save lots of time or processing time while operations such as storage, retrieval or processing of data.
  • Manipulation of large amount of data can be carried out easily with the use of good data structure approach.
  • Most of the well organized data structures like Array, stack, queues, graph, tree, linked list has well built and pre-planned approach for operations like storage, addition, retrieval, manipulation, deletion, etc. While using them, programmer can be completely rely on these data structures.
  • Data structure usage can simply encourage reusability in long run as well.

Binary tree

A Binary tree is a tree data structure in which each node has at most two children, which are referred to as the left child and the right child.

Binary Heap

A binary heap is a heap data structure that takes the form of a binary tree. Binary heaps are a common way of implementing priority queues.

Weight-balanced Tree

A weight-balanced tree is a binary search tree that stores the sizes of subtrees in the nodes.

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