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# C++ Data Structures Tutorial: Doubly Linked Lists Detailed Explanation

## Doubly Linked Lists detailed explanation for beginners (C++ Data Structures course)

This video contains an in-depth explanation of doubly-linked lists with visual examples.
You will also learn how to create a doubly-linked list, insert elements, traverse it in forward and backward directions, and print values of all nodes.

Contents:
00:00 - What will you learn in this video + free AI assistant that I use to help me code
01:57 - Introduction to doubly linked lists
04:36 - Creating a node
05:51 - How to create a doubly linked list (step-by-step)
07:32 - Why are linked lists implemented with pointers
09:35 - How to insert nodes into a doubly linked list
14:36 - Forward traversing of a doubly linked list
16:44 - Backward traversing of a doubly linked list

#cplusplus #cpp #datastructures

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## Linked List in Data Structure

In computer science, we refer to the format of storing data on storage devices as a data structure. An array is the collection of data stored in contiguous memory locations.

This makes accessibility very easy but it leads to not so efficient use of memory because the smaller chunks of memory that are left between earlier stored data are not used.

But what if you need more efficient utilization of your memory. Here dynamic data structures come into the picture. Dynamic data structures as the name suggest do not have a fixed memory size.

They can shrink or grow themselves by deallocating or allocating the memory respectively, as and when required.

#### Linked List in Data Structure

A linked list is the most basic type of dynamic data structure. A linked list is a linear collection of data where the order of elements is not given by their physical memory address. The user stores the data in blocks of memory called nodes.

Each node has two parts. The first part contains the data and the second part points towards the next node. It contains the address of the next node in the actual memory.

Singly-linked lists are the most basic and easy to implement linked lists. Each node stores the data at random memory locations and contains a pointer that points to the next node in the memory.

Each node contains data and two pointers. One point to the previous node and the other points to the next node. This makes doubly-linked traversable both forward and backward.

Just like a singly linked list, here also each node is linked to the next only with a slight modification. In a circular linked list, the last node of the list is pointed to the first node forming a loop. So we can reach the previous node by traversing forward.

#### Singly Linked list in Data Structure

A singly linked list as we have seen contains multiple nodes in which the earlier node points at the next node except the last node. A node has two parts, the first one contains the data and the second part contains the address of the next node.

#### Creating Node in Linked List

C program for creating a Linked List Node:

struct node { int data; // data to store in node struct node *next; //NULL for last node }

The previous part of the first node and the next part of the last node will always have NUL

#### Need of Pointers in Linked List

Unlike arrays, in a linked list, memory allocation takes place at runtime and therefore memory location of each node is random. Each node can be present anywhere in the memory and to access them, each node has the address of its next node stored with it.

This forms a kind of link between every node. This is the additional pointer that we need because if the link is not present or it’s broken, the memory locations will be lost.

• Insert: Insert the node at any position. Worst-case time complexity O(1).
• Delete: Delete the node at any position. Worst-case time complexity O(1).
• **Search: **Search for a specific node in the list. The worst-case time complexity O(n).
• Display: Display a complete list. The worst-case time complexity O(n).

Adding nodes in a linked list can be sometimes tricky. Since a linked list is a dynamic data structure, we can not just break a link and add or delete the node anywhere. To better understand this let us do a thought experiment.

Consider a linked list similar to a train with multiple coaches. Each coach represents the first part of the node where data is present, here passengers. The next part of the coach, i.e. the coupling represents the second part of the node. This part contains a connection to the next node.

Now, if you want to add a new coach to a moving train you cannot simply uncouple any two coaches and add a new coach. As soon as you uncouple the coaches, the second part of the train which is not attached to the engine will be left behind and that will fail the task.

Similarly, in the linked list, we cannot just break a link between any two nodes and add a new node. Suppose you want to add a new node between the fourth and fifth nodes. To do that you first have to traverse from the first node to the fifth node.

Point the new node to the fifth node and then traverse again from the start to the fourth node. Point the fourth node towards the new node. The new node is now a part of the linked list.

#data structure tutorials #data structures #delete node in linked list #linked list

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If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

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## SKP's Algorithms and Data Structures

Continuing on the Quick Revision of Important Questions for My Interviews. These Are Good Puzzles or Questions Related to Data Structures.

My Article Series on Algorithms and Data Structures in a Sort of ‘Programming Language Agnostic Way’. Few of the Algorithms and Data Structures in C, Few in C++, and Others in Core Java. Assorted Collection for Learning, Revising, Revisiting, Quick Refresh, and a Quick Glance for Interviews. You May Even Include them Directly for Professional or Open Source Efforts. Have Included Explanation Only for Few of These! Hope these turn out to be Really Helpful as per the Author’s Intention.

#### Data Structure — Interview Questions

#java #core java #data structures #dijkstra #core java basics #data structure using java #algorithms and data structures #java code examples #linked list in java #circular linked list

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## Getting Started With Data Lakes

### Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

### Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

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## C++ Tutorial for Beginners - Full Course. DO NOT MISS!!!

This course will give you a full introduction into all of the core concepts in C++.
⭐️ Contents ⭐
⌨️ (0:00:00) Introduction
⌨️ (0:01:38) Windows Installation
⌨️ (0:04:54) Mac Installation
⌨️ (0:08:44) Setup & Hello World
⌨️ (0:12:29) Drawing a Shape
⌨️ (0:19:55) Variables
⌨️ (0:31:43) Data Types
⌨️ (0:39:15) Working With Strings
⌨️ (0:49:00) Working With Numbers
⌨️ (0:59:41) Getting User Input
⌨️ (1:05:32) Building a Calculator
⌨️ (1:09:28) Building a Mad Libs
⌨️ (1:13:45) Arrays
⌨️ (1:20:03) Functions
⌨️ (1:29:47) Return Statement
⌨️ (1:35:22) If Statements
⌨️ (1:47:15) If Statements (con’t)
⌨️ (1:55:58) Building a Better Calculator
⌨️ (2:02:20) Switch Statements
⌨️ (2:10:47) While Loops
⌨️ (2:18:53) Building a Guessing Game
⌨️ (2:29:18) For Loops
⌨️ (2:38:32) Exponent Function
⌨️ (2:45:21) 2d Arrays & Nested Loops
⌨️ (2:59:11) Pointers
⌨️ (3:13:26) Classes & Objects
⌨️ (3:25:40) Constructor Functions
⌨️ (3:34:41) Object Functions
⌨️ (3:41:43) Getters & Setters
⌨️ (3:54:04) Inheritance

Course developed by Mike Dane. Check out his YouTube channel for more great programming
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=vLnPwxZdW4Y&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=10
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