Introduction to 8 Essential Data Structures

Introduction to 8 Essential Data Structures

Our understanding of data structures as programmers is mostly limited to using them at a higher level of abstraction with a programming language.

Our understanding of data structures as programmers is mostly limited to using them at a higher level of abstraction with a programming language. Though we know how to store and retrieve data from different data structures using a particular programming language, most of us don’t try to unravel what goes on in the lower level implementation of these data structures. 

Surface level knowledge of data structures is enough to somehow get our work done in most cases. But understanding how different data structures behave at the lower levels is crucial when it comes to selecting the optimal data structure for a given task. In this article, we will look under the wraps of 8 different data structures and see how they handle data. 


Array

Array data structure stores a fixed number of data of a single data type. Elements (items) in an array are stored in a block of contiguous memory slots. Due to this, elements in an array are assigned consecutive numbers, starting from 0 or 1, as their “indexes”.

One can access a single element stored in an array at random using its unique index. Accessing an element using the index has a time complexity of Θ(1). Reading or updating array elements can be easily achieved in this manner. Because of the contiguous location of array elements, arrays traversal is faster compared to most of the other data structures. 

Inserting to or deleting from an array is a rather complex and time-consuming task. When inserting, all the elements in the current array are copied to a newly created array with increased size, and the new element is added to the end of the new array. Deleting is also implemented in a similar manner to reduce the array size.

data visualization

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Visual Analytics and Advanced Data Visualization

Visual Analytics and Advanced Data Visualization - How CanvasJS help enterprises in creating custom Interactive and Analytical Dashboards for advanced visual analytics for data visualization

Visualization Best Practices for Data Scientists

Visualization Best Practices for Data Scientists. Disclaimer: The ideas presented in this article are from the book: Story Telling With Data by Cole Nussbaumer Knaflic.

Applications Of Data Science On 3D Imagery Data

The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.

The Importance of Data Visualization

The Importance of Data Visualization - It is the process of converting raw data at hand into easy and understandable image-photo-graphics for fast, effective and accurate…

Data Quality Testing Skills Needed For Data Integration Projects

Data Quality Testing Skills Needed For Data Integration Projects. Data integration projects fail for many reasons. Risks can be mitigated when well-trained testers deliver support. Here are some recommended testing skills.