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Elias Dabbas - Interactive Dashboards and Data Apps with Plotly and Dash

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Elias Dabbas Interactive Dashboards and Data Apps with Plotly and Dash
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Interactive Dashboards and Data Apps with Plotly and Dash: summary, description and annotation

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Learn how to build web-based and mobile-friendly analytic apps and interactive dashboards with PythonKey FeaturesDevelop data apps and dashboards without any knowledge of JavaScriptMap different types of data such as integers, floats, and dates to bar charts, scatter plots, and moreCreate controls and visual elements with multiple inputs and outputs and add functionality to the app as per your requirementsBook DescriptionWith Plotlys Dash framework, it is now easier than ever for Python programmers to develop complete data apps and interactive dashboards. Dash apps can be used by a non-technical audience, and this will make data analysis accessible to a much wider group of people. This book will help you to explore the functionalities of Dash for visualizing data in different ways and getting the most out of it.The book starts with an overview of the Dash ecosystem, its main packages, and the third-party packages crucial for structuring and building different parts of your apps. Youll learn how to create a basic Dash app and add different features to it. Next, youll integrate controls such as dropdowns, checkboxes, sliders, date pickers, and more in the app and then link them to charts and other outputs. Depending on the data you are visualizing, youll also add several types of charts, including scatter plots, line plots, bar charts, histograms, and maps, as well as explore the options available for customizing them.By the end of this book, youll have developed the skills you need to create and deploy an interactive dashboard, handle complexities and code refactoring, and understand the process of improving your application.What you will learnFind out how to run a fully interactive and easy-to-use appConvert your charts to various formats including images and HTML filesUse Plotly Express and the grammar of graphics for easily mapping data to various visual attributesCreate different chart types, such as bar charts, scatter plots, histograms, maps, and moreExpand your app by creating dynamic pages that generate content based on URLsImplement new callbacks to manage charts based on URLs and vice versaWho this book is forThis Plotly Dash book is for data professionals and data analysts who want to gain a better understanding of their data with the help of different visualizations and dashboards. Basic to intermediate-level knowledge of the Python programming language will help you to grasp the concepts covered in this book more effectively.Table of ContentsOverview of the Dash EcosystemExploring the Structure of a Dash AppWorking with Plotlys Figure ObjectsData Manipulation and Preparation - Paving the Way to Plotly ExpressInteractively Comparing Values with Bar Charts and Dropdown MenusExploring Variables with Scatter Plots and Filtering Subsets with SlidersExploring Map Plots and Enriching Your Dashboards with MarkdownCalculating Data Frequency and Building Interactive TablesLetting Your Data Speak for Itself with Machine LearningTurbo-charge Your Apps with Advanced CallbacksURLs and Multi-Page AppsDeploying Your AppNext Steps

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Interactive Dashboards and Data Apps with Plotly and Dash Harness the power of - photo 1
Interactive Dashboards and Data Apps with Plotly and Dash

Harness the power of a fully fledged frontend web framework in Python no JavaScript required

Elias Dabbas

BIRMINGHAMMUMBAI Interactive Dashboards and Data Apps with Plotly and Dash - photo 2

BIRMINGHAMMUMBAI

Interactive Dashboards and Data Apps with Plotly and Dash

Copyright 2021 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Group Product Manager: Kunal Parikh

Publishing Product Manager: Reshma Raman

Senior Editor: David Sugarman

Content Development Editor: Joseph Sunil

Technical Editor: Devanshi Deepak Ayare

Copy Editor: Safis Editing

Project Coordinator: Aparna Nair

Proofreader: Safis Editing

Indexer: Manju Arasan

Production Designer: Nilesh Mohite

First published: May 2021

Production reference: 1210421

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-80056-891-4

www.packt.com

Contributors
About the author

Elias Dabbas is an online marketing and data science practitioner. He produces open source software for building dashboards and data apps, as well as software for online marketing, with a focus on SEO, SEM, crawling, and text analysis.

About the reviewer

Leonardo Ferreira is an accountant and self-taught data scientist with the title of Kaggle Grandmaster and also acts as a data platform developer. He started his studies in data science in 2017 and started working in the field a few months after starting his apprenticeship. Since then, he has worked for large companies in Brazil and worldwide, with more than 100 open source projects adding GitHub, Kaggle, and their portfolio of web applications. He is currently a Top Rated Plus freelancer on the Upwork platform, where he has already carried out more than 20 data science and data platform projects. He is also enthusiastic about solutions on the Cardano blockchain.

Table of Contents
Preface

Plotly's Dash framework allows Python programmers to develop complete analytic data apps and interactive dashboards. This book will help you explore the functionalities of Dash for visualizing data in different ways and getting the most out of your data.

You'll start with an overview of the Dash ecosystem, its main packages, and the available third-party packages crucial for structuring and building different parts of your apps. Next, you will learn how to create a basic Dash app and add different features to it. You'll then integrate controls such as dropdowns, checkboxes, sliders, date pickers, and more in the app, and then link them to charts and other outputs. Depending on the data you are visualizing, you will also add several types of charts, including scatter plots, line plots, bar charts, histograms, maps, and more, as well as exploring the options available for customizing them.

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