Learning Responsive Data Visualization

Learning Responsive Data Visualization PDF Author: Christoph Korner
Publisher: Packt Publishing Ltd
ISBN: 1785884336
Category : Computers
Languages : en
Pages : 258

Get Book Here

Book Description
Master the art of building responsive visualizations on the Web About This Book Learn the techniques for building data visualizations that work well for all screen sizes Implement responsive techniques with popular libraries to get to grips with building responsive visualizations that work in the real world Incorporate responsive workflow in your data visualization process to build visualizations that take a mobile-first approach. Who This Book Is For Web developers and data science professionals who want to make their visualizations work for smaller screen sizes. Some basic knowledge of JavaScript and Data visualization is expected. What You Will Learn Get familiar with responsive design for data visualizations Understand the main concepts of D3.js to create interactive visualizations Unleash the power of Bootstrap to create stunning and responsive visualizations for all screen resolutions Implement Touch and Mouse interactions for mobile-first applications Design Transitions and Animations that impress in portrait and landscape Build a Responsive World Map using GeoJSON and D3.js In Detail Using D3.js and Responsive Design principles, you will not just be able to implement visualizations that look and feel awesome across all devices and screen resolutions, but you will also boost your productivity and reduce development time by making use of Bootstrap—the most popular framework for developing responsive web applications. This book teaches the basics of scalable vector graphics (SVG), D3.js, and Bootstrap while focusing on Responsive Design as well as mobile-first visualizations; the reader will start by discovering Bootstrap and how it can be used for creating responsive applications, and then implement a basic bar chart in D3.js. You will learn about loading, parsing, and filtering data in JavaScript and then dive into creating a responsive visualization by using Media Queries, responsive interactions for Mobile and Desktop devices, and transitions to bring the visualization to life. In the following chapters, we build a fully responsive interactive map to display geographic data using GeoJSON and set up integration testing with Protractor to test the application across real devices using a mobile API gateway such as AWS Device Farm. You will finish the journey by discovering the caveats of mobile-first applications and learn how to master cross-browser complications. Style and approach As the world shifts to mobile devices for consuming data on the Web, developers are faced with the unique challenge of making data visualizations work for their smaller screens. The growth of responsive web design enabled developers to adopt page layouts and media for smaller screens, but there is still little information available on how to adapt data visualizations for the smaller screens. This book fills this important gap and shows how responsive web design principles can be extended to create visualizations that work well regardless of the screen size, thereby allowing developers to build user-friendly visualizations that work well on all devices. In addition to covering some of the popular techniques and design patterns for building responsive visualizations, the book also shows readers how to implement these techniques with the help of some popular tools and libraries.

Learning Responsive Data Visualization

Learning Responsive Data Visualization PDF Author: Christoph Korner
Publisher: Packt Publishing Ltd
ISBN: 1785884336
Category : Computers
Languages : en
Pages : 258

Get Book Here

Book Description
Master the art of building responsive visualizations on the Web About This Book Learn the techniques for building data visualizations that work well for all screen sizes Implement responsive techniques with popular libraries to get to grips with building responsive visualizations that work in the real world Incorporate responsive workflow in your data visualization process to build visualizations that take a mobile-first approach. Who This Book Is For Web developers and data science professionals who want to make their visualizations work for smaller screen sizes. Some basic knowledge of JavaScript and Data visualization is expected. What You Will Learn Get familiar with responsive design for data visualizations Understand the main concepts of D3.js to create interactive visualizations Unleash the power of Bootstrap to create stunning and responsive visualizations for all screen resolutions Implement Touch and Mouse interactions for mobile-first applications Design Transitions and Animations that impress in portrait and landscape Build a Responsive World Map using GeoJSON and D3.js In Detail Using D3.js and Responsive Design principles, you will not just be able to implement visualizations that look and feel awesome across all devices and screen resolutions, but you will also boost your productivity and reduce development time by making use of Bootstrap—the most popular framework for developing responsive web applications. This book teaches the basics of scalable vector graphics (SVG), D3.js, and Bootstrap while focusing on Responsive Design as well as mobile-first visualizations; the reader will start by discovering Bootstrap and how it can be used for creating responsive applications, and then implement a basic bar chart in D3.js. You will learn about loading, parsing, and filtering data in JavaScript and then dive into creating a responsive visualization by using Media Queries, responsive interactions for Mobile and Desktop devices, and transitions to bring the visualization to life. In the following chapters, we build a fully responsive interactive map to display geographic data using GeoJSON and set up integration testing with Protractor to test the application across real devices using a mobile API gateway such as AWS Device Farm. You will finish the journey by discovering the caveats of mobile-first applications and learn how to master cross-browser complications. Style and approach As the world shifts to mobile devices for consuming data on the Web, developers are faced with the unique challenge of making data visualizations work for their smaller screens. The growth of responsive web design enabled developers to adopt page layouts and media for smaller screens, but there is still little information available on how to adapt data visualizations for the smaller screens. This book fills this important gap and shows how responsive web design principles can be extended to create visualizations that work well regardless of the screen size, thereby allowing developers to build user-friendly visualizations that work well on all devices. In addition to covering some of the popular techniques and design patterns for building responsive visualizations, the book also shows readers how to implement these techniques with the help of some popular tools and libraries.

Building Responsive Data Visualization for the Web

Building Responsive Data Visualization for the Web PDF Author: Bill Hinderman
Publisher: John Wiley & Sons
ISBN: 1119067138
Category : Computers
Languages : en
Pages : 451

Get Book Here

Book Description
Unchain your data from the desktop with responsive visualizations Building Responsive Data Visualization for the Web is a handbook for any front-end development team needing a framework for integrating responsive web design into the current workflow. Written by a leading industry expert and design lead at Starbase Go, this book provides a wealth of information and practical guidance from the perspective of a real-world designer. You'll walk through the process of building data visualizations responsively as you learn best practices that build upon responsive web design principles, and get the hands-on practice you need with exercises, examples, and source code provided in every chapter. These strategies are designed to be implemented by teams large and small, with varying skill sets, so you can apply these concepts and skills to your project right away. Responsive web design is the practice of building a website to suit base browser capability, then adding features that enhance the experience based on the user's device's capabilities. Applying these ideas to data produces visualizations that always look as if they were designed specifically for the device through which they are viewed. This book shows you how to incorporate these principles into your current practices, with highly practical hands-on training. Examine the hard data surrounding responsive design Master best practices with hands-on exercises Learn data-based document manipulation using D3.js Adapt your current strategies to responsive workflows Data is growing exponentially, and the need to visualize it in any context has become crucial. Traditional visualizations allow important data to become lost when viewed on a small screen, and the web traffic speaks for itself – viewers repeatedly demonstrate their preference for responsive design. If you're ready to create more accessible, take-anywhere visualizations, Building Responsive Data Visualization for the Web is your tailor-made solution.

Building Responsive Data Visualizations with D3.js

Building Responsive Data Visualizations with D3.js PDF Author: Merrill Cook
Publisher:
ISBN:
Category :
Languages : en
Pages :

Get Book Here

Book Description
"This video course starts out by describing ways in which D3.js fits into existing web standards to provide data visualization solutions that can be easily integrated. After working through the basic flow of simple visualizations, we'll start adding features: tool tips, axes, and scales. We'll take a look at interactivity and transitions. Then we'll walk through the use of external data sources, including CSV, TSV, JSON, and GeoJSON, which will prepare us for more in-depth visualizations. Further on we'll tackle responsive design, covering all the basic concepts, and then work our way through a site mockup the old fashioned way, looking for breakpoints and using media queries to provide smooth screen size transitions. Our work with responsive design will then be applied to a number of our early data visualizations. We'll resume our focus on responsive design later in the course when we'll cover using Bootstrap and Pym.js, a JavaScript library that enables the embedding of responsive iFrames. The data visualizations we'll tackle in the final sections of the course will include mapping with Topo and GeoJSON. By the end of this course, you will have an armory full of tools to create feature-rich data visualizations with D3.js that are responsive on different platforms."--Resource description page.

Building Responsive Data Visualization for the Web

Building Responsive Data Visualization for the Web PDF Author: Bill Hinderman
Publisher: John Wiley & Sons
ISBN: 1119067200
Category : Computers
Languages : en
Pages : 448

Get Book Here

Book Description
Unchain your data from the desktop with responsive visualizations Building Responsive Data Visualization for the Web is a handbook for any front-end development team needing a framework for integrating responsive web design into the current workflow. Written by a leading industry expert and design lead at Starbase Go, this book provides a wealth of information and practical guidance from the perspective of a real-world designer. You'll walk through the process of building data visualizations responsively as you learn best practices that build upon responsive web design principles, and get the hands-on practice you need with exercises, examples, and source code provided in every chapter. These strategies are designed to be implemented by teams large and small, with varying skill sets, so you can apply these concepts and skills to your project right away. Responsive web design is the practice of building a website to suit base browser capability, then adding features that enhance the experience based on the user's device's capabilities. Applying these ideas to data produces visualizations that always look as if they were designed specifically for the device through which they are viewed. This book shows you how to incorporate these principles into your current practices, with highly practical hands-on training. Examine the hard data surrounding responsive design Master best practices with hands-on exercises Learn data-based document manipulation using D3.js Adapt your current strategies to responsive workflows Data is growing exponentially, and the need to visualize it in any context has become crucial. Traditional visualizations allow important data to become lost when viewed on a small screen, and the web traffic speaks for itself – viewers repeatedly demonstrate their preference for responsive design. If you're ready to create more accessible, take-anywhere visualizations, Building Responsive Data Visualization for the Web is your tailor-made solution.

Mobile Data Visualization

Mobile Data Visualization PDF Author: Bongshin Lee
Publisher: CRC Press
ISBN: 1000522776
Category : Computers
Languages : en
Pages : 346

Get Book Here

Book Description
Mobile Data Visualization is about facilitating access to and understanding of data on mobile devices. Wearable trackers, mobile phones, and tablets are used by millions of people each day to read weather maps, financial charts, or personal health meters. What is required to create effective visualizations for mobile devices? This book introduces key concepts of mobile data visualization and discusses opportunities and challenges from both research and practical perspectives. Mobile Data Visualization is the first book to provide an overview of how to effectively visualize, analyze, and communicate data on mobile devices. Drawing from the expertise, research, and experience of an international range of academics and practitioners from across the domains of Visualization, Human Computer Interaction, and Ubiquitous Computing, the book explores the challenges of mobile visualization and explains how it differs from traditional data visualization. It highlights opportunities for reaching new audiences with engaging, interactive, and compelling mobile content. In nine chapters, this book presents interesting perspectives on mobile data visualization including: how to characterize and classify mobile visualizations; how to interact with them while on the go and with limited attention spans; how to adapt them to various mobile contexts; specific methods on how to design and evaluate them; reflections on privacy, ethical and other challenges, as well as an outlook to a future of ubiquitous visualization. This accessible book is a valuable and rich resource for visualization designers, practitioners, researchers, and students alike.

Learn Chart.js

Learn Chart.js PDF Author: Helder da Rocha
Publisher: Packt Publishing Ltd
ISBN: 1789342155
Category : Computers
Languages : en
Pages : 279

Get Book Here

Book Description
Design interactive graphics and visuals for your data-driven applications using the popular open-source Chart.js data visualization library. Key FeaturesHarness the power of JavaScript, HTML, and CSS to create interactive visualizationsDisplay quantitative information efficiently in the form of attractive charts by using Chart.js A practical guide for creating data-driven applications using open-source JavaScript libraryBook Description Chart.js is a free, open-source data visualization library, maintained by an active community of developers in GitHub, where it rates as the second most popular data visualization library. If you want to quickly create responsive Web-based data visualizations for the Web, Chart.js is a great choice. This book guides the reader through dozens of practical examples, complete with code you can run and modify as you wish. It is a practical hands-on introduction to Chart.js. If you have basic knowledge of HTML, CSS and JavaScript you can learn to create beautiful interactive Web Canvas-based visualizations for your data using Chart.js. This book will help you set up Chart.js in a Web page and show how to create each one of the eight Chart.js chart types. You will also learn how to configure most properties that override Chart’s default styles and behaviors. Practical applications of Chart.js are exemplified using real data files obtained from public data portals. You will learn how to load, parse, filter and select the data you wish to display from those files. You will also learn how to create visualizations that reveal patterns in the data. This book is based on Chart.js version 2.7.3 and ES2015 JavaScript. By the end of the book, you will be able to create beautiful, efficient and interactive data visualizations for the Web using Chart.js. What you will learnLearn how to create interactive and responsive data visualizations using Chart.jsLearn how to create Canvas-based graphics without Canvas programmingCreate composite charts and configure animated data updates and transitionsEfficiently display quantitative information using bar and line charts, scatterplots, and pie chartsLearn how to load, parse, and filter external files in JSON and CSV formatsUnderstand the benefits of using a data visualization frameworkWho this book is for The ideal target audience of this book includes web developers and designers, data journalists, data scientists and artists who wish to create interactive data visualizations for the Web. Basic knowledge of HTML, CSS, and JavaScript is required. No Canvas knowledge is necessary.

Data Visualization: Representing Information on Modern Web

Data Visualization: Representing Information on Modern Web PDF Author: Andy Kirk
Publisher: Packt Publishing Ltd
ISBN: 1787125076
Category : Computers
Languages : en
Pages : 531

Get Book Here

Book Description
Unleash the power of data by creating interactive, engaging, and compelling visualizations for the web About This Book Get a portable, versatile, and flexible data visualization design approach that will help you navigate the complex path towards success Get thorough explanation of the many visual variables and visualization taxonomy to provide you with a menu of creative options A comprehensive and contemporary introduction to data-driven visualization design and the most effective approaches to designing impact-maximizing and cognition-amplifying visualizations Who This Book Is For This course is for developers who are excited about data and who want to share that excitement with others and it will be handy for the web developers or data scientists who want to create interactive visualizations for the web. Prior knowledge of developing web applications is required. You should have a working knowledge of both JavaScript and HTML. What You Will Learn Harness the power of D3 by building interactive and real-time data-driven web visualizations Find out how to use JavaScript to create compelling visualizations of social data Identify the purpose of your visualization and your project's parameters to determine overriding design considerations across your project's execution Apply critical thinking to visualization design and get intimate with your dataset to identify its potential visual characteristics Explore the various features of HTML5 to design creative visualizations Discover what data is available on Stack Overflow, Facebook, Twitter, and Google+ Gain a solid understanding of the common D3 development idioms Find out how to write basic D3 code for server using Node.js In Detail Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories, and key insights that are locked away. This learning path is divided into three modules. The first module will equip you with the key techniques required to overcome contemporary data visualization challenges. After getting familiar with key concepts of data visualization, it's time to incorporate it with various technologies. In the second module, Social Data Visualization with HTML5 and JavaScript, it teaches you how to leverage HTML5 techniques through JavaScript to build visualizations. It also clears up how the often complicated OAuth protocol works to help you unlock a universe of social media data from sites such as Twitter, Facebook, and Google+. Once you are familiar with the concepts of incorporating data visualization with HTML5 and JavaScript, third module, Learning d3.js Data Visualization, will lead you to D3, which has emerged as one of the leading platforms to develop beautiful, interactive visualizations over the web. This module provides a strong foundation in designing compelling web visualizations with D3.js. By the end of this course, you will have unlocked the mystery behind successful data visualizations. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Data Visualization: a successful design process by Andy Kirk Social Data Visualization with HTML5 and JavaScript by Simon Timms Learning d3.js Data Visualization, Second Edition by Ǯdrew Rininsland and Swizec Teller Style and approach This course includes all the resources that will help you jump into creating interactive and engaging visualizations for the web. Through this comprehensive course, you'll learn how to create engaging visualizations for the web to represent your data from start to finish!

Mastering Azure Machine Learning

Mastering Azure Machine Learning PDF Author: Christoph Körner
Publisher: Packt Publishing Ltd
ISBN: 1789801524
Category : Computers
Languages : en
Pages : 437

Get Book Here

Book Description
Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and Kubernetes Key FeaturesMake sense of data on the cloud by implementing advanced analyticsTrain and optimize advanced deep learning models efficiently on Spark using Azure DatabricksDeploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS)Book Description The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud. The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure Machine Learning and takes you through the process of data experimentation, data preparation, and feature engineering using Azure Machine Learning and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure Automated Machine Learning and HyperDrive, and perform distributed training on Azure. Then, you'll learn different deployment and monitoring techniques using Azure Kubernetes Services with Azure Machine Learning, along with the basics of MLOps—DevOps for ML to automate your ML process as CI/CD pipeline. By the end of this book, you'll have mastered Azure Machine Learning and be able to confidently design, build and operate scalable ML pipelines in Azure. What you will learnSetup your Azure Machine Learning workspace for data experimentation and visualizationPerform ETL, data preparation, and feature extraction using Azure best practicesImplement advanced feature extraction using NLP and word embeddingsTrain gradient boosted tree-ensembles, recommendation engines and deep neural networks on Azure Machine LearningUse hyperparameter tuning and Azure Automated Machine Learning to optimize your ML modelsEmploy distributed ML on GPU clusters using Horovod in Azure Machine LearningDeploy, operate and manage your ML models at scaleAutomated your end-to-end ML process as CI/CD pipelines for MLOpsWho this book is for This machine learning book is for data professionals, data analysts, data engineers, data scientists, or machine learning developers who want to master scalable cloud-based machine learning architectures in Azure. This book will help you use advanced Azure services to build intelligent machine learning applications. A basic understanding of Python and working knowledge of machine learning are mandatory.

Learning Tableau 10

Learning Tableau 10 PDF Author: Joshua N. Milligan
Publisher: Packt Publishing Ltd
ISBN: 1786468921
Category : Computers
Languages : en
Pages : 432

Get Book Here

Book Description
Learn how to create effective data visualizations with Tableau and unlock a smarter approach to business analytics. It might just transform your organization About This Book Create stylish visualizations and dashboards that explain complexity with clarity Learn effective data storytelling to transform how your business uses ideas and makes decisions Explore all the new features in Tableau 10 and start to redefine what business analytics means to your organization Who This Book Is For Got data? Not sure what to make of it? This is the guide for you – whether you've been working with Tableau for years or are just beginning your adventure into business analytics. What You Will Learn Find out how to build effective visualizations and dashboards Prepare and clean your data so you can be sure Tableau is finding answers to your questions – not raising more problems Discover how to create advanced visualizations that explain complexity with clarity and style Dig deeper into your data with clustering and distribution models that allow you to analyze trends and make forecasts Learn how to use data storytelling to aid decision-making and strategy Share dashboards and visualizations to cultivate a culture where data is available and valued In Detail Tableau has for some time been one of the most popular Business Intelligence and data visualization tools available. Why? Because, quite simply, it's a tool that's responsive to the needs of modern businesses. But it's most effective when you know how to get what you want from it – it might make your business intelligent, but it isn't going to make you intelligent... We'll make sure you're well prepared to take full advantage of Tableau 10's new features. Whether you're an experienced data analyst that wants to explore 2016's new Tableau, or you're a beginner that wants to expand their skillset and bring a more professional and sharper approach to their organization, we've got you covered. Beginning with the fundamentals, such as data preparation, you'll soon learn how to build and customize your own data visualizations and dashboards, essential for high-level visibility and effective data storytelling. You'll also find out how to so trend analysis and forecasting using clustering and distribution models to inform your analytics. But it's not just about you – when it comes to data it's all about availability and access. That's why we'll show you how to share your Tableau visualizations. It's only once insights are shared and communicated that you – and your organization – will start making smarter and informed decisions. And really, that's exactly what this guide is for. Style and approach Practical yet comprehensive, this Tableau guide takes you from the fundamentals of the tool before diving deeper into creating advanced visualizations. Covering the latest features found in Tableau 10, this might be the guide that transforms your organization.

Mastering Azure Machine Learning

Mastering Azure Machine Learning PDF Author: Christoph Korner
Publisher: Packt Publishing Ltd
ISBN: 1803246790
Category : Computers
Languages : en
Pages : 624

Get Book Here

Book Description
Supercharge and automate your deployments to Azure Machine Learning clusters and Azure Kubernetes Service using Azure Machine Learning services Key Features Implement end-to-end machine learning pipelines on Azure Train deep learning models using Azure compute infrastructure Deploy machine learning models using MLOps Book Description Azure Machine Learning is a cloud service for accelerating and managing the machine learning (ML) project life cycle that ML professionals, data scientists, and engineers can use in their day-to-day workflows. This book covers the end-to-end ML process using Microsoft Azure Machine Learning, including data preparation, performing and logging ML training runs, designing training and deployment pipelines, and managing these pipelines via MLOps. The first section shows you how to set up an Azure Machine Learning workspace; ingest and version datasets; as well as preprocess, label, and enrich these datasets for training. In the next two sections, you'll discover how to enrich and train ML models for embedding, classification, and regression. You'll explore advanced NLP techniques, traditional ML models such as boosted trees, modern deep neural networks, recommendation systems, reinforcement learning, and complex distributed ML training techniques - all using Azure Machine Learning. The last section will teach you how to deploy the trained models as a batch pipeline or real-time scoring service using Docker, Azure Machine Learning clusters, Azure Kubernetes Services, and alternative deployment targets. By the end of this book, you'll be able to combine all the steps you've learned by building an MLOps pipeline. What you will learn Understand the end-to-end ML pipeline Get to grips with the Azure Machine Learning workspace Ingest, analyze, and preprocess datasets for ML using the Azure cloud Train traditional and modern ML techniques efficiently using Azure ML Deploy ML models for batch and real-time scoring Understand model interoperability with ONNX Deploy ML models to FPGAs and Azure IoT Edge Build an automated MLOps pipeline using Azure DevOps Who this book is for This book is for machine learning engineers, data scientists, and machine learning developers who want to use the Microsoft Azure cloud to manage their datasets and machine learning experiments and build an enterprise-grade ML architecture using MLOps. This book will also help anyone interested in machine learning to explore important steps of the ML process and use Azure Machine Learning to support them, along with building powerful ML cloud applications. A basic understanding of Python and knowledge of machine learning are recommended.