This book provides a complete and modern guide to web scraping, using Python as the programming language, without glossing over important details or best practices. Written with a data science audience in mind, the book explores both scraping and the larger context of web technologies in which it operates, to ensure full understanding. The authors recommend web scraping as a powerful tool for any data scientist’s arsenal, as many data science projects start by obtaining an appropriate data set. Starting with a brief overview on scraping and real-life use cases, the authors explore the core concepts of HTTP, HTML, and CSS to provide a solid foundation. Along with a quick Python primer, they cover Selenium for JavaScript-heavy sites, and web crawling in detail. The book finishes with a recap of best practices and a collection of examples that bring together everything you've learned and illustrate various data science use cases. What You'll Learn Leverage well-established best practices and commonly-used Python packages Handle today's web, including JavaScript, cookies, and common web scraping mitigation techniques Understand the managerial and legal concerns regarding web scraping Who This Book is For A data science oriented audience that is probably already familiar with Python or another programming language or analytical toolkit (R, SAS, SPSS, etc). Students or instructors in university courses may also benefit. Readers unfamiliar with Python will appreciate a quick Python primer in chapter 1 to catch up with the basics and provide pointers to other guides as well.

If programming is magic then web scraping is surely a form of wizardry. By writing a simple automated program, you can query web servers, request data, and parse it to extract the information you need. The expanded edition of this practical book not only introduces you web scraping, but also serves as a comprehensive guide to scraping almost every type of data from the modern web. Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the server's response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario you're likely to encounter. Parse complicated HTML pages Develop crawlers with the Scrapy framework Learn methods to store data you scrape Read and extract data from documents Clean and normalize badly formatted data Read and write natural languages Crawl through forms and logins Scrape JavaScript and crawl through APIs Use and write image-to-text software Avoid scraping traps and bot blockers Use scrapers to test your website

Python Web Scraping Cookbook is your comprehensive guide to building efficient and functional web scraping tools using Python. With practical recipes, you'll learn to overcome the challenges of dynamic content, captcha, and irregular web structures while deploying scalable solutions. What this Book will help me do Master the use of Python libraries like BeautifulSoup and Scrapy for scraping data. Perfect techniques for handling JavaScript-heavy sites using Selenium. Learn to overcome web scraping challenges, such as captchas and rate-limiting. Design scalable scraping pipelines with cloud deployment in AWS. Understand web data extraction techniques with XPath, CSS selectors, and more. Author(s) Michael Heydt is a seasoned software engineer and technical author with a focus on data engineering and cloud solutions. Having worked with Python extensively, he brings real-world insights into web scraping. His practical approach simplifies complex concepts. Who is it for? This book is perfect for Python developers and data enthusiasts keen to master web scraping techniques. If you're a programmer with insights into Python scripting and wish to scrape, analyze, and utilize web data efficiently, this book is for you.

D3.js in Action, Second Edition is completely revised and updated for D3 v4 and ES6. It's a practical tutorial for creating interactive graphics and data-driven applications using D3. About the Technology Visualizing complex data is hard. Visualizing complex data on the web is darn near impossible without D3.js. D3 is a JavaScript library that provides a simple but powerful data visualization API over HTML, CSS, and SVG. Start with a structure, dataset, or algorithm; mix in D3; and you can programmatically generate static, animated, or interactive images that scale to any screen or browser. It's easy, and after a little practice, you'll be blown away by how beautiful your results can be! About the Book D3.js in Action, Second Edition is a completely updated revision of Manning's bestselling guide to data visualization with D3. You'll explore dozens of real-world examples in full-color, including force and network diagrams, workflow illustrations, geospatial constructions, and more! Along the way, you'll pick up best practices for building interactive graphics, animations, and live data representations. You'll also step through a fully interactive application created with D3 and React. What's Inside Rich full-color diagrams and illustrations Updated for D3 v4 and ES6 Reusable layouts and components Geospatial data visualizations Mixed-mode rendering About the Reader Suitable for web developers with HTML, CSS, and JavaScript skills. No specialized data science skills required. About the Author Elijah Meeks is a senior data visualization engineer at Netflix. Quotes From basic to complex, this book gives you the tools to create beautiful data visualizations. - Claudio Rodriguez, Cox Media Group The best reference for one of the most useful DataViz tools. - Jonathan Rioux, TD Insurance From toy examples to techniques for real projects. Shows how all the pieces fit together. - Scott McKissock, USAID A clever way to immerse yourself in the D3.js world. - Felipe Vildoso Castillo, University of Chile

This book, "Learning D3.js 5 Mapping", guides developers through the process of creating dynamic and interactive data visualizations. With a focus on D3.js, you'll learn to harness the power of JavaScript to create maps and graphical objects that inform and engage. What this Book will help me do Gain expertise in working with SVG geometric shapes to design compelling graphics. Learn techniques to manage, process, and use geographic data effectively. Master adding interactivity to visual maps to provide an immersive user experience. Understand how to optimize and manipulate geoJSON files using topoJSON. Learn to create varied map types, such as hexbins and globes, using D3.js and Canvas. Author(s) None Newton and Oscar Villarreal, among others, collaborated to author this guide. They are experienced in front-end development and data visualization, bringing a practical and hands-on approach to learning through this book. Their backgrounds ensure the book addresses common challenges faced during implementation, offering thoughtful solutions. Who is it for? "Learning D3.js 5 Mapping" is perfect for web developers familiar with HTML, CSS, and JavaScript who want to expand their expertise in data visualization and mapping. If you're looking to incorporate interactive charts or maps into your web applications, this book will provide practical guidance and solid fundamentals. No prior experience with D3.js is necessary.

Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll learn an iterative approach that lets you quickly change the kind of analysis you’re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization. Build value from your data in a series of agile sprints, using the data-value pyramid Extract features for statistical models from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future via classification and regression Translate predictions into actions Get feedback from users after each sprint to keep your project on track

Learn how today’s businesses can transform themselves by leveraging real-time data and advanced machine learning analytics. This book provides prescriptive guidance for architects and developers on the design and development of modern Internet of Things (IoT) and Advanced Analytics solutions. In addition, Business in Real-Time Using Azure IoT and Cortana Intelligence Suite offers patterns and practices for those looking to engage their customers and partners through Software-as-a-Service solutions that work on any device. Whether you're working in Health & Life Sciences, Manufacturing, Retail, Smart Cities and Buildings or Process Control, there exists a common platform from which you can create your targeted vertical solutions. Business in Real-Time Using Azure IoT and Cortana Intelligence Suite uses a reference architecture as a road map. Building on Azure’s PaaS services, you'll see how a solution architecture unfolds that demonstrates a complete end-to-end IoT and Advanced Analytics scenario. What You'll Learn: Automate your software product life cycle using PowerShell, Azure Resource Manager Templates, and Visual Studio Team Services Implement smart devices using Node.JS and C# Use Azure Streaming Analytics to ingest millions of events Provide both "Hot" and "Cold" path outputs for real-time alerts, data transformations, and aggregation analytics Implement batch processing using Azure Data Factory Create a new form of Actionable Intelligence (AI) to drive mission critical business processes Provide rich Data Visualizations across a wide variety of mobile and web devices Who This Book is For: Solution Architects, Software Developers, Data Architects, Data Scientists, and CIO/CTA Technical Leadership Professionals

"Python Web Scraping" is a practical guide to extracting and processing online data using the Python programming language. With this book, you'll learn step-by-step how to build web scrapers and crawlers that can handle a range of data sources and structures. After reading this, you will be equipped to tackle real-world web scraping challenges effectively. What this Book will help me do Learn how to extract structured data from standard webpages using Python. Gain proficiency with libraries such as Selenium and PyQt for handling dynamic and JavaScript-dependent content. Build concurrent scrapers to efficiently process large volumes of web pages in parallel. Understand and implement form interaction automation for data extraction from complex websites. Develop advanced scrapers using Scrapy to handle sophisticated web crawling tasks. Author(s) None Jarmul is an experienced data scientist and programmer with extensive knowledge in Python. They bring practical expertise from working on real-world web scraping projects. In their work, they focus on creating content that empowers readers by demystifying complex technical topics. Who is it for? This book is perfect for software developers eager to dive into web scraping using Python, even if they're new to the subject. If you have basic to intermediate Python skills and want to automate data collection and processing, this is the book for you. The techniques here are valuable for tackling diverse data extraction scenarios.

Scala will be a valuable tool to have on hand during your data science journey for everything from data cleaning to cutting-edge machine learning About This Book Build data science and data engineering solutions with ease An in-depth look at each stage of the data analysis process — from reading and collecting data to distributed analytics Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulations, and source code Who This Book Is For This learning path is perfect for those who are comfortable with Scala programming and now want to enter the field of data science. Some knowledge of statistics is expected. What You Will Learn Transfer and filter tabular data to extract features for machine learning Read, clean, transform, and write data to both SQL and NoSQL databases Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Load data from HDFS and HIVE with ease Run streaming and graph analytics in Spark for exploratory analysis Bundle and scale up Spark jobs by deploying them into a variety of cluster managers Build dynamic workflows for scientific computing Leverage open source libraries to extract patterns from time series Master probabilistic models for sequential data In Detail Scala is especially good for analyzing large sets of data as the scale of the task doesn’t have any significant impact on performance. Scala’s powerful functional libraries can interact with databases and build scalable frameworks — resulting in the creation of robust data pipelines. The first module introduces you to Scala libraries to ingest, store, manipulate, process, and visualize data. Using real world examples, you will learn how to design scalable architecture to process and model data — starting from simple concurrency constructs and progressing to actor systems and Apache Spark. After this, you will also learn how to build interactive visualizations with web frameworks. Once you have become familiar with all the tasks involved in data science, you will explore data analytics with Scala in the second module. You’ll see how Scala can be used to make sense of data through easy to follow recipes. You will learn about Bokeh bindings for exploratory data analysis and quintessential machine learning with algorithms with Spark ML library. You’ll get a sufficient understanding of Spark streaming, machine learning for streaming data, and Spark graphX. Armed with a firm understanding of data analysis, you will be ready to explore the most cutting-edge aspect of data science — machine learning. The final module teaches you the A to Z of machine learning with Scala. You’ll explore Scala for dependency injections and implicits, which are used to write machine learning algorithms. You’ll also explore machine learning topics such as clustering, dimentionality reduction, Naïve Bayes, Regression models, SVMs, neural networks, and more. This learning path combines some of the best that Packt has to offer into one complete, curated package. It includes content from the following Packt products: Scala for Data Science, Pascal Bugnion Scala Data Analysis Cookbook, Arun Manivannan Scala for Machine Learning, Patrick R. Nicolas Style and approach A complete package with all the information necessary to start building useful data engineering and data science solutions straight away. It contains a diverse set of recipes that cover the full spectrum of interesting data analysis tasks and will help you revolutionize your data analysis skills using Scala. Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the code file.

Your indispensable guide to mastering the efficient use of D3.js in professional-standard data visualization projects. You will learn what data visualization is, how to work with it, and how to think like a D3.js expert, both practically and theoretically. Practical D3.js does not just show you how to use D3.js, it teaches you how to think like a data scientist and work with the data in the real world. In Part One, you will learn about theories behind data visualization. In Part Two, you will learn how to use D3.js to create the best charts and layouts. Uniquely, this book intertwines the technical details of D3.js with practical topics such as data journalism and the use of open government data. Written by leading data scientists Tarek Amr and Rayna Stamboliyska, this book is your guide to using D3.js in the real world -- add it to your library today. You Will Learn: How to think like a data scientist and present data in the best way What structure and design strategies you can use for compelling data visualization How to use data binding, animations and events, scales, and color pickers How to use shapes, path generators, arcs and polygons Who This Book is For: This book is for anyone who wants to learn to master the use of D3.js in a practical manner, while still learning the important theoretical aspects needed to enable them to work with their data in the best possible way.

Learning Pentaho CTools is a comprehensive guide to building sophisticated and custom analytics dashboards using the powerful capabilities of Pentaho CTools. This book walks you through the process of creating interactive dashboards, integrating data sources, and applying data visualization best practices. You'll quickly gain the expertise needed to create impactful dashboards with ease. What this Book will help me do Master installing and configuring CTools for Pentaho to jumpstart dashboard development. Harness diverse data sources and deliver data in formats like CSV, JSON, and XML for customized analytics. Design and implement dynamic, visually stunning dashboards using Community Dashboard Framework (CDF). Deploy and integrate plugins, leverage widgets, and manage dashboards effectively with version control. Enhance interactivity by customizing dashboard components, charts, and filters to suit unique requirements. Author(s) None Gaspar, an expert in Pentaho and its tools, has been a Senior Consultant at Pentaho, where he gained in-depth experience crafting analytics solutions. He brings to this book his teaching passion and field expertise, combining theoretical insights with practical applications. His approachable style ensures readers can follow technical concepts effectively. Who is it for? This book is ideal for developers who are looking to enhance their understanding of Pentaho's CTools portfolio to build advanced dashboards. A working knowledge of JavaScript and CSS will enable readers to get the most out of this guide. Whether you aim to extend your analytics capabilities or learn the tools from scratch, this book bridges the gap between learning and application.

Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science. About the Technology Many companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering what you need to learn to begin a career as a data scientist can seem bewildering. This book is designed to help you get started. About the Book Introducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You'll explore data visualization, graph databases, the use of NoSQL, and the data science process. You'll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you'll have the solid foundation you need to start a career in data science. What's Inside Handling large data Introduction to machine learning Using Python to work with data Writing data science algorithms About the Reader This book assumes you're comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required. About the Authors Davy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors. Quotes Read this book if you want to get a quick overview of data science, with lots of examples to get you started! - Alvin Raj, Oracle The map that will help you navigate the data science oceans. - Marius Butuc, Shopify Covers the processes involved in data science from end to end… A complete overview. - Heather Campbell, Kainos A must-read for anyone who wants to get into the data science world. - Hector Cuesta, Big Data Bootcamp

Embark on a journey to create stunning web-based 3D applications and games using Babylon.js, a powerful JavaScript framework. This essentials book takes you from the ground up, teaching the theory and practical applications of 3D development, with a particular focus on ease and accessibility. By the end of this guide, you'll possess the skills to design and implement dynamic 3D experiences. What this Book will help me do Gain a fundamental understanding of TypeScript and its advantages in large-scale projects like 3D engines. Master the foundational principles of 3D development with Babylon.js, emphasized through hands-on practice and clear theory. Learn to apply materials in Babylon.js, enabling you to alter and enrich the visual appeal of 3D objects. Incorporate collision physics and gameplay dynamics by understanding essential concepts like impostors in 3D simulations. Utilize advanced Babylon.js features, such as 3D audio spatialization and rendering post-process effects, to create immersive experiences. Author(s) None Moreau-Mathis, a software developer with significant experience, has worked on developing cutting-edge applications at companies like Microsoft. Their expertise in 3D development frameworks, particularly Babylon.js, has enabled them to break down complex technical concepts into approachable lessons. Moreau-Mathis combines a passion for sharing knowledge with years of hands-on experience to provide readers with practical and inspirational advice. Who is it for? This book is perfect for developers familiar with HTML5 and seeking to begin 3D Web application and game development using Babylon.js. Readers should have basic programming knowledge, such as in Object-Oriented Programming, and familiarity with web development concepts to grasp framework architecture effectively. Whether you are enhancing your web development toolkit or starting out with 3D, this book will help you achieve your aims.

This book dives into the practical application of R's power combined with Shiny's simplicity to build web-based analytics and interactive data summary tools. By following this step-by-step guide, you'll go from the basics of building with R and Shiny to creating sophisticated custom dashboards and interactive web apps. What this Book will help me do Create interactive web apps and dashboards using Shiny with impressive user interfaces. Integrate Shiny applications into custom HTML and CSS-based web pages for enhanced flexibility. Produce user-friendly Shiny applications extended with JavaScript and jQuery for added functionality. Develop web solutions that include interactive graphics, maps, and data analysis summaries. Deliver and deploy web apps securely using cloud solutions or self-hosted servers. Author(s) Chris Beeley, an experienced R developer and teacher, has a robust background in statistical programming and data analysis. Chris is passionate about sharing knowledge through practical examples and hands-on exercises. As the author of this book, Chris ensures that readers receive a clear and approachable entry into web application development using Shiny. Who is it for? This book is ideal for data enthusiasts, analysts, and developers looking to transition their analytic skills to the web. It caters to readers with basic programming knowledge but does not require prior experience with R or Shiny. It is perfect for professionals and learners wanting to create interactive analytics tools, dashboards, or data-driven web applications.

Explore the possibilities of web scraping using Python with this practical guide. The book provides a comprehensive introduction to extracting information from web pages, managing complex scraping scenarios, and utilizing specialized tools such as Scrapy. Whether you're dealing with static pages or interactive web content, this book equips you with the skills to gather and process web data efficiently. What this Book will help me do Gain proficiency in writing Python scripts to extract data from web pages. Learn to build and manage multithreaded crawlers to handle large-scale scraping tasks. Master techniques for interacting with dynamic web content and JavaScript-rendered pages. Understand how to work with web forms, sessions, and tackle challenges like CAPTCHA. Implement practical examples of web scraping using Scrapy for real-world data projects. Author(s) Richard Penman is an experienced software engineer and an expert in Python programming and web development. With years of practical expertise in web crawling and data extraction, Richard shares his extensive knowledge in this field to make complex tasks accessible to developers of all levels. His thoughtful approach aims to empower readers to confidently tackle data challenges on the web. Who is it for? This book is ideal for developers and technical professionals who want to learn effective techniques for web scraping with Python. A basic understanding of programming concepts and experience with Python will help readers get the most out of the practical examples. It's also suitable for advanced learners looking to apply Python skills for automating web data extraction tasks. If you're enthusiastic about turning web data into actionable insights, this guide is for you.

Have you ever wanted to transform your data analysis in R into interactive, web-based dashboards and applications? "Learning Shiny" is your guide to mastering R's Shiny framework to create dynamic, visual, and engaging web applications. With its step-by-step approach, this book enables you to harness Shiny's features effectively. What this Book will help me do Understand the core principles of R and data processing using tools like apply and lapply, empowering you to handle data programmatically. Learn the Shiny framework fundamentals, including structuring an interactive application using UI and server scripts. Create stunning visualizations and dashboards using libraries like ggplot2 and integrate Shiny seamlessly. Deploy and host Shiny web applications on Linux servers for effective sharing and collaboration. Enhance your applications with JavaScript integrations, using tools like D3.js, for advanced customization. Author(s) Hernan Resnizky is a renowned data scientist and educator with extensive experience in R programming and Shiny application development. Known for his clear teaching style, he has guided numerous professionals in using R for real-world applications. His practical approach ensures readers not only learn techniques but understand how to apply them effectively. Who is it for? "Learning Shiny" is ideal for data scientists looking to showcase their work through interactive web apps and visualizations, and for web developers curious about leveraging the Shiny framework in R. Beginners as well as those with some R experience will find tailored guidance to suit their level. If you aim to expand your toolkit with web-focused R capabilities, this book is for you.

D3.js in Action is a practical tutorial for creating interactive graphics and data-driven applications using D3.js. You'll start with in-depth explanations of D3's out-of-the-box layouts, along with dozens of practical use cases that align with different types of visualizations. Then, you'll explore practical techniques for content creation, animation, and representing dynamic data—including interactive graphics and data streamed live over the web. The final chapters show you how to use D3's rich interaction model as the foundation for a complete web application. In the end, you'll be ready to integrate D3.js into your web development process and transform any site into a more engaging and sophisticated user experience. About the Technology D3.js is a JavaScript library that allows data to be represented graphically on a web page. Because it uses the broadly supported SVG standard, D3 allows you to create scalable graphs for any modern browser. You start with a structure, dataset, or algorithm and programmatically generate static, interactive, or animated images that responsively scale to any screen. About the Book D3.js in Action introduces you to the most powerful web data visualization library available and shows you how to use it to build interactive graphics and data-driven applications. You'll start with dozens of practical use cases that align with different types of charts, networks, and maps using D3's out-of-the-box layouts. Then, you'll explore practical techniques for content design, animation, and representation of dynamic data—including interactive graphics and live streaming data. What's Inside Interacting with vector graphics Expressive data visualization Creating rich mapping applications Prepping your data Complete data-driven web apps in D3 About the Reader Readers need basic HTML, CSS, and JavaScript skills. No experience with D3 or SVG is required. About the Author Elijah Meeks is a senior data visualization engineer at Netflix. His D3.js portfolio includes work at Stanford University and with well-known companies worldwide. Quotes A mandatory introduction to a very complex and powerful library. - Stephen Wakely, Thomson Reuters Quickly gets you coding amazing visualizations. - Ntino Krampis, PhD, City University of New York A remarkable exploration of the world of dataviz possibilities with D3. - Arun Noronha, Directworks Inc. A must-have book. - Arif Shaikh, Sony Pictures Entertainment One of the most comprehensive books about data visualization I have ever read. - Andrea Mostosi, The Fool s.r.l.

Each new print copy includes Navigate 2 Advantage Access that unlocks a comprehensive and interactive eBook, student practice activities and assessments, a full suite of instructor resources, and learning analytics reporting tools.

Fully revised and updated, the Sixth Edition of the best-selling text Computer Science Illuminated retains the accessibility and in-depth coverage of previous editions, while incorporating all-new material on cutting-edge issues in computer science. Authored by the award-winning Nell Dale and John Lewis, Computer Science Illuminated’s unique and innovative layered approach moves through the levels of computing from an organized, language-neutral perspective.

Designed for the introductory computing and computer science course, this student-friendly Sixth Edition provides students with a solid foundation for further study, and offers non-majors a complete introduction to computing.

Key Features of the Sixth Edition include:

Access to Navigate 2 online learning materials including a comprehensive and interactive eBook, student practice activities and assessments, learning analytics reporting tools, and more
Completely revised sections on HTML and CSS
Updates regarding Top Level Domains, Social Networks, and Google Analytics
All-new section on Internet management, including ICANN control and net neutrality 
New design, including fully revised figures and tables
New and updated Did You Know callouts are included in the chapter margins
New and revised Ethical Issues and Biographies throughout emphasize the history and breadth of computing
Available in our customizable PUBLISH platform

A collection of programming language chapters are available as low-cost bundling options. Available chapters include: Java, C++, Python, Alice, SQL, VB.NET, RUBY, Perl, Pascal, and JavaScript.

With Navigate 2, technology and content combine to expand the reach of your classroom. Whether you teach an online, hybrid, or traditional classroom-based course, Navigate 2 delivers unbeatable value. Experience Navigate 2 today at www.jblnavigate.com/2

In this fast-paced 100-page guide, you’ll learn to load, display and interact with dynamic, data-powered Visio diagrams in SharePoint 2013 or Office 365. Visio Services Quick Guide gives you the tools to build anything from a simple project workflow to an organizational infrastructure diagram, powered by real data from SharePoint or SQL Server. Colleagues can load your diagrams entirely in the browser, meaning that a single Visio client installation is enough to get started. Readers with JavaScript experience will also find out how to get additional control over Visio diagrams using the JavaScript mashup API, and how to build a custom data provider. The final chapter covers some useful information on administering Visio Services. Get started bringing your Visio diagrams to life with the Visio Services Quick Guide.

Create Web Charts with D3 shows how to convert your data into eye-catching, innovative, animated, and highly interactive browser-based charts. This book is suitable for developers of all experience levels and needs: if you want power and control and need to create data visualization beyond traditional charts, then D3 is the JavaScript library for you. By the end of the book, you will have a good knowledge of all the elements needed to manage data from every possible source, from high-end scientific instruments to Arduino boards, from PHP SQL databases queries to simple HTML tables, and from Matlab calculations to reports in Excel. This book contains content previously published in Beginning JavaScript Charts. Create all kinds of charts using the latest technologies available on browsers Full of step-by-step examples, Create Web Charts with D3 introduces you gradually to all aspects of chart development, from the data source to the choice of which solution to apply. This book provides a number of tools that can be the starting point for any project requiring graphical representations of data, whether using commercial libraries or your own