Javascript And Jquery For Data Analysis And Visualization

Go beyond design concepts—build dynamic datavisualizations using JavaScript JavaScript and jQuery for Data Analysis and Visualizationgoes beyond design concepts to show readers how to build dynamic,best-of-breed visualizations using JavaScript—the mostpopular language for web programming. The authors show data analysts, developers, and web designershow they can put the power and flexibility of modern JavaScriptlibraries to work to analyze data and then present it usingbest-of-breed visualizations. They also demonstrate the use of eachtechnique with real-world use cases, showing how to apply theappropriate JavaScript and jQuery libraries to achieve the desiredvisualization. All of the key techniques and tools are explained in thisfull-color, step-by-step guide. The companion website includes allsample codes used to generate the visualizations in the book, datasets, and links to the libraries and other resources covered. Go beyond basic design concepts and get a firm grasp ofvisualization approaches and techniques using JavaScript andjQuery Discover detailed, step-by-step directions for buildingspecific types of data visualizations in this full-color guide Learn more about the core JavaScript and jQuery libraries thatenable analysis and visualization Find compelling stories in complex data, and create amazingvisualizations cost-effectively Let JavaScript and jQuery for Data Analysis andVisualization be the resource that guides you through themyriad strategies and solutions for combining analysis andvisualization with stunning results.

Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. A quick, instruction-based guide full of examples that details on the various aspects of Flot and how users can apply it to data groups for interactive data representation techniques.If you are a data visualization developer, mapping and presentation software developer, or anyone with an interest in jQuery visualization, this book is ideal for you. If you have a working knowledge of jQuery and JavaScript, you can use this book to add sophisticated visualizations to your web application so that your users can easily understand data that is crucial to them.

You've got data to communicate. But what kind of visualization do you choose, how do you build it, and how do you ensure that it's up to the demands of the Web? In Data Visualization with JavaScript, you'll learn how to use JavaScript, HTML, and CSS to build the most practical visualizations for your data. Step-by-step examples walk you through creating, integrating, and debugging different types of visualizations and will have you building basic visualizations, like bar, line, and scatter graphs, in no time. Then you'll move on to more advanced topics, including how to: Create tree maps, heat maps, network graphs, word clouds, and timelines Map geographic data, and build sparklines and composite charts Add interactivity and retrieve data with AJAX Manage data in the browser and build data-driven web applications Harness the power of the Flotr2, Flot, Chronoline.js, D3.js, Underscore.js, and Backbone.js libraries If you already know your way around building a web page but aren't quite sure how to build a good visualization, Data Visualization with JavaScript will help you get your feet wet without throwing you into the deep end. Before you know it, you'll be well on your way to creating simple, powerful data visualizations.

Applied User Data Collection and Analysis Using JavaScript and PHP is designed to provide the technical skills and competency to gather a wide range of user data from web applications in both active and passive methods. This is done by providing the reader with real-world examples of how a variety of different JavaScript- and PHP-based libraries can be used to gather data using custom feedback forms and embedded data gathering tools. Once data has been gathered, this book explores the process of working with numerical data, text analysis, visualization approaches, statistics, and rolling out developed applications to both data analysts and users alike. Using the collected data, this book aims to provide a deeper understanding of user behavior and interests, allowing application developers to further enhance web-application development. Key Features: Complete real-world examples of gathering data from users and web environments Offers readers the fundamentals of text analysis using JavaScript and PHP Allows the user to understand and harness JavaScript data-visualization tools Integration of new and existing data sources into a single, bespoke web-based analysis environment

Pro Data Visualization using R and JavaScript makes the R language approachable, and promotes the idea of data gathering and analysis. You'll see how to use R to interrogate and analyze your data, and then use the D3 JavaScript library to format and display that data in an elegant, informative, and interactive way. You will learn how to gather data effectively, and also how to understand the philosophy and implementation of each type of chart, so as to be able to represent the results visually. With the popularity of the R language, the art and practice of creating data visualizations is no longer the preserve of mathematicians, statisticians, or cartographers. As technology leaders, we can gather metrics around what we do and use data visualizations to communicate that information. Pro Data Visualization using R and JavaScript combines the power of the R language with the simplicity and familiarity of JavaScript to display clear and informative data visualizations. Gathering and analyzing empirical data is the key to truly understanding anything. We can track operational metrics to quantify the health of our products in production. We can track quality metrics of our projects, and even use our data to identify bad code. Visualizing this data allows anyone to read our analysis and easily get a deep understanding of the story the data tells.

How do you turn raw, unprocessed, or malformed data into dynamic, interactive web visualizations? In this practical book, author Kyran Dale shows data scientists and analysts--as well as Python and JavaScript developers--how to create the ideal toolchain for the job. By providing engaging examples and stressing hard-earned best practices, this guide teaches you how to leverage the power of best-of-breed Python and JavaScript libraries. Python provides accessible, powerful, and mature libraries for scraping, cleaning, and processing data. And while JavaScript is the best language when it comes to programming web visualizations, its data processing abilities can't compare with Python's. Together, these two languages are a perfect complement for creating a modern web-visualization toolchain. This book gets you started. You'll learn how to: Obtain data you need programmatically, using scraping tools or web APIs: Requests, Scrapy, Beautiful Soup Clean and process data using Python's heavyweight data processing libraries within the NumPy ecosystem: Jupyter notebooks with pandas+Matplotlib+Seaborn Deliver the data to a browser with static files or by using Flask, the lightweight Python server, and a RESTful API Pick up enough web development skills (HTML, CSS, JS) to get your visualized data on the web Use the data you've mined and refined to create web charts and visualizations with Plotly, D3, Leaflet, and other libraries

This book shows how to use JavaScript, HTML, and CSS to build the most practical visualizations for your data. Step-by-step examples walk you through creating, integrating, and debugging different types of visualizations and will have you building basic visualizations, like bar, line, and scatter graphs, in no time. Advanced topics include: tree maps, heat maps, network graphs, word clouds, and timelines; map geographic data, sparklines and composite charts; adding interactivity and retrieving data with AJAX; managing data in the browser and building data-driven web applications; Flotr2, Flot, Chronoline.js, D3.js, Underscore.js, and Backbone.js libraries. --

Learn how to build an interactive source code analytics system using Roslyn and JavaScript. This concise 150 page book will help you create and use practical code analysis tools utilizing the new features of Microsoft’s Roslyn compiler to understand the health of your code and identify parts of the code for refactoring. Source code is one of the biggest assets of a software company. However if not maintained well, it can become a big liability. As source code becomes larger. more complex and accessed via the cloud, maintaining code quality becomes even more challenging. The author provides straightforward tools and advice on how to manage code quality in this new environment. Roslyn exposes a set of APIs which allow developers to parse their C# and VB.NET code and drastically lower the barrier to entry for Meta programming in .NET. Roslyn has a dedicated set of APIs for creating custom refactoring for integrating with Visual Studio. This title will show readers how to use Roslyn along with industry standard JavaScript visualization APIs like HighCharts, D3.js etc to create a scalable and highly responsive source code analytics system. What You Will Learn Understand the Roslyn Syntax API Use Data Visualization techniques to assist code analysis process visually Code health monitoring matrices (from the standard of Code Query Language) Code mining techniques to identify design patterns used in source code Code forensics techniques to identify probable author of a given source code Techniques to identify duplicate/near duplicate code Who This Book is For .NET Software Developers and Architects