D3 Js Quick Start Guide

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D3.js Quick Start Guide

Author: Matthew Huntington
language: en
Publisher: Packt Publishing Ltd
Release Date: 2018-09-27
This book will help you build interactive graphs that are viewable in any web browser using JavaScript, D3.js, and SVG. You will learn how to make a scatter plot, a bar graph, a pie chart, a force directed graph, and a map. Key FeaturesTakes you through the most common graphs you'll needAdd interactivity to your visualizationsEasy to follow buildsBook Description D3.js is a JavaScript library that allows you to create graphs and data visualizations in the browser with HTML, SVG, and CSS. This book will take you from the basics of D3.js, so that you can create your own interactive visualizations, to creating the most common graphs that you will encounter as a developer, scientist, statistician, or data scientist. The book begins with an overview of SVG, the basis for creating two-dimensional graphics in the browser. Once the reader has a firm understanding of SVG, we will tackle the basics of how to use D3.js to connect data to our SVG elements. We will start with a scatter plot that maps run data to circles on a graph, and expand our scatter plot to make it interactive. You will see how you can easily allow the users of your graph to create, edit, and delete run data by simply dragging and clicking the graph. Next, we will explore creating a bar graph, using external data from a mock API. After that, we will explore animations and motion with a bar graph, and use various physics-based forces to create a force-directed graph. Finally, we will look at how to use GeoJSON data to create a map. What you will learnBuild a scatter plotBuild a bar graphBuild a pie chartBuild a force-directed graphBuild a mapBuild interactivity into your graphsWho this book is for This book is for web developers, interactive news developers, data scientists, and anyone interested in representing data through interactive visualizations on the Web with D3. Some basic knowledge of JavaScript is expected, but no prior experience with data visualization or D3 is required to follow this book.
Network Science with Python and NetworkX Quick Start Guide

Author: Edward L. Platt
language: en
Publisher: Packt Publishing Ltd
Release Date: 2019-04-26
Manipulate and analyze network data with the power of Python and NetworkX Key FeaturesUnderstand the terminology and basic concepts of network scienceLeverage the power of Python and NetworkX to represent data as a networkApply common techniques for working with network data of varying sizesBook Description NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use. If you’re a data scientist, engineer, or computational social scientist, this book will guide you in using the Python programming language to gain insights into real-world networks. Starting with the fundamentals, you’ll be introduced to the core concepts of network science, along with examples that use real-world data and Python code. This book will introduce you to theoretical concepts such as scale-free and small-world networks, centrality measures, and agent-based modeling. You’ll also be able to look for scale-free networks in real data and visualize a network using circular, directed, and shell layouts. By the end of this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems. What you will learnUse Python and NetworkX to analyze the properties of individuals and relationshipsEncode data in network nodes and edges using NetworkXManipulate, store, and summarize data in network nodes and edgesVisualize a network using circular, directed and shell layoutsFind out how simulating behavior on networks can give insights into real-world problemsUnderstand the ongoing impact of network science on society, and its ethical considerationsWho this book is for If you are a programmer or data scientist who wants to manipulate and analyze network data in Python, this book is perfect for you. Although prior knowledge of network science is not necessary, some Python programming experience will help you understand the concepts covered in the book easily.
Learn Chart.js

Author: Helder da Rocha
language: en
Publisher: Packt Publishing Ltd
Release Date: 2019-02-28
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.