Download or read book Fullstack D3 and Data Visualization written by Amelia Wattenberger and published by Fullstack.IO. This book was released on 2019-02 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build beautiful data visualizations with D3 The Fullstack D3 book is the complete guide to D3. With dozens of code examples showing each step, you can gain new insights into your data by creating visualizations. Learn how to quickly turn data into insights with D3 We have the data. But it needs to be understood by humans. The best way to convert this data into an understandable format is to mold it into a data visualization. And D3 is the best tool for job if you need to create custom data visualizations. With Fullstack D3 and Data Visualization you and your team will be able to share key insights, uncover problems before they start, and impress your boss by creating gorgeous visualizations. What's Inside Chapter 0: Introduction When would you want to use D3.js? There is a spectrum of libraries to create charts on the web: on one end, you have easy-to-use, basic libraries that will create a standard chart type. Chapter 1: Making your first chart In this chapter we make a line chart. Line charts are a great starting place because of their popularity, but also because of their simplicity. Chapter 2: Making a scatterplot When looking at the relationship between two metrics, a scatterplot is a good choice. In this chapter we show how to create a scatterplot. Chapter 3: Making a bar chart In this chapter we cover how to create a histogram, which is a bar chart that shows the distribution of one metric, with the metric values on the x axis and the frequency of values on the y axis. Chapter 4: Animations and Transitions When we update our charts, we can animate elements from their old to their new positions. These animations can be visually exciting, but more importantly, they have functional benefits. Chapter 5: Interactions The biggest advantage of creating charts with JavaScript is the ability to respond to user input. Chapter 6: Making a map Maps are also uniquely good at answering geography-based questions. In this chapter, we'll build a map and learn how to plot values within a location. Chapter 7: Data Visualization Basics Now that we're comfortable with how to create a chart, we should zoom out a bit and talk about what chart to create. Chapter 8: Common Charts In this chapter, we talk about common chart types and when to use them. Chapter 9: Dashboard Design A dashboard is any web interface that makes sense out of dynamic data, and in this chapter we learn how to make one. Chapter 10: Advanced Visualization: Marginal Histogram First, we'll focus on enhancing a chart we've already made: our scatter plot. This chart will have multiple goals, all exploring the daily temperature ranges in our weather dataset. Chapter 11: Advanced Visualization: Radial Weather Chart We talked about radar charts in Chapter 10. For this project, we'll build a more complex radar chart. Chapter 12: Advanced Visualization: Animated Sankey Diagram In this project, we'll be simulating real data and creating an animated diagram to engage our viewers. Chapter 13: D3 and React What's the best way to draw a chart within React? It turns out that there is a fair bit of overlap in functionality between a React and D3 - we'll discuss how we can create blazing fast charts using the two together. Chapter 14: D3 and Angular In this chapter we show how to create optimized SVG charts using D3 and Angular.

Download or read book Data Sketches written by Nadieh Bremer and published by CRC Press. This book was released on 2021-02-09 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Data Sketches, Nadieh Bremer and Shirley Wu document the deeply creative process behind 24 unique data visualization projects, and they combine this with powerful technical insights which reveal the mindset behind coding creatively. Exploring 12 different themes – from the Olympics to Presidents & Royals and from Movies to Myths & Legends – each pair of visualizations explores different technologies and forms, blurring the boundary between visualization as an exploratory tool and an artform in its own right. This beautiful book provides an intimate, behind-the-scenes account of all 24 projects and shares the authors’ personal notes and drafts every step of the way. The book features: Detailed information on data gathering, sketching, and coding data visualizations for the web, with screenshots of works-in-progress and reproductions from the authors’ notebooks Never-before-published technical write-ups, with beginner-friendly explanations of core data visualization concepts Practical lessons based on the data and design challenges overcome during each project Full-color pages, showcasing all 24 final data visualizations This book is perfect for anyone interested or working in data visualization and information design, and especially those who want to take their work to the next level and are inspired by unique and compelling data-driven storytelling.

Download or read book Learn D3 js written by Helder da Rocha and published by Packt Publishing Ltd. This book was released on 2019-05-03 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the power of D3.js 5 and its integration with web technologies for building rich and interactive data visualization solutions Key FeaturesExplore the latest D3.js 5 for creating charts, plots, and force-directed graphicsPractical guide for creating interactive graphics and data-driven apps with JavaScriptBuild Real-time visualization and transition on web using SVG with D3.jsBook Description This book is a practical hands-on introduction to D3 (Data-driven Documents): the most popular open-source JavaScript library for creating interactive web-based data visualizations. Based entirely on open web standards, D3 provides an integrated collection of tools for efficiently binding data to graphical elements. If you have basic knowledge of HTML, CSS and JavaScript you can use D3.js to create beautiful interactive web-based data visualizations. D3 is not a charting library. It doesn’t contain any pre-defined chart types, but can be used to create whatever visual representations of data you can imagine. The goal of this book is to introduce D3 and provide a learning path so that you obtain a solid understanding of its fundamental concepts, learn to use most of its modules and functions, and gain enough experience to create your own D3 visualizations. You will learn how to create bar, line, pie and scatter charts, trees, dendograms, treemaps, circle packs, chord/ribbon diagrams, sankey diagrams, animated network diagrams, and maps using different geographical projections. Fundamental concepts are explained in each chapter and then applied to a larger example in step-by-step tutorials, complete with full code, from hundreds of examples you can download and run. This book covers D3 version 5 and is based on ES2015 JavaScript. What you will learnLearn to use D3.js version 5 and web standards to create beautiful interactive data-driven visualizations for the webBind data to DOM elements, applying different scales, color schemes and configuring smooth animated transitions for data updatesGenerate data structures and layouts for many popular chart formats Apply interactive behaviors to any chartCreate thematic maps based on GIS data using different geographical projections with interactive behaviors Load, parse and transform data from JSON and CSV formatsWho this book is for The book is intended for web developers, web designers, data scientists, artists, and any developer who wish to create interactive data visualization for the Web using D3. The book assumes basic knowledge of HTML, CSs, and JavaScript.

Download or read book D3 for the Impatient written by Philipp K. Janert and published by O'Reilly Media. This book was released on 2019-05-02 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you’re in a hurry to learn D3.js, the leading JavaScript library for web-based graphics and visualization, this book is for you. Written for technically savvy readers with a background in programming or data science, the book moves quickly, emphasizing unifying concepts and patterns. Anticipating common difficulties, author Philipp K. Janert teaches you how to apply D3 to your own problems. Assuming only a general programming background, but no previous experience with contemporary web development, this book explains supporting technologies such as SVG, HTML5, CSS, and the DOM as needed, making it a convenient one-stop resource for a technical audience. Understand D3 selections, the library’s fundamental organizing principle Learn how to create data-driven documents with data binding Create animated graphs and interactive user interfaces Draw figures with curves, shapes, and colors Use the built-in facilities for heatmaps, tree graphs, and networks Simplify your work by writing your own reusable components

Download or read book Data Visualization with Python and JavaScript written by Kyran Dale and published by "O'Reilly Media, Inc.". This book was released on 2016-06-30 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript libraries—including Scrapy, Matplotlib, Pandas, Flask, and D3—for crafting engaging, browser-based visualizations. As a working example, throughout the book Dale walks you through transforming Wikipedia’s table-based list of Nobel Prize winners into an interactive visualization. You’ll examine steps along the entire toolchain, from scraping, cleaning, exploring, and delivering data to building the visualization with JavaScript’s D3 library. If you’re ready to create your own web-based data visualizations—and know either Python or JavaScript— this is the book for you. Learn how to manipulate data with Python Understand the commonalities between Python and JavaScript Extract information from websites by using Python’s web-scraping tools, BeautifulSoup and Scrapy Clean and explore data with Python’s Pandas, Matplotlib, and Numpy libraries Serve data and create RESTful web APIs with Python’s Flask framework Create engaging, interactive web visualizations with JavaScript’s D3 library

Download or read book Data Visualization with D3 and AngularJS written by Christoph Körner and published by Packt Publishing Ltd. This book was released on 2015-04-27 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a web developer with experience in AngularJS and want to implement interactive visualizations using D3.js, this book is for you. Knowledge of SVG or D3.js will give you an edge to get the most out of this book.

Download or read book Interactive Data Visualization for the Web written by Scott Murray and published by "O'Reilly Media, Inc.". This book was released on 2013-03-11 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser

Download or read book Fullstack React written by Accomazzo Anthony and published by Fullstack.IO. This book was released on 2017-03 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: LEARN REACT TODAY The up-to-date, in-depth, complete guide to React and friends. Become a ReactJS expert today

Download or read book Software Engineering at Google written by Titus Winters and published by O'Reilly Media. This book was released on 2020-02-28 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, software engineers need to know not only how to program effectively but also how to develop proper engineering practices to make their codebase sustainable and healthy. This book emphasizes this difference between programming and software engineering. How can software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life? Based on their experience at Google, software engineers Titus Winters and Hyrum Wright, along with technical writer Tom Manshreck, present a candid and insightful look at how some of the world’s leading practitioners construct and maintain software. This book covers Google’s unique engineering culture, processes, and tools and how these aspects contribute to the effectiveness of an engineering organization. You’ll explore three fundamental principles that software organizations should keep in mind when designing, architecting, writing, and maintaining code: How time affects the sustainability of software and how to make your code resilient over time How scale affects the viability of software practices within an engineering organization What trade-offs a typical engineer needs to make when evaluating design and development decisions

Download or read book Real Time Analytics written by Byron Ellis and published by John Wiley & Sons. This book was released on 2014-06-23 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's "recipe" layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.

Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2017-09-25 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples

Download or read book Interpretable Machine Learning with Python written by Serg Masís and published by Packt Publishing Ltd. This book was released on 2021-03-26 with total page 737 pages. Available in PDF, EPUB and Kindle. Book excerpt: A deep and detailed dive into the key aspects and challenges of machine learning interpretability, complete with the know-how on how to overcome and leverage them to build fairer, safer, and more reliable models Key Features Learn how to extract easy-to-understand insights from any machine learning model Become well-versed with interpretability techniques to build fairer, safer, and more reliable models Mitigate risks in AI systems before they have broader implications by learning how to debug black-box models Book DescriptionDo you want to gain a deeper understanding of your models and better mitigate poor prediction risks associated with machine learning interpretation? If so, then Interpretable Machine Learning with Python deserves a place on your bookshelf. We’ll be starting off with the fundamentals of interpretability, its relevance in business, and exploring its key aspects and challenges. As you progress through the chapters, you'll then focus on how white-box models work, compare them to black-box and glass-box models, and examine their trade-off. You’ll also get you up to speed with a vast array of interpretation methods, also known as Explainable AI (XAI) methods, and how to apply them to different use cases, be it for classification or regression, for tabular, time-series, image or text. In addition to the step-by-step code, this book will also help you interpret model outcomes using examples. You’ll get hands-on with tuning models and training data for interpretability by reducing complexity, mitigating bias, placing guardrails, and enhancing reliability. The methods you’ll explore here range from state-of-the-art feature selection and dataset debiasing methods to monotonic constraints and adversarial retraining. By the end of this book, you'll be able to understand ML models better and enhance them through interpretability tuning. What you will learn Recognize the importance of interpretability in business Study models that are intrinsically interpretable such as linear models, decision trees, and Naïve Bayes Become well-versed in interpreting models with model-agnostic methods Visualize how an image classifier works and what it learns Understand how to mitigate the influence of bias in datasets Discover how to make models more reliable with adversarial robustness Use monotonic constraints to make fairer and safer models Who this book is for This book is primarily written for data scientists, machine learning developers, and data stewards who find themselves under increasing pressures to explain the workings of AI systems, their impacts on decision making, and how they identify and manage bias. It’s also a useful resource for self-taught ML enthusiasts and beginners who want to go deeper into the subject matter, though a solid grasp on the Python programming language and ML fundamentals is needed to follow along.

Download or read book Serverless Handbook written by Swizec Teller and published by . This book was released on 2021-06-27 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Serverless Handbook for frontend engineers is the resource I wish I had jumping into serverless. A guide borne of experience and pain. No academic bullshit where you're not sure if the author ever used this stuff in production. I have. From baby side-projects to high traffic data processing monsters. As Google likes to say: serverless architectures, ]from prototype to production to planet-scale Here's what early readers had to say. - Serverless Handbook taught me high-leveled topics. I don't like specific courses with source code (unless it's the exactly thing I want to build) but these chapters helped me to feel like i'm not a total noob anymore. The hand-drawn diagrams and high-leveled descriptions gave me the feeling that i don't have any critical "knowledge gaps" anymore - I'm using these skills on some serverless projects in a dayjob. Also very convenient to use with my side projects. - The code examples! I like that you included a lot of code examples. It sparked my interest in serverless. Since reading the book I've taken a few courses/workshops in serverless but this was the book that started the serverless journey for me. Can't wait to build a micro SaaS app with my friends Serverless Handbook takes you from backend beginner to solid full-stack engineer. It shows you the mindsets and tactics to use with any backend. It talks about distributed data processing, designing a REST API, how to build GraphQL, handling authentication, and keeping your code secure. Every chapter helps you choose what to do. Because your project is unique and understanding beats cookie-cutter recipes. This book is a why, not a how. But there's enough how to start you off: ) Serverless Handbook is everything I wish I knew about backend programming 10 years ago.

Download or read book Building Web Apps with Ember js written by Jesse Cravens and published by "O'Reilly Media, Inc.". This book was released on 2014-07-09 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you’re a web developer interested in building scalable single-page applications—full-stack, browser-based apps that connect to a backend—this practical guide shows you how to use Ember.js, the popular JavaScript framework based on the model-view-controller (MVC) architectural pattern. Through the course of the book, you’ll learn how to build a prototype Ember application (a musician index called Rock’n’Roll Call), using routers, templates, models, controllers, and views. You’ll also understand how Ember’s convention over configuration approach helps you persist data, build backend technologies, and create widgets for developing production-capable applications that behave like desktop software. Set up workflow management and boilerplate code creation Learn how Ember’s “developer ergonomics” help you use less code Write templates for the book’s prototype with Handlebars.js Use routers to manage application states without reloading the page Connect controllers and views with events, and sync data with data-binding Build an Ember backend with a RESTful API or Ruby on Rails Use the Ember-Data library to persist data and talk to the backend Write reusable encapsulated widgets to extend your applications

Download or read book Data Wrangling with JavaScript written by Ashley Davis and published by Simon and Schuster. This book was released on 2018-12-02 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Data Wrangling with JavaScript is hands-on guide that will teach you how to create a JavaScript-based data processing pipeline, handle common and exotic data, and master practical troubleshooting strategies. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Why not handle your data analysis in JavaScript? Modern libraries and data handling techniques mean you can collect, clean, process, store, visualize, and present web application data while enjoying the efficiency of a single-language pipeline and data-centric web applications that stay in JavaScript end to end. About the Book Data Wrangling with JavaScript promotes JavaScript to the center of the data analysis stage! With this hands-on guide, you'll create a JavaScript-based data processing pipeline, handle common and exotic data, and master practical troubleshooting strategies. You'll also build interactive visualizations and deploy your apps to production. Each valuable chapter provides a new component for your reusable data wrangling toolkit. What's inside Establishing a data pipeline Acquisition, storage, and retrieval Handling unusual data sets Cleaning and preparing raw dataInteractive visualizations with D3 About the Reader Written for intermediate JavaScript developers. No data analysis experience required. About the Author Ashley Davis is a software developer, entrepreneur, author, and the creator of Data-Forge and Data-Forge Notebook, software for data transformation, analysis, and visualization in JavaScript. Table of Contents Getting started: establishing your data pipeline Getting started with Node.js Acquisition, storage, and retrieval Working with unusual data Exploratory coding Clean and prepare Dealing with huge data files Working with a mountain of data Practical data analysis Browser-based visualization Server-side visualization Live data Advanced visualization with D3 Getting to production

Download or read book Integrating D3 js with React written by Elad Elrom and published by Apress. This book was released on 2021-06-04 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrate D3.js into a React TypeScript project and create a chart component working in harmony with React. This book will show you how utilize D3 with React to bring life to your charts. Seasoned author Elad Elrom will show you how to create simple charts such as line, bar, donut, scatter, histogram and others, and advanced charts such as a world map and force charts. You'll also learn to share the data across your components and charts using React Recoil state management. Then integrate third-party chart libraries that are built on D3 such as Rechart, Visx, Nivo, React-vi, and Victory and in the end deploy your chart as a server or serverless app on popular platforms. React and D3 are two of the most popular frameworks in their respective areas – learn to bring them together and take your storytelling to the next level. What You'll Learn Set up your project with React, TypeScript and D3.js Create simple and advanced D3.js charts Work with complex charts such as world and force charts Integrate D3 data with React state management Improve the performance of your D3 components Deploy as a server or serverless app and debug test Who This Book Is For Readers that already have basic knowledge of React, HTML, CSS and JavaScript.

Download or read book Python Data Analytics written by Fabio Nelli and published by Apress. This book was released on 2018-09-27 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data. What You'll LearnUnderstand the core concepts of data analysis and the Python ecosystem Go in depth with pandas for reading, writing, and processing data Use tools and techniques for data visualization and image analysis Examine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorch Who This Book Is For Experienced Python developers who need to learn about Pythonic tools for data analysis