Data Wrangling With Javascript
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| Author | : Ashley Davis |
| Publisher | : Simon and Schuster |
| Total Pages | : 657 |
| Release | : 2018-12-02 |
| Genre | : Computers |
| ISBN | : 1638351139 |
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
| Author | : Jacqueline Kazil |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 507 |
| Release | : 2016-02-04 |
| Genre | : Computers |
| ISBN | : 1491948779 |
How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that’s initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started. Through various step-by-step exercises, you’ll learn how to acquire, clean, analyze, and present data efficiently. You’ll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain. Quickly learn basic Python syntax, data types, and language concepts Work with both machine-readable and human-consumable data Scrape websites and APIs to find a bounty of useful information Clean and format data to eliminate duplicates and errors in your datasets Learn when to standardize data and when to test and script data cleanup Explore and analyze your datasets with new Python libraries and techniques Use Python solutions to automate your entire data-wrangling process
| Author | : Jim Wilson |
| Publisher | : Pragmatic Bookshelf |
| Total Pages | : 428 |
| Release | : 2018-01-04 |
| Genre | : Computers |
| ISBN | : 168050536X |
Node.js is the platform of choice for creating modern web services. This fast-paced book gets you up to speed on server-side programming with Node.js 8, as you develop real programs that are small, fast, low-profile, and useful. Take JavaScript beyond the browser, explore dynamic language features, and embrace evented programming.Harness the power of the event loop and non-blocking I/O to create highly parallel microservices and applications. This expanded and updated second edition showcases the latest ECMAScript features, current best practices, and modern development techniques. JavaScript is the backbone of the modern web, powering nearly every web app's user interface. Node.js is JavaScript for the server. This greatly expanded second edition introduces new language features while dramatically increasing coverage of core topics. Each hands-on chapter offers progressively more challenging topics and techniques, broadening your skill set and enabling you to think in Node.js. Write asynchronous, non-blocking code using Node.js's style and patterns. Cluster and load balance services with Node.js core features and third-party tools. Harness the power of databases such as Elasticsearch and Redis. Work with many protocols, create RESTful web services, TCP socket clients and servers, and more. Test your code's functionality with Mocha, and manage its life cycle with npm. Discover how Node.js pairs a server-side event loop with a JavaScript runtime to produce screaming fast, non-blocking concurrency. Through a series of practical programming domains, use the latest available ECMAScript features and harness key Node.js classes and popular modules. Create rich command-line tools and a web-based UI using modern web development techniques. Join the smart and diverse community that's rapidly advancing the state of the art in JavaScript development. What You Need: Node.js 8.x Operating system with bash-like shell OMQ (pronounced "Zero-M-Q") library, version 3.2 or higher Elasticsearch version 5.0 or higher jq version 1.5 or higher Redis version 3.2 or higher
| Author | : John Resig |
| Publisher | : Manning |
| Total Pages | : 0 |
| Release | : 2013-01-17 |
| Genre | : Computers |
| ISBN | : 9781933988696 |
Summary Secrets of the Javascript Ninja takes you on a journey towards mastering modern JavaScript development in three phases: design, construction, and maintenance. Written for JavaScript developers with intermediate-level skills, this book will give you the knowledge you need to create a cross-browser JavaScript library from the ground up. About this Book You can't always attack software head-on. Sometimes youcome at it sideways or sneak up from behind. You need tomaster an arsenal of tools and know every stealthy trick.You have to be a ninja. Secrets of the JavaScript Ninja leads you down the pathway toJavaScript enlightenment. This unique book starts with keyconcepts, like the relationships between functions, objects, andclosures, taught from the master's perspective. You'll grow fromapprentice to ninja as you soak up fresh insights on the techniquesyou use every day and discover features and capabilities you neverknew about. When you reach the final chapters, you'll be ready tocode brilliant JavaScript applications and maybe even write yourown libraries and frameworks. You don't have to be a ninja to read this book—just be willing tobecome one. Are you ready? Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside Functions, objects, closures, regular expressions, and more Seeing applications and libraries from the right perspective Dealing with the complexities of cross-browser development Modern JavaScript design About the Authors John Resig is an acknowledged JavaScript authority and the creatorof the jQuery library. Bear Bibeault is a web developer and coauthorof Ajax in Practice, Prototype and Scriptaculous in Action, and jQueryin Action from Manning. Table of Contents PART 1 PREPARING FOR TRAINING Enter the ninja Arming with testing and debugging PART 2 APPRENTICE TRAINING Functions are fundamental Wielding functions Closing in on closures Object-orientation with prototypes Wrangling regular expressions Taming threads and timers PART 3 NINJA TRAINING Ninja alchemy: runtime code evaluation With statements Developing cross-browser strategies Cutting through attributes, properties, and CSS PART 4 MASTER TRAINING Surviving events Manipulating the DOM CSS selector engines
| Author | : Susan E. McGregor |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 416 |
| Release | : 2021-12-03 |
| Genre | : Computers |
| ISBN | : 1492091456 |
The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources Understand and use programming basics in Python to wrangle data at scale Organize, document, and structure your code using best practices Collect data from structured data files, web pages, and APIs Perform basic statistical analyses to make meaning from datasets Visualize and present data in clear and compelling ways
| Author | : Stefanie Molin |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 702 |
| Release | : 2019-07-26 |
| Genre | : Computers |
| ISBN | : 1789612802 |
Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery Key FeaturesPerform efficient data analysis and manipulation tasks using pandasApply pandas to different real-world domains using step-by-step demonstrationsGet accustomed to using pandas as an effective data exploration toolBook Description Data analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate significant value. Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification, using scikit-learn, to make predictions based on past data. By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. What you will learnUnderstand how data analysts and scientists gather and analyze dataPerform data analysis and data wrangling in PythonCombine, group, and aggregate data from multiple sourcesCreate data visualizations with pandas, matplotlib, and seabornApply machine learning (ML) algorithms to identify patterns and make predictionsUse Python data science libraries to analyze real-world datasetsUse pandas to solve common data representation and analysis problemsBuild Python scripts, modules, and packages for reusable analysis codeWho this book is for This book is for data analysts, data science beginners, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. You will also find this book useful if you are a data scientist who is looking to implement pandas in machine learning. Working knowledge of Python programming language will be beneficial.
| Author | : Michael Morrison |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 650 |
| Release | : 2007-12-20 |
| Genre | : Computers |
| ISBN | : 0596527748 |
Provides information on scripting Web applications with JavaScript.
| Author | : Rising Odegua |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 477 |
| Release | : 2021-09-24 |
| Genre | : Computers |
| ISBN | : 1801078416 |
Get hands-on with building data-driven applications using Danfo.js in combination with other data analysis tools and techniques Key FeaturesBuild microservices to perform data transformation and ML model serving in JavaScriptExplore what Danfo.js is and how it helps with data analysis and data visualizationCombine Danfo.js and TensorFlow.js for machine learningBook Description Most data analysts use Python and pandas for data processing for the convenience and performance these libraries provide. However, JavaScript developers have always wanted to use machine learning in the browser as well. This book focuses on how Danfo.js brings data processing, analysis, and ML tools to JavaScript developers and how to make the most of this library to build data-driven applications. Starting with an overview of modern JavaScript, you'll cover data analysis and transformation with Danfo.js and Dnotebook. The book then shows you how to load different datasets, combine and analyze them by performing operations such as handling missing values and string manipulations. You'll also get to grips with data plotting, visualization, aggregation, and group operations by combining Danfo.js with Plotly. As you advance, you'll create a no-code data analysis and handling system and create-react-app, react-table, react-chart, Draggable.js, and tailwindcss, and understand how to use TensorFlow.js and Danfo.js to build a recommendation system. Finally, you'll build a Twitter analytics dashboard powered by Danfo.js, Next.js, node-nlp, and Twit.js. By the end of this app development book, you'll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser. What you will learnPerform data experimentation and analysis with Danfo.js and DnotebookBuild machine learning applications using Danfo.js integrated with TensorFlow.jsConnect Danfo.js with popular database applications to aid data analysisCreate a no-code data analysis and handling system using internal librariesDevelop a recommendation system with Danfo.js and TensorFlow.jsBuild a Twitter analytics dashboard for sentiment analysis and other types of data insightsWho this book is for This book is for data analysts, data scientists, and JavaScript developers who want to create data-driven applications in the JavaScript/Node.js environment. Intermediate-level knowledge of JavaScript programming and data science using pandas is expected.
| Author | : Wes McKinney |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 553 |
| Release | : 2017-09-25 |
| Genre | : Computers |
| ISBN | : 1491957611 |
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
| Author | : Richard M. Reese |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 376 |
| Release | : 2017-01-10 |
| Genre | : Computers |
| ISBN | : 1785281240 |
Examine the techniques and Java tools supporting the growing field of data science About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples Make your Java applications more capable using machine learning Who This Book Is For This book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful. What You Will Learn Understand the nature and key concepts used in the field of data science Grasp how data is collected, cleaned, and processed Become comfortable with key data analysis techniques See specialized analysis techniques centered on machine learning Master the effective visualization of your data Work with the Java APIs and techniques used to perform data analysis In Detail Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application. The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. The final chapter illustrates an in-depth data science problem and provides a comprehensive, Java-based solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book. Style and approach This book follows a tutorial approach, providing examples of each of the major concepts covered. With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.
