Javascript And Open Data

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Data Science Fundamentals With R Python And Open Data

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Author : Marco Cremonini
language : en
Publisher: John Wiley & Sons
Release Date : 2024-04-02

Data Science Fundamentals With R Python And Open Data written by Marco Cremonini and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-02 with Computers categories.

Data Science Fundamentals with R, Python, and Open Data Introduction to essential concepts and techniques of the fundamentals of R and Python needed to start data science projects Organized with a strong focus on open data, Data Science Fundamentals with R, Python, and Open Data discusses concepts, techniques, tools, and first steps to carry out data science projects, with a focus on Python and RStudio, reflecting a clear industry trend emerging towards the integration of the two. The text examines intricacies and inconsistencies often found in real data, explaining how to recognize them and guiding readers through possible solutions, and enables readers to handle real data confidently and apply transformations to reorganize, indexing, aggregate, and elaborate. This book is full of reader interactivity, with a companion website hosting supplementary material including datasets used in the examples and complete running code (R scripts and Jupyter notebooks) of all examples. Exam-style questions are implemented and multiple choice questions to support the readers’ active learning. Each chapter presents one or more case studies. Written by a highly qualified academic, Data Science Fundamentals with R, Python, and Open Data discuss sample topics such as: Data organization and operations on data frames, covering reading CSV dataset and common errors, and slicing, creating, and deleting columns in R Logical conditions and row selection, covering selection of rows with logical condition and operations on dates, strings, and missing values Pivoting operations and wide form-long form transformations, indexing by groups with multiple variables, and indexing by group and aggregations Conditional statements and iterations, multicolumn functions and operations, data frame joins, and handling data in list/dictionary format Data Science Fundamentals with R, Python, and Open Data is a highly accessible learning resource for students from heterogeneous disciplines where Data Science and quantitative, computational methods are gaining popularity, along with hard sciences not closely related to computer science, and medical fields using stochastic and quantitative models.

Building Data Driven Applications With Danfo Js

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Author : Rising Odegua
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-09-24

Building Data Driven Applications With Danfo Js written by Rising Odegua and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-24 with Computers categories.

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.

Data Visualization With Python And Javascript

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Author : Kyran Dale
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-06-30

Data Visualization With Python And Javascript written by Kyran Dale and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-30 with Computers categories.

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

Open Heritage Data

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Author : Henriette Roued-Cunliffe
language : en
Publisher: Facet Publishing
Release Date : 2020-06-30

Open Heritage Data written by Henriette Roued-Cunliffe and has been published by Facet Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-30 with Language Arts & Disciplines categories.

Digital heritage can mean many things, from building a database on Egyptian textiles to interacting with family historians over Facebook. However, it is rare to see professionals with a heritage background working practically with the heritage datasets in their charge. Many institutions who have the resources to do so, leave this work to computer programmers, missing the opportunity to share their knowledge and passion for heritage through innovative technology. Open Heritage Data: An introduction to research, publishing and programming with open data in the heritage sector has been written for practitioners, researchers and students working in the GLAM (Galleries, Libraries, Archives and Museums) sector who do not have a computer science background, but who want to work more confidently with heritage data. It combines current research in open data with the author’s extensive experience in coding and teaching coding to provide a step-by-step guide to working actively with the increasing amounts of data available. Coverage includes: • an introduction to open data as a next step in heritage mediation • an overview of the laws most relevant to open heritage data • an Open Heritage Data Model and examples of how institutions publish heritage data • an exploration of use and reuse of heritage data • tutorials on visualising and combining heritage datasets and on using heritage data for research. Featuring sample code, case examples from around the world and step-by-step technical tutorials, this book will be a valuable resource for anyone in the GLAM sector involved in, or who wants to be involved in creating, publishing, using and reusing open heritage data.

Javascript Step By Step

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Author : Steve Suehring
language : en
Publisher: Pearson Education
Release Date : 2013-06-15

Javascript Step By Step written by Steve Suehring and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-15 with Computers categories.

Your hands-on guide to JavaScript fundamentals Expand your expertise—and teach yourself the fundamentals of JavaScript. If you have previous programming experience but are new to JavaScript, this tutorial delivers the step-by-step guidance and coding exercises you need to master core topics and techniques. Discover how to: Work with JavaScript syntax, variables, and data types Master techniques for building cross-browser programs Speed up and simplify app development with jQuery Quickly retrieve data from a server using AJAX requests Adapt your app for mobile devices with jQuery Mobile Build Windows 8 apps using HTML, CSS, and JavaScript

Open Data For Sustainable Community

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Author : Neha Sharma
language : en
Publisher: Springer Nature
Release Date : 2020-12-01

Open Data For Sustainable Community written by Neha Sharma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-01 with Technology & Engineering categories.

This book is an attempt to bring value to the enterprise pursuits in the areas of research and innovation around the specific issues in terms of topic selection, open data resources and researcher orientation. Over the last 300 years, industrial revolutions have had game-changing impact on societies. Presently, by and large, we are at the crossroads of the fourth industrial revolution, where phygital systems are going to play a massive role, where digital systems can simulate and go beyond the limitations of the physical world, thereby enabling a new world order. This transformation is cutting across every sphere known to mankind. The world will become a globally localized marketplace. In today’s business world, sustainability is a corporate agenda. Enterprises are also aiming to be purpose-driven, adaptive and resilient to disruptions. The contributions to community and environment are part of their corporate branding. The book explores and presents a part of the open data sets from government institutions to achieve the sustainable goals at local level, in turn contributing towards global mission. As the topic suggests, the authors are looking at some of the specific issues in the areas of environment, agriculture and health care through the lens of data science. The authors believe that the above three areas chosen have deep relevance in today’s world. The intent is to explore these issues from a data and analytics perspective and identify cracks through which deeper inroads can be made. Conscious efforts have been taken to make use of all the major data science techniques like prediction, classification, clustering, and correlation. Given the above background, deeper waters will be explored through the contents of this book.

Open Cities Open Data

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Author : Scott Hawken
language : en
Publisher: Springer Nature
Release Date : 2019-09-26

Open Cities Open Data written by Scott Hawken and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-26 with Social Science categories.

Today the world’s largest economies and corporations trade in data and its products to generate value in new disruptive markets. Within these markets vast streams of data are often inaccessible or untapped and controlled by powerful monopolies. Counter to this exclusive use of data is a promising world-wide “open-data” movement, promoting freely accessible information to share, reuse and redistribute. The provision and application of open data has enormous potential to transform exclusive, technocratic “smart cities” into inclusive and responsive “open-cities”. This book argues that those who contribute urban data should benefit from its production. Like the city itself, the information landscape is a public asset produced through collective effort, attention, and resources. People produce data through their engagement with the city, creating digital footprints through social medial, mobility applications, and city sensors. By opening up data there is potential to generate greater value by supporting unforeseen collaborations, spontaneous urban innovations and solutions, and improved decision-making insights. Yet achieving more open cities is made challenging by conflicting desires for urban anonymity, sociability, privacy and transparency. This book engages with these issues through a variety of critical perspectives, and presents strategies, tools and case studies that enable this transformation.

Data Wrangling With Javascript

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Author : Ashley Davis
language : en
Publisher: Simon and Schuster
Release Date : 2018-12-02

Data Wrangling With Javascript written by Ashley Davis and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-02 with Computers categories.

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

Data Visualization With Javascript

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Author : Stephen A. Thomas
language : en
Publisher: No Starch Press
Release Date : 2015-03-15

Data Visualization With Javascript written by Stephen A. Thomas and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-15 with Computers categories.

You’ve got data to communicate. But what kind of visualization do you choose, how do you build your visualizations, and how do you ensure that they're up to the demands of the Web? In Data Visualization with JavaScript, you’ll learn how to use JavaScript, HTML, and CSS to build practical visualizations for your data. Step-by-step examples walk you through creating, integrating, and debugging different types of visualizations and you'll be building basic visualizations (like bar, line, and scatter graphs) in no time. You'll also learn 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. You’ll soon be well on your way to creating simple, powerful data visualizations.

Linked Open Data

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Author : Kingsley Okoye
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-11-19

Linked Open Data written by Kingsley Okoye and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-19 with Computers categories.

This book intends to provide the reader with a comprehensive knowledge of the latest developments within the Linked Open Data (LOD) framework and the benefits of supported systems. The book covers the entire spectrum of “Linked Open Data - Applications, Trends and Future Developments” with six chapters. Each of the chapters provides an all-inclusive conceptualization of the LOD concepts, methodological approaches, case studies, and the main applications both in theory and practice. This book is a reference and educational book targeted to data scientists, software developers, semantic web engineers, information system designers, process managers, teachers, and researchers, and general consumers in application of LOD methods within various contexts.