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Data Visualization with Python and JavaScript

Data Visualization with Python and JavaScript Author Kyran Dale
ISBN-10 9781491920541
Release 2016-06-30
Pages 592
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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



Data Visualization with Python and JavaScript

Data Visualization with Python and JavaScript Author Kyran Dale
ISBN-10 9781491920534
Release 2016-06-30
Pages 592
Download Link Click Here

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



DATA VISUALIZATION WITH PYTHON JAVASCRIPT

DATA VISUALIZATION WITH PYTHON   JAVASCRIPT Author KYRAN. DALE
ISBN-10 935213429X
Release 2016
Pages
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DATA VISUALIZATION WITH PYTHON JAVASCRIPT has been writing in one form or another for most of life. You can find so many inspiration from DATA VISUALIZATION WITH PYTHON JAVASCRIPT also informative, and entertaining. Click DOWNLOAD or Read Online button to get full DATA VISUALIZATION WITH PYTHON JAVASCRIPT book for free.



Interactive Data Visualization for the Web

Interactive Data Visualization for the Web Author Scott Murray
ISBN-10 9781491921319
Release 2017-08-03
Pages 474
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Create and publish your own interactive data visualization projects on the web—even if you have little or no experience with data visualization or web development. It’s inspiring and fun with this friendly, accessible, and practical hands-on introduction. This fully updated and expanded second edition takes you through the fundamental concepts and methods of D3, the most powerful JavaScript library for expressing data visually in a web browser. Ideal for designers with no coding experience, reporters exploring data journalism, and anyone who wants to visualize and share data, this step-by-step guide will also help you expand your web programming skills by teaching you the basics of HTML, CSS, JavaScript, and SVG. Learn D3 4.x—the latest D3 version—with downloadable code and over 140 examples Create bar charts, scatter plots, pie charts, stacked bar charts, and force-directed graphs Use smooth, animated transitions to show changes in your data Introduce interactivity to help users explore your data Create custom geographic maps with panning, zooming, labels, and tooltips Walk through the creation of a complete visualization project, from start to finish Explore inspiring case studies with nine accomplished designers talking about their D3-based projects



Data Visualization with JavaScript

Data Visualization with JavaScript Author Stephen A. Thomas
ISBN-10 9781593276058
Release 2015
Pages 365
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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.



Making Data Visual

Making Data Visual Author Danyel Fisher
ISBN-10 9781491928448
Release 2017-12-20
Pages 168
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You have a mound of data front of you and a suite of computation tools at your disposal. Which parts of the data actually matter? Where is the insight hiding? If you’re a data scientist trying to navigate the murky space between data and insight, this practical book shows you how to make sense of your data through high-level questions, well-defined data analysis tasks, and visualizations to clarify understanding and gain insights along the way. When incorporated into the process early and often, iterative visualization can help you refine the questions you ask of your data. Authors Danyel Fisher and Miriah Meyer provide detailed case studies that demonstrate how this process can evolve in the real world. You’ll learn: The data counseling process for moving from general to more precise questions about your data, and arriving at a working visualization The role that visual representations play in data discovery Common visualization types by the tasks they fulfill and the data they use Visualization techniques that use multiple views and interaction to support analysis of large, complex data sets



Mastering Python Data Visualization

Mastering Python Data Visualization Author Kirthi Raman
ISBN-10 9781783988334
Release 2015-10-27
Pages 372
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Generate effective results in a variety of visually appealing charts using the plotting packages in Python About This Book Explore various tools and their strengths while building meaningful representations that can make it easier to understand data Packed with computational methods and algorithms in diverse fields of science Written in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs data visualization and wants to develop existing knowledge about Python to build analytical results and produce some amazing visual display, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed. What You Will Learn Gather, cleanse, access, and map data to a visual framework Recognize which visualization method is applicable and learn best practices for data visualization Get acquainted with reader-driven narratives and author-driven narratives and the principles of perception Understand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with it Explore with various visualization choices how Python can be very useful in computation in the field of finance and statistics Get to know why Python is the second choice after Java, and is used frequently in the field of machine learning Compare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.js Discover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis. By the end of this book, you will be able to effectively solve a broad set of data analysis problems. Style and approach The approach of this book is not step by step, but rather categorical. The categories are based on fields such as bioinformatics, statistical and machine learning, financial computation, and linear algebra. This approach is beneficial for the community in many different fields of work and also helps you learn how one approach can make sense across many fields



Data Wrangling with Python

Data Wrangling with Python Author Jacqueline Kazil
ISBN-10 9781491948774
Release 2016-02-04
Pages 508
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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



Python for Data Analysis

Python for Data Analysis Author Wes McKinney
ISBN-10 9781491957615
Release 2017-09-25
Pages 550
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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



D3 js 4 x Data Visualization

D3 js 4 x Data Visualization Author Ændrew Rininsland
ISBN-10 9781787128156
Release 2017-04-28
Pages 308
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Create and publish your own interactive and compelling data visualizations with D3.js 4.x About This Book Build interactive and rich graphics and visualization using JavaScript`s powerful library D3.js Learn D3 from the ground up, using the all-new version 4 of the library Gain insight into producing high-quality, extensible charts and visualizations using best practices such as writing testable, extensible code and strong typing Who 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. What You Will Learn Map data to visual elements using D3's scales Draw SVG elements using D3's shape generators Transform data using D3's collection methods Use D3's various layout patterns to quickly generate various common types of chart Write modern JavaScript using ES2017 and Babel Explore the basics of unit testing D3 visualizations using Mocha and Chai Write and deploy a simple Node.js web service to render charts via HTML Canvas Understand what makes a good data visualization and how to use the tools at your disposal to create accurate charts In Detail Want to get started with impressive interactive visualizations and implement them in your daily tasks? This book offers the perfect solution-D3.js. It has emerged as the most popular tool for data visualization. This book will teach you how to implement the features of the latest version of D3 while writing JavaScript using the newest tools and technique You will start by setting up the D3 environment and making your first basic bar chart. You will then build stunning SVG and Canvas-based data visualizations while writing testable, extensible code,as accurate and informative as it is visually stimulating. Step-by-step examples walk you through creating, integrating, and debugging different types of visualization and will have you building basic visualizations (such as bar, line, and scatter graphs) in no time. By the end of this book, you will have mastered the techniques necessary to successfully visualize data and will be ready to use D3 to transform any data into an engaging and sophisticated visualization. Style and approach This book follows a tutorial-based approach in teaching the world's most powerful data visualization library, D3.



Agile Data Science 2 0

Agile Data Science 2 0 Author Russell Jurney
ISBN-10 9781491960066
Release 2017-06-07
Pages 352
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Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll learn an iterative approach that lets you quickly change the kind of analysis you’re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization. Build value from your data in a series of agile sprints, using the data-value pyramid Extract features for statistical models from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future via classification and regression Translate predictions into actions Get feedback from users after each sprint to keep your project on track



Mastering Python Data Analysis

Mastering Python Data Analysis Author Magnus Vilhelm Persson
ISBN-10 9781783553303
Release 2016-06-27
Pages 284
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Become an expert at using Python for advanced statistical analysis of data using real-world examples About This Book Clean, format, and explore data using graphical and numerical summaries Leverage the IPython environment to efficiently analyze data with Python Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data Who This Book Is For If you are a competent Python developer who wants to take your data analysis skills to the next level by solving complex problems, then this advanced guide is for you. Familiarity with the basics of applying Python libraries to data sets is assumed. What You Will Learn Read, sort, and map various data into Python and Pandas Recognise patterns so you can understand and explore data Use statistical models to discover patterns in data Review classical statistical inference using Python, Pandas, and SciPy Detect similarities and differences in data with clustering Clean your data to make it useful Work in Jupyter Notebook to produce publication ready figures to be included in reports In Detail Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. Ever imagined how to become an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? Well, look no further, this is the book you want! Through this comprehensive guide, you will explore data and present results and conclusions from statistical analysis in a meaningful way. You'll be able to quickly and accurately perform the hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. You'll start off by learning about the tools available for data analysis in Python and will then explore the statistical models that are used to identify patterns in data. Gradually, you'll move on to review statistical inference using Python, Pandas, and SciPy. After that, we'll focus on performing regression using computational tools and you'll get to understand the problem of identifying clusters in data in an algorithmic way. Finally, we delve into advanced techniques to quantify cause and effect using Bayesian methods and you'll discover how to use Python's tools for supervised machine learning. Style and approach This book takes a step-by-step approach to reading, processing, and analyzing data in Python using various methods and tools. Rich in examples, each topic connects to real-world examples and retrieves data directly online where possible. With this book, you are given the knowledge and tools to explore any data on your own, encouraging a curiosity befitting all data scientists.



Mining the Social Web

Mining the Social Web Author Matthew A. Russell
ISBN-10 9781449388348
Release 2011-01-21
Pages 332
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Provides information on data analysis from a vareity of social networking sites, including Facebook, Twitter, and LinkedIn.



Visualizing Data

Visualizing Data Author Ben Fry
ISBN-10 9780596519308
Release 2007-12-18
Pages 382
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Provides information on the methods of visualizing data on the Web, along with example projects and code.



Learning Object Oriented Programming

Learning Object Oriented Programming Author Gastón C. Hillar
ISBN-10 9781785289934
Release 2015-07-16
Pages 280
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Learning Object-Oriented Programming is an easy-to-follow guide full of hands-on examples of solutions to common problems with object-oriented code in Python, JavaScript, and C#. It starts by helping you to recognize objects from real-life scenarios and demonstrates that working with them makes it simpler to write code that is easy to understand and reuse. You will learn to protect and hide data with the data encapsulation features of Python, JavaScript, and C#. You will explore how to maximize code reuse by writing code capable of working with objects of different types, and discover the advantage of duck typing in both Python and JavaScript, while you work with interfaces and generics in C#. With a fair understanding of interfaces, multiple inheritance, and composition, you will move on to refactor existing code and to organize your source for easy maintenance and extension. Learning Object-Oriented Programming will help you to make better, stronger, and reusable code.



Flask By Example

Flask By Example Author Gareth Dwyer
ISBN-10 9781785283482
Release 2016-03-31
Pages 276
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Unleash the full potential of the Flask web framework by creating simple yet powerful web applications About This Book The most up-to-date book on Flask on the market Create your own world-class applications and master the art of Flask by unravelling its enigma through this journey This step-by-step tutorial is packed with examples on blending different technologies with Flask to get you up and running Who This Book Is For Have you looked at PHP and hated the clunky bloated syntax? Or looked at .Net and wished it was more open and flexible? Maybe you've tried your hand at GUI libraries in Python and found them hard to use? If your answer to any one of these questions is a yes, then this is just the book for you. It is also intended for people who know the basics of Python and want to learn how to use it to build powerful solutions with a web front-end. What You Will Learn Build three web applications from the ground up using the powerful Python micro framework, Flask. Dynamically display data to your viewers, based on their requests Store user and static data in SQL and NoSQL databases and use this data to power your web applications Create a good user experience by combining HTML, CSS, and JavaScript Harness the convenience of freely available APIs, including OpenWeatherMap, Open Exchange Rates, and bitly Extend your applications to build advanced functionality, such as a user account control system using Flask-Login Learn about web application security and defend against common attacks, such as SQL injection and XSS In Detail This book will take you on a journey from learning about web development using Flask to building fully functional web applications. In the first major project, we develop a dynamic Headlines application that displays the latest news headlines along with up-to-date currency and weather information. In project two, we build a Crime Map application that is backed by a MySQL database, allowing users to submit information on and the location of crimes in order to plot danger zones and other crime trends within an area. In the final project, we combine Flask with more modern technologies, such as Twitter's Bootstrap and the NoSQL database MongoDB, to create a Waiter Caller application that allows restaurant patrons to easily call a waiter to their table. This pragmatic tutorial will keep you engaged as you learn the crux of Flask by working on challenging real-world applications. Style and approach This book will provide you with rich, practical experience of Flask. Every technology, that is employed along with Flask is comprehensively introduced, while the book focusses on developing web applications. Pointers to educational material are always given if you want to gain in-depth knowledge of the various technologies used.



Storytelling with Data

Storytelling with Data Author Cole Nussbaumer Knaflic
ISBN-10 9781119002260
Release 2015-10-09
Pages 288
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Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!