Data Visualization with Python and JavaScript: Scrape, Clean, Explore & Transform Your Data

Book Description

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

Table of Contents

Chapter 1 Development Setup
Chapter 2 A Language-Learning Bridge Between Python and JavaScript
Chapter 3 Reading and Writing Data with Python
Chapter 4 Webdev 101
Chapter 5 Getting Data off the Web with Python
Chapter 6 Development Setup
Chapter 7 A Language-Learning Bridge Between Python and JavaScript
Chapter 8 Reading and Writing Data with Python
Chapter 9 Webdev 101
Chapter 10 Getting Data off the Web with Python
Chapter 11 Heavyweight Scraping with Scrapy
Chapter 12 Introduction to NumPy
Chapter 13 Introduction to Pandas
Chapter 14 Cleaning Data with Pandas
Chapter 15 Visualizing Data with Matplotlib
Chapter 16 Exploring Data with Pandas
Chapter 17 Delivering the Data
Chapter 18 RESTful Data with Flask
Chapter 19 Imagining a Nobel Visualization
Chapter 20 Building a Visualization
Chapter 21 Introducing D3—The Story of a Bar Chart
Chapter 22 Visualizing Individual Prizes
Chapter 23 Mapping with D3
Chapter 24 Visualizing Individual Winners
Chapter 25 The Menu Bar
Chapter 26 Conclusion

中文：

书名：使用Python和JavaScript实现数据可视化：擦除、清理、探索和转换数据

了解如何将原始数据转化为丰富的、交互式的Web可视化，并将其与Python和JavaScript的强大组合相结合。在这篇实践指南中，作者Kyran Dale教您如何使用同类最好的Python和JavaScript库–包括Scrapy、Matplotlib、Pandas、Flask和D3–构建一个基本的Dataaviz工具链，用于制作引人入胜的、基于浏览器的可视化效果。

作为一个有效的例子，在整本书中，戴尔向你介绍了将维基百科基于表格的诺贝尔奖获得者名单转换成交互式可视化的过程。您将研究整个工具链上的步骤，从收集、清理、探索和交付数据到使用JAVASCRIPT的D3库构建可视化。如果您已经准备好创建您自己的基于Web的数据可视化–并且了解Python或JavaScript–这本书是为您准备的。

• 了解如何使用Python操作数据
• 了解Python和JavaScript之间的共同点
• 使用Python的Web抓取工具BeautifulSoup和Scrapy从网站中提取信息
• 使用Python的Pandas、Matplotlib和Numpy库清理和浏览数据
• 使用Python的FlASK框架提供数据并创建REST风格的Web API
• 使用JAVASCRIPT的D3库创建引人入胜的交互式Web可视化

Table of Contents

Chapter 1 Development Setup
第2章：Python和JavaScript之间的语言学习桥梁
第3章使用Python读取和写入数据
Chapter 4 Webdev 101
第5章使用Python从Web上获取数据
Chapter 6 Development Setup
第7章：Python和JavaScript之间的语言学习桥梁
第8章使用Python读取和写入数据
Chapter 9 Webdev 101
第10章使用Python从Web上获取数据
第11章重量级擦伤
Chapter 12 Introduction to NumPy
Chapter 13 Introduction to Pandas
Chapter 14 Cleaning Data with Pandas
Chapter 15 Visualizing Data with Matplotlib
第16章使用熊猫探索数据
Chapter 17 Delivering the Data
Chapter 18 RESTful Data with Flask
第十九章想象诺贝尔奖的可视化
Chapter 20 Building a Visualization
Chapter 21 Introducing D3—The Story of a Bar Chart
第二十二章个人奖品可视化
Chapter 23 Mapping with D3
第二十四章可视化个人获胜者
Chapter 25 The Menu Bar
Chapter 26 Conclusion