معرفی کتاب «Learning Python data visualization : master how to build dynamic HTML5-ready SVG charts using Python and the pygal library» نوشتهٔ Chad Adams، منتشرشده توسط نشر Packt Publishing Limited در سال 2014. این کتاب در 5 صفحه، فرمت pdf، زبان انگلیسی ارائه شده است. «Learning Python data visualization : master how to build dynamic HTML5-ready SVG charts using Python and the pygal library» در دستهٔ بدون دستهبندی قرار دارد.
**Master how to build dynamic HTML5-ready SVG charts using Python and the pygal library** About This Book* A practical guide that helps you break into the world of data visualization with Python * Understand the fundamentals of building charts in Python * Packed with easy-to-understand tutorials for developers who are new to Python or charting in Python Who This Book Is ForIf you are a Python novice or an experienced developer and want to explore data visualization libraries, then this is the book for you. No prior charting or graphics experience is needed. What You Will Learn* Build different types of Python charts and graphs * Master how to build Python graphics libraries * Test and validate your data sources * Explore common Python libraries for charts and graphics * Build charts using dynamic data from offline and online sources * Use CSS to modify embedded SVG images in HTML pages * Install and write Python code on Windows, Mac, or Linux * Discover how to install and reference libraries in Visual Studio or Eclipse In DetailThe best applications use data and present it in a meaningful, easy-to-understand way. Packed with sample code and tutorials, this book will walk you through installing common charts, graphics, and utility libraries for the Python programming language. Firstly you will discover how to install and reference libraries in Visual Studio or Eclipse. We will then go on to build simple graphics and charts that allow you to generate HTML5-ready SVG charts and graphs, along with testing and validating your data sources. We will also cover parsing data from the Web and offline sources, and building a Python charting application using dynamic data. Lastly, we will review other popular tools and frameworks used to create charts and import/export chart data. By the end of this book, you will be able to represent complex sets of data using Python. Cover Copyright Credits About the Author About the Reviewers www.PacktPub.com Table of Contents Preface Chapter 1: Setting Up Your Development Environment Introduction Setting up Python on Windows Installation Exploring the Python installation in Windows Python editors Setting up Python on Mac OS X Setting up Python on Ubuntu Summary Chapter 2: Python Refresher Python basics Importing modules and libraries Input and output Generating an image Creating SVG graphics using svgwrite For Windows users using VSPT For Eclipse or other editors on Windows For Eclipse on Mac and Linux Summary Chapter 3: Getting Started with pygal Why use pygal? Installing pygal using pip Installing pygal using Python Tools for Visual Studio Building a line chart Stacked line charts Simple bar charts Stacked bar charts Horizontal bar charts XY charts Scatter plots DateY charts Summary Chapter 4: Advanced Charts Pie charts Stacked pie charts Radar charts Box plots Dot charts Funnel charts Gauge charts Pyramid charts Worldmap charts Summary Chapter 5 : Tweaking pygal Country charts Parameters Legend at the bottom Legend settings Label settings Chart title settings Displaying no data pygal themes Summary Chapter 6: Importing Dynamic Data Pulling data from the Web The XML refresher RSS and the ATOM Understanding HTTP Using HTTP in Python Parsing XML in Python with HTTP About JSON Parsing JSON in Python with HTTP About JSONP JSONP with Python Summary Chapter 7 : Putting ItAll Together Chart usage for a blog Getting our data in order Converting date strings to dates Using strptime Saving the output as a counted array Counting the array Python modules Building the main method Modifying our RSS to return values Building our chart module Building a portable configuration for our chart Setting up our chart for data Configuring our main function to pass data Project improvements Summary Chapter 8: Further Resources The matplotlib library Installing the matplotlib library matplotlib's library download page Creating simple matplotlib charts Plotly Pyvot Summary Appendix: References and Resources Links for help and support Charting libraries Editors and IDEs for Python Other libraries and Python alternative shells Index
The best applications use data and present it in a meaningful, easy-to-understand way. Packed with sample code and tutorials, this book will walk you through installing common charts, graphics, and utility libraries for the Python programming language.
Firstly you will discover how to install and reference libraries in Visual Studio or Eclipse. We will then go on to build simple graphics and charts that allow you to generate HTML5-ready SVG charts and graphs, along with testing and validating your data sources. We will also cover parsing data from the Web and offline sources, and building a Python charting application using dynamic data. Lastly, we will review other popular tools and frameworks used to create charts and import/export chart data. By the end of this book, you will be able to represent complex sets of data using Python.