Mastering Python Data Visualization

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 prod