Book Description
Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualization
About This Book
- Learn how to set up an optimal Python environment for data visualization
- Understand how to import, clean and organize your data
- Determine different approaches to data visualization and how to choose the most appropriate for your needs
Who This Book Is For
If you already know about Python programming and want to understand data, data formats, data visualization, and how to use Python to visualize data then this book is for you.
What You Will Learn
- Introduce yourself to the essential tooling to set up your working environment
- Explore your data using the capabilities of standard Python Data Library and Panda Library
- Draw your first chart and customize it
- Use the most popular data visualization Python libraries
- Make 3D visualizations mainly using mplot3d
- Create charts with images and maps
- Understand the most appropriate charts to describe your data
- Know the matplotlib hidden gems
- Use plot.ly to share your visualization online
In Detail
Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts.
Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.
Style and approach
A step-by-step recipe based approach to data visualization. The topics are explained sequentially as cookbook recipes consisting of a code snippet and the resulting visualization.
Table of Contents
Chapter 1: Preparing Your Working Environment
Chapter 2: Knowing Your Data
Chapter 3: Drawing Your First Plots and Customizing Them
Chapter 4: More Plots and Customizations
Chapter 5: Making 3D Visualizations
Chapter 6: Plotting Charts with Images and Maps
Chapter 7: Using the Right Plots to Understand Data
Chapter 8: More on matplotlib Gems
Chapter 9: Visualizations in the Clouds with Plot.ly
中文：
书名：Python Data Visualization Cookbook, 2nd Edition
基于数据可视化的主要概念，您可以通过70多个食谱开始使用流行的Python库
About This Book
- 了解如何设置用于数据可视化的最佳Python环境
- 了解如何导入、清理和组织数据
- 确定数据可视化的不同方法以及如何选择最适合您需求的方法
这本书是为谁写的
如果您已经了解了Python编程，并且想要了解数据、数据格式、数据可视化以及如何使用Python可视化数据，那么这本书是为您准备的。
你将学到什么
- 向自己介绍设置工作环境所需的基本工具
- 使用标准Python数据库和熊猫库的功能浏览您的数据
- 绘制您的第一张图表并对其进行定制
- 使用最流行的数据可视化Python库
- 主要使用mplot3d进行3D可视化
- 使用图像和地图创建图表
- 了解最适合描述您的数据的图表
- 知道matplotlib隐藏的宝石
- 使用plot.ly在线共享您的可视化效果
In Detail
《Python数据可视化指南》将帮助读者从安装和设置用于数据操作和可视化的Python环境开始，一直到使用Python库制作3D动画。读者将受益于60多个精确和可重复的食谱，这些食谱将引导读者更好地理解数据概念，并为后续的、有时是更高级的概念奠定基础。
《Python Data Visualization Cookbook》首先介绍如何设置matplotlib和本书大部分内容所需的相关库，然后讨论一些较少使用的图表和图表，如甘特图或Sankey图表。最初，它使用简单的情节和图表，而不是更高级的图表，以便于读者理解。当读者通读这本书时，他们将了解3D图表和动画。地图在显示地理空间数据方面是不可替代的，因此本书还将介绍如何构建地图。在最后一章中，它解释了如何将matplotlib整合到不同的环境中，如书写系统、LaTeX或如何使用Python创建甘特图。
风格和方法
一种基于逐步配方的数据可视化方法。这些主题将按食谱顺序进行解释，这些食谱由代码片段和生成的可视化结果组成。
Table of Contents
第1章：准备您的工作环境
第2章：了解您的数据
第3章：绘制您的第一个情节并对其进行定制
Chapter 4: More Plots and Customizations
第5章：制作3D可视化效果
第6章：使用图像和地图绘制图表
第7章：使用正确的曲线图来理解数据
第8章：有关matplotlib宝石的更多信息
Chapter 9: Visualizations in the Clouds with Plot.ly
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