Python Data Visualization Cookbook - Second Edition
Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualization
By: Igor Milovanovic, Dimitry Foures, Giuseppe Vettigli
Publication Date: 2015-11-30
Number of pages: 302
Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualizationAbout This BookLearn how to set up an optimal Python environment for data visualizationUnderstand how to import, clean and organize your dataDetermine different approaches to data visualization and how to choose the most appropriate for your needsWho 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 LearnIntroduce yourself to the essential tooling to set up your working environmentExplore your data using the capabilities of standard Python Data Library and Panda LibraryDraw your first chart and customize itUse the most popular data visualization Python librariesMake 3D visualizations mainly using mplot3dCreate charts with images and mapsUnderstand the most appropriate charts to describe your dataKnow the matplotlib hidden gemsUse plot.ly to share your visualization onlineIn 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.