Book Image

Python Data Visualization Cookbook (Second Edition)

Book Image

Python Data Visualization Cookbook (Second Edition)

Overview of this book

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.
Table of Contents (16 chapters)
Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Defining plot line styles, properties, and format strings


This recipe shows how we can change various line properties such as styles, colors, or width. Having lines set up appropriately according to the information presented and distinct enough for target audiences (if the audience is a younger population, we may want to target them with more vivid colors; if they are older, we may want to use more contrasting colors) can make the difference between being barely noticeable and leaving a great impact on the viewer.

Getting ready

Although we stressed how important it is to aesthetically tune your presentation, we first must learn how to do it.

If you don't have a particular eye for color matching, there are free and commercial online tools that can generate color sets for you. One of the most well known is Colorbrewer2, which can be found at http://colorbrewer2.org/.

Some serious research has been conducted on the usage of color in data visualizations, but explaining that theory is out of the...