Book Image

Matplotlib 2.x By Example

By : Allen Yu, Claire Chung, Aldrin Yim
Book Image

Matplotlib 2.x By Example

By: Allen Yu, Claire Chung, Aldrin Yim

Overview of this book

Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization. Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts. By the end of this book, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This book will guide you to prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable.
Table of Contents (15 chapters)
Title Page
About the Authors
About the Reviewer
Customer Feedback

Chapter 7. A Practical Guide to Scientific Plotting

Creating scientific figures is where art meets science. Any scientific data visualization should be "of substance, statistics and design" (pg. 51, Tufte, Edward R. The Visual Display of Quantitative Information, Graphics Press: Cheshire, CT, 1983; pp 1‐197). We say a picture is worth a thousand words, but not all graphics are created equal. A well-drawn visual attracts audience and soundly delivers messages. On the contrary, poorly made plots can impede understanding, or even be misleading. We now have a myriad of tools for data plotting; virtually anyone can convert numbers to graphics before grasping the purpose or nature of these graphs. Such convenience makes good planning and careful crafting your actual survival skills in data visualization.

Undoubtedly, accuracy and clarity are the basic criteria to communicate scientific facts. It is more than labeling each axis properly with International System of Units (SI). The level of statistical...