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

Adjusting the layout

Figure layout, including the size and location of plots, directs the focus of our readers. A figure with good layout facilitates data presentation in a logical flow. It is thus important to familiarize ourselves with layout settings when plotting. Let's learn how to assign proper sizes, positions, and spacing to our plots.

Adjusting the size of the figure

Depending on where you want to put your figure, you may want to adjust the size and layout. Instead of manually stretching your image output afterward, which takes extra effort and can distort the text. You can set the height and width directly by calling pyplot.figure(figsize=()). As briefly mentioned in Chapter 2, Figure Aesthetics, the figure module contains all the plot elements. The figsize setting controls the overall size in inches and aspect ratio of the figure. This is also useful when we want to show a larger plot directly in a notebook, without having to export it in a high-resolution image.

Here is an example...