Matplotlib 2.x By Example: Multi-dimensional charts, graphs, and plots in Python

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Figure Aesthetics

Now that you have entered the world of Matplotlib, surely you will want more than plain boring figures that look all the same. This chapter talks about the aesthetics of a figure. We introduce the structure and components of a Matplotlib figure and how to style these details. In this chapter, you will learn how to make a figure stylish, professional, and genuinely yours.

Here are the topics covered in this chapter:

Basic structure and terminologies of a Matplotlib figure
Setting colors in Matplotlib
Adjusting text formats
Lines and markers
- Customizing line styles
- Customizing marker styles
Grids, ticks, and axes
- Adding and adjusting grid lines
- Adjusting tick spacing
- Customizing tick formatters
- Adding axes labeling
- Nonlinear axes
Title and legends
Style sheet support

Key benefits

Create and customize live graphs, by adding style, color, font to make appealing graphs.

A complete guide with insightful use cases and examples to perform data visualizations with Matplotlib's extensive toolkits.

Create timestamp data visualizations on 2D and 3D graphs in form of plots, histogram, bar charts, scatterplots and more.

Description

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.

What you will learn

• Familiarize with the latest features in Matplotlib 2.x

• Create data visualizations on 2D and 3D charts in the form of bar charts, bubble charts, heat maps, histograms, scatter plots, stacked area charts, swarm plots and many more.

• Make clear and appealing figures for scientific publications.

• Create interactive charts and animation.

• Extend the functionalities of Matplotlib with third-party packages, such as Basemap, GeoPandas, Mplot3d, Pandas, Scikit-learn, and Seaborn.

• Design intuitive infographics for effective storytelling.

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