#### Overview of this book

In this book, you’ll get hands-on with customizing your data plots with the help of Matplotlib. You’ll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You’ll explore non-trivial layouts, Pylab customization, and more about tile configuration. You’ll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you’ll explore them further in this book. You’ll delve into niche plots and visualize ordinal and tabular data. In this book, you’ll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will also be explored. Finally, you’ll learn how to create interactive plots with the help of Jupyter. Learn expert techniques for effective data visualization using Matplotlib 3 and Python with our latest offering -- Matplotlib 3.0 Cookbook
Preface
Free Chapter
Heavy Customization
Drawing on Plots
Special Purpose Plots
3D and Geospatial Plots
Interactive Plotting
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# 3D and Geospatial Plots

From the previous chapter, we learned about how to plot on non-Cartesian axes and how to plot high dimensional vector field data. This chapter explains how to add 3D axes and plotting on the 3D axes. The significance of this chapter is the basemap method, where we choose between different kinds of map projections.

In this chapter, we will learn about the following:

• How to set up and manipulate 3D axes
• The different kinds of 3D plots that Matplotlib provides
• How to use the basemap class to generate geospatial plots
• How to apply these plots on map projections
• How to add geography to the plots