Book Image

Mastering Matplotlib 2.x

By : Benjamin Walter Keller
Book Image

Mastering Matplotlib 2.x

By: Benjamin Walter Keller

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
Table of Contents (7 chapters)

Adding geography

This section describes how to add coastline and water features along with adding political boundaries.

How to add coastline and water features

We will begin by drawing coastlines using the following code:

# Just coastlines
m = Basemap(projection='ortho',lon_0=-114, lat_0=51)
m.drawcoastlines()
plt.show()

In the previous sections, we have seen that basemap can generate a sort of background image of coastlines of the globe, but we haven't seen how this is done. It is done simply by using the coastlines method in the preceding snippet. Using this gives us the coastlines, as shown in the following output:

In our preceding output, we see that the coastlines are fairly coarse. We can change how coarse...