Chapter 4. Interactive Plotting and Graphical Interfaces
In the previous chapter, we created a few plots with matplotlib and seaborn. In this chapter, we'll look at these libraries in more detail. We'll also discuss some of the many other visualization libraries in Python, with a particular emphasis on those that integrate with the Jupyter Notebook.
We will cover the following topics:
- Choosing a plotting backend
- matplotlib and seaborn essentials
- Image processing
- Further plotting and visualization libraries
Choosing a plotting backend
There are different ways to display a plot in the Jupyter Notebook.
Inline plots
So far, we have created plots within the Notebook using the matplotlib inline mode. This is activated with the %matplotlib inline magic command ...
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