November 2018
Beginner to intermediate
214 pages
5h 2m
English
Content preview from Mastering Matplotlib 2.x
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Interactive Plotting
Until now, we have studied how to plot on 3D axes and how to make various different kinds of plots within those 3D axes. We also studied how to use basemap to generate map projections. Interactive plotting defines a discussion on interactivity wherein Matplotlib plots aren't just static images but dynamic updated figures that can change the way they are displayed based on the changes in real time to actual data in order to build apps using Matplotlib. In this chapter, we will learn about the following topics:
- How to use the ipywidgets module with the Jupyter Notebook to make easy, interactive widgets
- How to add callbacks to plots for interactivity
- How to generate GUI neutral widgets for use in different kinds of Matplotlib ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.