January 2018
Beginner to intermediate
548 pages
12h 11m
English
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Chapter 6. Data Visualization
In this chapter, we will cover the following topics:
- Using Matplotlib styles
- Creating statistical plots easily with seaborn
- Creating interactive web visualizations with Bokeh and HoloViews
- Visualizing a NetworkX graph in the Notebook with D3.js
- Discovering interactive visualization libraries in the Notebook
- Creating plots with Altair and the Vega-Lite specification
Introduction
While Matplotlib is the main visualization library in Python, it is not the only one. In this chapter, we will introduce some of the many other visualization libraries that cover more domain-specific use cases, or that offer specific interactivity features in the Jupyter Notebook.
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.