python talk on data visualization - focused on matplotlib and bokeh libraries
Bokeh overview Basic Interactions Linked Charts & Tables + Saving Data Elegent intuition - Fourier Transform Visualizations (extend Bokeh maintainer example) Live Streaming Data - Audio Spectrogram (extend Bokeh maintainer example)
Understand why effective visualizations are important
Introduction to the grammar of graphics and how to choose the right visual approach
Get a snapshot of the python visualization universe
Explore Foundation - learn about matplotlib, understand core use cases & pitfalls + ways to make it better, do some live coding
Look at the Future - Learn about the bokeh library, learn about interactive visualizations, even more live coding
charles minard - march to moscow (charles minard)[https://en.wikipedia.org/wiki/Charles_Joseph_Minard#The_map_of_Napoleon%27s_Russian_campaign]
challenger disaster - Roberts Report (presentation obscured lack of data)[https://www.vice.com/en_us/article/kbb3qz/could-better-data-design-have-prevented-challenger] (13 charts failed to stop the launch - analysis of engineering discussions)[https://spacegrant.carthage.edu/live/files/2505-tap16workshop-4-tuftepdf] (primary chart - by launch date)[https://history.nasa.gov/rogersrep/v5p896.htm] (Report from Presidential Commission Hearings)[https://history.nasa.gov/rogersrep/v4p645.htm] (main report)[https://history.nasa.gov/rogersrep/v4part6.htm#645]
Matplotlib - use to explore Challenger Disaster Visualization
Matplotlib - explain and demo different APIs
Matplotlib - illustrate simple ways to improve... & Matplotlib - you need to know it, and how to solve
Bokeh - syntax, basic cases
Bokeh - interactivity - hover, zoom, pan, linking
Bokeh - key concepts; some ideas
Bokeh - animation / streaming data