"Hand Coded Artisanal Data-Visualization"
summary
Claims that hand-coded SVG replaces heavy libraries, demonstrates no d3 required workflows, and shows concrete wins: a full-screen HD SVG is 14K versus a GIF at 1.7MB. Shows actual tools and techniques: SVG elements, <animate>, filters, patterns, namespaces, inline JS, and DOM methods; builds a React chart component, gauge, polygon visualizer and map colorizer from raw path data; numbers include a 60-slide demo and a 20-hour learning target, and the examples work.
AI-written summary · about
chapters (9)
- 0:00Introduction
- 3:12Hand-coding SVGs for data
- 8:30Core SVG elements
- 13:51SVG filters and effects
- 16:47Interacting with SVGs
- 20:29Building interactive visualizations
- 22:53Theory to practice
- 26:25Data visualization design
- 28:10Summary
related talks
47mSVGs beyond mere shapes
29mSVGs beyond mere shapes
39mSVG Charts and Graphics with Ruby
43mThe Future of Data Visualization on the Web
12mBattle-Tested Techniques for Animation & Data Viz
24mBeyond the bar graph: Creative visualization with D3.js
47mData, Design, Code
39mBuilding Better Interfaces With SVG
