Data visualization
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Visual Exploration of Mathematics and Statistics
- A Visual Exploration of Gaussian Processes
- A Neural Network Playground
- Workshop on Visualization for AI Explainability
Visual Exploration of Computer Science
Data journalism
Plotting libraries
- Python
- lets-plot (ggplot2)
- plotly (interactive)
- matplotlib (classic)
- ggplot2 in R
- plotters in Rust
- D3.js
- 3D
- Bevy in Rust for simulation
- three.js
Papers
- Banking to 45 degree
- An Empirical Model of Slope Ratio Comparisons
- Principles of Beautiful Figures for Research Papers
Websites
- UW Interactive Data Lab — Visualization + Analysis
- Vis & Society 2024 MIT
- Dataviz Inspiration
- from Data to Viz
- 1 dataset 100 visualizations
Books
- Fundamentals of Data Visualization
- Interactive Data Visualization by Scott Murray
- D3 is great for explanatory visuals, not exploratory. If I am finished studying a refined hypothesis and want to show a specific result I’d use D3. Or if I want something highly customized because I know exactly how the data will look, D3 is great. But most of what I do is exploratory. I’m not exactly sure what the data will look like.
Tools
- Manim — A community maintained Python library for creating mathematical animations.
- How I animate 3Blue1Brown | A Manim demo with Ben Sparks
- How to learn D3.js
- Better Data Visualizations with Svelte