Data visualization with plotly py: Version 3 and beyond
summary
Plotly.py version 3 adds two-way widget sync so figures become live FigureWidget objects with an imperative property-assignment API, real-time hover and selection callbacks, and improved validation and autocompletion. It ships a packaged Electron image exporter called Orca electron image exporter to create publication-quality SVG/PDF and raster outputs. New traces (barpolar, histogram2dcontour, 3D cone/streamtube, parallel categories), theming, LaTeX mathjax in notebook, and binary transfer that handles ~1e6 points are demonstrated working end-to-end.
AI-written summary · about
chapters (14)
- 0:00Introduction
- 2:03Plotly.js background
- 5:34Version 3 key features
- 6:59Scatter plot demo
- 11:13Notebook views demo
- 15:13Overplotting and contours demo
- 17:21Sliders demo
- 18:27Hover tooltips demo
- 21:58Selection callbacks demo
- 24:06Updates and features since version 3 release
- 28:24Theming support demo
- 30:41Static image export demo
- 31:51LaTeX in labels demo
- 33:16Summary
related talks
41mInteractive Visualization in Jupyter with Bqplot and Interactive Widgets
31mbqplot Interactive Data Visualization in Jupyter
29mInteractive visualization for the curious
01h 55mInteractive Data Visualizations with Python
01h 38mEffective Data Visualization
43mAdvanced Data Visualizations In Jupyter Notebooks
01h 26mEasily build interactive plots and apps with hvPlot
02h 14mData Applications with Bokeh
