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D3 is a low-level JavaScript visualisation library: you’ll write more code, but it has an ‘ expressivity advantage ’. Can you put a D3 JavaScript visualisation into a Python Jupyter notebook? Yes!

Subtitled "Data visualization with JavaScript", this guide to the D3 JavaScript library that shows how the API can be used for data visualization over HTML, CSS, and SVG has been completely updated.

The Vega Project is happy to announce the release of version 5.3.0 of the Vega-Altair Python visualization library. This release has been 4 months in the making and includes enhancements, fixes, and ...

One of the things I enjoyed most about D3.js is the level of control it offers. Unlike Plotly.js, D3.js allowed me to manipulate every aspect of the visualization. From the placement of axes and ...

Book Abstract: Create stunning web-based data visualizations with D3.js. This totally-revised new edition of D3.js in Action guides you from simple charts to powerful interactive graphics.

D3.js in Action, Second Edition is completely revised and updated for D3 v4 and ES6. It's a practical tutorial for creating interactive graphics and data-driven applications using D3.