D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.




Gribouille is described as 'Create elegant graphics with the Grammar of Graphics for Typst' and is an app. There are eight alternatives to Gribouille for a variety of platforms, including Web-based, Self-Hosted, Mac, Windows and Linux apps. The best Gribouille alternative is D3.js, which is both free and Open Source. Other great apps like Gribouille are NVD3, Vega-Lite, Bokeh and C3.js.
D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.




This project is an attempt to build re-usable charts and chart components for d3.js without taking away the power that d3.js gives you. This is a very young collection of components, with the goal of keeping these components very customizeable, staying away from your standard...
Vega-Lite provides a higher-level grammar for visual analysis, comparable to ggplot or Tableau, that generates complete Vega specifications. Vega-Lite specifications consist of simple mappings of variables in a data set to visual encoding channels such as x, y, color, and size.

Bokeh is a Python interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of novel graphics in the style of D3.js, but also deliver this capability with high-performance interactivity over very...
D3-based reusable chart library that enables deeper integration of charts into web applications

Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. With Vega, you can describe the visual appearance and interactive behavior of a visualization in a JSON format, and generate web-based views using Canvas or...

Turn boring data into a visual masterpiece using picasso.js, an open-source library from Qlik.




Plotnine is an implementation of a grammar of graphics in Python based on ggplot2. The grammar allows you to compose plots by explicitly mapping variables in a dataframe to the visual characteristics (position, color, size etc.) of objects that make up the plot.



