D3 allows you to bind arbitrary data to a Document Object Model (DOM), and then apply data-driven transformations to the document. For example, you can use D3 to generate an HTML table from an array of numbers. Or, use the same data to create an interactive SVG bar chart with smooth transitions and interaction.
D3 is not a monolithic framework that seeks to provide every conceivable feature. Instead, D3 solves the crux of the problem: efficient manipulation of documents based on data. This avoids proprietary representation and affords extraordinary flexibility, exposing the full capabilities of web standards such as HTML, SVG, and CSS. With minimal overhead, D3 is extremely fast, supporting large datasets and dynamic behaviors for interaction and animation. D3’s functional style allows code reuse through a diverse collection of official and community-developed modules.
Based on our record, D3.js seems to be a lot more popular than BeakerX. While we know about 159 links to D3.js, we've tracked only 2 mentions of BeakerX. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / about 2 months ago
Java also has http://beakerx.com for Jupyter. It really should be promoted more. Source: almost 3 years ago
Yes this was done with a combination of GSAP Scrolltrigger https://gsap.com/docs/v3/Plugins/ScrollTrigger/ and https://d3js.org/. - Source: Hacker News / 12 days ago
d3 - very power visualization library enabling dynamic visualizations. docs. - Source: dev.to / about 1 month ago
Yep, Evidence is doing good work. We were most directly inspired by VitePress; we spent months rewriting both D3’s docs (https://d3js.org) and Observable Plot’s docs (https://observablehq.com/plot) in VitePress, and absolutely loved the experience. But we wanted a tool focused on data apps, dashboards, reports — observability and business intelligence use cases rather than documentation. Compared to Evidence, I’d... - Source: Hacker News / 2 months ago
They are images so it could be any number of things, datawrapper, charts.js, d3.js to name a few options. Source: 5 months ago
I made this interactive visualization that attempts to show the real-time frequency and location of births around the world. A country’s annual births (i.e. The country’s population times its birthrate) were distributed across all of the populated locations in each country, weighted by the population distribution (i.e. More populated areas got a greater fraction of the births). Data Sources and... Source: 5 months ago
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
Chart.js - Easy, object oriented client side graphs for designers and developers.
iPython - iPython provides a rich toolkit to help you make the most out of using Python interactively.
Plotly - Low-Code Data Apps
Observable Notebooks - The portfolio and technical blog of Chris Henrick – provider of professional web development, data visualization, GIS, mapping, & cartography services.
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application