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 167 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.
Do you mean something for data visualization, or tricks condensing large data sets with cursors? https://d3js.org/ Best of luck =3. - Source: Hacker News / about 2 months ago
Document address: D3.js Official Document. - Source: dev.to / 4 months ago
D3.js: One of the most popular JavaScript visualization libraries. - Source: dev.to / 7 months ago
A Dependency is an npm package that our code depends on in order to be able to run. Some popular packages that can be added as dependencies are lodash, D3, and chartjs. - Source: dev.to / 7 months ago
RacingBars is an open-source, light-weight (~45kb gzipped), easy-to-use, and feature-rich javascript library for bar chart race, based on D3.js. - Source: dev.to / 9 months ago
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 1 year ago
Java also has http://beakerx.com for Jupyter. It really should be promoted more. Source: almost 4 years ago
Chart.js - Easy, object oriented client side graphs for designers and developers.
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.
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application
iPython - iPython provides a rich toolkit to help you make the most out of using Python interactively.
Plotly - Low-Code Data Apps
nteract - nteract is a desktop application that allows you to develop rich documents that contain prose...