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 Panel. While we know about 167 links to D3.js, we've tracked only 10 mentions of Panel. 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 / 3 months ago
Document address: D3.js Official Document. - Source: dev.to / 5 months ago
D3.js: One of the most popular JavaScript visualization libraries. - Source: dev.to / 8 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 / 8 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 / 10 months ago
Manganite allows easy conversion of Jupyter notebooks into dashboards. Simply annotate existing notebooks with Jupyter magics and serve them as interactive web apps. Manganite has been created to empower master and doctoral students in econ and management to turn research notebooks into interactive dashboards. The students use Python for data analysis, math programming, and basic machine learning. Instead of... - Source: Hacker News / over 1 year ago
Https://panel.holoviz.org/ It's a web app framework for Python similar to what Dash does for plotly. It plays nicely with bokeh visuals and I think the front-end is built using bokeh css elements. Source: about 2 years ago
If you want to build Python dashboards, look at the solara (react-style lib, https://solara.dev/) and panel (https://panel.holoviz.org/). Source: about 2 years ago
My suggestion is https://panel.holoviz.org/ Fully open sourced, makes it easy to make reactive apps with small changes, can even configured as a graphical REPL. - Source: Hacker News / about 2 years ago
I am doing something like this in a [panel](https://panel.holoviz.org/) dashboard, which I am currently converting to nicegui. Maybe I can provide an example in some days. Source: about 2 years ago
Chart.js - Easy, object oriented client side graphs for designers and developers.
Streamlit - Turn python scripts into beautiful ML tools
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application
Dash by Plotly - Dash is a Python framework for building analytical web applications. No JavaScript required.
Plotly - Low-Code Data Apps
Turtle - New kind of anonymous messaging app