framework VS d3

Thanks for the feedback. We have a PR open to make it easier to register new interpreters (without needing to fallback to .sh or .exe); it’ll let you specify the interpreter associated with a given file extension (e.g., .kts for Kotlin). https://github.com/observablehq/framework/pull/935

As for inputs-driving-data-loaders, that does go against the grain a bit since Framework favors static data snapshots so that the built site is self-contained and performant. But a technique that works well is to generate Parquet files in data loaders representing the superset of data that you want to interact with, and then using DuckDB/SQL in the client to extract the subset you want to visualize. This tends to perform well, though obviously it’s dependent on the size of the superset you want to interact with.

From the Observable Framework point of view, you’re very welcome to use Apache ECharts or any other library instead of Observable Plot, since you can import whatever you like and it’s all just JavaScript.

Since there was a lot of interest in this thread, Mike added a page to the docs with an ECharts example: https://observablehq.com/framework/lib/echarts

There are two pieces of that example code specific to Framework: the html`` tagged template literal creates a DOM element (see https://github.com/observablehq/htl, also usable outside Framework), and the display function inserts it into the document above the code block (see https://observablehq.com/framework/javascript/display). Note that, whereas Observable Plot takes an options object and returns a DOM element, ECharts instead takes a DOM element and mutates it — but in general they should be equally easy to use in Framework.

Like Plot (and Vega-Lite, another great option), ECharts is also now one of Framework’s built-in “recommended libraries” (see https://observablehq.com/framework/javascript/imports#implic...), meaning that if you reference `echarts` Framework will lazy-load it for you. Adding that was a two-line diff: https://github.com/observablehq/framework/pull/811/files#dif.... But I wanna emphasize that Framework doesn’t have to explicitly “support” a given library for you to use it. “Supporting” in this case just means the convenience of saving you a one-line import statement. But don’t wait for our blessing!! Use whatever.

Yes this was done with a combination of GSAP Scrolltrigger https://gsap.com/docs/v3/Plugins/ScrollTrigger/ and https://d3js.org/

d3 - very power visualization library enabling dynamic visualizations. docs

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 say we’re trying to target data app developers more than data analysts; we offer a lot of power and expressiveness, and emphasize custom visualizations and interaction (leaning on Observable Plot or D3), as well as polyglot programming with data loaders written in any language (Python, R, not just SQL).

D3.js: A robust library to visualize your data and create interactive data-driven visualizations.

They are images so it could be any number of things, datawrapper, charts.js, d3.js to name a few options.

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 Tools Population and birthrate data for 2023 was obtained from Wikipedia (Population and birth rates). Population distribution across the globe was obtained from Socioeconomic Data and Applications Center (sedac) at Columbia University. Data is processed and visualized at a 1 degree x 1 degree resolution, each of which has a different probability of a birth occurring in a specific time period. D3.js was used to create the map elements and html, css and javascript were used to create the user interface.

When I go to the homepage of types/d3 the only hint for any kind of documentation is what seems to be the main github page of d3. It's highly possible I'm missing something here, so sorry if I am but I can't find any documentation of how you are supposed to type these library objects.

Website: D3.js official site

D3js