AnyChart VS d3

We'll delve into this process using a JavaScript charting library. As a support engineer at AnyChart, and with our JS library recently named best in data visualization, it was a natural choice to use our tool for this tutorial. What about the example data? Other tutorials! There's a treasure trove of JS charting tutorials on our blog, and it occurred to me that compiling these tutorials into a calendar chart would serve as a unique, engaging, and practical example for this guide.

Now that the basic HTML structure is in place, it's time to incorporate the JavaScript files necessary for creating our OHLC chart. We can add these to our project in two ways: by downloading and using them locally, or by linking to them through a Content Delivery Network (CDN). For this tutorial, let’s opt for the CDN approach, including links to the essential scripts in the section of our HTML page. We'll use AnyChart JS Charts, and to create an OHLC chart, it’s necessary to include the Core and Stock modules, as well as the Data Adapter one, which will make it easy to load data from a file.

Once the container is set up, include the necessary JavaScript files in the section. This tutorial shows how you can use a JS charting library like AnyChart.

Building a JavaScript pie graph from scratch can be a daunting task, but we're in luck! There are plenty of JS charting libraries that provide pre-built functions and features, making data visualization development seamless. For this tutorial, I’ve chosen the AnyChart JS library, suitable for beginners and experts alike, but feel free to use your favorite one as the logic of the process will be the same.

After setting up a basic HTML page, the next step is to include the necessary JavaScript files in the section. There are numerous charting libraries available. In this tutorial, we'll be using AnyChart. This library supports bubble charts and offers comprehensive documentation. But no matter which library you choose, the basic steps for creating a chart are similar.

There are not many JavaScript charting libraries out there that support sunburst charts out of the box. One of those is AnyChart, which has thorough documentation for its vast data visualization capabilities and a gallery full of ready-to-use chart examples, so I’ve chosen it for the sunburst chart development showcase in this tutorial.

There are a ton of various JS charting libraries out there. For this project, we're gonna go with the AnyChart JS library, which supports heatmap charts and is free for personal and other non-profit purposes.

To easily create data visualizations for the web, I use a JavaScript charting library with in-built utilities and functions. With the vast number of such JS libraries available, the process for creating charts and maps is similar in essence and logic across most of them. In this tutorial, I am using the AnyChart JS charting library as it is beginner-friendly with extensive documentation and plenty of examples to help you get started.

Using JavaScript charting libraries is an absolute game-changer when it comes to creating stunning interactive visualizations. Luckily, you don't need to be a technical wizard to use them. For this tutorial, we'll be working with AnyChart, which has detailed documentation (e.g., candlestick here and stock candlestick here), and does not require a fee for non-commercial use.

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