vis-timeline VS Numeral-js

Useful resources: documentation, samples

I've decided to use vis.js as it seems to be a minimal library but still pulls in 800 mbs of dependencies. I've not done web development before and I can't understand why such small use case requires so so many other libraries. It doesn't even look easy on the eye. It looks like something from the 2010s.

Refactored VisJS stacking algorithm to work in O(n log n) down from O(n2 log n)

This looks like a decent choice

vis-timeline

You can use a third-party library, which is a bunch of code that someone else wrote for you. Many awesome third-party libraries can format numbers with commas in JavaScript. For example, you can try Numeral.js, Accounting.js, or Format.js.

JavaScript provides built-in methods like toFixed() for number formatting, as well as libraries like numeral.js, which provides advanced formatting options. These methods and libraries can be used to format numbers in a variety of ways, including currency, percentages, and time. It's important to note that the way numbers are formatted can vary depending on the locale and currency, so it's important to be mindful of these considerations when formatting numbers in JavaScript.

The `a` at the end handles automatically shortening it. See the last example in [the docs for numeraljs](http://numeraljs.com/) under the "Format > Currency" section.

Long answer: The format part of tprintf roughly follows sprintf-js and the numbers are formatted using ns.nFormat which uses the syntax from numeraljs.com.

Numeral

However, there are always great libraries that the community develops to support missing features, such as dinero.js, currency.js, and numeral.js.

It's worth mentioning that to communicate your data better to your user, it's always a good idea to mix and match different types of data visualizations. Moreover, you can also have a date formatting library (such as Moment.js) or number formatting library (such as numeral.js) that could accompany your graphs and highlight any special or outstanding number in your dataset.