JavaScript (or "JS") is a high-level, interpreted programming language mainly used as a type of HTML for the World Wide Web, which is very dynamic in providing interactivity on websites. Variables are containers for storing values in them while the functions have the functionality with reusable blocks of code.

Together with HTML and CSS, JavaScript is one of the three core web technologies which is an essential part of the web applications to enable the interactivity in vast majority of websites and the web browsers generally have a dedicated JavaScript engine to execute it. JS has a number of top libraries and frameworks for web-based applications with data.

D3.js and C3.js

D3.js, or Data Driven Documents, is an open source, data visualization library of JavaScript that can manipulate data-based HTML documents by mapping the data to the documents. However, it functions much more than just visualization of data.

As one of the JavaScript libraries, D3.js enables to dynamically display data in graphical forms. With D3.js, data are visualized using HTML, CSS and SVG, which provides essential control over the web-based data visualization, powerfully (D3.js in Action, 2017).

C3.js is a D3-based reusable chart library since it is a simple wrapper around the D3.js. C3 is fast and compatible across browsers and facilitates deeper integration of charts into web applications.


NVD3.js creates re-usable charts for d3.js, which is a JavaScript visualization library and derived from the popular d3.js visualization library. NVD3.js can be very powerful for daily tasks as well as for business operations. One example is to make an online dashboard with this library, we can use NVD3.js to compile data into a centralized spot through visualization of relevant information using simple and neat graphics.


With the rise and the active development of the new platform Node.js, JavaScript code is able to run on the server side instead of relying only on a browser.

Machine learning (ML)

Javascript has become more and more popular, not only because it is widely used in web development, but also because of the need for increasing number of machine learning algorithms. Especially, it is relatively very convenient to develop machine learning tools in the web browser, which facilitates web users to gain access to the machine learning technologies, not to mention that browser-based machine learning provides effective visualization of many ML algorithms as well as the datasets.

jQuery-based data visualization

Quite often, many impactful insights can be achieved from graphical data visualization that enables people to harness the data easily by communicating the information clearly and efficiently. In addition to the D3.js library as mentioned above, a number of other jQuery charting tools, can facilitate the making of interactive data visualization and providing the adequate details in a big picture:

  • HighCharts: HighCharts enables creating interactive, intuitive and visually appealing graphics on websites as well as web applications. It supports many chart types such as area, line, bar, pie, scatter, areaspline, arearange, columnrange, angular gauges and polar charts etc. It can generate dynamic charts with real-time data which can be exported with different file formats including JPG, PDF, PNG and SVG. HighCharts is compatible with all modern web browsers, devices and platforms.
  • FusionCharts: With FusionCharts, charts can be created from XML data, HTML table and JSON data. FusionCharts is also compatible across different browsers including mobile browsers. It supports interactive zooming, scrolling functionality and real-time data updates. Charts are exportable in JPEG, PDF and PNG formats.
  • Flot: The Flot library creates easy-to-use interactive charts and graphs from a given dataset. It enables the user to turn on or off any particular values, axes and series and supports many options such as zooming, panning, axes changes and stacked charts, which is compatible with all browsers.
  • Chart.JS: Chart.js is a powerful open-source library with many features that facilitates drawing 8 different types of charts (such as lines, bars, pies etc.) using HTML5 “canvas” element. The charts are responsive across all browsers and devices.
  • Easy-Pie-Chart: This is a simple and efficient jQuery plugin for creating optimized pie charts by means of HTML5 “canvas” element. Easy-pie-chart is compatible with all browsers that support HTML5.

In addition, there are many other charting tools and libraries for data visualization such as Cytoscape.js, CanvasJS, Morris.js and jqPlot etc.

JavaScript Applications

Data visualization using D3.js - high yielding cultivars from crop variety trial