Learn to Create D3.js Data Visualizations by Example

D3.js: Draw dynamic data visualization with JavaScript

This article discusses D3.js, a powerful JavaScript library for creating dynamic and interactive data visualizations. It uses HTML, SVG and CSS to render data in web browsers.

Core points:

• D3.js is a versatile JavaScript library that allows developers to create dynamic, interactive data visualizations in web browsers using HTML, SVG and CSS.
• The library provides a wealth of tools for data processing, converting raw data into meaningful visual representations, and can be widely customized to suit unique creative ideas.
• D3.js uses scale bars to map data values ​​to visual display properties such as size or color, creating charts and other visual elements that accurately reflect the data.
• This article provides practical examples of bar charts, line charts, and animation visualizations, demonstrating how to render simple and complex data graphs using D3.js.
• D3.js supports advanced features such as transitions and animations, allowing developers to create visually engaging, dynamically updated visualizations that enhance user experience and data interaction.

D3.js is a data-based document operation JavaScript library. It helps you bring your data to life using HTML, SVG and CSS. The three JavaScript libraries that every web developer should learn are: jQuery, Underscore, and D3. These libraries allow you to think about code in new ways: jQuery allows you to do more about DOM with less code; Underscore (or lodash) provides functional tools to change the way you write programs; and D3 A rich set of tools is provided for data processing and graphical programming. If you are new to D3, take a moment to browse its impressive library of examples to see what it can do. This is not a chart library from your father's time. William Playfair invented the bar chart, line chart and area chart in 1786, and invented the pie chart in 1801. These are still the main ways most datasets are presented today. These charts are excellent, but D3 gives you the tools and flexibility to create unique web data visualizations, and your creativity is the only limiting factor. D3 is an extremely flexible low-level visualization library with a jQuery-like API for mapping data to HTML and SVG documents. It contains a large number of useful mathematical functions for data transformation and physical calculations, although most of its functions come from manipulating geometric figures and paths in SVG. This article aims to provide you with a high-level overview of the D3 features, in each example you will be able to see input data, convert and output documents. I wouldn't explain what each function does, but instead show you the code, you should be able to get a rough idea of ​​how it works. I only go into the most important concepts: Scale and Select .

Bar Chart

Creating simple bar charts using HTML is one of the easiest ways to understand how D3 converts data into documents. The code is as follows:

d3.select('#chart')
  .selectAll("div")
  .data([4, 8, 15, 16, 23, 42])
  .enter()
  .append("div")
  .style("height", (d)=> d + "px")

This code maps the input data [4, 8, 15, 16, 23, 42] to the output HTML.

GitHub contribution chart

With just a few extra lines of code, the above bar chart can be converted into a contribution chart similar to GitHub.

We no longer set the height according to the data's numerical value, but set the background color.

Beginner of SVG

Most of D3's functionality comes from the fact that it works with SVG, which contains labels for drawing 2D graphics such as circles, polygons, paths, and text.

Circular

D3 can handle more complex data types.

Line Chart

Drawing a line chart in SVG is very simple.

Scale

Scale is a function that maps the input domain to the output range.

Animation Flight Visualization

This is an example of an animation visualization showing flights between Melbourne and Sydney.

Conclusion

This article only covers a small part of the D3.js library. Hopefully this advanced overview and some practical examples will give you an idea of ​​how to use selections, scales, and transformations. Think about the best way to represent data and enjoy creating your own unique data visualization.

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