Here’s a short practice exercise to help you get familiar with D3.js:
- Create an HTML file and include D3.js via a CDN.
- Add a container element to the HTML file, such as a
<div>or an SVG element. - Create an array of data, such as
[10, 20, 30, 40, 50]. - Use D3.js to bind the data to the container element, using the
.data()method. - Use the
.enter()method to create a set of elements based on the data. For example, you could create a set of<rect>elements to represent each data point. - Use the
.attr()method to set attributes on the elements based on the data. For example, you could set the height of each<rect>element to be equal to the corresponding data point. - Customize the visual appearance of the elements using the many functions and methods provided by D3.js. For example, you could set the fill color of each
<rect>element based on the data point.
Here’s some example code to get you started:
phpCopy code<!DOCTYPE html>
<html>
<head>
<script src="https://d3js.org/d3.v6.min.js"></script>
</head>
<body>
<svg id="container"></svg>
<script>
const data = [10, 20, 30, 40, 50];
const svg = d3.select('#container');
svg.selectAll('rect')
.data(data)
.enter()
.append('rect')
.attr('x', (d, i) => i * 50)
.attr('y', 0)
.attr('width', 40)
.attr('height', d => d)
.attr('fill', d => `rgb(${d * 2}, ${d * 2}, ${d * 2})`);
</script>
</body>
</html>
This code creates a set of five <rect> elements, one for each data point. The height of each element is equal to the data point, and the fill color is based on the data point as well. You can customize this code to create many different types of visualizations, from bar charts to line graphs to complex geographic maps.