What Type of Data Is a Pie Chart Used For?


Heather Bennett

A pie chart is a popular type of data visualization that is used to represent data in a circular format. It is an effective way to display categorical data and show the proportionate distribution of each category. In this article, we will explore what type of data is best suited for a pie chart and how to create one using HTML.

When to Use a Pie Chart

Pie charts are most commonly used when you want to represent data that can be divided into categories or parts. They are particularly useful when you want to emphasize the relationship of each category to the whole or compare the proportions between different categories.

1. Proportional Data

A pie chart works best when you have proportional data, meaning that the values of each category represent a percentage or fraction of the whole. For example, if you want to visualize the market share of different companies in a specific industry, a pie chart would be an appropriate choice.

2. Limited Number of Categories

Pie charts are most effective when there are only a few categories to display. If you have too many categories, the chart can become cluttered and difficult to interpret. It’s generally recommended to limit the number of categories to 5-7 for optimal readability.

3. Non-Time Series Data

Pie charts are not suitable for displaying time series data, where values change over time. For such cases, line graphs or bar charts are more appropriate as they can effectively show trends and changes over time.

Creating a Pie Chart in HTML

To create a pie chart using HTML, you can utilize various libraries such as Chart.js or D3.js which provide powerful tools for data visualization. Using Chart.js

Chart.js is a popular JavaScript library that allows you to create beautiful charts and graphs. To create a pie chart using Chart.js, you need to include the library in your HTML file and define a canvas element:

<canvas id="myChart" width="400" height="400"></canvas>

Then, you can use JavaScript to initialize the chart and provide the data:

var ctx = document.getElementById('myChart').getContext('2d');
var myChart = new Chart(ctx, {
    type: 'pie',
    data: {
        labels: ['Category 1', 'Category 2', 'Category 3'],
        datasets: [{
            label: '# of Votes',
            data: [30, 40, 20],
            backgroundColor: [
                'rgba(255, 99, 132, 0.8)',
                'rgba(54, 162, 235, 0.8)',
                'rgba(255, 206, 86, 0.8)'
            borderColor: [
                'rgba(54, 162, 235,1)',
                'rgba(255, 206, 86)'
            borderWidth: 1
    options: {}

2. Using D3.js

D3.js is a powerful JavaScript library for manipulating documents based on data. It provides extensive capabilities for creating interactive and dynamic visualizations. To create a pie chart using D3.js:

<div id="chart"></div>
<script src="https://d3js.org/d3.v6.min.js"></script>
    var data = [
        { category: 'Category 1', value: 30 },
        { category: 'Category 2', value: 40 },
        { category: 'Category 3', value: 20 }

    var width = 400;
    var height = 400;
    var radius = Math.min(width, height) / 2;

    var color = d3.scaleOrdinal()
        .range(['#ff6384', '#36a2eb', '#ffce56']);

    var svg = d3.select('#chart')
        .attr('width', width)
        .attr('height', height)
        .attr('transform', 'translate(' + width / 2 + ',' + height / 2 + ')');

    var arc = d3.arc()

    var pie = d3.pie()
        .value(function (d) { return d.value; });

    var path = svg.selectAll('path')
        .attr('d', arc)
        .attr('fill', function (d) { return color(d.data.category); });


These are just a few examples of how you can create pie charts using HTML and JavaScript. There are many other libraries and frameworks available that offer different features and customization options.


Pie charts are an effective way to represent data when you want to show the proportionate distribution of different categories. They work best with proportional data, a limited number of categories, and non-time series data. By incorporating HTML styling elements such as bold, underlined text,


, and subheaders using


tags, you can make your content visually engaging and organized.

Remember to carefully choose the appropriate type of chart for your data to ensure clear communication and effective visualization.

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