Tutorials

Heat map examples using Highcharts

by

Highsoft

5 minutes read

A heat map is a data visualization technique that shows the magnitude of a phenomenon as color in two dimensions. The variation in color can make it easier to understand complex data sets, highlighting patterns and outliers. Heat maps are particularly useful in fields such as meteorology, finance, and epidemiology, where they help in analyzing geographical data and trends.

Highcharts makes creating interactive and responsive heat maps easy. This blog post will explore various examples of heat maps using Highcharts, demonstrating their versatility and practical applications.

To see more examples and get an even better understanding of the opportunities Highcharts offers, please head over to the demo section of our website or read up on the technical documentation on how to get started. Once you get the hang of it, the API reference will help you customize your charts in no time.

Whether you’re a developer working with JavaScript, .NET, React or other common frameworks, we’re confident you’ll find the inspiration you need.

Highcharts also integrates seamlessly with popular languages such as Python, R, PHP and Java, as well as mobile platforms like iOS and Android. Additional support for frameworks like Svelte, Angular, and Vue, makes it a versatile tool for various development environments.

Calendar heat map

This demo of a calendar heat map visualizes daily temperature variations in Oslo for July 2023. The chart displays each day of the month in a grid format, with color intensity representing temperature values. The weekdays are on the x-axis, while the y-axis denotes the weeks. Data points are color-coded from light blue (cooler temperatures) to orange (warmer temperatures), with interactive tooltips showing exact temperatures for each day.

Go to the demo page for the “Calendar heat map” heat map to view its code or edit it on JSFiddle or Codepen.

Geo heatmap of Europe

This example of a geo heat map of Europe visualizes the density of train stations near airports. This interactive map uses a color axis to represent the concentration of stations, ranging from light to dark blue. The map is overlaid with a grid of data points showing specific values at different geographical coordinates. Tooltips provide detailed information on the number of train stations at each location, and the map is designed to handle large datasets efficiently.

Go to the demo page for the “Geo heatmap of Europe” heat map to view its code or edit it on JSFiddle or Codepen.

Sales per employee per weekday

This example showcases a visualization of sales data per employee across weekdays. The chart uses a grid to display employees on the x-axis and weekdays on the y-axis. Color intensity represents the number of items sold, with darker colors indicating higher sales. The map includes interactive tooltips, providing specific sales data for each cell, and is responsive to different screen sizes.

Go to the demo page for the “Sales per employee per weekday” heat map to view its code or edit it on JSFiddle or Codepen.

Heat map with interpolation

This example showcases a heat map with interpolation, visualizing user activity on a website. The map uses a background image and different color stops to represent varying levels of user interactions across regions. The interpolation feature smooths the transitions between data points, creating a visually appealing gradient effect. The chart is fully responsive, adapting to different screen sizes, and includes tooltips for detailed information on interactions in specific areas.

Go to the demo page for the “Heatmap with interpolation” heat map to view its code or edit it on JSFiddle or Codepen.

Geo heatmap, orthographic

The geo heat map with an orthographic projection showcases city density across the globe. It uses an orthographic projection to create a 3D-like view of the Earth. Color intensity indicates the density of cities, with darker colors representing higher density. The map is interactive, allowing users to zoom and pan, and includes tooltips for detailed information on city density in specific regions.

Go to the demo page for the “GeoHeatMap Series Demo” heat map to view its code or edit it on JSFiddle or Codepen.

Large heat map

This demo of a large heat map visualizes temperature variations by day and hour for the year 2023. This heat map uses the Highcharts Boost module to handle large datasets efficiently. The x-axis represents dates throughout the year, while the y-axis shows hours of the day. Color intensity indicates temperature, ranging from blue (colder) to red (warmer). Tooltips provide detailed temperature information for specific times and dates. This example demonstrates Highcharts’ capability to manage and render extensive data smoothly.

Go to the demo page for the “Large heat map” heat map to view its code or edit it on JSFiddle or Codepen.

Conclusion and additional resources

Heat maps are a powerful tool for visualizing complex data sets, highlighting patterns, and identifying trends. Highcharts makes it easy to create interactive and responsive heat maps for various applications, from temperature variations to user activity on websites. The examples demonstrated, including calendar heat maps, geo heat maps, and large dataset visualizations, show the versatility and efficiency of Highcharts. To explore these demos further and experiment with the code, visit the Highcharts demo section and documentation for more detailed information and customization options.