Скачать или смотреть How to Use Metadata from a Second DataFrame in Plotly Heatmap Hovertemplates

Learn how to effectively use information from a second DataFrame in the hovertemplate of a Plotly heatmap. Discover tips and best practices for visualizing additional data seamlessly.
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This video is based on the question https://stackoverflow.com/q/68811436/ asked by the user 'Liam McIntyre' ( https://stackoverflow.com/u/2186650/ ) and on the answer https://stackoverflow.com/a/68814964/ provided by the user 'Liam McIntyre' ( https://stackoverflow.com/u/2186650/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Unleashing the Power of Plotly Heatmaps: Integrating Metadata in Hovertemplates

Heatmaps are incredible visualization tools that allow you to represent data in an easily digestible format. However, sometimes you might have additional information that could enhance your heatmap experience—like using metadata from a second DataFrame in the hover tooltip. If you've been trying to figure out how to seamlessly integrate this data, you’ve come to the right place!

The Challenge

You have two DataFrames:

The first DataFrame (df1) contains the values used to generate the heatmap.

The second DataFrame (df2) holds metadata that you want to display when hovering over different areas of the heatmap.

You want a solution that allows you to display values from df2 based on the position you're hovering over on the heatmap.

Initial Approach: What Wasn't Working?

You may have experimented with some code that looked something like this:

[[See Video to Reveal this Text or Code Snippet]]

However, you noticed the placeholders (%{x}, %{y}) were problematic because they weren't returning the actual values you expected during the hover event. You needed a method that properly linked the hover actions to the correct metadata.

The Solution

Thanks to insights from the community, there's a straightforward approach that utilizes Plotly’s graph_objects library to achieve the desired functionality. Here’s how you can do it:

Step-by-Step Guide

Import Required Libraries

Begin by importing the necessary libraries:

[[See Video to Reveal this Text or Code Snippet]]

Create Your DataFrames

Generate your two DataFrames with representative data:

[[See Video to Reveal this Text or Code Snippet]]

Construct the Heatmap

Use the go.Figure method to create the heatmap, and importantly, assign your metadata DataFrame to the customdata parameter:

[[See Video to Reveal this Text or Code Snippet]]

This allows you to reference all values from df2 directly in the hovertemplate.

Display the Figure

Finally, show the figure:

[[See Video to Reveal this Text or Code Snippet]]

Additional Insights

Customdata Handling: The customdata property enables you to link additional data for use in the hover template, which alleviates the hassle of passing data through functions.

Dynamic Hovertemplate: By leveraging values in the hovertemplate properly, you can format the output to display both the score and corresponding metadata smoothly.

Conclusion

Integrating metadata from a second DataFrame into a Plotly heatmap hovertemplate is now a task that can be done efficiently with just a few steps using the graph_objects library. This technique not only enriches your visualizations but also enhances informative insights for users interacting with your data.

Start exploring these techniques in your own projects, and elevate your heatmaps into powerful storytelling tools that convey rich context and narrative!