Скачать или смотреть Extracting GPS Boundaries and Values from Plotly Hexbin Heatmaps in Python

Learn how to efficiently download hexbin heatmap data, including GPS coordinates, average values, and centroids into a pandas DataFrame using Python and Plotly.
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Getting GPS Boundaries for Each Hexbin in a Plotly Heat Map

Creating visualizations with geographic data can be incredibly insightful, especially when using Python libraries like Plotly. One common challenge when generating hexbin heatmaps is the need to extract specific data points from the visualization, such as GPS coordinates and average values for each hexbin. In this post, we will walk through a step-by-step solution to help users obtain crucial data from their hexbin heatmaps, including the centroid GPS coordinates and the latitude/longitude of each corner of the hexbin.

Problem Overview

You’ve created a hexbin heatmap in Plotly that successfully displays numerous locations mapped through GPS latitude and longitude, complete with corresponding values. While you can see the average values by hovering over each hexbin, you want to download the following information into a pandas DataFrame for further analysis:

Average value in each hexbin (already calculated, but not readily accessible for download)

Centroid GPS coordinates for each hexbin

GPS coordinates for each corner of the hexbin (specifically, the latitude and longitude of the six corners)

Solution Steps

Here’s how to retrieve this information from your Plotly hexbin heatmap:

Step 1: Import Required Libraries

Make sure to start by importing the necessary libraries. You’ll need pandas for data manipulation, numpy for numerical operations, and geopandas to handle geographic data. Additionally, you will be working with shapely to create geometric representations of the corners.

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Step 2: Create Your Hexbin Map

You can use the existing code you have to create the hexbin map. Here's a snippet showcasing how to do this with your sample DataFrame:

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Step 3: Extract Hexbin Data

With your hexbin map generated, you can extract the coordinates of hexbin corners and their average values directly from the figure data structure.

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Step 4: Creating the Data DataFrame

Now you will create a DataFrame to consolidate the hexbin information.

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Step 5: Generate Centroids and Corner Data

You can now obtain centroids from the geometry data and create a separate DataFrame for the corner coordinates.

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Step 6: Final DataFrame Structure

Your resulting DataFrame will contain:

Coordinates for each hexbin

Average value for each hexbin

Centroid and corner GPS coordinates

The created data structure might look like this:

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

Conclusion

Using the above steps, you can efficiently extract crucial geospatial data from your hexbin heat map created with Plotly. You’ll have ready access to average values, centroid coordinates, and the GPS points for each corner—all captured neatly in a pandas DataFrame for further analysis or export.

Feel free to modify the approach to fit your specific use case or data requirements.