How To: Create an H3 Heatmap from Point Data ​

This tutorial provides step-by-step instructions to create an H3 heatmap from point data using Honeycomb Data Explorer. Watch the video or follow the step-by-step instructions below.

Prerequisites ​

• Access to Honeycomb Data Explorer
• A dataset with latitude and longitude columns
• Permission granted for Honeycomb to access your data table through the Snowflake UI

Step-by-Step Guide ​

1. Prepare Your Data ​

1. Ensure your data table contains:
   • Latitude column
   • Longitude column
   • Note: An H3 column is not required as Honeycomb can generate it automatically

2. Add Data to Your Map ​

1. Click on the table alias in Honeycomb
2. Honeycomb will automatically:
   • Detect latitude and longitude columns
   • Create points on the map
   • Generate an H3 column for your data

3. Create the H3 Heatmap Layer ​

1. Click "Edit Map" to open the sidebar
2. Navigate to "Map Layers"
3. Click "Add Map Layer"
4. Honeycomb will automatically:
   • Select your data source
   • Create a honeycomb layer
   • Use the auto-generated H3 field

4. Configure the Heatmap ​

1. Set the aggregation:
   • Choose a field to aggregate (e.g., ID)
   • Select "Count" as the aggregation method
2. Customize the appearance:
   • Choose a color scheme (e.g., purple)
   • Hide the point layer if desired
3. Select the interpolation type:
   • Value (Linear Scale):
     • Shows contrast between high and low-density areas
     • Darker colors for high-density areas
   • Quantile:
     • Divides values into equal buckets
     • Shows more color variation across the map
4. Adjust additional settings:
   • Set the number of color steps (default: 9)
   • Give your layer a name

Tips ​

• You don't need to pre-compute H3 columns in Snowflake; Honeycomb generates them automatically
• The Value interpolation type is best for showing absolute differences
• The Quantile interpolation type is better for showing relative distributions
• Experiment with different color schemes and steps to find the best visualization for your data

Next Steps ​

After creating your H3 heatmap, you can:

• Adjust the color scheme and interpolation settings
• Combine with other layers for more detailed visualization
• Add additional components to your dashboard

You have now successfully created an H3 heatmap from point data in Honeycomb Data Explorer. This visualization helps identify patterns and density distributions in your geographical data.