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geospatial-visualization

Convert tabular geospatial data into interactive map visualizations with Plotly.

Updated Aug 27, 2026
Search Tags:#visualization#plotly#geospatial#maps#choropleth#bubble-map#flow-map
One-click install
npx skills add https://github.com/Org-GAgent/result-interpreter --skill geospatial-visualization-org-gagent
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: geospatial-visualization
Source: https://github.com/Org-GAgent/result-interpreter/tree/main/.skills/visualization-skills/geospatial-visualization
Command: npx skills add https://github.com/Org-GAgent/result-interpreter --skill geospatial-visualization-org-gagent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, plotly, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Geospatial data is frequently stored in tables and hard to translate into actionable visual maps.

Core Features & Use Cases

  • Bubble Map: Map point data with bubble sizes representing a metric.
  • Choropleth Map: Visualize regional aggregates by shading areas.
  • Connection Map: Display flows or relations between locations.
  • Flow Map + Circos: Show directional movements with circular summaries.
  • Templates and libraries: Leverages Plotly, GeoPandas, and prepared templates for quick results.

Quick Start

Generate a bubble map from a CSV containing latitude, longitude, and value columns.

Frequently Asked Questions about geospatial-visualization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a choropleth map from regional data in a CSV file?▼

To create a choropleth map, load your regional data from a CSV file using pandas and pass the aggregated values to plotly. This visualizes regional aggregates by shading geographic areas based on your metric.

What is the best way to visualize spatial relationships between multiple locations?▼

The best way to visualize spatial relationships is by creating a connection map. This displays flows or relations between locations, showing directional movements and spatial comparisons across your geographic data.

Can I use plotly to generate a bubble map from latitude and longitude columns?▼

Yes, you can use plotly to generate a bubble map from latitude and longitude columns. Map your point data so that bubble sizes represent a specific metric, turning raw coordinates into insightful geospatial visuals.

Do I need pandas and numpy to render interactive geospatial visualizations?▼

Yes, you need pandas and numpy as foundational dependencies to process and structure your data. These libraries work with plotly to transform raw tabular data into interactive and static map-based outputs.

How do I show directional movements and flows between geographic points?▼

To show directional movements, apply a flow map with Circos summaries. This approach displays directional movements between locations while providing circular summaries to highlight flow volumes.

Why does my geospatial data table fail to show regional trends clearly?▼

Geospatial data tables fail to show regional trends because raw rows obscure spatial patterns. Converting this data into map-based visualizations like choropleth or bubble maps translates tables into actionable insights.

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