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transbigdata-visualize

Generate interactive Kepler and Matplotlib visualizations for transportation spatiotemporal datasets.

4|2|Updated Feb 4, 2026
Search Tags:#visualization#trajectory#matplotlib#gridding#transbigdata#keplergl#od-visualization
One-click install
npx skills add https://github.com/ni1o1/claude-skill-transbigdata --skill transbigdata-visualize
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: transbigdata-visualize
Source: https://github.com/ni1o1/claude-skill-transbigdata/tree/main/skills/transbigdata-visualize
Command: npx skills add https://github.com/ni1o1/claude-skill-transbigdata --skill transbigdata-visualize

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Visualizing large transportation spatiotemporal datasets is time-consuming and requires stitching together aggregation, basemap rendering, and plotting tools. This Skill centralizes common visualization workflows for mobility analysts so maps, heatmaps, OD flows, and trajectory animations can be produced reproducibly and interactively.

Core Features & Use Cases

  • Interactive Kepler maps: create point or heatmap visualizations for aggregated GPS data and explore results in Jupyter.
  • Trajectory and OD visualization: animate individual or fleet trajectories and draw aggregated OD flow maps for taxi or transit analysis.
  • Static Matplotlib basemaps: render high-quality static maps with plot_map, add scale bars and compass, and overlay gridded results.
  • Activity & spatial analysis: compute and plot activity timelines, confidence ellipses, and entropy metrics to summarize movement patterns.
  • Use Case: generate a 500m gridded heatmap of taxi GPS points to identify hotspots and then produce an OD flow map to analyze trip distribution.

Quick Start

Create an interactive 500m gridded heatmap of taxi GPS points in Jupyter using the transbigdata visualization functions.

Frequently Asked Questions about transbigdata-visualize

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

FAQPage Schema
How do I create an interactive heatmap from taxi GPS data?▼

Generate interactive Kepler heatmaps from taxi GPS data by aggregating points into a 500m or 1km gridded structure and rendering the visualized output directly within Jupyter notebooks.

Can I visualize OD flow maps and trajectory animations for urban mobility datasets?▼

Visualize OD flow maps and animate fleet trajectories for urban mobility datasets by aggregating trip distribution data and rendering the movement patterns interactively for transit analysis.

Does this visualization Skill support static Matplotlib basemaps?▼

Render high-quality static Matplotlib basemaps by utilizing the plot_map function to add scale bars, incorporate compass elements, and overlay gridded spatial results for transportation datasets.

What is the best way to compute activity patterns and entropy metrics from transportation spatiotemporal data?▼

Compute activity patterns and entropy metrics from transportation spatiotemporal data by calculating movement summaries, plotting activity timelines, and generating confidence ellipses to analyze urban mobility behavior.

Do I need Jupyter to use Kepler.gl for point-density visualization?▼

Use Kepler.gl for point-density visualization within Jupyter notebooks to explore aggregated GPS data interactively, generating heatmap visualizations and analyzing spatial distribution results directly.

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