skills.rest
bettercallfan
bettercallfanCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

mine_trajectory_patterns

Mine frequent travel patterns and commuting sequences from staypoint data.

Updated Jun 2, 2026
Search Tags:#trajectory analysis#spatiotemporal#geohash#travel patterns#commuting sequences
One-click install
npx skills add https://github.com/bettercallfan/deerflow --skill mine-trajectory-patterns
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mine_trajectory_patterns
Source: https://github.com/bettercallfan/deerflow/tree/main/skills/custom/spatiotemporal_trajectory/mine_trajectory_patterns
Command: npx skills add https://github.com/bettercallfan/deerflow --skill mine-trajectory-patterns

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps users identify frequent travel patterns, recurring commuting sequences, repeated geohash chains, or multi-stop trip patterns from staypoints.

Core Features & Use Cases

  • Frequent Pattern Mining: Extracts repeated grid sequences from staypoint data.
  • Commuting Sequence Analysis: Identifies recurring commuting sequences and patterns.
  • Use Case: For a city planner, this Skill can be used to understand common commuting routes and patterns in the city.

Quick Start

Run the mine_trajectory_patterns skill with the input file 'staypoints.jsonl' and output directory '/path/to/output'.

Frequently Asked Questions about mine_trajectory_patterns

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

FAQPage Schema
How do I identify recurring commuting sequences from staypoint data?▼

To identify recurring commuting sequences from staypoint data, you run sequence mining scripts that extract repeated geohash chains and multi-stop trip patterns. This outputs frequent travel patterns applicable for urban planning and traffic analysis.

What are frequent travel patterns and how are they extracted from spatiotemporal data?▼

Frequent travel patterns are repeated grid sequences extracted from spatiotemporal staypoints. They are identified by applying Python scripts for sequence mining and pattern extraction to reveal common mobility behaviors and multi-stop trips.

How do I start mining trajectory patterns from a staypoints file?▼

To start mining trajectory patterns, run the skill with your input file named 'staypoints.jsonl' and specify an output directory path. The Python scripts will process the spatiotemporal data and extract the frequent travel sequences.

Can I use this trajectory analysis approach for urban planning and mobility studies?▼

Yes, you can use this trajectory analysis for urban planning and mobility studies. It identifies recurring commuting sequences and frequent travel patterns from staypoints, providing actionable insights into city-wide movement behaviors.

Do I need specific Python libraries to extract geohash chains from staypoints?▼

You need Python scripts provided by the skill to extract geohash chains from staypoints. The skill has no external dependencies, running its internal sequence mining logic directly to process your spatiotemporal data.

Related Skills

Explore More Data & Analytics Skills→
bettercallfanbettercallfan

search_similar_trajectory

Search JSONL trajectory records by coordinates, distance, and duration.

Community
Intermediate
bettercallfanbettercallfan

analyze_spatiotemporal_accessibility

Computes empirical isochrones and reachable areas from OD matrix and starting geohash.

Community
Intermediate
bettercallfanbettercallfan

map_spatial_grid

Maps latitude/longitude trajectory data to Geohash grids for aggregation using Python's Geohash encoding.

Community
Intermediate
bettercallfanbettercallfan

detect_trajectory_cooccurrence

Detect trajectory co-occurrence by comparing staypoints within spatial and temporal boundaries.

Community
Advanced