geospatial-ds
CommunityGeospatial DS best practices in Python.
Authorb0glarka
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Geospatial data science projects often suffer from inconsistent workflows, fragmented tooling, and unclear best practices. This Skill provides a standardized, frontmatter-driven template and guidance to unify projects around Python geospatial libraries and proven patterns.
Core Features & Use Cases
- CRS and projections discipline: ensure correct coordinate reference systems and consistent reprojecting.
- Data formats and tooling guidance: recommend modern formats like GeoParquet, GeoPackage, GeoJSON, and basemap tools with GeoPandas, rasterio, rioxarray, OSMnx, h3, contextily, and PySAL.
- End-to-end workflow guidance: templates and patterns for vector + raster workflows, OSM data sourcing, geocoding, and spatial statistics.
Quick Start
Adopting these guidelines requires creating a SKILL.md with proper YAML frontmatter and applying CRS-first geospatial workflows to your Python projects.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: geospatial-ds Download link: https://github.com/b0glarka/la-wildfire-vulnerability-index/archive/main.zip#geospatial-ds Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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