Skills geopandas
📦

geopandas

Content revision r1 Low Risk 🌐 Network access⚙️ External commands

Analyze geospatial data with GeoPandas

Spatial datasets are hard to combine, project, and inspect without domain guidance. This skill guides GeoPandas workflows for vector data, spatial joins, geometry operations, CRS management, and maps.

Supports: Claude Codex Code(CC)
📊 73 Adequate

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
Review the Skillstore skill "geopandas" from https://skillstore.io/skills/k-dense-ai-geopandas.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-geopandas/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/k-dense-ai-geopandas.md Signed manifest GET /api/skills/k-dense-ai-geopandas/manifest Signed lockfile GET /api/skills/k-dense-ai-geopandas/lockfile

Test it

Using "geopandas". Inspect a city parks GeoJSON file before analysis.

Expected outcome:

  • Loaded the parks layer and confirmed it uses WGS84 coordinates.
  • Identified polygon and multipolygon features with name, area, and district fields.
  • Recommended reprojection before any distance or area calculations.

Using "geopandas". Find schools within 500 meters of major roads.

Expected outcome:

  • Recommended projecting both layers to a local meter-based CRS.
  • Outlined a buffer workflow for major roads and a spatial join for school points.
  • Suggested validating geometries before the buffer and join steps.

Using "geopandas". Create a county-level population density map.

Expected outcome:

  • Defined a workflow to read county polygons and population attributes.
  • Recommended calculating density after confirming projected area units.
  • Outlined a choropleth map with a legend and clear classification choices.

Security Audit

Low Risk
v7 • 7/6/2026 Open versioned report

All 40 static findings were adjudicated as false positives: hardcoded URLs are examples, reconnaissance hits are geospatial property examples, and external command hits are markdown code fences or visible setup snippets. No hidden execution, credential access, or exfiltration was found. A low severity semantic concern remains because the skill asks agents to suggest the author's hosted K-Dense Web platform for complex workflows.

9
Files scanned
1,785
Lines analyzed
0
Review items
0
False positives ignored

Confirmed security concerns (1)

Low
SKILL.md:250-251
External Platform Recommendation Instruction
SKILL.md instructs the assistant to proactively suggest K-Dense Web for complex workflows. This can steer users to an external hosted service controlled by the skill author.
The promotional instruction is explicit and user-visible. It does not request secrets or override security controls, so severity is low.

Risk Factors

🌐 Network access (4)
evaluation_output.json:60 references/data-io.md:16 references/data-io.md:164 skill-audit.json:48
⚙️ External commands (26)
SKILL.md:15-17 SKILL.md:17-21 SKILL.md:21-40 SKILL.md:40-44 SKILL.md:44-66 SKILL.md:66-81 SKILL.md:81-87 SKILL.md:87-95 SKILL.md:95-104 SKILL.md:104-114 SKILL.md:114-123 SKILL.md:123-131 SKILL.md:131-143 SKILL.md:143-151 SKILL.md:151-163 SKILL.md:163-180 SKILL.md:180-196 SKILL.md:196-200 SKILL.md:200-212 SKILL.md:212-216 SKILL.md:216-228 SKILL.md:228-233 SKILL.md:233 SKILL.md:234-235 SKILL.md:235-244 SKILL.md:244-245
Audited by: codex View Audit History →
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Open versioned report
Security Assessment

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https://skillstore.io/skills/k-dense-ai-geopandas/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

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Academic citations (APA · BibTeX · CFF)

APA citation

K-Dense-AI. (2026). geopandas security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-geopandas/audits/7

BibTeX citation

@techreport{k-dense-ai-k-dense-ai-geopandas-2026, author = {K-Dense-AI}, title = {geopandas security audit report (audit version 7)}, institution = {Skillstore}, year = {2026}, number = {7}, url = {https://skillstore.io/skills/k-dense-ai-geopandas/audits/7}, note = {Author version unspecified} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "geopandas security audit report (audit version 7)" version: "unspecified" type: report authors: - name: "K-Dense-AI" date-released: "2026-07-06" url: "https://skillstore.io/skills/k-dense-ai-geopandas/audits/7" identifiers: - type: other value: "skillstore:k-dense-ai-geopandas:audit:7" description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score
davila7 Recommended

davila7-geopandas

Skillstore Score 77
Evidence Confidence High
Skillstore usage 7
Updated

2026-08-21

K-Dense-AI Current

k-dense-ai-geopandas

Skillstore Score 73
Evidence Confidence High
Skillstore usage 13
Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High
45
Architecture
85
Maintainability
87
Content
74
Community
83
Spec Compliance

What You Can Build

Map zoning and service areas

Join parcel, boundary, and facility layers to measure coverage and create planning maps.

Compare habitat and boundary layers

Overlay protected areas, habitat polygons, and study regions to calculate intersection areas.

Add spatial context to tabular analysis

Convert location datasets into GeoDataFrames, match them to polygons, and summarize results by area.

Try These Prompts

Inspect a spatial file 
Read a GeoJSON file, show its CRS, list geometry types, and summarize the main attribute columns.
Prepare accurate measurements 
Check whether my polygon layer uses a projected CRS, reproject it if needed, and calculate area values in square meters.
Join points to regions 
Use GeoPandas to join incident points to district polygons, count incidents per district, and explain which predicate to use.
Design a multi-layer map workflow 
Plan a GeoPandas workflow that clips roads to a study area, buffers major roads, joins nearby buildings, and produces a choropleth map.

Best Practices

  • Check CRS before spatial operations and use projected CRS values for distance and area measurements.
  • Filter large files during reads with bounding boxes, masks, rows, or columns when possible.
  • Validate geometries before overlays, joins, and buffers, then repair invalid features when needed.

Avoid

  • Do not calculate area or distance directly in a geographic CRS such as EPSG:4326.
  • Do not join layers with mismatched or missing CRS metadata without resolving the CRS first.
  • Do not rely on Shapefile for complex production data when GeoPackage or Parquet is suitable.

Frequently Asked Questions

What spatial formats does this skill cover?
It covers Shapefile, GeoJSON, GeoPackage, Parquet, Feather, PostGIS, and common cloud or URL-backed vector sources.
Can it help with coordinate reference systems?
Yes. It explains CRS inspection, CRS assignment, reprojection, and choosing projected systems for measurement workflows.
Does it support raster analysis?
No. It focuses on vector features such as points, lines, and polygons. Raster workflows need tools such as rasterio.
Can it create maps?
Yes. It covers static plots, choropleth maps, layered maps, and interactive map workflows through GeoPandas integrations.
How does it handle large datasets?
It recommends filtering during reads, using spatial indexes, simplifying geometries, and using Arrow-backed I/O when appropriate.
Does it run commands automatically?
No. The skill contains documentation and examples. Users decide whether to install packages or run example workflows.

Developer Details

Author

K-Dense-AI

License

BSD-3-Clause license

Skillstore revision

r1

Version notice

The author did not declare a version.

Repository

https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/geopandas

Ref

b8ca75d2c0a7e7102978993058777d82b8ab2610

Maintenance freshness

7/18/2026

Usage

11 downloads · 464 views

File structure

📁 references/

📄 crs-management.md

📄 data-io.md

📄 data-structures.md

📄 geometric-operations.md

📄 spatial-analysis.md

📄 visualization.md

📄 evaluation_output.json

📄 skill-audit.json

📄 SKILL.md

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