geopandas-projections

geopandas-projections is a skill for Claude Code, Codex from cxcscmu/SkillLearnBench. It costs 21 tokens per session (736 once invoked), scanned A, original, MIT.

A guide to using GeoPandas, a Python library for working with geographic data, with coordinate systems that make measurements accurate.

In plain words
What is it for?
It is for creating geographic data tables, changing between coordinate systems, calculating distances, and performing spatial operations.
Why use it?
It prevents distance and spatial calculations from being wrong when map coordinates are treated as degrees instead of real-world units.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for creating geographic data tables, changing between coordinate systems, calculating distances, and performing spatial operations.

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Install with agentmods
npx agentmods add skills/cxcscmu/skilllearnbench/geopandas-projections
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add cxcscmu/SkillLearnBench --skill geopandas-projections
Clone the repo
git clone --depth 1 https://github.com/cxcscmu/SkillLearnBench

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for geopandas-projections

README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/geopandas-projections"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/geopandas-projections.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 736 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00021 $0.00736
Opus 5 $0.00010 $0.00368
Sonnet 5 $0.00004 $0.00147
Haiku 4.5 $0.00002 $0.00074

Measured 9d ago against content hash e72274e474e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

geopandas-projections scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/b1-one-shot-claude-haiku-4-5/earthquake-plate-calculation/geopandas-projections/SKILL.md · 87 lines

How it starts

The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GeoPandas Spatial Projections

Overview

GeoPandas is built on top of Shapely and Fiona, enabling geographic data manipulation with proper coordinate reference systems (CRS). Using correct projections is critical for accurate distance calculations and spatial operations.

Installation

pip install geopandas shapely fiona pyproj

Key Concepts

Coordinate Reference Systems (CRS)

  • EPSG:4326: WGS84 (lat/lon), commonly used for geographic data but NOT suitable for distance calculations
  • EPSG:3857: Web Mercator, used for web mapping
  • Regional Projected CRS: For accurate local distance calculations (e.g., UTM zones)

Distance Calculations

Always project to a projected CRS before calculating distances. Geographic CRS (like EPSG:4326) measure in degrees, not kilometers.

Code Examples

Creating GeoDataFrames from Points

import geopandas as gpd
from shapely.geometry import Point
import pandas as pd

# From earthquake data
earthquakes_df = pd.read_json('/root/earthquakes_2024.json')
geometry = [Point(xy) for xy in zip(earthquakes_df['longitude'], earthquakes_df['latitude'])]
gdf = gpd.GeoDataFrame(earthquakes_df, geometry=geometry, crs='EPSG:4326')

Loading GeoJSON with Boundaries

import json

# Load GeoJSON and convert to GeoDataFrame
with open('/root/PB2002_boundaries.json', 'r') as f:
    geojson_data = json.load(f)
boundaries_gdf = gpd.GeoDataFrame.from_features(geojson_data['features'], crs='EPSG:4326')

Projecting to Projected CRS

# Project to a suitable CRS for distance calculations
# Example: project to Mercator for global analysis
gdf_projected = gdf.to_crs('EPSG:3857')
boundaries_projected = boundaries_gdf.to_crs('EPSG:3857')

# Or use a specific UTM zone for a region
# EPSG:32633 is UTM zone 33N

Spatial Filtering (Point in Polygon)

# Check if points fall within polygons
earthquakes_in_plate = gpd.sjoin(gdf, plate_polygons, how='inner', predicate='within')

Read the full file on GitHub · 87 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 87 lines · 21 tokens per session scan A e72274e474e1

Subscribe to this mod's changes

geopandas-projections is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 2mo ago), licensed MIT. It adds 21 tokens to every session and 736 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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