geopandas-projections SKILL.md skillA
geopandas-projections from cxcscmu/skilllearnbench is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add cxcscmu/skilllearnbench/geopandas-projections@git:20260424.d50cf5aPins git:20260424.d50cf5a in mdr.lock. Pin the fingerprint instead.
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- Kind
- SKILL.md skill
- Repository
- cxcscmu/skilllearnbench
- Path
skills/b1-one-shot-claude-opus-4-6/earthquake-plate-calculation/geopandas-projections/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260424.d50cf5a, committed Apr 24, 2026
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- 91
- License
- MIT
Using GeoPandas coordinate projections for accurate distance calculations on geospatial data.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# GeoPandas Projections for Distance Calculations
## Overview
When calculating distances between geographic features, you must project from geographic coordinates (lat/lon, EPSG:4326) to a projected CRS that preserves distances. Using `.distance()` on unprojected data gives degrees, not meters/km.
## Key Projections
### World Azimuthal Equidistant (ESRI:54032)
- Preserves distances from center point
- Good for measuring distances from a single point to boundaries
- Usage: `gdf.to_crs("ESRI:54032")`
### Equal Area Cylindrical (EPSG:6933)
- Preserves area, approximate distances
- Usage: `gdf.to_crs("EPSG:6933")`
### Custom Azimuthal Equidistant
- Best accuracy when measuring from a known center point
- `proj_str = f"+proj=aeqd +lat_0={lat} +lon_0={lon} +datum=WGS84 +units=m"`
## Distance Calculation Pattern
```python
import geopandas as gpd
from shapely.ops import nearest_points
# Load data in WGS84
gdf = gpd.read_file("data.geojson") # EPSG:4326
# Project to meters-based CRS
gdf_proj = gdf.to_crs("ESRI:54032")
# Calculate distance (returns meters)
dist = gdf_proj.geometry.distance(some_geometry_proj)
# Convert to km
dist_km = dist / 1000
```
…Read the whole file at its exact version.
How to install
mdr add cxcscmu/skilllearnbench/geopandas-projections@sha256:10e662cee5de3003The line at the top of this page pins the label git:20260424.d50cf5a, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_75jjamq56oamcmzs)
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Versions
The registry has recorded 1 version of this file, committed on Apr 24, 2026.
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Source
cxcscmu/skilllearnbench · 91 stars · license MIT · pushed 2026-10-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_75jjamq56oamcmzs GET https://markdownregistry.com/api/v1/resolve?ref=cxcscmu/skilllearnbench/geopandas-projections GET https://markdownregistry.com/api/v1/blob/10e662cee5de300378df97d7a90dde35fd341c1d73ae426aab5701da0262b1ab
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Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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