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name: core-data-model description: "Use when working with GeoPandas GeoSeries and GeoDataFrame objects, geometry columns, CRS metadata, Shapely-backed geometry arrays, and spatial-index basics." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

Core Data Model

Use this sub-skill when the task is about creating, inspecting, repairing, or transforming GeoPandas objects before any file I/O, spatial analysis, map rendering, or testing-specific assertion work.

Read First

• API reference: verified signatures and object rules for GeoSeries, GeoDataFrame, geometry columns, CRS, coordinate access, and spatial index basics.
• Workflows: practical recipes for construction, active geometry repair, CRS assignment/reprojection, missing/empty geometry checks, and pandas interoperability.
• Troubleshooting: symptoms and fixes for missing active geometry, wrong CRS, metric operation misuse, invalid or missing geometries, and pandas conversions.
• validate_geodataframe.py: safe helper that builds or reads a tiny GeoDataFrame and reports geometry column, CRS, bounds, empty/missing geometry, and optional spatial-index status.

Route Here When

• The user asks how to build a GeoDataFrame or GeoSeries from Shapely objects, WKT/WKB, x/y coordinates, features, or tabular data.
• The task mentions geometry, active geometry column, set_geometry, rename_geometry, active_geometry_name, or pandas operations that lost geometry semantics.
• The task involves .crs, set_crs, to_crs, estimate_utm_crs, EPSG codes, or deciding whether coordinates need assignment versus transformation.
• The question is about missing/empty geometries, isna(), is_empty, bounds, coordinate extraction, geometry dtype, or when operations return pandas versus GeoPandas objects.
• The task asks for spatial index basics such as .sindex, has_sindex, valid predicates, or why a spatial operation is slow.

Route Elsewhere

• Use ../io-formats/SKILL.md for read_file, to_file, GeoJSON, WKB/WKT persistence, Arrow/Parquet/Feather, or PostGIS.
• Use ../spatial-operations/SKILL.md for joins, overlays, clips, dissolves, unary/binary geometry analysis, nearest searches, and predicate selection.
• Use ../mapping-geocoding/SKILL.md for .plot(), .explore(), folium, matplotlib, geocoding, or map classification.
• Use ../validation-testing/SKILL.md for geopandas.testing assertions or focused native test commands.

Default Operating Rules

1. Confirm the object type and active geometry column before applying GeoPandas methods.
2. Inspect .crs on all layers. Use set_crs() only to attach known metadata; use to_crs() to reproject coordinates.
3. For distance, area, buffer, nearest, or metric thresholds, prefer a projected CRS with suitable linear units.
4. Treat None/missing geometries separately from empty Shapely geometries.
5. When pandas operations strip GeoPandas metadata, rebuild with GeoDataFrame(df, geometry=..., crs=...) or call set_geometry() deliberately.
6. Use spatial index as an optimization or query surface, not as a replacement for exact Shapely predicates.

Minimal Checks

Run from this sub-skill directory or any other current working directory:

python scripts/validate_geodataframe.py --default-fixture --build-sindex

Expected high-level signal: the report names the active geometry column, CRS, row count, total bounds, missing and empty geometry counts, and whether a spatial index could be built.

Handoff to Other Workflows

• After constructing or repairing objects, move to spatial-operations for analysis or io-formats for persistence.
• Before maps or real geocoding, move to mapping-geocoding and check optional dependencies.
• When the result must be asserted in code review or tests, move to validation-testing.