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geopandas skill

by K-Dense-AI·K-Dense-AI/scientific-agent-skills·47k stars·MIT

Guidance and local audit tools for Python workflows that directly use GeoPandas GeoSeries, GeoDataFrame, spatial operations, or vector-data I/O.

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Is the geopandas skill safe?

Clean: nothing in its files matched our rules. We read 14 files in the folder on 2026-09-28.

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Install the geopandas skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. 

git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills.git /tmp/scientific-agent-skills
mkdir -p ~/.claude/skills
cp -r /tmp/scientific-agent-skills/skills/geopandas ~/.claude/skills/geopandas
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

GeoPandas

Use GeoPandas for planar vector data represented as pandas-like GeoSeries and GeoDataFrame objects. This skill targets stable GeoPandas 1.1.4 (released 2026-06-26), not the unreleased 1.2 documentation.

Reproducible environment

GeoPandas 1.1.4 requires Python 3.10+; its tagged source requires NumPy >=1.24, pandas >=2.0, Shapely >=2.0, pyproj >=3.5, pyogrio >=0.7.2, and packaging. This exact Python 3.12 snapshot was smoke-tested on 2026-07-23:

uv venv --python 3.12
uv pip install \
  "geopandas==1.1.4" \
  "numpy==2.5.1" \
  "pandas==3.0.5" \
  "shapely==2.1.2" \
  "pyproj==3.7.2" \
  "pyogrio==0.13.0" \
  "pyarrow==25.0.0" \
  "packaging==26.2"

Keep optional plotting and PostGIS packages pinned in the project lock as well. Do not mix binary geospatial packages from incompatible package channels.

Safety and privacy contract

small-area joins as sensitive. Default reports to counts, categories, coarse extents, and redacted identifiers. Generalize before publication.

  • Treat exact coordinates, addresses, parcel boundaries, trajectories, and

geocode an address. Obtain explicit approval, validate provenance and hashes, then stage an unpacked local file in an isolated workspace.

  • Never automatically load a URL, cloud URI, GDAL /vsi* path, archive, or

native-code trust boundary. Prefer official wheels/conda-forge, record native versions, restrict drivers, and process untrusted data in a sandbox.

  • GDAL/OGR drivers, GEOS, PROJ, pyogrio, Shapely, pyproj, and their wheels are a

GDAL drivers. The bundled CLIs use an extension allowlist and reject archives.

  • Do not open macro-enabled office files or nested archives through permissive

secret manager or scoped environment variable. Never embed a password in a URL or source, print an engine/URL, or dump the environment.

  • Read only named database secrets such as GEOPANDASPOSTGISPASSWORD; use a

predicate, join cardinality, precision/repair choices, and row-count checks.

  • Every derived artifact needs source hashes/versions, CRS, operation parameters,

Correctness gates

Apply these gates before trusting a result:

duplicate IDs, row count, geometry column, parser/driver, and content hash.

  1. Identity and provenance — identify the source layer, stable feature key,

geometries separately. None is missing; an empty Shapely geometry is real.

  1. Geometry state — count null, empty, invalid, mixed, Z/M, and collapsed

to_crs() transforms coordinates. Never guess a CRS from coordinate ranges.

  1. CRS semantics — require CRS metadata. set_crs() assigns metadata;

angular; do not use them directly for buffer, distance, area, nearest joins, precision grids, or tolerances. Choose a fit-for-purpose local/equal-area CRS or a geodesic method.

  1. Units and operation — GeoPandas is planar. Geographic coordinates are

expected accuracy, ballpark status, and missing grids. Keep PROJ network disabled unless the user explicitly approves grid retrieval.

  1. Transform quality — inspect axis order, area of use, datum pipeline,

precision grid from source accuracy and CRS units; arbitrary snapping can collapse features or create bias.

  1. Topology and precision — validate before and after repair/overlay. Pick a

behavior before merge, sjoin, or sjoin_nearest; audit unmatched and multiplied rows afterward.

  1. Cardinality — state expected one-to-one, one-to-many, or many-to-many

document schema/CRS/encoding, reopen the artifact, and compare counts/types.

  1. Output contract — use a new output path, preserve a stable feature ID,

CRS and antimeridian rules

GeoPandas stores CRS as pyproj.CRS. Coordinate arrays use traditional GIS (x, y) order, while authority definitions can advertise latitude-first axes. Use Transformer(..., always_xy=True) for explicit coordinate-array pipelines, and record that choice.

to_crs() transforms vertices and assumes each segment is straight in the source CRS; it does not transform geodesic arcs. Geometries crossing ±180° or a projection boundary can be badly wrapped. Detect crossings, split/unwrap and densify in a documented geographic representation, transform parts, then validate. Do not use Web Mercator as a general measurement CRS.

crs = gdf.crs  # a pyproj.CRS when present
if crs is None or crs.is_geographic:
    raise ValueError("Choose a justified projected CRS before planar measurement")

unit_names = [axis.unit_name for axis in crs.axis_info]
areas = gdf.geometry.area  # square CRS units, not automatically square metres

See CRS management.

Core API decisions

Data structures

but only activegeometryname drives frame-level spatial operations.

  • A GeoDataFrame can hold multiple geometry columns, each with CRS metadata,

align=False only when positional pairing is explicitly intended and lengths and order were verified.

  • Binary GeoSeries methods are row-wise and align by index by default. Use

resolve them before joins and exports.

  • Duplicate column names and duplicate feature IDs are ambiguous; reject or

See data structures.

Geometry validity, precision, and union

Use isvalid and redacted isvalidreason() categories before makevalid(method="linework"|"structure", keep_collapsed=...). Repair can change geometry type or dimension; retain the original and compare counts, area, types, empties, and collapsed parts.

setprecision(gridsize, mode=...) uses CRS units and may remove duplicate vertices or collapse features. unionall(method="unary", gridsize=...) is the robust default. Use coverage only after isvalidcoverage() proves non-overlap and edge matching; use disjoint_subset with Shapely >=2.1 when its partitioning assumption is useful.

See geometric operations.

Joins, overlay, clip, and dissolve

left.contains(right). intersects includes boundary contact; contains excludes boundary-only points, while covers includes boundary points.

  • sjoin predicates are directional: left.within(right) is not

are in CRS units. sjoinnearest returns all equidistant nearest matches and does not** implement a k= parameter.

  • predicate="dwithin" requires distance; scalar or per-left-row distances

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