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GeoQA Logo

GeoQA

Geospatial Data Quality Assessment & Interactive Profiling
Profile any geodataset with a single line of code

PyPI Python License CI

What is GeoQA?

GeoQA is a Python package for automated quality assessment and interactive profiling of geospatial vector data. Think of it as ydata-profiling (formerly pandas-profiling) but purpose-built for geodata.

  • Profile any vector dataset (Shapefile, GeoJSON, GeoPackage, etc.) with one line of code
  • Validate geometry quality — invalid, empty, duplicate, and mixed-type detection
  • Analyze attribute completeness, statistics, and distributions
  • Visualize data on interactive maps with quality-issue highlighting
  • Generate self-contained HTML quality reports with charts and tables
  • Automate QA/QC workflows via CLI or Python API

Ecosystem

GeoQA is the data-readiness gate in a two-stage geospatial quality control pipeline alongside OVC and OVC ArcGIS Pro.

flowchart LR
    A["Geospatial\nData"] --> B

    subgraph B["GeoQA"]
        direction TB
        B1["Score"]
        B2["Profile"]
        B3["Validate"]
        B4["Report"]
    end

    B -- "Pre-check\nGate" --> C
    B -- "Pre-check\nGate" --> E

    subgraph C["OVC Python"]
        C1["Road QC"]
        C2["Building Overlaps"]
        C3["Road Conflicts"]
    end

    subgraph E["OVC ArcGIS Pro"]
        E1["5 Toolbox Tools"]
    end

    C --> D["QC Results\n& Web Maps"]
    E --> D

    style A fill:#fff,stroke:#e91e63,color:#000
    style B fill:#2e9e49,stroke:#1b7a33,color:#fff
    style B1 fill:#fff,stroke:#e91e63,color:#000
    style B2 fill:#fff,stroke:#e91e63,color:#000
    style B3 fill:#fff,stroke:#e91e63,color:#000
    style B4 fill:#fff,stroke:#e91e63,color:#000
    style C fill:#2962ff,stroke:#1a44b8,color:#fff
    style C1 fill:#fff,stroke:#e91e63,color:#000
    style C2 fill:#fff,stroke:#e91e63,color:#000
    style C3 fill:#fff,stroke:#e91e63,color:#000
    style E fill:#7c3aed,stroke:#5b21b6,color:#fff
    style E1 fill:#fff,stroke:#e91e63,color:#000
    style D fill:#fff,stroke:#2962ff,color:#000
Loading

Key Features

Feature Description
One-liner profiling geoqa.profile("data.shp") — instant dataset overview
Geometry validation OGC-compliant validity checks, empty/null detection, duplicate finding
Attribute profiling Data types, null analysis, unique values, descriptive statistics
Interactive maps Folium-based maps with issue highlighting and quality coloring
HTML reports Self-contained quality reports with charts and tables
CLI interface geoqa profile data.shp — terminal access to all features
Auto-fix Repair invalid geometries with profile.geometry_results
Spatial analysis CRS info, extent, area/length statistics, centroid computation

Installation

pip install geoqa

From source (development):

git clone https://github.com/AmmarYasser455/geoqa.git
cd geoqa
pip install -e ".[dev]"

Requirements: Python 3.9+ — depends on geopandas, shapely, folium, matplotlib, pandas, numpy, jinja2, click, and rich.

Quick Start

Python API

import geoqa

# Profile a dataset
profile = geoqa.profile("buildings.shp")

# View summary
profile.summary()

# Interactive map with issue highlighting
profile.show_map()

# Quality check details
profile.quality_checks()

# Generate HTML report
profile.to_html("quality_report.html")

# Attribute and geometry statistics
profile.attribute_stats()
profile.geometry_stats()

From a GeoDataFrame

import geopandas as gpd
import geoqa

gdf = gpd.read_file("roads.geojson")
profile = geoqa.profile(gdf, name="City Roads")
profile.summary()

CLI

geoqa profile data.shp                        # Profile a dataset
geoqa report data.shp --output report.html     # Generate HTML report
geoqa check data.geojson                       # Run quality checks only
geoqa show data.gpkg --output map.html         # Open interactive map

Quality Score

GeoQA computes an overall quality score (0–100) based on:

Component Weight Description
Geometry Validity 40% Percentage of valid geometries (OGC compliance)
Attribute Completeness 30% Percentage of non-null attribute values
CRS Defined 15% Whether a coordinate reference system is set
No Empty Geometries 15% Percentage of non-empty geometries

Quality Checks

Check Severity Description
Geometry Validity High OGC Simple Features compliance
Empty Geometries Medium Geometries with no coordinates
Duplicate Geometries Medium Identical geometry pairs (WKB comparison)
CRS Defined High Coordinate reference system presence
Attribute Completeness Varies Null/missing value analysis
Mixed Geometry Types Low Multiple geometry types in one layer

Interactive Visualization

GeoQA creates interactive Folium maps with auto-reprojection to WGS84, quality highlighting (invalid in red, valid in blue), interactive tooltips, multiple basemaps, and layer controls.

profile.show_map()

# Or use the visualization API directly
from geoqa.visualization import MapVisualizer
viz = MapVisualizer(profile.gdf, name="My Data")
quality_map = viz.create_quality_map(profile.geometry_results)

HTML Reports

Generate comprehensive, self-contained HTML reports:

profile.to_html("report.html")

Reports include quality score badges, dataset overview cards, quality check tables with pass/fail/warn indicators, spatial extent information, attribute completeness bars, numeric column statistics, and geometry type distributions.

Supported Formats

All vector formats readable by GeoPandas/Fiona: Shapefile, GeoJSON, GeoPackage, KML, GML, CSV with geometry, File Geodatabase, and more via GDAL/OGR drivers.

Architecture

geoqa/
├── core.py           # GeoProfile — main entry point
├── geometry.py       # Geometry validation & quality checks
├── attributes.py     # Attribute profiling & statistics
├── spatial.py        # CRS, extent, area/length analysis
├── visualization.py  # Folium-based interactive maps
├── report.py         # HTML report generation (Jinja2)
├── charts.py         # Matplotlib chart generation
├── cli.py            # Click-based CLI interface
└── utils.py          # Utility functions

Contributing

Contributions are welcome. See CONTRIBUTING.md for guidelines.

git clone https://github.com/AmmarYasser455/geoqa.git
cd geoqa
pip install -e ".[dev]"
pytest
black geoqa/ tests/

Author

Ammar Yasser

License

MIT License

Acknowledgments

GeoQA is inspired by the development methodology and open-source philosophy of Dr. Qiusheng Wu and the opengeos community. Key inspirations include leafmap, geemap, and ydata-profiling.

Citation

@software{geoqa2026,
  title   = {GeoQA: A Python Package for Geospatial Data Quality Assessment},
  author  = {Ammar Yasser Abdalazim},
  year    = {2026},
  url     = {https://github.com/AmmarYasser455/geoqa},
  license = {MIT}
}