Genomic interval operations on Pandas DataFrames
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Updated
Aug 3, 2026 - Python
Genomic interval operations on Pandas DataFrames
BBoxDB is a scalable, highly available, and distributed data store for multi-dimensional big data. The software supports operations like multi-dimensional range queries and spatial joins. In addition, data streams are supported.
A fast library for spatial joining and merging data in JavaScript 🚀
An example of how to join point to polygon data with geopandas and Python
RTDL is a research system for writing and running non-graphical ray-tracing programs across Embree, OptiX, and Vulkan.
Spatial joining with a map reduce program on top of Apache Spark using the Apache Sedona spatial extension
How much of California's public wildfire damage-inspection record set can be attributed to a published electric service territory, and how much cannot. 37.9% of records fall inside more than one published boundary. Every rate carries its denominator and a confidence interval; no utility is ranked. Unofficial.
Polygon & GMR 1 — QGIS plugin: join a polygon layer with an Excel file (GMR). Reads the real column headers of every sheet, matches on a chosen join field, and outputs only the matching polygons with their attribute table enriched with the Excel columns.
Vector spatial analysis of vape-store proximity to Christchurch schools using CRS validation, buffers, spatial joins, and nearest distances.
An enhanced intersect operation with sjoin in GeoPandas
An advanced multi-scalar geovisualisation of the UK's renewable energy landscape. This project maps the "Renewable Gap" by integrating the Q4 2025 REPD database with 33,000+ LSOA boundaries, featuring a drill-down dashboard to analyze operational reality vs. the planning pipeline.
Adding timing and location to traditional types of data and to build data visualizations.
Point-in-polygon testing and point-to-polygon spatial joins for Standard ML, with an optional R-tree-accelerated join.
Geospatial pipeline converting KML/KMZ service areas into FCC Fabric-matched location datasets with DuckDB, Shapely, and Google Cloud.
End-to-end GIS data engineering pipeline: Natural Earth → GeoParquet QA → DuckDB Spatial analytics → GitHub Pages Leaflet map.
Benchmark spatial joins across GeoPandas, Shapely 2, and PostGIS
Interactive Streamlit lab for spatial joins, buffers and nearest-neighbor queries — upload two datasets, run the analysis on a map, download the result. Maintained by python-geospatial.com.
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