Core Python frameworks and automated data pipelines driving urban planning, zoning datasets, and spatial map products for New York City.
DCPY is the core Python data engineering package and architectural framework used by the NYC Department of City Planning to build, maintain, and publish critical urban data products.
Automated extraction, transformation, and loading routines processing complex civic datasets with precision.
Seamless handling of geographic boundaries, tax lots, zoning districts, and spatial map coordinates.
Publishing reliable, open-source datasets that power urban planning applications across New York City.
Standardized workflows designed to maintain accuracy, consistency, and reproducibility across all city planning data.
Python-driven modules executing multi-step data transformations from raw source files to query-ready spatial tables.
Rigorous spatial joining and coordinate system standards ensuring compatibility with NYC GIS infrastructure.
The primary domains handled through the DCPY data engineering ecosystem.
Processing zoning district boundaries, commercial overlays, and special purpose districts across the five boroughs.
Maintaining community districts, census tracts, council districts, and political boundaries.
Tracking housing pipeline data, development projects, and spatial demographic shifts over time.
Have questions regarding data pipeline integration, repository documentation, or geospatial tooling? Connect with our team.