Wrangling Parcel and Assessment Data: An Open-Data Property Explorer for Cook County
Skill Level: Intermediate
Intended Audience: GIS User, GIS Builder, GIS Developer, GIS Instructor, Student, Management
Abstract
Parcel and assessment data sit at the center of local government GIS, yet working with them is rarely straightforward. Property Index Numbers (PINs) encode geography in ways that trip up joins, condominiums fracture into unit-level records that don’t behave like single-family parcels, and assessment tables rarely align cleanly with spatial layers. This presentation walks through those challenges using Cook County as a worked example, built around an interactive explorer that pulls parcels and assessment data directly from the Cook County Assessor’s open data portal. I’ll cover the practical mechanics: how PINs are structured and parsed, why condos and single-family homes demand different handling, how to reliably join assessment attributes to parcel geometry, and how to catch the data-quality issues that quietly break analysis. Along the way I’ll map the county’s data landscape honestly - which layers are fully open and API-accessible (sales, addresses, characteristics, parcel-level locational data) versus geometry that carries the county’s conditions of use, and how that shapes whether you query live or redistribute. While Cook County is the example, the workflow is deliberately portable: the same patterns apply to parcel and assessment data across Illinois counties. Attendees leave with a concrete, replicable approach to turning messy property data into something analysis-ready, an open-source Python and web-mapping stack to borrow, and a clear-eyed view of what open data does and doesn’t permit.
Presenter(s)
Eshan Prashar
Senior Geospatial Scientist, Cotality
Eshan is a Senior Geospatial Scientist at Cotality, where he builds location intelligence products drawing on parcel, property, demographic and infrastructure data. They hold a Master’s in Computational Analysis and Public Policy from the University of Chicago and work at the intersection of spatial analysis, machine learning, and open civic data. Outside of client work, they build tools that make public datasets - like Cook County’s parcel and assessment data - easier to explore and analyze.