jc-taxes

Interactive 3D choropleth of Jersey City property tax payments, from 2018 to 2025: jct.rbw.sh

All view state is URL-encoded via use-prms (view, aggregation, selection, mh max height, pct percentile, sp settings position, ...):

• Lots — ?agg=lot&sel=14507-1
• Wards — ?agg=ward&sel=ward-E&wg=blocks
• Units — ?agg=unit&mh=1100&pct=99&sp=br
• From the west — ?v=…+106&agg=lot

What it shows

Every property tax payment in Jersey City, visualized as extruded polygons on a map. Color and height encode $/sqft (or $/capita). Parcels can be viewed at five aggregation levels: wards, census blocks, tax blocks, dissolved lots, and individual units.

Data is scraped from the HLS property tax inquiry system (70K+ accounts), joined with parcel geometries from NJGIN and JC Open Data, and census population data from Census TIGER/Line.

Structure

src/jc_taxes/       Python package: scrape, process, export
  cli.py            `jct` CLI (enumerate-accounts, fetch, export)
  api.py            HLS API client
  payments.py       Extract yearly payment totals from cached JSONs
  geojson_yearly.py Join payments + geometries → GeoJSON per year/aggregation
  building_desc.py  Parse encoded Building Desc field (stories, units, etc.)
  census.py         Census block + ward geometry/population processing
data/               Parcel data, payment caches, parquet exports
census/             Census block geometries, ward boundaries, population
www/                Vite + React web app (see www/README.md)

Data pipeline

jct enumerate-accounts   # discover ~70K accounts from parcel block numbers
jct fetch                # fetch account details from HLS (one JSON per account)
jct export               # extract structured data → data/taxes.parquet
python -m jc_taxes.payments      # → data/payments.parquet
python -m jc_taxes.geojson_yearly  # → www/public/taxes-{year}-{agg}.geojson

See DATA-SOURCES.md for details on each data source.

Setup

# Python (data pipeline)
uv sync

# Web app
cd www && pnpm install

Links

• ROADMAP.md — shipped features and future plans
• DATA-SOURCES.md — data sources and pipeline details
• www/README.md — web app docs

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cast.mp4

Try it live →