Detroit House Foreclosures

Fork of York Funding Data

This interactive visualization displays US city housing metrics across seven switchable views, including median home prices, household income, population, unemployment rate, and job growth. Built with React and D3 v7, each chart—bar, scatter, pie, bubble, box plot, heat map, and line—responds to user clicks, highlighting selected cities in a details panel. The heat map computes a correlation matrix using d3.quantile and scaleLinear with diverging colors, while the line chart fits a linear regression. Data loads from a CSV via d3.csv.

60% match

MI

This visualization displays Michigan counties, municipalities, and electoral boundaries on an interactive Leaflet map. It loads GeoJSON data for counties, municipalities, voting precincts, state house and senate districts, and school districts via d3.json, then renders each as a layer toggleable through Leaflet’s control panel. The map uses OSM tiles from OpenStreetMap as its base layer, with Turf.js loaded for potential spatial analysis. Data is fetched asynchronously from Gist-hosted URLs, organized by category in useMiData.js.

Zzach b.

59% match

York Funding Data Dashboard

This interactive dashboard presents housing market data for 16 U.S. cities, enabling exploration through seven switchable chart types: bar, scatter, pie, bubble, boxplot, heatmap, and line charts. Users click data points to select cities and reveal a details panel with metrics like median home price, rent, income, and job growth. Built with React and D3.js v7, the visualization uses scales, axes, and SVG rendering, with data loaded from a CSV file.

Housing Affordability

This interactive dashboard compares housing affordability across U.S. cities through three metrics: price-to-income ratio, monthly payment percentage, and years to save for a down payment. Users select a metric via dropdown, which updates a bar chart using d3.scaleBand and d3.scaleSequential with Viridis coloring, a multi-line time series chart with d3.line and d3.curveMonotoneX showing trends for five cities, and summary statistics. The visualization renders as SVG with hover tooltips, using d3.select, d3.axisBottom, and d3.axisLeft, leveraging simulated data generated from city income and price values.

Gist 9e143987ca94c3ea3cbbcd28943d7096

This visualization compares consumer expenditure patterns across four Midwest U.S. cities using a force-directed network layout. The code employs `d3.forceSimulation` to arrange nodes by category and city, with `d3.geoPath` absent, instead relying on SVG circles and lines to encode spending amounts. Data comes from a flattened CSV (midwest_flatten_3.csv) listing income and expense categories like housing, food, and transportation. Each city’s values are shown as labeled clusters, with node size and link thickness reflecting dollar figures, rendered via D3’s `enter`/`update` selections and `transition.attrTween` for smooth positioning.

JJustinGOSSES

Gist ac4a02b526cdd611b46159cb475c24e9

This visualization compares consumer expenditures across five Midwestern U.S. cities (Chicago, Detroit, Minneapolis-St. Paul, and St. Louis) using multi-column data from a flat CSV file. It displays a table-like layout where each row represents a spending category, and each column shows the dollar amounts or demographic statistics for that city. The rendering uses D3.js with a `d3.forceSimulation` algorithm to manage the positioning of data elements, making the comparison of values and category hierarchies visible at a glance. The data structure features three levels of headers, allowing users to trace broad categories like Food or Housing down to specific subcategories.

JJustinGOSSES

Fork of NY State Map 3 - working-Filtering Dashboard-York Funding Data

This interactive housing dashboard visualizes New York State county-level housing metrics alongside a U.S. city comparison map, supporting exploration via a year selector and county click-filtering. It renders a choropleth map of counties using TopoJSON geo data and `d3.geoPath`, with circles scaled by population and colored by median home price on a separate U.S. map. Linked bar charts and line charts update based on selections, making use of D3's scales, axes, and selection methods. The dashboard displays data sourced from a CSV containing sales counts and median prices for 2022–2024.

Aaparnachalumuri@gmail.com

Homessless house affordobility

This dashboard visualizes housing affordability and homelessness across U.S. states by merging two CSV datasets on state and year. It displays a grouped bar chart comparing the percentage of affordable housing against homeless population counts, with hover tooltips providing exact values. The visualization uses d3.scaleBand for the categorical axes, d3.scaleLinear for the value axis, and d3.scaleOrdinal for color encoding. Data is loaded asynchronously via d3.csv with Promise.all, and rendered as SVG elements with interactive mouseover events.