Kentucky Population Density

Kentucky Population Density

This example displays population density across Kentucky counties using a choropleth map. A threshold color scale with regularly-spaced breaks assigns color to each county based on population per square mile, while a legend with an axis shows the mapping. The visualization uses d3.geo.conicConformal projection, d3.geo.path for rendering, and TopoJSON data for county boundaries. The code loads county data via d3.json, computes density from population and area properties, and appends SVG paths with tooltips showing county names and densities.

94% match

Country population density

This choropleth map shows global population density by country, using color shading to represent people per square kilometer across multiple years from 2010 to 2021. The visualization is built from a GeoJSON file containing country boundaries and population density values for each year. The map encodes the population density data through a color scale, where darker or more intense colors indicate higher density values, allowing viewers to quickly compare population pressure across nations. Interactive hover or click tooltips would display the exact density values for each country and year.

WWill Carter

66% match

Population Choropleth

A population choropleth of U.S. counties uses a logarithmic color scale to show population density, ranging from pale yellow to dark blue. The map projects counties with d3.geo.albersUsa() and renders them as SVG paths via d3.geo.path. Density is calculated by dividing each county’s population (from the 2010 Census shapefile, converted to TopoJSON) by its projected area, with the color domain set between the 1st and 99th percentiles. The topojson.feature API extracts county geometries for display.

65% match

U.S. Population Density

This map visualizes U.S. population density by census tract using a choropleth coloring scheme, with darker reds indicating higher people per square mile. It renders static SVG via an HTML image tag, and the map is derived from 2014 American Community Survey data joined with census tract boundaries. The build uses TopoJSON CLI tools (`geo2topo`, `topomerge`, `toposimplify`) and D3 projections (`d3.geoAlbersUsa`), with color bins defined by `d3.schemeOrRd` and a custom legend.

63% match

White-tailed Deer in KY by County

This visualization plots White-tailed Deer observations across Kentucky counties over time, using a scatterplot where each point represents an observation dated by year-month on the x-axis and county on the y-axis, with point color and size encoding the county and month respectively. The data comes from an iNaturalist observation export, loaded via `d3.csv`. The chart is built using the vega-lite-api, which wraps Vega-Lite and Vega, with a custom tooltip handler and a dark-themed configuration for improved readability. The view renders as an SVG and auto-fits to the window size.

RRedSorrel

California Population Density

This map visualizes population density across California census tracts, coloring each tract according to its population per square mile. It uses a threshold color scale (d3.scaleThreshold) with a sequential color scheme, and renders the state's county boundaries as an overlay. The visualization is built with d3.geoPath for map projections and topojson for handling the topology data. The underlying data comes from the American Community Survey’s 2014 5-year estimates, joined with Census Bureau tract shapefiles and processed through the command-line tools geo2topo, toposimplify, and topomerge to compute densities and simplify the geometry.

California Population Density II

A choropleth map of California displays population density per square mile across 23,198 block groups, using a sequential red color scale and a square-root axis legend. Drawn with `d3.geoPath` and SVG, the visualization loads topology from a preprocessed `topo.json` file, created by scripts that download Census block group boundaries and ACS population data via the Census API. The `prepublish` script projects, joins, and simplifies the data using `geo2topo`, `topomerge`, and `topoquantize`. County borders are overlaid as semi-transparent outlines.

A D3 map using topojson

This example displays a map of Kentucky’s counties, rendered as blue polygons with white strokes on a light background. It uses the Albers equal-area conic projection, configured via `d3.geo.albers()`, and draws each county with `d3.geo.path()`. The visualization loads geographic data from the local `ky-counties.json` file, converts it using the TopoJSON library, and renders it as SVG paths within a React framework.

AAishwarya Manjunath