CO2

Reldens

This example displays a choropleth map of Switzerland, visualizing “Relatedness Density” data for NUTS2 regions using a threshold classification. The map uses a sequential RdYlBu color scale from `d3.scaleSequential` and `d3.interpolateRdYlBu` to encode the values. It leverages the `eurostat-map` library to render the map with SVG, and includes a legend, tooltips, and an inset for small screens. The underlying CSV data is loaded from a GitHub gist, and a button allows downloading the resulting SVG.

76% match

Fork of Reldens

This example visualizes Relatedness Density across Swiss NUTS2 regions using a choropleth map. It employs the eurostat-map library to render the geographic boundaries as SVG, with a sequential color scale created via d3.scaleSequential and d3.interpolateYlGnBu to encode data values. The map uses threshold-based classification with specific cutoffs, and includes a legend and tooltips. The visualization also provides a button to download the rendered SVG, and adapts its layout and legend position based on viewport width.

75% match

TRY COMPLEX

This map of Switzerland displays the normalized "Digital Complexity" across NUTS-2 regions, using a color gradient from the d3-scale-chromatic `d3.interpolatePlasma` scale. The eurostat-map library generates the SVG, with a threshold classification method and custom legend. The code also includes a button to download the rendered SVG, and the visualization adapts its layout and tooltip settings for smaller screens using responsive JavaScript conditions. The data is loaded from a CSV file stored on GitHub.

72% match

CMS Tech Share

This visualization maps the share of dependent live-chat traffic across Swiss NUTS-2 regions, using a sequential color scale built with `d3.scaleSequential` and `d3.interpolateRdPu`. The choropleth is rendered as SVG via the `eurostat-map` library, which loads CSV data from a GitHub gist and applies threshold-based classification. A custom arrow annotation and text label are appended to the SVG using `d3.select` and `svg.append`, drawing attention to a specific region. Users can download the resulting map as an SVG file through a button-triggered `XMLSerializer` export.

71% match

CMS Tech Share

This example shows the share of dependent individuals using live-chat technology across Swiss NUTS-2 regions, with a sequential RdPu color scale and threshold-based classification. It uses the `eurostat-map` library, D3 modules (`d3-scale`, `d3-scale-chromatic`, `d3-interpolate`), and a custom download button that serializes the rendered SVG via `XMLSerializer`. The map includes a legend, tooltips, and responsive adjustments for smaller screens.

Swiss Cantons

This example displays a choropleth map of the Swiss cantons, labeling each region with its name. The visualization is rendered as scalable vector graphics (SVG) using D3.js version 3 and the TopoJSON library. It loads geographic data from a `readme-swiss.json` file and projects it using an Albers equal-area conic projection with specific parameters for Switzerland. Canton boundaries are drawn as white paths, while `d3.geo.path()` handles the map projection and centroid calculations for label placement.

Mmbostock

complexity thesis

This interactive choropleth map displays digital complexity across Swiss NUTS2 regions using threshold-based classification. Built with the `eurostat-map` React library and rendered as SVG, it visualizes normalized complexity values from a CSV file, with a "DIGITAL COMPLEXITY" legend. The map includes insets for larger screens and a download button that serializes the SVG to a file via `XMLSerializer`, while responsive settings adjust legend and tooltip sizes for smaller devices.

D3 Data Dashboard

This dashboard visualizes global CO2 emissions across countries, continents, and years, allowing users to compare total emissions or per-capita values via an interactive world map, a pie chart of continental shares, and a bar chart of annual trends for a selected country. Built with D3 v4, it uses `d3.geoMercator` and `d3.geoPath` for map rendering from TopoJSON world atlas data, plus animated SVG transitions for the map, pie arcs, and bars. A year slider and radio buttons drive updates, with tooltips revealing detailed values from the CSV dataset.

VVishnu Sudireddy