Gist 516c27edc013850e5fa703af9f9c0f03

Gist 177f6c8fe1ef0050c1d0d9e490f6f6d5

This example visualizes the centroids of French communes as a particle system, with each point positioned by latitude and longitude from a CSV dataset. Using WebGL rendering within a Vue framework, the visualization employs a force simulation to spatialize the points, while geographic context is provided through a canvas-based path drawing approach. The underlying data includes commune names, INSEE codes, population, and coordinates, allowing the particles to reflect real administrative geography. The rendering leverages d3.forceSimulation for dynamic positioning and canvas getImageData for analyzing pixel density, creating a dense, interactive map-like scatter of population centers.

PPhilippe Rivière

80% match

Gist 1f575522ca61946b31d92bbd146a9dce

This visualization compares French legislative electoral districts between 2012 and 2017, showing how commune boundaries and canton assignments shifted across the two years. It displays two side-by-side maps, likely using Three.js with WebGL rendering to animate or morph between the two configurations. The data comes from CSV files containing commune-to-canton and commune-to-district correspondences for both years. The visualization relies on the Vue framework to manage the interface and handle state transitions, with the geographic comparisons rendered through WebGL for smooth interactive exploration.

77% match

Territoire vie santé (TVS)

This visualization displays the French "Territoires vie santé" (TVS) boundaries, aggregating communal administrative units into larger health-related regions. It shows the relationship between individual municipalities and their associated TVS zones, with contours generated by dissolving commune polygons based on shared TVS codes. The map employs WebGL for smooth rendering of the geographic data. Built with Vue, it loads GeoJSON data containing commune geometries and their TVS assignments, using mapshaper for geometric processing and the ouvre-contours-administratifs dataset as the underlying source.

71% match

regions 2017

This example visualizes France’s administrative regions in 2017 as a grid of labeled cells, showing how each region groups its constituent departments. It displays region names, IDs, and department codes from a CSV source. The visualization uses D3’s `d3.forceSimulation` to arrange the cells into a packed layout, while `d3.geoPath` and Canvas `getImageData` likely handle any geographic or pixel-based operations. The rendering relies on a custom force-directed placement, with each region’s departments listed in the data file, and no external mapping library beyond D3’s core modules.

PPhilippe Rivière

Récupération geolocalisation EHPAD 57

This example visualizes the geographic distribution of EHPAD (nursing homes) in the Moselle department (57) of France, displaying each facility as a point on a map. The data is retrieved from a public government API and converted to GeoJSON format using `jq` command-line tools for filtering and restructuring. The visualization is built with the Vue framework, rendering the geographic points to show facility locations, with additional property information such as name, city, and legal status included for reference. The map uses standard GeoJSON `Point` features to represent each facility's coordinates.

Gist 596274e96e08f79d5a6d5a6b1c37b944

This visualization displays the incidence of influenza across French regions during the 2014 season, with a choropleth map coloring each region based on its total annual case count. The map is rendered using `d3.geoConicConformal` projection and `d3.geoPath` to draw France’s departmental boundaries. Data from a CSV file is joined to a GeoJSON of regional shapes, and the final fill color reflects each region’s summed value. The code also includes a US states GeoJSON, though its use is not demonstrated in the visible implementation.

CChmits

Gist 32329a8557135f11cb5656e3bfd4d35c

A WebGL map visualizes the locations of French tobacco shops, using points to show their distribution. The code geocodes addresses from an official customs dataset via the data.gouv.fr API, then processes the CSV with the `requests` library. It uses a Vue.js front-end to render the points in a 3D space, allowing users to explore the spatial patterns of the shops.

data_viz_projet

This interactive map of France displays train stations as pink dots over gray regions. Users can click a region to zoom in via a smooth transition, and hover over any station or region to see a tooltip with its name. The visualization uses D3 v4 with `d3.geoConicConformal` for projection, `d3.geoPath` for rendering GeoJSON shapes, and a quantize color scale for potential thematic mapping. Region and station data come from external GeoJSON sources, with SVG elements animated through D3 transitions.

SSebDelSab