France Electoral and Immigration Map

Visualization of France's spreading of sickness 2

This visualization displays the spread of sickness across French regions on a chloropleth map, with a slider to navigate through different weeks. It shows regional infection values as colored areas, with a tooltip revealing the specific region name and its value on hover. The map is rendered using `d3.geoPath` with a conic conformal projection, while the color scale is dynamically updated using `d3.scale.quantize`. Data is loaded asynchronously from both a GeoJSON file for region boundaries and a CSV file containing weekly sickness counts, processed through the `queue()` API.

79% match

Visualization of France's spreading of sickness

A choropleth map of French regions colors each area by the total number of influenza cases reported in November 2014, with a five-color quantized scale ranging from light green to dark green. The visualization uses D3 v3’s `d3.geo.conicConformal` projection and `d3.geo.path` to render the geographic boundaries from a GeoJSON file, while a CSV dataset provides weekly regional sickness counts. Hovering over a region reveals a tooltip with the region’s name and its November total.

79% match

Visualization of France's spreading of sickness

A choropleth map displays the geographic spread of influenza-like illness across French regions for November 2014, using a five-color quantitative scale. The visualization loads regional illness counts from a CSV file and merges them with geographic boundaries from a GeoJSON file. The map is rendered with D3 v3, using its geo path and conic conformal projection APIs, while color encoding is applied via d3.scale.quantize. Hovering over a region reveals its name and the corresponding November case count in a tooltip.

79% match

covid en France!

This choropleth map shows the number of COVID-19 hospitalizations per French department, encoded with a white-to-dark-red color scale. The visualization uses a Mercator projection via `d3.geoPath` and `d3.geoMercator`, with `d3.scalePow` mapping hospitalization counts to fill colors. Hovering reveals the department name and its count through a `<title>` element. The map supports pan and zoom through `d3.zoom`, and data is loaded from a CSV file using `d3.csv`.

Yyvesponcon

covid en France avec légende!

A choropleth map of France displays cumulative COVID-19 hospitalizations per department, with a white-to-dark-red color scale using a power exponent to emphasize high totals. The visualization uses d3.geoMercator and d3.geoPath to project and draw geographic features from a JSON topology, while d3.scalePow maps the data domain to the color range. Department totals are loaded from a CSV file via d3.csv, and each path includes a title tooltip showing the department name and its value.

Yyvesponcon

Visualization of France's spreading of sickness

This visualization maps the spread of influenza across French regions for 2014 using a choropleth map. It shows the total number of sickness cases per region, aggregated from weekly data, with color intensity representing the November case counts. Built with D3 v3, the code loads geographic boundaries from a GeoJSON file and CSV data, projecting regions with `d3.geo.conicConformal`. A quantized color scale encodes values, and a tooltip displays region names and November totals on mouseover.

geographic

A choropleth map of France animates through 52 weeks of 2014, showing the incidence of flu cases by region. A slider lets the user scrub through time, and hovering over a region reveals its name. The visualization uses D3 v4 to load a GeoJSON of French regions and a CSV of weekly case counts, with `d3.geoConicConformal` and `d3.geoPath` drawing the map and a quantized color scale encoding case numbers.

AAubret