Gist baae6b15cf267f80467294f6cf1ab34b

Gist 0562486f752206b124480873ad868676

A choropleth map of France colors each region according to its total reported flu cases across 2014, using a green sequential scale to show geographic variation in incidence. The visualization loads weekly case counts from a CSV file and joins them to regional polygons from a GeoJSON file by matching region names. D3 v4’s `d3.geoConicConformal` projection and `d3.geoPath` render the map, while a `d3.scaleQuantize` maps summed annual values to five color classes. Regions lacking data appear gray.

EElisaDnr

94% match

Gist bfcd7300bf6652dd21c66bcd2c850bfe

A choropleth map of France displays the total annual flu cases per region for 2014, sourced from the `GrippeFrance2014.csv` file. The map uses a color scale ranging from 0 to 2000 to encode each region's cumulative count from the `somme2014` column. The visualization is built with D3 v4, utilizing `d3.geoPath` with a conic conformal projection to render the regional boundaries from the `regions.json` TopoJSON data, and then joins the CSV values to fill each polygon.

EEsdras08

94% match

Gist 7a670ce28de4fb296ed54dbff24bed19

A choropleth map of French regions colors each region by the sum of flu cases reported over five weeks in November 2014, using a green sequential scale from gray to dark green. It loads region boundaries from a GeoJSON file and joins them with CSV data containing weekly case counts per region. D3 v3’s `d3.geo.conicConformal` projection and `d3.geo.path` render the map, while a quantize color scale maps values to five color bins. Hovering over a region displays its name and total case count in a tooltip.

Gist bfc4fc4700e3d19007fa079cdb68d18a

A choropleth map of France shows the incidence of influenza across 22 regions for a five-week period in late 2014, with darker green fills marking higher case counts. The visualization merges weekly case data from a CSV file with regional boundaries from a GeoJSON file, using a conic conformal projection to render the map. Color values are assigned via `d3.scale.quantize()`, and interactive tooltips display the region name and summed case total on mouseover. The code relies on D3.js v3 for geospatial paths, data loading, and event handling.

Gist 557a7c0474a7c20c0723b9ab166c105b

A choropleth map of French regions shows the cumulative reported influenza cases for November 2014, using a five-color quantize scale from green to dark green on a light gray base. The map is rendered with d3.v3’s geo path and a conic conformal projection, loading region boundaries from a GeoJSON file and joining them with CSV data. Hovering over a region displays a tooltip with its name and total case count for that period.

Gist 8451fca4f10e880b32066b08ca934d3b

This choropleth map of French regions visualizes the total number of reported influenza cases for November 2014, coloring each region on a green scale from light to dark based on case counts. The visualization uses d3.geo.conicConformal projection and d3.geo.path to render the GeoJSON map, while a d3.scale.quantize maps data values to colors. Hovering over a region displays its name and case count via a tooltip. The data aggregates weekly flu statistics from the GrippeFrance2014.csv file specifically for the month of November.

Gist baa4df6da9fa4834e074874f5bf4dbb4

A choropleth map of France shows aggregated influenza cases per region for a one-week period in November 2014, with a green sequential color scale ranging from light to dark based on case counts. Built with D3 v4, the visualization merges weekly CSV data with a GeoJSON map of French regions. It uses `d3.geoConicConformal` for projection and `d3.geoPath` to render region boundaries, while a tooltip displays region names and exact case totals on mouseover.

CChaf1A

Gist 54ef66cc8b6ee717b9f33d505ce60940

A choropleth map of France shows the total number of influenza cases reported in 2014 for each administrative region. The map uses a green color scale, with darker shades representing higher case totals, and grey for regions without data. The visualization is built with D3 v3, using `d3.geo.conicConformal` for the map projection and `d3.geo.path` to render the GeoJSON boundaries. CSV data is joined to the geographic features, with a quantize scale mapping summed annual case counts to the color range.

OOrhanYaz