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@anouar009·6 public vizzes
This visualization displays a map of French departments drawn as SVG polygons, with each department colored according to its region. The data comes from a GeoJSON file containing department boundaries, centroid coordinates, and administrative metadata. The map uses a geographic projection to render the department shapes, with a bounding box covering France’s metropolitan territory. A color scale encodes the region attribute (`NOM_REGION`), while hovering over a department likely highlights it or reveals its name, making the map useful for exploring regional groupings across the country.
A map of French administrative departments rendered as an SVG using D3 v4, with each department drawn as a filled polygon from the `departments.json` GeoJSON data. The visualization uses a projected geographic layout, and the title "fresh block" suggests a clean, minimal presentation of the department boundaries.
This visualization maps the weekly incidence of influenza-like illnesses across 22 French regions in 2014, using a choropleth overlaid on a geographic map of metropolitan France. The data, from the GrippeFrance2014.csv file, records weekly case counts from January through December, with a cumulative yearly total per region. The map is rendered as an SVG using D3 v4, with region boundaries drawn as paths. Color intensity on each region encodes the value for the selected week, and a date slider or control allows viewers to step through the 52 weeks, revealing the temporal spread and intensity of flu activity across the country.
Four colored blocks in red, yellow, brown, pink, blue, and green each occupy 25% of the width and sit as inline-block elements in a single row, displaying only the text “XXX” in each. The visualization uses plain HTML and CSS within an SVG-enabled page, though the D3 v4 script is commented out, so no D3 API calls are active. The rendering relies on static div styling rather than data-driven SVG or JavaScript manipulation.
This visualization displays the classic Iris dataset, plotting sepal length against sepal width for three flower species—setosa, versicolor, and virginica. Each species is represented by a distinct symbol (diamonds, triangles, and stars) and color (gold, red, and blue). The chart uses d3.svg symbols for the points, linear scales for both axes, and adds axis labels in French ("Longueur" for length and "Largeur" for width). Additionally, the visualization includes least-squares regression lines for each species, overlaid on the scatterplot to show trends in the data. The data is loaded from a CSV file, and the visualization is rendered using D3 v4 with SVG.
This scatterplot visualizes the classic Iris dataset, mapping sepal length and width along the x- and y-axes while encoding petal length with point size. The three iris species are distinguished by both color (using d3.schemeCategory20) and by different d3 symbol shapes (circles, crosses, diamonds, etc.) generated with the d3.symbol API. Axes are labeled, and a legend identifies the species using the same symbols and colors. A tooltip is defined but not activated. Built with D3 v4 and SVG, the chart demonstrates how multiple visual channels—position, size, color, and shape—can be combined in a single scatterplot. Data is the classic Iris dataset loaded from a CSV.