MarineRu

@MarineRu·9 public vizzes

fresh block

A map of San Francisco Bay Area airports shows the percentage of time each month that a nearby weather station reports fog, with each station labeled by its three-letter code. The visualization embeds D3-selected SVG circles and text labels within a Google Maps overlay, positioning each marker using the map's projection. Airport data is loaded from a local JSON file, and the map itself is rendered with the Google Maps JavaScript API.

Jul 24, 2017

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fresh block

This visualization displays monthly values as a line chart with circular markers, showing a basic time series of twelve data points from January through December 2016. The SVG rendering uses d3.svg.line with an ordinal x-scale and linear y-scale to map the data. Hovering over a grey circle highlights it in red, reveals the corresponding value as text above the point, and draws a dashed vertical line from the marker down to the chart baseline. The code relies on d3.json for data loading and d3.time.format for date parsing.

Jul 24, 2017

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VisuVelov

VisuVelov visualizes the availability of bikes and docks at Lyon's Velo'v stations on a map. The visualization shows each station as a point, with its color or size likely representing the current number of available bikes or docks based on timestamped data. It uses D3.js v4 to render the map with SVG, combining geographic station coordinates from a JSON file with real-time availability data from CSV files. The map updates over time to show the dynamic state of the bike-sharing network.

Jul 18, 2017

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fresh block

This visualization displays bicycle and docking station availability in Lyon, France. The data includes station locations from a JSON file and time-stamped availability counts from CSV files. The code uses D3.js (version 4) to render an SVG visualization. It loads the data files and creates an interactive display showing the dynamic changes in bike and slot availability over time.

Jul 18, 2017

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testProjet

This visualization displays a choropleth map of European countries colored by their motor vehicle statistics over time. The code loads geographic boundaries from `eurotopo.json` and motor vehicle data from `type_of_motor_cars.csv`, then uses `d3.geo.conicConformalEurope` projection with `d3.geo.path` to render the map. The interface includes a tooltip for displaying values, suggesting interactive exploration of population and vehicle counts across different European regions and years.

Dec 22, 2016

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TP5

A choropleth map of French regions displays weekly influenza case counts from 2003 to 2015, with a slider to scrub through time and a tooltip showing the region name and value on hover. The visualization loads GeoJSON and CSV data asynchronously using `queue().defer`, projects the map with `d3.geo.conicConformal`, draws regions via `d3.geo.path`, and colors each region using a quantile scale applied to the weekly count.

Dec 6, 2016

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TP4

This choropleth map of French regions visualizes the total number of flu cases reported during November 2014, with a color scale from light to dark green indicating increasing values. Hovering over a region displays its name and computed value in a tooltip. The visualization uses d3.geo.conicConformal for projection and d3.geo.path to render the GeoJSON regions, while d3.csv loads the weekly flu data.

Dec 4, 2016

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Gist 114b7db11f7173d0ddc4f44d2c0ea687

A choropleth map displays weekly influenza case counts across French regions for 2014, with a slider to navigate through time and a tooltip showing region names and values. The visualization merges CSV data with GeoJSON region boundaries using `d3.csv` and `d3.json`, and renders the map with `d3.geo.conicConformal` and `d3.geo.path`. A quantize color scale encodes case totals, while `queue()` loads the data files asynchronously before processing.

Dec 1, 2016

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Gist cf47ed32426b88863d607d9d0dccb77d

This example shows a single outlined region of France rendered as a black-and-white map using the D3.js library. It uses the `d3.geo.path()` API with a conic conformal projection to transform GeoJSON polygon coordinates into SVG paths. The visualization loads its geographic data from a local `regions_geo.json` file and draws the shape on a fixed-size SVG canvas.

Nov 28, 2016