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A map of Japan displays the impact of the 2011 Tōhoku earthquake and tsunami, with a side panel providing context and narrative text. The visualization uses CartoDB's JavaScript library to render the map, integrating with Google Maps API for the base layer. The layout combines a full-width map with a text panel, and the code includes responsive CSS to adjust the display on smaller screens. The map data is loaded from a CartoDB visualization URL.

62% match

Gist 4503902

This map shows global cities categorized by type, with buttons to filter between all populated places, national capitals, and megacities. It overlays a second data layer that can be toggled via the same menu, though the code only reveals it on button click without a corresponding hide action. The visualization uses the CartoDB.js library to load tile layers and vector data from CartoDB’s viz.json API, with Leaflet handling the map interaction and tile display. Styling applies custom marker properties for red fill, white outlines, and overlap allowance, while CSS fades are disabled for smoother layer transitions.

61% match

CartoDB Fiesta

This example shows a live map of Denver traffic accidents from 2013, colored and animated over time with CartoDB’s Torque rendering, alongside a census-neighborhood choropleth layer for normalization. The visualization is built through the CartoDB editor and its JavaScript API, using SQL queries to filter and delete pre-2013 records, compute distances with `CDB_LatLng` and the `<->` operator, and join accident points to districts via `ST_Intersects`. The embedded map is served from a CartoDB-hosted URL.

Gist 4495761

This interactive map displays global cities, filtered by categories such as all locations, national capitals, and megacities. Users select a filter via buttons in the top-right menu, which dynamically updates the displayed points. The visualization uses the CartoDB library to create and manage layers over a Leaflet map, with a dark MapBox tile layer as the base. Point styling is defined through CartoDB’s tile style syntax, and SQL queries on the underlying dataset change the visible features per selection.

Bar Chart, Framed

Animated horizontal bar chart of hydro-vulnerability rates across Barcelona metro municipalities, sorted descending, with hover labels showing exact percentages. The visualization then transitions to a scatterplot comparing these rates against registered unemployment, framed within white panels on a gray background. Built with D3.js (version 3.5.6), it uses ordinal scales, SVG transitions, and axis components to render the data from the supplied CSV.

CContrastat

Gist cb853c154b8bb2343561

This visualization maps Barcelona’s neighborhood demographics across multiple years, contrasting population age brackets with a family income index (where the city average equals 100). It renders each district as a choropleth, using color intensity to represent income disparities, and likely employs discrete legends for each year. The code uses D3.js for geospatial paths and data binding, with an interactive year selector to toggle between 2008 and 2009 datasets. The data originates from a CSV file, parsed and joined to the geographic boundaries for display.

QQbelil

Gist 67fa3790166d6549f4a9

This interactive visualization pairs a large world map with a side panel, using D3’s `d3.forceSimulation` to scatter data points across geographic coordinates rendered via `d3.geoPath` and Canvas `getImageData` for pixel-level placement. The layout adapts responsively, and the code includes CSS themes for light or dark editorial styling, suggesting a map-based storytelling template.

Gist 4354110

This visualization displays a map rendered with CartoDB, showing geographic data from a hosted visualization. The page loads a full-screen map using the CartoDB.js library, which initializes the map via `cartodb.createVis` and connects to a remote visualization URL. The map itself is embedded in a fixed-size `<div>` element and relies on CartoDB’s built-in rendering and tile services to draw the geographic layers. The code does not include custom data processing or interaction logic; it simply leverages the CartoDB API to present the pre-configured map.