Gist 003d087ad317bf871eabd0fb77a719eb

Gist 80f99a186a44e6fa1930f2a08618d498

This visualization displays a QGIS project containing world map layers—countries, states, provinces, and disputed borders—from the bundled `world_map.gpkg` GeoPackage, alongside JSON-derived point layers for contributors, hackfests, and user groups. Using the QGIS Python API, the script loads each vector layer via `QgsVectorLayer` with OGR drivers, adds them to the project through `QgsProject.instance().addMapLayers`, and enables a retro canvas style by setting `iface.mapCanvas().setProperty("retro", True)` before refreshing. The example demonstrates procedural map composition from built-in geodata files.

64% match

Gist 56db21b335e25668ff86c2e8359bf3d1

This example visualizes tree inventory data from a CSV file, mapping each tree’s location as a point based on longitude and latitude coordinates. The data includes attributes such as species, planting date, height, and diameter. The implementation uses a VRT file to define the CSV’s geometry, with the QGIS XML configuration specifying the point layer’s symbology and coordinate system. The visualization is rendered through QGIS, leveraging the OGR provider to read the spatial data and display it as a map layer with a single symbol renderer.

Gist 349fc7fda8932252cbcb4ee8a0b605c8

This example tracks the availability and licensing of the French IGN’s BD TOPO® departmental datasets by organizing URLs for both December 2021 and March 2021 releases. It shows a structured index of geographic data files, with each entry linking to a specific departmental Shapefile resource. The visualization uses a data-driven list format, likely rendered with JavaScript’s `fetch` to parse the provided CSV or JSON and display the sorted URLs. It highlights the variation in resource IDs across departments and time periods, emphasizing the dataset’s scope without mapping or spatial rendering.

Gist eb7cd9a65aadb68945adc87e0e8c343d

This example visualizes the tram and metro network of an unnamed city using a TopoJSON topology. It shows routes as geographic paths overlaid on a map, with the data sourced from a gist by JulesBlm. The visualization uses D3.js to load and parse the TopoJSON file, then renders the network through its projection and path generation APIs, displaying the transit lines as connected arcs.

JJulesBlm

Gist 32329a8557135f11cb5656e3bfd4d35c

A WebGL map visualizes the locations of French tobacco shops, using points to show their distribution. The code geocodes addresses from an official customs dataset via the data.gouv.fr API, then processes the CSV with the `requests` library. It uses a Vue.js front-end to render the points in a 3D space, allowing users to explore the spatial patterns of the shops.

Gist c8b3e33ae90180e985646e1ef4876dfe

This example demonstrates how to convert tabular JSON data containing longitude and latitude fields into a GeoJSON FeatureCollection using the command-line tool jq, making it ready for map-based visualization. The dataset covers digital mediation locations in the Auvergne-Rhône-Alpes region of France, sourced from data.gouv.fr. The transformation maps each original record into a GeoJSON Feature, preserving properties like name, address, services, and accessibility conditions, while constructing Point geometry from the coordinate pair. The code includes a preview image showing the resulting spatial distribution of these locations, though the visualization itself uses no specific JavaScript mapping library or framework beyond the jq conversion process.

61% match

Gist 28a1d2e30c530c6a170ff5f68798b235

This example curates a set of GeoJSON-based specifications and extensions, organizing them by how they add keys, use multiple files, or serialize for streaming. It lists linked resources such as geojson-t, geocodejson-spec, geojson-ld, and the OGC Features API, alongside STAC and Mapbox simplestyle. It also covers the IMDF format for indoor data and the GeoJSON Text Sequences proposal, presenting a structured reference rather than a rendered map or interactive chart, with no code libraries or visualization APIs involved.

61% match