Locations of Datavis 2020 Students First Pass- my work
This visualization displays the approximate global locations of Datavis 2020 students based on their self-reported introductions in a Slack channel, with points representing centroids for broader regions. It uses a natural Earth projection via `d3.geoNaturalEarth1` and renders world landmasses, graticules, and interior boundaries using `d3.geoPath` within an SVG. City coordinates are geocoded and parsed from a CSV string using `d3.csvParse` and plotted as green circles, with styling defined in CSS for map elements and a title overlay. The world atlas data is fetched from a remote JSON file and processed with the `topojson` library.
AI-generated descriptionThis map shows approximate locations of the students who joined Datavis 2020 in its first few days.
The list of locations was compiled by manually going through the places mentioned by students in their introductions in our Slack channel #datavis-2020 in the D3 Slack Group. These are the locations where the students are actually located physically.
Each location mentioned was geocoded using Google (example Kansas City longitude and latitude and entered into the code here in useCities.js.
The locations mentioned range from countries to states to particular cities. For regions like countries or states, the point represents its centroid. Locations are by no means exact, but the point of this viz is to give a sense of the global distribution of students.