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useCities.js
import { useState, useEffect } from 'react';
import { csvParse } from 'd3';

const csv = `name,lat,lng
Oregon,43.8,-120.55
Georgia,32.1,-82.9
Chicago,41.88,-87.63
Kansas City,39.0997,-94.5786
Cincinnati,39.1031,-84.5120
Wisconsin,43.7844,-88.7879
Utah,39.3210,-111.0937
California,36.7783,-119.4179
India,20.5937,78.9629
Paris,48.8566,2.3522
Russia,61.5240,105.3188
Peru,-9.1900,-75.0152
Brazil,-14.2350,-51.9253
Canada,56.1304,-106.3468
México,23.6345,-102.5528
Australia,-25.2744,133.7751
Switzerland,46.8182,8.2275
China,35.8617,104.1954
Japan,36.2048,138.2529
Trinidad and Tobago,10.6918,-61.2225`;

export const data = csvParse(csv, d => {
d.lat = +d.lat;
d.lng = +d.lng;
return d;
});

Locations of Datavis 2020 Students First Pass

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Curran Kelleher

Last edited Jan 07, 2020
Created on Jan 03, 2020

This 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.

MIT Licensed