Data Visualization Developer at The Associated Press
Public
Edited
Apr 3, 2024
c = d3.scaleOrdinal().domain(bigEmitters).range(['darkorange', 'darksalmon', 'steelblue', 'skyblue', 'pink'])
byOrg = countByGroup('association')
byCompany = countByGroup('company').slice(0, 10)
function countByGroup(category) {
const group = Object.groupBy(lobbyists.filter(d => d.COP >= 14), d => d[category])
return Object.entries(group).map(([key, value]) => {
return {[category]: key, count: value.length}
}).filter(d => d[category] && d[category] !== "NaN")
.sort((a, b) => b.count - a.count)
}
total_cop_attendees.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
total_people.map(d => d.conference.split("COP")[1])
emissions = await FileAttachment("cop28_emissions.csv").csv()
bigEmitters = {
const b = emissions.sort((a,b) => +b.scope_1_2 - +a.scope_1_2).slice(0, 6).map(d => d.Company)
return [...new Set(byYearCompanyAll.filter(d => b.includes(d.company)).map(d => d.company))]
}
import {Swatches} from '@d3/color-legend'
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