Data Visualization Developer at The Associated Press
Public
Edited
Jan 5, 2024
function color(d) {
const neutrals = ['lightgrey', 'grey', 'black']
const primary = [ '#C2E778', '#A8D555', '#6C9715']
const fillColor = (type, arr) => type === 'wages' ? arr[0] : type === 'retirement' ? arr[1] : arr[2]
return d.decile === selectedSegment ? fillColor(d.type, primary) : fillColor(d.type, neutrals)
}
Select a data source…
Type Chart, then Shift-Enter. Ctrl-space for more options.
fig3_data@3.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
chartData = incomeData.map(d => ({
income: format(d.wages + d.investments + d.retirement ),
CO2: format(d.CO2_wages + d.CO2_investments + d.CO2_retirement),
investments: format(d.investments),
retirement: format(d.retirement),
CO2_investments: format(d.CO2_investments),
CO2_retirement: format(d.CO2_retirement),
wages: format(d.wages),
CO2_wages: format(d.CO2_wages)
}) )
.sort((a, b) => a.income - b.income)
.filter(d => d.income > 0)
format = (n) => +(n).toFixed(5)
thresholds = d3.range(thresholdIncrement, 1 + thresholdIncrement, thresholdIncrement).map(d => +(d).toFixed(2))
indeces = [0, ...thresholds.map(x => d3.quantileIndex(chartData.map(d => d.income), x))]
sumData = {
const results = []
for (let i = 1; i < indeces.length; i++) {
const slice = chartData.slice(indeces[i - 1], indeces[i])
const sumInvest = d3.sum(slice, d => d.CO2_investments)
const sumRetirement = d3.sum(slice, d => d.CO2_retirement)
const sumWages = d3.sum(slice, d => d.CO2_wages)
results.push({decile: +(i * thresholdIncrement).toFixed(2), investments: sumInvest, retirement: sumRetirement, wages: sumWages })
}
return results
}
mekkoData = {
const results = []
sumData.forEach(d => {
results.push([{decile: d.decile, type: 'investments', CO2: +d.investments.toFixed(5) },
{decile: d.decile, type: 'retirement', CO2: +d.retirement.toFixed(5) },
{decile: d.decile, type: 'wages', CO2: +d.wages.toFixed(5) } ])
})
return results.flat(2)
}
function floor(n) {
const pct = Math.round(n * 100)
return pct % 2 === 0 ? n : +(n + .01).toFixed(2)
}
floor(.17)
percentile = (arr, val) => {
let count = 0;
arr.forEach(v => {
if (v < val) {
count++;
} else if (v == val) {
count += 0.5;
}
});
return 100 * count / arr.length;
}
import {marimekko} from '@observablehq/plot-marimekko'
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.