employment = FileAttachment("e.csv").csv()
bins2 = d3.bin().domain([0,100]).thresholds(20)(occupazioneFemmine.map(d => d.value))
occupazioneTotale = data.filter(d => d.Sesso === 'totale').map(d => ({...d, value: +d.Value}))
occupazioneMaschi = data.filter(d => d.Sesso === 'maschi').map(d => ({...d, value: +d.Value}))
occupazioneFemmine = data.filter(d => d.Sesso === 'femmine').map(d => ({...d, value: +d.Value}))
splitByArea = ({
nord: getBins(data.filter(d => d.ITTER107.startsWith('ITF') || d.ITTER107.startsWith('ITD'))),
centro: getBins(data.filter(d => d.ITTER107.startsWith('ITE'))),
sud: getBins(data.filter(d => d.ITTER107.startsWith('ITF'))),
sudEIsole: getBins(data.filter(d => d.ITTER107.startsWith('ITG'))),
})
getBins = (data, thresholds = 10) => d3.bin().domain([20,70]).thresholds(thresholds)(data.filter(d => d.Sesso === 'totale').map(d => +d.Value))
data=FileAttachment("DCCV_TAXOCCU1_21012022151601966.csv").csv({typed: true})
d3 = require('d3')
colors
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
