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md`# Nigeria household survey`
d3 = require('d3@5')
d3.range(3,10)
genders = {
return {1: "Male", 2: "Female", "": "Sysmiss"}
}
postHarvestDemographics = rawDemographics.filter(d => d.gender !== 'Sysmiss')
rawDemographicsWave3 = {
const data = d3.csvParse(await FileAttachment("sect1_harvestw3.csv").text());
return data.map(mapPostHarvestDemographics(stillInHouseholdProperty.wave3))
.filter(d => stillInHousehold(d) && removeOutliers(d))
}
stillInHouseholdProperty = {return {wave4: "s1q4a", wave2: "s1q14", wave3: 's1q4a', wave1:'s1q19'}}
ruralHousehold.sort((a,b) => a.numberInHousehold - b.numberInHousehold)
stillInHousehold = d => d.stillInHousehold
removeOutliers = d => d.age <= 100
ruralHousehold = householdData.filter(d => d.sector === "Rural")
urbanHousehold = householdData.filter(d => d.sector === "Urban")
sectors = ["", "Urban", "Rural"]
zones = ["", "North Central", "North East", "North West", "South East", "South South", "South West"]
import {vl} from '@vega/vega-lite-api'
histogram(rawDemographicsWave1, {...histogramOptions, xAxisLabel: "Age wave 1"}).width(700).render()
histogram(rawDemographicsWave2, {...histogramOptions, colorField: 'gender', xAxisLabel: "Age wave 2", colorScale: {range: ["red", 'orange']}}).width(700).render()
histogram(rawDemographicsWave3, {...histogramOptions, xAxisLabel: "Age wave 3", markX: 93}).width(700).render()
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.
