import { tidy, mutate, arrange, desc } from '@pbeshai/tidyjs'
ACS_NYCHA.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
myACS = tidy(acs_nycha,
mutate({ pUnder15: d => d.pop5t9P + d.pop10t14P + d.popu5P,
p15to24: d => d.pop15t19P + d.pop20t24P,
p25to60: d => d.pop25t29P + d.pop30t34P + d.pop35t39P + d.pop40t44P +d.pop45t49P + d.pop50t54P + d.pop55t59P,
pOver60: d => d.pop60t64P + d.pop65t69P + d.pop70t74P + d.pop75t79P + d.pop80t84P + d.pop85plP,
devCosts: d => Number(d['DEVELOPMENT COST'].replace(/[$,]/g, '')),
amgRent: d => Number(d['AVG MONTHLY GROSS RENT'].replace(/[$,]/g, '')),
unbuiltArea: d=> Number(d['CUBAGE CU FT'].replace(/[$,]/g, '')) - Number(d['BLDG COVERAGE SQ FT'].replace(/[$,]/g, '')),
ages: d=> [d.pUnder15, d.p15to24, d.p25to60, d.pOver60]}
))
Plot.dot(myACS, {
y: "p25to60",
x: "unbuiltArea",
fill: (d) => d['AVG MONTHLY GROSS RENT']
}).plot({
color: { scheme: "reds" }
})
// Your code here
// Your code here
Plot.rect(myACS, Plot.bin({fillOpacity: "count"}, {x: "p25to60", y: "unbuiltArea"})).plot()
Plot.plot({
color: {
scheme: "bupu",
},
marks: [
Plot.rectY(
myACS,
Plot.binX(
{ y: "count" },
{
x: "p15to24",
fill: "BOROUGH",
fillOpacity: 1,
thresholds: 10
}
)
)
]
})
myACS[0].BOROUGH
Plot.plot({
color: {
scheme: "bupu",
},
marks: [
Plot.rectY(
myACS.filter(d=>d.BOROUGH == "BROOKLYN"),
Plot.binX(
{ y: "count" },
{
x: "p15to24",
fill: "BOROUGH",
fillOpacity: 1,
thresholds: 10
}
)
)
]
})
ages = myACS.columns
facetAge = {
const ages = myACS.slice(1); // convert wide data to tidy data
return Object.assign(ages.flatMap(x => myACS.map(d=> [d.pUnder15, d.p15to24, d.p25to60, d.pOver60])))
}
Plot.plot({
x: {insetRight: 10},
y: {grid: true},
color: {
// domain: myACS.ages,
scheme: "spectral"
},
facet: {
data: "ages",
x: "count"
},
marks: [
Plot.barX(myACS, Plot.groupY({x: "count"}, {fy: ages, y: "BOROUGH", fill: "ages"})),
]
})
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