cpi = (await FileAttachment("CPIAUCSL.csv").csv({ typed: true })).map((d) => ({
date: d.DATE,
value: d.CPIAUCSL
}))
cpiMap = d3.rollup(
cpi.filter(inBounds),
(arr) => arr[0].value, // or should it average the months?
(d) => d3.utcYear.floor(d.date)
)
boxoffice = (
await FileAttachment("Box Office Gross - box office.csv").csv({ typed: true })
).map((d) => ({
date: new Date(Date.UTC(d.year, 0, 1)),
value: d.total_gross
}))
boxofficeAdjusted = boxoffice.map(({ date, value }) => ({
date,
value: real ? value / (cpiMap.get(date) / index) : value
}))
ticks = d3.range(...valueExtent, 1e9)
adjustedTicks = real
? d3.range(
0,
valueExtent[1] ** 2 /
d3.min(
cpi
.filter(inBounds)
.map((d) => valueExtent[1] / (d.value / indexStart))
),
1e9
)
: ticks
gridlines = cpi
.filter(inBounds)
.flatMap((d) =>
adjustedTicks.map((tick) => ({
date: d.date,
value: real
? tick / (d.value / indexStart)
: tick * (d.value / indexStart),
tick
}))
)
.filter((d) => d.value <= valueExtent[1])
index = cpiMap.get(new Date(Date.UTC(year, 0, 1)))
indexStart = cpiMap.get(dateExtent[0])
dateExtent = d3.extent(boxoffice, d => d.date)
valueExtent = [0, d3.max(boxoffice, d => d.value)]
inBounds = d => d.date >= dateExtent[0] && d.date <= dateExtent[1]
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