Public
Edited
Sep 8, 2023
Paused
Plot.plot({
y: { grid: true, nice: true },
marks: [
Plot.dot(proportion_low_income, {
x: (d) => new Date(d.year.toString()),
y: "proportion",
tip: true
}),
Plot.line(
proportion_low_income,
Plot.regression({
x: (d) => new Date(d.year.toString()),
y: "proportion",
type: "LOESS",
bandwidth: 0.5,
order: 2
})
)
]
})
proportion_low_income = d3
.flatGroup(pums, (d) => d.year)
.map(([year, data]) => {
const total = d3.sum(data.map((d) => d.PWGTP));
const low_income_threshold =
federal_poverty_levels.find((d) => d.year === year).fourPerson * 1.85;
return {
year,
proportion:
d3.sum(
data.filter((d) => d.FINCP < low_income_threshold).map((d) => d.PWGTP)
) / total
};
})
federal_poverty_levels = [
{ year: 2021, fourPerson: 26500 },
{ year: 2020, fourPerson: 26200 },
{ year: 2019, fourPerson: 25750 },
{ year: 2018, fourPerson: 25100 },
{ year: 2017, fourPerson: 24600 },
{ year: 2016, fourPerson: 24300 },
{ year: 2015, fourPerson: 24250 },
{ year: 2014, fourPerson: 23850 },
{ year: 2013, fourPerson: 23550 },
{ year: 2012, fourPerson: 23050 },
{ year: 2011, fourPerson: 22350 },
{ year: 2010, fourPerson: 22050 },
{ year: 2009, fourPerson: 22050 },
{ year: 2008, fourPerson: 21200 },
{ year: 2007, fourPerson: 20650 },
{ year: 2006, fourPerson: 20000 }
]
pums = {
const data = await Promise.all(
d3
.range(2006, 2022)
.filter((year) => year !== 2020)
.map((year) =>
chicago_pums_one_year(["AGEP", "FINCP", "SCH", "SCHG", "PWGTP"], year, {
SCH: 2,
SCHG: year < 2008 ? "1:5" : "1:14"
})
)
);
return data.flat().filter((d) => d.FINCP !== -60000);
}
import { chicago_pums_one_year } from "@fgregg/chicago-pums-helper"
import { Plot } from "@fil/plot-regression"
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