The avatar for @lifewinning
Ingrid Burrington
Feral
Public
Edited
Sep 12, 2024
2 stars
3
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Inputs.table(toptracts)
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Inputs.table(tops)
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Inputs.table(udpnyc_by_type)
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highest = udpnyc.features.filter((f) => f.properties.soylent2020 > 5)
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mhi_a_tops = highest
.filter(
(h) => h.properties.typology_origin == "MHI - Advanced Gentrification"
)
.map((m) => m.properties)
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mhi_r_tops = highest
.filter((h) => h.properties.typology_origin == "MHI - At Risk of Exclusion")
.map((m) => m.properties)
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tops = mhi_a_tops.concat(mhi_r_tops).sort((s) => s.soylent20).map(m => {return {
type: m.typology_origin,
soylent2020: m.soylent2020,
bodega2020: m.soylent2020_bodega,
soylent2021: m.soylent2021,
neighborhood: m.municipali
};})
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average = (array) => array.reduce((a, b) => a + b) / array.length
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vendorRegression(udpnyc_by_type)
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percentsRegression = reg
.regressionLinear()
.x((d) => d.percent_soylent_20)
.y((d) => d.percent_soylent_21)
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percentsRegression(udpnyc_by_type_nooutlier)
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percentsRegression(udpnyc_by_type)
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colors2020 = d3.quantize(d3.interpolateViridis, 6)
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L = require("leaflet@1.2.0")
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RegPlot = addRegression(Plot_)
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reg = require("d3-regression@1")
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import { Plot as Plot_ } from "@fil/plot-splom"
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udpnyc = FileAttachment("udpnyc-soylentcounts.geojson").json()
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soylent20 = FileAttachment("soylent2020-categorized.geojson").json()
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soylent21 = FileAttachment("soylent-2021.geojson").json()
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