The avatar for @philipnelson
Philip Nelson
public servant data scientist (work and opinions here are my own)
Published
Edited
Sep 27, 2021
2 stars
5
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(2500.5234)
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color = d3.scaleOrdinal(d3.schemeTableau10)
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Type JavaScript, then Shift-Enter. Ctrl-space for more options. Arrow ↑/↓ to switch modes.

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H = width * 1 / 3
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path = d3.geoPath().projection(testprojection)
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counties = topojson.feature(sc, sc.objects.counties)
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testprojection = d3.geoIdentity()
.reflectY(true)
.fitSize([width, width * 1/3], counties)
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code = {
if(divisions=="counties" && place!=null)
return place.COUNTYFP
else if (place!= null)
return place.COUSUBFP
else
return null
}
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statedata = [JSON.parse('{"Total_2010": 4625364, "White_2010": 3060000, "Black_2010": 1290684, "AAIAN_2010": 19524, "Asian_2010": 59051, "NHPI_2010": 2706, "Other_2010": 113464, "Two_or_more_2010": 79935, "Hispanic_2010": 235682, "Total_2020": 5118425, "White_2020": 3243442, "Black_2020": 1280531, "AAIAN_2020": 24303, "Asian_2020": 90466, "NHPI_2020": 3431, "Other_2020": 177876, "Two_or_more_2020": 298376, "Hispanic_2020": 352838, "Other_combi__2010": 135694, "Other_combi__2020": 205610}')]
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place
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data
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mapval = (divisions=="places") ? "COUSUBA" : "COUNTYA"
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pctchangemap = d3.rollup(data, v => d3.sum(v, d => (d.Total_2020-d.Total_2010)/(d.Total_2010)), d => d[mapval])
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Math.max(...pctchangemap.values())
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mapcol = {
if(mapval=="COUNTYA")
return d3.scaleDiverging([-0.4, 0, 0.4], d3.interpolateRdYlGn)
else
return d3.scaleDiverging([-1.5, 0, 1.5], d3.interpolateRdYlGn)
}
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data = {
if (divisions == "places")
return FileAttachment("data@5.csv").csv()
else
return FileAttachment("county_data@4.csv").csv()
}
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countydata=FileAttachment("county_data@4.csv").csv()
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d3 = require("d3@7")
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import { aq, op } from '@uwdata/arquero'
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import {radio, select} from "@jashkenas/inputs"
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topojson = require("topojson-client@3")
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import {ramp} from "@mbostock/color-ramp"
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