md`# 2019 Yield of crop
bushel per acre`
d3 = require("d3@5")
import {legend} from "@d3/color-legend"
simple = require("simple-statistics@7.0.7/dist/simple-statistics.min.js")
format = d => `${d}%`
topojson = require("topojson-client@3")
iowacount = FileAttachment("countiesandcropiowa.json").json()
counties = topojson.feature(iowacount, iowacount.objects.countiesandcropiowa)
csv_data = d3.csvParse(await FileAttachment("iowacropcountjoin.csv").text(),({NAME, cropdatano__Yield_2019}) => [NAME, [+cropdatano__Yield_2019]])
//0=>d3.color("black")
data = Object.assign(new Map(csv_data), {title: "Bushels per Acre"})
//Array(99).filter(d => d==0)
//Array(99).filter(d=>0)
//Yield_2019.object.array(99).filter(d => d==0)
//Yieldthisone=domain[d3.min(50),d3.max(300)]
Yield_2019 = Array.from(csv_data.values(), d => d[1][0])
YlGnBu = [d3.color("#ffffcc"), d3.color("#a1dab4"), d3.color("#41b6c4"), d3.color("#2c7fb8"),d3.color("#253494")]
naturalbreaks = simple.ckmeans(Yield_2019, YlGnBu.length).map(v => v.pop())
//more information on sequential scales: https://observablehq.com/@d3/sequential-scales
//color = d3.scaleSequentialQuantile([...data.values()], d3.interpolateBlues)
//color = d3.scaleQuantile()
//.domain(Yield_2019)
//.range(["#ffffcc","#a1dab4","#41b6c4","#2c7fb8","#253494"])
color = d3.scaleThreshold()
.domain(naturalbreaks)
.range(YlGnBu)
//color= d3.scaleQuantize()
//.domain(["])
//.range(["#ffffcc", "#cbc9e2", "#9e9ac8","#756bb1","#54278f"])
width = 975
height = 610
margin = 100
//Rotate the map sets the longitude of origin for our UTM Zone 15N projection.
projection = d3.geoTransverseMercator().rotate([94,0]).fitExtent([[80, 80], [width, height]], counties);
//d3 reference for projections: https://github.com/d3/d3-geo/blob/master/README.md
//use the following url for specific projection settings: https://github.com/veltman/d3-stateplane
//Use this code to set up the map projection (if different than geographic projection)
//projection = d3.geoAlbers().fitExtent([[margin, margin], [width - margin, height - margin]], counties)
//projection = d3.geoMercator().fitExtent([[margin, margin], [width - margin, height - margin]], counties)
//Using a path generator to project geometry onto the map
path = d3.geoPath().projection(projection);
choropleth = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height]);
svg.append("g")
.attr("transform", "translate(360,20)")
.append(() =>
legend({
color: color,
title: data.title,
width: 260,
tickFormat: ".1f"
})
);
svg.append("g")
.selectAll("path")
.data(counties.features)
.join("path")
.attr("stroke", "white")
.attr("stroke-linejoin", "round")
.attr("stroke-width", 1)
// .attr("fill", function(d){
// console.log(color(data.get(d.properties.FIPS)[0]))
// return color(data.get(d.properties.FIPS)[0]);
// })
.attr("fill", d => color(data.get(d.properties.NAME)[0]))
.attr("d", path)
.append("title")
.text(d => " Yield: " + data.get(d.properties.NAME));
svg.selectAll(".subunit-label")
.data(counties.features)
.enter().append("text")
.attr("class", function(d) { return "subunit-label " + d.id; })
.attr("transform", function(d) { return "translate(" + path.centroid(d) + ")"; })
.attr("fill", "black")
.attr("fill-opacity", "1")
.attr("font-size", "15px")
.attr("font-weight", "300")
.attr("text-anchor", "middle")
.text(function(d) { return d.properties.NAME; })
return svg.node();
}
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