Public
Edited
Nov 3, 2022
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x = columns.map(c => d3.scaleLinear()
.domain(d3.extent(data, d => d[c]))
.rangeRound([padding / 2, size - padding / 2]))
y = x.map(x => x.copy().range([size - padding / 2, padding / 2]))
z = d3.scaleOrdinal()
.domain(['Black', 'Hispanic', 'White'])
.range(d3.schemeCategory10)
xAxis = {
const axis = d3.axisBottom()
.ticks(6)
.tickSize(size * columns.length);
return g => g.selectAll("g").data(x).join("g")
.attr("transform", (d, i) => `translate(${i * size},0)`)
.each(function(d) { return d3.select(this).call(axis.scale(d)); })
.call(g => g.select(".domain").remove())
.call(g => g.selectAll(".tick line").attr("stroke", "#ddd"));
}
yAxis = {
const axis = d3.axisLeft()
.ticks(6)
.tickSize(-size * columns.length);
return g => g.selectAll("g").data(y).join("g")
.attr("transform", (d, i) => `translate(0,${i * size})`)
.each(function(d) { return d3.select(this).call(axis.scale(d)); })
.call(g => g.select(".domain").remove())
.call(g => g.selectAll(".tick line").attr("stroke", "#ddd"));
}
data = d3.csvParse(await FileAttachment("district_filtered_data.csv").text(), d3.autoType)
columns = ["district_misconduct_rate", "police_male", "police_nonwhite"]
width = 954
size = (width - (columns.length + 1) * padding) / columns.length + padding
padding = 30
d3 = require("d3@6")
import {swatches} from "@d3/color-legend"
district_filtered_data.csv
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