Visiting Research at NYU Shanghai; previously @ Nest, Apple, AOL; faculty @ Olin College, NYU Shanghai.
plotDistricts(districtDayCommunityInfections, dateRange)
plotDistricts(highRiskAreas, dateRange, {
includeTotal: false,
yLabel: "Areas"
})
function plotDistricts(data, dateRange, options = {}) {
options = { yLabel: "Infections", includeTotal: true, ...options };
data = filterRange(data, dateRange);
const yMax = _.max(data.map((d) => d.infections));
// const latestCaseCounts = Object.fromEntries(
// districtNames.map((name) => [
// name,
// d3.greatest(
// data.filter((d) => d.district === name),
// (d) => d.date
// ).infections
// ])
// );
function memoize(fn) {
const cache = new Map();
return (arg) => {
if (cache.has(arg)) return cache.get(arg);
const value = fn(arg);
cache.set(arg, value);
return value;
};
}
const districtInfections = memoize((name) => {
return _.sum(
data.filter((d) => d.district === name).map((d) => d.infections)
);
});
// remove distrincts that don't have any infections
data = data.filter((d) => districtInfections(d.district) > 0);
const dNames = districtNames; //d3.sort(d3.group(data, (d) => d.district).keys());
// add indices, for faceting
const cols = Math.ceil(Math.sqrt(dNames.length));
data = data.map((d) => ({
...d,
index: dNames.indexOf(d.district)
}));
return Plot.plot({
grid: true,
width,
height: 600,
marginBottom: 80,
color: {
// range: ["#282", "#c22"],
// range: ["green", "orange", "red"],
range: ["orange", "red"],
interpolate: "hcl"
},
facet: {
data,
x: (d) => " ".repeat(d.index % cols),
y: (d) => " ".repeat(Math.floor(d.index / cols))
},
x: {
label: "Date",
// tickFormat: "%B %-d",
ticks: 10,
tickRotate: 45
// type: "utc"
},
y: {
label: options.yLabel,
tickFormat: ".0f"
},
marks: [
Plot.frame(),
Plot.areaY(data, {
x: "date",
y: "infections",
curve: "step-before",
fill: (d) => districtInfections(d.district)
}),
// Plot.lineY(data, {
// x: "date",
// y: "infections",
// curve: "step-before",
// stroke: "black"
// }),
Plot.text(data, {
text: (d) =>
options.includeTotal && districtInfections(d.district)
? `${d.district} (${districtInfections(d.district)})`
: d.district,
fontSize: 18,
y: yMax * 0.85
})
]
});
}
dateRange = ({
start: new Date("July 1, 2022"),
end: new Date("July 31, 2022")
})
function filterRange(data, dateRange) {
if (dateRange) {
data = data.filter(({ date }) => date >= dateRange.start);
data = data.filter(({ date }) => date <= dateRange.end);
}
return data;
}
districtDayCommunityInfections = ungroupCsv(
"https://docs.google.com/spreadsheets/d/e/2PACX-1vQn1YeYbOv31SCzJs0RlpXETOOKNO4HTn0F5eYT9w_teus0UXKBIxxfJshTuXL9QENK_e5qo2RGPoqZ/pub?output=csv"
)
async function ungroupCsv(url) {
const text = await (await fetch(url)).text();
return (
d3
.csvParse(text, (d) =>
d3.autoType(
// Remove commas
Object.fromEntries(
Object.entries(d).map(([k, v]) => [k, v.replace(/,/g, "")])
)
)
)
// Construct Dates from date strings
.map(({ Date: date, ...districts }) => ({
date: new Date(date + ", 2022"),
...districts
}))
// Subtract one day from each date, in order to translate report dates into infection dates
// .map(({ date, ...districts }) => ({
// date: new Date(date.getTime() - 86400000),
// ...districts
// }))
// The CSV is grouped by date. Ungroup it.
.flatMap(({ date, ...districts }) =>
Object.entries(districts).map(([district, infections]) => ({
date,
district,
infections
}))
)
);
}
districtDayInfections = ungroupCsv(
"https://docs.google.com/spreadsheets/d/e/2PACX-1vSbmGMVrwaU3z6VSi1mN1C4aYjHf49yPnyaYUtw_qNn84yEh0ZgkJmPqLKTkiFrPcpRpcm7p0Q989IB/pub?gid=0&single=true&output=csv"
)
highRiskAreas = {
const data = await ungroupCsv(
"https://docs.google.com/spreadsheets/d/e/2PACX-1vRdldpYPJ-Y0wmnWbZ1PmOdx_Txp5SYovsKzgvkof8bAL_RnOCtDPeMD3aoLSvti9-Ka4DsfEGqxTs5/pub?output=csv",
"areas",
0
);
return data;
// return data.map(({date, district,) => d);
}
mostRecentDate = d3.timeFormat("%b %-d")(
d3.max(districtDayInfections.map((d) => d.date))
)
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