Published
Edited
Jun 26, 2020
d3 = require("d3@5")
margin = ({top: 20, right: 20, bottom: 35, left: 40})
y = d3.scaleLinear([1000, 11000], [height - margin.bottom, margin.top])
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x))//.ticks(width / 80, ","))
.call(g => g.select(".domain").remove())
.call(g => g.append("text")
.attr("x", width)
.attr("y", margin.bottom - 4)
.attr("fill", "currentColor")
.attr("text-anchor", "end")
.text("Total confirmed cases of COVID-19 per 100000 people→"))
yAxis = g => g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y))
.call(g => g.select(".domain").remove())
.call(g => g.append("text")
.attr("x", -margin.left)
.attr("y", 10)
.attr("fill", "currentColor")
.attr("text-anchor", "start")
.text("↑ Tests per 100000 people"))
grid = g => g
.attr("stroke", "currentColor")
.attr("stroke-opacity", 0.1)
.call(g => g.append("g")
.selectAll("line")
.data(x.ticks())
.join("line")
.attr("x1", d => 0.5 + x(d))
.attr("x2", d => 0.5 + x(d))
.attr("y1", margin.top)
.attr("y2", height - margin.bottom))
.call(g => g.append("g")
.selectAll("line")
.data(y.ticks())
.join("line")
.attr("y1", d => 0.5 + y(d))
.attr("y2", d => 0.5 + y(d))
.attr("x1", margin.left)
.attr("x2", width - margin.right));
radius = d3.scaleSqrt([0, 5e8], [0, width / 6])
color = d3.scaleOrdinal(jsondata.map(d => d.region), d3.schemeCategory10).unknown("black")
bisectYear = d3.bisector(([year]) => year).left
function valueAt(values, year) {
const i = bisectYear(values, year, 0, values.length - 1);
const a = values[i];
if (i > 0) {
const b = values[i - 1];
const t = (year - a[0]) / (b[0] - a[0]);
return a[1] * (1 - t) + b[1] * t;
}
return a[1];
}
import {Scrubber} from "@mbostock/scrubber"
formatDate = d3.utcFormat("%Y")
function dataAt(year) {
return jsondata.map(d => ({
name: d.name,
region: d.region,
totpop:d.totpop,
pos_pop_100k: valueAt(d.pos_pop_100k, year),
population: valueAt(d.population, year),
ct_pop_100k: valueAt(d.ct_pop_100k, year),
tamp_pop_100k: valueAt(d.tamp_pop_100k, year)
}));
}
names = new Set(jsondata.map(d => d.name))
jdates = new Set(jsondata.map(d => d.jdate))
getdates=function(csvdoc){
var nested = d3.nest()
.key(function(d){ return d.justdata; })
.entries(csvdoc)
var dates = nested.map(function(d){
var dates_record = new Date(d.key);
// this is the variable that we grouped by
// dates_record.jdate = d.key;
//dates_record.justdata = d.values.map(function(c){ return [c.justdata]; });
return dates_record;
});
return dates;
}
mydates=getdates(data2)
csvtojson=function(csvdoc){
var nested = d3.nest()
.key(function(d){ return d.denominazione_regione; })
.entries(csvdoc)
var json = nested.map(function(d){
var namerecord = {};
// this is the variable that we grouped by
namerecord.name = d.key;
// this is another variable that I happen to know is constant for all
// years within a given "name", so I'll just grab the first value
namerecord.region = d.values[0].denominazione_regione;
namerecord.totpop = d.values[0]['Maschi + Femmine'];
// these are the time-series variables
// use a "map" to grab the year and amount from each of the child "values"
//namerecord.totale_casi = d.values.map(function(c){ var x=d3.autoType({date: c.justdata}); return [new Date(c.justdata), +c.totale_casi]; });
namerecord.totale_casi = d.values.map(function(c){ return [new Date(c.justdata), +c.totale_casi]; });
namerecord.tamponi = d.values.map(function(c){ return [new Date(c.justdata), +c.tamponi]; });
namerecord.population = d.values.map(function(c){ return [new Date(c.justdata), +c['Maschi + Femmine']]; });
namerecord.pos_pop_100k = d.values.map(function(c){ return [new Date(c.justdata), +c.pos_pop_100k]; });
namerecord.tamp_pop_100k = d.values.map(function(c){ return [new Date(c.justdata), +c.tamp_pop_100k]; });
namerecord.ct_pop_100k= d.values.map(function(c){ return [new Date(c.justdata), +c.ct_pop_100k]; });
return namerecord;
});
return json;
}
jsondata=csvtojson(data2)
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