currentData = dataAt(year)
x = d3.scaleLog([2, 1e5], [margin.left, width - margin.right])
fy = function(range){return d3.scaleLinear(range, [height - margin.bottom, margin.top])}
radius = d3.scaleSqrt([0, 5e8], [0, width / 30])
colorscale = d3.scaleOrdinal([1, 2, 3, 4], d3.schemeCategory10)
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x).ticks(width / 80, ","))
.call(g => g.select(".domain").remove())
.call(g => g.append("text")
.attr("x", width)
.attr("y", margin.bottom - 4)
.attr("fill", "currentColor")
.attr("text-anchor", "end")
.text("Government revenue per capita (USD) →"))
fyAxis = function(ay, annotation){
return g => g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(ay))
.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(annotation))}
fgrid = function(ay){
return 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(ay.ticks())
.join("line")
.attr("y1", d => 0.5 + ay(d))
.attr("y2", d => 0.5 + ay(d))
.attr("x1", margin.left)
.attr("x2", width - margin.right));}
function labelText(d, quantity){
return [d.name, "population: " + d3.format(",.9r")(d.population),
"gov. rev. per cap. : $" + d3.format(",.5r")(d.govRevCap),
quantity + ": " + d[quantity].toFixed(2)].join("\n");
}
margin = ({top: 20, right: 20, bottom: 35, left: 40})
height = 560
d3 = require("d3@5")
import {Scrubber} from "@mbostock/scrubber"
data = d3.csvParse(await FileAttachment("lives saved data.csv").text())
countriesnested = d3.nest()
.key(function(d) { return d.YEAR; })
.entries(data);
countries = d3.nest()
.key(function(d) { return d.COUNTRY; })
.entries(data)
.map(d => d.key)
//.filter(d => d.length > 0)
.sort()
mapped = countriesnested.map( function(d){
var obd = {year : +d.key,
data : d.values.map( function(e){
var obe = {
year : +d.key,
name: e.COUNTRY,
iso : e.ISO,
id : +e.ID,
economy : +e.INCOME,
population : +e.POPULATION,
govRevCap : +e.GOVREVPERCAP,
u5deaths : +e.U5DEATHS,
u5Pop : +e.U5POP,
births : +e.BIRTHS,
matdeaths : +e.MATDEATHS,
mortality : +e.U5MORTALITY,
matMortality : +e.MATMORTALITY}
return obe;
})}
return obd;
; })
function recomputedata(d){
var e = { ...d }
var computed = computeResult(e, "mortality");
e.mortality = computed[0];
var computed2 = computeResult(e, "matMortality");
e.matmortality = computed2[0];
var computedRev = getRevenue(d);
e.govRevCap = computedRev[3];
return e;
}
dataAt = function(year){
var res = mapped.filter(function(d) {return d.year == year})
if (res.length > 0)
{
var data2 = res[0].data.map(function(d){return recomputedata(d);})
return data2;
}
}
test = dataAt(1999)[20]
computeResult(test, "mortality")
function getRevenue(d)
{
var newAbsRev = (d.govRevCap * (govRevenue)) * d.population;
var additionalPerCapita = d.govRevCap * govRevenue;
var newPerCapita = d.govRevCap + additionalPerCapita;
return [govRevenue, newAbsRev, additionalPerCapita, newPerCapita];
}
betaU5M = 1472;
betaMMR = 576.6;
function computeResult(d, type)
{
// returns [improved outome, lives saved, original outome]
var computedRevenue = getRevenue(d);
var increase = computedRevenue[0];
if (type == "mortality")
{
if (d.mortality > 0)
{
var effectOnU5m = 0;
if (d.govRevCap > 0 )
{
effectOnU5m = Math.min(betaU5M / d.govRevCap * increase, d.mortality)
}
var livesSaved = effectOnU5m * d.u5Pop / 1000;
var u5m = d.mortality - effectOnU5m;
return [u5m, d.govRevCap > 0 ? livesSaved : NaN, +d.mortality];
}
else
return [NaN, NaN, NaN];
}
else if (type == "matMortality" )
{
if (d.matMortality > 0)
{
var effectOnMmr = 0;
if ( d.govRevCap > 0 )
{
effectOnMmr = Math.min(betaMMR / Math.pow(Math.log(d.govRevCap), 2.0) * increase, d.matMortality);
}
var livesSaved = effectOnMmr * d.BIRTHS / 100000;
var mmr = d.matMortality - effectOnMmr;
return [mmr, d.govRevCap > 0 ? livesSaved : NaN, +d.matMortality];
}
else
{
return [NaN, NaN, NaN]
}
}
else if(type == "PScompletion")
{
}
else if(type == "Immunisation")
{
}
}
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
