34:["$","title",null,{"children":"Mini-Project 2: Temporal Data Visualization (Due Nov. 12th) | Darsh Shani | Observable"}] 3c:Ta99,

[NOTE]

Please make sure to Read ALL instructions carefully for each part of this assignment!

1. Please **fork this notebook** for this mini-project. Ensure that the notebook is made either _public_ or _unlisted_ in the settings. 2. Complete each question to the best of your ability, clearly marking which visualization and/or written answer corresponds to which question asked. 3. Your coded solutions **must use D3**. Other visualization libraries (.e.g Vega-Lite) or other code languages (e.g. Python) are not allowed. - You are allowed to use functions and modules created by other creators. For example, you can use Mike Bostock's Color Legend notebook to create your legends. 4. You are free to modify any datasets mentioned in this project, or introduce new datasets if it helps you with any explanations or visualizations. For datasets originating from this dataset, you are free to modify them in any way as long as 1) the preprocessing is performed here in JavaScript, or 2) you preprocessed the dataset elsewhere (e.g. a Python notebook or Google Colab notebook via Python). - If you modified the dataset elsewhere, **please make sure to explicitly mention in your write-up where and how to access the code; preprocessing the dataset without a way for us to verify will lead to penalties on your score**. - If you are introducing a new dataset from elsewhere, **please make sure to explicitly mention how to access the dataset**. 5. Please adhere to our AI policy for the class, which is provided on our course syllabus: > _... you can use generative AI tools to do the assignments in this class. If you use an AI to guide you in completing an assignment, you must **disclose which parts were generated by the AI**. Remember that you are responsible for any errors or inaccuracies in AI-generated content, and you must be able to explain all submitted work._ 6. Submit the URL of this notebook on Brightspace by the listed due date. ### Submission Details This assignment is due **Nov. 12th @ 11:59pm**. This submission expects a URL to your notebook that is either public or unlisted. Please be aware that we will grade notebooks based on the version of the notebook we receive at the submission deadline. This means that if you decide to modify your notebooks after the deadline, your changes may not be considered while grading. This policy also applies to late submissions as well.3d:Tb68,Your goal is to create **3 independent visualizations of the same datasets**, each one with the intent of answering the questions stated below. For each numbered question, you should be able to 1) create a data visualization that answers **all** of the questions specified, 2) provide a written analysis that extrapolates from your visualization and answers **all** of the questions specified, and 3) provide a written description of your thought process and why you think your solution is *appropriate* and *effective*. These are the 3 visualizations you should create: - **Visualization #1 [25pts]:** 1. How does the amount donated vs. amount received change over time for each country? 2. Are there countries that mostly send or mostly receive and countries that have a similar amount of donations they receive and send? 3. Are there countries that change their role over time? That is, they used to mostly send donations and turn into mostly receiving donations and vice-versa? 4. Are there countries in which you can find a sudden increase ("peak") or a sudden decrease ("valley")? - **Visualization #2 [25pts]:** Focus on the top 10 "Coalesced Purposes" of donations (in terms of amount of disbursement across all countries and all time). What are the top 10 purposes of disbursements (in terms of total amount of disbursement) and how does their relative amount compare over time? E.g., are there purposes that tend to be prominent for a period of time and others that become more prominent during other periods? - **[Hint]**: looking at the graph one should be able to observe: “Ah! During these years donations were mostly about X but then there were way more donations about Y”. - **[Note]**: if the purpose is “UNSPECIFIED” it should be removed. - **Visualization #3 [25pts]:** Focusing exclusively on countries that receive donations, how do donations shift geographically over time? Do donations tend to be always in the same regions of the world over the years or they have been shifting over time? Can you build a visualization that shows the "history of donations" so that one can get a sense of which regions of the world have had more need for donations over the years? - **[Note 1]**: for this visualization you can, if you wish, use interaction (but you don’t have to). - **[Note 2]**: For this exercise you may want to review the lecture on geographical visualization in which we explain how you can visualize geographical data over time. - **[Note 3]**: if you want, you can aggregate data over a few years (say, group together data at 5 year intervals).

[NOTE]

It is okay to submit more than one solution for a given visualization problem if you think there are some competing solutions that work well. When you do that, make sure to compare the solutions by commenting on their advantages and disadvantages.

3e:T450,Your answers to each question are graded on the following qualities, with each question totaling up to **25 points**: - **[10pts]**: Does the visualization answer the questions posed in the exercise? - **[10pts]**: Does the written answer & discussion the questions posed in the exercise? - **[5pts]**: Is the visual representation clear? Does it have good aesthetics? If needed, you can review this notebook on clarity for reference. The questions above are a very useful tool for you to verify whether you are producing a good solution or not. As you go about solving this exercise you can use the questions above as an evaluation tool in two main ways: 1. Verify that you can indeed answer the questions with your visualization. If you can’t fully answer the questions, it means your solution has some problems. 2. Compare multiple solutions to the same problem and ask yourself: “which one makes it easier for me to answer these questions?”, where easier may mean, more accurately, with less effort or faster.3f:T90f,// Source: course's reduced AidData CSV, also used in Mini-Project #1. const mp2CsvURL = "https://docs.google.com/spreadsheets/d/1YiuHdfZv_JZ-igOemKJMRaU8dkucfmHxOP6Od3FraW8/gviz/tq?tqx=out:csv"; const mp2Raw = await d3.csv(mp2CsvURL); const mp2Rows = mp2Raw.map(d => { const rawAmount = d.commitment_amount_usd_constant; return { donor: String(d.donor ?? "").trim(), recipient: String(d.recipient ?? "").trim(), year: Number(d.year), amount: rawAmount == null || String(rawAmount).trim() === "" ? NaN : Number(rawAmount), purposeCode: String(d.coalesced_purpose_code ?? "").trim(), purposeName: String(d.coalesced_purpose_name ?? "").trim() }; }).filter(d => d.donor && d.recipient && Number.isInteger(d.year) && Number.isFinite(d.amount)); if (!mp2Rows.length) throw new Error("No valid AidData records loaded. Check the CSV URL and column names."); const mp2MinYear = d3.min(mp2Rows, d => d.year); const mp2MaxYear = d3.max(mp2Rows, d => d.year); const mp2Years = d3.range(mp2MinYear, mp2MaxYear + 1); if (mp2MinYear < 1900 || mp2MaxYear > 2026) throw new Error("Unexpected AidData year range. Check the CSV."); const mp2Countries = Array.from(new Set(mp2Rows.flatMap(d => [d.donor, d.recipient]))).sort(d3.ascending); const mp2Fmt = x => { if (!Number.isFinite(x)) return "n/a"; const a = Math.abs(x), sign = x < 0 ? "−" : ""; const body = a >= 1e12 ? `$${(a / 1e12).toFixed(2)}T` : a >= 1e9 ? `$${(a / 1e9).toFixed(2)}B` : a >= 1e6 ? `$${(a / 1e6).toFixed(1)}M` : a >= 1e3 ? `$${(a / 1e3).toFixed(0)}K` : `$${a.toFixed(0)}`; return sign + body; }; const mp2RoleColor = d3.scaleLinear([-1, 0, 1], ["#d87343", "#edf0f3", "#16649a"]).clamp(true); const mp2Audit = { rawRows: mp2Raw.length, validRows: mp2Rows.length, excludedInvalidRows: mp2Raw.length - mp2Rows.length, numberOfCountries: mp2Countries.length, observedYears: [mp2MinYear, mp2MaxYear], yearsWithRecords: new Set(mp2Rows.map(d => d.year)).size, negativeAdjustmentRows: mp2Rows.filter(d => d.amount < 0).length, selfCountryRowsRetained: mp2Rows.filter(d => d.donor === d.recipient).length, totalCommittedUSD: d3.sum(mp2Rows, d => d.amount), sourceColumns: mp2Raw.columns, uniquePurposeCodes: new Set(mp2Rows.map(d=>d.purposeCode).filter(Boolean)).size }; display(mp2Audit);40:Tfe4,// All year-by-country values come from the same validated commitments. const mp2DonatedMap = d3.rollup(mp2Rows, v => d3.sum(v, d => d.amount), d => d.donor, d => d.year); const mp2ReceivedMap = d3.rollup(mp2Rows, v => d3.sum(v, d => d.amount), d => d.recipient, d => d.year); const mp2ByCountry = new Map(mp2Countries.map(country => [country, mp2Years.map(year => { const donatedExists = mp2DonatedMap.get(country)?.has(year) ?? false; const receivedExists = mp2ReceivedMap.get(country)?.has(year) ?? false; const donated = mp2DonatedMap.get(country)?.get(year) ?? 0; const received = mp2ReceivedMap.get(country)?.get(year) ?? 0; const active = donatedExists || receivedExists; const net = donated - received; const denom = Math.abs(donated) + Math.abs(received); return {country, year, donated, received, active, net, role: denom > 0 ? net / denom : 0}; })])); const mp2CountryTotals = mp2Countries.map(country => { const rows = mp2ByCountry.get(country); const donated = d3.sum(rows, d => d.donated); const received = d3.sum(rows, d => d.received); const denom = Math.abs(donated) + Math.abs(received); return {country, donated, received, net: donated - received, role: denom > 0 ? (donated - received) / denom : 0, observedYears: rows.filter(d => d.active).length}; }); const mp2LargestCountries = mp2CountryTotals.slice() .sort((a, b) => d3.descending(Math.abs(a.donated) + Math.abs(a.received), Math.abs(b.donated) + Math.abs(b.received))); const mp2RoleSwitches = mp2Countries.map(country => { const active = mp2ByCountry.get(country).filter(d => d.active && d.role !== 0); const changes = d3.pairs(active).filter(([a, b]) => Math.sign(a.net) !== Math.sign(b.net)); return {country, changedRoleBetweenObservedYears: changes.length, transitions: changes.map(([a, b]) => `${a.year}→${b.year}`)}; }).sort((a, b) => d3.descending(a.changedRoleBetweenObservedYears, b.changedRoleBetweenObservedYears)); display({ totalDonatedAcrossCountries: d3.sum(mp2CountryTotals, d => d.donated), totalReceivedAcrossCountries: d3.sum(mp2CountryTotals, d => d.received), topDonors: mp2CountryTotals.slice().sort((a,b)=>b.donated-a.donated).slice(0,5), topRecipients: mp2CountryTotals.slice().sort((a,b)=>b.received-a.received).slice(0,5), largestObservedRoleChanges: mp2RoleSwitches.slice(0,8) }); // Explicit role-transition and consecutive-year change evidence. // Distinguish adjacent calendar years from transitions across a reporting gap. const mp2RoleEvents = mp2Countries.flatMap(country => { const observed = mp2ByCountry.get(country).filter(d => d.active && d.net !== 0); return d3.pairs(observed) .filter(([a,b]) => Math.sign(a.net) !== Math.sign(b.net)) .map(([a,b]) => ({country, from:a.year, to:b.year, adjacent:b.year===a.year+1, fromNet:a.net, toNet:b.net, minimumActivity:Math.min(Math.abs(a.donated)+Math.abs(a.received), Math.abs(b.donated)+Math.abs(b.received))})); }).sort((a,b) => d3.descending(a.minimumActivity,b.minimumActivity)); const mp2OneYearDrops = mp2Countries.flatMap(country => { const observed = mp2ByCountry.get(country).filter(d=>d.active); return d3.pairs(observed) .filter(([a,b]) => b.year===a.year+1) .map(([a,b]) => ({country, from:a.year, to:b.year, prior:a.donated+a.received, next:b.donated+b.received, difference:(b.donated+b.received)-(a.donated+a.received)})); }).filter(d=>d.difference<0).sort((a,b)=>a.difference-b.difference); // Look at changes in the two displayed lines, not just their combined total. const mp2SeriesChanges=mp2Countries.flatMap(country=>{ const obs=mp2ByCountry.get(country).filter(d=>d.active); return d3.pairs(obs).filter(([a,b])=>b.year===a.year+1).flatMap(([a,b])=> ["donated","received"].map(series=>({ country,series,from:a.year,to:b.year,prior:a[series],next:b[series], change:b[series]-a[series] }))); }); const mp2SharpIncrease=d3.greatest(mp2SeriesChanges,d=>d.change); const mp2SharpDecrease=d3.least(mp2SeriesChanges,d=>d.change);41:T23d5,const mp2Visualization1 = (() => { const root = d3.create("div").style("font", "13px sans-serif").style("max-width", "1080px"); root.append("p").text("Blue = aid donated; orange = aid received. Missing years are gaps, not zero. Click any heatmap row to examine that country."); const controls = root.append("div").style("margin", "8px 0 8px"); controls.append("label").text("Country: "); const select = controls.append("select").style("padding", "4px"); select.selectAll("option").data(mp2Countries).join("option").attr("value", d => d).text(d => d); const preferred = mp2Countries.includes("Thailand") ? "Thailand" : mp2LargestCountries[0].country; select.property("value", preferred); const W = 1050, H = 440, m = {top: 55, right: 26, bottom: 62, left: 95}; const svg = root.append("svg").attr("viewBox", `0 0 ${W} ${H}`) .style("width", "100%").style("background", "#fff"); const x = d3.scaleLinear().domain([mp2MinYear, mp2MaxYear]).range([m.left, W - m.right]); const tickYears = d3.range(Math.ceil(mp2MinYear/10)*10, mp2MaxYear+1, 10); svg.append("g").attr("transform", `translate(0,${H-m.bottom})`) .call(d3.axisBottom(x).tickValues(tickYears).tickFormat(d3.format("d"))); const yAxis = svg.append("g").attr("transform", `translate(${m.left},0)`); const grid = svg.append("g"); const seriesG = svg.append("g"); const peakG = svg.append("g"); const title = svg.append("text").attr("x", W/2).attr("y", 25) .attr("text-anchor", "middle").attr("font-size", 19).attr("font-weight", 700); svg.append("text").attr("x", W/2).attr("y", H-13).attr("text-anchor", "middle").text("Year"); svg.append("text").attr("transform", "rotate(-90)").attr("x", -H/2).attr("y", 21) .attr("text-anchor", "middle").text("Committed aid, constant USD"); const legend = svg.append("g").attr("transform", `translate(${W-275},43)`); [["Donated", "#1768ac"], ["Received", "#de763d"]].forEach(([name, color], i) => { legend.append("line").attr("x1", i*125).attr("x2", i*125+22).attr("y1", 0).attr("y2", 0) .attr("stroke",color).attr("stroke-width",3); legend.append("text").attr("x",i*125+27).attr("y",4).text(name); }); // Markers: hollow rings denote maxima; constant-size markers encode no third variable. const markerKey = svg.append("g").attr("transform", `translate(${W-540},43)`); markerKey.append("circle").attr("cx",0).attr("cy",-2).attr("r",6) .attr("fill","none").attr("stroke","#374151").attr("stroke-width",1.5); markerKey.append("text").attr("x",12).attr("y",2) .attr("font-size",11).text("Highest annual amount for each series"); const zeroReference = svg.append("line") .attr("x1",m.left).attr("x2",W-m.right) .attr("stroke","#80858d").attr("stroke-width",.9) .attr("stroke-dasharray","3 3"); const summary = root.append("p").style("line-height", "1.5"); function drawCountry(country) { const arr = mp2ByCountry.get(country); const active = arr.filter(d => d.active); const min = d3.min(active, d => Math.min(0,d.donated,d.received)) ?? 0; const max = d3.max(active, d => Math.max(0,d.donated,d.received)) ?? 1; const y = d3.scaleLinear().domain([Math.min(0,min), max || 1]).nice() .range([H-m.bottom,m.top]); yAxis.call(d3.axisLeft(y).ticks(6).tickFormat(mp2Fmt)); zeroReference.attr("y1",y(0)).attr("y2",y(0)); grid.selectAll("line").data(y.ticks(6)).join("line") .attr("x1",m.left).attr("x2",W-m.right) .attr("y1",d=>y(d)).attr("y2",d=>y(d)) .attr("stroke","#e5eaf0"); const series = [ {key:"donated",label:"Donated",color:"#1768ac"}, {key:"received",label:"Received",color:"#de763d"} ]; const line = key => d3.line().defined(d => d.active) .x(d => x(d.year)).y(d => y(d[key])); seriesG.selectAll("path.aid-line").data(series,d=>d.key).join("path") .attr("class","aid-line").attr("fill","none") .attr("stroke",d=>d.color).attr("stroke-width",2.2) .attr("d",d=>line(d.key)(arr)); seriesG.selectAll("g.points").data(series,d=>d.key).join("g") .attr("class","points").attr("fill",d=>d.color) .each(function(s) { d3.select(this).selectAll("circle").data(active,d=>d.year).join("circle") .attr("cx",d=>x(d.year)).attr("cy",d=>y(d[s.key])).attr("r",4) .selectAll("title").data(d=>[d]).join("title") .text(d=>`${country} · ${d.year}\nDonated ${mp2Fmt(d.donated)}\nReceived ${mp2Fmt(d.received)}\nNet ${mp2Fmt(d.net)}`); }); const peakDonated = d3.greatest(active,d=>d.donated); const peakReceived = d3.greatest(active,d=>d.received); const notable = [peakDonated&&{...peakDonated,key:"donated",color:"#1768ac"}, peakReceived&&{...peakReceived,key:"received",color:"#de763d"}].filter(Boolean); peakG.selectAll("circle.peak").data(notable,d=>d.key).join("circle") .attr("class","peak").attr("cx",d=>x(d.year)).attr("cy",d=>y(d[d.key])) .attr("r",6).attr("fill","none").attr("stroke",d=>d.color).attr("stroke-width",2); title.text(`${country} — yearly commitments (${mp2MinYear}–${mp2MaxYear})`); const changes = mp2RoleSwitches.find(d=>d.country===country); const consecutive = d3.pairs(active).filter(([a,b])=>b.year===a.year+1); const drop = d3.least(consecutive, ([a,b]) => (b.donated+b.received)-(a.donated+a.received)); summary.text(`Observed active years: ${active.length}. Peak donated: ${peakDonated ? `${mp2Fmt(peakDonated.donated)} (${peakDonated.year})` : "none"}. `+ `Peak received: ${peakReceived ? `${mp2Fmt(peakReceived.received)} (${peakReceived.year})` : "none"}. `+ `Changes of net donor/recipient sign between active years: ${changes.changedRoleBetweenObservedYears}. `+ (drop ? `Largest one-year drop in combined commitments: ${mp2Fmt((drop[1].donated+drop[1].received)-(drop[0].donated+drop[0].received))} (${drop[0].year}→${drop[1].year}).` : "No consecutive observed years to calculate a one-year drop.")); heatRows.attr("stroke",d=>d.country===country?"#101828":"none") .attr("stroke-width",d=>d.country===country?1.3:0); } root.append("h4").text("Country-year overview: net donor (blue) versus net recipient (orange)"); root.append("p").text("Each cell is one year. Gray = recorded but balanced; near-white = no record. Yearly balance is (donated − received) ÷ (|donated| + |received|). The intensity shows role, not financial magnitude."); const rowH = 18, hmW=1050, hmLeft=178, hmRight=30, hmTop=50, hmBottom=55; const hmH=hmTop+mp2Countries.length*rowH+hmBottom; const heat = root.append("svg").attr("viewBox",`0 0 ${hmW} ${hmH}`).style("width","100%"); const xb = d3.scaleBand().domain(mp2Years).range([hmLeft,hmW-hmRight]).paddingInner(0.05); const orderedCountries = mp2CountryTotals.slice().sort((a,b)=>b.role-a.role).map(d=>d.country); const yb = d3.scaleBand().domain(orderedCountries) .range([hmTop,hmTop+mp2Countries.length*rowH]).paddingInner(0.07); heat.append("g").attr("transform",`translate(0,${hmTop-7})`) .selectAll("text").data(tickYears).join("text") .attr("x",d=>xb(d)??0).attr("text-anchor","middle").attr("font-size",11) .text(d=>d); heat.append("g").selectAll("text").data(orderedCountries).join("text") .attr("x",hmLeft-8).attr("y",d=>yb(d)+yb.bandwidth()/2+4) .attr("text-anchor","end").attr("font-size",11).text(d=>d); const allCells = orderedCountries.flatMap(country=>mp2ByCountry.get(country)); const heatRows = heat.append("g").selectAll("rect.role").data(allCells) .join("rect").attr("class","role") .attr("x",d=>xb(d.year)).attr("y",d=>yb(d.country)) .attr("width",xb.bandwidth()).attr("height",yb.bandwidth()) .attr("fill",d=>!d.active?"#f8f9fa":mp2RoleColor(d.role)) .style("cursor","pointer") .on("click",(event,d)=>{select.property("value",d.country);drawCountry(d.country);}); heatRows.append("title").text(d=>`${d.country}, ${d.year}\n${d.active ? `Donated ${mp2Fmt(d.donated)}, received ${mp2Fmt(d.received)}; balance ${d.role.toFixed(2)}` : "No record in this sample"}\nClick to select country`); const legendHm=heat.append("g").attr("transform",`translate(${hmLeft},${hmH-30})`); const lv=d3.range(81).map(i=>-1+i/40); legendHm.selectAll("rect").data(lv).join("rect") .attr("x",(d,i)=>i*6.5).attr("width",6.6).attr("height",13).attr("fill",mp2RoleColor); legendHm.append("text").attr("x",0).attr("y",27).text("Mostly receiving").attr("font-size",11); legendHm.append("text").attr("x",263).attr("y",27).attr("text-anchor","middle").text("Balanced").attr("font-size",11); legendHm.append("text").attr("x",526).attr("y",27).attr("text-anchor","end") .text("Mostly donating").attr("font-size",11); const missingKey=legendHm.append("g").attr("transform","translate(580,0)"); missingKey.append("rect").attr("width",15).attr("height",13) .attr("fill","#f8f9fa").attr("stroke","#aeb4bd"); missingKey.append("text").attr("x",22).attr("y",11) .attr("font-size",11).text("No observed record"); select.on("change",function(){drawCountry(this.value);}); drawCountry(preferred); return root.node(); })(); display(mp2Visualization1);42:T186d,// This output supplies quantitative findings to the written answer; no invented numbers. const mp2DonorLeaders = mp2CountryTotals.slice().sort((a,b)=>b.donated-a.donated).slice(0,3); const mp2RecipientLeaders = mp2CountryTotals.slice().sort((a,b)=>b.received-a.received).slice(0,3); const mp2MostlyDonors = mp2CountryTotals.filter(d=>d.net>0); const mp2MostlyRecipients = mp2CountryTotals.filter(d=>d.net<0); const mp2Balanced = mp2CountryTotals.filter(d=>d.observedYears>0) .sort((a,b)=>Math.abs(a.role)-Math.abs(b.role)).slice(0,2); const mp2FeaturedSwitch = mp2RoleEvents.find(d=>d.adjacent) ?? mp2RoleEvents[0]; const mp2FeaturedDrop = mp2SharpDecrease; const mp2PeakAnnual = d3.greatest(mp2Countries.flatMap(country=>mp2ByCountry.get(country).filter(d=>d.active)), d=>Math.max(d.donated,d.received)); const mp2E1 = { donorLeaders:mp2DonorLeaders, recipientLeaders:mp2RecipientLeaders, mostlyDonorCountries:mp2MostlyDonors.length, mostlyRecipientCountries:mp2MostlyRecipients.length, nearBalancedExamples:mp2Balanced, meaningfulRoleChanges:mp2RoleEvents.slice(0,15), largestConsecutiveYearDeclines:mp2OneYearDrops.slice(0,10), sharpestLineIncrease:mp2SharpIncrease, sharpestLineDecrease:mp2SharpDecrease, peakObservedCountryYear:mp2PeakAnnual }; display(Inputs.table(mp2CountryTotals.slice().sort((a,b)=>b.donated-a.donated), {columns:["country","donated","received","net","role","observedYears"]})); display(mp2E1); // Separate, automatically data-grounded analysis panel (renders below the charts). const mp2Written1 = d3.create("section").style("font","14px sans-serif") .style("max-width","1000px").style("line-height","1.6"); mp2Written1.append("h3").text("Analysis — Visualization 1"); mp2Written1.append("p").text( `Across this reduced sample (${mp2MinYear}–${mp2MaxYear}), the largest total donors are `+ mp2DonorLeaders.map(d=>`${d.country} (${mp2Fmt(d.donated)})`).join(", ")+`. `+ `The largest total recipients are `+ mp2RecipientLeaders.map(d=>`${d.country} (${mp2Fmt(d.received)})`).join(", ")+`. `+ `${mp2MostlyDonors.length} countries have positive net outgoing commitments, `+ `${mp2MostlyRecipients.length} have positive net incoming commitments, and `+ `${mp2CountryTotals.length-mp2MostlyDonors.length-mp2MostlyRecipients.length} are exactly balanced in this sample. `+ `Countries closest to balance include `+ mp2Balanced.map(d=>`${d.country} (normalized balance ${d.role.toFixed(2)})`).join(" and ")+`.`); mp2Written1.append("p").text(mp2FeaturedSwitch ? `A concrete change of role occurred for ${mp2FeaturedSwitch.country}: its net balance `+ `was ${mp2Fmt(mp2FeaturedSwitch.fromNet)} in ${mp2FeaturedSwitch.from} and `+ `${mp2Fmt(mp2FeaturedSwitch.toNet)} in ${mp2FeaturedSwitch.to}. `+ (mp2FeaturedSwitch.adjacent ? `These are consecutive calendar years.` : `The years are not consecutive, so the precise reversal year is not observable.`) : `No donor-versus-recipient sign reversals were detected between observed years in this sample.`); mp2Written1.append("p").text( (mp2PeakAnnual ? `One large annual observation is ${mp2PeakAnnual.country} in ${mp2PeakAnnual.year}, `+ `with ${mp2Fmt(mp2PeakAnnual.donated)} donated and ${mp2Fmt(mp2PeakAnnual.received)} received. ` : "")+ (mp2SharpIncrease ? `The largest increase in either displayed line between consecutive years is `+ `${mp2SharpIncrease.country}'s ${mp2SharpIncrease.series} commitments, `+ `${mp2SharpIncrease.from}–${mp2SharpIncrease.to}: `+ `${mp2Fmt(mp2SharpIncrease.prior)} to ${mp2Fmt(mp2SharpIncrease.next)} `+ `(change +${mp2Fmt(mp2SharpIncrease.change)}). ` : "")+ (mp2FeaturedDrop ? `The largest decrease in either displayed line between consecutive years is `+ `${mp2FeaturedDrop.country}'s ${mp2FeaturedDrop.series} commitments, `+ `${mp2FeaturedDrop.from}–${mp2FeaturedDrop.to}: `+ `${mp2Fmt(mp2FeaturedDrop.prior)} to ${mp2Fmt(mp2FeaturedDrop.next)} `+ `(change ${mp2Fmt(mp2FeaturedDrop.change)}). ` : `Insufficient consecutive observations to calculate a one-year decline. `)+ `These are committed constant-USD amounts, not confirmed cash disbursements; missing years are not evidence of zero aid worldwide.`); // Additional evidence: role changes in each direction across observed years. const mp2RoleDirections = [ { label: "Donor to recipient", events: mp2RoleEvents.filter(d => d.fromNet > 0 && d.toNet < 0) }, { label: "Recipient to donor", events: mp2RoleEvents.filter(d => d.fromNet < 0 && d.toNet > 0) } ]; for (const direction of mp2RoleDirections) { const consecutive = direction.events.filter(d => d.adjacent); const example = d3.greatest( consecutive.length ? consecutive : direction.events, d => d.minimumActivity ); const nCountries = new Set(direction.events.map(d => d.country)).size; mp2Written1.append("p").text( `${direction.label}: ${direction.events.length} observed transitions ` + `across ${nCountries} countries. ` + (example ? `For example, ${example.country} changed from net ` + `${mp2Fmt(example.fromNet)} in ${example.from} to net ` + `${mp2Fmt(example.toNet)} in ${example.to}. ` + (example.adjacent ? "These observations are from consecutive calendar years." : "The observed years are not consecutive, so the precise switching year is unknown.") : "No example of this direction occurs in the reduced dataset.") ); } mp2Written1.append("h3").text("Design Decisions — Visualization 1"); mp2Written1.append("p").text( "The shared monetary axis compares incoming and outgoing commitments without a misleading dual scale. " + "Blue and orange are keyed as donated and received; outlined circles identify each series maximum. " + "The country selector and linked yearly role heatmap expose both country-specific peaks/valleys " + "and cross-country role changes. A centered diverging legend describes the normalized balance; " + "a separate swatch identifies missing country-year observations. Hover reveals exact dollar values. " + "The heatmap shows relative role, not magnitude, which is why the line chart retains absolute USD values."); display(mp2Written1.node());43:Ta91,const mp2PurposeRows = mp2Rows.filter(d => { const code = d.purposeCode.trim().toUpperCase(); const name = d.purposeName.trim().toUpperCase(); return code !== "" && code !== "UNSPECIFIED" && name !== "UNSPECIFIED"; }); const mp2PurposeTotals = d3.rollups(mp2PurposeRows, v => d3.sum(v,d=>d.amount), d=>d.purposeCode) .map(([code, amount]) => ({code, amount, recordCount:mp2PurposeRows.filter(d=>d.purposeCode===code).length})); const mp2PurposeName = new Map(d3.rollups(mp2PurposeRows, vv => { const names = d3.rollups(vv.filter(d=>d.purposeName), z=>z.length, d=>d.purposeName); return names.length ? d3.greatest(names,d=>d[1])[0] : "Unnamed purpose"; },d=>d.purposeCode)); const mp2Top10 = mp2PurposeTotals.sort((a,b)=>b.amount-a.amount).slice(0,10) .map(d=>({...d,name:mp2PurposeName.get(d.code)})); const mp2Top10Codes = new Set(mp2Top10.map(d=>d.code)); const mp2PeriodStart = Math.floor(mp2MinYear/5)*5; const mp2PeriodStarts = d3.range(mp2PeriodStart,mp2MaxYear+1,5); const mp2Periods = mp2PeriodStarts.map(start=>{ const observedStart=Math.max(start,mp2MinYear); const observedEnd=Math.min(start+4,mp2MaxYear); return {start, end:observedEnd, first:observedStart, years:observedEnd-observedStart+1, isFull:observedEnd-observedStart+1===5, label:`${observedStart}–${observedEnd}`}; }); const mp2PeriodOf = y => Math.floor(y/5)*5; const mp2PurposeByPeriod = d3.rollup( mp2PurposeRows.filter(d=>mp2Top10Codes.has(d.purposeCode)), vv=>d3.sum(vv,d=>d.amount), d=>mp2PeriodOf(d.year),d=>d.purposeCode ); const mp2PurposeCells = mp2Top10.flatMap(p=>mp2Periods.map(period=>({ code:p.code,name:p.name,period, amount:mp2PurposeByPeriod.get(period.start)?.get(p.code) ?? 0 }))); const mp2PeriodTopTenPositive = new Map(mp2Periods.map(period=>[ period.start,d3.sum(mp2Top10,p=>Math.max(0,mp2PurposeByPeriod.get(period.start)?.get(p.code)??0)) ])); const mp2PurposeShare=(start,code)=>{ const denom=mp2PeriodTopTenPositive.get(start)||0; return denom>0?Math.max(0,mp2PurposeByPeriod.get(start)?.get(code)??0)/denom:0; }; const mp2PurposeAnnualAvg=(start,code)=>{ const p=mp2Periods.find(d=>d.start===start); return (mp2PurposeByPeriod.get(start)?.get(code)??0)/(p?.years||1); }; const mp2PurposePeriodsWithNegativeNet = mp2PurposeCells.filter(d=>d.amount<0); display(Inputs.table(mp2Top10, {columns:["code","name","amount","recordCount"]})); display({ basis:"Top 10 purpose codes ranked by total committed constant USD (not record frequency)", fiveYearBins:mp2Periods.map(d=>d.label), binsWithNegativeNetCommitments:mp2PurposePeriodsWithNegativeNet.length, exampleNegativeBins:mp2PurposePeriodsWithNegativeNet.slice(0,5) });44:T1e28,const mp2Visualization2 = (() => { const root=d3.create("div").style("font","13px sans-serif") .style("max-width","1100px"); root.append("p").text( "Rows are the ten purpose codes receiving the most cumulative committed USD. " + "Color shows each purpose's share of positive top-ten commitments in that period; " + "the darker the blue, the larger the share. Click a cell or purpose name to inspect it."); const W=1090,left=268,right=28,top=92,rowH=43,H=top+mp2Top10.length*rowH+98; const svg=root.append("svg").attr("viewBox",`0 0 ${W} ${H}`) .style("width","100%"); const x=d3.scaleBand().domain(mp2PeriodStarts) .range([left,W-right]).paddingInner(.04); const y=d3.scaleBand().domain(mp2Top10.map(d=>d.code)) .range([top,top+rowH*mp2Top10.length]).paddingInner(.07); const short=s=>s.length>33?s.slice(0,31)+"…":s; svg.append("text").attr("x",W/2).attr("y",27) .attr("font-weight",700).attr("font-size",18).attr("text-anchor","middle") .text("How the top ten aid purposes change across five-year intervals"); svg.append("text").attr("x",W/2).attr("y",48).attr("text-anchor","middle") .attr("fill","#566171").attr("font-size",12) .text("Cell color: share of positive amounts among the top ten purposes (0–100%)"); svg.append("g").selectAll("text.period").data(mp2Periods).join("text") .attr("class","period").attr("x",d=>x(d.start)+x.bandwidth()/2) .attr("y",top-18).attr("font-size",10).attr("text-anchor","middle") .text(d=>d.label); //EDITED const labels=svg.append("g").selectAll("text.label") .data(mp2Top10).join("text").attr("class","label") .attr("x",left-12).attr("y",d=>y(d.code)+y.bandwidth()/2+4) .attr("text-anchor","end").attr("font-size",11) .text(d=>short(d.name)).style("cursor","pointer"); labels.append("title").text(d=>`${d.name} [${d.code}] All-time total: ${mp2Fmt(d.amount)}`); const hasRecord=(start,code)=>mp2PurposeByPeriod.get(start)?.has(code)??false; const cells=svg.append("g").selectAll("rect.cell").data(mp2PurposeCells) .join("rect").attr("class","cell") .attr("x",d=>x(d.period.start)).attr("y",d=>y(d.code)) .attr("width",x.bandwidth()).attr("height",y.bandwidth()) .attr("fill",d=>!hasRecord(d.period.start,d.code)?"#f4f6f8": d.amount<0?"#bc4545":d3.interpolateYlGnBu(mp2PurposeShare(d.period.start,d.code))) .style("cursor","pointer"); cells.append("title").text(d=>{ const share=mp2PurposeShare(d.period.start,d.code); return `${d.name}, ${d.period.label} Period commitments: ${mp2Fmt(d.amount)} `+ `Average per year: ${mp2Fmt(d.amount/d.period.years)} `+ `Share of positive top-ten period amounts: ${d3.format('.1%')(share)}`+ `${!hasRecord(d.period.start,d.code)?"\nNo records for this purpose and period":""}`; }); const legend=svg.append("g").attr("transform",`translate(${left},${H-66})`); legend.selectAll("rect.ramp").data(d3.range(101)).join("rect") .attr("class","ramp").attr("x",i=>i*4.7).attr("width",4.8) .attr("height",14).attr("fill",i=>d3.interpolateYlGnBu(i/100)); legend.append("text").attr("y",32).attr("font-size",11).text("0% of top-ten period dollars"); legend.append("text").attr("x",475).attr("y",32).attr("text-anchor","end") .attr("font-size",11).text("100%"); const noDataKey=legend.append("g").attr("transform","translate(500,0)"); noDataKey.append("rect").attr("width",14).attr("height",14) .attr("fill","#f4f6f8").attr("stroke","#aeb4bf"); noDataKey.append("text").attr("x",20).attr("y",12).attr("font-size",10) .text("No purpose records"); const negKey=legend.append("g").attr("transform","translate(678,0)"); negKey.append("rect").attr("width",14).attr("height",14).attr("fill","#bc4545"); negKey.append("text").attr("x",20).attr("y",12).attr("font-size",10) .text("Negative net adjustment"); const controls=root.append("div").style("margin","20px 0 10px"); controls.append("label").text("Purpose: "); const choose=controls.append("select").style("padding","5px"); choose.selectAll("option").data(mp2Top10).join("option") .attr("value",d=>d.code).text(d=>`${d.name} [${d.code}]`); const w=1050,h=380,mm={top:88,bottom:85,left:95,right:35}; // EDITED const detail=root.append("svg").attr("viewBox",`0 0 ${w} ${h}`) .style("width","100%"); const xx=d3.scaleBand().domain(mp2PeriodStarts) .range([mm.left,w-mm.right]).padding(.17); detail.append("g").attr("transform",`translate(0,${h-mm.bottom})`) .call(d3.axisBottom(xx).tickFormat(d=>mp2Periods.find(p=>p.start===d).label)) .selectAll("text").attr("font-size",10).attr("text-anchor","end") .attr("transform","rotate(-28)"); const ya=detail.append("g").attr("transform",`translate(${mm.left},0)`); const bars=detail.append("g"); const axisZero=detail.append("line").attr("x1",mm.left) .attr("x2",w-mm.right).attr("stroke","#798390"); const title=detail.append("text").attr("x",w/2).attr("y",25) .attr("text-anchor","middle").attr("font-size",17).attr("font-weight",700); detail.append("text").attr("transform","rotate(-90)") .attr("x",-h/2).attr("y",20).attr("text-anchor","middle") .text("Average annual commitments (constant USD/year)"); const barLegend=detail.append("g").attr("transform",`translate(${w-280},42)`); [["Positive net", "#2475ae"],["Negative adjustment", "#bc4545"]] .forEach(([label,color],i)=>{ const gg=barLegend.append("g").attr("transform",`translate(0,${i*19})`); gg.append("rect").attr("width",12).attr("height",12).attr("fill",color); gg.append("text").attr("x",18).attr("y",10).attr("font-size",11).text(label); }); const summary=root.append("p").style("line-height","1.5"); function update(code){ const purpose=mp2Top10.find(d=>d.code===code); const values=mp2Periods.map(period=>({period, total:mp2PurposeByPeriod.get(period.start)?.get(code)??0, avg:mp2PurposeAnnualAvg(period.start,code)})); const bounds=d3.extent(values,d=>d.avg); const ymin=Math.min(0,bounds[0]),ymax=Math.max(0,bounds[1]); const yy=d3.scaleLinear().domain([ymin,Math.max(ymin+1,ymax)]).nice() .range([h-mm.bottom,mm.top]); ya.call(d3.axisLeft(yy).ticks(6).tickFormat(mp2Fmt)); axisZero.attr("y1",yy(0)).attr("y2",yy(0)); bars.selectAll("rect.purpose-bar").data(values).join("rect") .attr("class","purpose-bar").attr("x",d=>xx(d.period.start)) .attr("width",xx.bandwidth()) .attr("y",d=>yy(Math.max(0,d.avg))) .attr("height",d=>Math.abs(yy(d.avg)-yy(0))) .attr("fill",d=>d.avg<0?"#bc4545":"#2475ae") .selectAll("title").data(d=>[d]).join("title") .text(d=>`${purpose.name}: ${d.period.label} Period total ${mp2Fmt(d.total)} `+ `Annual average ${mp2Fmt(d.avg)} over ${d.period.years} years`); title.text(`${purpose.name} — annual average by five-year interval`); const peak=d3.greatest(values,d=>d.avg); summary.text(`All-time ${mp2Fmt(purpose.amount)} across ${purpose.recordCount} records. `+ `Highest annual-average period: ${peak.period.label}, ${mp2Fmt(peak.avg)}/year. `+ `The period's unnormalized total is ${mp2Fmt(peak.total)} over ${peak.period.years} years. `+ `Partial first/last intervals are annualized so they can be compared fairly.`); cells.attr("stroke",d=>d.code===code?"#25374a":"none") .attr("stroke-width",d=>d.code===code?1.3:0); } choose.on("change",function(){update(this.value);}); cells.on("click",(_,d)=>{choose.property("value",d.code);update(d.code);}); labels.on("click",(_,d)=>{choose.property("value",d.code);update(d.code);}); update(mp2Top10[0].code); return root.node(); })(); display(mp2Visualization2);45:T1070,const mp2FullPeriods=mp2Periods.filter(p=>p.isFull && (mp2PeriodTopTenPositive.get(p.start)||0)>0); const mp2ComparisonEarly=mp2FullPeriods[0] ?? mp2Periods.find(p=>(mp2PeriodTopTenPositive.get(p.start)||0)>0); const mp2ComparisonLate=mp2FullPeriods[mp2FullPeriods.length-1] ?? mp2Periods[mp2Periods.length-1]; const mp2PurposeShifts=mp2Top10.map(p=>{ const early=mp2PurposeShare(mp2ComparisonEarly.start,p.code); const late=mp2PurposeShare(mp2ComparisonLate.start,p.code); const values=mp2Periods.map(period=>({period,avg:mp2PurposeAnnualAvg(period.start,p.code), total:mp2PurposeByPeriod.get(period.start)?.get(p.code)??0})); const peak=d3.greatest(values,d=>d.avg); return {purpose:p.name,code:p.code,overall:p.amount, earlyShare:early,lateShare:late,shareChangePoints:100*(late-early), peakPeriod:peak.period.label,peakAnnualAverage:peak.avg}; }); const mp2PurposeRise=d3.greatest(mp2PurposeShifts,d=>d.shareChangePoints); const mp2PurposeFall=d3.least(mp2PurposeShifts,d=>d.shareChangePoints); const mp2PurposeLeadAt=p=>d3.greatest(mp2Top10,d=>mp2PurposeShare(p.start,d.code)); const mp2EarlyLeader=mp2PurposeLeadAt(mp2ComparisonEarly); const mp2LateLeader=mp2PurposeLeadAt(mp2ComparisonLate); display(Inputs.table(mp2PurposeShifts)); const mp2Written2=d3.create("section").style("font","14px sans-serif") .style("max-width","1000px").style("line-height","1.6"); mp2Written2.append("h3").text("Analysis — Visualization 2"); mp2Written2.append("p").text( `The ten largest aid purposes by total monetary commitments are `+ mp2Top10.map((d,i)=>`${i+1}. ${d.name} (${mp2Fmt(d.amount)})`).join("; ")+`. `+ `These are ranked by dollars, not the frequency of commitment records. `+ `The source is a reduced country sample, so the ranking is not a claim about global aid.`); mp2Written2.append("p").text( `For comparable complete five-year bins, ${mp2ComparisonEarly.label} and `+ `${mp2ComparisonLate.label}, the leading top-ten purpose `+ (mp2EarlyLeader.code===mp2LateLeader.code ? `remained ${mp2EarlyLeader.name}` : `changed from ${mp2EarlyLeader.name} to ${mp2LateLeader.name}`) + ` (share: ${d3.format('.1%')(mp2PurposeShare(mp2ComparisonEarly.start,mp2EarlyLeader.code))} `+ `in the first comparison period; ${d3.format('.1%')(mp2PurposeShare(mp2ComparisonLate.start,mp2LateLeader.code))} `+ `in the later period). `+ `The largest share gain is ${mp2PurposeRise.purpose}: `+ `${d3.format('.1%')(mp2PurposeRise.earlyShare)} to ${d3.format('.1%')(mp2PurposeRise.lateShare)} `+ `(${mp2PurposeRise.shareChangePoints.toFixed(1)} percentage points). `+ `The largest share decline is ${mp2PurposeFall.purpose}: `+ `${d3.format('.1%')(mp2PurposeFall.earlyShare)} to ${d3.format('.1%')(mp2PurposeFall.lateShare)} `+ `(${mp2PurposeFall.shareChangePoints.toFixed(1)} percentage points).`); mp2Written2.append("p").text( `${mp2PurposeRise.purpose} reaches its highest average yearly amount in `+ `${mp2PurposeRise.peakPeriod} (${mp2Fmt(mp2PurposeRise.peakAnnualAverage)} per year). `+ `A category's share may fall while its monetary commitments grow, so the heatmap of relative `+ `prominence must be read alongside the selected-purpose dollar chart. `+ `The latest bin is ${mp2Periods[mp2Periods.length-1].label}, `+ `which may be partial; its annual-average values are shown in the detail chart. `+ `Period totals are available in hover text, and partial five-year periods are divided `+ `by their covered calendar years in the annual-average chart.`); mp2Written2.append("h3").text("Design Decisions — Visualization 2"); mp2Written2.append("p").text( "A ten-row heatmap with a labeled 0–100% color ramp provides comparable five-year shares. " + "Separate red and gray keys flag negative net adjustments and no recorded commitments. " + "Clicking any purpose opens a linked bar chart of average annual constant-USD commitments, " + "rather than visually connecting discrete five-year totals with a misleading continuous line. " + "The ranking uses all-time monetary totals and the temporal chart corrects for partial " + "first/last bins. Tooltips show precise amounts and denominators."); display(mp2Written2.node());46:Tcfe,// Natural Earth-derived country boundaries. Same reference geography as Mini-Project 1. const mp2Atlas = await d3.json("https://cdn.jsdelivr.net/npm/world-atlas@2/countries-50m.json"); const mp2Features = topojson.feature(mp2Atlas,mp2Atlas.objects.countries).features; const mp2World={type:"FeatureCollection",features:mp2Features}; const mp2Aliases=new Map(Object.entries({ "United States":"United States of America", "Korea":"South Korea", "Korea, Republic of":"South Korea", "Slovak Republic":"Slovakia", "Czech Republic":"Czechia", "Viet Nam":"Vietnam", "Russian Federation":"Russia", "Bosnia and Herzegovina":"Bosnia and Herz.", "Central African Republic":"Central African Rep.", "Democratic Republic of the Congo":"Dem. Rep. Congo", "Congo, Democratic Republic of":"Dem. Rep. Congo", "Congo, Republic of":"Congo", "Cote d'Ivoire":"Côte d'Ivoire", "Dominican Republic":"Dominican Rep.", "Equatorial Guinea":"Eq. Guinea", "Lao PDR":"Laos", "Lao People's Democratic Republic":"Laos", "South Sudan":"S. Sudan", "Solomon Islands":"Solomon Is.", "Marshall Islands":"Marshall Is.", "Syrian Arab Republic":"Syria", "Iran, Islamic Republic of":"Iran", "Kyrgyz Republic":"Kyrgyzstan", "Macedonia, FYR":"North Macedonia", "Swaziland":"eSwatini", "Tanzania, United Republic of":"Tanzania", "Brunei Darussalam":"Brunei", "West Bank and Gaza Strip":"Palestine", "Bahamas, The":"Bahamas", "Gambia, The":"Gambia", "Yemen, Republic of":"Yemen", "Egypt, Arab Republic of":"Egypt" })); const mp2AtlasName = c=>mp2Aliases.get(c)??c; const mp2RecipientCountries=[...new Set(mp2Rows.map(d=>d.recipient))]; const mp2CountryByAtlas=new Map(mp2RecipientCountries.map(c=>[mp2AtlasName(c),c])); const mp2AtlasNames=new Set(mp2Features.map(d=>d.properties.name)); const mp2Unmatched=mp2RecipientCountries.filter(c=>!mp2AtlasNames.has(mp2AtlasName(c))); const mp2Collisions=d3.rollups(mp2RecipientCountries,v=>v,c=>mp2AtlasName(c)) .filter(([name,v])=>v.length>1); const mp2RecipientByPeriod=d3.rollup(mp2Rows, v=>d3.sum(v,d=>d.amount),d=>mp2PeriodOf(d.year),d=>d.recipient); const mp2TotalByPeriod=new Map(mp2Periods.map(p=>[ p.start,d3.sum(mp2RecipientCountries,c=>mp2RecipientByPeriod.get(p.start)?.get(c)??0) ])); const mp2RecipientPeriodRows=mp2Periods.flatMap(p=>mp2RecipientCountries.map(country=>({ start:p.start,period:p.label,country, amount:mp2RecipientByPeriod.get(p.start)?.get(country)??0 }))); // Every map displays average annual dollars, so short first/last bins are comparable. const mp2RecipientAnnual=(start,country)=>(mp2RecipientByPeriod.get(start)?.get(country)??0)/ (mp2Periods.find(p=>p.start===start)?.years||1); const mp2RecipientHasRecords=(start,country)=>mp2RecipientByPeriod.get(start)?.has(country)??false; const mp2PositiveAmounts=mp2RecipientPeriodRows .filter(d=>d.amount>0) .map(d=>mp2RecipientAnnual(d.start,d.country)); const mp2MapMax=d3.max(mp2PositiveAmounts)||1; const mp2MapMin=Math.max(1,d3.min(mp2PositiveAmounts)||1); display({recipientCountries:mp2RecipientCountries.length, matchedCountries:mp2RecipientCountries.length-mp2Unmatched.length, unmatchedCountries:mp2Unmatched, aliasCollisions:mp2Collisions, fiveYearPeriods:mp2Periods.map(p=>p.label), negativeCountryPeriodTotals:mp2RecipientPeriodRows.filter(d=>d.amount<0).slice(0,10)});47:T19d8,const mp2Visualization3=(()=>{ const root=d3.create("div").style("font","13px sans-serif").style("max-width","1100px"); root.append("p").text("Country colors use one fixed logarithmic annual-USD scale across all periods. " + "Hatched = outside the reduced recipient sample; white = no record in this period; " + "gray = recorded net zero; red = negative net adjustment. Hover for period totals."); const line=root.append("div").style("margin","8px 0 12px"); line.append("label").text("Five-year period: "); const picker=line.append("select").style("padding","5px"); picker.selectAll("option").data(mp2Periods).join("option") .attr("value",d=>d.start).text(d=>d.label); picker.property("value",mp2Periods[mp2Periods.length-1].start); const W=1050,H=580; const svg=root.append("svg").attr("viewBox",`0 0 ${W} ${H}`).style("width","100%"); const defs=svg.append("defs"); const pattern=defs.append("pattern").attr("id","mp2-no-recipient") .attr("width",6).attr("height",6).attr("patternUnits","userSpaceOnUse") .attr("patternTransform","rotate(45)"); pattern.append("rect").attr("width",6).attr("height",6).attr("fill","#f4f6f9"); pattern.append("path").attr("d","M0,0V6").attr("stroke","#becbd9").attr("stroke-width",1.25); const projection=d3.geoNaturalEarth1().fitExtent([[16,65],[W-16,H-86]],mp2World); const path=d3.geoPath(projection); const logColor=d3.scaleSequentialLog().domain([mp2MapMin,Math.max(mp2MapMin*1.001,mp2MapMax)]) .interpolator(d3.interpolateYlGnBu).clamp(true); const title=svg.append("text").attr("x",W/2).attr("y",27) .attr("text-anchor","middle").attr("font-weight",700).attr("font-size",18); const countries=svg.append("g").selectAll("path.country").data(mp2Features,d=>d.id) .join("path").attr("class","country").attr("d",path) .attr("stroke","#8c98a4").attr("stroke-width",.38); countries.append("title"); const legend=svg.append("g").attr("transform",`translate(240,${H-61})`); const lv=d3.range(121).map(i=>i/120); legend.selectAll("rect").data(lv).join("rect") .attr("x",(d,i)=>i*4.5).attr("width",4.6).attr("height",15) .attr("fill",t=>logColor(Math.exp(Math.log(mp2MapMin)+t*(Math.log(Math.max(mp2MapMin*1.001,mp2MapMax))-Math.log(mp2MapMin))))); legend.append("text").attr("x",0).attr("y",30).text(mp2Fmt(mp2MapMin)); legend.append("text").attr("x",545).attr("y",30).attr("text-anchor","end") .text(mp2Fmt(mp2MapMax)); legend.append("text").attr("x",272).attr("y",-7).attr("text-anchor","middle") .text("Average annual committed USD — fixed logarithmic scale"); // Legend swatches for categorical statuses that the gradient does not encode. const status=svg.append("g").attr("transform",`translate(215,${H-13})`); const statuses=[ {label:"Not in source sample",fill:"url(#mp2-no-recipient)"}, {label:"No records this period",fill:"#fff"}, {label:"Recorded net zero",fill:"#d9dde2"}, {label:"Negative adjustment",fill:"#c44444"} ]; status.selectAll("g").data(statuses).join("g") .attr("transform",(_,i)=>`translate(${i*200},0)`) .each(function(d){ const z=d3.select(this); z.append("rect").attr("width",13).attr("height",13) .attr("stroke","#9aa3ae").attr("fill",d.fill); z.append("text").attr("x",19).attr("y",11) .attr("font-size",10).text(d.label); }); const stats=root.append("p").style("line-height","1.5"); root.append("h4").text("Ten leading recipient countries — average committed USD per year"); const bw=1020,bh=400,bm={left:190,right:165,top:30,bottom:45}; const bar=root.append("svg").attr("viewBox",`0 0 ${bw} ${bh}`).style("width","100%"); const bx=d3.scaleLinear().range([bm.left,bw-bm.right]); const by=d3.scaleBand().range([bm.top,bh-bm.bottom]).padding(.2); const bars=bar.append("g"); const yAxis=bar.append("g"); const xAxis=bar.append("g").attr("transform",`translate(0,${bh-bm.bottom})`); bar.append("text").attr("x",(bm.left+bw-bm.right)/2).attr("y",bh-4) .attr("text-anchor","middle").text("Average annual constant USD received"); function redraw(start){ const period=mp2Periods.find(p=>p.start===+start); const totals=mp2RecipientByPeriod.get(+start)??new Map(); countries.attr("fill",d=>{ const c=mp2CountryByAtlas.get(d.properties.name); if(!c) return "url(#mp2-no-recipient)"; if (!mp2RecipientHasRecords(+start,c)) return "#fff"; const amt=mp2RecipientAnnual(+start,c); return amt<0?"#c44444":amt===0?"#d9dde2":logColor(amt); }).select("title").text(d=>{ const c=mp2CountryByAtlas.get(d.properties.name); return c?`${c}, ${period.label}\n`+ (mp2RecipientHasRecords(+start,c) ? `Period total: ${mp2Fmt(totals.get(c)??0)}\nAnnual average: ${mp2Fmt(mp2RecipientAnnual(+start,c))}/year` : "No recorded receipts in this period") : `${d.properties.name}: not a recipient in the reduced dataset`; }); title.text(`Average annual aid commitments received — ${period.label}`); const ranked=mp2RecipientCountries.map(country=>({country,amount:mp2RecipientAnnual(+start,country)})) .filter(d=>d.amount>0).sort((a,b)=>b.amount-a.amount); const top=ranked.slice(0,10); const overall=mp2TotalByPeriod.get(+start)??0; stats.text(`Period ${period.label} (${period.years} years): ${mp2Fmt(overall)} net received commitments across the reduced dataset; `+ `average ${mp2Fmt(overall/period.years)} per year. ${ranked.length} recipients have positive net amounts. `+ `Leading annual-average recipients: ${top.slice(0,3).map(d=>`${d.country} (${mp2Fmt(d.amount)}/year)`).join(", ")||"none"}. `+ `These are observed commitments in this sample, not a measurement of actual worldwide need.`); by.domain(top.map(d=>d.country)); bx.domain([0,d3.max(top,d=>d.amount)||1]).nice(); yAxis.attr("transform",`translate(${bm.left},0)`).call(d3.axisLeft(by).tickSize(0)); xAxis.call(d3.axisBottom(bx).ticks(5).tickFormat(mp2Fmt)); bars.selectAll("rect").data(top,d=>d.country).join("rect") .attr("x",bm.left).attr("y",d=>by(d.country)).attr("height",by.bandwidth()) .attr("width",d=>Math.max(0,bx(d.amount)-bm.left)).attr("fill","#2b7bba"); bars.selectAll("text.value").data(top,d=>d.country).join("text") .attr("class","value").attr("x",d=>bx(d.amount)+5) .attr("y",d=>by(d.country)+by.bandwidth()/2+4).text(d=>mp2Fmt(d.amount)); } picker.on("change",function(){redraw(this.value);}); redraw(mp2Periods[mp2Periods.length-1].start); return root.node(); })(); display(mp2Visualization3);48:T1a62,const mp2PeriodSummary=mp2Periods.map(p=>{ const totals=mp2RecipientByPeriod.get(p.start)??new Map(); const ranked=mp2RecipientCountries.map(country=>({country, total:totals.get(country)??0, average:mp2RecipientAnnual(p.start,country)})) .filter(d=>d.average>0).sort((a,b)=>b.average-a.average); const positiveTotal=d3.sum(ranked,d=>d.total); const netTotal=mp2TotalByPeriod.get(p.start)??0; return { period:p.label, start:p.start, nYears:p.years, netCommittedTotal:netTotal, averageAnnualCommitted:netTotal/p.years, positiveRecipientCountries:ranked.length, leadingRecipient:ranked[0]?.country??"none", leadingAverageAnnual:ranked[0]?.average??0, leadingShareOfPositive:positiveTotal>0?(ranked[0]?.total??0)/positiveTotal:0, topThree:ranked.slice(0,3).map(d=>d.country), topThreeShareOfPositive:positiveTotal>0?d3.sum(ranked.slice(0,3),d=>d.total)/positiveTotal:0 }; }); display(Inputs.table(mp2PeriodSummary)); const mp2ActiveSummary=mp2PeriodSummary.filter(d=>d.positiveRecipientCountries>0); const mp2FirstGeo=mp2ActiveSummary[0]; const mp2LastGeo=mp2ActiveSummary[mp2ActiveSummary.length-1]; const mp2DistinctLeaders=[...new Set(mp2ActiveSummary.map(d=>d.leadingRecipient))]; const mp2LeaderChanges=d3.pairs(mp2ActiveSummary) .filter(([a,b])=>a.leadingRecipient!==b.leadingRecipient); const mp2BiggestPositiveRate=d3.greatest(mp2ActiveSummary,d=>d.averageAnnualCommitted); const mp2Written3=d3.create("section").style("font","14px sans-serif") .style("max-width","1000px").style("line-height","1.6"); mp2Written3.append("h3").text("Analysis — Visualization 3"); mp2Written3.append("p").text( `In ${mp2FirstGeo.period}, the leading recipient was ${mp2FirstGeo.leadingRecipient} `+ `(${mp2Fmt(mp2FirstGeo.leadingAverageAnnual)} per year), with `+ `${mp2FirstGeo.positiveRecipientCountries} recipient countries receiving a positive net amount. `+ `The three largest recipients accounted for `+ `${d3.format('.1%')(mp2FirstGeo.topThreeShareOfPositive)} of the positive commitments. `+ `By ${mp2LastGeo.period}, the leading recipient was ${mp2LastGeo.leadingRecipient} `+ `(${mp2Fmt(mp2LastGeo.leadingAverageAnnual)}/year), with `+ `${mp2LastGeo.positiveRecipientCountries} positive-net recipient countries and `+ `${d3.format('.1%')(mp2LastGeo.topThreeShareOfPositive)} going to the three largest. `+ `This compares changes in recipient concentration as well as which countries appear on the map.`); mp2Written3.append("p").text( `Across ${mp2ActiveSummary.length} observed time periods, `+ `${mp2DistinctLeaders.length} different countries have led the recipient ranking: `+ `${mp2DistinctLeaders.join(', ')}. `+ (mp2LeaderChanges.length ? `An example of a shift is ${mp2LeaderChanges[0][0].period} to `+ `${mp2LeaderChanges[0][1].period}, when the leading country changed from `+ `${mp2LeaderChanges[0][0].leadingRecipient} to `+ `${mp2LeaderChanges[0][1].leadingRecipient}. ` : `The leading country remains the same across periods, although amounts and other rankings can change. `)+ `The highest average annual aggregate receipt is ${mp2Fmt(mp2BiggestPositiveRate.averageAnnualCommitted)}/year `+ `in ${mp2BiggestPositiveRate.period}. The map shows changes in recorded aid commitments, `+ `not which part of the world objectively needed the most assistance.`); // Additional geographic evidence, calculated from the period-summary table. const mp2GeoComparisonPeriods = [ "1973–1974", "1990–1994", "2000–2004", "2010–2013" ].map(label => mp2PeriodSummary.find(d => d.period === label)) .filter(Boolean); const mp2GeoTopThreeDetails = mp2GeoComparisonPeriods.map(p => `${p.period}: ` + p.topThree.map(country => `${country} (${mp2Fmt(mp2RecipientAnnual(p.start, country))}/year)` ).join(", ") ); mp2Written3.append("p").text( "The geographic composition of the leading recipients beyond the overall leader " + "also changed. The three largest positive-net recipients in selected periods were: " + mp2GeoTopThreeDetails.join("; ") + ". " + "These are average annual commitments, which make short first/last periods " + "comparable with complete five-year intervals." ); // Only report these regional examples when the country actually ranked top three. const mp2RegionalExamples = [ {period: "1973–1974", country: "Korea", region: "East Asia"}, {period: "1990–1994", country: "Poland", region: "Central/Eastern Europe"}, {period: "2010–2013", country: "Brazil", region: "South America"}, {period: "2010–2013", country: "South Africa", region: "southern Africa"} ].filter(d => mp2PeriodSummary.find(p => p.period === d.period) ?.topThree.includes(d.country)); if (mp2RegionalExamples.length) { mp2Written3.append("p").text( "Examples of changing geographic prominence in the reduced sample: " + mp2RegionalExamples.map(d => `${d.country} (${d.region}) was among the top three in ${d.period}` ).join("; ") + "." ); } const mp2MostDispersedPeriod = d3.least( mp2ActiveSummary, d => d.topThreeShareOfPositive ); mp2Written3.append("p").text( `Recipient concentration was not constant: the top-three share was ` + `${d3.format(".1%")(mp2FirstGeo.topThreeShareOfPositive)} in ` + `${mp2FirstGeo.period}, reached ` + `${d3.format(".1%")(mp2MostDispersedPeriod.topThreeShareOfPositive)} ` + `in ${mp2MostDispersedPeriod.period}, and was ` + `${d3.format(".1%")(mp2LastGeo.topThreeShareOfPositive)} ` + `in ${mp2LastGeo.period}. ` + `The number of positive-net recipient countries changed from ` + `${mp2FirstGeo.positiveRecipientCountries} to ` + `${mp2MostDispersedPeriod.positiveRecipientCountries} to ` + `${mp2LastGeo.positiveRecipientCountries} across those periods. ` + `This illustrates dispersion followed by reconcentration in this reduced sample; ` + `it does not establish the distribution of all worldwide aid.` ); mp2Written3.append("h3").text("Design Decisions — Visualization 3"); mp2Written3.append("p").text( "All five-year maps share the same logarithmic average-annual-USD color scale, so equal " + "monetary amounts receive equal colors even when periods differ. A separate categorical " + "legend distinguishes unrepresented countries, countries without a period record, " + "recorded net zero, and negative adjustments. A period selector enables temporal " + "comparison, while the synchronized ranked bar chart avoids the geographic area bias " + "of choropleths and shows exact country rankings. The period-summary table quantifies " + "changes in the top three countries' share, rather than inferring a shift from map colors alone."); display(mp2Written3.node());49:T585,### Sources and limitations - **Financial aid dataset:** The course's reduced AidData spreadsheet: https://docs.google.com/spreadsheets/d/1YiuHdfZv_JZ-igOemKJMRaU8dkucfmHxOP6Od3FraW8/edit. All filtering, grouping, cleaning, and five-year aggregation used by this notebook are implemented in the JavaScript cells above. No external preprocessing script was used. - **Country boundaries:** Natural Earth 1:50m country geography via World Atlas: https://cdn.jsdelivr.net/npm/world-atlas@2/countries-50m.json. - **Measurement:** USD amounts describe commitments, not verified disbursements. The file covers a reduced subset of countries, and the observed years should be read from the data audit rather than assumed from the full AidData documentation. - **Interpretation:** No record is not automatically zero aid worldwide. The maps show aid *received*, not overall poverty, disaster need, or development outcomes. The first and final five-year intervals may contain fewer than five observed years. ### AI-use disclosure I used ChatGPT (OpenAI) to help produce the JavaScript/D3 preprocessing, interactive temporal visualizations, and initial written analysis/design explanations for Mini-Project #2. I reviewed the rendered outputs, checked the data diagnostics, and revised the interpretation against the assignment questions. All code used for preprocessing and charts is included in this Observable notebook.4a:[] 38:{"id":"b1883729677c6b43","slug":"mini-project-2-temporal-data-visualization-due-nov-12th","title":"Mini-Project 2: Temporal Data Visualization (Due Nov. 12th)","thumbnail":"535487e70b84e6b1de0a613cd117fc773c1af07b09ab42dd979558cea83f61c8","access_level":"public","create_time":"$D2026-11-07T02:29:46.575Z","update_time":"$D2026-11-12T16:48:12.287Z","view_time":null,"first_public_time":"$D2026-11-12T17:00:07.565Z","has_unpublished_edits":null,"fork":{"id":"25807f4e14142959","slug":"2026-infovis-cse_project-2","title":"Mini-Project 2: Temporal Data Visualization (Due Nov. 12th)","owner":{"id":"3d6c0f5acd6a20a4","login":"rk2546","name":"rk2546"}},"stars":0,"starred":false,"owner":{"type":"team","id":"bc206b9b8872724f","login":"darsh-shani","name":"Darsh Shani","avatar_url":"https://avatars-next.observableusercontent.com/1ce79dd2cd6bf4e7444b60bab6abaa0ba4815aee224523a0075aebca4c95fcc4","tier":"starter_2024","bio":"","followed_by_you":false,"follows_you":false},"version":358,"publish_version":358,"role":null,"authored":false,"authors":[{"type":"individual","id":"a7f0428c48da7341","login":"darsh-shani","name":"Darsh Shani","avatar_url":"https://avatars-next.observableusercontent.com/1ce79dd2cd6bf4e7444b60bab6abaa0ba4815aee224523a0075aebca4c95fcc4","tier":null,"bio":"","followed_by_you":false,"follows_you":false}],"members":[{"type":"team","id":"bc206b9b8872724f","login":"darsh-shani","name":"Darsh Shani","avatar_url":"https://avatars-next.observableusercontent.com/1ce79dd2cd6bf4e7444b60bab6abaa0ba4815aee224523a0075aebca4c95fcc4","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Mini-Project 2: Temporal Data Visualization (Due Nov. 12th)","cells":[{"id":155,"value":"# Mini-Project 2: Temporal Data Visualization (Due Nov. 12th)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":162,"value":"import { css } from \"@rk2546/infovis-cse-backend\";","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":165,"value":"css","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":180,"value":"---\n## Submission Instructions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":168,"value":"$3c","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":179,"value":"---\n## About the Datasets","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":181,"value":"We have **2** datasets that you must use for this project:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":175,"value":"### Aid Data, Revisited\n\nThis spreadsheet is a simplified and reduced version of the AidData dataset. This dataset describes commitment information for over 1.5 million development finance activities funded between 1947 and 2013. The simplified dataset contains the following columns:\n\n- **`aiddata_id`**: unique ID of the commitment\n- **`aiddata_2_id`**: secondary unique ID\n- **`year`**: year of the commitment\n- **`donor`**: country providing the financial resource\n- **`recipient`**: country receiving the financial resource\n- **`commitment_amount_usd_constant`**: the total amount of financial resources provided\n- **`coalesced_purpose_code`**: categorization ID for the stated purpose of the commitment\n- **`coalesced_purpose_name`**: the purpose of the commitment","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":32,"value":"### Country GeoData\n\nWe also have the GeoJSON data for countries, derived from data from Natural Earth. This GeoJSON is actually a TopoJSON that covers country boundaries at 1:50,000,000 scale.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":182,"value":"---\n## Questions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":119,"value":"$3d","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":183,"value":"---\n## Grading Criteria","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":143,"value":"$3e","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":186,"value":"\n\n---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":184,"value":"## Students' Workspace\n\n_From this point onward, you are free to modify the notebook in any way you see fit._","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":185,"value":"import * as d3 from \"npm:d3@7\";","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":191,"value":"import * as topojson from \"npm:topojson-client@3\";","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":192,"value":"$3f","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":193,"value":"$40","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":194,"value":"## Visualization 1 — How donated and received aid changes over time\n\n**Research questions:** How have annual donated and received commitments changed for each country? Which countries primarily donate or receive, which switch roles, and when do major peaks or valleys occur?","pinned":true,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":195,"value":"$41","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":196,"value":"$42","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":197,"value":"$43","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":198,"value":"## Visualization 2 — How aid purposes change over time\n\n**Research questions:** Which 10 aid purposes receive the most money across the entire reduced dataset? How does each purpose's share change over five-year periods, and which sectors gain or lose prominence?\n\n**Measurement:** The ranking uses total **committed constant USD** by `coalesced_purpose_code`. This dataset does not verify that the money was disbursed. Five-year periods allow a more stable comparison than single-year noise.","pinned":true,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":199,"value":"$44","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":200,"value":"$45","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":201,"value":"$46","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":202,"value":"## Visualization 3 — How the geography of aid recipients changes over time\n\n**Research questions:** Do the same countries consistently receive the greatest commitments, or does aid move to different locations and recipients over time? The map shows **received** commitments only, aggregated into five-year periods.","pinned":true,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":203,"value":"$47","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":204,"value":"$48","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":205,"value":"const mp2FinalChecks = {\n records:mp2Rows.length,\n countries:mp2Countries.length,\n observedYearRange:[mp2MinYear,mp2MaxYear],\n dataExcludedByCleaning:mp2Raw.length-mp2Rows.length,\n negativeRecordsRetained:mp2Rows.filter(d=>d.amount<0).length,\n totalDonated:d3.sum(mp2CountryTotals,d=>d.donated),\n totalReceived:d3.sum(mp2CountryTotals,d=>d.received),\n differenceBetweenDonatedAndReceived:d3.sum(mp2CountryTotals,d=>d.donated)-d3.sum(mp2CountryTotals,d=>d.received),\n top10PurposeNames:mp2Top10.map(d=>d.name),\n fiveYearBins:mp2Periods.map(d=>d.label),\n mapUnmatchedCountries:mp2Unmatched,\n mapAliasCollisions:mp2Collisions,\n temporalBinsWithPartialCoverage:mp2Periods.filter(p=>!p.isFull).map(p=>`${p.label} (${p.years} years)`),\n v1RoleEventExamples:mp2RoleEvents.slice(0,3),\n v2LargestShareIncrease:mp2PurposeRise.purpose,\n v3DistinctTopRecipients:mp2DistinctLeaders,\n visualizationsPresent:[!!mp2Visualization1,!!mp2Visualization2,!!mp2Visualization3]\n};\ndisplay(mp2FinalChecks);","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":206,"value":"$49","pinned":true,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W4a","stdlib":"2"}} 33:null