2e:null 2f:["$","title",null,{"children":"Salary analysis | senritsu | Observable"}] 34:Ta9c,Plot.plot({ color: { type: "ordinal", scheme: 'category10', legend: true }, marks: [ Plot.frame(), ...(graphDisplayOptions.includes('median') ? Object.values(medianValues) : []).map(x => [ Plot.ruleX([x], {x: 'hours', stroke: "rgba(0, 100, 0, 0.2)", strokeWidth: 5}), Plot.ruleY([x], {y: calculateHourly, stroke: "rgba(0, 100, 0, 0.2)", strokeWidth: 5}), Plot.text([x], {x: 'hours', y: calculateHourly, fill: 'rgba(0, 100, 0, 0.5)', text: d => 'median', dx: -25, dy: 10}), ]), // synthetic salary bands Plot.line(hourlySalaryData, {x: "hours", y: "salary", stroke: 'yearlySalary', opacity: graphDisplayOptions.includes('bands') ? 1 : 0.1}), // hypothetical Plot.ruleX([hypothetical], {x: 'hours', stroke: "darkviolet", strokeWidth: 2}), Plot.ruleY([hypothetical], {y: calculateHourly, stroke: "darkviolet", strokeWidth: 2}), Plot.text([hypothetical], {x: 'hours', y: calculateHourly, fill: 'darkviolet', text: d => 'hypothetical', dx: 30, dy: 10}), // hypothetical experimental Plot.ruleY([hourlySalaryFromYearlySalary(hypothetical.yearlySalary, hypothetical.hours) * vacationAdjustment], {stroke: "pink", strokeWidth: 1}), // current Plot.ruleX([current], {x: 'hours', stroke: "goldenrod", strokeWidth: 1}), Plot.ruleY([current], {y: calculateHourly, stroke: "goldenrod", strokeWidth: 1}), Plot.text([current], {x: 'hours', y: calculateHourly, fill: 'goldenrod', text: d => 'current', dx: -20, dy: 10}), // igm base ...(graphDisplayOptions.includes('IGM') ? [ Plot.ruleY(igmBrackets, {y: d => igmHourlyBase[d], stroke: "gray"}), Plot.text(igmBrackets, { x: d => 37.5 + igmBrackets.indexOf(d) * 1, y: d => igmHourlyBase[d], text: d => `${d} base`, dy: -7, fill: 'gray' }), Plot.ruleX(igmBrackets, { x: d => 37 + igmBrackets.indexOf(d) * 1, y1: d => igmHourlyBase[d], y2: d => igmHourlyRealistic[d].avg, stroke: 'gray', strokeWidth: 1, strokeLinecap: "round" }), // igm average Plot.ruleY(igmBrackets, {y: d => igmHourlyRealistic[d].avg, stroke: "rgba(0, 0, 0, 0.25)", strokeWidth: 3}), Plot.text(igmBrackets, { x: d => 37.5 + igmBrackets.indexOf(d) * 1, y: d => igmHourlyRealistic[d].avg, text: d => `${d} avg`, dy: -7, fill: 'black' }), // igm realistic Plot.ruleX(igmBrackets, { x: d => 37 + igmBrackets.indexOf(d) * 1, y1: d => igmHourlyRealistic[d].min, y2: d => igmHourlyRealistic[d].max, stroke: 'rgba(0, 0, 0, 0.25)', strokeWidth: 10, strokeLinecap: "round" }) ] : []) ] })35:T636,md`## Quantified changes ${summaryRow('Weekly time', 'hours', {smallerIsBetter: true, unit: 'h'})} ${summaryRow('Vacation days', 'vacationDays', {unit: 'days'})} ${summaryRow('Yearly salary', 'yearlySalary', {unit: '€', includeInflation: true, round: 0})} ${summaryRow('', 'yearlySalary', {unit: '%', includeInflation: true, round: 1, percent: true})} ${summaryRow('Hourly salary', x => hourlySalaryFromYearlySalary(x.yearlySalary, x.hours), {unit: '€/h', includeInflation: true, round: 2})} ${summaryRow('', x => hourlySalaryFromYearlySalary(x.yearlySalary, x.hours), {unit: '%', includeInflation: true, round: 1, percent: true})} ${summaryRow('Vacation value', x => vacationDayValue(x) * x.vacationDays, {unit: '€', includeInflation: true, round: 0, experimental: true})} ${summaryRow('', vacationDayValue, {unit: '€/day', includeInflation: true, round: 0})}

		202X	2022-202X	2022	${startYear}-2022	${startYear}	${startYear}-202X

(...) Inflation-adjusted

⚠ experimental

`36:T63c,summaryRow = (label, accessor, {round, unit, smallerIsBetter, includeInflation, percent, experimental}) => { const maybeRound = x => round !== undefined ? x.toFixed(round) : x const getRaw = collection => typeof accessor === 'string' ? collection[accessor] : accessor(collection) const get = (collection, useInflation) => useInflation ? getRaw(collection) * historicalInflation : getRaw(collection) const val = (collection, useInflation) => maybeRound(get(collection, useInflation)) const diffRaw = (a, b, useInflation) => percent ? 100 * ((get(a) / get(b, useInflation)) - 1) : get(a) - get(b, useInflation) const diff = (a, b, useInflation) => renderChange(maybeRound(diffRaw(a, b, useInflation)), '', smallerIsBetter) return htl.html.fragment` ${label}${experimental ? htl.html.fragment` ⚠` : ''} [${unit}] ${percent ? '' : val(hypothetical)} ${diff(hypothetical, current)} ${percent ? '' : val(current)} ${diff(current, original)}${includeInflation ? htl.html.fragment` (${diff(current, original, true)})` : ''} ${percent ? '' : val(original)}${!percent && includeInflation ? htl.html.fragment` (${val(original, true)})` : ''} ${diff(hypothetical, original)}${includeInflation ? htl.html.fragment` (${diff(hypothetical, original, true)})` : ''} ` }37:[] 32:{"id":"3a5059c248de30fc","slug":"salary-analysis","title":"Salary analysis","thumbnail":"09dc98c6b7e7495ccbd78153d6051dcce507e36c5b7479b02705563c33a6d3aa","access_level":"public","create_time":"$D2021-12-15T19:51:08.670Z","update_time":"$D2022-02-07T08:28:07.071Z","view_time":null,"first_public_time":"$D2022-02-07T08:04:59.744Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"c62aba2ac21021cb","login":"senritsu","name":"","avatar_url":"https://avatars-next.observableusercontent.com/2702f8a42e439426df2d134af708f1c3c3bdfa1a8434dfbeec26dfd7ce6bdcec","tier":"starter_2024"},"version":1186,"publish_version":1186,"role":null,"authored":false,"authors":[{"type":"individual","id":"cc9712af774c2953","login":"senritsu","name":"","avatar_url":"https://avatars-next.observableusercontent.com/2702f8a42e439426df2d134af708f1c3c3bdfa1a8434dfbeec26dfd7ce6bdcec","tier":null}],"members":[{"type":"individual","id":"cc9712af774c2953","login":"senritsu","name":"","avatar_url":"https://avatars-next.observableusercontent.com/2702f8a42e439426df2d134af708f1c3c3bdfa1a8434dfbeec26dfd7ce6bdcec","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Salary analysis","cells":[{"id":390,"value":"# Salary analysis\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1052,"value":"Personal model configuration stays local-only and is not cloud-shared. Click ${htl.html`here`} to download a template to fill out. Until a file is uploaded, the template will be used for the notebook.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1039,"value":"viewof uploadedPersonalData = Inputs.file({label: \"Personal data\", accept: \".json\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1119,"value":"uploadedPersonalData ? htl.html`