2b:null 2c:["$","title",null,{"children":"PSEO Margins User Story | Jody Hoon-Starr | Observable"}] 31:T5a3,
## Overview You're a prospective PhD/AuD student looking to study Audiology, Speech-Language Pathology or perhaps about to enter the job market with a newly minted degree. You've searched the internet for salary ranges, browsed popular salary reporting sites, etc. but you're unsure whether your sources are self selection bias. You come to PSEO and are interested in finding data - maybe for your institution specifically but moreso for generic career outcomes across all institutions or across institutions within a state.
## Goals The goals here is to use the margins to provide context - instead of throwing a single row of earnings data at the user they're given the full "tree" of margins as if they walked through the data step by step. For clarity, the "tree" would be earnings for - All grads within degree level (all institutions) - All grads within 2 digit cip (all institutions) - All grads within 4 digit cip (all institutions) - All grads within 4 digit cip (all institutions instate) - Single institution 4 digit cip > Note: all margins must have a degree level - it makes no sense to compare certificate holders to doctorate holders in any context
## How the user got here Assume the user is unfamiliar with PSEO, the Census, or any statistical product in general. They've been sent a link to this page and have nothing other than an interest in doctoral programs in Audiology/SLP.32:Td44,chart = { // convert the data into a longform and filter only selected year postgrad const data = convertToLongform(earningsMargins).filter( (e) => e.yearPostgrad == yearInput ); // have this lookup so that the sort order can be defined const rowKeysLookup = new Map( data.map((d) => { const result = generateRowKeyLookup(d); return [result.id, result.label]; }) ); const sortedRowKeys = [...rowKeysLookup.keys()].sort(); const dataGrouped = d3.group(data, (d) => generateRowKeys(d)); const percentiles = new Set(data.map((d) => d.percentile)); // Specify the chart’s dimensions. const width = 928; const height = dataGrouped.size * 46; const marginTop = 30; const marginRight = 100; const marginBottom = 10; const marginLeft = 450; // scale values const min = d3.min(data.map((e) => e.earnings)); const max = d3.max(data.map((e) => e.earnings)); // Prepare the scales for positional and color encodings const x = d3 .scaleLinear() .domain([min, max]) .rangeRound([marginLeft, width - marginRight]) .nice([6]); const [xMin, xMax] = x.domain(); const y = d3 .scalePoint() .domain(sortedRowKeys.map((k) => rowKeysLookup.get(k))) .rangeRound([marginTop, height - marginBottom]) .padding(1); const color = d3 .scaleOrdinal() .domain(percentiles) .range(d3.schemeTableau10) .unknown("#ccc"); // Create the SVG container. const svg = d3 .create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "max-width: 100%; height: auto;"); // Create the x axis. svg .append("g") .attr("transform", `translate(0,${marginTop})`) .call( d3 .axisTop(x) .ticks(7) .tickFormat((d) => "$" + d3.format(".2s")(d)) ) .call((g) => g .append("text") .text("earnings →") .attr("fill", "currentColor") .attr("transform", `translate(${width - marginRight},0)`) .attr("text-anchor", "end") .attr("dy", -22) ) .call((g) => g .selectAll(".tick line") .clone() .attr("stroke-opacity", 0.1) .attr("y2", height - marginBottom) ) .call((g) => g.selectAll(".domain").remove()); // Add a g container for each group const g = svg .append("g") .attr("text-anchor", "end") .style("font", "14px sans-serif") .selectAll() .data(dataGrouped) .join("g") .attr("transform", ([key]) => `translate(0,${y(key)})`); // Append a grey line to each container. g.append("line") .attr("stroke", "#aaa") .attr("stroke-width", 3) .attr("x1", ([, values]) => x(d3.min(values, (d) => d.earnings))) .attr("x2", ([, values]) => x(d3.max(values, (d) => d.earnings))); // Append the dots to each container. g.append("g") .selectAll() .data(([, values]) => values) .join("circle") .attr("cx", (d) => x(d.earnings)) .attr("fill", (d) => color(d.percentile)) .attr("stroke", "white") .attr("stroke-width", "2") .attr("r", 9); // Append the label to each container. g.append("text") .attr("dy", "0.35em") .attr("x", () => x(xMin) - 6) .text(([group, values]) => group); // Expose the color scale for a legend. return Object.assign(svg.node(), { scales: { color } }); }33:Tde0,chartInstMargins = { // convert the data into a longform and filter only selected year postgrad const data = convertToLongform(selectInstitutionAndMarginsData).filter( (e) => e.yearPostgrad == yearInputInst ); // have this lookup so that the sort order can be defined const rowKeysLookup = new Map( data.map((d) => { const result = generateRowKeyLookupInst(d); return [result.id, result.label]; }) ); const sortedRowKeys = [...rowKeysLookup.keys()].sort(); const dataGrouped = d3.group(data, (d) => generateRowKeysInst(d)); const percentiles = new Set(data.map((d) => d.percentile)); // Specify the chart’s dimensions. const width = 928; const height = dataGrouped.size * 46; const marginTop = 30; const marginRight = 100; const marginBottom = 10; const marginLeft = 450; // scale values const min = d3.min(data.map((e) => e.earnings)); const max = d3.max(data.map((e) => e.earnings)); // Prepare the scales for positional and color encodings const x = d3 .scaleLinear() .domain([min, max]) .rangeRound([marginLeft, width - marginRight]) .nice(); const [xMin, xMax] = x.domain(); const y = d3 .scalePoint() .domain(sortedRowKeys.map((k) => rowKeysLookup.get(k))) .rangeRound([marginTop, height - marginBottom]) .padding(1); const color = d3 .scaleOrdinal() .domain(percentiles) .range(d3.schemeTableau10) .unknown("#ccc"); // Create the SVG container. const svg = d3 .create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "max-width: 100%; height: auto;"); // Create the x axis. svg .append("g") .attr("transform", `translate(0,${marginTop})`) .call( d3 .axisTop(x) .ticks(7) .tickFormat((d) => "$" + d3.format(".2s")(d)) ) .call((g) => g .append("text") .text("earnings →") .attr("fill", "currentColor") .attr("transform", `translate(${width - marginRight},0)`) .attr("text-anchor", "end") .attr("dy", -22) ) .call((g) => g .selectAll(".tick line") .clone() .attr("stroke-opacity", 0.1) .attr("y2", height - marginBottom) ) .call((g) => g.selectAll(".domain").remove()); // Add a g container for each group const g = svg .append("g") .attr("text-anchor", "end") .style("font", "14px sans-serif") .selectAll() .data(dataGrouped) .join("g") .attr("transform", ([key]) => `translate(0,${y(key)})`); // Append a grey line to each container. g.append("line") .attr("stroke", "#aaa") .attr("stroke-width", 3) .attr("x1", ([, values]) => x(d3.min(values, (d) => d.earnings))) .attr("x2", ([, values]) => x(d3.max(values, (d) => d.earnings))); // Append the dots to each container. g.append("g") .selectAll() .data(([, values]) => values) .join("circle") .attr("cx", (d) => x(d.earnings)) .attr("fill", (d) => color(d.percentile)) .attr("fill-opacity", (d) => (d.earnings ? "1" : "0")) .attr("stroke", "white") .attr("stroke-width", "2") .attr("stroke-opacity", (d) => (d.earnings ? "1" : "0")) .attr("r", 9); // Append the label to each container. g.append("text") .attr("dy", "0.35em") .attr("x", () => x(xMin) - 6) .text(([group, values]) => group); // Expose the color scale for a legend. return Object.assign(svg.node(), { scales: { color } }); }34:Tdf5,chartInstSingle = { // convert the data into a longform and filter only selected year postgrad const data = convertToLongform(earningsTexas).filter( (e) => e.institution_label == selectInstitution ); // have this lookup so that the sort order can be defined const values = { y1: "1 year postgrad", y5: "5 years postgrad", y10: "10 years postgrad" }; const rowKeysLookup = new Map(Object.entries(values)); const sortedRowKeys = [...rowKeysLookup.keys()]; const dataGrouped = d3.group(data, (d) => d.yearPostgrad); const percentiles = new Set(data.map((d) => d.percentile)); // Specify the chart’s dimensions. const width = 928; const height = dataGrouped.size * 46; const marginTop = 30; const marginRight = 100; const marginBottom = 10; const marginLeft = 450; // scale values const min = d3.min(data.map((e) => e.earnings)); const max = d3.max(data.map((e) => e.earnings)); // Prepare the scales for positional and color encodings const x = d3 .scaleLinear() .domain([min, max]) .rangeRound([marginLeft, width - marginRight]) .nice(); const [xMin, xMax] = x.domain(); const y = d3 .scalePoint() .domain(sortedRowKeys.map((k) => rowKeysLookup.get(k))) .rangeRound([marginTop, height - marginBottom]) .padding(1); const color = d3 .scaleOrdinal() .domain(percentiles) .range(d3.schemeTableau10) .unknown("#ccc"); // Create the SVG container. const svg = d3 .create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "max-width: 100%; height: auto;"); // Create the x axis. svg .append("g") .attr("transform", `translate(0,${marginTop})`) .call( d3 .axisTop(x) .ticks(7) .tickFormat((d) => "$" + d3.format(".2s")(d)) ) .call((g) => g .append("text") .text("earnings →") .attr("fill", "currentColor") .attr("transform", `translate(${width - marginRight},0)`) .attr("text-anchor", "end") .attr("dy", -22) ) .call((g) => g .selectAll(".tick line") .clone() .attr("stroke-opacity", 0.1) .attr("y2", height - marginBottom) ) .call((g) => g.selectAll(".domain").remove()); // Add a g container for each group const g = svg .append("g") .attr("text-anchor", "end") .style("font", "14px sans-serif") .selectAll() .data(dataGrouped) .join("g") .attr("transform", ([key]) => `translate(0,${y(rowKeysLookup.get(key))})`); // Append a grey line to each container. g.append("line") .attr("stroke", "#aaa") .attr("stroke-width", 3) .attr("x1", ([, values]) => x(d3.min(values, (d) => d.earnings))) .attr("x2", ([, values]) => x(d3.max(values, (d) => d.earnings))); // Append the dots to each container. g.append("g") .selectAll() .data(([, values]) => values) .join("circle") .attr("cx", (d) => x(d.earnings)) .attr("fill", (d) => color(d.percentile)) .attr("fill-opacity", (d) => (d.earnings ? "1" : "0")) .attr("stroke", "white") .attr("stroke-width", "2") .attr("stroke-opacity", (d) => (d.earnings ? "1" : "0")) .attr("r", 9); // Append the label to each container. g.append("text") .attr("dy", "0.35em") .attr("x", () => x(xMin) - 6) .text(([group, values]) => rowKeysLookup.get(group)); // Expose the color scale for a legend. return Object.assign(svg.node(), { scales: { color } }); }35:T1629,

--- ## For Posterity: Creating the margins used above The following snippet shows how the y1 margins were created from the existing public use data files. y5, y10, and ipeds counts vars were excluded for brevity. They're essentially the exact same operation but on different variables. > Note: these margins ignore any status flags != 1 (aka are only calculated on "good" data) ```sql -- take the original pseoe table as used by explore and aggregate it to the institution level -- this means commenting out anything related to the institution -- agg_level_pseo, -- inst_level, -- institution, -- institution_label, -- institution_statefips, -- institution_statefips_label, -- create an empty table that's identical to the pseoe DROP TABLE IF EXISTS agg.earnings_all_inst; CREATE TABLE agg.earnings_all_inst (LIKE earnings.data INCLUDING ALL); WITH main as ( SELECT DISTINCT degree_level, cip_level, cipcode, grad_cohort, grad_cohort_years, geo_level, geography, ind_level, industry, degree_level_label, cipcode_label, grad_cohort_label, grad_cohort_id FROM earnings.data ), y1 AS ( SELECT -- agg_level_pseo, -- inst_level, -- institution, degree_level, cip_level, cipcode, grad_cohort, grad_cohort_years, geo_level, geography, ind_level, industry, (SUM(y1_p25_earnings * y1_grads_earn::bigint) / SUM(y1_grads_earn::bigint))::int AS y1_p25_earnings, (SUM(y1_p50_earnings * y1_grads_earn::bigint) / SUM(y1_grads_earn::bigint))::int AS y1_p50_earnings, (SUM(y1_p75_earnings * y1_grads_earn::bigint) / SUM(y1_grads_earn::bigint))::int AS y1_p75_earnings, (SUM(y1_grads_earn::bigint))::int AS y1_grads_earn, -- y5_p25_earnings, -- y5_p50_earnings, -- y5_p75_earnings, -- y5_grads_earn, -- y10_p25_earnings, -- y10_p50_earnings, -- y10_p75_earnings, -- y10_grads_earn, -- y1_ipeds_count, -- y5_ipeds_count, -- y10_ipeds_count, status_y1_earnings, status_y1_grads_earn, -- status_y5_earnings, -- status_y5_grads_earn, -- status_y10_earnings, -- status_y10_grads_earn, -- status_y1_ipeds_count, -- status_y5_ipeds_count, -- status_y10_ipeds_count, degree_level_label, cipcode_label, -- institution_label, grad_cohort_label, grad_cohort_id -- institution_statefips, -- institution_statefips_label FROM earnings.data WHERE status_y1_earnings = 1 AND status_y1_grads_earn = 1 GROUP BY -- agg_level_pseo, -- inst_level, -- institution, degree_level, cip_level, cipcode, grad_cohort, grad_cohort_years, geo_level, geography, ind_level, industry, -- y1_p25_earnings, -- y1_p50_earnings, -- y1_p75_earnings, -- y1_grads_earn, -- y5_p25_earnings, -- y5_p50_earnings, -- y5_p75_earnings, -- y5_grads_earn, -- y10_p25_earnings, -- y10_p50_earnings, -- y10_p75_earnings, -- y10_grads_earn, -- y1_ipeds_count, -- y5_ipeds_count, -- y10_ipeds_count, status_y1_earnings, status_y1_grads_earn, -- status_y5_earnings, -- status_y5_grads_earn, -- status_y10_earnings, -- status_y10_grads_earn, -- status_y1_ipeds_count, -- status_y5_ipeds_count, -- status_y10_ipeds_count, degree_level_label, cipcode_label, -- institution_label, grad_cohort_label, grad_cohort_id -- institution_statefips, -- institution_statefips_label ), --...etc for y5/y10/ipeds INSERT INTO agg.earnings_all_inst -- the actual query, filled with constants SELECT 'ZZ' as agg_level_pseo, '00' as inst_level, '00' as institution, main.degree_level, main.cip_level, main.cipcode, main.grad_cohort, main.grad_cohort_years, main.geo_level, main.geography, main.ind_level, main.industry, y1.y1_p25_earnings, y1.y1_p50_earnings, y1.y1_p75_earnings, y1.y1_grads_earn, y5.y5_p25_earnings, y5.y5_p50_earnings, y5.y5_p75_earnings, y5.y5_grads_earn, y10.y10_p25_earnings, y10.y10_p50_earnings, y10.y10_p75_earnings, y10.y10_grads_earn, y1_ipeds.y1_ipeds_count, y5_ipeds.y5_ipeds_count, y10_ipeds.y10_ipeds_count, y1.status_y1_earnings, y1.status_y1_grads_earn, y5.status_y5_earnings, y5.status_y5_grads_earn, y10.status_y10_earnings, y10.status_y10_grads_earn, y1_ipeds.status_y1_ipeds_count, y5_ipeds.status_y5_ipeds_count, y10_ipeds.status_y10_ipeds_count, main.degree_level_label, main.cipcode_label, 'All Institutions' as institution_label, main.grad_cohort_label, main.grad_cohort_id, '00' as institution_statefips, 'All States' as institution_statefips_label FROM main LEFT JOIN y1 USING(degree_level, cip_level, cipcode, grad_cohort, grad_cohort_years, geo_level, geography, ind_level, industry) -- ...etc for y10/ipeds vars 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\n## Disclaimer\n\nThis is an overly simplified demo. \n\nNone of this is intended to replace PSEO Explorer. Explorer can fit margins in by allowing \"All States\" and/or \"All Institutions\" as a valid selection in the dropdowns.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":593,"value":"
\n\n## Why change the form for presenting pseo data?\n\nExplorer doesn't give context to the data\n- How many grads contributed to the margin?\n- How many institutions contributed to the margin?\n\nUsing these margins as intended requires more explanation than explorer is able to provide. This context provides the ability to do some interesting things. We'll talk about this later but that's the gist.\n\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":22,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":42,"value":"

\n\n---\n\n## Data used\n\nThis data has been generated using the existing public use PSEO data files. The `pseoe_all` file was aggregated to \n- `Degree Level x All Institutions`\n- `Degree Level x All Institutions x State`\n\nTwo attached files contain the information used here\n- `aud.csv` - margins for CIP 5102, its parent CIP 51, and CIP 00 All\n- `aud_tx.csv` - standard pseoe data for Texas CIP 5102\n- `aud_time.csv` - are margins over time, aka grad_cohort ! '0000'\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":50,"value":"---\n \nThe data has already been filtered for a single `degree_level`: \n**${degreeLevel}** for **${gradCohort}**\n\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":13,"value":"Inputs.table(earningsMargins, {\n columns: [\n \"institution_label\",\n \"institution_statefips_label\",\n \"cipcode\",\n \"cipcode_label\"\n ],\n sort: \"cipcode\",\n reverse: false\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":83,"value":"

\n\n--- \n\n## Margins Viz\n\nAllow the higher-level margins to provide context when not looking at an individual institution","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":339,"value":"

\n## Earnings for Grads with a ${degreeLevel} Degree","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":85,"value":"viewof yearInput = Inputs.radio([\"y1\", \"y5\", \"y10\"], {\n value: \"y5\",\n label: \"Years Postgrad\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":90,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":284,"value":"Legend(chart.scales.color, { title: \"Earnings Percentile\", tickSize: 0 })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":351,"value":"

\n\n---\n\n## Institutions Viz\n\nInstead of horseracing institutions use the margins for comparison.\n\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":367,"value":"\n> NOTE: the ability to toggle between institutions (as seen below) **WOULD NOT** be available. You'd just see a page for a single institution. It's only here so we can examine drawbacks.\n\n
\n\nTexas Institutions offering \n`${degreeLevel}` degrees \nin `Communication Disorders Sciences and Services`\n\n
\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":358,"value":"viewof selectInstitution = Inputs.select([].concat(texasInstitutions), {\n label: \"Institutions\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":403,"value":"viewof yearInputInst = Inputs.radio([\"y1\", \"y5\", \"y10\"], {\n value: \"y5\",\n label: \"Years Postgrad\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":390,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":409,"value":"Legend(chartInstMargins.scales.color, {\n title: \"Earnings Percentile\",\n tickSize: 0\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":419,"value":"

\n\n---\n\n## No Margins\n\nWe can always use this format to show the 9 cell grid for a single institution. Ideally this would be in tandem with the margins comparison above.\n\n
\n\n`${selectInstitution}` \n`${degreeLevel}` degrees \nin `Communication Disorders Sciences and Services`\n\n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":422,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":463,"value":"Legend(chartInstSingle.scales.color, {\n title: \"Earnings Percentile\",\n tickSize: 0\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":467,"value":"

\n\n---\n## More margins\n\nAudiologist is a good example here because it's arguable that the currently published 2/4-digit CIP codes aren't detailed enough for our case study\n\nThe hierarchy is as follows\n- 00 All Programs\n- 51 Health Professions and Related Clinical Sciences.\n- 51.02 Communication Disorders Sciences and Services.\n- 51.0202 Audiology/Audiologist and Hearing Sciences.\n\n### The ask: \n\nCan/should the app compare against margins in lieu of horseracing programs/institutions?\n\n### The big ask:\n\nCan we publish 6 digit CIPs across all institutions as a margin?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":511,"value":"
\n\n---\n## Counts over Time\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":538,"value":"viewof yearInputOverTime = Inputs.radio([\"y1\", \"y5\", \"y10\"], {\n value: \"y5\",\n label: \"Years Postgrad\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":576,"value":"### The above data is based on ${totalGradCount} employed grads with a `${degreeLevel}` degree in `Communication Disorders Sciences and Services`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":523,"value":"Plot.plot({\n inset: 10,\n x: {\n label: \"Graduation Year\"\n },\n y: {\n label: \"Number of Grads\",\n grid: true,\n domain: [\n 0,\n d3.max(earningsMarginsOverTimeLongform.map((e) => e.grads)) * 1.2\n ]\n },\n marks: [\n Plot.ruleY([0]),\n Plot.line(\n earningsMarginsOverTimeLongform.filter(\n (e) => e.yearPostgrad === yearInputOverTime\n ),\n {\n x: \"grad_cohort_label\",\n y: \"grads\",\n marker: true\n }\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":480,"value":"$35","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":33,"value":"---\n## Helper functions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":9,"value":"earningsMargins = d3.csvParse(await FileAttachment(\"aud@3.csv\").text(), (d) => {\n return {\n ...d,\n y1_p25_earnings: d.y1_p25_earnings ? +d.y1_p25_earnings : null,\n y1_p50_earnings: d.y1_p50_earnings ? +d.y1_p50_earnings : null,\n y1_p75_earnings: d.y1_p75_earnings ? +d.y1_p75_earnings : null,\n y1_grads_earn: d.y1_grads_earn ? +d.y1_grads_earn : null,\n y5_p25_earnings: d.y5_p25_earnings ? +d.y5_p25_earnings : null,\n y5_p50_earnings: d.y5_p50_earnings ? +d.y5_p50_earnings : null,\n y5_p75_earnings: d.y5_p75_earnings ? +d.y5_p75_earnings : null,\n y5_grads_earn: d.y5_grads_earn ? +d.y5_grads_earn : null,\n y10_p25_earnings: d.y10_p25_earnings ? +d.y10_p25_earnings : null,\n y10_p50_earnings: d.y10_p50_earnings ? +d.y10_p50_earnings : null,\n y10_p75_earnings: d.y10_p75_earnings ? +d.y10_p75_earnings : null,\n y10_grads_earn: d.y10_grads_earn ? +d.y10_grads_earn : null\n };\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":70,"value":"earningsTexas = d3.csvParse(await FileAttachment(\"aud_tx.csv\").text(), (d) => {\n return {\n ...d,\n y1_p25_earnings: d.y1_p25_earnings ? +d.y1_p25_earnings : null,\n y1_p50_earnings: d.y1_p50_earnings ? +d.y1_p50_earnings : null,\n y1_p75_earnings: d.y1_p75_earnings ? +d.y1_p75_earnings : null,\n y1_grads_earn: d.y1_grads_earn ? +d.y1_grads_earn : null,\n y5_p25_earnings: d.y5_p25_earnings ? +d.y5_p25_earnings : null,\n y5_p50_earnings: d.y5_p50_earnings ? +d.y5_p50_earnings : null,\n y5_p75_earnings: d.y5_p75_earnings ? +d.y5_p75_earnings : null,\n y5_grads_earn: d.y5_grads_earn ? +d.y5_grads_earn : null,\n y10_p25_earnings: d.y10_p25_earnings ? +d.y10_p25_earnings : null,\n y10_p50_earnings: d.y10_p50_earnings ? +d.y10_p50_earnings : null,\n y10_p75_earnings: d.y10_p75_earnings ? +d.y10_p75_earnings : null,\n y10_grads_earn: d.y10_grads_earn ? +d.y10_grads_earn : null\n };\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":515,"value":"earningsMarginsOverTime = d3.csvParse(\n await FileAttachment(\"aud_time.csv\").text(),\n (d) => {\n return {\n ...d,\n y1_p25_earnings: d.y1_p25_earnings ? +d.y1_p25_earnings : null,\n y1_p50_earnings: d.y1_p50_earnings ? +d.y1_p50_earnings : null,\n y1_p75_earnings: d.y1_p75_earnings ? +d.y1_p75_earnings : null,\n y1_grads_earn: d.y1_grads_earn ? +d.y1_grads_earn : null,\n y5_p25_earnings: d.y5_p25_earnings ? +d.y5_p25_earnings : null,\n y5_p50_earnings: d.y5_p50_earnings ? +d.y5_p50_earnings : null,\n y5_p75_earnings: d.y5_p75_earnings ? +d.y5_p75_earnings : null,\n y5_grads_earn: d.y5_grads_earn ? +d.y5_grads_earn : null,\n y10_p25_earnings: d.y10_p25_earnings ? +d.y10_p25_earnings : null,\n y10_p50_earnings: d.y10_p50_earnings ? +d.y10_p50_earnings : null,\n y10_p75_earnings: d.y10_p75_earnings ? +d.y10_p75_earnings : null,\n y10_grads_earn: d.y10_grads_earn ? +d.y10_grads_earn : null\n };\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":562,"value":"totalGradCount = convertToLongformTimeSeries(earningsMargins).filter(\n (e) =>\n e.yearPostgrad === yearInputOverTime &&\n e.cipcode === \"5102\" &&\n e.institution_statefips === \"00\"\n)[0].grads","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":557,"value":"earningsMarginsOverTimeLongform = convertToLongformTimeSeries(\n earningsMarginsOverTime\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":354,"value":"texasInstitutions = [...new Set(earningsTexas.map((e) => e.institution_label))]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":383,"value":"selectInstitutionAndMarginsData = [\n ...earningsMargins.filter((d) => d.cipcode == \"5102\"),\n ...earningsTexas.filter((d) => d.institution_label == selectInstitution)\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":199,"value":"convertToLongform = (data) =>\n data.flatMap((d) => {\n return [\"y1\", \"y5\", \"y10\"].flatMap((y) => {\n return [\"p25\", \"p50\", \"p75\"].flatMap((p) => {\n return {\n institution: d.institution,\n institution_label: d.institution_label,\n institution_statefips: d.institution_statefips,\n institution_statefips_label: d.institution_statefips_label,\n cipcode: d.cipcode,\n cipcode_label: d.cipcode_label,\n degree_level: d.degree_level,\n degree_level_label: d.degree_level_label,\n grad_cohort: d.grad_cohort,\n grad_cohort_label: d.grad_cohort_label,\n yearPostgrad: y,\n percentile: p,\n earnings: d[`${y}_${p}_earnings`]\n };\n });\n });\n })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":520,"value":"convertToLongformTimeSeries = (data) =>\n data.flatMap((d) => {\n return [\"y1\", \"y5\", \"y10\"].flatMap((y) => {\n return {\n institution: d.institution,\n institution_label: d.institution_label,\n institution_statefips: d.institution_statefips,\n institution_statefips_label: d.institution_statefips_label,\n cipcode: d.cipcode,\n cipcode_label: d.cipcode_label,\n degree_level: d.degree_level,\n degree_level_label: d.degree_level_label,\n grad_cohort: d.grad_cohort,\n grad_cohort_label: d.grad_cohort_label,\n yearPostgrad: y,\n grads: d[`${y}_grads_earn`]\n };\n });\n })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":24,"value":"function getDistinctValues(arr, property) {\n const distinctValues = new Set();\n\n arr.forEach((obj) => {\n if (obj.hasOwnProperty(property)) {\n distinctValues.add(obj[property]);\n }\n });\n\n return Array.from(distinctValues);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":172,"value":"generateRowKeys = (d) => `${d.cipcode_label} (${d.institution_statefips_label})`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":297,"value":"generateRowKeyLookup = (d) => ({\n id: `${d.institution_statefips}-${d.cipcode}`,\n label: generateRowKeys(d)\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":395,"value":"generateRowKeysInst = (d) =>\n `${d.institution_label} (${d.institution_statefips_label})`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":392,"value":"generateRowKeyLookupInst = (d) => ({\n id: `${d.institution_statefips}-${d.institution}`,\n label: generateRowKeysInst(d)\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":27,"value":"degreeLevel = getDistinctValues(earningsMargins, \"degree_level_label\")[0]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"gradCohort = getDistinctValues(earningsMargins, \"grad_cohort_label\")[0]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":286,"value":"import { Legend } from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W36","stdlib":"1"}} 30:"$2f:body"