2b:null 2c:["$","title",null,{"children":"PSEO Margins Over Time | Jody Hoon-Starr | Observable"}] 31:T4c9,The examples seen below are a continuation of the work in the [PSEO Margins Overview](https://observablehq.com/d/645590ed20692432). The goal here is to explore how changes over time in the [PSEO data](https://lehd.ces.census.gov/data/pseo_experimental.html) can be communicated and whether there are valid comparisons against the margins. As the PSEO program grows, and the years go past, we collect more graduate information. This allows to look back and see what has changed with regards to the employment of graduates at various points in their career. Looking at change over time is a significant weakness of [PSEO Explorer](https://lehd.ces.census.gov/applications/pseo/). What's seen below is a test ground for future iterations and tools. The data seen below continues as if the user is interested in *Communication Disorders* but makes one major change from the previous examples in the margins overview. In order to view changes over time we need a handful of grad cohorts to make a useful trend. The doctoral cohorts are in 5-year intervals which only allows for 2 or 3 points in time. Below we switch to look at bachelor's degree holders in *Communication Disorders* so that the cohorts are in 3-year intervals. 32:T439,Plot.plot({ height: 280, inset: 10, x: { label: "Graduation Year" }, y: { label: "Earnings", grid: true, domain: [ 0, d3.max(earningsBAMarginsOverTimeLongform.map((e) => e.p75_earnings)) * 1.2 ], tickFormat: "~s" }, marks: [ Plot.ruleY([0]), Plot.line( earningsBAMarginsOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputOverTime ), { x: "grad_cohort_label", y: "p25_earnings", marker: true, stroke: colorScheme.p25 } ), Plot.line( earningsBAMarginsOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputOverTime ), { x: "grad_cohort_label", y: "p50_earnings", marker: true, stroke: colorScheme.p50 } ), Plot.line( earningsBAMarginsOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputOverTime ), { x: "grad_cohort_label", y: "p75_earnings", marker: true, stroke: colorScheme.p75 } ) ] })33:T44f,Plot.plot({ height: 280, inset: 10, x: { label: "Graduation Year" }, y: { label: "Earnings", grid: true, domain: [ 0, d3.max(earningsCSBAMarginsOverTimeLongform.map((e) => e.p75_earnings)) * 1.2 ], tickFormat: "~s" }, marks: [ Plot.ruleY([0]), Plot.line( earningsCSBAMarginsOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputOverTimeCS ), { x: "grad_cohort_label", y: "p25_earnings", marker: true, stroke: colorScheme.p25 } ), Plot.line( earningsCSBAMarginsOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputOverTimeCS ), { x: "grad_cohort_label", y: "p50_earnings", marker: true, stroke: colorScheme.p50 } ), Plot.line( earningsCSBAMarginsOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputOverTimeCS ), { x: "grad_cohort_label", y: "p75_earnings", marker: true, stroke: colorScheme.p75 } ) ] })34:Tb3f,Plot.plot({ height: 380, inset: 10, x: { label: "Graduation Year" }, y: { label: "Earnings", grid: true, domain: [ 0, d3.max([ ...earningsTexasOverTimeLongform .filter((e) => e.yearPostgrad === yearInputTexas) .map((e) => e.p75_earnings), earningsCSBAMarginsOverTimeLongform .filter((e) => e.yearPostgrad === yearInputTexas) .map((e) => e.p75_earnings) ]) * 1.2 ], tickFormat: "~s" }, marks: [ Plot.ruleY([0]), Plot.line( earningsCSBAMarginsOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputTexas ), { x: "grad_cohort_label", y: "p25_earnings", marker: true, stroke: colorScheme.p25 } ), Plot.line( earningsTexasOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputTexas && e.institution_label === selectInstitution ), { x: "grad_cohort_label", y: "p25_earnings", marker: (color) => htl.svg``, stroke: colorScheme.p25, strokeDasharray: [2, 4] } ), Plot.line( earningsCSBAMarginsOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputTexas ), { x: "grad_cohort_label", y: "p50_earnings", marker: true, stroke: colorScheme.p50 } ), Plot.line( earningsTexasOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputTexas && e.institution_label === selectInstitution ), { x: "grad_cohort_label", y: "p50_earnings", marker: (color) => htl.svg``, stroke: colorScheme.p50, strokeDasharray: [2, 4] } ), Plot.line( earningsCSBAMarginsOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputTexas ), { x: "grad_cohort_label", y: "p75_earnings", marker: true, stroke: colorScheme.p75 } ), Plot.line( earningsTexasOverTimeLongform.filter( (e) => e.yearPostgrad === yearInputTexas && e.institution_label === selectInstitution ), { x: "grad_cohort_label", y: "p75_earnings", marker: (color) => htl.svg``, stroke: colorScheme.p75, strokeDasharray: [2, 4] } ) ] })35:T61f,Plot.plot({ height: 380, inset: 10, x: { label: "Graduation Year", domain: [ ...new Set( earningsCSBAMarginsOverTimeLongformEmploymentYear.map( (e) => e.employment_year_label ) ) ] .filter((o) => { return parseInt(o.substring(0, 4)) <= 2018; }) .sort((a, b) => parseInt(a.substring(0, 4)) > parseInt(b.substring(0, 4))) }, y: { label: "Earnings", grid: true, domain: [ 0, d3.max( earningsCSBAMarginsOverTimeLongformEmploymentYear.map( (e) => e.p75_earnings ) ) * 1.2 ], tickFormat: "~s" }, marks: [ Plot.ruleY([0]), Plot.line( earningsCSBAMarginsOverTimeLongformEmploymentYear.filter( (e) => e.yearPostgrad === yearInputOverTimeCSEmploymentYear ), { x: "employment_year_label", y: "p25_earnings", marker: true, stroke: colorScheme.p25 } ), Plot.line( earningsCSBAMarginsOverTimeLongformEmploymentYear.filter( (e) => e.yearPostgrad === yearInputOverTimeCSEmploymentYear ), { x: "employment_year_label", y: "p50_earnings", marker: true, stroke: colorScheme.p50 } ), Plot.line( earningsCSBAMarginsOverTimeLongformEmploymentYear.filter( (e) => e.yearPostgrad === yearInputOverTimeCSEmploymentYear ), { x: "employment_year_label", y: "p75_earnings", marker: true, stroke: colorScheme.p75 } ) ] })36:[{"id":"03dba0717283a9391cebd5099014c34608647077d3f767c81dd9fddfc261cf6b3631c19957912e4a54588a90a412594efba944516c39fb2344389c41efe8bcfb","href":"https://static.observableusercontent.com/files/03dba0717283a9391cebd5099014c34608647077d3f767c81dd9fddfc261cf6b3631c19957912e4a54588a90a412594efba944516c39fb2344389c41efe8bcfb","name":"aud_ba.csv","type":"text/csv","lastModified":1695593546971.056,"size":1395},{"id":"e6a07859de3b1a65185ad010d22244c05184ddd356cc3fa3c5dee09a47a1ab5b230a59a7b29debe0a5c4381ac1f9da6c0a4bd8ead60093d9d09b137c473a01b0","href":"https://static.observableusercontent.com/files/e6a07859de3b1a65185ad010d22244c05184ddd356cc3fa3c5dee09a47a1ab5b230a59a7b29debe0a5c4381ac1f9da6c0a4bd8ead60093d9d09b137c473a01b0","name":"cs_ba.csv","type":"text/csv","lastModified":1695595908052.429,"size":1229},{"id":"acd5e8780f89c613d7028d9d57416f9a5057c1828923a2c12d6acfcdbf1f0a060cebb40be050f31081bcd4a6fa54ecad8ee7b4d7502586312c97cf72f3547599","href":"https://static.observableusercontent.com/files/acd5e8780f89c613d7028d9d57416f9a5057c1828923a2c12d6acfcdbf1f0a060cebb40be050f31081bcd4a6fa54ecad8ee7b4d7502586312c97cf72f3547599","name":"cs_tx.csv","type":"text/csv","lastModified":1695607558725.715,"size":3734}] 2f:{"id":"14fc977cede6296c","slug":null,"title":"PSEO Margins Over Time","thumbnail":"f5be0ed9fc7e4f0ffc91b8821a5047e1d7ee5bf4b02be55e14ba44b7c02937ca","access_level":"public","create_time":"$D2023-09-24T22:12:14.578Z","update_time":"$D2023-09-25T17:11:18.844Z","view_time":null,"first_public_time":"$D2023-09-24T22:12:14.578Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"3f0a5555946a91ca","login":"jodyhoonstarr","name":"Jody Hoon-Starr","avatar_url":"https://avatars-next.observableusercontent.com/f014ea613ff43e463687094066d9acde784357d91102e4a80afaee7d02ccf3fc","tier":"starter_2024","bio":""},"version":302,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"741cd9e9458a548a","login":"jodyhoonstarr","name":"Jody Hoon-Starr","avatar_url":"https://avatars-next.observableusercontent.com/f014ea613ff43e463687094066d9acde784357d91102e4a80afaee7d02ccf3fc","tier":null,"bio":""}],"members":[{"type":"individual","id":"741cd9e9458a548a","login":"jodyhoonstarr","name":"Jody Hoon-Starr","avatar_url":"https://avatars-next.observableusercontent.com/f014ea613ff43e463687094066d9acde784357d91102e4a80afaee7d02ccf3fc","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"PSEO Margins Over Time","cells":[{"id":0,"value":"# PSEO Margins Over Time","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":283,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":38,"value":"---\n

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":41,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":294,"value":"## BA in Communication Disorders","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":84,"value":"Program: Communication Disorders Sciences and Services \nDegree Level: BA ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":25,"value":"viewof yearInputOverTime = Inputs.radio([\"y1\", \"y5\", \"y10\"], {\n value: \"y1\",\n label: \"Years Postgrad\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":43,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":88,"value":"Legend(chartInstMargins.scales.color, {\n title: \"Earnings Percentile\",\n tickSize: 0\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":32,"value":"Plot.plot({\n height: 200,\n inset: 10,\n x: {\n label: \"Graduation Year\"\n },\n y: {\n label: \"Number of Employed Grads\",\n grid: true,\n domain: [\n 0,\n d3.max(earningsBAMarginsOverTimeLongform.map((e) => e.grads)) * 1.2\n ],\n tickFormat: \"~s\"\n },\n marks: [\n Plot.ruleY([0]),\n Plot.line(\n earningsBAMarginsOverTimeLongform.filter(\n (e) => e.yearPostgrad === yearInputOverTime\n ),\n {\n x: \"grad_cohort_label\",\n y: \"grads\",\n marker: true\n }\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":131,"value":"---\n

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":134,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":292,"value":"## BA in Computer Science\nExamine how the trends in computer science differ from communication disorders","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":137,"value":"Program: Computer Science \nDegree Level: BA ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":116,"value":"viewof yearInputOverTimeCS = Inputs.radio([\"y1\", \"y5\", \"y10\"], {\n value: \"y1\",\n label: \"Years Postgrad\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":113,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":139,"value":"Legend(chartInstMargins.scales.color, {\n title: \"Earnings Percentile\",\n tickSize: 0\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":128,"value":"Plot.plot({\n height: 200,\n inset: 10,\n x: {\n label: \"Graduation Year\"\n },\n y: {\n label: \"Number of Employed Grads\",\n grid: true,\n domain: [\n 0,\n d3.max(earningsCSBAMarginsOverTimeLongform.map((e) => e.grads)) * 1.2\n ],\n tickFormat: \"~s\"\n },\n marks: [\n Plot.ruleY([0]),\n Plot.line(\n earningsCSBAMarginsOverTimeLongform.filter(\n (e) => e.yearPostgrad === yearInputOverTimeCS\n ),\n {\n x: \"grad_cohort_label\",\n y: \"grads\",\n marker: true\n }\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":217,"value":"---\n

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":152,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":206,"value":"## All BA Computer Science Grads \n## vs\n## ${selectInstitution} BA Computer Science Grads\n\nMargins: Solid \nSelected Institution: Dashed","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":214,"value":"> *NOTE: the ability to toggle between institutions (as seen below) **WOULD NOT** be available in any Census application. It is for **testing and evaluation only**.*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":154,"value":"viewof selectInstitution = Inputs.select([].concat(texasInstitutions), {\n value: \"Texas A&M University\",\n label: \"Institutions\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":162,"value":"viewof yearInputTexas = Inputs.radio([\"y1\", \"y5\", \"y10\"], {\n value: \"y1\",\n label: \"Years Postgrad\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":160,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":221,"value":"Legend(chartInstMargins.scales.color, {\n title: \"Earnings Percentile\",\n tickSize: 0\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":143,"value":"---\n

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":219,"value":"## Flip the Graduation Year to Employment Year\n\n> **WARNING: Experimental** \n> This one is a little bit weird because of the overlapping time ranges\n\nThe PSEO data can be confusing because we're taking grads from a specific time window (cohort) and determining their earnings 1, 5, and 10 years after graduation. With minor changes we can adjust the model to look at the earnings at the point in time that they're taken. \n\ne.g. \nGrads from `2002-2004` would have their 10 year earnings measured in `2012-2014`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":237,"value":"viewof yearInputOverTimeCSEmploymentYear = Inputs.radio([\"y1\", \"y5\", \"y10\"], {\n value: \"y1\",\n label: \"Years Postgrad\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":234,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":299,"value":"---\n

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":301,"value":"## Final Word\nAs PSEO matures these changes over time will become more interesting. It's fully intended that future work will incorporate them as a first class citizen in the PSEO ecosystem. \n\nWhether individual institutions should be compared against the margins is entirely up for debate. The utility of such a function surely has value but whether it promotes our institution partners in a way they approve of is unclear.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":10,"value":"---\n

\n

\n\n## Appendix","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":5,"value":"convertToLongformTimeSeries = (data) =>\n data.flatMap((d) => {\n return [\"y1\", \"y5\", \"y10\"].flatMap((y) => {\n return {\n institution: d.institution,\n institution_label: d.institution_label,\n institution_statefips: d.institution_statefips,\n institution_statefips_label: d.institution_statefips_label,\n cipcode: d.cipcode,\n cipcode_label: d.cipcode_label,\n degree_level: d.degree_level,\n degree_level_label: d.degree_level_label,\n grad_cohort: d.grad_cohort,\n grad_cohort_label: d.grad_cohort_label,\n yearPostgrad: y,\n grads: d[`${y}_grads_earn`],\n p25_earnings: d[`${y}_p25_earnings`],\n p50_earnings: d[`${y}_p50_earnings`],\n p75_earnings: d[`${y}_p75_earnings`]\n };\n });\n })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":14,"value":"earningsBAMarginsOverTime = d3.csvParse(\n await FileAttachment(\"aud_ba.csv\").text(),\n (d) => {\n return {\n ...d,\n y1_p25_earnings: d.y1_p25_earnings ? +d.y1_p25_earnings : null,\n y1_p50_earnings: d.y1_p50_earnings ? +d.y1_p50_earnings : null,\n y1_p75_earnings: d.y1_p75_earnings ? +d.y1_p75_earnings : null,\n y1_grads_earn: d.y1_grads_earn ? +d.y1_grads_earn : null,\n y5_p25_earnings: d.y5_p25_earnings ? +d.y5_p25_earnings : null,\n y5_p50_earnings: d.y5_p50_earnings ? +d.y5_p50_earnings : null,\n y5_p75_earnings: d.y5_p75_earnings ? +d.y5_p75_earnings : null,\n y5_grads_earn: d.y5_grads_earn ? +d.y5_grads_earn : null,\n y10_p25_earnings: d.y10_p25_earnings ? +d.y10_p25_earnings : null,\n y10_p50_earnings: d.y10_p50_earnings ? +d.y10_p50_earnings : null,\n y10_p75_earnings: d.y10_p75_earnings ? +d.y10_p75_earnings : null,\n y10_grads_earn: d.y10_grads_earn ? +d.y10_grads_earn : null\n };\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":17,"value":"earningsBAMarginsOverTimeLongform = convertToLongformTimeSeries(\n earningsBAMarginsOverTime\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":61,"value":"rawColorScheme = d3.schemeTableau10.slice(0, 3)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":70,"value":"colorScheme = ({\n p25: rawColorScheme[0],\n p50: rawColorScheme[1],\n p75: rawColorScheme[2]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":89,"value":"import { chartInstMargins } from \"a33759822b5a6d59\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":93,"value":"import { Legend } from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":105,"value":"earningsCSBAMarginsOverTime = d3.csvParse(\n await FileAttachment(\"cs_ba.csv\").text(),\n (d) => {\n return {\n ...d,\n y1_p25_earnings: d.y1_p25_earnings ? +d.y1_p25_earnings : null,\n y1_p50_earnings: d.y1_p50_earnings ? +d.y1_p50_earnings : null,\n y1_p75_earnings: d.y1_p75_earnings ? +d.y1_p75_earnings : null,\n y1_grads_earn: d.y1_grads_earn ? +d.y1_grads_earn : null,\n y5_p25_earnings: d.y5_p25_earnings ? +d.y5_p25_earnings : null,\n y5_p50_earnings: d.y5_p50_earnings ? +d.y5_p50_earnings : null,\n y5_p75_earnings: d.y5_p75_earnings ? +d.y5_p75_earnings : null,\n y5_grads_earn: d.y5_grads_earn ? +d.y5_grads_earn : null,\n y10_p25_earnings: d.y10_p25_earnings ? +d.y10_p25_earnings : null,\n y10_p50_earnings: d.y10_p50_earnings ? +d.y10_p50_earnings : null,\n y10_p75_earnings: d.y10_p75_earnings ? +d.y10_p75_earnings : null,\n y10_grads_earn: d.y10_grads_earn ? +d.y10_grads_earn : null\n };\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":108,"value":"earningsCSBAMarginsOverTimeLongform = convertToLongformTimeSeries(\n earningsCSBAMarginsOverTime\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":145,"value":"texasInstitutions = [...new Set(earningsTexas.map((e) => e.institution_label))]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":147,"value":"earningsTexas = d3.csvParse(await FileAttachment(\"cs_tx.csv\").text(), (d) => {\n return {\n ...d,\n y1_p25_earnings: d.y1_p25_earnings ? +d.y1_p25_earnings : null,\n y1_p50_earnings: d.y1_p50_earnings ? +d.y1_p50_earnings : null,\n y1_p75_earnings: d.y1_p75_earnings ? +d.y1_p75_earnings : null,\n y1_grads_earn: d.y1_grads_earn ? +d.y1_grads_earn : null,\n y5_p25_earnings: d.y5_p25_earnings ? +d.y5_p25_earnings : null,\n y5_p50_earnings: d.y5_p50_earnings ? +d.y5_p50_earnings : null,\n y5_p75_earnings: d.y5_p75_earnings ? +d.y5_p75_earnings : null,\n y5_grads_earn: d.y5_grads_earn ? +d.y5_grads_earn : null,\n y10_p25_earnings: d.y10_p25_earnings ? +d.y10_p25_earnings : null,\n y10_p50_earnings: d.y10_p50_earnings ? +d.y10_p50_earnings : null,\n y10_p75_earnings: d.y10_p75_earnings ? +d.y10_p75_earnings : null,\n y10_grads_earn: d.y10_grads_earn ? +d.y10_grads_earn : null\n };\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":157,"value":"earningsTexasOverTimeLongform = convertToLongformTimeSeries(earningsTexas)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":224,"value":"gradCohortToEmploymentYear = (o) => {\n const [startYearStr, endYearStr] = o.grad_cohort_label.split(\"-\");\n const yearPostgradStr = o.yearPostgrad.replace(\"y\", \"\");\n const yearPostgradInt = parseInt(yearPostgradStr);\n\n const startYearInt = parseInt(startYearStr) + yearPostgradInt;\n const endYearInt = parseInt(endYearStr) + yearPostgradInt;\n\n return {\n ...o,\n employment_year_label: `${startYearInt}-${endYearInt}`\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":228,"value":"earningsCSBAMarginsOverTimeLongformEmploymentYear = earningsCSBAMarginsOverTimeLongform.map(\n (o) => gradCohortToEmploymentYear(o)\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W36","stdlib":"1"}} 30:"$2f:body"