45:["$","title",null,{"children":"USAFacts Higher Education Data | NOJ | Observable"}] 4d:T51a,

${StatCard(getCollegeEnrollmentRate(condition, year), "enrolled college", "college-enrollment-rate")} ${StatCard(getCollegeGraduationRate2YearInstitutionsWithin3YearsByStartingYear(condition, year), condition + " grad from 2-year institution", "college-graduation-rate-2-year-institutions-within-3-years-by-starting-year")} ${StatCard(getCollegeGraduationRate4YearInstitutionsWithin6YearsByStartingYear(condition, year), condition + " grad from 4-year institution", "college-graduation-rate-4-year-institutions-within-6-years-by-starting-year")} ${StatCard(getAverageStudentLoanAwardedInflationAdjusted("", year), "avg. student loan awarded", "average-student-loan-awarded-inflation-adjusted")} ${StatCard(getBachelorsDegrees(condition, year+4), condition + " recieved BS in " + (year+4), "bachelors-degrees")} ${StatCard(getMastersDegrees(condition, year+6), condition + " recieved MS in " + (year+6), "masters-degrees")} ${StatCard(getDoctersDegrees(condition, year+15), condition + " recieved PhD in " + (year+15), "doctors-degrees")} ${StatCard(getMedianAnnualEarningsOfWorkers2534YearsOld2016Dollars(condition, year+12), condition + " median annual earning", "median-annual-earnings-of-workers-25-34-years-old-2016-dollars")}

4e:T402,## My thought after the Jam The idea of the interactive model is "Back in the days, as a ___ student in a specific year", what's the background of education at that time? The input interface and the stat cards are done, and I was thinking about deeper interaction, for example, click on stat card to show the chart of related data beneath. A possible use case is, I can choose "In 1990, as an Asian student" then the model show the stat cards, and I can choose one of them depends on my interest, such as "median annual earning", to expand some charts below and can see something like "the ranking of earning by academic degree". Unfortunately I don't have much time to finish the model and hero visualization. 😢 Overall, I spent about 1 hr to familiar with the dataset, 1 hr to design the interactive model and 3 hrs to implement. I'm very enjoying in this Data Jam and looking forward to the future events, **thank you @Observable for holding this wonderful data jam !!** [TzuWei](https://observablehq.com/@uier)4f:T559,function tidy(rows) { // expects a CSV parsed with type: true and array: true // we want to turn the "wide" table where each column is a year, into a tidy table where each row is a year and value pair // there is a nested structure where categories are broken down into separate rows, so we parse them const hierarchy = []; const values = []; const years = rows[0].slice(1); // each row is a category (starting with the series total) for (const row of rows.slice(1)) { let name = row[0]; // null value indicates the end of the table (there are sources metadata below the null row) if (!name) break; // count the number of spaces to determine the depth const depth = name.match(/^ */)[0].length / 4; hierarchy[depth] = name.trim(); name = hierarchy .slice(0, depth + 1) .reverse() .join(" / "); const category = hierarchy.slice(1, depth).reverse().join(" / ") || "Total"; // grab all the values for the row (after the name) const r = row.slice(1); for (const [i, year] of years.entries()) { const value = r[i]; if (value != null) values.push({ name, category, series: hierarchy[0], year: new Date(Date.UTC(+year, 0, 1)), // we convert the year as a number into a UTC Date value }); } } return values; }50:T985,files = ({ "college-enrollment": tidy( await FileAttachment("college_enrollment_usafacts.csv").csv({ typed: true, array: true }) ), "college-enrollment-rate": tidy( await FileAttachment("college_enrollment_rate_usafacts.csv").csv({ typed: true, array: true }) ), "college-graduation-rate-2-year-institutions-within-3-years-by-starting-year": tidy( await FileAttachment( "college_graduation_rate_at_twoyear_institutions_within_three_years_of_start_usafacts.csv" ).csv({ typed: true, array: true }) ), "college-graduation-rate-4-year-institutions-within-6-years-by-starting-year": tidy( await FileAttachment( "college_graduation_rate_at_fouryear_institutions_within_six_years_of_start_usafacts.csv" ).csv({ typed: true, array: true }) ), "bachelors-degrees": tidy( await FileAttachment("bachelors_degrees_conferred_usafacts.csv").csv({ typed: true, array: true }) ), "masters-degrees": tidy( await FileAttachment("masters_degrees_conferred_usafacts.csv").csv({ typed: true, array: true }) ), "doctors-degrees": tidy( await FileAttachment("doctors_degrees_usafacts.csv").csv({ typed: true, array: true }) ), "instructional-faculty": tidy( await FileAttachment("instructional_faculty_usafacts.csv").csv({ typed: true, array: true }) ), "avg-higher-ed-instructional-full-time-faculty-salary": tidy( await FileAttachment( "average_fulltime_instructional_faculty_salary_usafacts.csv" ).csv({ typed: true, array: true }) ), "median-annual-earnings-of-workers-25-34-years-old-2016-dollars": tidy( await FileAttachment( "inflationadjusted_median_annual_earnings_of_fulltime_workers_aged_2534_usafacts.csv" ).csv({ typed: true, array: true }) ), "average-student-loan-awarded": tidy( await FileAttachment("average_student_loan_awarded_usafacts.csv").csv({ typed: true, array: true }) ), "average-student-loan-awarded-inflation-adjusted": tidy( await FileAttachment( "average_student_loan_awarded_inflation_usafacts.csv" ).csv({ typed: true, array: true }) ), "stem-degrees-conferred-postsecondary-institutions": tidy( await FileAttachment( "stem_degrees_conferred_by_postsecondary_institutions_usafacts.csv" ).csv({ typed: true, array: true }) ) })51:[{"id":"dc27895d0fb9d87f9427be01eea00c8c788b3062f239289c4218f0c34bf850a06c9ceab5ca22199cda40e65d58fc4d932000d328ec02b52d166d9ecaeeb530b7","href":"https://static.observableusercontent.com/files/dc27895d0fb9d87f9427be01eea00c8c788b3062f239289c4218f0c34bf850a06c9ceab5ca22199cda40e65d58fc4d932000d328ec02b52d166d9ecaeeb530b7","name":"college_enrollment_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":8843},{"id":"b1a0efc4e7c7d78cdff732d19dcef36d041139aa2c7d9c204bd439a283cf9dc4ae27cd62d1c6c8071abef1b9b7e0d40999405a7920c3a747d786c85ea64e7069","href":"https://static.observableusercontent.com/files/b1a0efc4e7c7d78cdff732d19dcef36d041139aa2c7d9c204bd439a283cf9dc4ae27cd62d1c6c8071abef1b9b7e0d40999405a7920c3a747d786c85ea64e7069","name":"stem_degrees_conferred_by_postsecondary_institutions_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":3083},{"id":"457c40c3814c0402c73bc5fe1cdf7bf826c78a2fb2a77ba9b4d6c54adfc03e7cc8a369b411bc8c2a054ad4fbac5d6896fc046d6b0504380c60ea03e7c5de6898","href":"https://static.observableusercontent.com/files/457c40c3814c0402c73bc5fe1cdf7bf826c78a2fb2a77ba9b4d6c54adfc03e7cc8a369b411bc8c2a054ad4fbac5d6896fc046d6b0504380c60ea03e7c5de6898","name":"bachelors_degrees_conferred_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":9243},{"id":"49b65265737a01a9df14ab2066f9d49e579540c338d820943f5f8954d6c3de0e7dde6ef6bb245d22404b6fb41bcc20db3d9676ad843c565e2c3a400ec76042cb","href":"https://static.observableusercontent.com/files/49b65265737a01a9df14ab2066f9d49e579540c338d820943f5f8954d6c3de0e7dde6ef6bb245d22404b6fb41bcc20db3d9676ad843c565e2c3a400ec76042cb","name":"average_student_loan_awarded_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":887},{"id":"688f05218abdcd85a99aa12b90294afe1a312c9dbf312a081b870e742f8816a4bc5c688516a9ba83a2228ff123724cf5a8b57cae4bc0bb68c105b3d1c841f8d4","href":"https://static.observableusercontent.com/files/688f05218abdcd85a99aa12b90294afe1a312c9dbf312a081b870e742f8816a4bc5c688516a9ba83a2228ff123724cf5a8b57cae4bc0bb68c105b3d1c841f8d4","name":"college_enrollment_rate_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":8541},{"id":"7a60321643bf43ee0e233f4e1b9697ee5fa3fe3d881bcfd207a46c473ac989457658db802617942974c9695b71045cbf7710cdb617f060a157c4ed3e97960cec","href":"https://static.observableusercontent.com/files/7a60321643bf43ee0e233f4e1b9697ee5fa3fe3d881bcfd207a46c473ac989457658db802617942974c9695b71045cbf7710cdb617f060a157c4ed3e97960cec","name":"average_fulltime_instructional_faculty_salary_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":5757},{"id":"92e7b495c9dccb526f422ec1b4dee8f39ae1e77a5c17cf7a01ec6bc90e186ee8ca68c375f84961067dfefc4a1e552ecd623a1e1c39bc3a548dcdb4936b401e74","href":"https://static.observableusercontent.com/files/92e7b495c9dccb526f422ec1b4dee8f39ae1e77a5c17cf7a01ec6bc90e186ee8ca68c375f84961067dfefc4a1e552ecd623a1e1c39bc3a548dcdb4936b401e74","name":"college_graduation_rate_at_twoyear_institutions_within_three_years_of_start_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":3680},{"id":"d4c635eddbb4a48b5b6a5a619ab2c42e6aeb31928ad60f308b3921a3a076cc6e629c0fcc3455e62e1616de10735ce8de23a643bc40a2c975bfcc1cfd049b1fe3","href":"https://static.observableusercontent.com/files/d4c635eddbb4a48b5b6a5a619ab2c42e6aeb31928ad60f308b3921a3a076cc6e629c0fcc3455e62e1616de10735ce8de23a643bc40a2c975bfcc1cfd049b1fe3","name":"masters_degrees_conferred_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":4456},{"id":"589a396f0d712be4ce889f7b7ba6177d401889ac9d3f8c9c8b07154ca2d703d7a235fb97c25b34f19aa24849b70ed30533a671d1f43e2c76d3ed78f6087dc2b0","href":"https://static.observableusercontent.com/files/589a396f0d712be4ce889f7b7ba6177d401889ac9d3f8c9c8b07154ca2d703d7a235fb97c25b34f19aa24849b70ed30533a671d1f43e2c76d3ed78f6087dc2b0","name":"doctors_degrees_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":7407},{"id":"d9eedd4dd35c5c694d0aec18eb4ce647c86f05c742491d89861cec1b837687c0addd43f541db1b772dabaf78d518c8bc2804dfe513988452b337246061d2733f","href":"https://static.observableusercontent.com/files/d9eedd4dd35c5c694d0aec18eb4ce647c86f05c742491d89861cec1b837687c0addd43f541db1b772dabaf78d518c8bc2804dfe513988452b337246061d2733f","name":"instructional_faculty_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":4906},{"id":"7cf35f34b9325a064930b9ebac161a6e661b2cf54afd8f9d94a18503c4d5bb1931ecb8a4b795de823c9ca8c1e6e12bb0400963376fd2b1e369283ae7c4c042eb","href":"https://static.observableusercontent.com/files/7cf35f34b9325a064930b9ebac161a6e661b2cf54afd8f9d94a18503c4d5bb1931ecb8a4b795de823c9ca8c1e6e12bb0400963376fd2b1e369283ae7c4c042eb","name":"college_graduation_rate_at_fouryear_institutions_within_six_years_of_start_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":4817},{"id":"d6e2755fd300343c08fb7cac6e507ae5ebb9cd7afa1a7b87425eeae13214c8bc9e8c7fdab49a0d270d5913fac79977307afb323a29e0a2ffce321559cc814a14","href":"https://static.observableusercontent.com/files/d6e2755fd300343c08fb7cac6e507ae5ebb9cd7afa1a7b87425eeae13214c8bc9e8c7fdab49a0d270d5913fac79977307afb323a29e0a2ffce321559cc814a14","name":"inflationadjusted_median_annual_earnings_of_fulltime_workers_aged_2534_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":3098},{"id":"6d64869ca2998e26cae3217f1abfc4bbf6e5c147530784fbf9374fb2d6a7beedf6ceb267193a12369b41082be2869d97638c76e22c607e3ae6e3be421b2e25ca","href":"https://static.observableusercontent.com/files/6d64869ca2998e26cae3217f1abfc4bbf6e5c147530784fbf9374fb2d6a7beedf6ceb267193a12369b41082be2869d97638c76e22c607e3ae6e3be421b2e25ca","name":"average_student_loan_awarded_inflation_usafacts.csv","type":"text/csv","lastModified":1665536925642.353,"size":1497}] 49:{"id":"443205827ea36d75","slug":"usafacts-higher-education-data","title":"USAFacts Higher Education Data","thumbnail":"977e205135ae0f076f140b19e00fc132e23f1405da427252325817882415b805","access_level":"public","create_time":"$D2022-10-12T01:08:45.642Z","update_time":"$D2022-10-19T06:51:06.114Z","view_time":null,"first_public_time":"$D2022-10-12T01:08:45.642Z","has_unpublished_edits":null,"fork":{"id":"8cfaf163cc9791c6","slug":"usafacts-higher-education-data","title":"USAFacts Higher Education Data","owner":{"id":"f35c755083683fe5","login":"observablehq","name":"Observable"}},"stars":1,"starred":false,"owner":{"type":"team","id":"e4ba0fb9d4d75e39","login":"noj-tw","name":"NOJ","avatar_url":"https://avatars-next.observableusercontent.com/4243c82cfcd085f997784d50bfe7d8aefdd17cbf04f6693a57372294d164b8d1","tier":"starter_2024","bio":"","followed_by_you":false,"follows_you":false},"version":915,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"0f57052923586bf5","login":"uier","name":"TzuWei","avatar_url":"https://avatars-next.observableusercontent.com/e9804c75339c06872188c18615de542bff60b897d65b15c5519fd906c8be761a","tier":null,"bio":"Hi 👋, I'm TzuWei (uier).\n\na computer science student from Taiwan 🇹🇼","followed_by_you":false,"follows_you":false}],"members":[{"type":"team","id":"e4ba0fb9d4d75e39","login":"noj-tw","name":"NOJ","avatar_url":"https://avatars-next.observableusercontent.com/4243c82cfcd085f997784d50bfe7d8aefdd17cbf04f6693a57372294d164b8d1","tier":"starter_2024","role":"editor"},{"type":"individual","id":"0f57052923586bf5","login":"uier","name":"TzuWei","avatar_url":"https://avatars-next.observableusercontent.com/e9804c75339c06872188c18615de542bff60b897d65b15c5519fd906c8be761a","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"USAFacts Higher Education Data","cells":[{"id":737,"value":"# USAFacts Higher Education Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":740,"value":"# Interactive Model","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":763,"value":"viewof options = Inputs.form(\n [\n Inputs.range([1961, 2021], {\n label: \"In\",\n step: 1,\n value: 2003\n }),\n Inputs.select(conditions, {\n label: \"\",\n value: \"Male\",\n width: 160\n })\n ],\n {\n template: (inputs) =>\n html`

${inputs[0]}as a/an high school graduated${inputs[1]}student

`\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":773,"value":"$4d","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":829,"value":"datasetId\n ? Plot.plot({\n marks: [\n Plot.ruleY([0]),\n Plot.areaY(files[datasetId], { x: \"year\", y: \"value\", fill: \"name\" })\n ],\n color: { legend: true, columns: `${width}px` },\n marginLeft: 100,\n width\n })\n : html`click on stat card to open full chart (not done yet)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":901,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":903,"value":"$4e","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":557,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":561,"value":"# Workspace","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":768,"value":"condition = options[1]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":770,"value":"year = options[0]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":577,"value":"getCollegeEnrollmentRate(\"Black\", 2000)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":574,"value":"function getCollegeEnrollmentRate(condition, year) {\n condition = genderConditionTransform[condition] || condition;\n const result = files[\"college-enrollment-rate\"].find(\n (d) =>\n d.year.getFullYear() === year &&\n (d.name.includes(condition) || d.category === condition)\n );\n if (!result) return \"N/A\";\n return d3.format(\".1%\")(result.value);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":599,"value":"getCollegeGraduationRate2YearInstitutionsWithin3YearsByStartingYear(\n \"Female\",\n 2017\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":597,"value":"function getCollegeGraduationRate2YearInstitutionsWithin3YearsByStartingYear(\n condition,\n year\n) {\n condition = genderConditionTransform[condition] || condition;\n const result = files[\n \"college-graduation-rate-2-year-institutions-within-3-years-by-starting-year\"\n ].find(\n (d) =>\n d.year.getFullYear() === year &&\n (d.name.includes(condition) || d.category === condition)\n );\n if (!result) return \"N/A\";\n return d3.format(\".1%\")(result.value);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":616,"value":"getCollegeGraduationRate4YearInstitutionsWithin6YearsByStartingYear(\n \"Asian\",\n 2010\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":610,"value":"function getCollegeGraduationRate4YearInstitutionsWithin6YearsByStartingYear(\n condition,\n year\n) {\n condition = genderConditionTransform[condition] || condition\n const result = files[\n \"college-graduation-rate-4-year-institutions-within-6-years-by-starting-year\"\n ].find((d) => d.year.getFullYear() === year && (d.name.includes(condition) || d.category === condition));\n if (!result) return \"N/A\";\n return d3.format(\".1%\")(result.value);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":624,"value":"getBachelorsDegrees(\"Male\", 1920) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":621,"value":"function getBachelorsDegrees(condition, year) {\n const totalBachelorsInYear = files[\"bachelors-degrees\"].find(\n (d) => d.category === \"Total\" && d.year.getFullYear() === year\n );\n if (condition === \"Total\" && totalBachelorsInYear)\n return d3.format(\".3s\")(totalBachelorsInYear.value);\n const result = files[\"bachelors-degrees\"].find(\n (d) => d.year.getFullYear() === year && d.name.includes(condition)\n );\n if (!result || !totalBachelorsInYear) return \"N/A\";\n return d3.format(\".3s\")(totalBachelorsInYear.value * result.value);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":664,"value":"getMastersDegrees(\"Asian\", 2019)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":661,"value":"function getMastersDegrees(condition, year) {\n const result = files[\"masters-degrees\"].find(\n (d) => d.year.getFullYear() === year && (d.name.includes(condition) || d.category === condition)\n );\n if (!result) return \"N/A\";\n return d3.format(\".3s\")(result.value);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":680,"value":"getDoctersDegrees(\"Female\", 2019)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":674,"value":"function getDoctersDegrees(condition, year) {\n const result = files[\"doctors-degrees\"].find(\n (d) => d.year.getFullYear() === year && (d.name.includes(condition) || d.category === condition)\n );\n if (!result) return \"N/A\";\n return d3.format(\".3s\")(result.value);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":718,"value":"getMedianAnnualEarningsOfWorkers2534YearsOld2016Dollars(\"\", 2015)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":713,"value":"function getMedianAnnualEarningsOfWorkers2534YearsOld2016Dollars(\n condition,\n year\n) {\n const result = files[\n \"median-annual-earnings-of-workers-25-34-years-old-2016-dollars\"\n ].find((d) => d.year.getFullYear() === year && (d.name.includes(condition) || d.category === condition));\n if (!result) return \"N/A\";\n return d3.format(\".3s\")(result.value);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":726,"value":"getAverageStudentLoanAwardedInflationAdjusted(\"\", 2010)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":723,"value":"function getAverageStudentLoanAwardedInflationAdjusted(\n condition,\n year\n) {\n const result = files[\n \"average-student-loan-awarded-inflation-adjusted\"\n ].find((d) => d.year.getFullYear() === year && (d.name.includes(condition) || d.category === condition));\n if (!result) return \"N/A\";\n return d3.format(\".3s\")(result.value);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":834,"value":"mutable datasetId = null","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":783,"value":"StatCard = (value, desc, id = null) => {\n return html`

\n ${value}\n ${desc}\n

`;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":876,"value":"{\n d3.select(\"body\")\n .selectAll(\".stat-card\")\n .on(\"click\", (event) => {\n mutable datasetId = event.target.id;\n });\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":779,"value":"styles = ({\n card: {\n display: \"flex\",\n \"flex-direction\": \"column\",\n \"align-items\": \"center\",\n \"text-align\": \"center\",\n padding: \"2px\",\n border: \"2px solid #777\",\n width: \"220px\",\n cursor: \"pointer\"\n },\n cardValue: {\n \"font-size\": \"24px\",\n \"font-weight\": \"bold\"\n },\n cardDesc: {\n \"font-size\": \"14px\"\n },\n cardsContainer: {\n display: \"grid\",\n \"grid-template-columns\": \"auto auto auto auto\",\n \"grid-template-rows\": \"auto auto auto auto\",\n \"column-gap\": \"10px\",\n \"row-gap\": \"15px\"\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":781,"value":"styleStringify = (styleObj) =>\n Object.entries(styleObj)\n .map(([k, v]) => `${k}: ${v}`)\n .join(\"; \")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":0,"value":"## USAFacts Higher Education Data\n\nThis notebook prepares 12 datasets from the [USAFacts Education statistics](https://usafacts.org/data/topics/people-society/education/#higher-education) focused on higher education. Each of these datasets focuses on a particular metric over many years, such as college enrollment rates, number of instructional faculty and average student loan amounts.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":430,"value":"## What's in the data\nSelect one of the datasets to get a preview of its contents. Each dataset has a number of subcategories it can be broken down by, which we expose as another choice.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":331,"value":"viewof dataset = Inputs.select(Object.keys(files), {label: \"Select a dataset\", format: x => sentenceName(x)})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":165,"value":"viewof data_sub = Inputs.select(d3.group(data, d => d.category), {label: \"Select a subcategory\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":169,"value":"Plot.plot({\n caption: `${sentenceName(dataset)}`,\n marks: [\n Plot.ruleY([0]),\n Plot.areaY(data_sub, {x: \"year\", y: \"value\", fill: \"name\"})\n ],\n color: { legend: true, columns: `${width}px` },\n marginLeft: 100\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":381,"value":"data = files[dataset]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":745,"value":"conditions = [\n \"Total\",\n \"Female\",\n \"Male\",\n \"Alaska Native\",\n \"American Indian\",\n \"Asian\",\n \"Black\",\n \"Hispanic\",\n \"Nonresident of the US\",\n \"Pacific Islander\",\n \"Two or more races\",\n \"White\"\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":752,"value":"genderConditionTransform = ({\n Female: \"Women\",\n Male: \"Men\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":572,"value":"Inputs.table(data)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":35,"value":"[${sentenceName(dataset)} dataset on USAFacts](https://usafacts.org/data/topics/people-society/education/higher-education/${dataset.replace(\"-inflation-adjusted\",\"\")}/).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":432,"value":"## Using the data\nThere are a number of ways to use this data, the most straightforward is to access the `files` cell. \nYou an import the value of `files` to your notebook like so:\n~~~js\nimport { files } from \"@observablehq/usafacts-higher-education-data\"\n~~~\n\nYou can also fork this notebook, adding your analysis and removing any cells that you don't want to keep around.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":497,"value":"files","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":438,"value":"## Data completeness\nNot all of the series in a dataset have values for all years. The following visualization helps show which series have entries for which years.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":216,"value":"Plot.plot({\n caption: `${sentenceName(dataset)}`,\n marks: [\n Plot.dot(data, {\n x: \"year\",\n y: \"name\",\n fill: \"value\",\n stroke: \"gray\",\n title: \"value\"\n })\n ],\n color: { scheme: \"greens\" },\n y: { axis: \"right\" },\n grid: true,\n width,\n marginRight: 400\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":512,"value":"dataset","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":138,"value":"## Data processing\nThe data is downloaded directly from the [USAFacts page for each dataset](https://usafacts.org/data/topics/people-society/education/#higher-education). We then upload the data to this notebook as a FileAttachment. As is, the CSV files that are exported from USAFacts are a bit difficult to use programatically. We wrote this `tidy` function to process the data into a tidy format, making it easier to use with [Observable Plot](https://observablehq.com/@observablehq/plot) and other JavaScript analysis tools.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":33,"value":"$4f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":319,"value":"$50","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":365,"value":"sentenceName = (name) => {\n const sent = name.split(\"-\").join(\" \");\n return sent[0].toUpperCase() + sent.slice(1);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W51","stdlib":"1"}} 44:null