2f:T456,//https://en.wikipedia.org/wiki/List_of_colloquial_names_for_universities_and_colleges_in_the_United_States chart1barv2 = function() { let thebardata = (barshow == 'pct') ? group_bar_data2.filter(d => d.gender == 'female') : group_bar_data2; //let thebardata = group_bar_data; return vl.markBar({tooltip: true}) .data(thebardata) .encode( vl.y().fieldN("school") .sort(vl.fieldQ('count').order('descending')), //sort vl.x().sum(barshow).scale({domain: {unionWith: [0,1]}}).title(barshow == 'pct' ? 'percent women' : 'count'), //https://vega.github.io/vega-lite/docs/scale.html vl.row().fieldN("relationship").sort(["phd", "alma", "empl"]), //https://observablehq.com/@observablehq/vega-lite-chart-types vl.color().fieldN("gender").scale({ "domain": ["female", "male"], "range": ["#Fc7d0b", 'steelblue'] }).legend(barshow == 'pct' ? null : true) ) .width(250) .height(30) .title({text:"Gender Diversity", subtitle: "CS PhD graduates and CS tenure track faculty", anchor: "middle"})//https://vega.github.io/vega-lite/docs/title.html }30:Tb0f,//get both on tooltip by graphing both with 0 opacity?? //https://vega.github.io/vega-lite/docs/axis.html //https://observablehq.com/@observablehq/synchronized-inputs //https://vega.github.io/vega/docs/marks/line/ chart2line = function() { // The selection const hover = vl.selectSingle("hover") .on("mouseover") .encodings("x") .nearest(true) .clear("moouseout") .init({ x: { year: 1998 } }); // The line and point marks. Notice how we filter the points on hover const lineAndPoint = vl.layer( vl.markLine(), vl.markPoint() .transform(vl.filter(hover)) ).encode( vl.y().fieldQ("count").scale({domain: [0,facnet_scalemax+2]}), vl.color().fieldN("type") ); const lineAndPoint2 = vl.layer( vl.markLine(), vl.markPoint() .transform(vl.filter(hover)) ).encode( vl.y().fieldQ("count").scale({domain: [0,facnet_scalemax+2]}), vl.color().fieldN("type").legend({symbolOpacity: 1.0}),//https://vega.github.io/vega-lite/docs/legend.html vl.opacity().value(0.2) ); // The rule helps as a proxy for the hover. We draw rules all over the chart // so we can easily find the nearest one. We then hide them using opacity 0 const rule =vl.markRule({ strokeWidth: 0.5, tooltip: true }) // We pivot the data so we can show all the stock prices at once .transform(vl.pivot("type").value("count").groupby(["year"])) .encode( vl.opacity().value(0).if(hover, vl.value(0.7)), vl.tooltip([vl.fieldO("year"), "men", "women"]) ) .select(hover); const ruleavg = vl.markLine().encode( vl.y().fieldQ("avg").scale({domain: [0,facnet_scalemax+2]}), vl.x().fieldO("year"), vl.color().value("orange"), vl.strokeDash().value([8,8]), vl.opacity().value(1.0) ); const ruleavg2 = vl.markLine().encode( vl.y().fieldQ("avg").scale({domain: [0,facnet_scalemax+2]}), vl.x().fieldO("year"), vl.color().value("orange"), vl.strokeDash().value([8,8]), vl.opacity().value(0.15) ); const line2 = vl .layer(ruleavg, lineAndPoint, rule ) .encode(vl.x().fieldO("year").axis({values: [1984, 1987, 1990, 1993, 1996, 1999, 2002, 2005, 2008, 2011], labelAngle: 0})) .data(ipeds_data_line2.filter(aq.escape(d => d.ipeds_id == facnet_selected.ipeds_id))) .width(350) .height(175) .title({ text: "CS PhD graduates 1984 - 2011", subtitle: univ + " vs national average" }); const line3 = vl .layer(lineAndPoint2) .encode(vl.x().fieldO("year").axis({values: [1984, 1987, 1990, 1993, 1996, 1999, 2002, 2005, 2008, 2011], labelAngle: 0})) // .data(ipeds_data_line2.filter(aq.escape(d => d.ipeds_id == facnet_selected2.ipeds_id))) .data(ipeds_data_line_wholeavg) .width(350) .height(175); return vl.layer(line3, line2); }31:T4a6,chart2zerobar = function() { return vl.layer( vl.markBar() .data(ipeds_all_zero_rollup .filter(aq.escape(d => d.zero_type == zerobarshow)) //.filter(aq.escape(d => d.ipeds_id == facnet_selected.ipeds_id || d.ipeds_id == facnet_selected2.ipeds_id))) .filter(aq.escape(d => op.includes(facnet_selected3, d.ipeds_id))) //.concat(ipeds_all_zero_rollup.filter(aq.escape(d => d.zero_type == zerobarshow)) // .filter(aq.escape(d => d.ipeds_id == facnet_selected.ipeds_id))) ) .encode( vl.x().fieldQ('zero_count'), vl.y().fieldN('school').sort(vl.fieldQ('zero_count').order('descending')), vl.color().value("lightgrey"), ), vl.markRule({strokeWidth: 3}) //https://vega.github.io/vega-lite/examples/layer_bar_annotations.html //https://vega.github.io/vega-lite/docs/line.html .data(ipeds_zero_avg.filter(aq.escape(d => d.zero_type == zerobarshow))) .encode( vl.x().fieldQ("avg"), //vl.x().fieldO("year"), vl.color().value("grey"), vl.strokeDash().value([8,4]) ) ) .title("Number of years with no female graduates (" + zerobarshow + ")") .width(350) .height(30) }32:T4ad,chart3emplbar = function() { //!bar3zoom.includes("alma") ? facedge_data_top5_alma_reg2 : facedge_data_top5_alma_inst2 const mydata = (tofrom == 'from' && !bar3zoom.includes("alma")) ? facedge_data_top5_alma_reg2 : (tofrom == 'from' && bar3zoom.includes("alma")) ? facedge_data_top5_alma_inst2 : (tofrom == 'to' && !bar3zoom.includes("employer")) ? facedge_data_top5_alma_reg2_inv : facedge_data_top5_alma_inst2_inv; const mylab = (tofrom == 'from') ? 'employer' : 'alma'; const myotherlab = (tofrom == 'from') ? 'alma' : 'employer'; return vl.markBar() .data(mydata) .encode( vl.x().fieldQ("count"), vl.y().fieldN("institution") .sort(vl.fieldQ('count').order('descending')), // vl.color({value: 'grey'}) vl.color().fieldN("gender").scale({ "domain": ["female", "male"], "range": ["#Fc7d0b", 'steelblue'] }) ) .width(150) .height(60) .title({text:"2012 Top " + mylab + "s, " + (!bar3zoom.includes(myotherlab) ? facnet_selected.Region + " Region " + myotherlab : facnet_selected.school + " " + myotherlab), anchor: 'center'}) } 33:T1bbb,//https://observablehq.com/@nyuvis/interaction //https://colorbrewer2.org/#type=qualitative&scheme=Dark2&n=5 //add tooltips!! //https://stackoverflow.com/questions/38670322/d3-brushing-and-mouse-move-coexist but opposite function brushableScatterplot() { // set up // the value for when there is no brush const initialValue = facedge_data3.filter(aq.escape(d => op.includes(scatter0zoom, d.Region))).concat(facedge_data3.filter(aq.escape(d => d.institution == facnet_selected.institution))); const colorSelect = "#e41a1c"; const colorOther = "#676767"; const visWidth = 120; const visHeight = 120; const margin = ({top: 30, right: 20, bottom: 40, left: 50}); const x = d3.scaleLinear() .domain(d3.extent(facedge_data3, d => d.pct_alma)).nice() .range([0, visWidth]); const y = d3.scaleLinear() .domain(d3.extent(facedge_data3, d => d.pct_emp)).nice() .range([visHeight, 0]); const myx0 = d3.min(facedge_data3, d => d.pct_alma); const myx1 = d3.max(facedge_data3, d => d.pct_alma); const myy0 = d3.min(facedge_data3, d => d.pct_emp); const myy1 = d3.max(facedge_data3, d => d.pct_emp); scatter_window_filter([myx0, myx1, myy0, myy1]); const svg = d3.create('svg') .attr('width', visWidth + margin.left + margin.right) .attr('height', visHeight + margin.top + margin.bottom) .property('value', initialValue); const g = svg.append('g') .attr('transform', `translate(${margin.left}, ${margin.top})`); const xAxis = (g, scale, label) => g.attr('transform', `translate(0, ${visHeight})`) // add axis .call(d3.axisBottom(scale).ticks(5)) // remove baseline .call(g => g.select('.domain').remove()) // add grid lines // references https://observablehq.com/@d3/connected-scatterplot .call(g => g.selectAll('.tick line') .clone() .attr('stroke', '#d3d3d3') .attr('y1', -visHeight) .attr('y2', 0)) // add label .append('text') .attr('x', visWidth / 2) .attr('y', 30) .attr('fill', 'black') .attr('text-anchor', 'middle') .text(label); const yAxis = (g, scale, label) => // add axis g.call(d3.axisLeft(scale).ticks(6)) // remove baseline .call(g => g.select('.domain').remove()) // add grid lines // refernces https://observablehq.com/@d3/connected-scatterplot .call(g => g.selectAll('.tick line') .clone() .attr('stroke', '#d3d3d3') .attr('x1', 0) .attr('x2', visWidth)) // add label .append('text') .attr('y', -40) .attr('x', -visHeight / 2+40) .attr('fill', 'black') .attr('dominant-baseline', 'middle') .attr("transform", "rotate(270)") .text(label); // axes g.append("g").call(xAxis, x, '% women (alma)'); g.append("g").call(yAxis, y, '% women (employer)'); const brush = d3.brush() // set the space that the brush can take up .extent([[0, 0], [visWidth, visHeight]]) // handle events .on('brush', onBrush) .on('end', onEnd); // g.append('g') // .call(brush); g.call(brush); // draw points const radius = 3; const dots = g.selectAll('circle') .data(initialValue) .join('circle') .attr('cx', d => x(d.pct_alma)) .attr('cy', d => y(d.pct_emp)) //.attr('fill', d => d.institution == facnet_selected.institution ? "#e7298a" : "#7570b3") .attr('fill', d => d.institution == facnet_selected.institution ? colorSelect : colorOther) //"#f781bf", "#6a3d9a" .attr('opacity', 1) //.attr('r', d => d.institution == facnet_selected.institution ? radius * 1.5 : radius) .attr('r', radius) .on('mouseenter', mouseEnter) .on('mouseleave', mouseLeave); const tooltip = g.append('g') .attr('visibility', 'hidden'); const tooltipHeight = 12; // add a rectangle to the tooltip to serve as a background const tooltipRect = tooltip.append('rect') .attr('fill', 'black') .attr('rx', 5) .attr('height', tooltipHeight); // add a text element to the tooltip to contain the label const tooltipText = tooltip.append('text') .attr('fill', 'white') .attr('font-family', 'sans-serif') .attr('font-size', 9) .attr('y', 2) // offset it from the edge of the rectangle .attr('x', 3) // offset it from the edge of the rectangle .attr('dominant-baseline', 'hanging'); // handle hovering over a circle function mouseEnter(event, d) { // update the label's text and get its width tooltipText.text(d.institution.replace("University", "U")); const labelWidth = tooltipText.node().getComputedTextLength(); // set the width of the tooltip's background rectangle // to match the width of the label, plus some extra space tooltipRect.attr('width', labelWidth + 6); // move the tooltip to the position of the circle (offset by a bit) // and make the tooltip visible const xPos = (x(d.pct_alma) > visWidth / 2) ? x(d.pct_alma) - labelWidth : x(d.pct_alma) + 10 ; const yPos = y(d.pct_emp) - tooltipHeight ; tooltip.attr('transform', `translate(${xPos},${yPos})`) .attr('visibility', 'visible'); } // handle leaving a circle function mouseLeave(event, d) { // make the tooltip invisible tooltip .attr('visibility', 'hidden'); } //title svg.append("text") .attr("x", (visWidth / 2) + margin.left - 10) .attr("y", margin.top / 2) .attr('fill', 'black') .attr('font-family', 'sans-serif') .attr("text-anchor", "middle") .style("font-size", "10px") .attr("font-weight",900) .text("2012 CS Faculty Gender"); // ********** new stuff starts here ********** // grab the brush's rect and add the tooltip events function onBrush(event) { // event.selection gives us the coordinates of the // top left and bottom right of the brush box const [[x1, y1], [x2, y2]] = event.selection; scatter_window_filter([x.invert(x1), x.invert(x2), y.invert(y2), y.invert(y1)]); // return true if the dot is in the brush box, false otherwise function isBrushed(d) { const cx = x(d.pct_alma); const cy = y(d.pct_emp) return cx >= x1 && cx <= x2 && cy >= y1 && cy <= y2; } // style the dots dots.attr('fill', d => d.institution == facnet_selected.institution ? colorSelect : isBrushed(d) ? colorOther : 'lightgray'); // update the data that appears in the cars variable svg.property('value', initialValue.filter(isBrushed)).dispatch('input'); } function onEnd(event) { // if the brush is cleared if (event.selection === null) { // reset the color of all of the dots dots.attr('fill', d => d.institution == facnet_selected.institution ? colorSelect : colorOther); scatter_window_filter([myx0, myx1, myy0, myy1]); svg.property('value', initialValue).dispatch('input'); } } return svg.node(); }34:T423,## Data Data set: Integrated Postsecondary Education Data System, Completions, Awards/degrees conferred by program (6-digit CIP code), award level, race/ethnicity, and gender, 1984 - 2011 * https://nces.ed.gov/ipeds/datacenter/DataFiles.aspx?year=2011&surveyNumber=3 * CS PhDs awarded per year per institution, by gender Data set: 2012 Computer Science Faculty Hiring Network (Tenure-Track) * https://www.science.org/doi/10.1126/sciadv.1400005 * CS tenure-track faculty, by gender, job title, alma mater name and region, employing institution name and region Data set: Wikidata US Universities * https://query.wikidata.org/#SELECT%20DISTINCT%20%3Fitem%20%3FitemLabel%20%3Fipeds%0AWHERE%20%7B%0A%20%20%3Fitem%20wdt%3AP31%2Fwdt%3AP279%2a%20wd%3AQ3918.%0A%20%20%3Fitem%20wdt%3AP17%20wd%3AQ30.%0A%20%20OPTIONAL%20%7B%20%3Fitem%20wdt%3AP1771%20%3Fipeds.%20%7D%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%7D%0A%7D * US Universities, by name and IPEDS code, used to align above data sets35:T484,group_bar_data2 = facedge_data3 //.filter(aq.escape(d => op.includes(facedge_data4.array('ipeds_id'), d.ipeds_id))) .filter(aq.escape(d => op.includes(brushedschools, d.institution))) .concat(facedge_data3.filter(aq.escape(aq.escape(d => d.ipeds_id == facnet_selected.ipeds_id)))) .select('institution', 'pct_alma', 'pct_emp', 'pct_phd', 'count_m_alma', 'count_f_alma', 'count_m_emp', 'count_f_emp', 'count_m_phd', 'count_f_phd', 'school') .derive({pct: d => [d.pct_alma, d.pct_emp, d.pct_phd]}) .derive({count_m: d => [d.count_m_alma, d.count_m_emp, d.count_m_phd]}) .derive({count_f: d => [d.count_f_alma, d.count_f_emp, d.count_f_phd]}) .derive({relationship: d => ['alma', 'empl', 'phd']}) .select('institution', 'pct', 'count_m', 'count_f', 'relationship', 'school') .unroll(['relationship', 'pct', 'count_m', 'count_f'] ) //https://uwdata.github.io/arquero/api/verbs.html#unroll .derive({count: d=>[d.count_m, d.count_f], gender: d=> ['male', 'female']}) .select('institution', 'relationship', 'pct', 'count', 'gender', 'school') .unroll(['gender', 'count']) .derive({pct: d => d.gender == 'female' ? d.pct : 1 - d.pct})36:T598,facedge_data3 = aq.from(facedge_data2) .derive({pct_alma: d => d.type == 'alma' && d.gender == 'F' ? d.pct : 0}) .derive({pct_emp: d => d.type == 'employer' && d.gender == 'F' ? d.pct : 0}) .derive({count_m_alma: d => d.type == 'alma' && d.gender == 'M' ? d.count : 0}) .derive({count_f_alma: d => d.type == 'alma' && d.gender == 'F' ? d.count : 0}) .derive({count_m_emp: d => d.type == 'employer' && d.gender == 'M' ? d.count : 0}) .derive({count_f_emp: d => d.type == 'employer' && d.gender == 'F' ? d.count : 0}) //.filter(d => d.gender == 'F') .groupby('u') .rollup({pct_alma: d=> op.max(d.pct_alma), pct_emp: d=> op.max(d.pct_emp), count_m_alma: d => op.max(d.count_m_alma), count_f_alma: d => op.max(d.count_f_alma), count_m_emp: d => op.max(d.count_m_emp), count_f_emp: d => op.max(d.count_f_emp), }) //.filter(d => d.type == 'employer') .derive({u: d => op.parse_int(d.u)}) .join(facnet_data) //.select('wiki_id', 'pct_alma', 'pct_emp') //.join(salary_data) .select('wiki_id', 'institution', 'Region', 'pct_alma', 'pct_emp', 'count_m_alma', 'count_f_alma', 'count_m_emp', 'count_f_emp') .join(ipeds_data_rollup2_join.select('wiki_id', 'pct_phd', 'count_m_phd', 'count_f_phd', 'ipeds_id')) .derive({school: d => op.replace(d.institution, /[^A-Z]/g, '')}) //https://uwdata.github.io/arquero/api/op.html#string-functions37:T8f9,## References * Arquero API Reference, https://uwdata.github.io/arquero/api/ * UW Interactive Data Lab, Arquero Cookbook, Cumulative Sum, https://observablehq.com/@uwdata/arquero-cookbook#cumulative_sum * UW Interactive Data Lab, Arquero Row Manipulation, https://observablehq.com/@uwdata/arquero-row-manipulation * Vega-Lite Documentation, https://vega.github.io/vega-lite/docs/ * Vega Documentation, https://vega.github.io/vega/docs/ * Vega-Lite Chart Types, https://observablehq.com/@observablehq/vega-lite-chart-types * Observable Inputs, https://observablehq.com/@observablehq/inputs * Synchronized Inputs, https://observablehq.com/@observablehq/synchronized-inputs * Observable’s not JavaScript, https://observablehq.com/@observablehq/observables-not-javascript * Lesley Frew, HW4 part 2 - CS 725, Spring 2022, https://observablehq.com/d/3c32e4c36e55d340 * NYU Visualization, Interaction, https://observablehq.com/@nyuvis/interaction * d3 brushing and mouse move coexist, https://stackoverflow.com/questions/38670322/d3-brushing-and-mouse-move-coexist * Color Brewer, Dark scheme, https://colorbrewer2.org/#type=qualitative&scheme=Dark2&n=5 * Mozilla Developer Documentation: Maps, https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Map * Mozilla Developer Documentation: String.prototype.replace(), https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/String/replace * Counting the occurrences / frequency of array elements, https://stackoverflow.com/questions/5667888/counting-the-occurrences-frequency-of-array-elements * JavaScript String substring(), https://www.w3schools.com/jsref/jsref_substring.asp * How to replace/name keys in a Javascript key:value object?, https://stackoverflow.com/questions/17539236/how-to-replace-name-keys-in-a-javascript-keyvalue-object * How to quickly create an array of sequential numbers in JavaScript (and how it works), https://tobiasljungstrom.net/blog/2019-07-26-array-of-sequential-numbers-in-js/ * How to get the difference between two arrays in JavaScript?, https://stackoverflow.com/questions/1187518/how-to-get-the-difference-between-two-arrays-in-javascript * Set cellpadding and cellspacing in CSS?, https://stackoverflow.com/questions/339923/set-cellpadding-and-cellspacing-in-css38:[{"id":"2ad7dda92fec7693e892b16fdeae223e156d9d934fb8e79841ccf74750d23c703f7a6b6d6f0a30a0d526e9b046ac4280b4db98e8905eabe6c1597bbbaeef063a","href":"https://static.observableusercontent.com/files/2ad7dda92fec7693e892b16fdeae223e156d9d934fb8e79841ccf74750d23c703f7a6b6d6f0a30a0d526e9b046ac4280b4db98e8905eabe6c1597bbbaeef063a","name":"query@4.csv","type":"text/csv","lastModified":1646430921829.084,"size":191526},{"id":"6a853c0895dbfb17e8990b2650c5ab56bcf75b257837158e5d1047f6e77d141b65bb3838335267d711392747870a6cb7a22274e1bd53606b98bba0d0645d4b5e","href":"https://static.observableusercontent.com/files/6a853c0895dbfb17e8990b2650c5ab56bcf75b257837158e5d1047f6e77d141b65bb3838335267d711392747870a6cb7a22274e1bd53606b98bba0d0645d4b5e","name":"ipeds-glob.csv","type":"text/csv","lastModified":1646426375509.531,"size":129006},{"id":"d43695f82f6bc645cf86aba73bb2ae5996d60c72ba3e34356305ce809dc730409a8147d55be4152d9cb11e5d26f8041fd737c6d969469079467cf60dc577ed46","href":"https://static.observableusercontent.com/files/d43695f82f6bc645cf86aba73bb2ae5996d60c72ba3e34356305ce809dc730409a8147d55be4152d9cb11e5d26f8041fd737c6d969469079467cf60dc577ed46","name":"edges.csv","type":"text/csv","lastModified":1646432027966.818,"size":124023},{"id":"9f85614f3cbf1a4839700bb5130dbe9a6dd089dafd5d2435d49c9379123d6b1ffb320843e378ce669ff360abd902285149c5edfe499570877b6f7bcc849f61ce","href":"https://static.observableusercontent.com/files/9f85614f3cbf1a4839700bb5130dbe9a6dd089dafd5d2435d49c9379123d6b1ffb320843e378ce669ff360abd902285149c5edfe499570877b6f7bcc849f61ce","name":"query-universities-wiki@2.csv","type":"text/csv","lastModified":1646432244720.989,"size":19091}] 2d:{"title":"US Computer Science Faculty Pipeline","cells":[{"id":0,"value":"# US Computer Science Faculty Pipeline","pinned":false,"hidden":false,"mode":"md"},{"id":1060,"value":"## Dashboard","pinned":false,"hidden":false,"mode":"md"},{"id":994,"value":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n

${viewof univ}		${viewof scatter0d3}
${viewof brushedschools}	${viewof scatter0zoom}
${await(chart1barv2().render())}	${await(chart2line().render())}
${viewof barshow}
${await(chart3bar().render())}	${await(chart2zerobar().render())}
${viewof bar3zoom}	${viewof zerobarshow}

","pinned":false,"hidden":false,"mode":"html"},{"id":2630,"value":"viewof tofrom = Inputs.radio([\"to\", \"from\"], {label: \"employment:\", value: 'from'})","pinned":false,"hidden":false,"mode":"ojs"},{"id":49,"value":"## Chart Functions","pinned":false,"hidden":false,"mode":"md"},{"id":2067,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs"},{"id":961,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":924,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":1597,"value":"chart3bar = function() {\n if (tofrom == 'from') {\n if (bar3zoom.includes(\"employer\")) return chart3emplbar(); //covers almazoom also\n else if (bar3zoom.includes(\"alma\")) return chart3almazoombar();\n else return chart3regionbar();\n }\n else {\n if (bar3zoom.includes(\"employer\") && bar3zoom.includes(\"alma\")) return chart3emplbar();\n else if (bar3zoom.includes(\"employer\")) return chart3almazoombar();\n else if (bar3zoom.includes(\"alma\")) return chart3emplbar();\n else return chart3regionbar();\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1558,"value":"chart3regionbar = function(){\n\n const mydata = (tofrom == 'from') ? facedge_data_regionroll2 : facedge_data_regionroll2_inv;\n const mylab = (tofrom == 'from') ? 'employer' : 'alma';\n const myotherlab = (tofrom == 'from') ? 'alma' : 'employer';\n \n const chart1 = vl.markBar()\n /*.data(aq.from(region_flow).filter(aq.escape(d => d.source == facnet_selected.Region + \" Alma\")))\n .encode(\n vl.y().fieldO(\"target\").title(\"Employer\")\n .sort(vl.fieldQ('value').order('descending')),\n vl.x().fieldQ(\"value\"),\n vl.color({value: 'grey'})\n )*/\n .data(mydata)\n .encode(\n vl.y().fieldO(mylab + \"_region\").title(mylab)\n .sort(vl.fieldQ('count').order('descending')),\n vl.x().fieldQ(\"count\"),\n vl.color().fieldN(\"gender\").scale({\n \"domain\": [\"female\", \"male\"],\n \"range\": [\"#Fc7d0b\", 'steelblue']\n })\n )\n .width(150)\n .height(60)\n .title(\"2012 \" + mylab + \" Regions, \" + facnet_selected.Region + \" Region \" + myotherlab);\n return chart1;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1572,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1625,"value":"chart3almazoombar = function() {\n\n const mydata = (tofrom == 'from') ? facedge_data_regzoom_alma : facedge_data_regzoom_alma_inv;\n const mylab = (tofrom == 'from') ? 'employer' : 'alma';\n const myotherlab = (tofrom == 'from') ? 'alma' : 'employer';\n\nreturn vl.markBar()\n .data(mydata)\n .encode(\n vl.y().fieldO(mylab + \"_region\").title(mylab)\n .sort(vl.fieldQ('count').order('descending')),\n vl.x().fieldQ(\"count\"),\n //vl.color({value: 'grey'})\n vl.color().fieldN(\"gender\").scale({\n \"domain\": [\"female\", \"male\"],\n \"range\": [\"#Fc7d0b\", 'steelblue']\n })\n )\n .width(150)\n .height(60)\n .title(\"2012 \" + mylab + \" Regions, \" + facnet_selected.school + \" \" + myotherlab)\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1921,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":1479,"value":"## Inputs Setup\nThe inputs appear blank below; they have been added to the dashboard HTML table.","pinned":false,"hidden":false,"mode":"md"},{"id":1925,"value":"viewof scatter0d3 = brushableScatterplot()","pinned":false,"hidden":false,"mode":"ojs"},{"id":52,"value":"viewof univ = Select(new Set(facnet_data2.filter(aq.escape(d => !op.includes(ipeds_nograds,d.ipeds_id))).array('institution')), {label: \"Institution\", value: \"University of North Carolina, Chapel Hill\", width: 310})","pinned":false,"hidden":false,"mode":"ojs"},{"id":952,"value":"viewof zerobarshow = Inputs.radio([\"count\", \"streak\"], {label: \"display:\", value: 'count'})","pinned":false,"hidden":false,"mode":"ojs"},{"id":214,"value":"viewof barshow = Inputs.radio([\"pct\", \"count\"], {label: \"comparison:\", value: 'pct'})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1682,"value":"viewof bar3zoom = Inputs.checkbox([\"employer\", \"alma\"], {label: \"zoom:\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1885,"value":"viewof scatter0zoom = Inputs.checkbox([\"Midwest\", \"Northeast\", \"South\", \"West\"], {value: [\"Midwest\", \"Northeast\", \"South\", \"West\"], label: \"region:\"})\n//bind to selection","pinned":false,"hidden":false,"mode":"ojs"},{"id":2086,"value":"viewof brushedschools = Inputs.select(facedge_data4.array('institution'), {label: \"Benchmark Instititions\", multiple: 4, width: 310})","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"$34","pinned":false,"hidden":false,"mode":"md"},{"id":1339,"value":"### Selected institutions data","pinned":false,"hidden":false,"mode":"md"},{"id":75,"value":"facnet_selected = facnet_data2.filter(aq.escape(d => d.institution == univ)).objects()[0]","pinned":false,"hidden":false,"mode":"ojs"},{"id":180,"value":"selected_region = facnet_data2.filter(aq.escape(d => d.Region == facnet_selected.Region))","pinned":false,"hidden":false,"mode":"ojs"},{"id":2193,"value":"facnet_selected3 = facnet_data2.filter(aq.escape(d => op.includes(brushedschools, d.institution)))\n .concat(facnet_data2.filter(aq.escape(aq.escape(d => d.ipeds_id == facnet_selected.ipeds_id))))\n .array('ipeds_id')","pinned":false,"hidden":false,"mode":"ojs"},{"id":1233,"value":" ### Data for Gender Diversity Bar Chart","pinned":false,"hidden":false,"mode":"md"},{"id":2069,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":1237,"value":"### Data for Line chart","pinned":false,"hidden":false,"mode":"md"},{"id":17,"value":"raw_ipeds_data = FileAttachment(\"ipeds-glob.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":30,"value":"ipeds_data = aq.from(raw_ipeds_data)\n //.concat(aq.table({ year: [2011], ipeds_id: [190044], cip: [11.0101], major_num: [1], degree_code: [17], total: [0], men: [0], women: [0] }))","pinned":false,"hidden":false,"mode":"ojs"},{"id":229,"value":"ipeds_data_rollup = ipeds_data\n .groupby('year')\n .rollup({type: d => 'men', count: d => op.sum(d.men)})\n .concat(\n ipeds_data\n .groupby('year')\n .rollup({type: d => 'women', count: d => op.sum(d.women)})\n )\n .orderby('type', 'year')\n .groupby('type')\n .derive({ ra: aq.rolling(d => op.sum(d.count)) })\n//https://observablehq.com/@uwdata/arquero-cookbook#cumulative_sum","pinned":false,"hidden":false,"mode":"ojs"},{"id":255,"value":"ipeds_data_line = ipeds_data\n .groupby('ipeds_id', 'year')\n .rollup({type: d => 'men', count: d => op.sum(d.men)})\n .concat(\n ipeds_data\n .groupby('ipeds_id', 'year')\n .rollup({type: d => 'women', count: d => op.sum(d.women)})\n //.derive({avg: d => aq.escape(facnet_selected_avg)})\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":685,"value":"ipeds_data_line2 = ipeds_data_line\n .derive({avg: aq.escape(d => d.ipeds_id == facnet_selected.ipeds_id ? facnet_selected_avg : 0)})","pinned":false,"hidden":false,"mode":"ojs"},{"id":433,"value":"ipeds_data_rollup2 = ipeds_data\n .groupby('ipeds_id')\n .rollup({type: d => 'men', count: d => op.sum(d.men)})\n .concat(\n ipeds_data\n .groupby('ipeds_id')\n .rollup({type: d => 'women', count: d => op.sum(d.women)})\n )\n .orderby('ipeds_id')\n .derive({count_m_phd: d => d.type == 'men' ? d.count : 0})\n .derive({count_f_phd: d => d.type == 'men' ? 0 : d.count})\n .groupby('ipeds_id')\n .rollup({count_m_phd: d => op.max(d.count_m_phd), count_f_phd: d => op.max(d.count_f_phd)})\n .derive({pct_phd: d => d.count_f_phd / (d.count_m_phd + d.count_f_phd)})\n//https://observablehq.com/@uwdata/arquero-cookbook#cumulative_sum","pinned":false,"hidden":false,"mode":"ojs"},{"id":471,"value":"ipeds_selected = ipeds_data_line.filter(aq.escape(d => d.ipeds_id == facnet_selected.ipeds_id))\n .filter(d => d.type == 'women')\n .orderby( 'year')\n .derive({ ra: aq.rolling(d => op.sum(d.count)) })","pinned":false,"hidden":false,"mode":"ojs"},{"id":2175,"value":"ipeds_data_line_wholeavg = ipeds_data\n .groupby('year')\n .rollup({type: d => 'men', count: d => op.average(d.men)})\n .concat(\n ipeds_data\n .groupby('year')\n .rollup({type: d => 'women', count: d => op.average(d.women)})\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":2545,"value":"ipeds_nograds = ipeds_data_line\n .groupby('ipeds_id')\n .rollup({avg: d => op.average(d.count)})\n .orderby('avg')\n .filter(d => d.avg < .0001)\n .array('ipeds_id')","pinned":false,"hidden":false,"mode":"ojs"},{"id":1243,"value":"### Data for Zero bar chart","pinned":false,"hidden":false,"mode":"md"},{"id":862,"value":"ipeds_all_zeroes = ipeds_data_line\n .filter(d => d.type == 'women')\n .orderby('ipeds_id', 'year')\n .groupby('ipeds_id')\n .derive({ ra: aq.rolling(d => op.sum(d.count)) })","pinned":false,"hidden":false,"mode":"ojs"},{"id":869,"value":"ipeds_all_zero_rollup = ipeds_all_zeroes\n .filter(d => d.count == 0)\n .groupby('ipeds_id')\n .rollup({ipeds_id: d => op.max(d.ipeds_id), zero_ct_arr: d => op.array_agg(d.count)})\n .derive({zero_ct: aq.escape(d => d.zero_ct_arr.length)})\n .select('ipeds_id', 'zero_ct') //https://uwdata.github.io/arquero/api/op#count\n .derive({zero_streak: aq.escape(d => ipeds_zero_streak.get(d.ipeds_id))})\n .orderby('ipeds_id')\n .derive({zero_type: d => ['count', 'streak']})\n .derive({zero_count: d => [d.zero_ct, d.zero_streak]})\n .unroll(['zero_type', 'zero_count'] )\n .select('ipeds_id', 'zero_type', 'zero_count')\n .join(facedge_data3)\n .select('ipeds_id', 'zero_type', 'zero_count', 'school')","pinned":false,"hidden":false,"mode":"ojs"},{"id":881,"value":"ipeds_zero_avg = ipeds_all_zero_rollup\n .groupby('zero_type')\n .rollup({avg: d => op.average(d.zero_count)})","pinned":false,"hidden":false,"mode":"ojs"},{"id":865,"value":"ipeds_zero_streak = {\n let m = new Map();//https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Map\n \n let long = 0;\n let longest = 0;\n let id = ipeds_all_zeroes.objects()[0].ipeds_id;\n for (let i = 0; i < ipeds_all_zeroes.objects().length; i++) {\n if (ipeds_all_zeroes.objects()[i].ipeds_id != id) {\n if (long > longest) longest = long;\n m.set(id, longest);\n id = ipeds_all_zeroes.objects()[i].ipeds_id;\n long = 0;\n longest = 0;\n }\n \n let curr = ipeds_all_zeroes.objects()[i].count;\n if (curr == 0) {\n long++;\n }\n else {\n if (long > longest) longest = long;\n long = 0;\n }\n }\n return m;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1240,"value":"### Faculty data","pinned":false,"hidden":false,"mode":"md"},{"id":21,"value":"raw_facnet_data = FileAttachment(\"query-universities-wiki@2.csv\").csv({typed: true})\n//trim spaces","pinned":false,"hidden":false,"mode":"ojs"},{"id":26,"value":"facnet_data = aq.from(raw_facnet_data)\n .derive({Region: d => op.trim(d.Region)})\n .derive({wiki_id: d => d.u == 111 ? 'http://www.wikidata.org/entity/Q1079140' : d.wiki_id})//indiana u\n .derive({wiki_id: d => d.u == 162 ? 'http://www.wikidata.org/entity/Q749718' : d.wiki_id})//oklahoma s u\n .derive({wiki_id: d => d.u == 58 ? 'http://www.wikidata.org/entity/Q1024543' : d.wiki_id})//cuny","pinned":false,"hidden":false,"mode":"ojs"},{"id":24,"value":"raw_ipedwiki_data = FileAttachment(\"query@4.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":33,"value":"ipedwiki_data = aq.from(raw_ipedwiki_data)\n .concat(aq.table({ wiki_id: ['http://www.wikidata.org/entity/Q1024543'], institution2: ['Graduate Center, CUNY'], ipeds_id: ['190576'] }))\n//https://observablehq.com/@uwdata/arquero-row-manipulation","pinned":false,"hidden":false,"mode":"ojs"},{"id":36,"value":"facnet_data2 = facnet_data.join(ipedwiki_data)\n .orderby('institution')\n //.orderby('u')\n .derive({school: d => op.replace(d.institution, /[^A-Z]/g, '')})\n // .view(500)\n//rutgers 186380\n//poly = tandon 194541","pinned":false,"hidden":false,"mode":"ojs"},{"id":2453,"value":"facnet_arr1 = facnet_data2.array('u')","pinned":false,"hidden":false,"mode":"ojs"},{"id":2455,"value":"//1-206\nfacnet_arr2 = [...Array(206).keys()]\n//https://tobiasljungstrom.net/blog/2019-07-26-array-of-sequential-numbers-in-js/","pinned":false,"hidden":false,"mode":"ojs"},{"id":2458,"value":"facnet_missing_u = facnet_arr2.filter(value => !facnet_arr1.includes(value));\n//https://stackoverflow.com/questions/1187518/how-to-get-the-difference-between-two-arrays-in-javascript","pinned":false,"hidden":false,"mode":"ojs"},{"id":2470,"value":"facnet_data2_missing = facnet_data.filter(aq.escape(d => facnet_missing_u.includes(d.u)))\n .filter(d => d.Region != 'Canada')\n//CUNY Graduate CenterQ1024543 190576 not in data set add\n//Indiana University Q1079140 151351\n//Oklahoma State University Q749718 207388","pinned":false,"hidden":false,"mode":"ojs"},{"id":81,"value":"raw_facedge_data = FileAttachment(\"edges.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":86,"value":"facedge_data = aq.from(raw_facedge_data)\n .derive({alma_region: aq.escape(d => u_to_region(d.alma)),\n employer_region: aq.escape(d => u_to_region(d.employer))})","pinned":false,"hidden":false,"mode":"ojs"},{"id":154,"value":"facedge_data2 = {\n var data = [];\n Object.keys(facedge_rollup2).forEach(function(key){\n data.push({'u': key, 'type': 'alma', 'count': facedge_rollup2[key].M, 'gender': 'M', pct: facedge_rollup2[key].M / (facedge_rollup2[key].M + facedge_rollup2[key].F)});\n data.push({'u': key, 'type': 'alma', 'count' : facedge_rollup2[key].F, 'gender': 'F', pct: facedge_rollup2[key].F / (facedge_rollup2[key].M + facedge_rollup2[key].F)});\n \n });\n Object.keys(facedge_rollup2b).forEach(function(key){\n//data.push({'u': key, 'type': 'employer', 'M': facedge_rollup2b[key].M, 'F': facedge_rollup2b[key].F});\n data.push({'u': key, 'type': 'employer', 'count': facedge_rollup2b[key].M, 'gender': 'M', pct: facedge_rollup2b[key].M / (facedge_rollup2b[key].M + facedge_rollup2b[key].F)});\n data.push({'u': key, 'type': 'employer', 'count' : facedge_rollup2b[key].F, 'gender': 'F', pct: facedge_rollup2b[key].F / (facedge_rollup2b[key].M + facedge_rollup2b[key].F)});\n });\n return data;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":379,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":2008,"value":"facedge_data4 = facedge_data3.filter(aq.escape(d => op.includes(scatter0zoom, d.Region)))\n .filter(aq.escape(d => d.pct_alma >= scatter_window[0] && d.pct_alma <= scatter_window[1] && \n d.pct_emp >= scatter_window[2] && d.pct_emp <= scatter_window[3]))\n .orderby('institution')","pinned":false,"hidden":false,"mode":"ojs"},{"id":446,"value":"ipeds_data_rollup2_join = ipeds_data_rollup2\n .join(ipedwiki_data)","pinned":false,"hidden":false,"mode":"ojs"},{"id":100,"value":"facedge_rollup = facedge_data.array('alma_gender').reduce(function (acc, curr) {\n return acc[curr] ? ++acc[curr] : acc[curr] = 1, acc\n}, {})","pinned":false,"hidden":false,"mode":"ojs"},{"id":148,"value":"facedge_rollup1b = facedge_data.array('employer_gender').reduce(function (acc, curr) {\n return acc[curr] ? ++acc[curr] : acc[curr] = 1, acc\n}, {})","pinned":false,"hidden":false,"mode":"ojs"},{"id":151,"value":"facedge_rollup2 = {\n\nvar newHashmap = {};\nObject.keys(facedge_rollup).forEach(function(key){\n var value = facedge_rollup[key];\n key = key.substring(0, key.indexOf(\"_\"));\n newHashmap[key]= {};\n});\n\n Object.keys(facedge_rollup).forEach(function(key){\n var value = facedge_rollup[key];\n\n var key2 = key.substring(0, key.indexOf(\"_\"));\n var key3 = key.indexOf('M') > 0 ? 'M' : 'F';\n newHashmap[key2][key3] = value;\n});\n\n return newHashmap;\n}\n//https://stackoverflow.com/questions/5667888/counting-the-occurrences-frequency-of-array-elements\n//https://www.w3schools.com/jsref/jsref_substring.asp\n//https://stackoverflow.com/questions/17539236/how-to-replace-name-keys-in-a-javascript-keyvalue-object","pinned":false,"hidden":false,"mode":"ojs"},{"id":105,"value":"facedge_rollup2b = {\n\nvar newHashmap = {};\nObject.keys(facedge_rollup1b).forEach(function(key){\n var value = facedge_rollup1b[key];\n key = key.substring(0, key.indexOf(\"_\"));\n newHashmap[key]= {};\n});\n\n Object.keys(facedge_rollup1b).forEach(function(key){\n var value = facedge_rollup1b[key];\n\n var key2 = key.substring(0, key.indexOf(\"_\"));\n var key3 = key.indexOf('M') > 0 ? 'M' : 'F';\n newHashmap[key2][key3] = value;\n});\n\n return newHashmap;\n}\n//https://stackoverflow.com/questions/5667888/counting-the-occurrences-frequency-of-array-elements\n//https://www.w3schools.com/jsref/jsref_substring.asp\n//https://stackoverflow.com/questions/17539236/how-to-replace-name-keys-in-a-javascript-keyvalue-object","pinned":false,"hidden":false,"mode":"ojs"},{"id":1818,"value":"### Faculty data for employer bar charts","pinned":false,"hidden":false,"mode":"md"},{"id":1483,"value":"facedge_data_top5_alma_inst = facedge_data\n .filter(aq.escape(d => d.alma == facnet_selected.u))\n .groupby('employer')\n .rollup({count: d => op.count()})\n .orderby(aq.desc('count'))\n .derive({institution: aq.escape(d => u_to_name(d.employer, false))})\n .slice(0,5)\n//indiana university 111 doesn't have an ipeds id - check for other us schools","pinned":false,"hidden":false,"mode":"ojs"},{"id":2618,"value":"facedge_data_top5_alma_inst_inv = facedge_data\n .filter(aq.escape(d => d.employer == facnet_selected.u))\n .filter(d => d.alma != 206)\n .groupby('alma')\n .rollup({count: d => op.count()})\n .orderby(aq.desc('count'))\n .derive({institution: aq.escape(d => u_to_name(d.alma, false))})\n .slice(0,5)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1660,"value":"facedge_data_top5_alma_inst2 = facedge_data\n .filter(aq.escape(d => d.alma == facnet_selected.u))\n .filter(aq.escape(d => op.includes(facedge_data_top5_alma_inst.array('employer'), d.employer)))\n .groupby('employer_gender')\n .rollup({count: d => op.count()})\n .derive({employer: d => op.substring(d.employer_gender, 0, d.employer_gender.length-2)})\n .derive({gender: d => op.substring(d.employer_gender, d.employer_gender.length-1, d.employer_gender.length)})\n .derive({gender: d => d.gender == 'M' ? 'male' : 'female'})\n .derive({institution: aq.escape(d => u_to_name(d.employer, false))})\n .derive({institution: d => op.replace(d.institution, 'University', 'U')})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2620,"value":"facedge_data_top5_alma_inst2_inv = facedge_data\n .filter(aq.escape(d => d.employer == facnet_selected.u))\n .filter(aq.escape(d => op.includes(facedge_data_top5_alma_inst_inv.array('alma'), d.alma)))\n .groupby('alma_gender')\n .rollup({count: d => op.count()})\n .derive({alma: d => op.substring(d.alma_gender, 0, d.alma_gender.length-2)})\n .derive({gender: d => op.substring(d.alma_gender, d.alma_gender.length-1, d.alma_gender.length)})\n .derive({gender: d => d.gender == 'M' ? 'male' : 'female'})\n .derive({institution: aq.escape(d => u_to_name(d.alma, false))})\n .derive({institution: d => op.replace(d.institution, 'University', 'U')})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1492,"value":"facedge_data_top5_alma_reg = facedge_data\n .filter(aq.escape(d => d.alma_region == facnet_selected.Region))\n .groupby('employer')\n .rollup({count: d => op.count()})\n .orderby(aq.desc('count'))\n .derive({institution: aq.escape(d => u_to_name(d.employer, false))})\n .slice(0,5)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2622,"value":"facedge_data_top5_alma_reg_inv = facedge_data\n .filter(aq.escape(d => d.employer_region == facnet_selected.Region))\n .filter(d => d.alma != 206)\n .groupby('alma')\n .rollup({count: d => op.count()})\n .orderby(aq.desc('count'))\n .derive({institution: aq.escape(d => u_to_name(d.alma, false))})\n .slice(0,5)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1677,"value":"facedge_data_top5_alma_reg2 = facedge_data\n .filter(aq.escape(d => d.alma_region == facnet_selected.Region))\n .filter(aq.escape(d => op.includes(facedge_data_top5_alma_reg.array('employer'), d.employer)))\n .groupby('employer_gender')\n .rollup({count: d => op.count()})\n .derive({employer: d => op.substring(d.employer_gender, 0, d.employer_gender.length-2)})\n .derive({gender: d => op.substring(d.employer_gender, d.employer_gender.length-1, d.employer_gender.length)})\n .derive({gender: d => d.gender == 'M' ? 'male' : 'female'})\n .derive({institution: aq.escape(d => u_to_name(d.employer, false))})\n .derive({institution: d => op.replace(d.institution, 'University', 'U')})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2624,"value":"facedge_data_top5_alma_reg2_inv = facedge_data\n .filter(aq.escape(d => d.employer_region == facnet_selected.Region))\n .filter(aq.escape(d => op.includes(facedge_data_top5_alma_reg_inv.array('alma'), d.alma)))\n .groupby('alma_gender')\n .rollup({count: d => op.count()})\n .derive({employer: d => op.substring(d.alma_gender, 0, d.alma_gender.length-2)})\n .derive({gender: d => op.substring(d.alma_gender, d.alma_gender.length-1, d.alma_gender.length)})\n .derive({gender: d => d.gender == 'M' ? 'male' : 'female'})\n .derive({institution: aq.escape(d => u_to_name(d.employer, false))})\n .derive({institution: d => op.replace(d.institution, 'University', 'U')})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1612,"value":"/*viewof facedge_data_regzoom_alma = facedge_data\n .filter(aq.escape(d => d.alma == facnet_selected.u))\n .groupby('employer_region')\n .rollup({count: d => op.count()})\n .view()*/\nfacedge_data_regzoom_alma = facedge_data\n .filter(aq.escape(d => d.alma == facnet_selected.u))\n .filter(d => !op.includes(['Canada'], d.employer_region))\n .derive({emp_reg_gend: d => d.employer_region + d.gender})\n .groupby('emp_reg_gend')\n .rollup({count: d => op.count()})\n .derive({employer_region: d => op.substring(d.emp_reg_gend, 0, d.emp_reg_gend.length-1)})\n .derive({gender: d => op.substring(d.emp_reg_gend, d.emp_reg_gend.length-1, d.emp_reg_gend.length)})\n .derive({gender: d => d.gender == 'M' ? 'male' : 'female'})\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":2628,"value":"facedge_data_regzoom_alma_inv = facedge_data\n .filter(aq.escape(d => d.employer == facnet_selected.u))\n .filter(d => !op.includes(['Canada'], d.alma_region))\n .derive({alma_reg_gend: d => d.alma_region + d.gender})\n .groupby('alma_reg_gend')\n .rollup({count: d => op.count()})\n .derive({alma_region: d => op.substring(d.alma_reg_gend, 0, d.alma_reg_gend.length-1)})\n .derive({gender: d => op.substring(d.alma_reg_gend, d.alma_reg_gend.length-1, d.alma_reg_gend.length)})\n .derive({gender: d => d.gender == 'M' ? 'male' : 'female'})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1633,"value":"facedge_data_regionroll = facedge_data\n .filter(aq.escape(d => d.alma_region == facnet_selected.Region))\n .groupby('employer_region')\n .rollup({count: d => op.count()})\n .filter(d => !op.includes(['Canada'], d.employer_region))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1641,"value":"facedge_data_regionroll2 = facedge_data\n .filter(aq.escape(d => d.alma_region == facnet_selected.Region))\n .filter(d => !op.includes(['Canada'], d.employer_region))\n .derive({emp_reg_gend: d => d.employer_region + d.gender})\n .groupby('emp_reg_gend')\n .rollup({count: d => op.count()})\n .derive({employer_region: d => op.substring(d.emp_reg_gend, 0, d.emp_reg_gend.length-1)})\n .derive({gender: d => op.substring(d.emp_reg_gend, d.emp_reg_gend.length-1, d.emp_reg_gend.length)})\n .derive({gender: d => d.gender == 'M' ? 'male' : 'female'})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2614,"value":"facedge_data_regionroll_inv = facedge_data\n .filter(aq.escape(d => d.employer_region == facnet_selected.Region))\n .groupby('alma_region')\n .rollup({count: d => op.count()})\n .filter(d => !op.includes(['Canada'], d.alma_region))","pinned":false,"hidden":false,"mode":"ojs"},{"id":2616,"value":"facedge_data_regionroll2_inv = facedge_data\n .filter(aq.escape(d => d.employer_region == facnet_selected.Region))\n .filter(d => !op.includes(['Canada', 'Earth'], d.alma_region))\n .derive({alma_reg_gend: d => d.alma_region + d.gender})\n .groupby('alma_reg_gend')\n .rollup({count: d => op.count()})\n .derive({alma_region: d => op.substring(d.alma_reg_gend, 0, d.alma_reg_gend.length-1)})\n .derive({gender: d => op.substring(d.alma_reg_gend, d.alma_reg_gend.length-1, d.alma_reg_gend.length)})\n .derive({gender: d => d.gender == 'M' ? 'male' : 'female'})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1203,"value":"### Data Calculations","pinned":false,"hidden":false,"mode":"md"},{"id":1973,"value":"mutable scatter_window = Array();","pinned":false,"hidden":false,"mode":"ojs"},{"id":563,"value":"facnet_scalemax = ipeds_data_line_wholeavg//ipeds_data_line.filter(aq.escape(d => d.ipeds_id == facnet_selected2.ipeds_id))\n .concat(ipeds_data_line.filter(aq.escape(d => d.ipeds_id == facnet_selected.ipeds_id)))\n .rollup({max: d => op.max(d.count)})\n .objects()[0].max","pinned":false,"hidden":false,"mode":"ojs"},{"id":663,"value":"facnet_selected_avg = ipeds_data_line.filter(aq.escape(d => d.ipeds_id == facnet_selected.ipeds_id))\n .filter(d => d.type == 'women')\n .rollup({avg: d => op.average(d.count)})\n .objects()[0].avg","pinned":false,"hidden":false,"mode":"ojs"},{"id":657,"value":"## Functions","pinned":false,"hidden":false,"mode":"md"},{"id":1979,"value":"scatter_window_filter = function(data) {\n mutable scatter_window = data; //https://observablehq.com/@observablehq/observables-not-javascript\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1193,"value":"function u_to_region(u) {\n return facnet_data.filter(aq.escape(d => d.u == u)).objects()[0].Region;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1497,"value":"u_to_name = function(u, nickname) {\n let ipeds_lookup = facnet_data2.filter(aq.escape(d => d.u == u)).objects();\n if (ipeds_lookup.length == 0) return \"\";\n let ret_data = facedge_data3.filter(aq.escape(d => d.ipeds_id == ipeds_lookup[0].ipeds_id)).objects();\n if (ret_data.length == 0) {\n return (nickname == true) ?ipeds_lookup[0].institution.replace(/[^A-Z]/g, '') : ipeds_lookup[0].institution;\n }\n return (nickname == true) ? ret_data[0].school : ret_data[0].institution;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"## Appendix","pinned":false,"hidden":false,"mode":"md"},{"id":3,"value":"import {aq, op} from \"@uwdata/arquero\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":45,"value":"import {Range, Select} from \"@observablehq/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":331,"value":"import {vl} from \"@vega/vega-lite-api-v5\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1310,"value":"$37","pinned":false,"hidden":false,"mode":"md"}],"files":"$W38","stdlib":"1","titling":"auto"}