2e:null 2f:["$","title",null,{"children":"The Jobs Calculator | Justus Schollmeyer | Observable"}] 34:T4a2,textExpl1 = html`

The starting numbers above reflect the investments needed to fulfill the THRIVE Agenda — an economic renewal plan to create nearly 16 million jobs — backed by over 100 members of Congress and hundreds of union, racial justice, climate, and other grassroots organizations. For details on these investments and the kinds of jobs they would create, see How to Build Back Better: A 10-Year Plan for Economic Renewal. For a closer look at the underlying data and jobs modeling methodology, see the Political Economy Research Institute’s Employment Impacts of Proposed U.S. Economic Stimulus Programs: Job Creation, Job Quality, and Demographic Distribution Measures. Click here for fact sheets on each investment category.

`35:T5df,columnsDisagg = [ { name: "Sectors", cellType: "fix", data: retrieveDataFromDf( dataSelected, dataSelected.length + 1, "Sectors", "Total" ), total: false, className: "text" }, { name: "Annual budget in billions of US$", cellType: "input", data: addMutableColumnData( dataSelected, dataSelected.length + 1, ``, `` ), total: true, rounding: "toFixed(3)", className: "number" }, { name: "Number of jobs created annually", cellType: "result", data: addMutableColumnData( dataSelected, dataSelected.length + 1, ``, `` ), operation: { variables: { array1: { columnTitle: "Annual budget in billions of US$", sourceType: "input" }, array2: { columnTitle: "Total Jobs", sourceType: "original" } }, operator: "*", factor: 1000 }, total: true, rounding: "round", className: "number" }, { name: "Total Jobs", cellType: "none", data: retrieveDataFromDf( dataSelected, dataSelected.length + 1, "Total Jobs", "" ), total: false, className: "number" } ]36:T15ab,createDynamicTable = (data, columns, css_instructions) => { let tableColumns = columns.filter(item => { return item.cellType != "none"; }); let columnNames = tableColumns.map(item => { return item.name; }); //Create a HTML Table element let table = document.createElement("TABLE"); table['border'] = "0"; //Create Style element to pass css_instructions let style = document.createElement("STYLE"); style.innerHTML = css_instructions; table.appendChild(style); //Add the header row let row = table.insertRow(-1); for (let i = 0; i < columnNames.length; i++) { let col = columnNames[i]; let headerCell = document.createElement("TH"); headerCell.class = tableColumns[i]["className"]; headerCell.innerHTML = col; row.appendChild(headerCell); } //Add the data rows //Loop through rows for (let i = 0; i < tableColumns[0].data.length; i++) { row = table.insertRow(-1); //Loop through cells per row for (let j = 0; j < tableColumns.length; j++) { let cell = row.insertCell(-1); cell.class = tableColumns[j]["className"]; cell.innerHTML = tableColumns[j]["data"][i]; } } let mutableColumns = columns.filter(item => { return item.cellType != "none" && item.cellType != "fix"; }); table.oninput = () => { const outputDict = {}; const inputElements = table.getElementsByTagName("input"); for (let col = 0; col < mutableColumns.length; col++) { let colValues = []; let columnName = mutableColumns[col].name; if (mutableColumns[col].cellType === "input") { for ( let e = col; e < inputElements.length; e += mutableColumns.length ) { colValues.push(inputElements[e].valueAsNumber); } outputDict[mutableColumns[col].name] = colValues; } else if (mutableColumns[col].cellType === "result") { let array1Title = mutableColumns[col]["operation"]["variables"]["array1"][ "columnTitle" ]; let array1SourceType = mutableColumns[col]["operation"]["variables"]["array1"]["sourceType"]; let operator = mutableColumns[col]["operation"]["operator"]; let factor = mutableColumns[col]["operation"]["factor"]; let array1Data = undefined; if (array1SourceType === "input") { array1Data = outputDict[array1Title]; } else if (array1SourceType === "original") { array1Data = outputDict[array1Title]; array1Data = columns.filter(item => item.name === array1Title)[0] .data; } else { array1Data = [1, 1, 1, 1, 1, 1, 1]; } let array2Title = mutableColumns[col]["operation"]["variables"]["array2"][ "columnTitle" ]; let array2SourceType = mutableColumns[col]["operation"]["variables"]["array2"]["sourceType"]; let array2Data = undefined; if (array2SourceType === "input") { array2Data = outputDict[array2Title]; } else if (array2SourceType === "original") { array2Data = columns.filter(item => item.name === array2Title)[0] .data; } colValues = interArrayOperation(array1Data, array2Data, operator); if (factor) { for (let k = 0; k < colValues.length; k++) { colValues[k] = colValues[k] * factor; } } outputDict[mutableColumns[col].name] = colValues; } } // Calculate totals for mutable columns (currently not checking whether or not to add totals but just asusming that it is desired) for (let i = 0; i < Object.keys(outputDict).length; i++) { let colNameOutputDict = Object.keys(outputDict)[i]; let dataArray = outputDict[colNameOutputDict]; for (let n = 0; n < dataArray.length; n++) { dataArray[n] = dataArray[n] || 0; } let totalValue = dataArray .slice(0, dataArray.length - 1) .reduce((a, b) => { return a + b; }, 0); dataArray[dataArray.length - 1] = totalValue; outputDict[colNameOutputDict] = dataArray; } // update values that are visible in cells of mutable columns for (let col = 0; col < Object.values(outputDict).length; col++) { let currentName = Object.keys(outputDict)[col]; let rounding = columns.filter(item => { return item.name === currentName; })[0]["rounding"]; let cellType = columns.filter(item => { return item.name === currentName; })[0]["cellType"]; let dataInColumn = outputDict[currentName]; // loop through the mutable columns for ( let c = col; c < inputElements.length; c += Object.values(outputDict).length ) { let rowIndex = Math.floor(c / Object.values(outputDict).length); if (rounding === "round" && cellType == "result") { inputElements[c].value = Math.round(dataInColumn[rowIndex]); } else if (rounding === "toFixed(3)" && cellType == "result") { inputElements[c].value = dataInColumn[rowIndex].toFixed(3); } else if (cellType === "result") { inputElements[c].value = dataInColumn[rowIndex]; } else if ( cellType === "input" && rowIndex === Object.values(outputDict)[0].length - 1 ) { inputElements[c].value = dataInColumn[rowIndex].toFixed(3); } } } table.value = outputDict; }; table.oninput(); return table; }37:T15e5,createDynamicTableWithSep = (data, columns, css_instructions) => { let tableColumns = columns.filter(item => { return item.cellType != "none"; }); let columnNames = tableColumns.map(item => { return item.name; }); //Create a HTML Table element let table = document.createElement("TABLE"); table['border'] = "0"; //Create Style element to pass css_instructions let style = document.createElement("STYLE"); style.innerHTML = css_instructions; table.appendChild(style); //Add the header row let row = table.insertRow(-1); for (let i = 0; i < columnNames.length; i++) { let col = columnNames[i]; let headerCell = document.createElement("TH"); headerCell.class = tableColumns[i]["className"]; headerCell.innerHTML = col; row.appendChild(headerCell); } //Add the data rows //Loop through rows for (let i = 0; i < tableColumns[0].data.length; i++) { row = table.insertRow(-1); //Loop through cells per row for (let j = 0; j < tableColumns.length; j++) { let cell = row.insertCell(-1); cell.class = tableColumns[j]["className"]; cell.innerHTML = tableColumns[j]["data"][i]; } } let mutableColumns = columns.filter(item => { return item.cellType != "none" && item.cellType != "fix"; }); table.oninput = () => { const outputDict = {}; const inputElements = table.getElementsByTagName("input"); for (let col = 0; col < mutableColumns.length; col++) { let colValues = []; let columnName = mutableColumns[col].name; if (mutableColumns[col].cellType === "input") { for ( let e = col; e < inputElements.length; e += mutableColumns.length ) { colValues.push(Number(inputElements[e].value)); } outputDict[mutableColumns[col].name] = colValues; } else if (mutableColumns[col].cellType === "result") { let array1Title = mutableColumns[col]["operation"]["variables"]["array1"][ "columnTitle" ]; let array1SourceType = mutableColumns[col]["operation"]["variables"]["array1"]["sourceType"]; let operator = mutableColumns[col]["operation"]["operator"]; let factor = mutableColumns[col]["operation"]["factor"]; let array1Data = undefined; if (array1SourceType === "input") { array1Data = outputDict[array1Title]; } else if (array1SourceType === "original") { array1Data = outputDict[array1Title]; array1Data = columns.filter(item => item.name === array1Title)[0] .data; } else { array1Data = [1, 1, 1, 1, 1, 1, 1]; } let array2Title = mutableColumns[col]["operation"]["variables"]["array2"][ "columnTitle" ]; let array2SourceType = mutableColumns[col]["operation"]["variables"]["array2"]["sourceType"]; let array2Data = undefined; if (array2SourceType === "input") { array2Data = outputDict[array2Title]; } else if (array2SourceType === "original") { array2Data = columns.filter(item => item.name === array2Title)[0] .data; } colValues = interArrayOperation(array1Data, array2Data, operator); if (factor) { for (let k = 0; k < colValues.length; k++) { colValues[k] = colValues[k] * factor; } } outputDict[mutableColumns[col].name] = colValues; } } // Calculate totals for mutable columns (currently not checking whether or not to add totals but just asusming that it is desired) for (let i = 0; i < Object.keys(outputDict).length; i++) { let colNameOutputDict = Object.keys(outputDict)[i]; let dataArray = outputDict[colNameOutputDict]; for (let n = 0; n < dataArray.length; n++) { dataArray[n] = dataArray[n] || 0; } let totalValue = dataArray .slice(0, dataArray.length - 1) .reduce((a, b) => { return a + b; }, 0); dataArray[dataArray.length - 1] = totalValue; outputDict[colNameOutputDict] = dataArray; } // update values that are visible in cells of mutable columns for (let col = 0; col < Object.values(outputDict).length; col++) { let currentName = Object.keys(outputDict)[col]; let rounding = columns.filter(item => { return item.name === currentName; })[0]["rounding"]; let cellType = columns.filter(item => { return item.name === currentName; })[0]["cellType"]; let dataInColumn = outputDict[currentName]; // loop through the mutable columns for ( let c = col; c < inputElements.length; c += Object.values(outputDict).length ) { let rowIndex = Math.floor(c / Object.values(outputDict).length); if (rounding === "round" && cellType == "result") { inputElements[c].value = addCommas(Math.round(dataInColumn[rowIndex])); } else if (rounding === "toFixed(3)" && cellType == "result") { inputElements[c].value = addCommas(dataInColumn[rowIndex].toFixed(3)); } else if (cellType === "result") { inputElements[c].value = addCommas(dataInColumn[rowIndex]); } else if ( cellType === "input" && rowIndex === Object.values(outputDict)[0].length - 1 ) { inputElements[c].value = addCommas(dataInColumn[rowIndex].toFixed(3)); } } } table.value = outputDict; }; table.oninput(); return table; }38:T594,function checkbox_menu_scroll(category_dict) { const checkbox_menu = html`

`; //let checkbox_menu = document.getElementById("scrollbox") for (let i=0; i0){ checkbox_menu.append(lineBreak); } checkbox_menu.append(header); for (let j=0; j' + choices[j] + '
'; checkbox_menu.append(div); } } checkbox_menu.oninput = () => { let new_values = []; let input_elements = checkbox_menu.getElementsByTagName("input"); for (let e=0; e

`; hc.chart(container_chart, { credits: { enabled: false }, chart: { type: 'column', zoomType: 'xy', style: { fontFamily: 'inherit', width: '100%' } }, // tooltip: { // headerFormat: '{point.x}
', // pointFormat: '{series.name}: {point.y}
Total: {point.stackTotal}' // }, plotOptions: { column: { stacking: 'normal', dataLabels: { enabled: true } } }, title: { text: "Jobs Created in Disaggregated Sectors (Manufacturing only)" }, xAxis: { categories: columnsDisagg[0].data.slice( 0, columnsDisagg[0].data.length - 1 ) }, yAxis: { //min: 0, title: { text: "Jobs Created" }, type: dictionary['scale'], stackLabels: { enabled: true, style: { fontWeight: 'bold', color: // theme (hc.defaultOptions.title.style && hc.defaultOptions.title.style.color) || 'gray' } } }, colors: ["#388092", "#C54F21", "#5B8049", "#163A48", "#9AD0D7", "#6D8045"], // yAxis: { // title: { // text:"Jobs Created" // }, // type:dictionary['scale'] // }, series: [ { name: 'Direct Jobs', data: getJobsDetailed( investmentDisagg, dataSelectedManu, 'Direct Jobs per million', 1000 ) }, { name: 'Indirect Jobs', data: getJobsDetailed( investmentDisagg, dataSelectedManu, 'Indirect Jobs per million', 1000 ) }, { name: 'Induced Jobs', data: getJobsDetailed( investmentDisagg, dataSelectedManu, 'Induced Jobs per million', 1000 ) } ] }); return container_chart; }3d:T480,function createGauge(gaugePair) { const gaugeChart = c3({ data: { columns: [ gaugePair ], type: 'gauge', onclick: function (d, i) { console.log("onclick", d, i); }, onmouseover: function (d, i) { console.log("onmouseover", d, i); }, onmouseout: function (d, i) { console.log("onmouseout", d, i); } }, gauge: { // label: { // format: function(value, ratio) { // return value; // }, // show: false // to turn off the min/max labels. // }, // min: 0, // 0 is default, //can handle negative min e.g. vacuum / voltage / current flow / rate of change // max: 100, // 100 is default // units: ' %', // width: 39 // for adjusting arc thickness }, color: { pattern: ['#FF0000', '#F97600', '#F6C600', '#60B044'], // the three color levels for the percentage values. threshold: { // unit: 'value', // percentage is default // max: 200, // 100 is default values: [30, 60, 90, 100] } }, size: { height: 180 } }); return gaugeChart}3e:Tb19,dataDisagg = d3.tsvParse(`Sectors Direct jobs Indirect jobs Induced Jobs Total Jobs Direct jobs (manu) Indirect Jobs (manu) Induced Jobs (manu) Total Jobs (manu) macro_category Surface transportation 11.6 3.3 5.7 20.6 0.6 0.7 0.2 1.5 Infrastructure programs Water/wastewater 5.9 3.4 5.4 14.7 0.7 0.5 0.2 1.4 Infrastructure programs Electricity 3.2 3.1 4.2 10.5 1.6 0.9 0.2 2.7 Infrastructure programs Airports 3.6 2.5 4.2 10.3 0.5 0.7 0.2 1.4 Infrastructure programs Inland waterways/marine ports 4.0 3.9 4.9 12.8 1.2 0.7 0.2 2.1 Infrastructure programs Dams 8.0 3.8 6.8 18.6 0.8 0.7 0.3 1.8 Infrastructure programs Hazardous and solid waste 6.5 3.4 5.4 15.3 0.0 0.5 0.2 0.7 Infrastructure programs Levees 8.1 3.8 6.9 18.8 0.8 0.7 0.3 1.8 Infrastructure programs Public parks and recreation 11.6 3.4 6.2 21.2 0.0 0.3 0.3 0.6 Infrastructure programs Rail 3.2 3.5 4.5 11.2 0.6 0.9 0.2 1.7 Infrastructure programs Schools 12.0 2.4 6.4 20.8 0.0 0.4 0.3 0.7 Infrastructure programs Gas distribution pipelines-leak repairs only 1.1 2.3 5.2 8.6 0.0 0.1 0.2 0.3 Infrastructure programs Broadband 2.5 3.6 4.0 10.1 0.6 0.5 0.2 1.3 Infrastructure programs Building retrofits 4.7 4.0 4.7 13.4 0.0 0.8 0.2 1.0 Clean renewable energy and energy efficiency programs Industrial efficiency 5.2 3.4 5.6 14.2 1.5 0.7 0.2 2.4 Clean renewable energy and energy efficiency programs High-efficiency autos 1.4 3.7 3.5 8.6 1.4 1.3 0.2 2.9 Clean renewable energy and energy efficiency programs Wind energy 3.6 3.5 4.7 11.8 1.9 0.7 0.2 2.8 Clean renewable energy and energy efficiency programs Solar energy 3.8 3.1 4.4 11.3 2.2 0.7 0.2 3.1 Clean renewable energy and energy efficiency programs Geothermal energy 3.7 3.2 4.8 11.7 0.4 0.4 0.2 1.0 Clean renewable energy and energy efficiency programs Regenerative agriculture 14.1 4.9 4.8 23.8 0.0 0.4 0.2 0.6 Agriculture and land restoration programs Farmland conservation 9.8 3.8 5.7 19.3 0.2 0.4 0.2 0.8 Agriculture and land restoration programs Organic farming 14.1 4.9 4.8 23.8 0.0 0.4 0.2 0.6 Agriculture and land restoration programs Resources for marginalized farmers 11.8 4.1 5.7 21.6 0.3 0.5 0.2 1.0 Agriculture and land restoration programs Agricultural R&D 6.9 3.8 5.5 16.2 0.1 0.2 0.2 0.5 Agriculture and land restoration programs Pollution cleanup 7.5 2.9 5.8 16.2 0.0 0.2 0.3 0.5 Agriculture and land restoration programs Closing orphaned wells 7.1 3.2 5.6 15.9 0.0 0.3 0.2 0.5 Agriculture and land restoration programs Ecosystem restoration 13.2 3.4 6.4 23.0 0.0 0.2 0.3 0.5 Agriculture and land restoration programs Care Economy 18.6 2.9 7.1 28.6 0.0 0.3 0.3 0.6 Care economy, public health, and postal service Public Health 8.0 3.2 5.9 17.1 0.0 0.2 0.3 0.5 Care economy, public health, and postal service Postal Service 7.6 2.2 6.2 16.0 0.4 0.5 0.3 1.2 Care economy, public health, and postal service`)3f:Tc80,dataDisaggBudget = d3.tsvParse(`Sectors Total Jobs/$1 Million Annual Budget Direct Jobs Indirect Jobs Induced Jobs Total Jobs macro_category Surface transportation 20.6 110100.0 1277160.0 363330.0 627570.0 2268060.0 Infrastructure programs Water/wastewater 14.7 32200.0 189980.0 109480.0 173880.0 473340.0 Infrastructure programs Electricity 10.5 42700.0 136640.0 132370.0 179340.0 448350.0 Infrastructure programs Airports 10.3 4200.0 15120.0 10500.0 17640.0 43260.0 Infrastructure programs Inland waterways/marine ports 12.8 1500.0 6000.0 5850.0 7350.0 19200.0 Infrastructure programs Dams 18.6 3900.0 31200.0 14820.0 26520.0 72540.0 Infrastructure programs Hazardous and solid waste 15.3 300.0 1950.0 1020.0 1620.0 4590.0 Infrastructure programs Levees 18.8 7000.0 56700.0 26600.0 48300.0 131600.0 Infrastructure programs Public parks and recreation 21.2 10200.0 118320.0 34680.0 63240.0 216240.0 Infrastructure programs Rail 11.2 20900.0 66880.0 73150.0 94050.0 234080.0 Infrastructure programs Schools 20.8 38000.0 456000.0 91200.0 243200.0 790400.0 Infrastructure programs Gas distribution pipelines-leak repairs only 8.6 18300.0 20130.0 42090.0 95160.0 157380.0 Infrastructure programs Broadband 10.1 35000.0 87500.0 126000.0 140000.0 353500.0 Infrastructure programs Building retrofits 13.4 56500.0 265550.0 226000.0 265550.0 757100.0 Clean renewable energy and energy efficiency programs Industrial efficiency 14.2 6300.0 32760.0 21420.0 35280.0 89460.0 Clean renewable energy and energy efficiency programs High-efficiency autos 8.6 56000.0 78400.0 207200.0 196000.0 481600.0 Clean renewable energy and energy efficiency programs Wind energy 11.8 108000.0 388800.0 378000.0 507600.0 1274400.0 Clean renewable energy and energy efficiency programs Solar energy 11.3 108000.0 410400.0 334800.0 475200.0 1220400.0 Clean renewable energy and energy efficiency programs Geothermal energy 11.7 24000.0 88800.0 76800.0 115200.0 280800.0 Clean renewable energy and energy efficiency programs Regenerative agriculture 23.8 41000.0 578100.0 200900.0 196800.0 975800.0 Agriculture and land restoration programs Farmland conservation 19.3 25000.0 245000.0 95000.0 142500.0 482500.0 Agriculture and land restoration programs Organic farming 23.8 1500.0 21150.0 7350.0 7200.0 35700.0 Agriculture and land restoration programs Resources for marginalized farmers 21.6 91000.0 1073800.0 373100.0 518700.0 1965600.0 Agriculture and land restoration programs Agricultural R&D 16.2 2500.0 17250.0 9500.0 13750.0 40500.0 Agriculture and land restoration programs Pollution cleanup 16.2 12600.0 94500.0 36540.0 73080.0 204120.0 Agriculture and land restoration programs Closing orphaned wells 15.9 12000.0 85200.0 38400.0 67200.0 190800.0 Agriculture and land restoration programs Ecosystem restoration 23.0 1000.0 13200.0 3400.0 6400.0 23000.0 Agriculture and land restoration programs Care Economy 28.6 77500.0 1441500.0 224750.0 550250.0 2216500.0 Care economy, public health, and postal service Public Health 17.1 4500.0 36000.0 14400.0 26550.0 76950.0 Care economy, public health, and postal service Postal Service 16.0 2500.0 19000.0 5500.0 15500.0 40000.0 Care economy, public health, and postal service`)40:Tfef,dataDisaggManu = d3.tsvParse(`Sectors Annual Budget Direct Jobs Indirect Jobs Induced Jobs Total Jobs macro_category sub_category Total Jobs per million Direct Jobs per million Indirect Jobs per million Induced Jobs per million Surface transportation 110100.0 66060.0 77070.0 22020.0 165150.0 Infrastructure programs Manufacturing Sector 1.5 0.6 0.7 0.2 Water/wastewater 32200.0 22540.0 16100.0 6440.0 45080.0 Infrastructure programs Manufacturing Sector 1.4 0.7 0.5 0.2 Electricity 42700.0 68320.0 38430.0 8540.0 115290.0 Infrastructure programs Manufacturing Sector 2.7 1.6 0.9 0.2 Airports 4200.0 2100.0 2940.0 840.0 5880.0 Infrastructure programs Manufacturing Sector 1.4 0.5 0.7 0.2 Inland waterways/marine ports 1500.0 1800.0 1050.0 300.0 3150.0 Infrastructure programs Manufacturing Sector 2.1 1.2 0.7 0.2 Dams 3900.0 3120.0 2730.0 1170.0 7020.0 Infrastructure programs Manufacturing Sector 1.8 0.8 0.7 0.3 Hazardous and solid waste 300.0 0.0 150.0 60.0 210.0 Infrastructure programs Manufacturing Sector 0.7 0.0 0.5 0.2 Levees 7000.0 5600.0 4900.0 2100.0 12600.0 Infrastructure programs Manufacturing Sector 1.8 0.8 0.7 0.3 Public parks and recreation 10200.0 0.0 3060.0 3060.0 6120.0 Infrastructure programs Manufacturing Sector 0.6 0.0 0.3 0.3 Rail 20900.0 12540.0 18810.0 4180.0 35530.0 Infrastructure programs Manufacturing Sector 1.7 0.6 0.9 0.2 Schools 38000.0 0.0 15200.0 11400.0 26600.0 Infrastructure programs Manufacturing Sector 0.7 0.0 0.4 0.3 Gas distribution pipelines-leak repairs only 18300.0 0.0 1830.0 3660.0 5490.0 Infrastructure programs Manufacturing Sector 0.3 0.0 0.1 0.2 Broadband 35000.0 21000.0 17500.0 7000.0 45500.0 Infrastructure programs Manufacturing Sector 1.3 0.6 0.5 0.2 Building retrofits 56500.0 0.0 45200.0 11300.0 56500.0 Clean renewable energy and energy efficiency programs Manufacturing Sector 1.0 0.0 0.8 0.2 Industrial efficiency 6300.0 9450.0 4410.0 1260.0 15120.0 Clean renewable energy and energy efficiency programs Manufacturing Sector 2.4 1.5 0.7 0.2 High-efficiency autos 56000.0 78400.0 72800.0 11200.0 162400.0 Clean renewable energy and energy efficiency programs Manufacturing Sector 2.9 1.4 1.3 0.2 Wind energy 108000.0 205200.0 75600.0 21600.0 302400.0 Clean renewable energy and energy efficiency programs Manufacturing Sector 2.8 1.9 0.7 0.2 Solar energy 108000.0 237600.0 75600.0 21600.0 334800.0 Clean renewable energy and energy efficiency programs Manufacturing Sector 3.1 2.2 0.7 0.2 Geothermal energy 24000.0 9600.0 9600.0 4800.0 24000.0 Clean renewable energy and energy efficiency programs Manufacturing Sector 1.0 0.4 0.4 0.2 Regenerative agriculture 41000.0 0.0 16400.0 8200.0 24600.0 Agriculture and land restoration programs Manufacturing Sector 0.6 0.0 0.4 0.2 Farmland conservation 25000.0 5000.0 10000.0 5000.0 20000.0 Agriculture and land restoration programs Manufacturing Sector 0.8 0.2 0.4 0.2 Organic farming 1500.0 0.0 600.0 300.0 900.0 Agriculture and land restoration programs Manufacturing Sector 0.6 0.0 0.4 0.2 Resources for marginalized farmers 91000.0 27300.0 45500.0 18200.0 91000.0 Agriculture and land restoration programs Manufacturing Sector 1.0 0.3 0.5 0.2 Agricultural R&D 2500.0 250.0 500.0 500.0 1250.0 Agriculture and land restoration programs Manufacturing Sector 0.5 0.1 0.2 0.2 Pollution cleanup 12600.0 0.0 2520.0 3780.0 6300.0 Agriculture and land restoration programs Manufacturing Sector 0.5 0.0 0.2 0.3 Closing orphaned wells 12000.0 0.0 3600.0 2400.0 6000.0 Agriculture and land restoration programs Manufacturing Sector 0.5 0.0 0.3 0.2 Ecosystem restoration 1000.0 0.0 200.0 300.0 500.0 Agriculture and land restoration programs Manufacturing Sector 0.5 0.0 0.2 0.3 Care Economy 77500.0 0.0 23250.0 23250.0 46500.0 Care economy, public health, and postal service Manufacturing Sector 0.6 0.0 0.3 0.3 Public Health 4500.0 0.0 900.0 1350.0 2250.0 Care economy, public health, and postal service Manufacturing Sector 0.5 0.0 0.2 0.3 Postal Service 2500.0 1000.0 1250.0 750.0 3000.0 Care economy, public health, and postal service Manufacturing Sector 1.2 0.4 0.5 0.3`)41:[] 32:{"id":"80082bb8f7c11161","slug":"the-jobs-calculator","title":"The Jobs Calculator","thumbnail":"cb01fa1310942c87fed2d52638d09b5d94494bd84a54ce7b537ef02ec033fb93","access_level":"public","create_time":"$D2021-01-25T19:14:58.633Z","update_time":"$D2021-03-19T14:43:04.888Z","view_time":null,"first_public_time":"$D2021-02-10T21:53:10.239Z","has_unpublished_edits":null,"fork":true,"stars":0,"starred":false,"owner":{"type":"team","id":"60a9a8012f5d802f","login":"jussi","name":"Justus 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The Jobs Calculator

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5355,"value":"subTitle = html`

A tool to estimate job creation from an economic recovery package

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4405,"value":"introText = html`Over 15 million people remain unemployed or underemployed amid the COVID-19 economic crisis. Economists, movement organizations, the Biden administration, and Congress are all calling for a bold economic recovery package to put millions of people back to work building a more equitable clean energy economy.

\n\nHow many jobs would an economic recovery package create? That depends on the size of the investments in each economic sector. This calculator is a tool to help you generate estimates of job creation by entering investment amounts for each sector.

\n\nInstructions: Type dollar amounts into the table below to see how many jobs that investment would yield. To make your own customized calculation table, use the Disaggregated Sectors tool below.
`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3932,"value":"viewof table_agg = createDynamicTableWithSep(dataAgg, columnsAgg, css_instructions_table) //createDynamicTable(data_agg, columns_agg, css_instructions_table)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6017,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2388,"value":"viewof scale_jobs_agg = html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5150,"value":"viewof manuRadioButtonsAgg = createSectorRadioButton()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5307,"value":"chartAggChoice = selectSubCategoryBarChartAgg(manuRadioButtonsAgg[0])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5344,"value":"noteOfCaution = html`
This graph assumes that the distribution of investments within each sector matches the distribution specified in the report How to Build Back Better: A 10-Year Plan for Economic Renewal and in this report from the Political Economy Research Institute. To customize the distribution of investments within each sector, use the Disaggregated Sectors tool below.\n

Disaggregated Sectors

\n
Scroll through the menu and pick sectors of interest to create a calculation table. Then type in dollar amounts for each of them to see how many jobs that investment would yield.

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3604,"value":"viewof checkbox_menu = checkbox_menu_scroll(sector_dict)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4176,"value":"sep3 = html`

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4521,"value":"viewof table_disagg = createDynamicTableWithSep(\n dataDisagg,\n columnsDisagg,\n css_instructions_table\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2916,"value":"html`

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3147,"value":"viewof scale_jobs_disagg = html`\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5544,"value":"viewof manuRadioButtonsDisagg = createSectorRadioButton()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3813,"value":"chartDisagg = selectSubCategoryBarChartDisagg(manuRadioButtonsDisagg[0])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2908,"value":"md`## Dictionaries and Variables`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4496,"value":"md`#### Dynamically Changed`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4910,"value":"investmentDisagg = table_disagg['Annual budget in billions of US$'].slice(0, table_disagg['Annual budget in billions of US$'].length-1)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4636,"value":"investmentAgg = table_agg['Annual budget in billions of US$'].slice(0, table_agg['Annual budget in billions of US$'].length-1)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4025,"value":"dataSelected = selectDataThroughCheckbox(dataDisagg, checkbox_menu)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5555,"value":"dataSelectedManu = selectDataThroughCheckbox(dataDisaggManu, checkbox_menu)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5505,"value":"function selectDataThroughCheckbox(data, checkboxList) {\n let dataSelected = [];\n for (let i=0; i\n @media (min-width:750px) {\n #hc_container {\n width:100%;\n overflow: hidden;\n }}\n\n${chart}`;\n\n return chartDisagg;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4497,"value":"md`#### Fixed`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4513,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5802,"value":"columnsAgg = [\n {name:\"Sectors\", cellType:\"fix\", data:retrieveDataFromDf(dataAgg, dataAgg.length + 1, \"macro_category\", \"Total\"), total:false, className:\"text\"}, \n {name:\"Annual budget in billions of US$\", cellType:\"input\", data : addMutableColumnDataWithVaryingValues([186.6, 84.5, 358.8, 324.3]), total:true, rounding:\"toFixed(3)\", className:\"number\"},\n {name:\"Number of jobs created annually\", cellType:\"result\", \n data: addMutableColumnData(dataAgg, dataAgg.length + 1, ``, ``), \n operation:{variables: {array1:{columnTitle:\"Annual budget in billions of US$\", sourceType:\"input\"}, array2:{columnTitle:\"Total Jobs per million\", sourceType:\"original\"}},operator:\"*\", factor:1000}, \n total:true, rounding: \"round\", className:\"number\"},\n {name:\"Total Jobs per million\", cellType:\"none\", data:retrieveDataFromDf(dataAgg, dataAgg.length + 1, \"Total Jobs per million\", \"\"), total:false, className:\"number\"}\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2403,"value":"jobs_agg_chart_dict = ({scale:scale_jobs_agg})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3154,"value":"jobs_disagg_chart_dict = ({scale:scale_jobs_disagg})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2533,"value":"sector_dict = {\n let sector_dict = {};\n for (let i=0; i< macro_categories.length; i++){\n let sector_list = [];\n for (let j=0; j< dataDisagg.length; j++){\n if (dataDisagg[j].macro_category === macro_categories[i]){\n sector_list.push(dataDisagg[j].Sectors)\n }\n }\n sector_dict[macro_categories[i]] = sector_list;\n}\n return sector_dict\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2381,"value":"sectors = dataDisagg.map((item) => {return item.Sectors})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4148,"value":"macro_categories = dataAgg.map((item)=>{return item.macro_category})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3902,"value":"md`## Functions`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3907,"value":"md`#### Primary`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3910,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5782,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3252,"value":"$38","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1441,"value":"function jobs_bar_chart(dictionary) {\nconst container_chart = html`\n\n

\n\n`;\n hc.chart(container_chart, {\n credits: {\n enabled: false\n },\n chart: {\n type: 'column',\n zoomType: 'xy',\n style: {\n fontFamily: 'inherit',\n width:'100%'\n }\n },\n title:{\n text:\"Jobs Created in Aggregated Sectors\"\n },\n xAxis: {\n categories: columnsAgg[0].data.slice(0, columnsAgg[0].data.length-1)\n },\n yAxis: {\n title: {\n text:\"Jobs Created\"\n },\n type:dictionary['scale']\n },\n series: [\n {\n name: 'Aggregated Sectors',\n data: table_agg['Number of jobs created annually'].slice(0, table_agg['Number of jobs created annually'].length -1)\n }\n ]\n });\n \n return container_chart\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4689,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5245,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3038,"value":"function jobs_bar_chart_disagg(dictionary) {\nconst container_chart = html`\n

Test

\n`;\n hc.chart(container_chart, {\n credits: {\n enabled: false\n },\n chart: {\n type: 'column',\n zoomType: 'xy',\n style: {\n fontFamily: 'inherit',\n width:'100%'\n }\n },\n title:{\n text:\"Jobs Created in Disaggregated Sectors\"\n },\n xAxis: {\n categories: columnsDisagg[0].data.slice(0, columnsDisagg[0].data.length-1)\n },\n yAxis: {\n title: {\n text:\"Jobs Created\"\n },\n type:dictionary['scale']\n },\n series: [\n {\n name: 'Disaggregated Sectors',\n data: table_disagg['Number of jobs created annually'].slice(0, table_disagg['Number of jobs created annually'].length -1)\n }\n ]\n });\n \n return container_chart\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4920,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5503,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3918,"value":"md`#### Secondary`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5667,"value":"function addCommas(nStr) {\n nStr += '';\n let x = nStr.split('.');\n let x1 = x[0];\n let x2 = x.length > 1 ? '.' + x[1] : '';\n let rgx = /(\\d+)(\\d{3})/;\n while (rgx.test(x1)) {\n x1 = x1.replace(rgx, '$1' + ',' + '$2');\n }\n return x1 + x2;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4825,"value":"function getJobsDetailed(investment, data, column, scaleFactor) {\nlet results = []\nlet factors = interArrayOperation(investment, data.map((item) => {return Number(item[column])}), \"*\")\nfor (let i=0; i`;}\n );\n arrayData.push(``);\n return arrayData\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3939,"value":"addMutableColumnData = function(df, numRows, cellContent, additionalCellContent){\n if (df.length === numRows) {\n return Array.apply(null, Array(df.length)).map(function(){return cellContent}); \n } else if (df.length + 1 === numRows) {\n let dataArray = Array.apply(null, Array(df.length)).map(function(){return cellContent});\n dataArray.push(additionalCellContent);\n return dataArray\n } else {\n return undefined\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3944,"value":"retrieveDataFromDf = function(df, numRows, column, additionalCellContent){\n if (df.length === numRows) {\n return df.map((item)=>{return item[column];});\n } else if (df.length + 1 === numRows) {\n let dataArray = df.map((item)=>{return item[column];});\n dataArray.push(additionalCellContent);\n return dataArray\n } else {\n return undefined\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2514,"value":"function onlyUnique(value, index, self) {\n return self.indexOf(value) === index;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5521,"value":"function createSectorRadioButton() {\n let form = html`\n`;\n \n form.oninput = () => {\n let outputElements = []; \n \n let inputElements = form.getElementsByTagName('input');\n for (let i=0; i\n @media (min-width:750px) {\n #hc_container {\n width:100%;\n overflow: hidden;\n }}\n\n${chart}`;\n\n return chartAgg;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5246,"value":"dataAggManu.map(item => {return item.macro_category;})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5237,"value":"dataAggManu = d3.tsvParse(`sub_category\tmacro_category\tAnnual Budget\tDirect Jobs\tIndirect Jobs\tInduced Jobs\tTotal Jobs\tTotal Jobs per million\tDirect Jobs per million\tIndirect Jobs per million\tInduced Jobs per million\nManufacturing Sector\tAgriculture and land restoration programs\t186600.0\t32550.0\t79320.0\t38680.0\t150550.0\t0.8068060021436227\t0.17443729903536978\t0.42508038585209\t0.20728831725616292\nManufacturing Sector\tCare economy, public health, and postal service\t84500.0\t1000.0\t25400.0\t25350.0\t51750.0\t0.6124260355029586\t0.011834319526627219\t0.3005917159763314\t0.3\nManufacturing Sector\tClean renewable energy and energy efficiency programs\t358800.0\t540250.0\t283210.0\t71760.0\t895220.0\t2.4950390189520624\t1.5057134894091415\t0.7893255295429209\t0.2\nManufacturing Sector\tInfrastructure programs\t324300.0\t203080.0\t199770.0\t70770.0\t473620.0\t1.4604378661732964\t0.6262102991057663\t0.6160037002775208\t0.21822386679000924`)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5498,"value":"$40","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1403,"value":"md`## Imports`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1239,"value":"import {log} from '@sorig/console-log-without-leaving-your-notebook'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":526,"value":"d3 = require('d3-dsv')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1427,"value":"hc = require('highcharts')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3164,"value":"import {c3} from \"@mbostock/c3\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2566,"value":"import {checkbox} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4096,"value":"md`## CSS`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3883,"value":"css_instructions_table = `table {\n table-layout:fixed;\n font-family: inherit;\n font-size: inherit;\n margin-left: auto;\n margin-right: auto;\n}\n\n.tableContainer{\nwidth: 1000px;\ntext-align: center;\n}\n\n.number {\nwidth: 25%;\n}\n\n.text {\n width: 50%;\n}\n\ntd {\n padding:0 15px;\n\n}\n\nth {\n padding:0 15px;\n}\n\ninput {\n border: none;\n font-size: inherit;\n font-family: inherit;\n}\n\n/* Chrome, Safari, Edge, Opera */\ninput::-webkit-outer-spin-button,\ninput::-webkit-inner-spin-button {\n -webkit-appearance: none;\n margin: 0;\n}\n\n/* Firefox */\ninput[type=number] {\n -moz-appearance: textfield;\n}\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5625,"value":"contactInfo = html`

\nDesign by: Justus Schollmeyer

\nFor inquiries regarding this calculator, including how to embed it into your own website, please contact justusschollmeyer[at]gmail.com.\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W41","stdlib":"1","titling":"auto"}} 33:"$32:body"