3d:null 3e:["$","title",null,{"children":"Correlation Between Covid-19 and 2020 Elections | sabaina-haroon | Observable"}] 44:T720,{ const rows = covid_19_Data; const unpack = (rows, key) => rows.map(function(row) { return row[key]; }) const z_value = unpack(rows, 'cases'); const location = unpack(rows, 'state').map(state=>state_abbr[state]); if (MailBallots == "Vote Ballots requested by mail") { const rows = RequestedBallots; var data = [{ type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows, 'State').map(state=>state_abbr[state]), z: unpack(rows, 'Requested'), text: unpack(rows, 'state'), autocolorscale: true }]; var layout = { title: 'Total Requested Ballots by Mail per state', geo:{ scope: 'usa' } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } else if (MailBallots == "Vote Ballots returned by mail") { const rows = ReturnedBallots; var data = [{ type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows, 'State').map(state=>state_abbr[state]), z: unpack(rows, 'Returned'), text: unpack(rows, 'state'), autocolorscale: true }]; var layout = { title: 'Total Returned Ballots by Mail per state', geo:{ scope: 'usa' } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } var data = [{ type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows, 'state').map(state=>state_abbr[state]), z: z_value, text: unpack(rows, 'state'), autocolorscale: true }]; var layout = { title: 'Live US Covid-19 Cases by state', geo:{ scope: 'usa' } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv }45:T61b,{ const rows_Returned = ReturnedBallots; const rows_covid = covid_19_Data; function unpack(rows, key) { return rows.map(function(row) { return row[key]; }); }; const z_value = unpack(rows_covid, 'cases'); var stateName = unpack(rows_Returned, 'State'), stateDeaths = unpack(rows_Returned, 'Returned'), color = [,"rgb(255,65,54)","rgb(133,20,75)","rgb(255,133,27)","lightgrey"], stateSize = [], hoverText = [], scale = 100000; for ( var i = 0 ; i < stateDeaths.length; i++) { var currentSize = stateDeaths[i] / scale; var currentText = stateName[i] + " Returned: " + stateDeaths[i]; stateSize.push(currentSize); hoverText.push(currentText); } var data = [{ type: 'scattergeo', locationmode: 'USA-states', lat: state_lat, lon: state_long, hoverinfo: 'text', text: hoverText, marker: { size: stateSize, line: { color: 'black', width: 2 }, } }, { type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows_covid, 'state').map(state=>state_abbr[state]), z: z_value, text: unpack(rows_covid, 'state'), autocolorscale: true }]; var layout = { title: 'Returned Ballots vs Covid Cases per state', showlegend: false, geo: { scope: 'usa', projection: { type: 'albers usa' }, }, height: 500, width: 900, }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv }46:T4b1,{ let trace0 = { mode: 'markers', x: returned, y: covid_casesForReturnedVotes, //line: {shape: 'spline'}, text: unpack(ReturnedBallots, 'State'), marker: {size:8}, type: 'scatter', name: "correlation data" }; //let trace1 = { // mode: 'line', // x: fetchCloseValue(dataNIKE), // y: pred_y, // type: 'scatter', // name: "regression fit" //}; let data0 = [trace0]; let layout0 = { //title: "Correlation. R :" + round(correlation, 3) + ", Coeff of Determination: " + //round(coeff_sqbycovariance, 3) + " vs Rsq: " + round(coeff_sqbyregressionLine, 3) + "
Regression //Coefficients: Slope: " + round(b, 3) + " , Intercept: " + round(a, 3), xaxis: { title: "By state count of Mail Ballot papers returned"//, //tickvals: returned, //ticktext: unpack(ReturnedBallots, 'State') }, yaxis: { title: "Covid cases in those states" }, width: 1000, hovermode: 'closest' }; const config = { staticPlot: true, responsive: true, displayModeBar: false }; const div = DOM.element('div'); Plotly.newPlot(div, data0, layout0, { showLink: false }); return div; }47:T4b5,{ let trace0 = { mode: 'markers', x: requested, y: covid_casesForRequestedVotes, //line: {shape: 'spline'}, text: unpack(RequestedBallots, 'State'), marker: {size:8}, type: 'scatter', name: "correlation data" }; //let trace1 = { // mode: 'line', // x: fetchCloseValue(dataNIKE), // y: pred_y, // type: 'scatter', // name: "regression fit" //}; let data0 = [trace0]; let layout0 = { //title: "Correlation. R :" + round(correlation, 3) + ", Coeff of Determination: " + //round(coeff_sqbycovariance, 3) + " vs Rsq: " + round(coeff_sqbyregressionLine, 3) + "
Regression //Coefficients: Slope: " + round(b, 3) + " , Intercept: " + round(a, 3), xaxis: { title: "By state count of Mail Ballot papers Requested"//, //tickvals: returned, //ticktext: unpack(ReturnedBallots, 'State') }, yaxis: { title: "Covid cases in those states" }, width: 1000, hovermode: 'closest' }; const config = { staticPlot: true, responsive: true, displayModeBar: false }; const div = DOM.element('div'); Plotly.newPlot(div, data0, layout0, { showLink: false }); return div; }48:T52c,{ let trace0 = { mode: 'markers', x: req_ret_diff, //y: covid_casesForRequestedVotes, y: covid_cases_rate_per_100k, //line: {shape: 'spline'}, text: unpack(RequestedBallots, 'State'), marker: {size:8}, type: 'scatter', name: "correlation data" }; //let trace1 = { // mode: 'line', // x: fetchCloseValue(dataNIKE), // y: pred_y, // type: 'scatter', // name: "regression fit" //}; let data0 = [trace0]; let layout0 = { //title: "Correlation. R :" + round(correlation, 3) + ", Coeff of Determination: " + //round(coeff_sqbycovariance, 3) + " vs Rsq: " + round(coeff_sqbyregressionLine, 3) + "
Regression //Coefficients: Slope: " + round(b, 3) + " , Intercept: " + round(a, 3), xaxis: { title: "By state Mail Ballot papers Rate of Return"//, //tickvals: returned, //ticktext: unpack(ReturnedBallots, 'State') }, yaxis: { title: "Covid cases per 100k" }, title: "Correlation between 'Covid-19 Rates' vs 'Mail ballot Return Rates' per state", width: 1000, hovermode: 'closest' }; const config = { staticPlot: true, responsive: true, displayModeBar: false }; const div = DOM.element('div'); Plotly.newPlot(div, data0, layout0, { showLink: false }); return div; }49:T54c,{ if (soretedChoice == "Sorted by Returned Ballots") { const trace1 = { x: returned, y: unpack(ReturnedBallots, 'State'), name: 'Returned Ballots', type: 'bar', orientation: 'h', transforms: [{ type: 'sort', target: 'x', order: 'ascending' }] }; const trace2 = { x: covid_casesForReturnedVotes, y: unpack(ReturnedBallots, 'State'), name: 'Covid Case by state', type: 'bar', orientation: 'h' }; const data = [trace1, trace2]; const layout = {barmode: 'group', height: 1200, title: "Covid Cases vs Votes Returned Bas Graph"}; const div = DOM.element('div'); Plotly.newPlot(div, data, layout); return div; } if (soretedChoice == "Sorted by Covid Cases") { const trace2 = { x: returned, y: unpack(ReturnedBallots, 'State'), name: 'Returned Ballots', type: 'bar', orientation: 'h' }; const trace1 = { x: covid_casesForReturnedVotes, y: unpack(ReturnedBallots, 'State'), name: 'Covid Case by state', type: 'bar', orientation: 'h', transforms: [{ type: 'sort', target: 'x', order: 'ascending' }] }; const data = [trace1, trace2]; const layout = {barmode: 'group', height: 1200, title: "Covid Cases vs Votes Returned Bas Graph"}; const div = DOM.element('div'); Plotly.newPlot(div, data, layout); return div; } }4a:T4c8,{ const rows = covid_19_Data; const unpack = (rows, key) => rows.map(function(row) { return row[key]; }) const z_value = unpack(rows, 'cases'); const location = unpack(rows, 'state').map(state=>state_abbr[state]); if (TurnOut == "Voters Turn out per state") { const rows = TurnoutRate; var data = [{ type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows, 'State').map(state=>state_abbr[state]), z: unpack(rows, 'Turnout Rate'), text: unpack(rows, 'State'), autocolorscale: true }]; var layout = { title: 'Total Voters Turnout rate per state', geo:{ scope: 'usa' } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } var data = [{ type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows, 'state').map(state=>state_abbr[state]), z: z_value, text: unpack(rows, 'state'), autocolorscale: true }]; var layout = { title: 'Live US Covid-19 Cases by state', geo:{ scope: 'usa' } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv }4b:T62f,{ const rows_Returned = TurnoutRate; const rows_covid = Case_rate_per_100k; function unpack(rows, key) { return rows.map(function(row) { return row[key]; }); }; const z_value = unpack(rows_covid, 'Case Rate per 100,000'); var stateName = unpack(rows_Returned, 'State'), stateDeaths = unpack(rows_Returned, 'Turnout Rate'), color = [,"rgb(255,65,54)","rgb(133,20,75)","rgb(255,133,27)","lightgrey"], stateSize = [], hoverText = [], scale = 0.025; for ( var i = 0 ; i < stateDeaths.length; i++) { var currentSize = stateDeaths[i] / scale; var currentText = stateName[i] + " Turnout Rate: " + stateDeaths[i]; stateSize.push(currentSize); hoverText.push(currentText); } var data = [{ type: 'scattergeo', locationmode: 'USA-states', lat: state_lat, lon: state_long, hoverinfo: 'text', text: hoverText, marker: { size: stateSize, line: { color: 'black', width: 2 }, } }, { type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows_covid, 'State/Territory').map(state=>state_abbr[state]), z: z_value, text: unpack(rows_covid, 'state'), autocolorscale: true }]; var layout = { title: 'TurnOut Rate vs Covid Cases', showlegend: false, geo: { scope: 'usa', projection: { type: 'albers usa' }, }, height: 500, width: 900, }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv }4c:T50a,{ let trace0 = { mode: 'markers', x: unpack(TurnoutRate, 'Turnout Rate'), //y: covid_casesForRequestedVotes, y: rate_covid_turnout, //line: {shape: 'spline'}, text: unpack(TurnoutRate, 'State'), marker: {size:8}, type: 'scatter', name: "correlation data" }; //let trace1 = { // mode: 'line', // x: fetchCloseValue(dataNIKE), // y: pred_y, // type: 'scatter', // name: "regression fit" //}; let data0 = [trace0]; let layout0 = { //title: "Correlation. R :" + round(correlation, 3) + ", Coeff of Determination: " + //round(coeff_sqbycovariance, 3) + " vs Rsq: " + round(coeff_sqbyregressionLine, 3) + "
Regression //Coefficients: Slope: " + round(b, 3) + " , Intercept: " + round(a, 3), xaxis: { title: "Turn out rate"//, //tickvals: returned, //ticktext: unpack(ReturnedBallots, 'State') }, yaxis: { title: "Covid cases rate" }, title: "Correlation between 'Covid-19 Rates' vs 'Voter Turn out by state", width: 1000, hovermode: 'closest' }; const config = { staticPlot: true, responsive: true, displayModeBar: false }; const div = DOM.element('div'); Plotly.newPlot(div, data0, layout0, { showLink: false }); return div; }4d:Tbf7,{ function unpack(rows, key) { return rows.map(function(row) { return row[key]; }); }; if (TotalEarlyVoteRadio == "Total Early Votes") { const rows = TotalEarlyVote; var data = [{ type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows, 'State').map(state=>state_abbr[state]), z: unpack(rows, 'Total Early Votes'), text: unpack(rows, 'State'), autocolorscale: true }]; var layout = { title: 'Total Early Votes by State', geo:{ scope: 'usa' } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } else if (TotalEarlyVoteRadio == "Covid Cases by state during Election") { const rows = covid_19_Data; var data = [{ type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows, 'state').map(state=>state_abbr[state]), z: unpack(rows, 'cases'), text: unpack(rows, 'state'), autocolorscale: true }]; var layout = { title: 'Covid Cases by state', geo:{ scope: 'usa' } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } else if (TotalEarlyVoteRadio == "Side by Side") { const rows_totalEarlyVotes = TotalEarlyVote; const rows_covid = covid_19_Data; function unpack(rows, key) { return rows.map(function(row) { return row[key]; }); }; const z_value = unpack(rows_covid, 'cases'); var stateName = unpack(rows_totalEarlyVotes, 'State'), stateDeaths = unpack(rows_totalEarlyVotes, 'Total Early Votes'), color = [,"rgb(255,65,54)","rgb(133,20,75)","rgb(255,133,27)","lightgrey"], stateSize = [], hoverText = [], scale = 100000; for ( var i = 0 ; i < stateDeaths.length; i++) { var currentSize = stateDeaths[i] / scale; var currentText = stateName[i] + " Early Votes: " + stateDeaths[i]; stateSize.push(currentSize); hoverText.push(currentText); } var data = [{ type: 'scattergeo', locationmode: 'USA-states', locations: unpack(rows_totalEarlyVotes, 'State').map(state=>state_abbr[state]), hoverinfo: 'text', text: hoverText, marker: { size: stateSize, line: { color: 'black', width: 2 }, } }, { type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows_covid, 'state').map(state=>state_abbr[state]), z: z_value, text: unpack(rows_covid, 'state'), autocolorscale: true }]; var layout = { title: 'Total Early Vote Counts vs Covid Cases by state', showlegend: false, geo: { scope: 'usa', projection: { type: 'albers usa' }, }, height: 500, width: 900, }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } };4e:Tee7,{ function unpack(rows, key) { return rows.map(function(row) { return row[key]; }); }; if (Comparisonwith2016 == "Early Votes 2020") { const rows = TotalEarlyVotebyWashingtonPost; var data = [{ type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows, 'State').map(state=>state_abbr[state]), z: unpack(rows, '2020 early votes'), text: unpack(rows, 'State'), autocolorscale: true }]; var layout = { title: 'Total Early Votes by State', geo:{ scope: 'usa' } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } else if (Comparisonwith2016 == "Total Votes 2016") { const rows = TotalEarlyVotebyWashingtonPost; var data = [{ type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows, 'State').map(state=>state_abbr[state]), z: unpack(rows, '2016 total votes'), text: unpack(rows, 'State'), autocolorscale: true }]; var layout = { title: 'Total Votes 2016', geo:{ scope: 'usa' } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } else if (Comparisonwith2016 == "Percent of 2020 votes from 2016") { const rows = TotalEarlyVotebyWashingtonPost; var data = [{ type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows, 'State').map(state=>state_abbr[state]), z: unpack(rows, 'Total Vote Percent with 2016'), text: unpack(rows, 'State'), autocolorscale: true }]; var layout = { title: 'Covid Cases by state', geo:{ scope: 'usa' } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } else if (Comparisonwith2016 == "Covid Cases vs Percent as area of bubbles") { const rows_totalEarlyVotes = TotalEarlyVotebyWashingtonPost; const rows_covid = Case_rate_per_100k; function unpack(rows, key) { return rows.map(function(row) { return row[key]; }); }; const z_value = unpack(rows_totalEarlyVotes, 'Total Vote Percent with 2016'); var stateName = unpack(rows_covid, 'State/Territory'), stateDeaths = unpack(rows_covid, 'Case Rate per 100,000'), color = [,"rgb(255,65,54)","rgb(133,20,75)","rgb(255,133,27)","lightgrey"], stateSize = [], hoverText = [], scale = 100; for ( var i = 0 ; i < stateDeaths.length; i++) { var currentSize = stateDeaths[i] / scale; var currentText = stateName[i] + " Case Rate per 100,000: " + stateDeaths[i]; stateSize.push(currentSize); hoverText.push(currentText); } var data = [{ type: 'scattergeo', locationmode: 'USA-states', locations: unpack(rows_covid, 'State/Territory').map(state=>state_abbr[state]), hoverinfo: 'text', text: hoverText, marker: { size: stateSize, line: { color: 'black', width: 2 }, } }, { type: 'choropleth', locationmode: 'USA-states', locations: unpack(rows_totalEarlyVotes, 'State').map(state=>state_abbr[state]), z: z_value, text: unpack(rows_totalEarlyVotes, 'State'), autocolorscale: true }]; var layout = { title: 'Percent of early votes by 2016 vs Covid Cases by state per 100,000', showlegend: false, geo: { scope: 'usa', projection: { type: 'albers usa' }, }, height: 500, width: 900, }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } };4f:Tcb3,{ const unpack = (rows, key) => rows.map(function(row) { return row[key]; }) if (countyRadio == "Total Early Votes Florida") { const rows = earlyVotesFlorida; var data = [{ type: 'choropleth', locations: unpack(rows, 'State'), z: unpack(rows,'Total Early Votes'), featureidkey:"properties.name", geojson: floridaCounties, autocolorscale: true }]; var layout = { "width": 900, "height": 600, title: '2020 Total Early Votes in Florida', geo:{ scope: 'usa', center : { lon:-81.3792, lat:28.5383 }, lataxis: { range: [ 25, 30.4] }, lonaxis:{ range: [-87.2, -80.04] } } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } else if (countyRadio == "Covid Cases Florida") { const rows = earlyVotesFlorida; var data = [{ type: 'choropleth', locations: unpack(rows, 'State'), z: unpack(rows,'Cases per 100000'), featureidkey:"properties.name", geojson: floridaCounties, autocolorscale: true }]; var layout = { "width": 900, "height": 600, title: 'Covid Cases per 100,000', geo:{ scope: 'usa', center : { lon:-81.3792, lat:28.5383 }, lataxis: { range: [ 25, 30.4] }, lonaxis:{ range: [-87.2, -80.04] } } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } else if (countyRadio == "Side by Side") { const rows = earlyVotesFlorida; var stateName = unpack(rows, 'State'), stateDeaths = unpack(rows, 'Cases per 100000'), color = [,"rgb(255,65,54)","rgb(133,20,75)","rgb(255,133,27)","lightgrey"], stateSize = [], hoverText = [], scale = 500; for ( var i = 0 ; i < stateDeaths.length; i++) { var currentSize = stateDeaths[i] / scale; var currentText = stateName[i] + " Cases/100,000: " + stateDeaths[i]; stateSize.push(currentSize); hoverText.push(currentText); } var data = [{ type: 'choropleth', locations: unpack(rows, 'State'), z: unpack(rows,'turnout'), featureidkey:"properties.name", geojson: floridaCounties, autocolorscale: true }, { type: 'scattergeo', locations: unpack(rows, 'State'), hoverinfo: 'text', text: hoverText, marker: { size: stateSize, line: { color: 'black', width: 2 }, }, featureidkey:"properties.name", geojson: floridaCounties, autocolorscale: true } ]; var layout = { "width": 900, "height": 600, title: '2020 Covid Cases Florida per 100,000k vs Voters Turn out by Counties', geo:{ scope: 'usa', center : { lon:-81.3792, lat:28.5383 }, lataxis: { range: [ 25, 30.4] }, lonaxis:{ range: [-87.2, -80.04] } } }; const myDiv = DOM.element("div") Plotly.newPlot(myDiv, data, layout, {showLink: false}); return myDiv } }50:T41a,md`# Conclusion The goal of the project is to analyze the effect of COVID-19 cases on US presidential elections 2020. First we collected the data for election 2020 and COVID-19 cases. Once the data was collected, we showed different graphs for vote ballots requested by mail per state, vote ballots returned by mail per state and covid cases by state. We observed that the states with most COVID-19 cases has most vote ballots returned. Next, we quantified the correlation between voter turnout per state and COVID-19 cases and we observed the same trend as the first analysis. Next, we compared the number of early votes 2020 and the total turnout in 2016 elections and observed that the U.S. hit 73% of 2016 voting before Election Day 2020. Next, we show that covid geared about two-third of total voters to vote through Mail-In Ballots. Finally, we show in detail the early vote count per county for the state of florida. Overall, we observed the way COVID-19 affected 2020 Presidential Election shows some correlation between the two quanities. `51:T75e,state_abbr = ({ 'Alabama' : 'AL' , 'Alaska' : 'AK' , 'America Samoa' : 'AS' , 'Arizona' : 'AZ' , 'Arkansas' : 'AR' , 'California' : 'CA' , 'Colorado' : 'CO' , 'Connecticut' : 'CT' , 'Delaware' : 'DE' , 'District of Columbia': 'DC' , 'Micronesia' : 'FM' , 'Florida' : 'FL' , 'Georgia' : 'GA' , 'Guam' : 'GU' , 'Hawaii' : 'HI' , 'Idaho' : 'ID' , 'Illinois' : 'IL' , 'Indiana' : 'IN' , 'Iowa' : 'IA' , 'Kansas' : 'KS' , 'Kentucky' : 'KY' , 'Louisiana' : 'LA' , 'Maine' : 'ME' , 'Marshall Islands' : 'MH' , 'Maryland' : 'MD' , 'Massachusetts' : 'MA' , 'Michigan' : 'MI' , 'Minnesota' : 'MN' , 'Mississippi' : 'MS' , 'Missouri' : 'MO' , 'Montana' : 'MT' , 'Nebraska' : 'NE' , 'Nevada' : 'NV' , 'New Hampshire' : 'NH' , 'New Jersey' : 'NJ' , 'New Mexico' : 'NM' , 'New York' : 'NY' , 'North Carolina' : 'NC' , 'North Dakota' : 'ND' , 'Ohio' : 'OH' , 'Oklahoma' : 'OK' , 'Oregon' : 'OR' , 'Palau' : 'PW' , 'Pennsylvania' : 'PA' , 'Puerto Rico' : 'PR' , 'Rhode Island' : 'RI' , 'South Carolina' : 'SC' , 'South Dakota' : 'SD' , 'Tennessee' : 'TN' , 'Texas' : 'TX' , 'Utah' : 'UT' , 'Vermont' : 'VT' , 'Virgin Islands' : 'VI' , 'Virginia' : 'VA' , 'Washington' : 'WA' , 'West Virginia' : 'WV' , 'Wisconsin' : 'WI' , 'Wyoming' : 'WY' })52:T11f2,stateToLatLong = [ { "state":"Alaska", "latitude":61.3850, "longitude":-152.2683 }, { "state":"Alabama", "latitude":32.7990, "longitude":-86.8073 }, { "state":"Arkansas", "latitude":34.9513, "longitude":-92.3809 }, { "state":"Arizona", "latitude":33.7712, "longitude":-111.3877 }, { "state":"California", "latitude":36.1700, "longitude":-119.7462 }, { "state":"Colorado", "latitude":39.0646, "longitude":-105.3272 }, { "state":"Connecticut", "latitude":41.5834, "longitude":-72.7622 }, { "state":"Delaware", "latitude":39.3498, "longitude":-75.5148 }, { "state":"Florida", "latitude":27.8333, "longitude":-81.7170 }, { "state":"Georgia", "latitude":32.9866, "longitude":-83.6487 }, { "state":"Hawaii", "latitude":21.1098, "longitude":-157.5311 }, { "state":"Iowa", "latitude":42.0046, "longitude":-93.2140 }, { "state":"Idaho", "latitude":44.2394, "longitude":-114.5103 }, { "state":"Illinois", "latitude":40.3363, "longitude":-89.0022 }, { "state":"Indiana", "latitude":39.8647, "longitude":-86.2604 }, { "state":"Kansas", "latitude":38.5111, "longitude":-96.8005 }, { "state":"Kentucky", "latitude":37.6690, "longitude":-84.6514 }, { "state":"Louisiana", "latitude":31.1801, "longitude":-91.8749 }, { "state":"Massachusetts", "latitude":42.2373, "longitude":-71.5314 }, { "state":"Maryland", "latitude":39.0724, "longitude":-76.7902 }, { "state":"Maine", "latitude":44.6074, "longitude":-69.3977 }, { "state":"Michigan", "latitude":43.3504, "longitude":-84.5603 }, { "state":"Minnesota", "latitude":45.7326, "longitude":-93.9196 }, { "state":"Missouri", "latitude":38.4623, "longitude":-92.3020 }, { "state":"Mississippi", "latitude":32.7673, "longitude":-89.6812 }, { "state":"Montana", "latitude":46.9048, "longitude":-110.3261 }, { "state":"North Carolina", "latitude":35.6411, "longitude":-79.8431 }, { "state":"North Dakota", "latitude":47.5362, "longitude":-99.7930 }, { "state":"Nebraska", "latitude":41.1289, "longitude":-98.2883 }, { "state":"New Hampshire", "latitude":43.4108, "longitude":-71.5653 }, { "state":"New Jersey", "latitude":40.3140, "longitude":-74.5089 }, { "state":"New Mexico", "latitude":34.8375, "longitude":-106.2371 }, { "state":"Nevada", "latitude":38.4199, "longitude":-117.1219 }, { "state":"New York", "latitude":42.1497, "longitude":-74.9384 }, { "state":"Ohio", "latitude":40.3736, "longitude":-82.7755 }, { "state":"Oklahoma", "latitude":35.5376, "longitude":-96.9247 }, { "state":"Oregon", "latitude":44.5672, "longitude":-122.1269 }, { "state":"Pennsylvania", "latitude":40.5773, "longitude":-77.2640 }, { "state":"Rhode Island", "latitude":41.6772, 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42:{"id":"dd23cee55ce1b701","slug":null,"title":" Correlation Between Covid-19 and 2020 Elections","thumbnail":"8a37f5b6207b0188c92396d64effa8a8ad6a38ddf620d83087d9074dfb37e4c8","access_level":"unlisted","create_time":"$D2020-11-16T05:05:51.457Z","update_time":"$D2020-12-08T13:23:53.052Z","view_time":null,"first_public_time":null,"has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"bce8751b3f5a86b9","login":"sabaina-haroon","name":"","avatar_url":"https://avatars-next.observableusercontent.com/627a21c4fa5724fbbf7134f0b8ae5e8e1d81a819ddad2b99874c752879a2c48b","tier":"starter_2024","bio":""},"version":735,"publish_version":735,"role":null,"authored":false,"authors":[{"type":"individual","id":"c0c67d04079b1165","login":"sabaina-haroon","name":"","avatar_url":"https://avatars-next.observableusercontent.com/627a21c4fa5724fbbf7134f0b8ae5e8e1d81a819ddad2b99874c752879a2c48b","tier":null,"bio":""}],"members":[{"type":"individual","id":"c0c67d04079b1165","login":"sabaina-haroon","name":"","avatar_url":"https://avatars-next.observableusercontent.com/627a21c4fa5724fbbf7134f0b8ae5e8e1d81a819ddad2b99874c752879a2c48b","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"titling":"auto","title":" Correlation Between Covid-19 and 2020 Elections","cells":[{"id":0,"value":"md`# Correlation Between Covid-19 and 2020 Elections`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":669,"value":" md`\n### Motivation\n
\nIn October 2020, Stanford Institute for Economic Policy Research published a paper suggesting numbers of increase in Covid cases due to trump rallies using a statistical model:\n\n- 18 rallies\n- 30,000 coronavirus cases\n- 700 deaths\n- Timeline of rallies : June to September\n\nPaper can be read from here : https://siepr.stanford.edu/sites/default/files/publications/20-043.pdf `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":706,"value":"md ` There are different ways of vote casting every year, such as in person voting or by mail voting. By\nmail voting trends were important for elections of this year since most of the people are\nconcerned about COVID-19 and might have avoided going in gatherings to cast in person vote. The following three plots show vote ballots requested by mail per state, vote ballots returned by mail per state and covid cases by state. California has the most vote ballots requested by mail and vote ballots returned by mail whereas California, Texas and Florida lead in the number of COVID-19 cases.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":36,"value":"viewof MailBallots = radio({\n options: [\"Vote Ballots requested by mail\", \n \"Vote Ballots returned by mail\", \"Covid Cases by state during Election\"],\n value: \"Covid Cases by state during Election\",\n description: \"Side by side Comparison of Mail ballots requested returned and Covid trend in the states\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":34,"value":"$44","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":718,"value":"md ` The following chloropleth bubble graph shows returned ballots vs covid cases per state. It can be seen that states with higher number of cases have more vote ballots returned except for some outliers.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":361,"value":"$45","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":285,"value":"md ` Following two graphs are dominated by an outlier California. But it shows overall that states having more covid cases opted more for in home voting, except for Texas, where the trend is a bit different. It should also be noted but the return rate for Texas was 100% i.e. people voting from home were responsive with a greater rate.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":101,"value":"$46","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":161,"value":"$47","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":278,"value":"md ` Number related to Covid-19 cases and Mail ballots requested and returned by states might be biased towards their population. For instance we see california dominating in all the graphs above for requested votes, Covid-19 and returned, but it might be the case that their population is highest also. Below we are trying to see a trend that is independent of total population and shows covid per 100k people in each state. We do not have the same kind of data for Ballots, but for Ballots rate we have divided Returned ballots by each state to the total ballots requested in that state `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":256,"value":"$48","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":324,"value":"md ` Below graphs will provide detail preview of all the types of data and their independent bar graphs to let the viewer not get decieved by any of the data visualization illusion created above for them`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":303,"value":"viewof soretedChoice = radio({\n options: [\"Sorted by Returned Ballots\", \n \"Sorted by Covid Cases\"],\n value: \"Sorted by Returned Ballots\",\n description: \"Select different sorting trends and see the trend\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":174,"value":"$49","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":709,"value":"md ` Below two graph shows the percentage of ballots returned for each state and COVID-19 cases per state. Here, we can see that Texas show strong correlation between these two. However, for other states, weak correlation is observed.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":247,"value":"{var trace1 = {\n x: req_ret_diff,\n y: unpack(RequestedBallots, 'State'),\n name: 'Rate of Returned Ballots',\n type: 'bar',\n orientation: 'h',\n transforms: [{\n type: 'sort',\n target: 'x',\n order: 'ascending'\n }]\n};\n\nvar trace2 = {\n x: covid_cases_rate_per_100k,\n y: unpack(RequestedBallots, 'State'),\n name: 'Covid Cases Rate by state per 100k',\n type: 'bar',\n orientation: 'h'\n};\n\nvar data = [trace1];\n\nvar layout = {barmode: 'group',\n height: 1000, \n title: \"Return Rate per state\"};\nconst div = DOM.element('div');\nPlotly.newPlot(div, data, layout);\n return div;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":290,"value":"{var trace1 = {\n x: covid_casesForRequestedVotes,\n y: unpack(RequestedBallots, 'State'),\n name: 'Rate of Returned Ballots',\n type: 'bar',\n orientation: 'h',\n transforms: [{\n type: 'sort',\n target: 'x',\n order: 'ascending'\n }]\n};\n\nvar trace2 = {\n x: covid_cases_rate_per_100k,\n y: unpack(RequestedBallots, 'State'),\n name: 'Covid Cases Rate by state per 100k',\n type: 'bar',\n orientation: 'h'\n};\n\nvar data = [trace1];\n\nvar layout = {barmode: 'group',\n height: 1000,\n title: 'Covid Cases per state'};\nconst div = DOM.element('div');\nPlotly.newPlot(div, data, layout);\n return div;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":344,"value":"md ` So we can see from the below choropeth graphs that overall voter turn outs are higher for states low in Covid-19 virus count, except for some of the outliers.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":335,"value":"viewof TurnOut = radio({\n options: [\"Voters Turn out per state\", \n \"Covid Cases by state\"],\n value: \"Covid Cases by state\",\n description: \"Side by side Comparison of Voter Turn Out and Covid trend in the states\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":333,"value":"$4a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":720,"value":"md ` The following chloropleth bubble graph shows turn out rates vs covid cases per state. It can be seen that states with lower number of cases have more voter turnout. Number of cases per county also confirm this claim.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":388,"value":"$4b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":347,"value":"{var trace1 = {\n x: unpack(TurnoutRate, 'Turnout Rate'),\n y: unpack(TurnoutRate, 'State'),\n name: 'Rate of Voters Turnout',\n type: 'bar',\n orientation: 'h',\n transforms: [{\n type: 'sort',\n target: 'x',\n order: 'ascending'\n }]\n};\n\n\nvar data = [trace1];\n\nvar layout = {barmode: 'group',\n height: 1000,\n title: \"Rate of Voter's Turn Out\"};\nconst div = DOM.element('div');\nPlotly.newPlot(div, data, layout);\n return div;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":711,"value":"md ` The following graph attempts to show Correlation between Covid-19 Rates and Voter Turn out by state. It can be seen that there is not much correlation shown. Adjusting the axis scales might produce better results.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":355,"value":"$4c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":724,"value":"md ` In the following graph, we can see the number of total early votes and covid cases by state. Here also, we can obseerve that states with higher number of covid cases have more number of early votes. `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":413,"value":"viewof TotalEarlyVoteRadio = radio({\n options: [\"Total Early Votes\", \"Covid Cases by state during Election\", \"Side by Side\"],\n value: \"Total Early Votes\",\n description: \"Side by side Comparison of Total Early Votes and Covid trend in the states\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":417,"value":"$4d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":610,"value":"md`# The U.S. hit 73% of 2016 voting before Election Day\n source: Washington Post`\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":511,"value":"viewof Comparisonwith2016 = radio({\n options: [\"Early Votes 2020\", \"Total Votes 2016\", \"Percent of 2020 votes from 2016\",\n \"Covid Cases vs Percent as area of bubbles\"],\n value: \"Early Votes 2020\",\n description: \"Side by side Comparison of Early Votes in 2020 and Total Votes in 2016 \"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":516,"value":"$4e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":561,"value":"{\n\n const trace1 = {\n x: unpack(TotalEarlyVotebyWashingtonPost, '2016 total votes'),\n y: unpack(TotalEarlyVotebyWashingtonPost, 'State'),\n name: '2016 total votes',\n type: 'bar',\n orientation: 'h',\n width: 0.5,\n transforms: [{\n type: 'sort',\n target: 'x',\n order: 'ascending'\n }]\n};\n\nconst trace2 = {\n x: unpack(TotalEarlyVotebyWashingtonPost, '2020 early votes'),\n y: unpack(TotalEarlyVotebyWashingtonPost, 'State'),\n name: '2020 early votes',\n type: 'bar',\n orientation: 'h',\n marker: {\n opacity:0.6\n },\n transforms: [{\n type: 'sort',\n target: 'x',\n order: 'ascending'\n }]\n};\n\nconst data = [trace1, trace2];\n\nconst layout = {barmode: 'overlay',\n height: 1500,\n title: \"2020 EARLY Votes vs 2016 TOTAL votes\"};\nconst div = DOM.element('div');\nPlotly.newPlot(div, data, layout);\n return div;\n \n\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":604,"value":"md`# Covid geared about two-third of total voters to vote through Mail-In Ballots\n source: vox.com`\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":593,"value":"{var pieDiv = DOM.element(\"pie-chart\");\n\nvar traceA = {\n type: \"pie\",\n values: [35720830, 69936249],\n labels: ['In Person', 'Mail In']\n};\n\nvar data = [traceA];\n\nvar layout = {\n title: \"Percentage of In person and Mail in Ballots\"\n};\n\nPlotly.newPlot(pieDiv, data, layout);\n return pieDiv;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":630,"value":"md`# Stats for Florida\n source: US.Elections Project by University of Florida`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":727,"value":"md ` In this section, total number of early votes are shown per county of Florida. Miami and Briward county have the most number of early votes.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":490,"value":"viewof countyRadio = radio({\n options: [\"Total Early Votes Florida\", \"Covid Cases Florida\", \"Side by Side\"],\n value: \"Total Early Votes Florida\",\n description: \"Side by side Comparison of Total Early Votes and Covid trend Florida\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":464,"value":"$4f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":729,"value":"$50","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":482,"value":"earlyVotesFlorida = d3.csvParse(await FileAttachment(\"Total_early_votes_florida_@6.csv\").text(),d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":472,"value":"florida_countynames =[...floridaRedCounties.features.map(d=>d.properties.name), ...floridaBlueCounties.features.map(d=>d.properties.name)]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":467,"value":"floridaBlueCounties = d3.json('https://raw.githubusercontent.com/plotly/datasets/master/florida-blue-data.json',d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":469,"value":"floridaRedCounties = d3.json('https://raw.githubusercontent.com/plotly/datasets/master/florida-red-data.json',d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":466,"value":"floridaCounties = {\n return {\n type: \"FeatureCollection\",\n features: [...floridaRedCounties.features, ...floridaBlueCounties.features]\n }\n}\n ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":441,"value":"counties_geojson = ({\n type: \"FeatureCollection\",\n features: county.map(d=>({type: \"Feature\", id: d.county+\" \"+d.state_code, property: {county: d.county, state_code: d.state_code}, geometry: JSON.parse(d.json_object)}))\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":442,"value":"floida_red_data = florida_red_data_raw.features.map(d=>d.properties.name.substring(0, d.properties.name.indexOf(' County'))+\" FL\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":444,"value":"florida_red_data_raw = d3.json('https://raw.githubusercontent.com/plotly/datasets/master/florida-red-data.json',d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":446,"value":"floida_blue_data = florida_blue_data_raw.features.map(d=>d.properties.name.substring(0, d.properties.name.indexOf(' County'))+\" FL\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":450,"value":"county = d3.csvParse(await FileAttachment(\"us_county_geojson.csv\").text(),d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":448,"value":"florida_blue_data_raw = d3.json('https://raw.githubusercontent.com/plotly/datasets/master/florida-blue-data.json', d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":452,"value":"us_states = d3.json(\"https://raw.githubusercontent.com/python-visualization/folium/master/examples/data/us-states.json\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":181,"value":"rate_covid_turnout = {\n const sum_ = covid_casesForTurnoutStates.reduce((a, b) => a + b, 0)\n const cases_rate = []\n for( var i = 0; i < covid_casesForTurnoutStates.length; i++){\n cases_rate.push(covid_casesForTurnoutStates[i]/sum_)\n }\n return cases_rate\n \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":189,"value":"rate_returned = {\n const sum_ = returned.reduce((a, b) => a + b, 0)\n const return_rate = []\n for( var i = 0; i < returned.length; i++){\n return_rate.push(returned[i]/total)\n }\n return return_rate\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":196,"value":"total = returned.reduce((a, b) => a + b, 0) + covid_casesForReturnedVotes.reduce((a, b) => a + b, 0)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":142,"value":"unpack(ReturnedBallots, 'State')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":105,"value":"function getCases(rows, state, key){\n for( var i=0; i < rows.length; i++) {\n if (rows[i].state == state){\n return rows[i][key]\n }\n }\n};","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":221,"value":"function getVotes(rows, state, key){\n for( var i=0; i < rows.length; i++) {\n if (rows[i].State == state){\n return rows[i][key]\n }\n }\n};","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":205,"value":"req_ret_diff = {\n const cases = []\n for( var i = 0; i < RequestedBallots.length; i++){\n const ret = getVotes(ReturnedBallots, RequestedBallots[i].State, 'Returned');\n const req = RequestedBallots[i].Requested;\n cases.push(ret/req)\n }\n return cases\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":237,"value":"covid_cases_rate_per_100k = {\n const cases = []\n for( var i = 0; i < RequestedBallots.length; i++){\n cases.push(getCase_rate_per_100k(Case_rate_per_100k, RequestedBallots[i].State, 'Case Rate per 100,000'))\n }\n return cases\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":102,"value":"covid_casesForRequestedVotes = {\n const cases = []\n for( var i = 0; i < RequestedBallots.length; i++){\n cases.push(getCases(covid_19_Data, RequestedBallots[i].State, 'cases'))\n }\n return cases\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":112,"value":"covid_casesForReturnedVotes = {\n const cases = []\n for( var i = 0; i < ReturnedBallots.length; i++){\n cases.push(getCases(covid_19_Data, ReturnedBallots[i].State, 'cases'))\n }\n return cases\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":352,"value":"covid_casesForTurnoutStates = {\n const cases = []\n for( var i = 0; i < TurnoutRate.length; i++){\n cases.push(getCases(covid_19_Data, TurnoutRate[i].State, 'cases'))\n }\n return cases\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":125,"value":"requested = unpack(RequestedBallots, \"Requested\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":123,"value":"returned = unpack(ReturnedBallots, \"Returned\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":406,"value":"TotalEarlyVote = d3.csvParse(await FileAttachment(\"TotalEarlyVote@2.csv\").text(), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":539,"value":"unpack(TotalEarlyVotebyWashingtonPost, '2020 early votes')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":527,"value":"TotalEarlyVotebyWashingtonPost = d3.csvParse(await FileAttachment(\"TotalEarlyVote_byWashingtonPost@5.csv\").text(), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":327,"value":"TurnoutRate = d3.csvParse(await FileAttachment(\"Turnout_rate.csv\").text(), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":49,"value":"ReturnedBallots = d3.csvParse(await FileAttachment(\"Returned@4.csv\").text(), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":44,"value":"RequestedBallots = d3.csvParse(await FileAttachment(\"Requested@9.csv\").text(), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":235,"value":"function getCase_rate_per_100k(rows, state, key){\n for( var i=0; i < rows.length; i++) {\n if (rows[i]['State/Territory'] == state){\n return rows[i][key]\n }\n }\n};","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":228,"value":"Case_rate_per_100k =d3.csvParse(await FileAttachment(\"Case_rate_per_100k@1.csv\").text(), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":32,"value":"unpack = (rows, key) => rows.map(function(row) { return row[key]; })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":21,"value":"function getLatLong(rows, state, key){\n for( var i=0; i < rows.length; i++) {\n if (rows[i].state == state){\n return rows[i][key]\n }\n }\n};","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":24,"value":"$51","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":29,"value":"state_lat = {\n const lat = []\n for( var i = 0; i < covid_19_Data.length; i++){\n lat.push(getLatLong(stateToLatLong, covid_19_Data[i].state, 'latitude'))\n }\n return lat\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":18,"value":"state_long = {\n const long = []\n for( var i = 0; i < covid_19_Data.length; i++){\n long.push(getLatLong(stateToLatLong, covid_19_Data[i].state, 'longitude'))\n }\n return long\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":9,"value":"$52","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":7,"value":"covid_19_Data = d3.csv('https://raw.githubusercontent.com/nytimes/covid-19-data/master/live/us-states.csv', d3.autoType);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"Plotly = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4,"value":"d3 = require(\"d3@5\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":38,"value":"import {radio,select} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W53","stdlib":"1"}} 43:"$42:body"