25:["$","title",null,{"children":"MTA + COVID-19 | Rebecca Cawkwell | Observable"}] 4c:T11e1,chart_map = { var x = d3.scaleUtc() .domain(d3.extent(data.dates)) .range([margin.left, width - margin.right]) var y = d3.scaleLinear() .domain([0, d3.max(data.series, d => d3.max(d.values))]).nice() .range([height - margin.bottom, margin.top]) var line = d3.line() .defined(d => !isNaN(d)) .x((d, i) => x(data.dates[i])) .y(d => y(d)) var xAxis = g => g .attr("transform", `translate(0,${height - margin.bottom})`) .call(d3.axisBottom(x).ticks(width / 80).tickSizeOuter(0)) var yAxis = g => g .attr("transform", `translate(${margin.left},0)`) .call(d3.axisLeft(y)) .call(g => g.select(".domain").remove()) function hover(svg, path) { if ("ontouchstart" in document) svg .style("-webkit-tap-highlight-color", "transparent") .on("touchmove", moved) .on("touchstart", entered) .on("touchend", left) else svg .on("mousemove", moved) .on("mouseenter", entered) .on("mouseleave", left); const dot = svg.append("g") .attr("display", "none"); dot.append("circle") .attr("r", 2.5); dot.append("text") .attr("font-family", "sans-serif") .attr("font-size", 10) .attr("text-anchor", "middle") .attr("y", -8); function moved() { d3.event.preventDefault(); const ym = y.invert(d3.event.layerY); const xm = x.invert(d3.event.layerX); const i1 = d3.bisectLeft(data.dates, xm, 1); const i0 = i1 - 1; const i = xm - data.dates[i0] > data.dates[i1] - xm ? i1 : i0; const s = d3.least(data.series, d => Math.abs(d.values[i] - ym)); path.attr("stroke", d => d === s ? null : "#ddd").filter(d => d === s).raise(); dot.attr("transform", `translate(${x(data.dates[i])},${y(s.values[i])})`); dot.select("text").text(s.station); } function entered() { path.style("mix-blend-mode", null).attr("stroke", "#ddd"); dot.attr("display", null); } function left() { path.style("mix-blend-mode", "multiply").attr("stroke", null); dot.attr("display", "none"); } } var svg = d3.create("svg") .attr("width", 1000) .attr("height", 700) var g = svg.append("g") g.selectAll("path") .data(nyc2.features) .enter().append("path") .attr("d", path) .attr("fill","#C0C0C0"); var h = svg.append("g") var circles = h.selectAll("circle") .data(data.series) .enter().append("circle") .style("opacity", 0.7) .attr("cx",function(d,i) { var coords = proj([d.longitude,d.latitude]); return coords[0]; }) .attr("cy",function(d,i) { var coords = proj([d.longitude,d.latitude]); return coords[1]; }) .attr("r",function(d,i) { var proportion = d.values[3]/30000; return 20*proportion; }) .attr("fill",function(d) { return d3.interpolateMagma(d.values[3]/30000); }); g.attr("transform", "translate(200, 0)"); h.attr("transform", "translate(200, 0)"); var datetext = svg.append("text") .text("Wednesday, Febrary 19th") .attr("x", 50) .attr("y", 100) .style("font-size","30px") .style("font-weight","bold"); svg.append("text") .text("Total riders: ") .attr("x",50) .attr("y",130) .style("font-size","20px") .style("font-weight",20); var valtext = svg.append("text") .attr("x", 50) .attr("y", 150) .style("font-size","20px") .style("font-weight",500) .text("2868501"); const slider = d3.sliderBottom() .min(d3.min(data.dates)) .max(d3.max(data.dates)) .marks(data.dates) .width(300) .tickFormat(d3.utcFormat("%b %d")) .ticks(5) .on("onchange", function(i) { var index for(var n = 0; n < data.dates.length; n++) { //console.log(data.dates[n]); if (data.dates[n] == i) { index = n; } } circles.transition().attr("r",function(d,i) { var proportion = d.values[index]/30000; return 20*proportion; }) .attr("fill", function(d,i) { return d3.interpolateMagma(d.values[index]/30000); }); datetext.transition().text(d3.utcFormat("%A, %B %d")(i)); valtext.transition().text(function() { console.log(index); var total = 0; for (var n = 0; n < data.series.length; n++) { total += data.series[n].values[index] } return total; }); }); svg.call(slider); return svg.node() }4d:T440,md`However, as you can see on the map, stations did not experience the decrease in ridership uniformly. We decided to use MTA turnstile data and NYC COVID-19 data to determine whether the decrease in ridership was systematic, because this could have severe public health implications for the spread of coronavirus. More crowded subways means less social distancing and easier spread of disease, which could lead to health disparities between neighborhoods whose subway ridership heavily declined and whose subway ridership did not decline as much. We chose to investigate whether socioeconomic status had a significant impact on the relative decline of subway usage in different neighborhoods. Because of the COVID-19 and MTA data available to us, we looked at the average income bracket for each zip code in New York City. We acknowledge that this is not the most accurate measure of socioeconomic status or of COVID-19 cases (and zip codes != neighborhoods), but hope that this project is a good starting point to look at the implications of subway usage on the spread of COVID-19. `4e:Ta7a,chart_line = { const x = d3.scaleTime() .domain(d3.extent(turnstile_data, d => d.date)) .range([margin.left, width - margin.right]) const y = d3.scaleLinear() .domain([0, d3.max(turnstile_data, d=> d.value)]).nice() .range([height - margin.bottom, margin.top]) const line = d3.line() .defined(d => !isNaN(d.value)) .x(d => x(d.date)) .y(d => y(d.value)) function tweenDash() { const l = this.getTotalLength(), i = d3.interpolateString("0," + l, l + "," + l); return function(t) { return i(t) }; } var stage = 0 var turnstile_data_1 = turnstile_data.slice(0, 7); var turnstile_data_2 = turnstile_data.slice(6,14); var turnstile_data_3 = turnstile_data.slice(13,20); var turnstile_data_4 = turnstile_data.slice(19,); function transition(path) { path.transition() .duration(2500) .attrTween("stroke-dasharray", tweenDash) .on("end", () => { d3.select(this).call(transition); svg.selectAll('.text-box') .text(setText(stage)) .attr("style","font-size:10px"); }); } const svg = d3.create("svg") .attr("viewBox", [0, 0, width, height]) .style("overflow", "visisble"); svg.append("g") .attr("transform", "translate(0, " + (height - margin.top -10) + ")") .call(d3.axisBottom(x)); svg.append("g") .attr("transform", "translate(" + (margin.left) + ",0)") .attr('style', 'font-size: 7px') .call(d3.axisLeft(y)); svg.append("image") .attr("xlink:href", "https://cdn.onlinewebfonts.com/svg/img_70339.png") .attr("width", 30) .attr("height", 30) .attr('x', height-350) .attr('y', margin.top) .on("click", function(d) { stage += 1 var next_data; if (stage == 1){ next_data = turnstile_data_1 } if (stage == 2){ next_data = turnstile_data_2 } if (stage == 3){ next_data = turnstile_data_3 } if (stage == 4){ next_data = turnstile_data_4 } svg.append('path') .datum(next_data) .attr("fill", "none") .attr("stroke", "#7c1e84") .attr("stroke-width", 3) .attr("d", line) .call(transition); }) svg.append("text") .attr('class', 'text-box') .attr("x", height-310) .attr("y", margin.top + 10) .attr('style', 'font-size: 10px') .append("tspan") .text(setText(stage)[0]) .append("tspan") .text(setText(stage)[1]) .attr("x", height-310) .attr("dy", 22) .append("tspan") .text(setText(stage)[2]) .attr("x", height-310) .attr("dy", 22) return svg.node(); }4f:T4b7,bar_chart = { var y = d3.scaleLinear() .domain([30, d3.max(bar_data, d => d.value)]).nice() .range([height - margin.bottom, margin.top]) var x = d3.scaleBand() .domain(d3.range(bar_data.length)) .range([margin.left, width - margin.right]) .padding(0.1) var xAxis = g => g .attr("transform", `translate(0,${height - margin.bottom})`) .call(d3.axisBottom(x).tickFormat(i => bar_data[i].name).tickSizeOuter(0)) const svg = d3.create("svg") .attr("viewBox", [0, 0, width, height]); svg.append("g") .call(xAxis); svg.append("g") .attr("transform", "translate(40, 0)") .call(d3.axisLeft(y)); const bar = svg.append("g") .attr("fill", "#fdfab8") .selectAll("rect") .data(bar_data) .join("rect") .attr("x", (d, i) => x(i)) .attr("y", d => y(d.value)) .attr("height", d => y(30) - y(d.value)) .attr("width", x.bandwidth()); var myText = svg.selectAll(".mytext") .data(bar_data) .enter() .append("text") .attr('x', (d,i) => x(i) + 15) .attr('y', d => y(d.value) + 20) .attr('fill', '#7c1e84') .style("font-size", 15) .text(function(d){return d.value.toFixed(1)}) return svg.node(); }50:Tf3d,scatter_chart = { var x = d3.scaleLinear() .domain(d3.extent(scatter_data, d => d.agi_avg)).nice() .range([margin.left, width - margin.right]) var y = d3.scaleLinear() .domain(d3.extent(scatter_data, d => d.ent_percent)).nice() .range([height - margin.bottom, margin.top]) var yAxis = g => g .attr("transform", `translate(${margin.left},0)`) .call(d3.axisLeft(y)) .call(g => g.select(".domain").remove()) .call(g => g.append("text") .attr("x", margin.left) .attr("y", 10) .attr("fill", "currentColor") .attr("text-anchor", "start") .text(scatter_data.ent_percent)) var xAxis = g => g .attr("transform", `translate(0,${height - margin.bottom})`) .call(d3.axisBottom(x).ticks(width / 80)) .call(g => g.select(".domain").remove()) .call(g => g.append("text") .attr("x", width) .attr("y", margin.bottom - 4) .attr("fill", "currentColor") .attr("text-anchor", "end") .text(scatter_data.avg_agi)) function filterClick(d){ if (d == "All") { d3.selectAll('circle') .style('opacity', '1'); } else { d3.selectAll('circle') .style('opacity', '0'); d3.selectAll('.' + d) .style('opacity', '1'); } } function filterOver(d){ if (d != "All") { d3.selectAll('circle') .style('opacity', '.2'); d3.selectAll('.' + d) .style('opacity', '1'); } } function filterOut(d){ d3.selectAll('circle') .style('opacity', '1'); } const svg = d3.create("svg") .attr("viewBox", [0, 0, width, height]); var most_recent = '' svg.append("g") .attr("transform", "translate(-20, 565)" ) .call(d3.axisBottom(x)); svg.append("g") .attr("transform", "translate(20, 0)") .call(d3.axisLeft(y)); svg.append("g") .selectAll('legendcircle') .data(keys) .enter() .append("circle") .attr("class", function(d){ return d}) .attr("cx", 700) .attr("cy", function(d,i){ return 300 + i*25}) .attr("r", 3) .style("fill", function(d){ return setColor(d)}); svg.append("g") .selectAll('legendtext') .attr('class', function(d){ return d}) .data(keys) .enter() .append("text") .attr("x", 720) .attr("y", function(d,i){ return 300 + i*25}) .style("fill", function(d){ return setColor(d)}) .text(function(d){ return d}) .attr("text-anchor", "left") .style("alignment-baseline", "middle") .on('click', function(d){ console.log(d) if (most_recent == d || d == "All") { d3.selectAll('circle').style("opacity",1); d3.selectAll('text').on('mouseout', function(d){ filterOut(d); console.log(d)}); d3.selectAll('text').on('mouseover', function(d){ filterOver(d) d3.select(this).style("cursor", "pointer"); }) most_recent = "" } else{ d3.selectAll('circle').style("opacity", 0) d3.selectAll('.' + d).style("opacity", 1) d3.selectAll('text').on('mouseout', null) d3.selectAll('text').on('mouseover', null) most_recent = d } ;}) .on('mouseover', function(d){ filterOver(d) d3.select(this).style("cursor", "pointer");}) .on('mouseout', function(d) { filterOut(d)}); svg.append("g") .selectAll("circle") .data(scatter_data) .join("circle") .attr("class", function(d){ if (d.line_name == "123"){ return "Red-123"} if (d.line_name == "456"){ return "Green-456"} if (d.line_name == "7") {return "Seven"} return d.line_name}) .attr("cx", d => x(d.agi_avg)) .attr("cy", d => y(d.ent_percent)) .attr("r", 3) .attr("stroke", function(d){ return setColor(d.line_name)}) .attr("stroke-width", 1.5) .attr('fill', 'none') .on('click', function(d){ console.log(this)}); return svg.node(); }51:Tbf1,chart = { var height = 400; var y_covid = d3.scaleLinear() .domain([0, 30000]) //d3.max(covid_data, d=> d.value)]) .range([height - margin.bottom, margin.top]) var x_covid = d3.scaleTime() .domain(d3.extent(covid_data, d => d.date)).nice() .range([margin.left, width - margin.right-10]) var line_covid = d3.line() .defined(d => !isNaN(d.value)) .x(d => x_covid(d.date)) .y(d => y_covid(d.value)) function transition(path) { path.transition() .duration(5000) .attrTween("stroke-dasharray", tweenDash) .on("end", () => { d3.select(this).call(transition); }); } function tweenDash() { const l = this.getTotalLength(), i = d3.interpolateString("0," + l, l + "," + l); return function(t) { return i(t) }; } const svg = d3.create("svg") .attr("viewBox", [0, 0, width, height]) .style("overflow", "visisble"); svg.append("g") .attr("transform", "translate(0, " + (height - margin.top) + ")") .attr('style','font-size: 10px') .call(d3.axisBottom(x_covid)); svg.append("g") .attr("transform", "translate(" + (margin.left) + ",0)") .attr('style', 'font-size: 10px') .call(d3.axisLeft(y_covid)); var a = svg.append("text") .text("Queens") .attr("x", width-50) .attr("y", 50) .attr('style','font-size:10px'); var b = svg.append("text") .text("Brooklyn") .attr("x", width-50) .attr("y", 100) .attr('style','font-size:10px'); var c = svg.append("text") .text("Bronx") .attr("x", width-50) .attr("y", 160) .attr('style','font-size:10px'); var d = svg.append("text") .text("Manhattan") .attr("x", width-50) .attr("y", 230) .attr('style','font-size:10px'); var e = svg.append("text") .text("Staten Island") .attr("x", width-50) .attr("y", 300) .attr('style','font-size:8px'); // 3 var line3 = svg.append("path") .datum(bronx_data) .attr("fill", "none") .attr("stroke", d => d3.interpolateMagma(0.5)) .attr("stroke-width", 1.5) .attr("d", line_covid) .call(transition); // 1 var line1 = svg.append("path") .datum(queens_data) .attr("fill", "none") .attr("stroke", d => d3.interpolateMagma(0.85)) .attr("stroke-width", 1.5) .attr("d", line_covid) .call(transition); // 4 var line4 = svg.append("path") .datum(manhattan_data) .attr("fill", "none") .attr("stroke", d => d3.interpolateMagma(0.3)) .attr("stroke-width", 1.5) .attr("d", line_covid) .call(transition); // 2 var line2 = svg.append("path") .datum(brooklyn_data) .attr("fill", "none") .attr("stroke", d => d3.interpolateMagma(0.7)) .attr("stroke-width", 1.5) .attr("d", line_covid) .call(transition); // 5 var line5 = svg.append("path") .datum(si_data) .attr("fill", "none") .attr("stroke", d => d3.interpolateMagma(0.15)) .attr("stroke-width", 1.5) .attr("d", line_covid) .call(transition); return svg.node(); }52:T5f6,md` While subway usage is certainly not the only reason reason for differing rates of COVID-19 cases, our finding that lower-income zip codes did not experience as much of a decrease in ridership as higher-income neighborhoods could be one explanation for why Queens has the highest rate of COVID-19 cases while it does not have the largest population, and similarly why the Bronx has more cases than Manhattan. Lower-income neighborhoods already have worse health outcomes as a result of less access to healthcare and medical attention, and more crowded subways and forced contact can lead to higher rates of COVID-19 infection and exacerbate this issue. This is just one of the public health inequalities raised during the pandemic. This project can be used to make recommendations can be made to the MTA for how to minimize this issue. For example, while the MTA has cut service everywhere, it should not decrease service as much in areas where ridership has not decreased, so that people can socially distance on trains. Additionally, some subway lines might require additional cleaning if they are experiencing more riders. We won't fully understand the implications of subway ridership on the spread of COVID-19 (and vise-versa) until after the pandemic, but our findings are useful in beginning to understand the nature of the impact of COVID-19 on New York City. Future work for this project would involve using this post-pandemic data to understand how exactly the spread impacted lower income communities. `53:T8b8,md` ### Turnstile Data MTA releases turnstile data every week, which includes entry and exit data for every subway station. This data was messy, including values in the billions and negatives when turnstiles reset. We cleaned the data using python to get rid of extranneous data values and aggregate the entires/exits into one data point per station. We additionally added in zipcode data by finding a [source](https://github.com/chriswhong/nycturnstiles) that already had the latitude and longitude for each turnstile. We used an [online reverse geo-encoding program](http://more.stevemorse.org/latlonbatch2.html?direction=reverse) to find the corresponding zipcode and county for each station. ### COVID-19 Data We used the New York Times COVID-19 data. We also used the [New York State COVID-19 testing data](https://health.data.ny.gov/Health/New-York-State-Statewide-COVID-19-Testing/xdss-u53e) to look at COVID-19 cases by borough. Both data sets were cleaned with python to select only the NYC data. ### Income Data We used the IRS income data and created an "average income score" by zip code by finding the average adjusted gross income bracket for each zip code, between 1 and 5. ### Visualizations All made with D3. Preliminary exploratory visualizations were made using python and Tableau. We chose to encode each station as a point in both the map and the scatter plot to maintain the stations' individuality and show the range of ridership within subway lines. This made our data story more powerful, as many users are already familiar with the NYC subway map, so showing a different view of a familiar map helped amplify our message. With the scatterplot, the points showed the trend while showing the variance in subway lines. It was also important to us to show the changing nature of the subway and the pandemic over time, so we used line graphs to help us accomplish that. Since all of these visualizations are common, there was little user confusion, making it easier for users to focus on understanding the data story. Additionally, because we were concerned mainly with showing a correlation in the data, we did not use any specific libraries, techniques, or algorithms in the visualization itself. `54:T413,data_raw = { const fin_data = [] var data_line = [] var current_ca = "" var current_station = "" var current_zip = "" var current_lat = "" var current_long = "" d3.csv('https://raw.githubusercontent.com/avivaweinbaum/nyc-mta-covid/master/turnstile.csv').then(function(data) { data.forEach(function(d) { if (current_ca == d['C/A']){ data_line.push( +d['ent_diff'] ) } else { if (data_line.length == 48) { fin_data.push({ c_a: current_ca, station: current_station, zipcode: current_zip, latitude: current_lat, longitude: current_long, values: data_line }) //console.log(data_line) } data_line = [] current_ca = d['C/A'] current_station = d['STATION'] current_zip = d['ZIPCODE'] current_lat = d['LAT'] current_long = d['LONG'] data_line.push( +d['ent_diff'] ) } }); }); return fin_data }55:T4ba,bar_data = { var d = {"1.75": [], "2": [], "2.25": [], "2.5": [], "2.75":[], "3":[], "3.25":[], "3.5": [], "3.75":[], "4":[], "4.25": [], "4.5":[]} var col = ["1.75", "2", "2.25", "2.5", "2.75", "3", "3.25", "3.5", "3.75", "4", "4.25", "4.5"] for (var i=0; i < bar_raw_data.length; i++){ var agi = bar_raw_data[i].agi_avg var ent = bar_raw_data[i].ent_percent if (agi < 1.75) { d["1.75"].push(ent) } else if (agi < 2){ d["2"].push(ent) } else if (agi < 2.25){ d["2.25"].push(ent) } else if (agi < 2.5){ d["2.5"].push(ent) } else if (agi < 2.75){ d["2.75"].push(ent) } else if (agi < 3){ d["3"].push(ent) } else if (agi < 3.25){ d["3.25"].push(ent) } else if (agi < 3.5){ d["3.5"].push(ent) } else if (agi < 3.75){ d["3.75"].push(ent) } else if (agi < 4){ d["4"].push(ent) } else if (agi < 4.25){ d["4.25"].push(ent) } else if (agi < 4.5){ d["4.5"].push(ent) } } var data = [] for (var j=0; j < col.length; j++){ var avg_ent = d3.mean(d[col[j]]) data.push({"name": col[j], "value": avg_ent}) } return data }56:[] 48:{"id":"c0cdd259b25c492d","slug":"mta-covid","title":"MTA + COVID-19","thumbnail":"2a64bce9f0a4d2e4003cae7a85bd0963c9dff497591c641dea3ad30564e2458a","access_level":"public","create_time":"$D2020-05-04T23:09:04.170Z","update_time":"$D2020-05-14T18:02:28.392Z","view_time":null,"first_public_time":"$D2020-05-05T01:09:30.563Z","has_unpublished_edits":null,"fork":false,"stars":9,"starred":false,"owner":{"type":"team","id":"b033b8c01467a7f7","login":"rcawkwell","name":"Rebecca Cawkwell","avatar_url":"https://avatars-next.observableusercontent.com/35f1f3a88420e6cd19d8f5d3e518b8f5fc827eaa20d998688d062ccc5e5befe9","tier":"starter_2024","bio":"","followed_by_you":false,"follows_you":false},"version":244,"publish_version":244,"role":null,"authored":false,"authors":[{"type":"individual","id":"4df903033b8bd75a","login":"rcawkwell","name":"Rebecca Cawkwell","avatar_url":"https://avatars-next.observableusercontent.com/35f1f3a88420e6cd19d8f5d3e518b8f5fc827eaa20d998688d062ccc5e5befe9","tier":null,"bio":"","followed_by_you":false,"follows_you":false}],"members":[{"type":"individual","id":"4df903033b8bd75a","login":"rcawkwell","name":"Rebecca Cawkwell","avatar_url":"https://avatars-next.observableusercontent.com/35f1f3a88420e6cd19d8f5d3e518b8f5fc827eaa20d998688d062ccc5e5befe9","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":5,"collection":null,"type":"notebook","body":{"titling":"auto","title":"MTA + COVID-19","cells":[{"id":0,"value":"md`# MTA + COVID-19 \n \n### Aviva Weinbaum, Rebecca Cawkwell, Tabara Nosiba \n### Columbia Univeristy - Introduction to Data Visualization \n \nA series of data visualizations to explore the impact of the COVID-19 pandemic on New York City MTA subway usage. \n\nOur data comes from [the MTA](http://web.mta.info/developers/turnstile.html), [The New York Times](https://github.com/nytimes/covid-19-data), and [the IRS](https://www.irs.gov/statistics/soi-tax-stats-individual-income-tax-statistics-zip-code-data-soi).`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":180,"value":"html`\n

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\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":231,"value":"md`### Discussion and Future Work\n\nOur project could be expanded to potentially include visualizations that show how the data differs across neighborhoods in New York City. Moreover, while this project shows the difference in ridership among different income brackets as well as the amount of ridership across different subway routes, it would be interesting to compare turnstile data to see which particular neighborhoods or subway stops have higher movement of people. This would allow the MTA and New York City Sanitation Department better clean stations in addition to subway carts. This data can also be used to help contact tracing and warn riders of which stops to avoid if possible. \n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":236,"value":"md`### Acknowledgements or References\n\nMTA Turnstile Data\nhttp://web.mta.info/developers/turnstile.html\n\nIncome Tax Statistics by Zipcode\nhttps://www.irs.gov/statistics/soi-tax-stats-individual-income-tax-statistics-zip-code-data-soi\n\nNYC Covid-19 Test\nhttps://health.data.ny.gov/Health/New-York-State-Statewide-COVID-19-Testing/xdss-u53e/data\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":192,"value":"md`### Code, data, helper functions:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":191,"value":"function setText(stage){ \n if (stage == 0){ \n return [\"Over the course of March, COVID-19 became a greater threat.\", \"Watch how the MTA subway usage changes.\", \"The MTA usage normally fluctuates throughout the week and is lowest during the weekends.\"]\n }\n if (stage == 1){ \n return \"On Sunday March 7th, New York Governor Andrew Cuomo declared a State Emergency.\"\n }\n if (stage == 2) {\n return \"On March 14th, the first COVID-19 deaths in New York occur.\"\n }\n if (stage == 3) {\n return \"On March 20th, Governor Andrew Cuomo implements NY Pause.\"\n }\n if (stage==4){\n return \"MTA ridership has declined over 90% since March 1st.\"\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":166,"value":"proj = d3.geoConicConformal()\n .parallels([33, 45])\n .rotate([96, -39])\n .fitSize([1000, 700], nyc2)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":165,"value":"path = d3.geoPath()\n .projection(d3.geoConicConformal()\n .parallels([33, 45])\n .rotate([96, -39])\n .fitSize([1000, 700], nyc2))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":164,"value":"nyc2 = {\n var betterfeatures = nyc.features.filter(function(d) { \n return d.properties.borough != \"Staten Island\";\n })\n return {\n type: nyc.type,\n features: betterfeatures\n };\n \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":163,"value":"nyc = d3.json(\"https://gist.githubusercontent.com/pstuffa/928a2a31f352e59edef5ef56fa767e20/raw/7ba0230c627237c12cc1b3809f85d99486621756/nyc.json\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":162,"value":"data = {\n var dateRange = d3.timeDays(new Date(2020, 1, 16), new Date(2020, 3, 4));\n var format = d3.timeFormat(\"%a %d\")\n return {\n y: \"Daily Station Entries\",\n series: data_raw,\n dates: dateRange\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":161,"value":"data_raw.splice(0,1)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":160,"value":"$54","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":159,"value":"turnstile_data ={ \n var lst_dates = []\n var fin_data = []\n var f_data = d3.csv('https://raw.githubusercontent.com/avivaweinbaum/nyc-mta-covid/master/turnstile.csv').then(function(data) {\n data.forEach(function(d) {\n if (lst_dates.indexOf(d['DATE']) != -1){\n fin_data[d['DATE']].push(d['ent_diff']) \n }\n else{\n if (d['DATE'] > '02/29/2020'){\n fin_data[d['DATE']] = [d['ent_diff']] \n lst_dates.push(d['DATE'])\n }\n }\n })\n var f_data = []\n for (var i=0; i < lst_dates.length; i++){ \n var sum_ent = d3.sum(fin_data[lst_dates[i]]) \n var parser = d3.timeParse(\"%m/%d/%Y\")\n var date = parser(lst_dates[i])\n f_data.push({\"date\": date, \"value\": sum_ent})\n }\n return f_data\n })\n return f_data\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":158,"value":"$55","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":157,"value":"bar_raw_data = d3.csv(\"https://raw.githubusercontent.com/avivaweinbaum/nyc-mta-covid/master/agi_ent_diff.csv\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":103,"value":"keys = [\"All\", \"ACE\",\"BDFM\", \"G\", \"L\", \"JZ\", \"NQRW\", \"Red-123\", \"Green-456\", \"Seven\", \"S\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":102,"value":"scatter_data = d3.csv(\"https://raw.githubusercontent.com/avivaweinbaum/nyc-mta-covid/master/agi_ent_diff.csv\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":98,"value":"function setColor(d){\n console.log(d)\n if (d == \"ACE\"){\n return \"#0039A6\"\n }\n if (d == \"BDFM\"){\n return \"#FF6319\"\n }\n if (d == \"G\"){\n return \"#6CBE45\"\n }\n if (d == \"L\"){\n return \"#A7A9AC\"\n }\n if (d == \"JZ\"){\n return \"#996633\"\n }\n if (d == \"NQRW\"){\n return \"#FCCC0A\"\n }\n if (d == \"123\" || d == \"Red-123\"){\n return \"#EE352E\"\n }\n if (d == \"456\" || d == \"Green-456\"){\n return \"#00933C\"\n }\n if (d == \"7\" || d == \"Seven\"){\n return \"#B933AD\"\n }\n if (d == \"S\"){\n return \"#808183\"\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":130,"value":"bronx_data = covid_data.filter(function(d) {\n return d.boro == \"Bronx\" \n}).reverse();","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":128,"value":"queens_data = covid_data.filter(function(d) {\n return d.boro == \"Queens\" \n}).reverse();","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":126,"value":"manhattan_data = covid_data.filter(function(d) {\n return d.boro == \"New York\" \n}).reverse();","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":125,"value":"brooklyn_data = covid_data.filter(function(d) {\n return d.boro == \"Kings\" \n}).reverse();","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":122,"value":"si_data = covid_data.filter(function(d) {\n return d.boro == \"Richmond\" \n}).reverse();","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":120,"value":"covid_data ={\n var final_data = []\n var f_data = d3.csv(\"https://raw.githubusercontent.com/avivaweinbaum/nyc-mta-covid/master/covid-nyc-by-boro.csv\").then(function(data) {\n data.forEach(function(d) {\n var parser = d3.timeParse(\"%m/%d/%Y\");\n final_data.push({\n \"date\": parser(d['date']), \n \"boro\": d['county'],\n \"value\": d['total cases']\n })\n })\n return final_data\n})\n return f_data\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":26,"value":"height = 600","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":23,"value":"margin = ({top:20, right:30, bottom:30, left:40})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"d3 = require.alias({\n \"d3-array\": \"d3@5\",\n \"d3-axis\": \"d3@5\",\n \"d3-dispatch\": \"d3@5\",\n \"d3-drag\": \"d3@5\",\n \"d3-ease\": \"d3@5\",\n \"d3-scale\": \"d3@5\",\n \"d3-selection\": \"d3@5\",\n \"d3-transition\": \"d3@5\"\n})(\"d3@5\", \"d3-simple-slider@1\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W56","stdlib":"1"}} 24:null