2f:T54d,lyft_CI = Plot.plot({ width: 1100, height: 500, marginLeft: 225, marginRight: 50, marginTop: 50, insetLeft: 25, insetTop: 0, r: { range: [0, circle_radius] }, y: { tickSize: 0, label: null, //domain: no_lyff_domain }, x: { label: null, // type: 'point' }, marks: [ //Plot.frame({opacity: 0.25}), // Plot.axisX({anchor: 'top', label: null}), Plot.dot(clean_count_time_week.objects().filter(d => top_companies.includes(d.company)), { //filter: lyft_include ? null : d => d.company != 'Lyft', x: 'week_date', y: 'company', r: 'percent', //fill: 'black', fill: appcast_color_palette[5], opacity: 0.9, //interval: d3.utcWeek, interval: d3.utcMonday, title: d => `${d3.format('.0%')(d.percent)}` }), toggle ? Plot.text(clean_count_time_week.objects().filter(d => top_companies.includes(d.company)), { x: 'week_date', y: 'company', r: 'percent', fill: d => d.percent <= text_thresh ? null : 'white', fontSize: font_size, text: d => `${d3.format('.0%')(d.percent)}`, //interval: d3.utcWeek, interval: d3.utcMonday, }) : null, Plot.axisX({anchor: 'top', tickFormat: 'W' + '%U', tickSize: 0}), Plot.axisX({anchor: 'top', tickFormat: '%B', tickSize: 0, dy: -15, ticks: 3}), ] })30:T45b,Plot.plot({ inset: 50, width: 800, projection: 'albers-usa', marks: [ //Plot.geo(counties, {clip: 'frame', stroke: 'gray', strokeOpacity: 0.1, strokeWidth: 0.25}), // Add the state boundaries, Plot.geo(states, {clip: 'frame', stroke: 'gray', strokeOpacity: 0.25, strokeWidth: 0.5}), // Add the state boundaries Plot.geo(nation, {strokeWidth: 0.75, clip: 'frame'}), // Add the nation outline Plot.dot(cities_data_collect, { x: 'lng', //Provide longitude values y: "lat", // Provide latitude values fill: appcast_color_palette[1], //title: d => `${d3.format(',')(d.population)} people`, }), Plot.text(cities_data_collect, { filter: d => d.geo_city != 'Tacoma' && d.geo_city != 'Baltimore' && d.geo_city != 'Orlando' && d.geo_city != 'Sacramento' && d.geo_city != 'New Haven' && d.geo_city != 'Olympia', x: 'lng', y: 'lat', text: d => d.geo_city, dx: 20, dy: 5, stroke: 'white', fill: 'black' }) ] })31:T4bf,vl.markRect() .data(clean_count_overtime) .encode( vl.x().fieldT('date').title(null) .timeUnit('utcyearmonthdate') .axis({orient: 'top', tickCount: 'month'}), vl.y().fieldN('company').title(null) .sort(vl.sum('count').order('descending')), vl.color().fieldQ('count') .scale({ //scheme: 'redpurple', //scheme: myContinuousColors, scheme: d3.quantize(d3.interpolate(myContinuousColors[0], myContinuousColors[1]), 9) }) .legend({offset: 50, gradientThickness: 7, title: 'Number of posts'}), vl.tooltip([ {field: 'date', type: 'temporal', format: '%b %d, %Y', title: 'Date', scale: {type: 'utc'}}, {field: 'company', type: 'nominal', title: 'Company'}, {field: 'count', type: 'quantitative', title: 'Number of Posts'} ]) ) .config({ view: {stroke: null, step: 15}, axis: {labelFontWeight: 200, labelFontSize: 9, grid: false, domain: false, tickCount: 2}, axisY: {ticks: false, labelPadding: 7}, axisX: {labelOpacity: 0.5, labelLimit: 600, tickOpacity: 0.5, tickCount: 'week'}, rect: {width: {band: 0.975}, height: {band: 0.95}} }) .padding({top: 25, bottom: 100}) .width(640) .render()32:T42c,"new job" // new_jobs = Plot.plot({ // width: 500, // marginTop: 50, // marginLeft: 125, // height: 500, // color: { // //legend: true, // domain: ['true', 'false'], // range: [appcast_color_palette[0], appcast_color_palette[5]] // }, // facet: { // marginRight: 100 // }, // fy: { // padding: 0.2, // label: null // }, // fx: { // label: "Is it a new job?", // padding: 0.2 // }, // marks: [ // Plot.frame(), // Plot.axisX({ticks: 'month'}), // Plot.axisY({labelAnchor: 'center', interval: 50, anchor: 'right', labelOffset: 50,}), // //Plot.gridY(), // Plot.axisFx({anchor: 'top'}), // Plot.axisFy({anchor: 'left'}), // Plot.rectY(clean.filter(d => top_companies.includes(d.company)), Plot.binX({y: 'count'},{ // x: 'date', // thresholds: d3.utcMonday, // fx: 'new_job', // fy: 'company', // fill: d => d.new_job, // === 'true' ? appcast_color_palette[0] : appcast_color_palette[5] // insetRight: 2, // insetLeft: 2 // })) // ] // })33:T49b,"old jobs" // new_jobs2 = Plot.plot({ // width: 250, // // marginTop: 50, // marginLeft: 125, // // height: 500, // color: { // scheme: 'YlOrBr', // legend: true, // width: 150, // label: 'Old posts by month' // }, // // facet: { // // marginRight: 100 // // }, // fy: { // padding: 0.2 // }, // // fx: { // // label: "Is it a new job?", // // padding: 0.2 // // }, // marks: [ // Plot.axisX({anchor: 'bottom', tickFormat: Plot.formatMonth()}), // // Plot.axisY({labelAnchor: 'center', interval: 50, anchor: 'right', labelOffset: 50,}), // // //Plot.gridY(), // Plot.axisY({label: null}), // // Plot.axisFy({anchor: 'left'}), // Plot.cell(clean.filter(d => top_companies.includes(d.company) && d.new_job == 'false'), Plot.group({fill: 'count'},{ // filter: d => d.company != 'Lyft', // x: d => d3.utcMonth.count(d3.utcYear(d.date), d.date), // //x: (d) => d3.utcWeek.count(d3.utcYear(d.date), d.date), // // thresholds: d3.utcMonday, // y: 'company', // sort: {y: 'fill', reverse: true} // // insetRight: 2, // // insetLeft: 2 // })) // ] // })34:T64e,Plot.plot({ marginLeft: 110, marginRight: 0, marginBottom: 100, width: 1000, //height: 1000, projection: "albers", // Set the projection r: { range: [1, 8] }, fy: { label: null }, x: { label: 'Weeks' }, facet: { data: zips_filtered_month, y: 'company', x: d => d.month_date }, fx: { padding: 0.1, tickFormat: '%B' }, marks: [ Plot.geo(states, {clip: 'frame', stroke: 'gray', strokeOpacity: 0.5, strokeWidth: 0.25}), // Add the state boundaries Plot.geo(nation, {strokeWidth: 1, clip: 'frame'}), // hex binned // Plot.dot(zips_filtered, Plot.hexbin({r: 'sum', title: 'sum', opacity: 'sum'},{ // x: 'longitude', //Provide longitude values // y: "latitude", // Provide latitude values // r: "count", // Update bubble radius based on this variable's value, // //fill: d => d.company, // == 'Lyft' ? d3.schemeAccent[5] : d.company, // fill: '#eb2484', // //opacity: 'count', // //symbol: 'circle', // title: d => `${d.count}` // Posts in ${zip_map.get(d.corrected_zip).city}`, // })), // no bins Plot.dot(zips_filtered_month, { x: 'longitude', //Provide longitude values y: "latitude", // Provide latitude values r: "count", // Update bubble radius based on this variable's value, //fill: d => d.company == 'Lyft' ? appcast_color_palette[1] : appcast_color_palette[4], fill: d => d.company == 'Lyft' ? appcast_color_palette[1] : 'black', opacity: 0.75, title: d => `${d.count} Posts in ${zip_map.get(d.corrected_zip).city}`, }), ] })35:T887,viewof title_categories = Inputs.table(titles .select(1,0) //.orderby(aq.desc('company'), 'job_title') .derive({ title_category: d => op.includes(op.lower(d.job_title), 'extra') ? 'gig' : // gig op.includes(op.lower(d.job_title), 'deliver') ? 'deliver goods' : // deliver goods op.includes(op.lower(d.job_title), 'contractor') ? 'contractor' : op.includes(op.lower(d.job_title), '$') ? 'incentive or hourly amount' : // incentive op.includes(op.lower(d.job_title), 'medical') ? 'medical' : // drive to medical appointments op.includes(op.lower(d.job_title), 'flexible') ? 'flexible schedule' : // flexible schedule op.includes(op.lower(d.job_title), 'schedule') ? 'flexible schedule' : // flexible schedule op.includes(op.lower(d.job_title), 'sign up today') ? 'gig' : // gig op.includes(op.lower(d.job_title), 'gig') ? 'gig' : // gig op.includes(op.lower(d.job_title), 'part time') ? 'part time' : // part time op.includes(op.lower(d.job_title), 'needed') ? 'needed' : // needed op.includes(op.lower(d.job_title), 'choose') ? 'flexible schedule' : // flexible schedule op.includes(op.lower(d.job_title), 'school') ? 'school' : // drive to school op.includes(op.lower(d.job_title), 'drive with') ? 'drive with us' : // invitation 'other' }) .groupby('company') .rollup({ title_categories: d => op.array_agg_distinct(d.title_category), //distinct_titles: d => op.array_agg_distinct(d.job_title), 'Number of unique titles': d => op.distinct(d.job_title) }) // .derive({ // distinct_title_count: aq.escape(d => d3.count(d.distinct_titles)) // }) .orderby('company') .rename({title_categories: 'Title Categories'}) // .filter(d => d.company != "Lyft") .objects(), { height: 550, width: 900, layout: 'auto' })36:Taa0,title_categories_notes = Inputs.table(titles .select(1,0) //.orderby(aq.desc('company'), 'job_title') .derive({ title_category: d => op.includes(op.lower(d.job_title), 'extra') ? 'gig' : // gig op.includes(op.lower(d.job_title), 'deliver') ? 'deliver goods' : // deliver goods //op.includes(op.lower(d.job_title), 'tips') ? 'tips' : op.includes(op.lower(d.job_title), '$') ? 'incentive or hourly amount' : // incentive op.includes(op.lower(d.job_title), 'medical') ? 'medical' : // drive to medical appointments op.includes(op.lower(d.job_title), 'flexible') ? 'flexible schedule' : // flexible schedule op.includes(op.lower(d.job_title), 'schedule') ? 'flexible schedule' : // flexible schedule op.includes(op.lower(d.job_title), 'sign up today') ? 'gig' : // gig op.includes(op.lower(d.job_title), 'gig') ? 'gig' : // gig op.includes(op.lower(d.job_title), 'part time') ? 'part time' : // part time op.includes(op.lower(d.job_title), 'needed') ? 'needed' : // needed op.includes(op.lower(d.job_title), 'choose') ? 'flexible schedule' : // flexible schedule op.includes(op.lower(d.job_title), 'school') ? 'school' : // drive to school op.includes(op.lower(d.job_title), 'drive with') ? 'drive with us' : // invitation 'other' }) .derive({notes: d => d.title_category == 'gig' ? 'Related to getting a side gig or suggesting you can "earn extra"' : d.title_category == 'deliver goods' ? 'Calling out that these are for delivering goods' : d.title_category == 'incentive or hourly amount' ? 'Emphasizing incentives' : d.title_category == 'medical' ? 'A gig related to driving people to/from medical appointments' : d.title_category == 'flexible schedule' ? 'Mentions the flexibility of the job/schedule' : d.title_category == 'part time' ? 'Highlighting the part time aspect' : d.title_category == 'needed' ? 'Company mentioning they need drivers' : d.title_category == 'school' ? 'In relation to driving students to/from school' : d.title_category == 'drive with us' ? 'Framing as an invitation' : d.title_category}) .select(2,3) .dedupe() .rename({title_category: 'Title Category'}) .objects(), { width: 700, layout: 'auto' })37:T85a,viewof title_categories_incentives = Inputs.table(titles .select(1,0) //.orderby(aq.desc('company'), 'job_title') .derive({ title_category: d => op.includes(op.lower(d.job_title), 'extra') ? 'gig' : // gig op.includes(op.lower(d.job_title), 'deliver') ? 'deliver goods' : // deliver goods op.includes(op.lower(d.job_title), 'contractor') ? 'contractor' : op.includes(op.lower(d.job_title), '$') ? 'incentive or hourly amount' : // incentive op.includes(op.lower(d.job_title), 'medical') ? 'medical' : // drive to medical appointments op.includes(op.lower(d.job_title), 'flexible') ? 'flexible schedule' : // flexible schedule op.includes(op.lower(d.job_title), 'schedule') ? 'flexible schedule' : // flexible schedule op.includes(op.lower(d.job_title), 'sign up today') ? 'gig' : // gig op.includes(op.lower(d.job_title), 'gig') ? 'gig' : // gig op.includes(op.lower(d.job_title), 'part time') ? 'part time' : // part time op.includes(op.lower(d.job_title), 'needed') ? 'needed' : // needed op.includes(op.lower(d.job_title), 'choose') ? 'flexible schedule' : // flexible schedule op.includes(op.lower(d.job_title), 'school') ? 'school' : // drive to school op.includes(op.lower(d.job_title), 'drive with') ? 'drive with us' : // invitation 'other' }) // .groupby('company') // .rollup({ // title_categories: d => op.array_agg_distinct(d.title_category), // //distinct_titles: d => op.array_agg_distinct(d.job_title), // 'Number of unique titles': d => op.distinct(d.job_title) // }) .orderby('company') //.rename({title_categories: 'Title Categories'}) .filter(d => d.title_category == 'incentive or hourly amount') .dedupe('job_title') .objects(), { height: 550, width: 900, layout: 'auto' })38:T554,// clean up process for benefits viewof benefits = aq.from(clean) .select('company', 'benefits') // select these columns only .derive({ num_benefits: aq.escape( d => d3.count(d.benefits) ) // get a count of benefits by row }) .dedupe('company','benefits') // deduplicate rows with the same benefit list .filter(d => d.num_benefits > 0) // remove those without benefits (for other purposes, this might be useful) // below is the part where I very ungracefully work with the arrays // starts here .derive({ benefits: d => op.replace(d.benefits, "['", "") }) .derive({ benefits: d => op.replace(d.benefits, "']", "") }) .derive({ benefits: d => op.replace(d.benefits, /'/g, "") }) // ends here ^ .groupby('company') // once the array is clean, group all benefits by company .rollup({ all_benefits: d => op.array_agg(d.benefits) // one company, one array of benefits }) .derive({ all_benefits: d => op.split(d.all_benefits, ',') }) .unroll('all_benefits') // do one company and one benefit per row .derive({ all_benefits: d => op.trim(d.all_benefits) }) .dedupe('company', 'all_benefits') // remove duplicates that resulted from the above .rename({all_benefits: 'benefit'}) .derive({ benefit: d => d.company == 'Lyft' ? null : d.benefit }) .filter(d => d.benefit != null) .view()39:[{"id":"d5c74363cebed077b16f2c25d09fa42d22dc06803a2ff0958ee1ca56c460369689cdc894c33422c3de9cb102062bbfe8a98a6ea834fd69b7122a4297ebecc56b","href":"https://static.observableusercontent.com/files/d5c74363cebed077b16f2c25d09fa42d22dc06803a2ff0958ee1ca56c460369689cdc894c33422c3de9cb102062bbfe8a98a6ea834fd69b7122a4297ebecc56b","name":"uscities.csv","type":"text/csv","lastModified":1681834258438.311,"size":5114540}] 2d:{"title":"Competitive Intelligence","cells":[{"id":0,"value":"md `# Competitive Intelligence`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2990,"value":"md `

\n## Step 1`","pinned":false,"hidden":false,"mode":"ojs"},{"id":503,"value":"viewof file = Inputs.file({label: \"Load the data\", required: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3167,"value":"md `*Note: if you need the query that is used to generate the data, click [here](https://observablehq.com/d/346afbc3992b2dbd#query) (it will take you to the bottom of this page)*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3019,"value":"md `
\n## Step 2\nSelect the end for the date range. This date drop-down can be used when you need to modify the date range, however, the default for the weekly report should be from \"3/02/2023\" to Sunday of the previous week.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3035,"value":"viewof start_date = Inputs.date({label: \"Start Date\", value: d3.min(clean, d => d.date)})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2610,"value":"viewof end_date = Inputs.date({label: \"End Date\", value: d3.utcDay.offset(new Date(), -1)})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3201,"value":"md `
\n## Step 3\nTake screenshots of the two charts below. Keep in mind that you might need to make adjustments for each of the visuals, you can use the *control panels* for that.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2994,"value":"md `

\n# Top Competitors`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3014,"value":"md `## Market Share by Top Competitor`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1156,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs"},{"id":3010,"value":"md `### *Control Panel*\n*(for bubble chart)*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1290,"value":"viewof toggle = Inputs.toggle({label: \"Show labels\", value: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2289,"value":"viewof font_size = Inputs.range([1, 15], {label: \"Font size\", step: 0.5})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2705,"value":"viewof circle_radius = Inputs.range([0, 30], {label: \"Dot radius\", step: 1, value: 20})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2981,"value":"viewof text_thresh = Inputs.range([0, 0.3], {label: \"text thresh\", step: 0.01, value: 0.15})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3023,"value":"md `

\n\n## Overall Top Competitor Intensity`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1375,"value":"wow_competitor_count_plot = Plot.plot({\n insetTop: 0,\n width: 425,\n height: 200,\n marginTop: 50,\n marginRight,\n y: {\n label: 'Weekly count of posts by Top Competitors (excluding Lyft)',\n },\n x: {\n domain: [new Date(2023,0,1), d3.max(clean_count_overtime_agg, d => d.date)],\n nice: d3.utcMonth\n },\n marks: [\n Plot.axisX({interval: 'month'}),\n Plot.rectY(clean_count_overtime_agg, {\n //filter: d => d.company != 'Lyft',\n x: 'date',\n y: 'count',\n interval: d3.utcMonday,\n insetRight: 2,\n insetLeft: 2,\n fill: appcast_color_palette[0]\n }),\n Plot.text(clean_count_overtime_agg, Plot.selectLast({\n x: 'date',\n y: 'count',\n text: d => `${d3.format('+.0%')(d.perc_change)} WoW`,\n dy: text_y,\n dx: text_x,\n fill: appcast_color_palette[0]\n })),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3026,"value":"md `### *Control Panel*\n*(for the text on the most recent week of the bar chart)*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2726,"value":"viewof text_x = Inputs.range([-50, 50], {label: \"text x\", step: 1, value: 30})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2729,"value":"viewof text_y = Inputs.range([-40, 30], {label: \"text y\", step: 1, value: -20})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2733,"value":"viewof marginRight = Inputs.range([0, 200], {label: \"Marging Right\", step: 1, value: 60})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3192,"value":"md `

\n\n# Other views\n*Not used in the weekly report*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3438,"value":"toc({\n title: 'Other data views',\n headers: 'h1,h2',\n skip: [\"Competitive Intelligence\", 'Step 1', 'Step 2', 'Step 3', 'Top Competitors', 'Market Share by Top Competitor', 'Overall Top Competitor Intensity', 'Other views'],\n hideStartingFrom: 'Appendix'\n \n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1660,"value":"md `

\n\n## Distinct competitors by day`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1650,"value":"viewof view_by_day = Inputs.toggle({label: \"View by day\", value: false})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1613,"value":"Plot.plot({\n height: 300,\n insetTop: 25,\n x: {\n nice: d3.utcMonth\n },\n marks: [\n Plot.gridY({interval: 5}),\n Plot.axisX({interval: 'month'}),\n Plot.axisX({anchor: 'top', tickFormat: 'Q' + '%q', opacity: 0.25, interval: 'quarter', tickSize: 0}),\n Plot.axisY({interval: 5, label: 'Distinct Competitors by Day ↑'}),\n Plot.gridX({interval: 'quarter'}),\n Plot.ruleY([0]),\n view_by_day ? null : Plot.lineY(distinct_competitors, {x: \"date\", y: \"distinct\", curve: 'basis', stroke: appcast_color_palette[0]}),\n Plot.dot(distinct_competitors, Plot.selectLast({x: 'date', y: 'distinct', fill: appcast_color_palette[0]})),\n view_by_day ? Plot.lineY(distinct_competitors, {x: \"date\", y: \"distinct\", strokeWidth: 1, marker: true, stroke: appcast_color_palette[0]}) : null,\n view_by_day ? Plot.dot(distinct_competitors, {filter: d => d.distinct < 5, x: 'date', y: 'distinct', fill: 'red'}) : null,\n Plot.ruleX([d3.utcParse('%Y-%m-%d')(\"2023-06-01\")], {stroke: appcast_color_palette[2]}),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3397,"value":"md `

\n## Locations where we collect data`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1550,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":3400,"value":"md `

\n\n## Competition intensity by day`","pinned":false,"hidden":false,"mode":"ojs"},{"id":645,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":1802,"value":"Plot.plot({\n insetTop: 25,\n width: 450,\n height: 200,\n marginRight: 60,\n x: {\n domain: [new Date(2023,0,1), d3.max(clean_count_overtime_agg, d => d.date)]\n },\n y: {\n label: 'Total count of posts by Top Competitors'\n },\n marks: [\n Plot.rectY(clean_count_overtime.objects().filter(d => top_companies.includes(d.company)), Plot.binX({y: 'sum'},{\n x: 'date',\n y: 'count',\n interval: d3.utcMonday,\n insetRight: 2,\n insetLeft: 2,\n //fill: d => d.company == 'Lyft' ? appcast_color_palette[4] : appcast_color_palette[5],\n fill: d => d.company == 'Lyft' ? appcast_color_palette[1] : 'black',\n })),\n // Plot.text(clean_count_overtime.objects().filter(d => top_companies.includes(d.company)), Plot.binX({y: 'sum'},{\n // x: 'date',\n // y: 'count',\n // interval: d3.utcDay,\n // text: 'date'\n // })),\n // Plot.gridX({interval: 'week'}),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1899,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":2154,"value":"\"new job heat\"\n// new_jobs1 = Plot.plot({\n// width,\n// marginLeft: 125,\n// //height: 2000,\n// color: {\n// range: color_range,\n// //legend: true,\n// //width: 150,\n// //label: 'New posts by month'\n// },\n// // facet: {\n// // marginRight: 100\n// // },\n// fy: {\n// padding: 0.2\n// },\n// // fx: {\n// // label: \"Is it a new job?\",\n// // padding: 0.2\n// // },\n// marks: [\n// Plot.axisX({anchor: 'top', ticks: 'month'}),\n// // Plot.axisY({labelAnchor: 'center', interval: 50, anchor: 'right', labelOffset: 50,}),\n// // //Plot.gridY(),\n// Plot.axisY({label: null}),\n// // Plot.axisFy({anchor: 'left'}),\n// Plot.cell(clean.filter(d => top_companies.includes(d.company) && d.new_job == 'true'), Plot.group({fill: 'count'},{\n// filter: d => d.company != 'Lyft',\n// x: d => d3.utcDay.count(d3.utcYear(d.date), d.date),\n// y: 'company',\n// //fy: 'geo_city',\n// sort: {y: 'fill', reverse: true}\n// }))\n// ]\n// })","pinned":false,"hidden":false,"mode":"ojs"},{"id":2199,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":823,"value":"geo = md `

\n\n## By geographic area\n*Size of the circle denotes the total number of posts*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":922,"value":"viewof company_selector = Inputs.select(zips_clean.map(d => d.company), {label: \"Select a company (CTRL + click to select multiple)\", unique: true, multiple: true, value: ['Lyft', 'Uber Drivers', 'DoorDash']})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1734,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":1433,"value":"md `## Benefits`","pinned":false,"hidden":false,"mode":"ojs"},{"id":895,"value":"vl.markCircle({\n fill: appcast_color_palette[1],\n size: 70\n})\n .data(benefits)\n .encode(\n vl.y().fieldN('benefit')\n .title('Benefit'),\n vl.x().fieldN('company')\n .title('Company')\n .axis({\n orient: 'top'\n }),\n )\n .config({\n view: {stroke: null, step: 20},\n //view: {stroke: 'black', strokeOpacity: 0.5, step: 20},\n axis: {\n grid: true, gridOpacity: 0.5, \n tickOpacity: 0.75, domain: false, \n labelFontWeight: 200, labelFontSize: 10,\n titleFontWeight: 50\n },\n axisY: {titlePadding: 50},\n circle: {size: 200}\n })\n //.width(400).height(300)\n .padding({top: 25, bottom: 50, right: 50, left: 50})\n .render()","pinned":false,"hidden":false,"mode":"ojs"},{"id":2326,"value":"md `

\n\n## Job titles`","pinned":false,"hidden":false,"mode":"ojs"},{"id":777,"value":"vl.markCircle({fill: '#eb2484', opacity: 0.5, tooltip: true})\n .data(titles.filter(d => d.company != \"Lyft\")) \n .encode(\n vl.x().fieldN('company')\n .axis({orient: 'top'}),\n vl.y().fieldN('job_title').title(null)\n .axis({labelLimit: 400})\n )\n .config({\n view: {stroke: null, step: 20},\n axis: {grid: true, gridOpacity: 0.25, tickOpacity: 0.25, domain: false, labelFontWeight: 200, labelFontSize: 10},\n circle: {size: 200}\n })\n .render()","pinned":false,"hidden":false,"mode":"ojs"},{"id":2363,"value":"md `

\n\n## Titles by company`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2355,"value":"Inputs.bind(Inputs.select(zips_clean.map(d => d.company), {label: \"Select a company (CTRL + click to select multiple)\", unique: true, multiple: true, sort: true, value: ['Lyft', 'Uber Drivers', 'DoorDash']}), viewof company_selector)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2358,"value":"titles\n .filter(aq.escape(d => company_selector.includes(d.company)))\n .select(1,0)\n .orderby(aq.desc('company'), 'job_title')\n .view()","pinned":false,"hidden":false,"mode":"ojs"},{"id":2366,"value":"md `
\n## Title categories`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2329,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":2467,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":2545,"value":"md `## Incentives in titles`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2548,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":2034,"value":"md `## Ad placement`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1845,"value":"Plot.plot({\n marginLeft: 115,\n marginTop: 40,\n height: 450,\n width: 900,\n insetTop: 0,\n insetLeft: 5,\n //width: 1000,\n facet: {\n marginRight: 200\n },\n fy: {\n padding: 0.3\n },\n fx: {\n padding: 0.1\n },\n marks: [\n Plot.axisX({anchor: 'top', interval: 3, labelAnchor: 'center', labelOffset: 35, facetAnchor: 'top', label: 'Ad placement'}),\n Plot.axisY({anchor: 'right', labelAnchor: 'center', interval: 100, labelOffset: 50}),\n //Plot.gridY({interval: 50, opacity: 0.05}),\n Plot.axisFy({anchor: 'left', label: null}),\n Plot.axisFx({anchor: 'bottom', tickFormat: Plot.formatMonth(\"en\", \"long\")}),\n Plot.frame({opacity: 0.5}),\n Plot.rectY(top_clean.filter(d => d.company != 'Shipt' && d.company != 'AxleHire' && d.company != 'Lime'), Plot.binX({y: 'count'},{\n x: 'rank',\n fy: 'company',\n fx: d => d.date.getUTCMonth(),\n insetRight: 0,\n insetLeft: 0\n }))\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3074,"value":"md `# By Market`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3076,"value":"viewof city_selector = Inputs.select(list_of_cities, {label: \"Select a city\", sort: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3049,"value":"vl.markRect({tooltip: true, height: {band: 0.9}, width: {band: 0.9}})\n .data(by_market)\n .encode(\n vl.x().fieldT('date').title(city_selector +' - Competitor Post Counts')\n .timeUnit('utcweek')\n .axis({orient: 'top', format: '%b %d', tickCount: 'month'}),\n vl.y().fieldN('company').title(null),\n vl.color().count()\n .scale({\n range: [appcast_color_palette[8], appcast_color_palette[5]]\n })\n .legend({offset: 50, title: 'Number of posts', gradientThickness: 5, direction: 'horizontal'})\n )\n .config({\n view: {stroke: null},\n axis: {grid: null, domain: false},\n axisX: {titlePadding: 10}\n })\n .render()","pinned":false,"hidden":false,"mode":"ojs"},{"id":834,"value":"htl.html `

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":88,"value":"
\n
\n
\n

","pinned":false,"hidden":false,"mode":"html"},{"id":20,"value":"md `## Appendix\n\n_Implementation & data stuff_`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3210,"value":"md `### *Color*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":942,"value":"viewof color_selector = Inputs.color({label: \"Favorite color\", value: \"#4682b4\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1505,"value":"color_range = d3.quantize(d3.interpolate(myContinuousColors[0], myContinuousColors[1]), 9)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1460,"value":"myContinuousColors = ['#e4e4e4', appcast_color_palette[0]] // [appcast_color_palette[3], appcast_color_palette[0]]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1462,"value":"{\n const div = d3.create('div')\n .style('display', 'flex')\n div.selectAll('div')\n .data(myContinuousColors)\n .join('div')\n .style('width', 'auto')\n .style('padding', '5px')\n .style('margin', '2px')\n .style('border-radius', '2px')\n .style('background-color', d => d)\n .text(d => d).node()\n return div.node()\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1458,"value":"Plot.plot({\n color: {\n type: \"linear\",\n range: myContinuousColors // uses d3.interpolateRgb\n },\n marks: [\n Plot.cell(d3.range(50), {x: d => d, fill: d => d})\n ],\n axis: null,\n height: 30,\n x: {padding: -0.1},\n width: 300\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1482,"value":"Plot.plot({\n color: {\n type: \"linear\",\n range: myContinuousColors,\n interpolate: 'hcl'\n },\n marks: [\n Plot.cell(d3.range(50), {x: d => d, fill: d => d})\n ],\n axis: null,\n height: 30,\n x: {padding: -0.1},\n width: 300\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3173,"value":"query = md `\n
\n\n### *Query*\n
\nBelow is the query needed for this notebook (any analyst with access to the Chuck's competitive intel database should be able to get this data):\n\n~~~sql\nselect *\nfrom indeed_master2\nwhere dataset = 'Lyft'\n~~~\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":198,"value":"

\n\n### *Data*","pinned":false,"hidden":false,"mode":"md"},{"id":1607,"value":"viewof distinct_competitors = aq.from(raw_data)\n .derive({date: d => op.parse_date(d.date)})\n .groupby('date')\n .rollup({\n distinct: d => op.distinct(d.company)\n })\n .orderby('date')\n .view()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1010,"value":"viewof clean_count_time_week = clean_count_overtime\n .derive({date: d => op.parse_date(d.date)})\n .derive({\n week_date: aq.escape( d => d3.utcMonday(d.date) )\n })\n .groupby('week_date', 'company')\n .rollup({\n count: d => op.sum(d.count)\n })\n .groupby('week_date')\n .derive({\n percent: d => d.count/op.sum(d.count)\n })\n .filter(aq.escape( d => d.week_date >= start_date && d.week_date <= end_date) )\n .view()","pinned":true,"hidden":false,"mode":"ojs"},{"id":1000,"value":"top_companies = clean_count_overtime\n .groupby('company')\n .rollup({\n count: d => op.sum(d.count)\n })\n .orderby(aq.desc('count'))\n .filter(d => op.rank() <= 10)\n .array('company')","pinned":true,"hidden":false,"mode":"ojs"},{"id":1893,"value":"top_clean = clean.filter(d => top_companies.includes(d.company))","pinned":true,"hidden":false,"mode":"ojs"},{"id":981,"value":"palettes","pinned":true,"hidden":false,"mode":"ojs"},{"id":874,"value":"$38","pinned":true,"hidden":false,"mode":"ojs"},{"id":1645,"value":"Inputs.table(cities_data_collect)","pinned":true,"hidden":false,"mode":"ojs"},{"id":2082,"value":"cities_data_collect\n .count()\n .view()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1512,"value":"// list of cities that we gather data from\nviewof cities_data_collect = aq.from(raw_data)\n .select(7,8)\n .dedupe()\n .derive({\n geo_city: d => op.trim(d.geo_city),\n geo_state: d => op.trim(d.geo_state)\n })\n .join(aq.from(us_cities_lat_long), ['geo_city', 'city'])\n .select(0,1,8,9,10)\n .orderby('geo_city')\n .dedupe('geo_city', 'geo_state')\n .derive({\n text_show: d => d.geo_state\n })\n .derive({geo_city: d => op.trim(d.geo_city)})\n .view()","pinned":true,"hidden":false,"mode":"ojs"},{"id":1518,"value":"us_cities_lat_long = FileAttachment(\"uscities.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs"},{"id":771,"value":"viewof titles = aq.from(clean)\n // .derive({\n // date: d => op.parse_date(d.date)\n // })\n .select('job_title', 'company')\n .dedupe()\n .view()","pinned":true,"hidden":false,"mode":"ojs"},{"id":925,"value":"zips_filtered_month = zips_clean_month.filter(d => company_selector.includes(d.company))","pinned":true,"hidden":false,"mode":"ojs"},{"id":1743,"value":"zips_filtered = zips_clean.filter(d => company_selector.includes(d.company))","pinned":true,"hidden":false,"mode":"ojs"},{"id":1739,"value":"zips_clean_month = aq.from(clean)\n .derive({\n corrected_zip: aq.escape( d => d3.count(d.geo_zipcode) == 4 ? `0${d.geo_zipcode}` : d.geo_zipcode ),\n date: d => op.parse_date(d.date)\n })\n .filter(aq.escape( d => d.date <= end_date) )\n .select('date', 'company', 'corrected_zip')\n .derive({month_date: aq.escape(d => d3.utcMonth(d.date))})\n .join(aq.from(zip_codes), ['corrected_zip', 'zip_code'])\n .groupby('month_date', 'company', 'latitude', 'longitude', 'corrected_zip')\n .count()\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":673,"value":"zips_clean = aq.from(clean)\n .derive({\n corrected_zip: aq.escape( d => d3.count(d.geo_zipcode) == 4 ? `0${d.geo_zipcode}` : d.geo_zipcode ),\n date: d => op.parse_date(d.date)\n })\n .filter(aq.escape( d => d.date <= end_date) )\n .select('date', 'company', 'corrected_zip')\n .derive({week_date: aq.escape(d => d3.utcMonday(d.date))})\n .join(aq.from(zip_codes), ['corrected_zip', 'zip_code'])\n .groupby('week_date', 'company', 'latitude', 'longitude', 'corrected_zip')\n .count()\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":710,"value":"import {us} from \"@observablehq/build-your-first-choropleth-map-with-observable-plot\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":733,"value":"states = topojson.feature(us, us.objects.states)","pinned":true,"hidden":false,"mode":"ojs"},{"id":793,"value":"nation = topojson.feature(us, us.objects.nation)","pinned":true,"hidden":false,"mode":"ojs"},{"id":857,"value":"counties_ = topojson.feature(us, us.objects.counties)","pinned":true,"hidden":false,"mode":"ojs"},{"id":723,"value":"latitude_map = new Map(zips_filtered.map(({corrected_zip, latitude}) => [corrected_zip, latitude]))","pinned":true,"hidden":false,"mode":"ojs"},{"id":932,"value":"zips_filtered","pinned":true,"hidden":false,"mode":"ojs"},{"id":726,"value":"longitude_map = new Map(zips_filtered.map(({corrected_zip, longitude}) => [corrected_zip, longitude]))","pinned":true,"hidden":false,"mode":"ojs"},{"id":508,"value":"viewof clean_count_overtime = aq.from(clean)\n .derive({date: d => op.parse_date(d.date)})\n .groupby('date')\n .derive({\n distinct_cities: d => op.distinct(d.company)\n })\n // .filter(d => d.company != 'Lyft')\n .groupby('date', 'company')\n .rollup({\n count: d => op.count(),\n })\n // .derive({\n // perc_change: d => (d.count - op.lag(d.count,1)) / op.lag(d.count,1)\n // })\n .orderby('date')\n .view()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2504,"value":"viewof clean_count_overtime_agg = aq.from(clean)\n .derive({date: d => op.parse_date(d.date)})\n .derive({\n date: aq.escape(d => d3.utcMonday(d.date))\n })\n .filter(aq.escape( d => d.date <= end_date) )\n .groupby('date')\n .derive({\n distinct_cities: d => op.distinct(d.company)\n })\n .filter(d => d.company != 'Lyft')\n .filter(aq.escape(d => top_companies.includes(d.company)))\n .groupby('date')\n .rollup({\n count: d => op.count(),\n })\n .derive({\n perc_change: d => (d.count - op.lag(d.count,1)) / op.lag(d.count,1)\n })\n .orderby('date')\n .view()","pinned":true,"hidden":false,"mode":"ojs"},{"id":871,"value":"md `## Clean data`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1810,"value":"viewof search = Inputs.search(clean)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1814,"value":"Inputs.table(search)","pinned":true,"hidden":false,"mode":"ojs"},{"id":869,"value":"clean = aq.from(raw_data)\n .derive({date: d => op.parse_date(d.date)})\n .derive({\n company: d => d.company == 'Ohio Independent Contractor Services (OICS)' || \n d.company == 'Ohio Independent Contractor Services (OICS) [Website: oicsdeliver.com]' || \n d.company == 'Ohio Independent Contractor Services [Website: oicsdeliver.com]' ||\n d.company == 'Ohio Independent Contractor Services [website: oicsdeliver.com]'\n ? 'Ohio Independent Contractor Services' : d.company\n })\n .derive({rank: d => +d.rank})\n .orderby('date')\n .derive({\n city_state: d => `${op.trim(d.geo_city)}, ${d.geo_state}`\n })\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":3078,"value":"md `## By market`","pinned":true,"hidden":false,"mode":"ojs"},{"id":3041,"value":"viewof by_market = aq.from(clean)\n .derive({date: aq.escape(d => d3.utcMonday(d.date))})\n .filter(aq.escape(d => d.city_state == city_selector))\n .view()","pinned":true,"hidden":false,"mode":"ojs"},{"id":3081,"value":"list_of_cities = aq.from(clean)\n .select('city_state')\n .dedupe()\n .array('city_state')","pinned":true,"hidden":false,"mode":"ojs"},{"id":3070,"value":"

","pinned":false,"hidden":false,"mode":"html"},{"id":705,"value":"zip_codes = d3.csvParse(data)","pinned":true,"hidden":false,"mode":"ojs"},{"id":689,"value":"prox_url = 'https://corsproxy.io?' + encodeURIComponent(v_data['zipcodes.csv'].url)","pinned":true,"hidden":false,"mode":"ojs"},{"id":698,"value":"data = fetch(prox_url).then(response => response.text())","pinned":true,"hidden":false,"mode":"ojs"},{"id":505,"value":"raw_data = file.csv({typed: false})","pinned":true,"hidden":false,"mode":"ojs"},{"id":187,"value":"### *Secondary data sources*","pinned":false,"hidden":false,"mode":"md"},{"id":69,"value":"// all vega data-sets\n\n// to 'extract' a dataset as an array (only for .csv and .json)\n// use this format: football = v_data['football.json']()\n// for some .csv, it's better to use the url format: zipcodes = v_data['zipcodes.csv'].url\n// this is due to the fact that parsing it as an array of objects results in zipcodes of the form \"00313\" turning into \"313\"\n\nv_data = require('vega-datasets@2')","pinned":false,"hidden":false,"mode":"ojs"},{"id":98,"value":"zips = d3.csv(v_data['zipcodes.csv'].url)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1099,"value":"zip_map = new Map(zips.map(d => [d.zip_code, d]))\n\n//broadband_access_2018 = new Map(us_broadband_2018.map(({id, broadband}) => [id, broadband]))","pinned":true,"hidden":false,"mode":"ojs"},{"id":159,"value":"us_holidays_2021 = USholidays.filter(d => op.utcyear(date_parser(d.date)) == 2021)","pinned":false,"hidden":false,"mode":"ojs"},{"id":193,"value":"### *Libraries*","pinned":false,"hidden":false,"mode":"md"},{"id":4,"value":"import {vl} from '@vega/vega-lite-api-v5'","pinned":false,"hidden":false,"mode":"ojs"},{"id":36,"value":"import {uniqueValid} from '@uwdata/data-utilities'","pinned":false,"hidden":false,"mode":"ojs"},{"id":59,"value":"import { aq, op } from '@uwdata/arquero'","pinned":false,"hidden":false,"mode":"ojs"},{"id":137,"value":"// object containing all of the FiPS us county codes\n\nimport {counties} from \"@d3/choropleth\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":391,"value":"// list of US Holidays\n\nimport {USholidays} from \"@observablehq/microsoft-reactor-hackathon\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":480,"value":"import {Legend, Swatches} from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":483,"value":"import {DuckDBClient} from \"@cmudig/duckdb\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":486,"value":"import { palettes } from '@makio135/give-me-colors'","pinned":false,"hidden":false,"mode":"ojs"},{"id":496,"value":"// this is a really cool way of displaying tables. Much more aesthetically pleasing than the defaults of arquero and input.table\n\nimport { formatTable } from \"@saneef/pretty-tables\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":514,"value":"import {textcolor} from \"@observablehq/text-color-annotations-in-markdown\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":519,"value":"import {viewof fileLog} from \"5b757a31fd4f7329\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":3440,"value":"import {toc} from \"@nebrius/indented-toc\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":456,"value":"md `### *Functions*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":409,"value":"date_parser = d3.utcParse('%m/%d/%Y')","pinned":true,"hidden":false,"mode":"ojs"},{"id":208,"value":"### *Chart configuration*","pinned":false,"hidden":false,"mode":"md"},{"id":1379,"value":"appcast_color_palette = ['#05062C', '#3138BB','#FF7D6F', '#AF9BFC', '#C7FFE2', '#127FFC', '#FF9B77', '#B7D8FE', '#DAE2FD', '#FAFAFA']","pinned":true,"hidden":false,"mode":"ojs"},{"id":202,"value":"clean_config = ({\n view: { stroke: null },\n axis: {\n gridOpacity: 0.5,\n labelFontWeight: 75,\n domain: false,\n offset: 5,\n titleFontWeight: 350,\n titleFontSize: 10\n },\n axisX: {\n tickCount: 5,\n titlePadding: 10,\n labelPadding: 4\n },\n axisY: {\n ticks: false,\n labelLimit: 300,\n labelFontSize: 7\n },\n title: {\n fontWeight: 300,\n fontSize: 13,\n offset: 25\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":632,"value":"// sample of how to place html blocks in a grid\n\n// html `

\n// ${viewof spend}\n// ${viewof cpl}\n// ${viewof cpc}\n//

`","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W39","stdlib":"1","titling":"auto"}