2f:T882,t_heat = vl.layer( // vl.markText() // .data(date_line) // .encode( // vl.x().fieldT('date'), // vl.text().value('bla') // ), vl.markRect({tooltip: true}) .title(metric_selector) .data(treatment) // .data(clean_test.filter(d => d.master_publisher_aggregated != 'Google Test CPC' && // d.master_publisher_aggregated != 'Birddog CPA' && // d.master_publisher_aggregated != 'Jobcase CPA' && // d.master_publisher_aggregated != 'Upward.net CPA' && // d.master_publisher_aggregated != 'Jobcase CPC' && // d.master_publisher_aggregated != 'ZipRecruiter CPA' && // d.spend > 0 // )) .encode( //vl.column().fieldN('master_publisher_aggregated').title(null).spacing(100), vl.x().fieldT('date') .timeUnit('utcyearmonthdate'), vl.y().fieldN('title').title(null) .sort(vl.median('LtoBGC').order('descending')), vl.color().if('datum.LtoBGC == 0', vl.value('#e6e6e6')).fieldQ(metric_selector) .scale({ scheme: d3.schemeBlues[5], type: 'quantize' }), vl.tooltip([ {field: 'title', type: 'nominal', title: 'Campaign'}, {field: 'date', type: 'temporal', title: 'Date', format: '%b-%d (%a)', scale: {type: 'utc'}}, {field: metric_selector, type: 'quantitative', title: metric_selector} ]) ), vl.markRule() .data(date_line) .encode( vl.x().fieldT('date') ), ) .config({ view: {step: 15, stroke: null}, rect: {height: {band: band}, width: {band: band}}, axis: {grid: null, domain: false, labelFontWeight: 200}, axisY: {tickBand: 'extent', ticks: false, labelPadding: 7.5, labelFontSize: 9}, axisX: {orient: 'top', title: null, tickCount: 'week'}, legend: {gradientThickness: 7.5,labelOverlap: 'greedy', offset: 50, labelFontWeight: 200, titleFontWeight: 50, orient: 'bottom'}, title: {offset: 10, fontWeight: 50}, rule: {stroke: 'firebrick', strokeWidth: 2} }) .padding({left: 25, bottom: 100, top: 25}) .width(width) .render()30:T904,vl.layer( // vl.markText() // .data(date_line) // .encode( // vl.x().fieldT('date'), // vl.text().value('bla') // ), vl.markRect({tooltip: true}) .title(metric_selector) .data(control_filtered_by_list_active.filter(d => d.LtoBGC <= 1)) // .data(control_filtered_top_k.filter(d => d.master_publisher_aggregated != 'Google Test CPC' && // d.master_publisher_aggregated != 'Birddog CPA' && // d.master_publisher_aggregated != 'Jobcase CPA' && // d.master_publisher_aggregated != 'Upward.net CPA' && // d.master_publisher_aggregated != 'Jobcase CPC' && // d.master_publisher_aggregated != 'ZipRecruiter CPA' && // d.spend > 0 // && // //d.date >= start_date && d.date <= end_date // )) .encode( //vl.column().fieldN('master_publisher_aggregated').title(null).spacing(100), vl.x().fieldT('date') .timeUnit('utcyearmonthdate'), vl.y().fieldN('title').title(null) .sort(vl.median('LtoBGC').order('descending')), vl.color().if('datum.LtoBGC == 0', vl.value('#e6e6e6')).fieldQ(metric_selector) .scale({ scheme: d3.schemeBlues[5], type: 'quantize' }), vl.tooltip([ {field: 'title', type: 'nominal', title: 'Campaign'}, {field: 'date', type: 'temporal', title: 'Date', format: '%b-%d (%a)', scale: {type: 'utc'}}, {field: metric_selector, type: 'quantitative', title: metric_selector} ]) ), vl.markRule() .data(date_line) .encode( vl.x().fieldT('date') ), ) .config({ view: {step: 15, stroke: null}, rect: {height: {band: band}, width: {band: band}}, axis: {grid: null, domain: false, labelFontWeight: 200}, axisY: {tickBand: 'extent', ticks: false, labelPadding: 7.5, labelFontSize: 9}, axisX: {orient: 'top', title: null, tickCount: 'week'}, legend: {gradientThickness: 7.5,labelOverlap: 'greedy', offset: 50, labelFontWeight: 200, titleFontWeight: 50, orient: 'bottom'}, title: {offset: 10, fontWeight: 50}, rule: {stroke: 'firebrick', strokeWidth: 2} }) .padding({left: 25, bottom: 100, top: 25}) .width(width) .render()31:[{"id":"38df538c027a5ed3d450d1fd23dd72396db7bcfe5e80fbab2583fb86b7822d9086b378c36fa9345736e4159a6292d4cb326666a2cbf028bed90019017378915f","href":"https://static.observableusercontent.com/files/38df538c027a5ed3d450d1fd23dd72396db7bcfe5e80fbab2583fb86b7822d9086b378c36fa9345736e4159a6292d4cb326666a2cbf028bed90019017378915f","name":"Lyft Repository - incentive test regions 1_19 (3).csv","type":"text/csv","lastModified":1674248557777.348,"size":541},{"id":"0ce16e5dbaa2382831e2f4e661ee2e2b478a9b0e1f2824443cd0e805dd0effe309ad243aed779420f140b396701b99488e58b4defd84cf7d11057ed76b384bc7","href":"https://static.observableusercontent.com/files/0ce16e5dbaa2382831e2f4e661ee2e2b478a9b0e1f2824443cd0e805dd0effe309ad243aed779420f140b396701b99488e58b4defd84cf7d11057ed76b384bc7","name":"Lyft Repository - Active Markets & Bids (1).csv","type":"text/csv","lastModified":1674248557777.348,"size":2987},{"id":"cd934859b3049257790a01b0520cb8358f0e3beaa1ab3bfe2992f72b43e20fe6fc6bcf222d2e9edc31144b5c4c9593fddc6d043e8cdd71d7588598a5b61dcab1","href":"https://static.observableusercontent.com/files/cd934859b3049257790a01b0520cb8358f0e3beaa1ab3bfe2992f72b43e20fe6fc6bcf222d2e9edc31144b5c4c9593fddc6d043e8cdd71d7588598a5b61dcab1","name":"sc2_control.csv","type":"text/csv","lastModified":1675097124311.793,"size":138},{"id":"82606904763fd4ee3c8390f89334fab70506b04df4f5a9036501b682fc043ef4bc3719a48eed61cf889a2cfac76e259a418472f27ed585e032a3fcdafdfd3269","href":"https://static.observableusercontent.com/files/82606904763fd4ee3c8390f89334fab70506b04df4f5a9036501b682fc043ef4bc3719a48eed61cf889a2cfac76e259a418472f27ed585e032a3fcdafdfd3269","name":"lyft-by_campaign-2023-01-30-2023-01-30.csv","type":"text/csv","lastModified":1675109408281.733,"size":37053}] 2d:{"title":"SC2 Incentive Test","cells":[{"id":0,"value":"md `# SC2 Incentive Test`","pinned":false,"hidden":false,"mode":"ojs"},{"id":742,"value":"md `The date today is ${formatter(new Date())}. The date 45 days ago was: **${formatter(forty_five_days_ago_today)}**\n

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1529,"value":"viewof file6 = Inputs.file({label: \"Load the .csv file\", required: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2141,"value":"md `

\n# *Slide 1*\n

\n
\n## Overall Summary`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2363,"value":"date_range_text = md `Date range for this data: **${formatter(date_range[0])}** to **${formatter(date_range[1])}**\n

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2212,"value":"summary_table_output = Inputs.table(summary_table, {\n layout: 'auto',\n format: {\n 'L to BGC CR': d3.format('.2%'),\n CPL: d3.format('$.2f'),\n CPBGC: d3.format('$.2f'),\n 'Total Spend' : d3.format('$,.2f'),\n },\n width: 900 \n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2545,"value":"md `
\n### Differences`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2564,"value":"md `*Control*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2575,"value":"difference_control_table_output = Inputs.table(differences_control, {\n layout: 'auto',\n format: {\n 'Spend Difference': d3.format('+$,.2f'),\n 'CPL Difference': d3.format('+$.2f'),\n 'BGC Difference': d3.format('+'),\n 'CPBGC Difference': d3.format('+$.2f'),\n 'L to BGC CR Difference': d3.format('+.2f'),\n 'Lead Difference': d3.format('+')\n }, \n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2568,"value":"md `*Treatment*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2592,"value":"difference_treatment_table_output = Inputs.table(differences_treatment, {\n layout: 'auto',\n format: {\n 'Spend Difference': d3.format('+$,.2f'),\n 'CPL Difference': d3.format('+$.2f'),\n 'CPBGC Difference': d3.format('+$.2f'),\n 'L to BGC CR Difference': d3.format('+.2f'),\n 'Lead Difference': d3.format('+'),\n 'BGC Difference': d3.format('+'),\n }, \n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1780,"value":"md `

\n# *Slide 2*\n

\n
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2621,"value":"md `## Treatment`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1737,"value":"t_line = vl.layer(\n \n vl.markLine()\n .data(daily_aggregate_treatement)\n .encode(\n vl.x().fieldT('date')\n .timeUnit('utcyearmonthdate')\n .title(null),\n vl.y().fieldQ('LtoBGC')\n .scale({\n domain: [0,1]\n }),\n vl.tooltip([\n {field: 'date', type: 'temporal', scale: {type: 'utc'}}\n ])\n ),\n\n vl.markRule()\n .data(date_line)\n .encode(\n vl.x().fieldT('date')\n .timeUnit('utcyearmonthdate')\n ),\n )\n .config({\n view: {stroke: null},\n axis: {grid: null, labelFontWeight: 200, titleFontWeight: 50},\n axisY: {domain: false, grid: true, gridOpacity: 0.5, titlePadding: 15},\n axisX: {format: '%B %d', tickCount: 'week'},\n line: {strokeWidth: 1, point: {stroke: 'white', size: 20}},\n rule: {stroke: 'firebrick', strokeWidth: 1, strokeDash: [8,3]}\n })\n .height(height)\n .width(width)\n .render()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1555,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs"},{"id":1784,"value":"md `## Control`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1792,"value":"vl.layer(\n \n vl.markLine()\n .data(daily_aggregate_control)\n .encode(\n vl.x().fieldT('date')\n .timeUnit('utcyearmonthdate')\n .title(null),\n vl.y().fieldQ('LtoBGC')\n .scale({\n domain: [0,1]\n }),\n vl.tooltip([\n {field: 'date', type: 'temporal', scale: {type: 'utc'}}\n ])\n ),\n\n vl.markRule()\n .data(date_line)\n .encode(\n vl.x().fieldT('date')\n .timeUnit('utcyearmonthdate')\n ),\n )\n .config({\n view: {stroke: null},\n axis: {grid: null, labelFontWeight: 200, titleFontWeight: 50},\n axisY: {domain: false, grid: true, gridOpacity: 0.5, titlePadding: 15},\n axisX: {format: '%B %d', tickCount: 'week'},\n line: {strokeWidth: 1, point: {stroke: 'white', size: 20}},\n rule: {stroke: 'firebrick', strokeWidth: 1, strokeDash: [8,3]}\n })\n .height(height)\n .width(width)\n .render()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1622,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":88,"value":"
\n
\n
\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":2333,"value":"md `## Control Panel`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1666,"value":"viewof band = Inputs.range([0, 1], {label: \"Amount\", step: 0.05, value: 0.85})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2290,"value":"viewof height = Inputs.range([0, 400], {label: \"height\", step: 10, value: 200})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2292,"value":"viewof width = Inputs.range([0, 1000], {label: \"width\", step: 10, value: 660})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2392,"value":"md `

\n### *Date range*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2374,"value":"md `The range for data should be: ${formatter(start_date)} to ${formatter(end_date)}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2377,"value":"// changed to 30 days based on sc2 feedback\nstart_date = d3.utcDay(d3.utcDay.offset(incentive_date, -30))","pinned":true,"hidden":false,"mode":"ojs"},{"id":2388,"value":"end_date = d3.utcDay(d3.utcDay.offset(incentive_date, 30))","pinned":true,"hidden":false,"mode":"ojs"},{"id":2379,"value":"days_from_incentive = d3.utcDay.count(incentive_date, new Date(now))","pinned":true,"hidden":false,"mode":"ojs"},{"id":1821,"value":"md `### Athena Query\n~~~sql\n\nselect date, sum(clicks) clicks, sum(spend) spend, sum(impressions) impressions, sum(applies_paid) leads, sum(qualified) bgc, sum(hired) activations, job_groups.title, job_boards.master_publisher_aggregated\nfrom jobdata\nleft join job_boards\non jobdata.job_board_id = job_boards.id\nleft join job_groups\non jobdata.job_group_id = job_groups.id\nwhere employer_id = 4972\nand date between cast('${date_as_string_formatter(start_date)}' as date) and cast('${date_as_string_formatter(end_date)}' as date)\ngroup by date, job_groups.title, job_boards.master_publisher_aggregated\norder by date\n\n~~~\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2279,"value":"md `### *Summaries*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2144,"value":"control_summary = aq.from(daily_aggregate_control)\n .derive({\n Segment: d => d.date < op.utcdatetime(2023,0,19) ? 'pre-incentive' : 'post-incentive'\n })\n .groupby('Segment')\n .rollup({\n 'Total Leads': d => op.sum(d.t_leads),\n //'Average (Median) L to BGC CR': d => op.median(d.LtoBGC), // decided to calculate it below instead of averaging\n 'CPL': d => op.sum(d.t_spend) / op.sum(d.t_leads),\n 'CPBGC': d => op.sum(d.t_spend) / op.sum(d.t_bgc),\n 'Total BGCs': d => op.sum(d.t_bgc),\n 'Total Spend': d => op.sum(d.t_spend)\n })\n .derive({\n 'L to BGC CR': d => d['Total BGCs'] / d['Total Leads']\n })\n .derive({Group: d => 'control'})\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2149,"value":"treatment_summary = aq.from(daily_aggregate_treatement)\n .derive({\n Segment: d => d.date < op.utcdatetime(2023,0,19) ? 'pre-incentive' : 'post-incentive'\n })\n .groupby('Segment')\n .rollup({\n 'Total Leads': d => op.sum(d.t_leads),\n //'Average (Median) L to BGC CR': d => op.median(d.LtoBGC), // decided to calculate it below instead of averaging\n 'CPL': d => op.sum(d.t_spend) / op.sum(d.t_leads),\n 'CPBGC': d => op.sum(d.t_spend) / op.sum(d.t_bgc),\n 'Total BGCs': d => op.sum(d.t_bgc),\n 'Total Spend': d => op.sum(d.t_spend)\n })\n .derive({\n 'L to BGC CR': d => d['Total BGCs'] / d['Total Leads']\n })\n .derive({Group: d => 'treatment'})\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2184,"value":"summary_table = aq.from(treatment_summary)\n .concat(aq.from(control_summary))\n .relocate('Group', {before: 'Segment'})\n .relocate(7, {before: 2})\n .relocate(7, {after: 3})\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2600,"value":"md `### Summary Differences`","pinned":true,"hidden":false,"mode":"ojs"},{"id":2539,"value":"differences_treatment = aq.from(treatment_summary)\n .derive({\n 'Spend Difference': d => d['Total Spend'] - op.lag(d['Total Spend'],1,NaN),\n 'Lead Difference': d => d['Total Leads'] - op.lag(d['Total Leads'],1, NaN),\n 'L to BGC CR Difference': d => (d['L to BGC CR'] - op.lag(d['L to BGC CR'],1, NaN)) * 100,\n 'CPL Difference': d => d.CPL - op.lag(d.CPL,1, NaN),\n 'CPBGC Difference': d => d.CPBGC - op.lag(d.CPBGC,1, NaN),\n 'BGC Difference': d => d['Total BGCs'] - op.lag(d['Total BGCs'],1, NaN)\n })\n .select(7,0,8,9,13,aq.range(10,12))\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2519,"value":"differences_control = aq.from(control_summary)\n .derive({\n 'Spend Difference': d => d['Total Spend'] - op.lag(d['Total Spend'],1,NaN),\n 'Lead Difference': d => d['Total Leads'] - op.lag(d['Total Leads'],1, NaN),\n 'L to BGC CR Difference': d => (d['L to BGC CR'] - op.lag(d['L to BGC CR'],1, NaN)) * 100,\n 'CPL Difference': d => d.CPL - op.lag(d.CPL,1, NaN),\n 'CPBGC Difference': d => d.CPBGC - op.lag(d.CPBGC,1, NaN),\n 'BGC Difference': d => d['Total BGCs'] - op.lag(d['Total BGCs'],1, NaN)\n })\n .select(7,0,8,9,13,aq.range(10,12))\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":198,"value":"## Treatment Data","pinned":false,"hidden":false,"mode":"md"},{"id":1896,"value":"md `### *Data wrangling, filters, etc*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1536,"value":"viewof incentive_date = Inputs.date({label: \"Date\", value: \"2023-01-19\", disabled: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1541,"value":"viewof toggle = Inputs.toggle({label: \"Filter by Test Markets\", value: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1561,"value":"viewof metric_selector = Inputs.radio(['leads','bgc','spend', 'CtoL','LtoBGC'], {label: \"Select one\", value: \"LtoBGC\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1523,"value":"test_market_list = test_market_list_raw\n .filter(d => d.Status == 'active')\n .map(d => d.region)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1531,"value":"raw_athena_data = file6.csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1539,"value":"my_data = { \n if (toggle == true){\n return raw_athena_data.filter(d => test_market_list.includes(d.title))}\n else {\n return raw_athena_data}\n }","pinned":true,"hidden":false,"mode":"ojs"},{"id":1534,"value":"viewof treatment = aq.from(my_data)\n .derive({\n CtoL: d => d.leads / d.clicks,\n LtoBGC: d => d.bgc / d.leads\n })\n .view()","pinned":true,"hidden":false,"mode":"ojs"},{"id":1716,"value":"date_line = [{date: incentive_date}]","pinned":true,"hidden":false,"mode":"ojs"},{"id":1752,"value":"daily_aggregate_treatement = treatment\n .groupby('date')\n .rollup({\n t_spend: d => op.sum(d.spend),\n t_clicks: d => op.sum(d.clicks),\n t_leads: d => op.sum(d.leads),\n t_bgc: d => op.sum(d.bgc),\n t_impressions: d => op.sum(d.impressions)\n })\n .derive({\n CtoL: d => d.t_leads / d.t_clicks,\n LtoBGC: d => d.t_bgc / d.t_leads\n })\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":1519,"value":"test_market_list_raw = FileAttachment(\"Lyft Repository - incentive test regions 1_19 (3).csv\").csv()","pinned":true,"hidden":false,"mode":"ojs"},{"id":1989,"value":"md `## Control data`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2673,"value":"control_market_list = control_market_list_raw.map(d => d['Control markets'])","pinned":true,"hidden":false,"mode":"ojs"},{"id":2667,"value":"control_market_list_raw = FileAttachment(\"sc2_control.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2108,"value":"viewof top_k_number = Inputs.range([0, 50], {label: \"top k\", step: 1, value: 20})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1619,"value":"control = \n//aq.from(raw_athena_data.filter(d => !test_market_list.includes(d.title))) // <-- All \"non-treatment markets\" (5607 arrays)\naq.from(raw_athena_data.filter(d => control_market_list.includes(d.title))) // <-- control list provided by POC\n .derive({\n cl: d => op.match(op.lower(d.title), /craigslist/g,0)\n })\n .filter(d => d.cl != 'craigslist')\n .filter(d => d.title != 'Min Bid' && d.title != 'All Other')\n .derive({\n CtoL: d => d.leads / d.clicks,\n LtoBGC: d => d.bgc / d.leads\n })\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2677,"value":"control_filtered_by_list = control.filter(d => control_market_list.includes(d.title))","pinned":true,"hidden":false,"mode":"ojs"},{"id":2692,"value":"control_filtered_by_list_active = control_filtered_by_list.filter(d => control_active.includes(d.title))","pinned":true,"hidden":false,"mode":"ojs"},{"id":1634,"value":"// what are the top k markets by lead count\ntop_k = aq.from(control)\n .groupby('title')\n .rollup({\n t_spend: d => op.sum(d.spend),\n t_leads: d => op.sum(d.leads),\n t_bgc: d => op.sum(d.bgc)\n })\n .orderby(aq.desc('t_bgc'))\n //.filter(aq.escape( d => op.rank() <= top_k_number ))\n .filter(d => op.rank() <= 20)\n .select('title')\n .reify()\n .array('title')","pinned":true,"hidden":false,"mode":"ojs"},{"id":1648,"value":"// filter the data by the top k\ncontrol_filtered_top_k = control.filter(d => top_k.includes(d.title))","pinned":true,"hidden":false,"mode":"ojs"},{"id":1788,"value":"daily_aggregate_control = aq.from(control)\n .groupby('date')\n .rollup({\n t_spend: d => op.sum(d.spend),\n t_clicks: d => op.sum(d.clicks),\n t_leads: d => op.sum(d.leads),\n t_bgc: d => op.sum(d.bgc),\n t_impressions: d => op.sum(d.impressions)\n })\n .derive({\n CtoL: d => d.t_leads / d.t_clicks,\n LtoBGC: d => d.t_bgc / d.t_leads\n })\n .objects()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2680,"value":"md `### *Control markets that are active*`","pinned":true,"hidden":false,"mode":"ojs"},{"id":2682,"value":"raw_campaigns = FileAttachment(\"lyft-by_campaign-2023-01-30-2023-01-30.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs"},{"id":2684,"value":"control_active = aq.from(raw_campaigns.filter(d => control_market_list.includes(d.Campaign)))\n .filter(d => d.Status == 'Active')\n .dedupe()\n .array('Campaign')","pinned":true,"hidden":false,"mode":"ojs"},{"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 = v_data['zipcodes.csv'].url","pinned":false,"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":609,"value":"md `### *Dates*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":612,"value":"date_range = d3.extent(raw_athena_data, d => d.date)","pinned":true,"hidden":false,"mode":"ojs"},{"id":616,"value":"forty_five_days_ago = d3.timeDay.offset(date_range[1], -45)","pinned":true,"hidden":false,"mode":"ojs"},{"id":745,"value":"forty_five_days_ago_today = d3.utcDay(d3.utcDay.offset(new Date(), -45))","pinned":true,"hidden":false,"mode":"ojs"},{"id":630,"value":"dateLine = [\n {date: forty_five_days_ago_today}, \n {week_num: op.week(forty_five_days_ago_today)}, \n {week_date: d3.utcWeek(forty_five_days_ago_today)},\n // {week_time_date: d3.timeWeek(forty_five_days_ago_today)},\n // {week_monday: d3.utcMonday(forty_five_days_ago_today)},\n // {test: d3.utcMonday(test_date)}\n ]","pinned":true,"hidden":false,"mode":"ojs"},{"id":1101,"value":"test_date = new Date('2022-10-31')","pinned":true,"hidden":false,"mode":"ojs"},{"id":1104,"value":"d3.utcWeek(test_date)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1106,"value":"d3.utcMonday(test_date)","pinned":true,"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":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":747,"value":"formatter = d3.utcFormat('%B %d, %Y')","pinned":true,"hidden":false,"mode":"ojs"},{"id":2397,"value":"date_as_string_formatter(incentive_date)","pinned":true,"hidden":false,"mode":"ojs"},{"id":2395,"value":"date_as_string_formatter = d3.utcFormat('%Y-%m-%d')","pinned":true,"hidden":false,"mode":"ojs"},{"id":208,"value":"### *Chart configuration*","pinned":false,"hidden":false,"mode":"md"},{"id":810,"value":"appcast_color_palette = ['#3138BB', '#FF7D6F', '#AF9BFC', '#C7FFE2', '#127FFC', '#FF9B77']","pinned":true,"hidden":false,"mode":"ojs"},{"id":202,"value":"clean_config = ({\n view: { \n stroke: null,\n step: 10\n },\n rect: {\n width: {band: 0.9},\n height: {band: 0.9}\n },\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"}],"files":"$W31","stdlib":"1","titling":"auto"}