2d:null 2e:["$","title",null,{"children":"Covid Charts : Italy | alastairorchard | Observable"}] 33:T454,viewof national_chart = vl.data(final_world_data .filter(d => +d["new_cases"] > 0) .filter(d => +d["new_deaths"] > 0) .filter(d => d.location === selectedCountry) ) .title(selectedCountry + " Daily Cases & Deaths") .layer( vl.markBar() .encode( vl.x().fieldT("date") .scale({domain: ["2020-02-01",Date()]}) .axis({grid: false, tickSize: 6, labelColor: '#929292' }), vl.y().sum("new_cases") .title("Daily Cases in Blue"), // vl.tooltip(['new_cases']) ), vl.markLine() .encode( vl.x().fieldT("date") .title(null), vl.y().sum("new_deaths") .title(null), vl.color({ value: 'darkred' }) ), vl.markArea({opacity: 0.3}) .encode( vl.x().fieldT("date") .title(null), vl.y().sum("new_deaths") .title("Daily Deaths in Red"), vl.color({ value: 'darkred' }) ) ) .width(width*0.85) .height(width*0.6) .resolve({scale:{y:'independent'}}) .render()34:T404,viewof ICU_chart_country = { if(icuItalyRegionalData .filter(d => d.country === selectedCountry).length > 0) { const brush = vl.selectInterval().encodings('x'); const x = vl.x().fieldT('date').title(null); const base = vl["mark" + curveType]() .encode( vl.x().fieldT("date") .scale({domain: ["2020-02-01",Date()]}) .axis({grid: false, tickSize: 6, labelColor: '#929292' }) .title(null), vl.y().mean("percentageBedsOccupied").scale({type: country_dist_type}) .title(null), ) .height(width*0.6) .width(width*0.9); return vl.data(icuItalyRegionalData .filter(d => d.country === selectedCountry && +d["percentageBedsOccupied"] > 0)) .title("Mean ICU Occupation by Country " + " (" + country_dist_type + " scale) - zoom using the lower chart") .vconcat( base.encode(x.scale({domain: brush})), base.select(brush).height(width*0.1).width(width*0.9) ) .render() } return "No ICU data available for this country" }35:T749,viewof mortality_chart = { if(mortalityCodes.filter(d => d.country == selectedCountry)[0] === undefined) { return "No regional data available for this country" } { var chart = vl.data(mortalityByCountry(selectedCountry).data2016.filter(d => d.Sex == mortalitySex) ) .title(selectedCountry + " Excess Mortality") .layer( vl.markLine() .encode( vl.x().fieldQ("Week") .axis({grid: false, tickSize: 6, labelColor: '#929292' }), vl.y().fieldQ(mortalityAge), vl.color({ value: 'grey' }) ), vl.markLine() .data(mortalityByCountry(selectedCountry).data2017.filter(d => d.Sex == mortalitySex)) .encode( vl.x().fieldQ("Week") .axis({grid: false, tickSize: 6, labelColor: '#929292' }), vl.y().fieldQ(mortalityAge), vl.color({ value: 'grey' }) ), vl.markLine() .data(mortalityByCountry(selectedCountry).data2018.filter(d => d.Sex == mortalitySex)) .encode( vl.x().fieldQ("Week") .axis({grid: false, tickSize: 6, labelColor: '#929292' }), vl.y().fieldQ(mortalityAge), vl.color({ value: 'grey' }) ), vl.markLine() .data(mortalityByCountry(selectedCountry).data2019.filter(d => d.Sex == mortalitySex)) .encode( vl.x().fieldQ("Week") .axis({grid: false, tickSize: 6, labelColor: '#929292' }), vl.y().fieldQ(mortalityAge), vl.color({ value: 'grey' }) ), vl.markLine() .data(mortalityByCountry(selectedCountry).data2020.filter(d => d.Sex == mortalitySex)) .encode( vl.x().fieldQ("Week") .axis({grid: false, tickSize: 6, labelColor: '#929292' }), vl.y().fieldQ(mortalityAge), vl.color({ value: 'red' }) ), vl.markRule({opacity:0.5, color:'green'}) .data(mortalityWeek) .encode( vl.x().fieldQ('current') ) ) .width(width*0.9) .height(width*0.6) .render() return chart } }36:T433,viewof ICU_chart = { if(icuItalyRegionalData .filter(d => d.country === selectedCountry).length > 0) { const brush = vl.selectInterval().encodings('x'); const x = vl.x().fieldT('date').title(null); const base = vl["mark" + curveType]() .encode( vl.x().fieldT("date") .scale({domain: ["2020-02-01",Date()]}) .axis({grid: false, tickSize: 6, labelColor: '#929292' }) .title(null), vl.y().fieldQ("percentageBedsOccupied").scale({type: country_dist_type}) .title(null), vl.color().fieldN("region"), vl.tooltip(['region']) ) .height(width*0.6) .width(width*0.8); return vl.data(icuItalyRegionalData .filter(d => d.country === selectedCountry && +d["percentageBedsOccupied"] > 0)) .title("ICU Occupation by Region " + " (" + country_dist_type + " scale) - zoom using the lower chart") .vconcat( base.encode(x.scale({domain: brush})), base.select(brush).height(width*0.1).width(width*0.8) ) .render() } return "No ICU data available for this country" }37:T4da,viewof regional_chart = { if(final_regional_data_global .filter(d => d.country === selectedCountry) .length === 0) { return "No regional data available for this country" } { var chart = vl.data(final_regional_data_global .filter(d => d.region === selectedRegion) .filter(d => +d["new_cases"] > 0) .filter(d => +d["new_deaths"] > 0) ) .title(selectedRegion + " Daily Cases & Deaths") .layer( vl.markBar() .encode( vl.x().fieldT("date") .scale({domain: ["2020-02-01",Date()]}) .axis({grid: false, tickSize: 6, labelColor: '#929292' }), vl.y().fieldQ("new_cases") .title(null), vl.tooltip(['new_cases']) ), vl.markLine() .encode( vl.x().fieldT("date") .title(null), vl.y().fieldQ("new_deaths") .title(null), vl.color({ value: 'darkRed' }) ), vl.markArea({opacity: 0.2}) .encode( vl.x().fieldT("date") .title(null), vl.y().fieldQ("new_deaths") .title(null), vl.color({ value: 'darkRed' }), vl.tooltip(['new_deaths']) ) ) .width(width*0.9) .height(width*0.6) .resolve({scale:{y:'independent'}}) .render() return chart } }38:T51e,andon = { var matrix = new Array; matrix = {Country: grouped_world_data.filter(d => d[0] == selectedCountry)[0][0], Latest_Cases: +(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1][(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1].length)-1].new_cases), Total_Cases: +(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1][(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1].length)-1].total_cases), Cases_per_1M: +(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1][(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1].length)-1].total_cases_per_million), Latest_Deaths: +(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1][(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1].length)-1].new_deaths), Total_Deaths: +(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1][(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1].length)-1].total_deaths), Deaths_per_1M: Math.ceil((grouped_world_data.filter(d => d[0] == selectedCountry)[0][1][(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1].length)-1].total_deaths_per_million)) } return matrix }39:[] 31:{"id":"6bcf3cc1a59d2634","slug":"covid-charts-italy","title":"Covid Charts : Italy","thumbnail":"e46e082fe75e0e674d421b8a2224e2a9ea71f40ec46da98c046199ccaf18056f","access_level":"public","create_time":"$D2020-10-29T07:07:39.783Z","update_time":"$D2020-11-16T08:35:35.558Z","view_time":null,"first_public_time":"$D2020-10-29T10:08:56.901Z","has_unpublished_edits":null,"fork":{"id":"3070e772c5e3eb4c","slug":"covid-charts","title":"Covid Charts","owner":{"id":"bcbd34b126c1c773","login":"alastairorchard","name":""}},"stars":0,"starred":false,"owner":{"type":"team","id":"bcbd34b126c1c773","login":"alastairorchard","name":"","avatar_url":"https://avatars-next.observableusercontent.com/323fd2061169ea2bd69b7ab108d92e1d575c6ee8e03abf6a96428e2dd691eef9","tier":"starter_2024"},"version":6470,"publish_version":6470,"role":null,"authored":false,"authors":[{"type":"individual","id":"4be011186b558e8a","login":"alastairorchard","name":"","avatar_url":"https://avatars-next.observableusercontent.com/323fd2061169ea2bd69b7ab108d92e1d575c6ee8e03abf6a96428e2dd691eef9","tier":null}],"members":[{"type":"individual","id":"4be011186b558e8a","login":"alastairorchard","name":"","avatar_url":"https://avatars-next.observableusercontent.com/323fd2061169ea2bd69b7ab108d92e1d575c6ee8e03abf6a96428e2dd691eef9","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"title":"Covid Charts : Italy","cells":[{"id":0,"value":"md`# Covid Charts : Italy`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":923,"value":"md`\nI'm building an automated notebook to replace an excel spreadsheet that is laborious to maintain, but it's become too large so I'm splitting it up. This fork looks specifically at [Italy](https://observablehq.com/@alastairorchard/covid-charts-italy) (where I live). Other views are available at the following links :`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5872,"value":"md`\n- [The original notebook](https://observablehq.com/@alastairorchard/covid-charts)\n- [Global](https://observablehq.com/@alastairorchard/covid-charts-global)\n- [Countries & Regions](https://observablehq.com/@alastairorchard/covid-charts-countries-regions)\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2123,"value":"md `Shout out to my bro @dunstan and his colleagues on the Observable team, as well as to all the talented folks from whom I imported code!`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5869,"value":"toc('h1, h2, h3, h4', 'Table of Contents')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6292,"value":"md`## Situation Chart`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5964,"value":"viewof table_size = radio({\n options: [\n { label: 'Compact', value: 'compact' },\n { label: 'Extended', value: 'extended' },\n ],\n value: 'compact',\n})\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5961,"value":"viewof dashboard = {\n if (table_size === \"compact\") {\n var tablet = table(compact_andon_ordered)\n}\n else\n{\n var tablet = table(andon_ordered)\n}\n return tablet\n }\n \n ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2933,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":937,"value":"md` Next I grab the output of a Jupyter notebook I use to calculate the realtime Rt values for each region. I'm trying to convert this to Observable, but it's pretty hard. I only have data for Italy, UK and US, and I update them every few days...`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1298,"value":"viewof mean_rt_chart \n \n = {\n if(final_rt_data_global.filter(d => d.country === selectedCountry).length > 0) {\n\nvar chart = vl.data(final_rt_data_global.filter(d => d.country === selectedCountry))\n .title(selectedCountry + \" Mean Rt\")\n\n.layer(\n\n vl.markLine({point:{filled: false,fill: \"white\"}}) \n\n .encode(\n vl.x().fieldT(\"date\")\n .axis({title: null})\n .axis({grid: false, tickSize: 6, labelColor: '#929292' }),\n vl.y().mean(\"Rt\")\n .axis({title: `Rt`})\n \n ),\n vl.markArea({opacity: 0.2}) \n .encode(\n vl.x().fieldT(\"date\")\n .axis({title: null}),\n vl.y().mean('Low_90'),\n vl.y2().mean('High_90')\n// .axis({title: `Rt`})\n ),\n\n vl.markRule({opacity:0.5, color:'green'})\n.data(rt_threshold)\n .encode(\n vl.y().fieldQ('threshold')\n )\n \n .width(width*0.9)\n .height(400)\n )\n .render()\nreturn chart\n }\nreturn \"No Rt data available for this country\"\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6066,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6367,"value":"tests_to_cases_ratio_chart = {\n const brush = vl.selectInterval().encodings('x');\n const x = vl.x().fieldT('date').title(null);\n \n const base = vl[\"mark\" + curveType]()\n.encode(\n vl.x().fieldT(\"date\")\n .scale({domain: [\"2020-02-01\",Date()]})\n .axis({grid: false, tickSize: 6, labelColor: '#929292' })\n .title(null),\n vl.y().fieldQ(\"new_ratio\")\n .title(null)\n )\n .height(width*0.6)\n .width(width*0.9);\n \n return vl.data(ratio_tests_to_cases.filter(d => +d[\"new_ratio\"] > 0))\n .title(\"Percentage of Tests Positive (linear scale) - zoom using the lower chart\")\n \n .vconcat(\n base.encode(x.scale({domain: brush})),\n base.select(brush).height(width*0.1).width(width*0.9)\n )\n .render()\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6361,"value":"cases_to_death_ratio_chart = {\n const brush = vl.selectInterval().encodings('x');\n const x = vl.x().fieldT('date').title(null);\n \n const base = vl[\"mark\" + curveType]()\n.encode(\n vl.x().fieldT(\"date\")\n .scale({domain: [\"2020-02-01\",Date()]})\n .axis({grid: false, tickSize: 6, labelColor: '#929292' })\n .title(null),\n vl.y().fieldQ(\"total_ratio\")\n .title(null)\n )\n .height(width*0.6)\n .width(width*0.9);\n \n return vl.data(ratio_deaths_to_cases.filter(d => +d[\"total_ratio\"] > 0))\n .title(\"Total % Mortality (linear scale) - zoom using the lower chart\")\n \n .vconcat(\n base.encode(x.scale({domain: brush})),\n base.select(brush).height(width*0.1).width(width*0.9)\n )\n .render()\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6150,"value":"md`## Excess Mortality`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6147,"value":"md `The red line indicates 2020 mortality of all types. The grey lines are 2016-19. Think that Covid is fake? Think that deaths are being wrongly attributed to Covid? This chart is the best way to see the effect of the pandemic on the overall mortality of a population`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6153,"value":"md`Choose between age range and sex to filter mortality rates`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6139,"value":"viewof mortalityAge = radio({\n options: [\n { label: '0-14', value: 'D0_14' },\n { label: '15-64', value: 'D15_64' },\n { label: '65-74', value: 'D65_74' },\n { label: '75-84', value: 'D75_84' },\n { label: '85+', value: 'D85p' },\n { label: 'All', value: 'DTotal' },\n ],\n value: 'DTotal',\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6142,"value":"viewof mortalitySex = radio({\n options: [\n { label: 'Male', value: 'm' },\n { label: 'Female', value: 'f' },\n { label: 'All', value: 'b' },\n ],\n value: 'b',\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6137,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6295,"value":"md`## Regional Analysis`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4624,"value":"viewof category = radio({\n title: 'Data Type',\n options: categories.map(c => ({\n label: c.title,\n value: c.key\n })),\n value: 'cases'\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4628,"value":"viewof dataKey = radio({\n title: 'Data View',\n // description: 'Please select your preferred contact method',\n options: dataSources\n .filter(c => c.category === category)\n .map(c => ({\n label: c.title,\n value: c.key\n })),\n value: `total_${category}`\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4250,"value":"viewof country_dist_type = radio({\n options: [\n { label: 'Linear', value: 'linear' },\n { label: 'Log', value: 'log' },\n ],\n value: 'linear',\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5337,"value":"viewof curveType = radio({\n options: [\n { label: 'Area', value: 'Area' },\n { label: 'Line', value: 'Line' },\n ],\n value: 'Line',\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6393,"value":"country_chart = {\n const brush = vl.selectInterval().encodings('x');\n const x = vl.x().fieldT('date').title(null);\n \n const base = vl[\"mark\" + curveType]()\n.encode(\n vl.x().fieldT(\"date\")\n .scale({domain: [\"2020-02-01\",Date()]})\n .axis({grid: false, tickSize: 6, labelColor: '#929292' })\n .title(null),\n vl.y().sum(dataKey).scale({type: country_dist_type})\n .title(null),\n vl.color().fieldN(\"location\"),\n vl.tooltip(['location'])\n )\n .height(width*0.6)\n .width(width*0.8);\n \n return vl.data(data_to_chart.filter(d => +d[dataKey] > 0 )) \n .title(dataKey + \" by Country \" + \" (\" + country_dist_type + \" scale) - zoom using the lower chart\")\n \n .vconcat(\n base.encode(x.scale({domain: brush})),\n base.select(brush).height(width*0.1).width(width*0.8)\n )\n .render()\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6411,"value":"viewof table_start = text({\n title: \"Filter Results from\",\n min: 1,\n max: andon.length - 2,\n step:1,\n value: 1\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6412,"value":"viewof table_end = text({\n title: \"...to\",\n // description: \"use these values to filter the data set\",\n value: 5,\n min: 1,\n max: andon.length - 1,\n step:1,\n value: 10\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6408,"value":"viewof region_dashboard = {\n if ((table_end - table_start) > 1) {\n if (region_table_size === \"compact\") {\n var tablet = table(compact_region_andon_ordered.slice(table_start-1,table_end))\n}\n else\n{\n var tablet = table(region_andon_ordered.slice(table_start-1,table_end))\n}\n return tablet\n }\n else\n {\n return \"invalid range\"\n }\n \n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6417,"value":"viewof region_table_size = radio({\n options: [\n { label: 'Compact', value: 'compact' },\n { label: 'Extended', value: 'extended' },\n ],\n value: 'compact',\n})\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6396,"value":"viewof manualList = text({\n title: \"Region List Manual Override\",\n value: \"\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4853,"value":"regions_chart = {\n const brush = vl.selectInterval().encodings('x');\n const x = vl.x().fieldT('date').title(null);\n \n const base = vl[\"mark\" + curveType]()\n.encode(\n vl.x().fieldT(\"date\")\n .scale({domain: [\"2020-02-01\",Date()]})\n .axis({grid: false, tickSize: 6, labelColor: '#929292' })\n .title(null),\n vl.y().sum(dataKey).scale({type: country_dist_type})\n .title(null),\n vl.color().fieldN(\"region\"),\n vl.tooltip(['region'])\n )\n .height(width*0.6)\n .width(width*0.8);\n \n return vl.data(regional_data_to_chart\n .filter(d => +d[dataKey] > 0))\n .title(dataKey + \" by Region \" + \" (\" + country_dist_type + \" scale) - zoom using the lower chart\")\n \n .vconcat(\n base.encode(x.scale({domain: brush})),\n base.select(brush).height(width*0.1).width(width*0.8)\n )\n .render()\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6289,"value":"md`## ICU Status`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6215,"value":"md`Number of ICU Beds Remaining`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6224,"value":"icuBedsRemaining","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6251,"value":"viewof ICU_status_chart = {\n\n var chart = vl.data(latestICUData)\n \n .title(selectedCountry + \" Regional ICU Status\")\n .layer(\n vl.markBar() \n .encode(\n vl.x().fieldN('region'),\n vl.y().fieldQ('percentageBedsOccupied'),\n\n ),\n vl.markRule({opacity:0.5, color:'red'})\n.data(ICU_threshold)\n .encode(\n vl.y().fieldQ('threshold')\n )\n )\n \n .width(width*0.9)\n .height(width*0.6)\n .render()\nreturn chart\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6278,"value":"viewof ICU_beds_chart = {\n\n var chart = vl.data(latestICUData)\n \n .title(selectedCountry + \" Regional ICU Beds\")\n .layer(\n vl.markBar() \n .encode(\n vl.x().fieldN('region'),\n vl.y().fieldQ('intensiveCare'),\n\n ),\n vl.markBar({opacity:0.3, color: 'green'}) \n .encode(\n vl.x().fieldN('region'),\n vl.y().fieldQ('bedsNow'),\n )\n )\n \n .width(width*0.9)\n .height(width*0.6)\n .render()\nreturn chart\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6164,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4437,"value":"viewof rt_chart = {\n if(final_rt_data_global.filter(d => d.country === selectedCountry).length > 0) {\n\nvar chart = vl.data(final_rt_data_global.filter(d => d.country === selectedCountry))\n\n .title(selectedCountry + \" Rt by Region\")\n .layer(\n\nvl.markLine({ opacity: 0.8 }) \n \n\n .encode(\n \n vl.x().fieldT(\"date\")\n// .scale({domain: [\"2020-07-01\",Date()]})\n .axis({grid: false, tickSize: 6, labelColor: '#929292' })\n .title(null),\n vl.y().fieldQ(\"Rt\")\n .axis({title: `Rt`}),\n vl.color().fieldN(\"region\"),\n vl.tooltip(['Rt', 'region'])\n \n ),\n\n vl.markRule({opacity:0.5, color:'green'})\n.data(rt_threshold)\n .encode(\n vl.y().fieldQ('threshold')\n )\n \n .width(width*0.75)\n .height(400)\n )\n .render()\nreturn chart\n }\nreturn \"No Rt data available for this country\"\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2982,"value":"md`I then split all the data into separate graphs for each region. You can change the scale using the radio buttons...`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2977,"value":"viewof region_scale_type = radio({\n title: 'Scale',\n options: [\n { label: 'Shared', value: 'shared' },\n { label: 'Independent', value: 'independent' },\n ],\n value: 'independent',\n})\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3136,"value":"viewof regional_chart_matrix = vl.markLine()\n .data(final_regional_data_global\n .filter(d => d.country === selectedCountry))\n.title(null)\n .encode(\n vl.x().fieldT(\"date\")\n .title(null),\n vl.y().fieldQ(vl.repeat(\"repeat\")),\n // .title(null),\n vl.color().fieldN(\"region\") \n .legend(null),\n \n vl.row().fieldN(\"region\")\n .title(null)\n\n )\n .width((width / 8)-10)\n .height(100)\n .resolve({\n axis: { x: 'independent' },\n scale: { y: region_scale_type }})\n .repeat([\"new_cases\", \"total_cases\", \"new_deaths\", \"total_deaths\"])\n .columns(4)\n .render()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6353,"value":"md`## Region Chart`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2963,"value":"md`We can show a specific graph for any region from the selected country`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3764,"value":"viewof selectedRegion = \n{\n if (final_regional_data_global.filter(d => d.country === selectedCountry).length === 0) {\n return select({options: [\"No Regions Available\"], value:\"No Regions Available\"})\n }\n else {\n return select({\n title: 'Select Region',\n options: Array.from(new Set((final_regional_data_global.filter(d => d.country === selectedCountry)).map(d => d.region))).sort(),\n placeholder: \"Search for a region . . .\",\n value: '',\n})\n }\n}\n\n ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3307,"value":"viewof regional_dash = {\nif (final_regional_data_global.filter(d => d.country === selectedCountry).length === 0) {\nreturn \"No regional data available for this country\"\n}\n\n var table = printTable(regional_KPIs, [\n {field: 'Region', title: 'Region'},\n {field: 'Total_Cases', title: 'Total Cases'},\n {field: 'Total_Deaths', title: 'Total Deaths'},\n])\n return table\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3728,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6070,"value":"ICU_chart_region = {\n const brush = vl.selectInterval().encodings('x');\n const x = vl.x().fieldT('date').title(null);\n \n const base = vl[\"mark\" + curveType]()\n.encode(\n vl.x().fieldT(\"date\")\n .scale({domain: [\"2020-02-01\",Date()]})\n .axis({grid: false, tickSize: 6, labelColor: '#929292' })\n .title(null),\n vl.y().fieldQ(\"percentageBedsOccupied\").scale({type: country_dist_type})\n .title(null),\n )\n .height(width*0.6)\n .width(width*0.9);\n \n return vl.data(icuItalyRegionalData\n .filter(d => d.country === selectedCountry && d.region === selectedRegion && +d[\"percentageBedsOccupied\"] > 0))\n .title(\"ICU Occupation \" + selectedRegion + \" (\" + country_dist_type + \" scale) - zoom using the lower chart\")\n \n .vconcat(\n base.encode(x.scale({domain: brush})),\n base.select(brush).height(width*0.1).width(width*0.9)\n )\n .render()\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3021,"value":" viewof regional_rt_chart = {\n if(final_rt_data_global.filter(d => d.country === selectedCountry).length === 0) {\n \n return \"No Rt data available for this region\" }\n {\nvar chart = vl.data(final_rt_data_global.filter(d => d.region === selectedRegion))\n .layer(\n \n vl.markLine({point:{filled: false,fill: \"white\"}}) \n .title(selectedRegion + \" Realtime Rt\")\n .encode(\n vl.x().fieldT(\"date\")\n .axis({title: null})\n .axis({grid: false, tickSize: 6, labelColor: '#929292' }),\n vl.y().fieldQ(\"Rt\")\n .axis({title: `Rt`})\n ),\n vl.markArea({opacity: 0.2}) \n .encode(\n vl.x().fieldT(\"date\")\n .axis({title: null}),\n vl.y().fieldQ('Low_90'),\n vl.y2().fieldQ('High_90')\n// .axis({title: `Rt`})\n ),\n\n vl.markRule({opacity:0.5, color:'green'})\n .data(rt_threshold)\n .encode(\n vl.y().fieldQ('threshold')\n )\n \n\n .width(width*0.9)\n .height(400)\n \n )\n .render()\nreturn chart\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5957,"value":"md`# Appendix`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1646,"value":"md`## Data Handling`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1650,"value":"md`Here is where I try to clean up the various csv files that I suck into the notebook from repositories around the net. First the source files :`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2137,"value":"regional_data_eu = d3.csv(\"https://raw.githubusercontent.com/ec-jrc/COVID-19/master/data-by-region/jrc-covid-19-all-days-by-regions.csv\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3536,"value":"world_data = d3.csv('https://covid.ourworldindata.org/data/owid-covid-data.csv')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1663,"value":"md`Then the filtered ones :`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2374,"value":"filtered_regional_data_eu = Array.from(d3.group(regional_data_eu, d => d.Region))\n .map(([, rows]) => process_data(rows)).flat()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2057,"value":"md`...and finalized :`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2376,"value":"final_regional_data_eu = filtered_regional_data_eu.filter(d => d.region !==\"NOT SPECIFIED\" && d.date > \"1973-01-01\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4421,"value":"rt_threshold = [{date: \"2020-02-01\", threshold: 1},{date: Date(), threshold: 1}]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3353,"value":"ratio_deaths_to_cases = {\n var matrix = new Array;\n for (var i = 0; i<(data_to_chart.length);i++)\n {\n matrix[i] = {location: data_to_chart[i].location,\n date: data_to_chart[i].date,\n region: data_to_chart[i].region,\n lat:data_to_chart[i].lat,\n long:data_to_chart[i].long,\n new_ratio: ((data_to_chart[i].new_deaths)/(data_to_chart[i].new_cases))*100,\n total_ratio: ((data_to_chart[i].total_deaths)/(data_to_chart[i].total_cases))*100\n }\n }\n return matrix\n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5190,"value":"ratio_tests_to_cases = {\n\n \n \n var matrix = new Array;\n for (var i = 0; i<(data_to_chart.length);i++)\n {\n if (data_to_chart[i].new_tests == 0) {\n var NR = NaN}\n else\n {\n var NR = ((data_to_chart[i].new_cases)/(data_to_chart[i].new_tests))*100\n }\n if (data_to_chart[i].total_tests == 0) {\n var TR = NaN}\n else\n {\n var TR = ((data_to_chart[i].total_cases)/(data_to_chart[i].total_tests))*100\n }\n matrix[i] = {location: data_to_chart[i].location,\n date: data_to_chart[i].date,\n region: data_to_chart[i].region,\n lat:data_to_chart[i].lat,\n long:data_to_chart[i].long,\n new_ratio: NR,\n total_ratio: TR\n }\n }\n return matrix\n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3303,"value":"regional_KPIs = \n[\n {Region: selectedRegion, Total_Cases: d3.sum(final_regional_data_global.filter(d => d.region === selectedRegion), d => d.new_cases), Total_Deaths: d3.sum(final_regional_data_global.filter(d => d.region === selectedRegion), d => d.new_deaths)\n }\n ]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3810,"value":"country_KPIs = \n[\n {Country: selectedCountry, Total_Cases: d3.sum(final_world_data.filter(d => d.location === selectedCountry), d => d.new_cases), Total_Deaths: d3.sum(final_world_data.filter(d => d.location === selectedCountry), d => d.new_deaths)\n }\n ]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1322,"value":"covid_heatmap = {\n var matrix = new Array;\n for (var i = 0; i<(final_regional_data_global.length);i++)\n {\n matrix[i] = [final_regional_data_global[i].lat, final_regional_data_global[i].long, final_regional_data_global[i].new_cases*0.1]}\n \n return matrix\n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2908,"value":"md`Finally, all the charts in the notebook point to these combined arrays :`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2318,"value":"final_regional_data_global = final_regional_data_eu","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3559,"value":"final_world_data = world_data.filter(d => d.date > \"2020-02-01\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4035,"value":"grouped_world_data = Array.from(d3.group(final_world_data, d => d.location))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4783,"value":"md`## Dashboard`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6040,"value":"import {andon_ordered} with {andon} from '@alastairorchard/covid-charts'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6045,"value":"import {compact_andon_ordered} with {compact_andon} from '@alastairorchard/covid-charts'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6427,"value":"grouped_regional_data = Array.from(d3.group((final_regional_data_global.filter(c => c.country === selectedCountry)), d => d.region))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6002,"value":"$38","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6048,"value":"compact_andon = {\n var matrix = new Array;\n matrix = {Region: grouped_world_data.filter(d => d[0] == selectedCountry)[0][0],\n Total_Cases: +(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1][(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1].length)-1].total_cases),\n Total_Deaths: +(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1][(grouped_world_data.filter(d => d[0] == selectedCountry)[0][1].length)-1].total_deaths)\n \n }\n return matrix\n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6424,"value":"compact_region_andon = {\n var matrix = new Array;\n for (var i = 0; i d.Region)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6401,"value":"region_list = {\n if(manualList.length === 0) {\nreturn andon_region_list}\n {\n return d3.csvParse(manualList).columns}\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4168,"value":"data_to_chart = {\n var matrix = new Array;\n var k = 0;\n for (var i = 0; i {\n const output = data.map((d, i) => ({\n country: d.CountryName,\n date: d.Date,\n region: d.Region,\n lat: d.lat,\n long: d.lon,\n new_cases: Math.max(d.CumulativePositive - (data[i - 1] ? data[i - 1].CumulativePositive : 0), 0),\n total_cases: d.CumulativePositive,\n new_deaths: Math.max(d.CumulativeDeceased - (data[i - 1] ? data[i - 1].CumulativeDeceased : 0), 0),\n total_deaths: d.CumulativeDeceased,\n }));\n\n// Object.assign(output, data[0], {\n \n ['Date', 'CumulativePositive', 'CumulativeDeceased'].forEach(key => delete output[key]);\n\n return output;\n};","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2750,"value":"firstBy = thenBy.firstBy","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2747,"value":"thenBy = require('https://bundle.run/thenby@1.3.4')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6,"value":"d3 = require(\"d3@5\", \"d3-array@2\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":12,"value":"//import { vl } from \"@vega/vega-lite-api\"\nvl = {\n const [vega, vegalite, api, tooltip] = await Promise.all([\n 'vega@5.15',\n 'vega-lite@4.13.1',\n 'vega-lite-api@0.12.0',\n 'vega-tooltip@0.23.2'\n ].map(module => require(module)));\n\n const options = {\n config: {\n // vega-lite default configuration\n config: {\n view: {continuousWidth: 400, continuousHeight: 300},\n mark: {tooltip: null}\n }\n },\n init: view => {\n // initialize tooltip handler\n view.tooltip(new tooltip.Handler().call);\n // enable horizontal scrolling for large plots\n if (view.container()) view.container().style['overflow-x'] = 'auto';\n },\n view: {\n // view constructor options\n loader: vega.loader({baseURL: 'https://cdn.jsdelivr.net/npm/vega-datasets@1/'}),\n renderer: 'canvas'\n }\n };\n \n return api.register(vega, vegalite, options);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":10,"value":"md`## Imports`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4657,"value":"import {dataSources, categories} from '@unkleho/covid-19-bubble-chart-with-d3-render'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4369,"value":"import {table, defaultHumanize} from '@awendland/fancy-table'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":50,"value":"import {filter, filteri} from \"@mbostock/manipulating-flat-arrays\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":59,"value":"import {take} from \"@mbostock/manipulating-flat-arrays\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":61,"value":"import {taker} from \"@mbostock/manipulating-flat-arrays\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":575,"value":"import {thumbnail} from \"@observablehq/vega-lite-chart-types\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":701,"value":"import { radio, select, autoSelect, worldMapCoordinates, slider, text } from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2629,"value":"import {printTable} from '@uwdata/data-utilities'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4283,"value":"import {rangeSlider} from '@mootari/range-slider'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1316,"value":"L = {\n const L = await require('leaflet');\n if (!L._css) {\n document.head.appendChild(L._css = html`\n \n \n `);\n }\n await require('leaflet.markercluster@1.4.1').catch(() => L.markerClusterGroup);\n await require('leaflet.heat').catch(() => L.heatLayer);\n return L;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1434,"value":"leafletCSS = html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5867,"value":"import {toc} from \"@tomshanley/indented-toc\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W39","stdlib":"1","titling":"auto"}} 32:"$31:body"