31:T4b9,chart_desc = vegalite({ data: {values: data_agg.map(d => d.value)}, hconcat: [{ mark: "bar", height: 3/4 * width/5, encoding: { x: {field: "Recruitment status", type: "ordinal", sort: {op: "count", field: "Recruitment status", order: "descending"}}, y: {aggregate: "count", field: "*", type: "quantitative"}, //color: {field: "Recruitment status", type: "nominal"} } },{ mark: "bar", height: 3/4 * width/5, encoding: { x: {field: "Study design", type: "ordinal", sort: {op: "count", field: "Study design", order: "descending"}}, y: {aggregate: "count", field: "*", type: "quantitative"} } }, { mark: "bar", width: width/5, height: 3/4 * width/5, encoding: { x: {field: "Center", type: "ordinal", sort: {op: "count", field: "Center", order: "descending"}}, y: {aggregate: "count", field: "*", type: "quantitative"} } }, { mark: "bar", width: width/5, height: 3/4 * width/5, encoding: { x: {field: "registration_code", type: "ordinal", sort: {op: "count", field: "registration_code", order: "descending"}}, y: {aggregate: "count", field: "*", type: "quantitative"} } }] })32:T4c2,generate_research_evolution_treatment_type = (title, filter) => { const brush = vl.selectInterval().encodings('x'); // limit selection to x-axis (year) values const data_recent = data .filter(d => new Date(d["Registration date"]) > new Date("2019")) .filter(filter); // dynamic query histogram const years = vl .markBar({ width: 4, title: "Test" }) .data(data_recent) .select(brush) .encode( vl.x().fieldT("Registration date"), vl .y() .count() .title(null) ) .width(width - 200) .height(50); // ratings scatter plot const ratings = vl .markBar() .data(data_recent) .transform(vl.filter(brush)) .encode( vl .y() .fieldN("Severity scale") .scale({ domain: data_agg_severity.map(d => d.key).sort() }), vl .x() .fieldN("Treatment type") .scale({ domain: data_agg_treatment1.map(d => d.key).sort() }), vl .color() .count() .title('Number of arms'), vl.tooltip(["Treatment type"]) ) .width(width - 200); return vl .vconcat(years, ratings) .spacing(15) .title({ text: title }) .render(); }33:Ta52,chart_research_evolution_sample_size = { const data_filtered = data .filter(d => new Date(d["Registration date"]) > new Date("2019")) .filter( d => evolution_sample_size_study_aim === 'All' || d['Study aim'] === evolution_sample_size_study_aim ) .filter( d => evolution_sample_size_pharmalogical_filter === 'All' || d['Pharmacological treatment'] === evolution_sample_size_pharmalogical_filter ) .filter( d => evolution_sample_size_severity_filter.length === 0 || evolution_sample_size_severity_filter.includes(d['Severity scale']) ) .filter( d => evolution_sample_size_country_filter === 'All' || d['Countries'] === evolution_sample_size_country_filter ) .slice() .map(d => { if (d['Severity scale'] === 'N/A') d['Severity scale'] = -1; return d; }); const list_treatments = [ ...new Set(data_filtered.map(d => d['Treatment name'])) ]; const sample_size_min = Math.min( ...data_filtered.map(d => Number(d['n randomized in this arm'])) ); const sample_size_max = Math.max( ...data_filtered.map(d => Number(d['n randomized in this arm'])) ); return vegalite({ title: 'Research evolution for each treatment with sample size', data: { values: data_filtered }, mark: { type: "circle" }, width, height: Math.max(list_treatments.length * 20, 500), autosize: "fit", encoding: { x: { field: "Registration date", type: "temporal" }, y: { field: "Treatment name", type: "nominal" }, color: { field: "Severity scale", type: "quantitative", scale: { range: ['green', 'blue'] } }, // size: {aggregate: "count", type: "quantitative", legend: {title: "In Selected Category"}}, size: { field: "n randomized in this arm", type: "quantitative", scale: { type: 'log' }, legend: { title: "n randomized in this arm" } }, tooltip: [ { field: "Trial registration number", type: "nominal" }, { field: "First author", type: "nominal" }, { field: "Countries", type: "nominal" }, { field: "Number of arms", type: "nominal" }, { field: "Registration date", type: "temporal" }, { field: "Treatment name", type: "nominal" }, { field: "Treatment type", type: "nominal" }, { field: "Severity scale", type: "quantitative" }, { field: "n randomized in this arm", type: "quantitative" }, { field: "Total sample size", type: "quantitative" } ] } }); }34:[{"id":"8012d06a275ebc090fd7feaa77d63d5ba77ffae95b6fc4642879878b07113d843c9744eeaf453d3edf5ba6a2588a68049434ee60f25f5d1be60dfbc6680a95dd","href":"https://static.observableusercontent.com/files/8012d06a275ebc090fd7feaa77d63d5ba77ffae95b6fc4642879878b07113d843c9744eeaf453d3edf5ba6a2588a68049434ee60f25f5d1be60dfbc6680a95dd","name":"Database 080420 visualization.csv","type":"text/csv","lastModified":1586550838239.144,"size":1254623},{"id":"3735fbe41967928d40c7cd139d8bc05aeb15f99affb970356829fefcb31ce25569e62e115e33ac2909228dc0cbc6a829c6068e735a1f4eda45658bb4786ff3b0","href":"https://static.observableusercontent.com/files/3735fbe41967928d40c7cd139d8bc05aeb15f99affb970356829fefcb31ce25569e62e115e33ac2909228dc0cbc6a829c6068e735a1f4eda45658bb4786ff3b0","name":"Database 080420.csv","type":"text/csv","lastModified":1586459720367.645,"size":1486233},{"id":"895506bb061bdb5504e28dadadcc8c5d2b30d7e104f1ba534a1701b4a67b3bb55f72f6a509c30b7a94952d0886e5c3394c1bc937949d8b8ebabb8bdbf9179240","href":"https://static.observableusercontent.com/files/895506bb061bdb5504e28dadadcc8c5d2b30d7e104f1ba534a1701b4a67b3bb55f72f6a509c30b7a94952d0886e5c3394c1bc937949d8b8ebabb8bdbf9179240","name":"Database 080420_140420.csv","type":"text/csv","lastModified":1586933820108.885,"size":1266895}] 2f:{"title":"Visualizing the Network Meta-Analysis of Covid-19 Studies","cells":[{"id":0,"value":"md`# Visualizing the Network Meta-Analysis of Covid-19 Studies\n\n\n\nDATASET FROM https://covid-nma.com/\n\nCONTRIBUTORS (Visualizations)\n\n- Romain Vuillemot - LIRIS, École Centrale de Lyon - [@romsson](https://twitter.com/romsson)\n- Philippe Rivière - LIRIS, VisionsCarto - [@recifs](https://twitter.com/recifs)\n- Pierre Ripoll - LIRIS, INSA Lyon- [@ripoll](https://twitter.com/pierreripoll)\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":725,"value":"md`Here we provide a description of studies registered in ICTRP as of April 9, 2020.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":172,"value":"html`Currently, there are ${data_agg.length} randomized controlled trials registered with ${data_agg.filter(d => (d.value[\"Recruitment status\"] === \"Recruiting\")).length} trials recruiting patients. Most of trials are being conducted in Asia (${bycontinent.get(\"Asia\")} trials) with the majority from China (${data_agg.filter(d => (d.value[\"Countries\"] == \"China\")).length} trials). Other countries in Europe (${bycontinent.get(\"Europe\")} trials) and North America (${bycontinent.get(\"North America\")} trials) are rapidly setting up new trials with the majority being conducted in multiple centers (${data_agg.filter(d => (d.value[\"Center\"] == \"multi-center\")).length} trials).`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1270,"value":"viewof textFilter","pinned":false,"hidden":false,"mode":"ojs"},{"id":747,"value":"d3.select(map).attr(\"width\", 800).attr(\"height\", 600).node()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1269,"value":"viewof recruitmentFilter","pinned":false,"hidden":false,"mode":"ojs"},{"id":1268,"value":"viewof zoomType","pinned":false,"hidden":false,"mode":"ojs"},{"id":952,"value":"// TODO: group by regions as a stacked chart\n// TODO: need to split countries..\nchart_countries = vegalite({\n data: {values: data_agg.map(d => d.value)},\n mark: \"bar\",\n encoding: {\n x: {field: \"Countries\", type: \"ordinal\", sort: {op: \"count\", field: \"Countries\", order: \"descending\"}},\n y: {aggregate: \"count\", field: \"*\", type: \"quantitative\", title: \"Number of studies\"},\n// color: {field: \"Countries\", type: \"nominal\"}\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":974,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":469,"value":"// Filtering out the 2015 study\nchart_date = vegalite({\n data: {\n values: data.filter(\n d => new Date(d[\"Registration date\"]) > new Date(\"2019\")\n )\n },\n mark: \"bar\",\n width: width * .9,\n height: 50,\n encoding: {\n y: {\n aggregate: \"count\",\n field: \"*\",\n type: \"quantitative\",\n title: \"# studies\"\n },\n x: { field: \"Registration date\", type: \"temporal\" }\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1083,"value":"// \"First author\"\nchart_authors = vegalite({\n title: {text: \"Top PIs\"},\n data: {values: data_agg_authors.filter(d => d.value > 0)},\n transform: [\n //{aggregate: [{op: \"count\", field: \"First author\", field: \"First author\", as: \"b3\"}]},\n //{filter: \"datum.b3>0\"}\n ],\n mark: \"bar\",\n encoding: {\n x: {field: \"key\", type: \"ordinal\", sort: {field: \"value\", order: \"descending\"}, title: \"\"},\n y: {field: \"value\", type: \"quantitative\", title: \"\"},\n //color: {field: \"Recruitment status\", type: \"nominal\"}\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1087,"value":"// \"First author\"\nchart_studies = vegalite({\n title: { text: \"# Studies by Funding\" },\n data: { values: data_agg.map(d => d.value) },\n transform: [\n //{aggregate: [{op: \"count\", field: \"First author\", field: \"First author\", as: \"b3\"}]},\n //{filter: \"datum.b3>0\"}\n ],\n width: 800,\n mark: \"bar\",\n encoding: {\n x: {\n field: \"Funding\",\n as: \"b1\",\n type: \"ordinal\",\n sort: { op: \"count\", field: \"First author\", order: \"descending\" }\n },\n y: {\n aggregate: \"count\",\n as: \"b2\",\n field: \"*\",\n type: \"quantitative\",\n title: \"# Studies by Funding\"\n }\n //color: {field: \"Recruitment status\", type: \"nominal\"}\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1097,"value":"chart_treatment = vegalite({\n data: {values: data.map(d => d)},\n mark: \"bar\",\n encoding: {\n x: {field: \"Treatment type\", type: \"ordinal\", sort: \"ascending\", sort: {op: \"count\", field: \"Treatment type\", order: \"descending\"}},\n y: {aggregate: \"count\", field: \"*\", type: \"quantitative\", title: \"Top Treatments\"},\n// color: {field: \"Treatment type1\", type: \"nominal\"}\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1338,"value":"md`## Research evolution during time for treatment types`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1104,"value":"//chart_treatment_by_severity_prevention = generate_research_evolution_treatment_type(\n// \"Research evolution for treatment types : prevention\",\n// d => d[\"Study aim\"] === \"Prevention\"\n//)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1336,"value":"// Treatments are at the arm level but in this case we are interested in the number of studies\n// TODO: keep labels instead of numbers\n// TODO: keep at the study level\n// Keep order of type of treatments as given\n// They will update based on treatment based on severity (e.g. protective not relevant in high severity)\nchart_treatment_by_severity_treatment = generate_research_evolution_treatment_type(\n \"Research evolution for treatment types : treatment\",\n d => {\n return (\n (pharmalogical_filter_treatment_evolution_time === 'All' ||\n d['Pharmacological treatment'] ===\n pharmalogical_filter_treatment_evolution_time) &&\n d[\"Study aim\"] === \"Treatment\"\n );\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1335,"value":"// TODO remove standard of care and Placebo as only 1 category\nviewof pharmalogical_filter_treatment_evolution_time = {\n var data = all_co_xy\n .filter(d => d.aim === \"Treatment\")\n .map(d => d.pharmalogical_type);\n return radio({\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1334,"value":"// No more relevant as \n//chart_treatment_by_severity_post = generate_research_evolution_treatment_type(\n// \"Research evolution for treatment types : post treatment\",\n// d => d[\"Study aim\"] === \"Post treatment\"\n//)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1333,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1325,"value":"md`## Mapping of treatments comparisons`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1324,"value":"// TODO: only keep treatment name \n// TODO: matric: prevention: treatmeent name\n// TODO: Mapping of treatment comparisons: treatment type (remettre l'option dessous)\nviewof treatment_field = {\n return radio({\n title: \"Choose treatment field for mapping\",\n value: \"Treatment type\",\n options: [\"Treatment type\", \"Treatment name\"]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1110,"value":"map_treatment_comparison_type_prevention = {\n return generate_mapping_treatment_comparisons(\n \"Mapping of treatment comparisons : prevention\",\n d => {\n return (\n (pharmalogical_filter_prevention === 'All' ||\n d.pharmalogical_type === pharmalogical_filter_prevention) &&\n (patient_filter_prevention === 'All' ||\n d.patient === patient_filter_prevention) &&\n (country_filter_prevention === 'All' ||\n d.countries === country_filter_prevention) &&\n d.aim === \"Prevention\"\n );\n }\n );\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1322,"value":"viewof pharmalogical_filter_prevention = {\n var data = all_co_xy\n .filter(d => d.aim === \"Prevention\")\n .map(d => d.pharmalogical_type);\n return radio({\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1321,"value":"viewof patient_filter_prevention = {\n var data = all_co_xy.filter(d => d.aim === \"Prevention\").map(d => d.patient);\n return radio({\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1320,"value":"viewof country_filter_prevention = {\n var data = all_co_xy\n .filter(d => d.aim === \"Prevention\")\n .map(d => d.countries);\n return select({\n description: \"Country\",\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1319,"value":"map_treatment_comparison_type_treatment = {\n return generate_mapping_treatment_comparisons(\n \"Mapping of treatment comparisons : treatment\",\n d => {\n return (\n (pharmalogical_filter_treatment === 'All' ||\n d.pharmalogical_type === pharmalogical_filter_treatment) &&\n (patient_filter_treatment === 'All' ||\n d.patient === patient_filter_treatment) &&\n (country_filter_treatment === 'All' ||\n d.countries === country_filter_treatment) &&\n d.aim === \"Treatment\"\n );\n }\n );\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1318,"value":"viewof pharmalogical_filter_treatment = {\n var data = all_co_xy\n .filter(d => d.aim === \"Treatment\")\n .map(d => d.pharmalogical_type);\n return radio({\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1317,"value":"viewof patient_filter_treatment = {\n var data = all_co_xy.filter(d => d.aim === \"Treatment\").map(d => d.patient);\n return radio({\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1316,"value":"viewof country_filter_treatment = {\n var data = all_co_xy.filter(d => d.aim === \"Treatment\").map(d => d.countries);\n return select({\n description: \"Country\",\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1315,"value":"map_treatment_comparison_type_post = {\n return generate_mapping_treatment_comparisons(\n \"Mapping of treatment comparisons : post treatment\",\n d => {\n return (\n (pharmalogical_filter_post === 'All' ||\n d.pharmalogical_type === pharmalogical_filter_post) &&\n (patient_filter_post === 'All' || d.patient === patient_filter_post) &&\n (country_filter_treatment === 'All' ||\n d.countries === country_filter_post) &&\n d.aim === \"Post treatment\"\n );\n }\n );\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1314,"value":"viewof pharmalogical_filter_post = {\n var data = all_co_xy\n .filter(d => d.aim === \"Post treatment\")\n .map(d => d.pharmalogical_type);\n return radio({\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1313,"value":"viewof patient_filter_post = {\n var data = all_co_xy\n .filter(d => d.aim === \"Post treatment\")\n .map(d => d.patient);\n return radio({\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1312,"value":"viewof country_filter_post = {\n var data = all_co_xy\n .filter(d => d.aim === \"Post treatment\")\n .map(d => d.countries);\n return select({\n description: \"Country\",\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1311,"value":"all_co_xy = get_all_co_xy(treatment_field)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1310,"value":"data_agg_field = get_data_agg_field(treatment_field)","pinned":false,"hidden":false,"mode":"ojs"},{"id":591,"value":"get_all_co_xy = field =>\n data_agg\n .map(function(d, i) {\n return d.value.values.map(function(e, j) {\n return d.value.values.map(function(f, k) {\n if (e[field] !== f[field]) {\n return [\n {\n x: e[field],\n y: f[field],\n s: f[\"Severity scale\"],\n aim: f[\"Study aim\"],\n countries: f[\"Countries\"],\n patient: f['Type of patients'],\n pharmalogical_type: f['Pharmacological treatment']\n },\n {\n x: f[field],\n y: e[field],\n s: f[\"Severity scale\"],\n aim: f[\"Study aim\"],\n countries: f[\"Countries\"],\n patient: f['Type of patients'],\n pharmalogical_type: f['Pharmacological treatment']\n }\n ];\n } else {\n return [];\n }\n });\n });\n })\n .flat(Infinity)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1307,"value":"generate_mapping_treatment_comparisons = (title, filter) => {\n return vegalite(\n {\n title: title,\n data: {\n values: all_co_xy.filter(filter)\n },\n mark: \"rect\",\n width: 600,\n height: 500,\n encoding: {\n x: {\n field: \"y\",\n type: \"nominal\",\n scale:\n treatment_field === \"Treatment type\"\n ? { domain: data_agg_field.map(d => d.key) }\n : undefined\n },\n y: {\n field: \"x\",\n type: \"nominal\",\n scale:\n treatment_field === \"Treatment type\"\n ? { domain: data_agg_field.map(d => d.key) }\n : undefined\n },\n color: {\n aggregate: \"count\",\n type: \"quantitative\",\n title: \"Number of trials\"\n }\n }\n },\n { renderer: 'svg' }\n );\n //}\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1044,"value":"data_agg_authors = d3.nest().key(function(d) { return d[\"First author\"]; }).rollup(function(values) { return values.length }).entries(data_agg.map(d => d.value))","pinned":true,"hidden":false,"mode":"ojs"},{"id":1123,"value":"data_agg_severity = d3\n .nest()\n .key(function(d) {\n return d[\"Severity\"];\n })\n .rollup(function(values) {\n return values.length;\n })\n .entries(data_agg.map(d => d.value))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1330,"value":"data_agg","pinned":true,"hidden":false,"mode":"ojs"},{"id":1140,"value":"data_agg_treatment1 = get_data_agg_field(\"Treatment type\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":1302,"value":"get_data_agg_field = field => {\n return d3\n .nest()\n .key(function(d) {\n return d[field];\n })\n .rollup(function(values) {\n return values.length;\n })\n .entries(data);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1143,"value":"data_agg_treatment1","pinned":true,"hidden":false,"mode":"ojs"},{"id":35,"value":"html`

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":221,"value":"data_agg.map(d => d.value.values)","pinned":true,"hidden":false,"mode":"ojs"},{"id":39,"value":"html`

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1346,"value":"md`## Research evolution with sample size`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1345,"value":"viewof evolution_sample_size_study_aim = {\n var data = all_co_xy.map(d => d.aim);\n return radio({\n title: \"Research question\",\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1344,"value":"viewof evolution_sample_size_pharmalogical_filter = {\n var data = all_co_xy.map(d => d.pharmalogical_type);\n return radio({\n title: \"Pharmacological treatment\",\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1343,"value":"viewof evolution_sample_size_severity_filter = {\n var data = data_agg_severity.map(d => d.key).sort();\n return checkbox({\n title: \"Severity\",\n options: [...new Set(data)],\n description: 'If none is selected filter is not used'\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1342,"value":"viewof evolution_sample_size_country_filter = {\n var data = all_co_xy.filter(d => d.aim === \"Treatment\").map(d => d.countries);\n return select({\n title: \"Country\",\n value: \"All\",\n options: [\"All\", ...new Set(data)]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1341,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":779,"value":"import {vl} from '@vega/vega-lite-api'","pinned":true,"hidden":false,"mode":"ojs"},{"id":783,"value":"data","pinned":true,"hidden":false,"mode":"ojs"},{"id":921,"value":"data_agg","pinned":true,"hidden":false,"mode":"ojs"},{"id":505,"value":"data_agg.map(function(d, i) { return d.value.values.map(e => e[\"Treatment type\"]) })","pinned":true,"hidden":false,"mode":"ojs"},{"id":47,"value":"html`

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\n`","pinned":true,"hidden":false,"mode":"ojs"},{"id":49,"value":"html`

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\n`","pinned":true,"hidden":false,"mode":"ojs"},{"id":53,"value":"html`

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\n`","pinned":true,"hidden":false,"mode":"ojs"},{"id":61,"value":"html`

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`","pinned":true,"hidden":false,"mode":"ojs"},{"id":63,"value":"html`

\n
\n`","pinned":true,"hidden":false,"mode":"ojs"},{"id":8,"value":"d3 = require(\"d3@5\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":24,"value":"vegalite = require(\"@observablehq/vega-lite@0.2\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":445,"value":"data = d3.csvParse(await FileAttachment(\"Database 080420_140420.csv\").text())","pinned":true,"hidden":false,"mode":"ojs"},{"id":449,"value":"data_agg = d3.nest().key(function(d) { return d[\"Trial ID\"]; }).rollup(function(values) { \n return {values: values, \n \"Recruitment status\": values[0][\"Recruitment status\"],\n \"Countries\": values[0][\"Countries\"],\n \"Center\": values[0][\"Center\"],\n \"First author\": values[0][\"First author\"],\n \"Publication date online\": values[0][\"Publication date online\"],\n \"Trial registration number\": values[0][\"Trial registration number\"],\n \"Funding\": values[0][\"Funding\"],\n \"Severity\": values[0][\"Severity scale\"],\n \"Study design\": values[0][\"Study design\"],\n \"registration_code\": values[0][\"Trial registration number\"].slice(0, 3)\n } \n}).entries(data);","pinned":true,"hidden":false,"mode":"ojs"},{"id":452,"value":"Treatment_type1 = new Set(data.map(d => d[\"Treatment type\"]))","pinned":true,"hidden":false,"mode":"ojs"},{"id":529,"value":"Treatment_type1_list = Array.from(Treatment_type1)","pinned":true,"hidden":false,"mode":"ojs"},{"id":517,"value":"Array.from(Treatment_type1).map(d => 0)","pinned":true,"hidden":false,"mode":"ojs"},{"id":533,"value":" import {\n extractSets,\n UpSet,\n generateIntersections\n } from '@sgratzl/upset-observable-library'","pinned":false,"hidden":false,"mode":"ojs"},{"id":569,"value":"md`Using [UpSets](https://observablehq.com/@sgratzl/upset-observable-example?collection=@sgratzl/upset-visualization-technique) to visualize co-occurences`","pinned":true,"hidden":false,"mode":"ojs"},{"id":540,"value":"all_co_binary = data_agg.map(function(d, i) { \n let a = Array.from(Treatment_type1).map(d => 0)\n d.value.values.forEach(function(e) {\n i = Treatment_type1_list.indexOf(e[\"Treatment type1\"])\n a[i] = 1\n })\n return a\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":548,"value":"// EXPERIMENTAL \n// Only with a dataset otherwise too many intersections\n// We need to reduce the number of categories\nall_co_data = data_agg.filter((d, i) => i < 30).map(function(d, i) { \n let sets = []\n d.value.values.forEach(function(e) {\n // if(e[\"Treatment type1\"] != \"*\")\n sets.push(e[\"Treatment type1\"])\n })\n let a = {}\n a[\"name\"] = d.value[\"Trial registration number\"]\n a[\"Trial registration number\"] = d.value[\"Trial registration number\"]\n a[\"First author\"] = d.value[\"First author\"]\n a[\"Publication date online\"] = d.value[\"Publication date online\"]\n a[\"sets\"] = sets\n return a\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":559,"value":"sets = extractSets(all_co_data)","pinned":true,"hidden":false,"mode":"ojs"},{"id":565,"value":"intersections = generateIntersections(sets).sort(\n (a, b) => b.cardinality - a.cardinality\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":801,"value":"intersections","pinned":true,"hidden":false,"mode":"ojs"},{"id":567,"value":"viewof selection = UpSet(sets, intersections)","pinned":true,"hidden":false,"mode":"ojs"},{"id":681,"value":"printTable(selection ? selection.elems.map(d => d): \"\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":654,"value":"selection","pinned":true,"hidden":false,"mode":"ojs"},{"id":1023,"value":"bycontinent = new Map(d3.nest().key(d => d).rollup(v => v.length).entries(Array.from(countriesIndex).map(d => Array.from(new Set(d[1].map(d => continents.get(d))))).flat()).map(d => [d.key, d.value]))","pinned":true,"hidden":false,"mode":"ojs"},{"id":1277,"value":"md`## Imports`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1276,"value":"html`\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1275,"value":"import {\n checkbox,\n slider,\n button,\n text,\n select,\n autoSelect,\n radio\n} from \"@jashkenas/inputs\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":670,"value":"import {printTable} from '@uwdata/data-utilities'","pinned":true,"hidden":false,"mode":"ojs"},{"id":989,"value":"// https://observablehq.com/d/3c709ffbafcdb388\nimport {\n map,\n viewof textFilter,\n viewof recruitmentFilter,\n viewof zoomType,\n countriesIndex,\n continents\n} from \"3c709ffbafcdb388\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":739,"value":"md`Other Viz\n\nhttps://observablehq.com/d/8215857ffae42ded\n\n`","pinned":true,"hidden":false,"mode":"ojs"},{"id":949,"value":"stackedBar = vl.markBar()\n .data(data_agg.map(d => d.value))\n .encode(\n vl.x().fieldO(\"Countries\"),//.timeUnit(\"utcmonth\"),\n vl.y().count(), // .stack(\"normalize\").axis({ format: \"%\" }),\n vl.color().fieldN(\"continent\") // .scale({ range: weatherColors })\n )\n .render()","pinned":true,"hidden":false,"mode":"ojs"},{"id":1018,"value":"// Without Date filter\nchart_date_strip = embed({\n data: {values: data},\n mark: \"tick\",\n width: width/2,\n encoding: {\n x: {field: \"Registration date\", type: \"temporal\"}\n }\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":1171,"value":"embed = require(\"vega-embed@6\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":1157,"value":"vegalite({\n data: {values: data.filter(d => (new Date(d[\"Registration date\"]) > new Date(\"2019\")) )},\n mark: \"area\",\n width: width/2,\n encoding: {\n y: {aggregate: \"count\", field: \"Treatment type1\", type: \"quantitative\"},\n x: {field: \"Registration date\", type: \"temporal\"},\n color: {field: \"Treatment type\", \"type\":\"nominal\", \"scale\":{\"scheme\": \"category20b\"}}\n },\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":1078,"value":"md`OLD CHARTS`","pinned":true,"hidden":false,"mode":"ojs"},{"id":1081,"value":"html`

`","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W34","stdlib":"1","titling":"auto"}