31:T10e5,conversations_count_heatmap_chart_gen = { let data = conversations_count_array; const id = 'conversations_count_heatmap_chart'; // set the dimensions and margins of the graph const margin = {top: 24, right: 0, bottom: 20, left: 135}, heatmap_width = (width*0.5) - margin.left - margin.right, //width declared outside of this block of code heatmap_height = 700 - margin.top - margin.bottom; // append the svg object to the body of the page d3.select("#" + id).html(''); let svg = d3.select("#" + id) .append("svg") .attr("width", heatmap_width + margin.left + margin.right) .attr("height", heatmap_height + margin.top + margin.bottom) .append("g") .attr("transform", "translate(" + margin.left + "," + margin.top + ")"); // Labels of row and columns -> unique identifier of the column called 'group' and 'variable' let myGroups = Array.from(new Set(data.map(d => d.group))) let myVars = Array.from(new Set(data.map(d => d.variable))) let myValues = Array.from(new Set(data.map(d => d.value))); // Build X scales and axis: let x = d3.scaleBand() .range([ 0, heatmap_width/2 ]) .domain(myGroups) .padding(0.05); svg.append("g") .style("font-size", 15) .attr("transform", "translate(0," + heatmap_height + ")") .call(d3.axisBottom(x).tickSize(0)) .select(".domain").remove() // Build Y scales and axis: let y = d3.scaleBand() .range([ heatmap_height, 0 ]) .domain(myVars) .padding(0.05); svg.append("g") .style("font-size", 15) .call(d3.axisLeft(y).tickSize(0)) .select(".domain").remove() // Build color scale let myColor = d3.scaleSequential() .interpolator(d3.interpolateGreens) //https://github.com/d3/d3-scale-chromatic .domain([d3.min(myValues),d3.max(myValues)]) // Three function that change the tooltip when user hover / move / leave a cell let mouseover = function(d) { //tooltip // .style("opacity", 1) let this_class = d3.select(this).attr("class") d3.selectAll("."+ this_class) //d3.select(this) .style("stroke", "black") .style("opacity", 1) console.log('mouseover', this_class); } let mousemove = function(d) { } let mouseleave = function(d) { //tooltip // .style("opacity", 0) let this_class = d3.select(this).attr("class") d3.selectAll("."+ this_class) //d3.select(this) .style("stroke", "none") .style("opacity", 0.8); console.log('mouseleave', this_class); } // add the squares svg.selectAll() .data(data, function(d) {return d.group+':'+d.variable;}) .enter() .append("rect") .attr("class", function(d) {return d.variable.split(":")[0].replaceAll('&', '').replaceAll(' ', '_')}) .attr("x", function(d) { return x(d.group) }) .attr("y", function(d) { return y(d.variable) }) .attr("rx", 4) .attr("ry", 4) .attr("width", x.bandwidth()< min_cell_width? min_cell_width: x.bandwidth() ) .attr("height", y.bandwidth() ) .style("fill", function(d) { return d.value == ''||0?'none': myColor(d.value) } ) .style("stroke-width", 4) .style("stroke", "none") .style("opacity", 0.8) .on("mouseover", mouseover) .on("mousemove", mousemove) .on("mouseleave", mouseleave) let valuesTextStroke = svg.selectAll(".valuesTextStroke") .data(data) .enter() .append("text") .attr("x", function(d) { return x(d.group) + (x.bandwidth()< min_cell_width? min_cell_width: x.bandwidth())/2.5 }) .attr("y", function(d) { return y(d.variable) + (y.bandwidth()/1.3) }) .attr("width", x.bandwidth()< min_cell_width? min_cell_width: x.bandwidth() ) .attr("height", y.bandwidth() ) .text(d => d.value ) .attr("fill", "none") .attr("stroke", "white") .attr("stroke-width", 2); let valuesText = svg.selectAll(".valuesText") .data(data) .enter() .append("text") .attr("x", function(d) { return x(d.group) + (x.bandwidth()< min_cell_width? min_cell_width: x.bandwidth())/2.5 }) .attr("y", function(d) { return y(d.variable) + (y.bandwidth()/1.3) }) .attr("width", x.bandwidth()< min_cell_width? min_cell_width: x.bandwidth() ) .attr("height", y.bandwidth() ) .text(d => d.value ) return svg; }32:T10e4,conversations_sentiment_heatmap_chart_gen = { let data = conversations_sentiment_array; const id = 'conversations_sentiment_heatmap_chart'; // set the dimensions and margins of the graph const margin = {top: 24, right: 0, bottom: 20, left: 135}, heatmap_width = (width*0.5) - margin.left - margin.right, //width declared outside of this block of code heatmap_height = 700 - margin.top - margin.bottom; // append the svg object to the body of the page d3.select("#" + id).html(''); let svg = d3.select("#" + id) .append("svg") .attr("width", heatmap_width + margin.left + margin.right) .attr("height", heatmap_height + margin.top + margin.bottom) .append("g") .attr("transform", "translate(" + margin.left + "," + margin.top + ")"); // Labels of row and columns -> unique identifier of the column called 'group' and 'variable' let myGroups = Array.from(new Set(data.map(d => d.group))) let myVars = Array.from(new Set(data.map(d => d.variable))) let myValues = Array.from(new Set(data.map(d => d.value))); // Build X scales and axis: let x = d3.scaleBand() .range([ 0, heatmap_width/2 ]) .domain(myGroups) .padding(0.05); svg.append("g") .style("font-size", 15) .attr("transform", "translate(0," + heatmap_height + ")") .call(d3.axisBottom(x).tickSize(0)) .select(".domain").remove() // Build Y scales and axis: let y = d3.scaleBand() .range([ heatmap_height, 0 ]) .domain(myVars) .padding(0.05); svg.append("g") .style("font-size", 15) .call(d3.axisLeft(y).tickSize(0)) .select(".domain").remove() // Build color scale let myColor = d3.scaleSequential() .interpolator(d3.interpolateRdYlGn) //https://github.com/d3/d3-scale-chromatic .domain([d3.min(myValues),d3.max(myValues)]) // Three function that change the tooltip when user hover / move / leave a cell let mouseover = function(d) { //tooltip // .style("opacity", 1) let this_class = d3.select(this).attr("class") d3.selectAll("." + this_class) //d3.select(this) .style("stroke", "black") .style("opacity", 1); console.log('mouseover',this_class); } let mousemove = function(d) { } let mouseleave = function(d) { //tooltip // .style("opacity", 0) let this_class = d3.select(this).attr("class") d3.selectAll("." + this_class) //d3.select(this) .style("stroke", "none") .style("opacity", 0.8) console.log('mouseleave',this_class); } // add the squares svg.selectAll() .data(data, function(d) {return d.group+':'+d.variable;}) .enter() .append("rect") .attr("class", function(d) {return d.variable.split(":")[0].replaceAll('&', '').replaceAll(' ', '_')}) .attr("x", function(d) { return x(d.group) }) .attr("y", function(d) { return y(d.variable)}) .attr("rx", 4) .attr("ry", 4) .attr("width", x.bandwidth()< min_cell_width? min_cell_width: x.bandwidth() ) .attr("height", y.bandwidth() ) .style("fill", function(d) { return d.value == ''||0?'none': myColor(d.value) } ) .style("stroke-width", 4) .style("stroke", "none") .style("opacity", 0.8) .on("mouseover", mouseover) .on("mousemove", mousemove) .on("mouseleave", mouseleave) let valuesTextStroke = svg.selectAll(".valuesTextStroke") .data(data) .enter() .append("text") .attr("x", function(d) { return x(d.group) + (x.bandwidth()< min_cell_width? min_cell_width: x.bandwidth())/2.5 }) .attr("y", function(d) { return y(d.variable) + (y.bandwidth()/1.3) }) .attr("width", x.bandwidth()< min_cell_width? min_cell_width: x.bandwidth() ) .attr("height", y.bandwidth() ) .text(d => d.value ) .attr("fill", "none") .attr("stroke", "white") .attr("stroke-width", 2); let valuesText = svg.selectAll(".valuesText") .data(data) .enter() .append("text") .attr("x", function(d) { return x(d.group) + (x.bandwidth()< min_cell_width? min_cell_width: x.bandwidth())/2.5 }) .attr("y", function(d) { return y(d.variable) + (y.bandwidth()/1.3) }) .attr("width", x.bandwidth()< min_cell_width? min_cell_width: x.bandwidth() ) .attr("height", y.bandwidth() ) .text(d => d.value ) return svg; }33:T490,conversations_sentiment_array = { const conversation_sentiments = d3.rollup(main_file.filter( el => ['first post','max reply time exceed','not reply'].indexOf(el['previous sender']) == -1 ), v => v.reduce(function(arr, elem) { return arr.concat(elem); }, []), d => `${d['previous sender']}-${d['sender']}` ); const conversations = Array.from(conversation_sentiments.keys()).map(function(e){ let two_way_concat_array = conversation_sentiments.get(e.split("-")[0] + '-' + e.split("-")[1]).concat( conversation_sentiments.get(e.split("-")[1] + '-' + e.split("-")[0])) let pair = e.split("-").sort().join(" & ") return {pair:pair, arr: two_way_concat_array } }) .filter(e => e.arr.length >= 50) .map(e => `${e.pair}|${d3.mean(e.arr.map(d => d['Google sentiment product'])).toFixed(2)}`); const output = Array.from(new Set(conversations)).map(e => ({group:'conversation sentiment', variable: e.split("|")[0], value: Number(e.split("|")[1]) })).sort((a,b) => a.value - b.value).map(function(e,i){ let permutations = new Set(conversations).size e.variable += `: ${permutations - (i)}`; return e; }) return output; }34:T1682,engagement_o_meter_chart_gen = { const gaugeOptions = { chart: { type: 'solidgauge', height: 200 }, title: null, pane: { center: ['50%', '85%'], size: '140%', startAngle: -90, endAngle: 90, background: { backgroundColor: Highcharts.defaultOptions.legend.backgroundColor || '#EEE', innerRadius: '60%', outerRadius: '100%', shape: 'arc' } }, exporting: { enabled: false }, tooltip: { enabled: false }, // the value axis yAxis: { stops: [ [0.1, '#DF5353'], // red [0.5, '#DDDF0D'], // yellow [0.9, '#55BF3B'] // green ], lineWidth: 0, tickWidth: 0, minorTickInterval: null, tickAmount: 2, title: { y: -70 }, labels: { y: 16 } }, plotOptions: { solidgauge: { dataLabels: { y: 5, borderWidth: 0, useHTML: true } } } }; // The speed gauge let chart_originator_sentiment = new Highcharts.chart('engagement_o_meter_originator_sentiment_chart', Highcharts.merge(gaugeOptions, { yAxis: { min: engagement_o_meter_object['originator_sentiment_avg']['range'][0], max: engagement_o_meter_object['originator_sentiment_avg']['range'][1], title: { text: 'Originator Sentiment' } }, credits: { enabled: false }, series: [{ name: 'Originator Sentiment', data: [engagement_o_meter_object['originator_sentiment_avg']['value']], dataLabels: { format: '

' + '{y:,.2f}
' + 'score' + '

' }, tooltip: { valueSuffix: ' sentiment score' } }] })); // The speed gauge let chart_sentiment = new Highcharts.chart('engagement_o_meter_sentiment_chart', Highcharts.merge(gaugeOptions, { yAxis: { min: engagement_o_meter_object['sentiment_avg']['range'][0], max: engagement_o_meter_object['sentiment_avg']['range'][1], title: { text: 'Follow-up Sentiment' } }, credits: { enabled: false }, series: [{ name: 'Follow-up Sentiment', data: [engagement_o_meter_object['sentiment_avg']['value']], dataLabels: { format: '

' + '{y:,.2f}
' + 'score' + '

' }, tooltip: { valueSuffix: ' sentiment score' } }] })); let chart_people = new Highcharts.chart('engagement_o_people_chart', { chart: { type: 'column', height: 200 }, legend: { enabled: false }, title: { text: null }, credits: { enabled: false }, xAxis: { labels: { enabled: false } }, yAxis: { max: engagement_o_meter_object['people_engaged_avg']['range'][1], title: { text: 'Avg other members engaged' }, gridLineWidth:0, lineWidth: 0, minorGridLineWidth: 0, labels: { enabled: false } }, plotOptions: { column: { colorByPoint: true }, series: { dataLabels: { enabled: true } } }, tooltip:{ enabled: false }, /* sentiment_avg: 0.01259807847194903 people_engaged_avg: 2.7723880597014925 post_count_avg: 9.389925373134329*/ series: [ { name: 'Avg other members engaged', data:[{ //x: 'Members', y: Number(engagement_o_meter_object['people_engaged_avg']['value']), color: Highcharts.getOptions().colors[0] }], dataLabels: { format: '{y:,.1f}
' + 'people' } } ] }); let chart_posts = new Highcharts.chart('engagement_o_posts_chart', { chart: { type: 'column', height: 200 }, legend: { enabled: false }, title: { text: null }, credits: { enabled: false }, xAxis: { labels: { enabled: false } }, yAxis: { max: engagement_o_meter_object['post_count_avg']['range'][1], title: { text: 'Avg posts from other members' }, gridLineWidth:0, lineWidth: 0, minorGridLineWidth: 0, labels: { enabled: false } }, plotOptions: { column: { colorByPoint: true }, series: { dataLabels: { enabled: true } } }, tooltip:{ enabled: false }, /* sentiment_avg: 0.01259807847194903 people_engaged_avg: 2.7723880597014925 post_count_avg: 9.389925373134329*/ series: [ { name: 'Avg posts from other members', data:[{ //x: 'Posts', y: Number(engagement_o_meter_object['post_count_avg']['value']), color: Highcharts.getOptions().colors[0] }], dataLabels: { format: '

' + '{y:,.1f}
' + 'posts' + '

' } } ] }); } 35:T4c6,function get_stage1_aggregates(main_file, fullyFilteredData, hours, category_indexes_object = false){ let bisect = d3.bisector(d => d['timestamp']); let stage1_output = fullyFilteredData.map(function(e,i){ //get engagement aggregates of all posts in date-range let categories = false; if(category_indexes_object){ categories = getCategory(e['index'], category_indexes_object); if (categories){ categories.forEach(category => e[category] = true) } } let sender = e['sender']; let slice_end = bisect.right(main_file, (e['timestamp'] + hours*60*60*1000)); let follow_up_posts = main_file.slice(main_file.findIndex((element) => element['index'] == e['index']), slice_end).filter(d => d['sender'] != e['sender']); let stage_one_agg = d3.rollups( follow_up_posts, function(v){ return { originator: e, sentiment_avg1: d3.mean(v, d => Number(d['Google sentiment product'])), people_engaged_avg1: new Set(d3.map(v, d => d['sender'])).size, post_count_1: v.length } }) return stage_one_agg; }); return stage1_output; }36:Tb14,function stage2_aggregates(stage1_output, originator_sentiment_avg_value = false){ let output; if(originator_sentiment_avg_value){ output = d3.rollups(stage1_output, function(v){ //single category view: roll-up the stage 1 filtered aggregates let post_sum = d3.sum(v, d => d['post_count_1']); let sentiment_avg_value = d3.sum(v,d => d['sentiment_avg1']*(d['post_count_1']/post_sum)); let people_engaged_avg_value = d3.mean(v, d => d['people_engaged_avg1']); let post_count_avg_value = d3.mean(v, d => d['post_count_1']); return { originator_post_count: v.length, originator_sentiment_avg: {value: originator_sentiment_avg_value, range:[-0.4, 0.4]}, sentiment_avg: {value: undefined_to_zero(sentiment_avg_value), range:[-0.4, 0.4]}, //weighted avg people_engaged_avg: {value: undefined_to_zero(people_engaged_avg_value), range:[0, members_by_post_volume_array.length]}, post_count_avg: {value: undefined_to_zero(post_count_avg_value), range:[0, 25]} } }) } if(!originator_sentiment_avg_value){ let obj = {}; members_by_post_volume_array.forEach(function(member){ obj[member] = {}; Array.from( Object.keys(exploded_file_top10_category_indexes) ).forEach(function(category){ obj[member][category] = {}; years_array.forEach(function(year){ obj[member][category][year] = d3.rollups(stage1_output .filter( e => (e['originator'][category] == true) && (e['originator']['sender'] == member) && (new Date (e['originator']['timestamp']).getFullYear() == year) ), function(v){ //multi category view (follow-up data only): roll-up the stage 1 filtered aggregates let post_sum = d3.sum(v, d => d['post_count_1']); let sentiment_avg_value = d3.sum(v,d => d['sentiment_avg1']*(d['post_count_1']/post_sum)); let people_engaged_avg_value = d3.mean(v, d => d['people_engaged_avg1']); let post_count_avg_value = d3.mean(v, d => d['post_count_1']); return { sentiment_avg: undefined_to_zero(sentiment_avg_value), //weighted avg people_engaged_avg: undefined_to_zero(people_engaged_avg_value), post_count_avg: undefined_to_zero(post_count_avg_value) } }); }); }); }); output = obj; } return output; }37:T562,function get_follow_on_aggregates(main_file, fullyFilteredData, hours, category_indexes_object = false, sender_category_year_volume_array = false){ let stage1_output = get_stage1_aggregates(main_file, fullyFilteredData, hours, category_indexes_object) let originator_sentiment_avg_value = d3.rollup(fullyFilteredData, v => d3.mean(v, d => Number(d['Google sentiment product']))); let output; if(sender_category_year_volume_array){ let stage2_output = stage2_aggregates(stage1_output); output = sender_category_year_volume_array.map(function(entry){ return { sender: entry[0], category: entry[1], volume: entry[2],//years_array.map(function(e){ return mapYearEntry(e, entry[2]) }), //test: stage2_output, followOnPosts: entry[2].map(e => [ e[0], undefined_to_zero(stage2_output[entry[0]][entry[1]][e[0]]['post_count_avg']) ] ), followOnMembers: entry[2].map(e => [ e[0], undefined_to_zero(stage2_output[entry[0]][entry[1]][e[0]]['people_engaged_avg']) ] ) } }); } if(!sender_category_year_volume_array){ output = stage2_aggregates(stage1_output, originator_sentiment_avg_value) } return output; }38:[] 2f:{"title":"Part 5 - Conversations and Influence","cells":[{"id":0,"value":"md `# Part 5 - Conversations and Influence`\n\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":604,"value":"md `Conversations are here defined as two successive posts one after another. Note this does not take into account people replying to specific posts in the past.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":264,"value":"conversations_count_heatmap_chart = html `

Which are the most frequent, positive / negative conversations?

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":223,"value":"md `### Infectious Vibes: A case for going back to our roots! Or gameifying book club\n

There are two topics that have positive originator sentiment and an even more positive sentiment in 2 hours of follow-up posts from others: Games and Sports. That somewhat justifies starting a sports bookclub!

Topics like News & Politics, Business, Finance are cases where negativity begets negativity, especially with News & Politics.

Henni is the only person to have a negative originator sentiment and a positive sentiment in 2 hours of follow-up posts from others. These trends are particulary pronounced with his Arts & Entertainments, People & Society, Sports, Games and Travel posts - quite possibly this is an indicator of his style of houmour.

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":51,"value":"engagement_o_meter_inputs = html `\n

${viewof senders_copy2_input}

${viewof engagement_category_input}

\n\n`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":133,"value":"html `

Given the
${engagement_o_meter_origin_posts}
posts by ${senders_copy2_input}, on topic: '${engagement_category_input}'. Here is the engagement of other members in the next 2 hours:

`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"engagement_o_meter_chart = html `\n

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":226,"value":"md `### Appendix - Code: Conversation count / sentiment heatmaps`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":636,"value":"min_cell_width = 100","pinned":false,"hidden":false,"mode":"ojs"},{"id":232,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":231,"value":"conversations_count_array = {\n const conversation_counts = d3.rollup(main_file.filter( el => ['first post','max reply time exceed','not reply'].indexOf(el['previous sender']) == -1 ), v => v.length, d => `${d['previous sender']}-${d['sender']}` );\n\n \n const conversations = Array.from(conversation_counts.keys()).map(function(e){\n let two_way = conversation_counts.get(e.split(\"-\")[0] + '-' + e.split(\"-\")[1]) + conversation_counts.get(e.split(\"-\")[1] + '-' + e.split(\"-\")[0]) \n let pair = e.split(\"-\").sort().join(\" & \")\n return `${pair}-${two_way}`\n });\n \n const output = Array.from(new Set(conversations)).map(e => ({group:'conversation count', variable: e.split(\"-\")[0], value: Number(e.split(\"-\")[1]) })).sort((a,b) => a.value - b.value).map(function(e,i){ \n let permutations = new Set(conversations).size\n e.variable += `: ${permutations - (i)}`; \n return e; })\n \n return output;\n\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":279,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":277,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"md `### Appendix: Guages & Bars combo charts`","pinned":false,"hidden":false,"mode":"ojs"},{"id":75,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":53,"value":"viewof senders_copy2_input = Radio(['Any'].concat(members_by_post_volume_array), {label: \"Originator:\", value: \"Any\"})\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":24,"value":"viewof engagement_threshold_input = Range([0, d3.max(filtered_originator_engagement_data.map(d => Number(d['words'])))], {value: 0, step:((senders_copy2_input == 'Any') && (engagement_category_input == 'All'))? 20: 5, label: \"Originator post min word count\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":208,"value":"percent_of_part_filtered_posts = 100*(filtered_originator_engagement_data.filter(e => Number(e['words']) >= Number(engagement_threshold_input)).length/filtered_originator_engagement_data.length).toFixed(2)","pinned":false,"hidden":false,"mode":"ojs"},{"id":29,"value":"viewof engagement_category_input = Select(['All'].concat(post_categories_top15_array), {value: \"All\", label: \"Originator post category\"}) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":47,"value":"//exploded file filtered by category\nexploded_file_category_filtered_indexes = Array.from (new Set(exploded_file.filter(e => (engagement_category_input == 'All'? true: e['Google classification category - top'] == engagement_category_input)).map(e => e['index'])) )","pinned":false,"hidden":false,"mode":"ojs"},{"id":372,"value":"exploded_file_top10_category_indexes = { \n \n let obj = {}; \n ['All'].concat(post_categories_top15_array).slice(0,7).forEach(function(e){\n obj[e] = []\n })\n \n exploded_file.forEach(function(e){\n if (e['Google classification category - top'] != 'Unclassified'){ \n \n obj['All'].push(e['index']);\n if(post_categories_top15_array.slice(0,6).indexOf(e['Google classification category - top']) > -1){\n\n obj[post_categories_top15_array[post_categories_top15_array.indexOf(e['Google classification category - top'])]].push(e['index']);\n \n } \n \n }\n\n });\n \n //de-dupe arrays\n for (const prop in obj){\n obj[prop] = Array.from(new Set(obj[prop]))\n }\n \n return obj;\n} ","pinned":false,"hidden":false,"mode":"ojs"},{"id":49,"value":"filtered_originator_engagement_data = main_file.filter(e => [\n (senders_copy2_input == 'Any'? true: senders_copy2_input == e['sender']), \n (engagement_category_input == 'All'? true: exploded_file_category_filtered_indexes.indexOf(e['index']) > -1? true: false)\n ].every((input) => input == true)); ","pinned":false,"hidden":false,"mode":"ojs"},{"id":344,"value":"fullyFilteredData = filtered_originator_engagement_data.filter(e => \n [\n (Number(e['words']) >= Number(engagement_threshold_input)? true: false)\n ].every((input) => input == true)\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":435,"value":"function getCategory(main_file_index, category_indexes_object){\n let output = false;\n let holding_array = [];\n for (const prop in category_indexes_object) {\n if(category_indexes_object[prop].indexOf(main_file_index) > -1) {\n holding_array.push(prop);\n //output = prop;\n //break;\n }\n }\n \n return holding_array.length == 0? output: holding_array;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":439,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":466,"value":"function undefined_to_zero(input){\n return typeof input == 'undefined'? 0: input;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":443,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":337,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":71,"value":"engagement_o_meter_object = get_follow_on_aggregates(main_file, fullyFilteredData, 2)","pinned":false,"hidden":false,"mode":"ojs"},{"id":72,"value":"engagement_o_meter_origin_posts = engagement_o_meter_object.originator_post_count","pinned":false,"hidden":false,"mode":"ojs"},{"id":12,"value":"md `### Imports`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":15,"value":"import {Button, Checkbox, Toggle, Radio, Range, Select, Text, Search, Table, Input, bind, html} from \"@observablehq/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":17,"value":"import {rangeSlider,persistentSelect} from \"@bumbeishvili/utils\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":19,"value":"import {d3, Highcharts, main_file, exploded_file, colors, types, post_volume_array, members_by_post_volume_array, post_categories_top15_array, post_categories_top10_array, entities_per_topic_map, years_array} from \"@mtsvelik/book-club-whatsapp-group-what-our-posts-say-about-us-intro\" ","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W38","stdlib":"1","titling":"auto"}