32:T4ad,md`###### Atlante Calvino: letteratura e visualizzazione ###### Hypothetical Text - 2nd level of analysis # Automated data preparation Literary scholars worked on Google Spreadhseet and curated data about the phenomenon of "hypothetical text" in the compositions of Italo Calvino. The spreadsheets are supposed to remain as deviced by scholars, but this makes their visualization very difficult. Furthermore they are in a continuous evolution. This notebook's supposed to be a middle layer that manipulates and prepare data to be visualized (also by integrating information coming from other datasets). This notebook is supposed to be run (and modified if necessary) everytime the original data chages. The process of data gathering/authoring is iterative and influenced by many factors. Among them we can certainly find the 'sandcastle visualizations'. This notebook is supposed to help researchers in be more agile in the research, by making them save time and by reducing the manul work needed at any iterative cycle. 👉 Get the data using **Observable Cell options** features: hover on a cell with the array of data and click the three-dots-icon, then download the JSON or the CSV 😎.`33:T42c,gantt_data_no_alternativa = { let here_data = data.filter(d=>d.category!=='alternativa') let txt_subj = here_data.map(d=>{ return { composition: d['ID opera'], category: 'soggetto', group: d['ID opera'] + ' ' + 'A soggetto', start: d.soggetto_starts_at/d.length, end: d.soggetto_ends_at/d.length } }) let txt_dubbio = here_data.filter(d=>d.category==='dubbio').map(d=>{ return { composition: d['ID opera'], category: `dubbio - ${d.macro_categoria}`, group: d['ID opera'] + ' ' + 'B dubbio', start: d.starts_at/d.length, end: d.ends_at/d.length } }) let txt_alternative = here_data.filter(d=>d.category==='alternativa').map(d=>{ return { composition: d['ID opera'], category: 'alternativa', group: d['ID opera'] + ' ' + 'C alternativa', start: d.starts_at/d.length, end: d.ends_at/d.length } }) console.log(txt_alternative) return txt_subj.concat(txt_dubbio, txt_alternative)//.filter((d,i)=>{ return (i%5===0) }) }34:T135d,data_bars = { let _with_lengths = with_lengths.filter(d=>d['Testo Alternativo']==="") // console.log(_with_lengths) let _data = d3.nest() .key(d=>d['ID opera']) .entries(_with_lengths.filter(d=>d['Testo Alternativo']==="")) .map(d=>{ return { ...d, all_sogg: d.values.map(dd=>[+dd.soggetto_starts_at, +dd.soggetto_ends_at]), all_dubb: d.values.map(dd=>[+dd.starts_at, +dd.ends_at]) } }) // console.log(_data) let data_bars = [] let data_bars_matrix = [] let data_char = [] corpusData.titles.forEach(t=>{ //if (t.id !== "V021") return; console.log(t.id, t.title, t.txt_length); let _this_year = corpusData.publications.filter(d=>d.id===t.id)[0].year let obj = { 'source': t.id, 'year_title': _this_year + ' - ' + t.title, 'title': t.title, 'length': +t.txt_length, 'soggetto': 0, 'dubbio': 0, 'misto': 0, 'definitivo': 0, 'soggetto_perc': 0, 'dubbio_perc': 0, 'misto_perc': 0, 'definitivo_perc': 0 } let _this_data = _data.filter(d=>d.key===t.id) if (_this_data.length) { _this_data = _this_data[0] // console.log(_this_data) let char_data = []; let chunks = [] for (let char = 0; char < t.txt_length; char++) { const _s = _this_data.all_sogg.filter(s=> char>=s[0]&&char char>=s[0]&&char0 && _d.length>0){ obj.misto++; char_cat = "misto" } else if (_s.length>0) { obj.soggetto++; char_cat = "soggetto" } else if (_d.length>0) { obj.dubbio++; char_cat = "dubbio" } else { obj.definitivo++; char_cat = "definitivo" } let this_chunk = { start: char, end: char+1, category: char_cat } if (chunks.length < 1) { chunks.push(this_chunk); } else if (chunks[chunks.length-1].category === char_cat) { chunks[chunks.length-1].end = char+1 } else { chunks.push(this_chunk); } const char_obj = { index: char, category: char_cat, was_subject: _s.length, was_doubt: _d.length } char_data.push(char_obj); } obj.chunks = chunks; char_data = d3.nest() .key(d=>d.category) .key(d=>d.was_subject) .rollup(values=>values.length) .entries(char_data) .map(d=>{ d.values = d.values.map(dd=>{ return { ...dd, 'percentage': dd.value/t.txt_length*100 } }).sort((a,b)=>+a.key-b.key) return d }); data_char.push({ id: t.id, title: t.title, data: char_data }); // console.log(char_data); } else { // obj.definitivo = +t.txt_length } // console.log(obj); const check_length = obj.misto + obj.soggetto + obj.dubbio + obj.definitivo; if (check_length!==+t.txt_length) { console.warn('Warning:', t.title, check_length, t.txt_length) } // calculate percentages obj.definitivo_perc = obj.definitivo/obj.length * 100 obj.soggetto_perc = obj.soggetto/obj.length * 100 obj.misto_perc = obj.misto/obj.length * 100 obj.dubbio_perc = obj.dubbio/obj.length * 100 // console.log(obj) data_bars_matrix.push(obj); data_bars.push({ 'source': t.id, 'title': t.title, 'year': _this_year, 'year_title': obj.year_title, 'category': 'definitivo', 'value': obj.definitivo, 'percentage': obj.definitivo/obj.length * 100 }) data_bars.push({ 'source': t.id, 'title': t.title, 'year': _this_year, 'year_title': obj.year_title, 'category': 'soggetto', 'value': obj.soggetto, 'percentage': obj.soggetto/obj.length * 100 }) data_bars.push({ 'source': t.id, 'title': t.title, 'year': _this_year, 'year_title': obj.year_title, 'category': 'misto', 'value': obj.misto, 'percentage': obj.misto/obj.length * 100 }) data_bars.push({ 'source': t.id, 'title': t.title, 'year': _this_year, 'year_title': obj.year_title, 'category': 'dubbio', 'value': obj.dubbio, 'percentage': obj.dubbio/obj.length * 100 }) }) console.log(data_bars_matrix) mutable data_bars_matrix_exp = data_bars_matrix mutable subject_how_many_times = data_char; return data_bars.sort((a,b)=>a.year-b.year) }35:T4d1,{ let data_phase_2 = mutable data_bars_matrix_exp.slice(0); let data_how_many_times = mutable subject_how_many_times; console.log("data_how_many_times", data_how_many_times); data_phase_2.forEach(d=>{ if (!d.id) { d["id"] = d["source"];+ delete d["source"]; } if (!d.year) { d["year"] = d["year_title"].split(" - ")[0].replace(",",""); delete d["year_title"]; } if (d.dubbio == d.misto == d.soggetto == d.definitivo) { d.definitivo = d.length; d.definitivo_perc = 100; } d.details = with_lengths .filter(dd=>dd["ID opera"]===d.id) .filter(dd=>dd["Testo Alternativo"]!=="YES"); if (data_how_many_times.find(dd=>dd.id===d.id)) { d.levels_doubt = data_how_many_times.find(dd=>dd.id===d.id).data d.levels_doubt = d.levels_doubt.map(l=>{ console.log("level", l) l.name = l.key; l.children = l.values.map(c=>{ return { 'name': c.key, 'value': c.value } }); delete l.key; delete l.values; return l; }) console.log(d.levels_doubt) } else { d.levels_doubt = [] } }) return data_phase_2; 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30:{"title":"Automated data preparation","cells":[{"id":0,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":461,"value":"md`---`","pinned":false,"hidden":false,"mode":"ojs"},{"id":76,"value":"viewof corpus_url = text({title: \"Corpus: dataset of Calvino's works\",placeholder: \"spreadsheet url\", description: \"Insert the url to the Google Spreadsheet of the corpus\", value: \"https://docs.google.com/spreadsheets/d/1CsBoCfG_b_J29_FiPhhBjfM1kzNmRGScoqyA-Blc_Ek/edit?usp=sharing\", width: 500})","pinned":false,"hidden":false,"mode":"ojs"},{"id":44,"value":"corpusData = new Promise((resolve, reject) => {\n Tabletop.init({\n key: corpus_url,\n callback: data => {\n if (data) {\n data = {\n 'titles': data.titles.elements,\n 'publications': data.publications.elements\n }\n resolve(data)\n } else reject(new Error(\"unable to load\"));\n }\n })\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"viewof doubtful_url = text({title: \"Doubts: curated dataset of doubtful text manifestation\", placeholder: \"spreadsheet url\", description: \"Insert the url to the Google Spreadsheet\", value: \"https://docs.google.com/spreadsheets/d/11gwVrrpqawYyHTUrlWQZ_ptM0O-vZmKZinNyW3ReYbM/edit?usp=sharing\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":6,"value":"doubtufulData = new Promise((resolve, reject) => {\n Tabletop.init({\n key: doubtful_url,\n originalColumns:true,\n callback: data => {\n if (data) resolve(data);\n else reject(new Error(\"unable to load\"));\n }\n })\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":382,"value":"md`### 🔮 Data about text chunks`","pinned":false,"hidden":false,"mode":"ojs"},{"id":229,"value":"md`##### Merge all the tables`;","pinned":false,"hidden":false,"mode":"ojs"},{"id":66,"value":"all_records = {\n let all_records = [];\n let all_headers = '\\n';\n for (var sheetName in doubtufulData) {\n let to_skip = sheetName.includes('SKIP');\n if (!to_skip){\n let sheet = doubtufulData[sheetName];\n all_records = all_records.concat(sheet.elements);\n all_headers += sheet.columnNames + '\\n';\n }\n }\n \n all_records = all_records.map(d=>{\n return {\n ...d,\n 'year': corpusData.publications.filter(p=>p.id===d['ID opera'])[0].year,\n 'length': corpusData.titles.filter(p=>p.id===d['ID opera'])[0].txt_length\n }\n })\n \n console.log('all_records', all_records)\n \n \n mutable data = all_records;\n return all_records;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":162,"value":"md`##### Add year based on the first publications`","pinned":false,"hidden":false,"mode":"ojs"},{"id":165,"value":"with_years = {\n console.log(all_records)\n let all_records_plus_years = all_records.map(d=>{\n console.log(corpusData.publications.filter(p=>p.id===d['ID opera'])[0].year)\n return {\n ...d,\n 'year': corpusData.publications.filter(p=>p.id===d['ID opera'])[0].year\n }\n })\n mutable data = all_records_plus_years;\n return all_records_plus_years;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":399,"value":"md`##### First publication complete date`","pinned":false,"hidden":false,"mode":"ojs"},{"id":404,"value":"with_dates = {\n let with_dates = with_years.map(d=>{\n let year = corpusData.publications.filter(p=>p.id===d['ID opera'])[0].year\n let month = corpusData.publications.filter(p=>p.id===d['ID opera'])[0].month\n let day = corpusData.publications.filter(p=>p.id===d['ID opera'])[0].day\n let this_date_complete = `${year}-${month}-${day}`\n return {\n ...d,\n 'date_complete': this_date_complete\n }\n })\n mutable data = with_dates;\n return with_dates;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":238,"value":"md`##### Calulate size of doubtful texts chunks`","pinned":false,"hidden":false,"mode":"ojs"},{"id":199,"value":"with_size = {\n let with_size = with_dates.map(r=>{\n return {\n ...r,\n 'size': r.ends_at - r.starts_at\n }\n })\n mutable data = with_size;\n return with_size;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":321,"value":"md`##### Set chunk category (doubt, alternative)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":371,"value":"with_categories = {\n let with_cats = with_size.map(d=>{\n return {\n ...d,\n 'category': d.macro_categoria===\"\"?\"alternativa\":\"dubbio\"\n }\n });\n mutable data = with_cats;\n return with_cats;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":584,"value":"with_lengths = {\n let with_lengths = with_categories.map(d=>{\n return {\n ...d,\n 'length': corpusData.titles.filter(p=>p.id===d['ID opera'])[0].txt_length,\n 'title': corpusData.titles.filter(p=>p.id===d['ID opera'])[0].title,\n 'year': corpusData.publications.filter(p=>p.id===d['ID opera'])[0].year\n }\n });\n mutable data = with_lengths;\n return with_lengths;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":520,"value":"md`Filter out volumes and keep short stories (don't merge with 'data')`","pinned":false,"hidden":false,"mode":"ojs"},{"id":523,"value":"data_stories = {\nreturn with_categories.filter( d=> d['ID opera'].includes('S') )\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":422,"value":"md`### 🔮 Data clustered on compositions`","pinned":false,"hidden":false,"mode":"ojs"},{"id":411,"value":"md`##### Cluster data on compositions`","pinned":false,"hidden":false,"mode":"ojs"},{"id":430,"value":"composition = {\n let comps = d3.nest()\n .key(d=>d['ID opera'])\n .entries(data)\n .map(d=>{\n return {\n ...d,\n length: corpusData.titles.filter(p=>p.id===d.key)[0].txt_length,\n title: corpusData.titles.filter(p=>p.id===d.key)[0].title,\n date_complete: d.values[0].date_complete\n }\n })\n \n mutable data_2 = comps;\n \n return comps;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":478,"value":"md`### 🔮 Data clustered on categories\nSo that we can make a normalized bumpchart\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":487,"value":"and_categories = {\n let and_cats = composition.map(d=>{ \n d.values = d3.nest()\n .key(dd=>dd.category)\n .entries(d.values)\n \n return d;\n })\n \n return and_cats;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":483,"value":"mess = 'it is a mess, continue later'","pinned":false,"hidden":false,"mode":"ojs"},{"id":241,"value":"md`### 📊 Some statistics`","pinned":false,"hidden":false,"mode":"ojs"},{"id":202,"value":"size_extent = {\n const extent = d3.extent(with_size, d=>d.size) \n return extent\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":283,"value":"average = {\n const sum = with_size.map(d=>d.size).reduce( (total, element) => { return total+element })\n return Math.round(sum/with_size.length)\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":248,"value":"md`## Visualizations`","pinned":false,"hidden":false,"mode":"ojs"},{"id":515,"value":"md`##### Just Short stories (and no volumes) over time`","pinned":false,"hidden":false,"mode":"ojs"},{"id":448,"value":"md`##### 👀 Text chunks`","pinned":false,"hidden":false,"mode":"ojs"},{"id":541,"value":"md`\n

Temporal distribution, short stories only. Every circle is an occurrence of doubtful text.
Purple = \"come\", blue = \"cosa\", green = \"senso\".
Visualized in RAWGraphs.Width\n1024\nHeight\n768\nAnticollision Iterations\n10\nCircles Padding\n0.5\nVertical Padding\n0\nMin Radius\n1\nMax Radius\n20\n

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":631,"value":"html`Click here to download a PDF.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":363,"value":"mutable data = []","pinned":false,"hidden":false,"mode":"ojs"},{"id":547,"value":"small_data = data.map(d=>{\n return {\n composition: d['ID opera'],\n year: d.year,\n start: d.starts_at,\n end: d.ends_at,\n size: d.size,\n category: d.category,\n category_doubt: d.macro_categoria,\n style: d.manifestazioni_stilistiche,\n soggetto_start: d.soggetto_starts_at,\n soggetto_end: d.soggetto_ends_at,\n soggetto_size: d.soggetto_ends_at-d.soggetto_starts_at\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":568,"value":"md`##### 👀 Gantt categories`","pinned":false,"hidden":false,"mode":"ojs"},{"id":615,"value":"md`\n \n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":571,"value":"gantt_data = {\n let txt_subj = data.map(d=>{\n return {\n composition: d['ID opera'],\n category: 'soggetto',\n group: d['ID opera'] + ' ' + 'A soggetto',\n start: d.soggetto_starts_at/d.length,\n end: d.soggetto_ends_at/d.length\n }\n })\n \n let txt_dubbio = data.filter(d=>d.category==='dubbio').map(d=>{\n return {\n composition: d['ID opera'],\n category: `dubbio - ${d.macro_categoria}`,\n group: d['ID opera'] + ' ' + 'B dubbio',\n start: d.starts_at/d.length,\n end: d.ends_at/d.length\n }\n })\n \n let txt_alternative = data.filter(d=>d.category==='alternativa').map(d=>{\n return {\n composition: d['ID opera'],\n category: 'alternativa',\n group: d['ID opera'] + ' ' + 'C alternativa',\n start: d.starts_at/d.length,\n end: d.ends_at/d.length\n }\n })\n \n return txt_subj.concat(txt_dubbio, txt_alternative)//.filter((d,i)=>{ return (i%5===0) })\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":634,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":682,"value":"md`##### 👀 Gantt categories (no alternativa)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":668,"value":"md`\n

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":675,"value":"html`Click here to download a PDF.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":685,"value":"md`### Data for bars`","pinned":false,"hidden":false,"mode":"ojs"},{"id":689,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":810,"value":"mutable subject_how_many_times = []","pinned":true,"hidden":false,"mode":"ojs"},{"id":763,"value":"mutable data_bars_matrix_exp = []","pinned":true,"hidden":false,"mode":"ojs"},{"id":779,"value":"data_bars_matrix_exp.find(d=>d.source==='V021')","pinned":true,"hidden":false,"mode":"ojs"},{"id":854,"value":"$35","pinned":true,"hidden":false,"mode":"ojs"},{"id":847,"value":"md`### Data for React`","pinned":false,"hidden":false,"mode":"ojs"},{"id":451,"value":"md`---\n#### 💾 Data clustered on compositions`","pinned":false,"hidden":false,"mode":"ojs"},{"id":434,"value":"mutable data_2 = []","pinned":false,"hidden":false,"mode":"ojs"},{"id":25,"value":"md`## Dependencies`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3,"value":"Tabletop = require(\"tabletop\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":78,"value":"import {text} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":205,"value":"d3 = require(\"d3\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":505,"value":"md`\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n\n---\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":308,"value":"md`### Things got removed\n\nI was actually looking for the possibility to archive those cells and bring them up later if needed.\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":111,"value":"{\n let to_download = new Blob([JSON.stringify(all_records, null, 4)], {type : 'application/json'})\n return DOM.download(to_download, `doubts_all_${new Date()}.json`, 'Download time-stamped JSON of all records');\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":141,"value":"{\n const items = all_records\n const replacer = (key, value) => value === null ? '' : value // specify how you want to handle null values here\n const header = Object.keys(items[0])\n const separator = '\\t';\n let dsv = items.map(row => header.map(fieldName => JSON.stringify(row[fieldName], replacer)).join(separator))\n dsv.unshift(header.join(separator))\n dsv = dsv.join('\\r\\n')\n \n let to_download = new Blob([dsv], {type : 'text/tsv'})\n return DOM.download(to_download, `doubts_all_${new Date()}.tsv`, 'Download time-stamped TSV of all records');\n}","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W36","stdlib":"1","titling":"auto"}