31:T645,Plot.plot({ marks: [ Plot.line([8000, 1_000_000_000], { x: (d) => d, y: (d) => (d * 1000) / 1_000_000, stroke: "#cccccc", strokeWidth: 1.5, strokeDasharray: "4,4", clip: true }), Plot.line([8000, 1_000_000_000], { x: (d) => d, y: (d) => (d * 100) / 1_000_000, stroke: "#cccccc", strokeWidth: 1.5, strokeDasharray: "4,4", clip: true }), Plot.line([8000, 1_000_000_000], { x: (d) => d, y: (d) => (d * 10) / 1_000_000, stroke: "#cccccc", strokeWidth: 1.5, strokeDasharray: "4,4", clip: true }), Plot.dot(df_notability_by_country, { x: (d) => d.wpp_count, y: (d) => d.wd_count, r: 5, fill: (d) => d.ratio_cat, title: (d) => d.Name + "\n" + d.ratio.toFixed(1) + " bio per million births" + "\n" + d.wd_count.toLocaleString("en-US") + " biographies\n" + d.wpp_count.toLocaleString("en-US") + " births" }) ], color: { range: ["#b2182b", "#f4a582", "#92c5de", "#2166ac"], domain: ["> 1000", "100 - 999", "10 - 99", "< 10"], tickFormat: (d) => d.replace(" biographies per million births", ""), label: "Biographies per million births", legend: true }, x: { type: "log", label: "Births", domain: d3.extent(df_notability_by_country, (d) => d.wpp_count) }, y: { type: "log", label: "Biographies", domain: d3.extent(df_notability_by_country, (d) => d.wd_count) }, height: 600, marginLeft: 60, marginRight: 60 })32:T46a,Plot.plot({ marks: [ Plot.dot(df_notability_by_country, { x: "wpp_count", y: "ratio", r: 4, fill: "#831C91", fillOpacity: 0.5, color: "#462C7D", tip: true, title: (d) => `${d.Name} (${d.Alpha_3})\nRatio: ${d.ratio.toFixed(1)}` }), Plot.linearRegressionY(df_notability_by_country, { x: "wpp_count", y: "ratio", stroke: "#462C7D", ci: 0 }), Plot.text( df_notability_by_country.filter((d) => [ "SMR", "AND", "ISL", "FLK", "CHN", "USA", "JPN", "IRL", "EST", "SWE", "CAN", "GBR", "IND", "ETH" ].includes(d.Alpha_3) ), { x: (d) => d.wpp_count, y: (d) => d.ratio, text: (d) => d.Alpha_3, dx: 22, fontSize: 12, fill: "black", clip: false } ) ], marginRight: 60, x: { type: "log", label: "Births (WPP) →" }, y: { type: "log", label: "↑ Biographies per million births" } })33:T51a,Plot.plot({ marks: [ Plot.dot( df_notability2.filter((d) => d.wiki == "fr"), { x: "wpp_count", y: "ratio", r: 4, fill: "#831C91", fillOpacity: 0.5, color: "#462C7D", tip: true, title: (d) => `${d.Name} (${d.Alpha_3})\nRatio: ${d.ratio.toFixed(1)}` } ), Plot.linearRegressionY( df_notability2.filter((d) => d.wiki == "fr"), { x: "wpp_count", y: "ratio", stroke: "#462C7D", ci: 0 } ), Plot.text( df_notability2 .filter((d) => d.wiki == "fr") .filter((d) => [ "SMR", "AND", "ISL", "FLK", "CHN", "USA", "JPN", "IRL", "EST", "SWE", "CAN", "GBR", "IND", "ETH" ].includes(d.Alpha_3) ), { x: (d) => d.wpp_count, y: (d) => d.ratio, text: (d) => d.Alpha_3, dx: 22, fontSize: 12, fill: "black", clip: false } ) ], marginRight: 60, x: { type: "log", label: "Births (WPP) →" }, y: { type: "log", label: "↑ Biographies per million births" } })34:[{"id":"f49aa5667ef6a3253bc60452163d66ae3b205775ef0ce3ee96e61b49534fe038ca90c4ac41bf864af4e0cfd6deda14b903039dcdb8e2fee36a9b02f6a928eb7c","href":"https://static.observableusercontent.com/files/f49aa5667ef6a3253bc60452163d66ae3b205775ef0ce3ee96e61b49534fe038ca90c4ac41bf864af4e0cfd6deda14b903039dcdb8e2fee36a9b02f6a928eb7c","name":"df_notability@3.parquet","type":"application/octet-stream","lastModified":1776230340771.856,"size":315440},{"id":"ec8ba33fedda18a9c9eb4356719e483ddd1ca06e1e9fe720330f94f99f69b6a0070df5a881da476b56941f4e875ffe61ed897d9d58fd701b1c24e0c45971fccc","href":"https://static.observableusercontent.com/files/ec8ba33fedda18a9c9eb4356719e483ddd1ca06e1e9fe720330f94f99f69b6a0070df5a881da476b56941f4e875ffe61ed897d9d58fd701b1c24e0c45971fccc","name":"df_wpp@1.parquet","type":"application/octet-stream","lastModified":1776227628274.376,"size":568984},{"id":"c3067a09091c9c8a6769e5486c35ef4c92e4963d86858df4aceb1ee4ee35435e5efdaaf01e487f069e8db3473df637de004ae2b3f28d5d829325c079bf5820a0","href":"https://static.observableusercontent.com/files/c3067a09091c9c8a6769e5486c35ef4c92e4963d86858df4aceb1ee4ee35435e5efdaaf01e487f069e8db3473df637de004ae2b3f28d5d829325c079bf5820a0","name":"df_iso@1.parquet","type":"application/octet-stream","lastModified":1776227650194.73,"size":7334}] 2f:{"title":"Does the country of birth affect the likelihood of having a Wikipedia biography?","cells":[{"id":0,"value":"# Does the country of birth affect the likelihood of having a Wikipedia biography?\n## A Cross-Country and Cross-Wikipedia Comparison\n\nWe compare the number of biographies by birth year and country against demographic birth data to estimate the probability of appearing in different Wikipedia language editions, depending on one's country of birth.\n\nResearch Questions\n* What is the probability of having a biography in different Wikipedia language editions?\n* Does country of birth affect this probability?\n* If so, which birth countries are most overrepresented on Wikipedia?\n* Do different Wikipedia editions differ in their country rankings?","pinned":false,"hidden":false,"mode":"md"},{"id":517,"value":"db = DuckDBClient.of({\n wpp: FileAttachment(\"df_wpp@1.parquet\"),\n iso: FileAttachment(\"df_iso@1.parquet\"),\n notability: FileAttachment(\"df_notability@3.parquet\")\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":546,"value":"db.describeTables()","pinned":false,"hidden":false,"mode":"ojs"},{"id":606,"value":"We look at the 10 editions of Wikipedia with the highest number of active users:\n\n${wikis.map((w) => `- ${w}.wikipedia.org`).join(\"\\n\")}","pinned":false,"hidden":false,"mode":"md"},{"id":564,"value":"wikis = [\"en\", \"de\", \"es\", \"fr\", \"it\", \"ja\", \"zh\", \"pl\", \"nl\", \"fa\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":520,"value":"## Datasets\n\nThree data sources are combined to compute the notability index.\n\n### ISO 3166 Country Codes\n\nExtracted from the [`ISOcodes` R package](https://r-packages.io/packages/ISOcodes/ISO_3166), this dataset provides the reference list of countries and their standardized identifiers used to join the three datasets.\n\n| Variable | Description |\n|---|---|\n| `Numeric` | ISO 3166-1 numeric code |\n| `Alpha_3` | ISO 3166-1 three-letter code |\n| `Name` | Country name |\n","pinned":false,"hidden":false,"mode":"md"},{"id":526,"value":"countries = db.query(\"SELECT Name, Numeric FROM iso\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":529,"value":"countriesMap = new Map(\n countries.map(({ Numeric, Name }) => [Name + \" (\" + Numeric + \")\", Numeric])\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":523,"value":"### UN World Population Prospects\n\nPublished by the United Nations Population Division, this dataset provides historical birth counts by country from 1950 onwards.\n\n| Variable | Description |\n|---|---|\n| `LocID` | ISO 3166-1 numeric country code |\n| `Time` | Year |\n| `Births` | Live births recorded between 1 January and 31 December ([glossary](https://population.un.org/wpp/glossary-demographic-terms)) |\n\n","pinned":false,"hidden":false,"mode":"md"},{"id":532,"value":"viewof country = Inputs.select(countriesMap, { value: \"566\" })","pinned":false,"hidden":false,"mode":"ojs"},{"id":535,"value":"df_wpp = db.query(`SELECT * FROM wpp WHERE LocID = ${country} AND Time < 2000`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":538,"value":"Plot.plot({\n width: 800,\n height: 400,\n marginLeft: 60,\n marginBottom: 40,\n style: { fontSize: 13, fontFamily: \"sans-serif\" },\n x: {\n label: \"Year\",\n tickFormat: (d) => String(d)\n },\n y: {\n label: \"Number of births\",\n domain: [0, d3.max(df_wpp, (d) => d.Births)],\n grid: true\n },\n marks: [\n Plot.ruleY([0]),\n Plot.areaY(df_wpp, {\n x: (d) => d.Time,\n y: (d) => d.Births,\n fill: \"#93c5fd\",\n fillOpacity: 0.3\n }),\n Plot.line(df_wpp, {\n x: (d) => d.Time,\n y: (d) => d.Births,\n stroke: \"#2563eb\",\n strokeWidth: 2\n }),\n Plot.dot(df_wpp, {\n x: (d) => d.Time,\n y: (d) => d.Births,\n fill: \"#2563eb\",\n r: 3\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":859,"value":"Inputs.table(df_wpp)","pinned":false,"hidden":false,"mode":"ojs"},{"id":87,"value":"### Wikidata Biographical Data\n\nCollected via the [QLever SPARQL endpoint](https://qlever.dev/), this dataset counts the number of people born in each country who have a biography in each Wikipedia, by year of birth. See the [example query for Belgium](https://qlever.dev/wikidata/nxGdSG) and the [data collection notebook](https://codeberg.org/pac2/atlasofnotability/src/branch/main/data_collection_multiwiki.qmd) for full details. Data have been collected between the 10th and the 15th of March 2026.\n\n| Variable | Description |\n|---|---|\n| `country` | Wikidata entity identifier (QID) |\n| `count` | Number of biographies in French Wikipedia |\n\n","pinned":false,"hidden":false,"mode":"md"},{"id":567,"value":"viewof w = Inputs.select(wikis)","pinned":false,"hidden":false,"mode":"ojs"},{"id":570,"value":"df_notability_filtered = await db.query(\n `SELECT wiki, year, count, Births, 1e6 * count / Births AS ratio \n FROM notability WHERE country_code = '${country}' AND wiki = '${w}'`\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":573,"value":"Plot.plot({\n width: 800,\n height: 400,\n marginLeft: 60,\n marginBottom: 40,\n style: { fontSize: 13, fontFamily: \"sans-serif\" },\n x: {\n label: \"Year\",\n tickFormat: (d) => String(d)\n },\n y: {\n label: \"Number of people with biography\",\n domain: [0, d3.max(df_notability_filtered, (d) => d.count)],\n grid: true\n },\n marks: [\n Plot.ruleY([0]),\n Plot.areaY(df_notability_filtered, {\n x: (d) => d.year,\n y: (d) => d.count,\n fill: \"#93c5fd\",\n fillOpacity: 0.3\n }),\n Plot.line(df_notability_filtered, {\n x: (d) => d.year,\n y: (d) => d.count,\n stroke: \"#2563eb\",\n strokeWidth: 2\n }),\n Plot.dot(df_notability_filtered, {\n x: (d) => d.year,\n y: (d) => d.count,\n fill: \"#2563eb\",\n title: (d) => `${d.year}: ${d.count}`,\n r: 3\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":557,"value":"### Biography per million births ratio\n\nThe biography per million births ratio is defined as:\n\n${tex`\\text{ratio} = \\frac{\\text{count}}{\\text{Births}} \\times 10^6`}\n\nFull details are available in the [data preparation notebook](https://codeberg.org/pac2/atlasofnotability/src/branch/main/data_preparation.qmd).","pinned":false,"hidden":false,"mode":"md"},{"id":686,"value":"#### Biographies per million of births for ${countries.find((d) => d.Numeric == country)?.Name} in ${w}.wikipedia.org ","pinned":false,"hidden":false,"mode":"md"},{"id":42,"value":"Plot.plot({\n width: 800,\n height: 400,\n marginLeft: 60,\n marginBottom: 40,\n style: { fontSize: 13, fontFamily: \"sans-serif\" },\n x: {\n label: \"Year\",\n tickFormat: (d) => String(d)\n },\n y: {\n label: \"Biographies per million births\",\n domain: [0, d3.max(df_notability_filtered, (d) => d.ratio)],\n grid: true\n },\n marks: [\n Plot.ruleY([0]),\n Plot.areaY(df_notability_filtered, {\n x: (d) => d.year,\n y: (d) => d.ratio,\n fill: \"#93c5fd\",\n fillOpacity: 0.3\n }),\n Plot.line(df_notability_filtered, {\n x: (d) => d.year,\n y: (d) => d.ratio,\n stroke: \"#2563eb\",\n strokeWidth: 2\n }),\n Plot.dot(df_notability_filtered, {\n x: (d) => d.year,\n y: (d) => d.ratio,\n fill: \"#2563eb\",\n r: 3\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":53,"value":"## Cross-country comparisons for each wikipedia\n\nWe aggregate data by country to perform cross-country comparisons.","pinned":false,"hidden":false,"mode":"md"},{"id":693,"value":"viewof start = Inputs.range([1950, 2000], { step: 10, value: 1950 })","pinned":false,"hidden":false,"mode":"ojs"},{"id":697,"value":"viewof end = Inputs.range([1950, 2000], { step: 10, value: 1990 })","pinned":false,"hidden":false,"mode":"ojs"},{"id":715,"value":"viewof w2 = Inputs.select(wikis)","pinned":false,"hidden":false,"mode":"ojs"},{"id":727,"value":"viewof wd_threshold = Inputs.range([0, 30], {\n value: 10,\n step: 10,\n label: \"Minimum number of bios\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":712,"value":"df_notability_by_country = await db.query(`SELECT\n Name,\nAlpha_3, \n SUM(Births)::INTEGER AS wpp_count,\n SUM(count)::INTEGER AS wd_count,\n 1e6 * SUM(count) / SUM(Births) AS ratio, \n RANK() OVER (ORDER BY 1e6 * SUM(count) / SUM(Births) DESC) AS rank,\nCASE\n WHEN 1e6 * SUM(count) / SUM(Births) > 1000 THEN '> 1000'\n WHEN 1e6 * SUM(count) / SUM(Births) >= 100 THEN '100 - 999'\n WHEN 1e6 * SUM(count) / SUM(Births) >= 10 THEN '10 - 99'\n ELSE '< 10'\n END AS ratio_cat\nFROM notability\nWHERE year >= ${start} AND year < ${end} AND wiki = '${w2}' AND Births IS NOT NULL\nGROUP BY Name, Alpha_3\nHAVING SUM(count)::INTEGER > 0 AND SUM(count)::INTEGER >= ${wd_threshold}`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":146,"value":"Inputs.table(df_notability_by_country, {\n columns: [\"Name\", \"wd_count\", \"wpp_count\", \"ratio\", \"rank\"],\n header: {\n Name: \"Country\",\n wd_count: \"People with a bio\",\n wpp_count: \"Births\",\n ratio: \"People with a bio per million births\",\n rank: \"Ranking\"\n },\n format: {\n ratio: (x) =>\n x.toLocaleString(\"en-US\", {\n maximumFractionDigits: 0\n })\n },\n sort: \"ratio\",\n reverse: true,\n layout: \"auto\",\n select: false\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1437,"value":"### Biographies vs births","pinned":false,"hidden":false,"mode":"md"},{"id":732,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":1439,"value":"### Biographies per million births world map","pinned":false,"hidden":false,"mode":"md"},{"id":768,"value":"geo_countries = d3.json(\n \"https://gisco-services.ec.europa.eu/distribution/v2/countries/geojson/CNTR_RG_60M_2020_4326.geojson\"\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":753,"value":"geo_notability = geoviz.tool.merge({\n geom: geo_countries,\n geom_id: \"ISO3_CODE\",\n data: df_notability_by_country,\n data_id: \"Alpha_3\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":758,"value":"geo_data = geo_notability.featureCollection","pinned":false,"hidden":false,"mode":"ojs"},{"id":771,"value":"choro = geoviz.tool.choro(\n geo_data.features.map((d) => d.properties.ratio),\n {\n method: \"manual\",\n breaks: [0, 10, 100, 1000, 100000],\n precision: 0,\n colors: [\"#2166ac\", \"#92c5de\", \"#f4a582\", \"#b2182b\"]\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":763,"value":"geoviz.draw({\n params: { projection: d3.geoPeirceQuincuncial(), width: 600 },\n layers: [\n { type: \"outline\", fill: \"#fff\" },\n {\n type: \"graticule\",\n stroke: \"#a0b8cc\",\n strokeWidth: 0.5,\n strokeOpacity: 0.8\n },\n {\n type: \"layer\",\n data: geo_data,\n fill: \"#daeaf5\",\n stroke: \"#78909c\",\n strokeWidth: 0.6\n },\n {\n type: \"circle\",\n data: geo_data,\n r: 5,\n dodge: true,\n sort: \"wpp_count\",\n fill: (d) => choro.colorize(d.properties.ratio),\n fillOpacity: 0.9,\n stroke: \"#ffffff\",\n strokeWidth: 0.6,\n tip: (d) =>\n `${d.properties.NAME_ENGL}\\n` +\n `${d.properties.ratio.toLocaleString(\"en-US\", {\n maximumFractionDigits: 0\n })} biographies per million births`\n },\n {\n type: \"leg_choro_horizontal\",\n pos: [20, 50],\n title: \"Biographies per million births\",\n colorize: choro.colorize,\n breaks: choro.breaks,\n colors: choro.colors\n }\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1441,"value":"### Biographies per million birth vs births","pinned":false,"hidden":false,"mode":"md"},{"id":1222,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1231,"value":"ss.sampleCorrelation(\n df_notability_by_country.map((d) => Math.log(d.wpp_count)),\n df_notability_by_country.map((d) => Math.log(d.ratio))\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":659,"value":"## Cross wiki comparisons","pinned":false,"hidden":false,"mode":"md"},{"id":815,"value":"df_by_wiki = db.query(`SELECT\n wiki,\n COUNT(DISTINCT country_code) AS distinct_country_codes,\n SUM(Births) AS wpp_count,\n SUM(count) AS wd_count,\n 1e6 * SUM(count) / SUM(Births) AS ratio\n FROM notability\n WHERE year >= 1950 AND year < 1990\n GROUP BY wiki`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":215,"value":"Inputs.table(df_by_wiki, {\n select: false,\n layout: \"auto\",\n sort: \"ratio\",\n reverse: true,\n columns: [\"wiki\", \"wd_count\", \"wpp_count\", \"ratio\"]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":668,"value":"## Cross-wiki analysis","pinned":false,"hidden":false,"mode":"md"},{"id":744,"value":"df_by_country_wiki = await db.query(`SELECT\n Name,\n wiki,\n SUM(Births)::INTEGER AS wpp_count,\n SUM(count)::INTEGER AS wd_count,\n 1e6 * SUM(count) / SUM(Births) AS ratio, \n LOG(1e6 * SUM(count) / SUM(Births)) AS log_ratio, \nFROM notability\nWHERE year >= ${start} AND year < ${end} \nGROUP BY Name, wiki\nHAVING SUM(count)::INTEGER > 0\n`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1173,"value":"Plot.plot({\n marginLeft: 60,\n marginRight: 20,\n marginBottom: 50,\n height: 2000,\n grid: true,\n width: 800,\n y: {\n label: \"Biographies per million births\",\n type: \"log\",\n tickFormat: (d) => d3.format(\"~r\")(d)\n },\n fx: {\n label: null,\n tickRotate: -30\n },\n color: {\n type: \"quantile\",\n n: 10,\n legend: true,\n scheme: \"RdPu\",\n label: \"Births\"\n },\n\n marks: [\n Plot.dot(\n df_by_country_wiki,\n Plot.dodgeX(\"middle\", {\n fx: \"wiki\",\n y: \"ratio\",\n r: 5,\n fill: \"wpp_count\",\n stroke: \"#360185\",\n fillOpacity: 0.85,\n tip: {\n channels: {\n Name: \"Name\",\n Ratio: { value: \"ratio\", format: \",.0f\" },\n Births: { value: \"wpp_count\", format: \",\" },\n Biographies: { value: \"wd_count\", format: \",\" }\n }\n }\n })\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1344,"value":"## Similarity between Wikipedia editions","pinned":false,"hidden":false,"mode":"md"},{"id":1269,"value":"countryWikiMap = d3.group(df_by_country_wiki, (d) => d.Name)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1271,"value":"commonCountries = [...countryWikiMap]\n .filter(([, rows]) => rows.length === wikis.length)\n .map(([name]) => name)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1273,"value":"pivoted = Object.fromEntries(\n commonCountries.map((name) => [\n name,\n Object.fromEntries(\n countryWikiMap.get(name).map((d) => [d.wiki, d.log_ratio])\n )\n ])\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1443,"value":"### Pearson's correlation matrix","pinned":false,"hidden":false,"mode":"md"},{"id":1275,"value":"correlationMatrix = wikis.map((w1) =>\n wikis.map((w2) => {\n const pairs = commonCountries\n .map((c) => [pivoted[c][w1], pivoted[c][w2]])\n .filter(([a, b]) => a != null && b != null && isFinite(a) && isFinite(b));\n return ss.sampleCorrelation(\n pairs.map((p) => p[0]),\n pairs.map((p) => p[1])\n );\n })\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1277,"value":"correlation = wikis.map((w1, i) => ({\n wiki: w1,\n ...Object.fromEntries(\n wikis.map((w2, j) => [w2, correlationMatrix[i][j].toFixed(3)])\n )\n}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1304,"value":"d3.min(correlationMatrix.flat())","pinned":false,"hidden":false,"mode":"ojs"},{"id":1280,"value":"Inputs.table(correlation, { layout: \"auto\" })","pinned":true,"hidden":false,"mode":"ojs"},{"id":1446,"value":"### Spearman correlation matrix","pinned":false,"hidden":false,"mode":"md"},{"id":1294,"value":"function spearman_correlation(x, y) {\n const rank = (arr) => {\n const sorted = [...arr].map((v, i) => ({ v, i })).sort((a, b) => a.v - b.v);\n const ranks = new Array(arr.length);\n sorted.forEach(({ i }, r) => (ranks[i] = r + 1));\n return ranks;\n };\n return ss.sampleCorrelation(rank(x), rank(y));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1292,"value":"spearmanMatrix = wikis.map((w1) =>\n wikis.map((w2) => {\n const pairs = commonCountries\n .map((c) => [pivoted[c][w1], pivoted[c][w2]])\n .filter(([a, b]) => a != null && b != null && isFinite(a) && isFinite(b));\n return spearman_correlation(\n pairs.map((p) => p[0]),\n pairs.map((p) => p[1])\n );\n })\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1301,"value":"spearman = wikis.map((w1, i) => ({\n wiki: w1,\n ...Object.fromEntries(\n wikis.map((w2, j) => [w2, spearmanMatrix[i][j].toFixed(3)])\n )\n}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1297,"value":"Inputs.table(spearman, { layout: \"auto\" })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1448,"value":"### Pairwise comparisons","pinned":false,"hidden":false,"mode":"md"},{"id":1039,"value":"columns = [\n \"ratio_en\",\n \"ratio_fr\",\n \"ratio_de\",\n \"ratio_es\",\n \"ratio_it\",\n \"ratio_ja\",\n \"ratio_zh\",\n \"ratio_pl\",\n \"ratio_nl\",\n \"ratio_fa\"\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1043,"value":"viewof xCol = Inputs.select(columns, { value: \"ratio_en\", label: \"X axis\" })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1019,"value":"viewof yCol = Inputs.select(\n columns.filter((d) => d != xCol),\n { value: \"ratio_ja\", label: \"Y axis\" }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1018,"value":"Plot.plot({\n marks: [\n Plot.dot(df_by_country, {\n x: xCol,\n y: yCol,\n stroke: \"#462C7D\",\n fill: \"#831C91\",\n fillOpacity: 0.4,\n r: 5,\n tip: true,\n title: (d) =>\n `${d.Name}\\n${xCol}: ${d[xCol]?.toFixed(1)}\\n${yCol}: ${d[\n yCol\n ]?.toFixed(1)}`\n }),\n Plot.linearRegressionY(df_by_country, {\n x: xCol,\n y: yCol,\n stroke: \"#D552A3\",\n strokeWidth: 1.5\n })\n ],\n x: {\n type: \"log\",\n label: xCol.replace(\"ratio_\", \"wikipedia — \"),\n tickFormat: (d) => d3.format(\"~r\")(d)\n },\n y: {\n type: \"log\",\n label: yCol.replace(\"ratio_\", \"wikipedia — \"),\n tickFormat: (d) => d3.format(\"~r\")(d)\n },\n height: 600,\n marginLeft: 60,\n marginRight: 60\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":701,"value":"df_by_country = db.query(`SELECT\n Name,\n COALESCE(MAX(CASE WHEN wiki = 'en' THEN ratio END), 0) AS ratio_en,\n COALESCE(MAX(CASE WHEN wiki = 'fr' THEN ratio END), 0) AS ratio_fr,\n COALESCE(MAX(CASE WHEN wiki = 'de' THEN ratio END), 0) AS ratio_de,\n COALESCE(MAX(CASE WHEN wiki = 'es' THEN ratio END), 0) AS ratio_es,\n COALESCE(MAX(CASE WHEN wiki = 'it' THEN ratio END), 0) AS ratio_it,\n COALESCE(MAX(CASE WHEN wiki = 'ja' THEN ratio END), 0) AS ratio_ja,\n COALESCE(MAX(CASE WHEN wiki = 'zh' THEN ratio END), 0) AS ratio_zh,\n COALESCE(MAX(CASE WHEN wiki = 'pl' THEN ratio END), 0) AS ratio_pl,\n COALESCE(MAX(CASE WHEN wiki = 'nl' THEN ratio END), 0) AS ratio_nl,\n COALESCE(MAX(CASE WHEN wiki = 'fa' THEN ratio END), 0) AS ratio_fa\nFROM (\n SELECT\n Name,\n wiki,\n 1e6 * SUM(count) / SUM(Births) AS ratio\n FROM notability\n WHERE year >= 1950 AND year < 1990\n GROUP BY Name, wiki\n)\nGROUP BY Name`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":705,"value":"Inputs.table(df_by_country, { layout: \"auto\", select: false })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1367,"value":"df_by_country_wiki_ranked = await db.query(`\n SELECT\n Name,\n wiki,\n 1e6 * SUM(count) / SUM(Births) AS ratio,\n LOG(1e6 * SUM(count) / SUM(Births)) AS log_ratio,\n RANK() OVER (PARTITION BY wiki ORDER BY 1e6 * SUM(count) / SUM(Births) DESC) AS rank\n FROM notability\n WHERE year >= ${start} AND year < ${end}\n GROUP BY Name, wiki\n HAVING SUM(count)::INTEGER > 2\n`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1369,"value":"df_rank_wide = [...d3.group(df_by_country_wiki_ranked, (d) => d.Name)].map(\n ([name, rows]) => ({\n Name: name,\n ...Object.fromEntries(rows.map((d) => [d.wiki, d.rank]))\n })\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1371,"value":"Inputs.table(df_rank_wide, {\n columns: [\"Name\", ...wikis],\n sort: \"en\",\n select: false,\n layout: \"auto\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1077,"value":"## Appendix","pinned":false,"hidden":false,"mode":"md"},{"id":284,"value":"geoviz = require(\"geoviz\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":291,"value":"d3 = require(\"d3@7\", \"d3-geo-projection@4\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":1337,"value":"ss = require(\"simple-statistics\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":1131,"value":"import { toWikiTable } from \"@pac02/who-gets-a-biography-on-french-language-wikipedia\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":1365,"value":"toWikiTable(\n df_by_wiki\n .sort((a, b) => b.ratio - a.ratio)\n .map(({ wiki, wd_count, ratio }) => ({\n wiki,\n wd_count: \"{{formatnum:\" + wd_count + \"}}\",\n ratio: \"{{formatnum:\" + ratio.toFixed(1) + \"}}\"\n }))\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1216,"value":"df_notability_by_country_en = await db.query(`SELECT\n Name,\nAlpha_3, \n SUM(Births)::INTEGER AS wpp_count,\n SUM(count)::INTEGER AS wd_count,\n 1e6 * SUM(count) / SUM(Births) AS ratio, \nCASE\n WHEN 1e6 * SUM(count) / SUM(Births) > 1000 THEN '> 1000'\n WHEN 1e6 * SUM(count) / SUM(Births) >= 100 THEN '100 - 999'\n WHEN 1e6 * SUM(count) / SUM(Births) >= 10 THEN '10 - 99'\n ELSE '< 10'\n END AS ratio_cat\nFROM notability\nWHERE year >= 1950 AND year < 1990 AND wiki = 'en' AND Births IS NOT NULL\nGROUP BY Name, Alpha_3\nHAVING SUM(count)::INTEGER > 0`)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1218,"value":"toWikiTable(\n df_notability_by_country_en\n .slice()\n .sort((a, b) => b.ratio - a.ratio)\n .slice(0, 20)\n .map(({ Name, wd_count, wpp_count, ratio }) => ({\n Name: \"[[\" + Name + \"]]\",\n wd_count: \"{{formatnum:\" + wd_count + \"}}\",\n wpp_count: \"{{formatnum:\" + wpp_count + \"}}\",\n ratio: \"{{formatnum:\" + ratio.toFixed(1) + \"}}\"\n }))\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1351,"value":"toWikiTable(\n df_notability_by_country_en\n .slice()\n .sort((a, b) => b.ratio - a.ratio)\n .filter((d) => d.wpp_count > 10000000)\n .map(({ Name, wd_count, wpp_count, ratio }) => ({\n Name: \"[[\" + Name + \"]]\",\n wd_count: \"{{formatnum:\" + wd_count + \"}}\",\n wpp_count: \"{{formatnum:\" + wpp_count + \"}}\",\n ratio: \"{{formatnum:\" + ratio.toFixed(1) + \"}}\"\n }))\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1354,"value":"toWikiTable(\n correlation\n .map(({ wiki, en }) => ({ wiki, en }))\n .sort((a, b) => +b.en - +a.en)\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1389,"value":"toWikiTable(\n df_rank_wide\n .sort((a, b) => a.en - b.en)\n .slice(-20)\n .map(({ Name, ...d }) => ({\n Name,\n ...Object.fromEntries(wikis.map((k) => [k, d[k]]))\n }))\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1392,"value":"toWikiTable(\n df_rank_wide\n .sort((a, b) => a.en - b.en)\n .slice(0, 20)\n .map(({ Name, ...d }) => ({\n Name,\n ...Object.fromEntries(wikis.map((k) => [k, d[k]]))\n }))\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1450,"value":"df_notability2 = await db.query(`\n SELECT\n Name,\nAlpha_3,\n wiki,\n SUM(Births) as wpp_count,\n 1e6 * SUM(count) / SUM(Births) AS ratio\n FROM notability\n WHERE year >= 1950 AND year < 1990 AND Alpha_3 != 'IOT'\n GROUP BY Name,Alpha_3,wiki\n`)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1455,"value":"$33","pinned":true,"hidden":false,"mode":"ojs"},{"id":1491,"value":"Plot.plot({\n marks: [\n Plot.dot(df_by_country, {\n x: (d) => d.ratio_en,\n y: (d) => d.ratio_fa,\n stroke: \"#462C7D\",\n fill: \"#831C91\",\n fillOpacity: 0.4,\n r: 5,\n tip: true,\n title: (d) =>\n `${d.Name} - ${d.Alpha_3}\\n ratio_en: ${d.ratio_en?.toFixed(\n 1\n )}\\n ratio_fa: ${d.ratio_fa?.toFixed(1)}`\n }),\n Plot.linearRegressionY(df_by_country, {\n x: (d) => d.ratio_en,\n y: (d) => d.ratio_fa,\n stroke: \"#D552A3\",\n strokeWidth: 1.5,\n ci: false\n })\n ],\n x: {\n type: \"log\",\n label: \"wikipedia — en\",\n tickFormat: (d) => d3.format(\"~r\")(d)\n },\n y: {\n type: \"log\",\n label: yCol.replace(\"ratio_\", \"wikipedia — \"),\n tickFormat: (d) => d3.format(\"~r\")(d)\n },\n height: 600,\n marginLeft: 60,\n marginRight: 60\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":1497,"value":"df_by_country","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W34","stdlib":"1","titling":"auto"}