25:["$","title",null,{"children":"Aging NBA players | Andrew Witherspoon | Observable"}] 49:T40c,Plot.plot({ height: 500, y: { ticks: [-8, -6, -4, -2, 0, 2, 4, 6, 8, 10, 12, 14], grid: true }, x: { ticks: [ "1970", "1975", "1980", "1985", "1990", "1995", "2000", "2005", "2010", "2015", "2020" ] }, color: { type: "threshold", domain: [0, 2, 4], range: ["#6cc5b0", "#ff725c", "#efb118", "#4269d0"], legend: true, label: "BPM" }, marks: [ Plot.ruleY([0]), Plot.dot( allAgesData.filter((f) => +f.Age < minAge), { channels: { name: "Player", age: "Age" }, x: (d) => d.Season.split("-")[0], y: (d) => parseFloat(d.BPM), opacity: 0.1, fill: "gray", tip: true } ), Plot.dot( allAgesData.filter((f) => +f.Age >= minAge), { channels: { name: "Player", age: "Age" }, x: (d) => d.Season.split("-")[0], y: (d) => parseFloat(d.BPM), opacity: 1, fill: (d) => d.BPM, tip: true } ) ] })4a:T401,Plot.plot({ height: 500, style: "overflow: visible;", color: { legend: true }, x: { domain: d3.range(18, 43) }, y: { domain: [-8, 12] }, marks: [ Plot.ruleY([0]), Plot.lineY(lebronData, { x: "age", y: (d) => (d.BPM ? d.BPM : NaN), z: "player", sort: "age", curve: "cardinal", stroke: (d) => d.player == "LeBron James" ? "red" : toHighlight.includes(d.player) ? "#121212" : "#ccc", raise: (d) => toHighlight.includes(d.player), opacity: (d) => d.player == "LeBron James" ? 1 : toHighlight.includes(d.player) ? 0.5 : 0.3, tip: true }), Plot.text( lebronData.filter((f) => toHighlight.includes(f.player)), Plot.selectLast({ x: "age", y: "BPM", z: "player", text: "player", textAnchor: "start", fill: (d) => (d.player == "LeBron James" ? "red" : "black"), dx: 3 }) ) ] })4b:T9dc,function makeAgetiers(data) { let seasons = d3.range( d3.min(data, (r) => +r.Season.split("-")[0]), d3.max(data, (r) => +r.Season.split("-")[0]) + 1 ); let final = []; let formatted = seasons.forEach((season, index) => { if (index > 4) { let smoothedYears = data.filter( (f) => +f.Season.split("-")[0] > season - 4 && +f.Season.split("-")[0] <= season ); let baby = { season, age: "18-22", number: data.filter( (f) => +f.Season.split("-")[0] == season && +f.Age <= 22 ).length, medianBPM: d3.median( data.filter((f) => +f.Season.split("-")[0] == season && +f.Age <= 22), (m) => +m.BPM ), smoothedMedianBPM: d3.median( smoothedYears.filter((f) => +f.Age <= 22), (m) => +m.BPM ) }; final.push(baby); let mid = { season, age: "23-27", number: data.filter( (f) => +f.Season.split("-")[0] == season && +f.Age > 22 && +f.Age <= 27 ).length, medianBPM: d3.median( data.filter( (f) => +f.Season.split("-")[0] == season && +f.Age > 22 && +f.Age <= 27 ), (m) => +m.BPM ), smoothedMedianBPM: d3.median( smoothedYears.filter((f) => +f.Age > 22 && +f.Age <= 27), (m) => +m.BPM ) }; final.push(mid); let vet = { season, age: "28-32", number: data.filter( (f) => +f.Season.split("-")[0] == season && +f.Age > 27 && +f.Age <= 32 ).length, medianBPM: d3.median( data.filter( (f) => +f.Season.split("-")[0] == season && +f.Age > 27 && +f.Age <= 32 ), (m) => +m.BPM ), smoothedMedianBPM: d3.median( smoothedYears.filter((f) => +f.Age > 27 && +f.Age <= 32), (m) => +m.BPM ) }; final.push(vet); let old = { season, age: "33+", number: data.filter( (f) => +f.Season.split("-")[0] == season && +f.Age > 33 ).length, medianBPM: d3.median( data.filter((f) => +f.Season.split("-")[0] == season && +f.Age > 33), (m) => +m.BPM ), smoothedMedianBPM: d3.median( smoothedYears.filter((f) => +f.Age > 32), (m) => +m.BPM ) }; final.push(old); } }); return final; }4c:T50f,function makeBPMtiers(data) { let seasons = d3.range( d3.min(data, (r) => +r.Season.split("-")[0]), d3.max(data, (r) => +r.Season.split("-")[0]) + 1 ); let final = []; let formatted = seasons.forEach((season) => { let replaceObj = { season, category: "replacement (<0 BPM)", val: data.filter( (f) => parseInt(f.Season.split("-")[0]) == season && parseFloat(f.BPM) < 0 ).length }; final.push(replaceObj); let avgObj = { season, category: "average (0-2 BPM)", val: data.filter( (f) => parseInt(f.Season.split("-")[0]) == season && parseFloat(f.BPM) > 0 && parseFloat(f.BPM) <= 2 ).length }; final.push(avgObj); let allstarObj = { season, category: "allstar (2-4 BPM)", val: data.filter( (f) => parseInt(f.Season.split("-")[0]) == season && parseFloat(f.BPM) > 2 && parseFloat(f.BPM) <= 4 ).length }; final.push(allstarObj); let allNBA = { season, category: "allnba (4+ BPM)", val: data.filter( (f) => parseInt(f.Season.split("-")[0]) == season && parseFloat(f.BPM) > 4 ).length }; final.push(allNBA); }); return final; 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29:{"id":"165c58a3ba927f5a","slug":null,"title":"Aging NBA players","thumbnail":"11a2df4b95375a4b00a2b023fecdcabdabfa8f803059d47dc09ed0dbdd7acd8b","access_level":"public","create_time":"$D2024-04-12T18:45:48.690Z","update_time":"$D2024-04-24T19:26:15.126Z","view_time":null,"first_public_time":"$D2024-04-12T18:45:48.690Z","has_unpublished_edits":null,"fork":{"id":"a7880e605a48e039","slug":null,"title":"Aging NBA players","owner":{"id":"e9d0700f86f0bd9d","login":"andrewwitherspoon","name":"Andrew Witherspoon"}},"stars":1,"starred":false,"owner":{"type":"team","id":"e9d0700f86f0bd9d","login":"andrewwitherspoon","name":"Andrew 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Witherspoon","avatar_url":"https://avatars-next.observableusercontent.com/8f490800810ce3ba1c52e327affe1547bdbad849dc781226bd105e2555362cd2","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Aging NBA players","cells":[{"id":0,"value":"# Aging NBA players\nLook at [Stathead Basketball data](https://stathead.com/basketball) to look into the performance of players as they age over time. \n\n**Links:**\n- [All players, 1979/80-2023/24, >500 min, by BPM](https://stathead.com/basketball/player-season-finder.cgi?request=1&draft_pick_type=overall&comp_type=reg&order_by=bpm&match=player_season&season_start=1&display_type=totals&season_end=-1&comp_id=NBA&year_min=1980&cstat[1]=mp&ccomp[1]=gt&cval[1]=500&offset=13800)\n- [HOF's 1973-74 by BPM](https://stathead.com/basketball/player-season-finder.cgi?request=1&order_by=bpm&is_hof=Y)\n- [BMP methodology](https://www.basketball-reference.com/about/bpm2.html)\n- [HOF probability](https://www.basketball-reference.com/leaders/hof_prob.html)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":5,"value":"***\n# Visualizations","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":615,"value":"### Number of players by age\n1979-80 to 2023-24 seasons, >500 min played","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":618,"value":"Plot.plot({\n color: { legend: true },\n marks: [\n Plot.ruleY([0]),\n Plot.lineY(ageData, {\n x: \"season\",\n y: \"number\",\n z: \"age\",\n stroke: \"age\",\n tip: true\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":625,"value":"### Older players were the only age group with a median BPM above 0 in 2023-24\nMedian BPM of NBA players, 1979-80 to 2023-24 seasons, >500 min played","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":668,"value":"Plot.plot({\n color: { legend: true },\n y: { ticks: [-2.5, -2, -1.5, -1, -0.5, 0, 0.5], domain: [-2.5, 0.75] },\n marks: [\n Plot.ruleY([0]),\n Plot.lineY(ageData, {\n channels: { \"Number of players\": \"number\" },\n x: \"season\",\n y: \"medianBPM\",\n z: \"age\",\n curve: \"natural\",\n stroke: \"age\",\n tip: true\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":799,"value":"### 2023-24 does stand out for the 33+ age bucket as a high performing year\nMedian BPM of NBA players, 1979-80 to 2023-24 seasons, >500 min played","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":753,"value":"Plot.plot({\n marginLeft: 50,\n padding: 0,\n // width: 350,\n x: { ticks: [1985, 1990, 1995, 2000, 2005, 2010, 2020] },\n y: { domain: [\"18-22\", \"23-27\", \"28-32\", \"33+\"], axis: \"left\" },\n color: { legend: true, scheme: \"RdBu\", reverse: true },\n marks: [\n Plot.cell(\n ageData,\n Plot.group(\n { fill: \"mean\" },\n {\n channel: { \"Number of players\": \"number\" },\n y: \"age\",\n x: \"season\",\n fill: \"medianBPM\",\n inset: 0.5,\n tip: true\n }\n )\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":819,"value":"### Below is a table of the players 33+ in 2023-24, sorted by BPM\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":815,"value":"allAgesData","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":666,"value":"### 5-year smoothed median BPM, to undo the spaghetti. Olds don't lead the pack, but in the avg for this season they're similar to the the more prime aged 23-27 and 28-32 buckets\nMedian BPM of NBA players, 1979-80 to 2023-24 seasons, >500 min played","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":628,"value":"Plot.plot({\n color: { legend: true },\n marks: [\n Plot.ruleY([0]),\n Plot.lineY(ageData, {\n channels: { \"Number of players\": \"number\" },\n x: \"season\",\n y: \"smoothedMedianBPM\",\n z: \"age\",\n stroke: \"age\",\n tip: true\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1041,"value":"Plot.plot({\n y: { grid: true },\n marks: [\n Plot.ruleY([0]),\n Plot.dot(bpm_2024, {\n channels: { player: \"Player\" },\n x: \"Age\",\n y: (d) => +d[\"BPM▼\"],\n fill: (d) => (+d.Age >= 33 ? \"red\" : \"#ccc\"),\n tip: true\n })\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":676,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":825,"value":"### Set minimum age for \"old\" players","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":544,"value":"viewof minAge = Inputs.range([18, 40], {\n label: \"Min age for 'old'\",\n step: 1,\n value: 33\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":652,"value":"The min age for old players is **${minAge}**. That is a group of **${\n allAgesData.filter((f) => +f.Age > minAge).length} player seasons** from 1979-80 to 2023-24 (out of ${formatNumber(allAgesData.length)} total player seasons, all ages, >500 min).\n \n The minimum BPM of that group is **${d3.min(\n allAgesData.filter((f) => +f.Age > minAge),\n (d) => +d.BPM\n)}**. The max is **${d3.max(\n allAgesData.filter((f) => +f.Age > minAge),\n (d) => +d.BPM\n)}**. The median is **${d3.median(\n allAgesData.filter((f) => +f.Age > minAge),\n (d) => +d.BPM\n)}**.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":378,"value":"### BPM of older players\nNumber of NBA players ${minAge} years old and up. 1979-80 to 2023-24 seasons, >500 min played. Younger players grayed out","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":290,"value":"$49","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":433,"value":"### The number and performance of all older NBA players\nNumber of NBA players ${minAge} years old and up. 1979-80 to 2023-24 seasons, >500 min played","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":446,"value":"Plot.plot({\n // y: { grid: true, ticks: [0, 5, 10, 15, 20, 25, 20, 30], domain: [0, 30] },\n x: {\n ticks: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020]\n },\n color: { legend: true },\n marks: [\n Plot.rectY(BPM_oldplayer_tiers, {\n x: \"season\",\n y: \"val\",\n fill: \"category\",\n tip: true\n }),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":476,"value":"### The number of above average older NBA players spiked in the mid 90's, and has remained above 4 a year\nNumber of NBA players ${minAge} years old and up. 1979-80 to 2023-24 seasons, >500 min","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":478,"value":"Plot.plot({\n y: { grid: true, domain: [0, 50] },\n x: {\n ticks: [1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020]\n },\n color: { legend: true },\n marks: [\n Plot.rectY(\n BPM_oldplayer_tiers.filter((f) => !f.category.includes(\"replacement\")),\n {\n x: \"season\",\n y: \"val\",\n fill: \"category\",\n tip: true\n }\n ),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":576,"value":"### The number of below average older NBA players has declined\nNumber of NBA players ${minAge} years old and up. 1979-80 to 2023-24 seasons, >500 min","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":578,"value":"Plot.plot({\n y: { grid: true, domain: [0, 50] },\n x: {\n ticks: [1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020]\n },\n color: { legend: true },\n marks: [\n Plot.rectY(\n BPM_oldplayer_tiers.filter((f) => f.category.includes(\"replacement\")),\n {\n x: \"season\",\n y: \"val\",\n fill: \"rgb(108, 197, 176)\",\n tip: true\n }\n ),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":363,"value":"allAgesData","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":956,"value":"### LeBron had the best season for an old player, ever\nBPM of Hall of Famers and active players at least 33 years old with a Basketball-Reference HOF projection over 90%. Note: BPM only available since 1973-74 seasons","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":852,"value":"$4a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":895,"value":"toHighlight = [\n \"Michael Jordan\",\n \"Kevin Durant\",\n // \"Chris Paul\",\n // \"Larry Bird\",\n // \"Tim Duncan\",\n \"Kobe Bryant\",\n // \"Karl Malone\",\n \"John Stockton\",\n \"LeBron James\",\n \"Dirk Nowitzki\",\n \"Stephen Curry\"\n // \"Kareem Abdul-Jabbar\",\n // \"Patrick Ewing\",\n // \"Grant Hill\"\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":910,"value":"lebronData.filter((f) => toHighlight.includes(f.player))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":9,"value":"***\n# Analysis","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":602,"value":"$4b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":611,"value":"ageData = makeAgetiers(allAgesData)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":399,"value":"$4c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":403,"value":"BPM_oldplayer_tiers = makeBPMtiers(allAgesData.filter((f) => +f.Age >= minAge))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":837,"value":"function combineHOF(arr, arr2) {\n let final = [];\n arr.forEach((d) => {\n let obj = {\n player: d.Player,\n season: d.Season,\n age: +d.Age,\n BPM: +d.BPM\n };\n final.push(obj);\n });\n arr2.forEach((d) => {\n let obj = {\n player: d.Player,\n season: d.Season,\n age: +d.Age,\n BPM: +d.BPM\n };\n final.push(obj);\n });\n return final;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":849,"value":"lebronData = combineHOF(hofData, modernHOF)\n .sort((a, b) => a.age - b.age)\n .sort((a, b) => a.player.localeCompare(b.player))\n .filter((f) => f.player !== \"Pat Riley\" && f.player !== \"George Karl\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":11,"value":"***\n# Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":525,"value":"allAgesData = FileAttachment(\"data-all_ages.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":833,"value":"hofData = FileAttachment(\"hof.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":835,"value":"modernHOF = FileAttachment(\"modern_players@2.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1043,"value":"bpm_2024 = FileAttachment(\"bpm_2024@1.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":13,"value":"***\n# Utilities","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":285,"value":"colors = [\n \"#0d0887\",\n \"#4c02a1\",\n \"#7e03a8\",\n \"#aa2395\",\n \"#cc4778\",\n \"#e66c5c\",\n \"#f89540\",\n \"#fdc527\",\n \"#f0f921\"\n].reverse()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":715,"value":"function formatNumber(x) {\n return x.toString().replace(/\\B(?=(\\d{3})+(?!\\d))/g, \",\");\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W4d","stdlib":"1"}} 24:null