2c:null 2d:["$","title",null,{"children":"milestone report v1.9.0 | KyungYeol Kim | Observable"}] 32:Tb83,calendar = { // forked from https://beta.observablehq.com/@mbostock/d3-calendar-view const cellSize = 15 const width = 964 const height = cellSize * 9 const timeWeek = d3.timeSunday const countDay = d => d.getDay() const pathMonth = (t) => { const n = 7 const d = Math.max(0, Math.min(n, countDay(t))); const w = timeWeek.count(d3.timeYear(t), t); return `${d === 0 ? `M${w * cellSize},0` : d === n ? `M${(w + 1) * cellSize},0` : `M${(w + 1) * cellSize},0V${d * cellSize}H${w * cellSize}`}V${n * cellSize}`; } const formatDate = d3.timeFormat("%Y-%m-%d") const formatDay = d => "SMTWTFS"[d.getDay()] const formatMonth = d3.timeFormat("%b") const combined = actions.map(({createdAt}) => ({date: new Date(createdAt)})) const lookup = d3 .nest() .key((d) => formatDate(d.date)) .rollup((v) => v.length) .object(combined); const data = d3.timeDays(...d3.extent(combined, d => d.date)) .map(d => ({date: d, value: lookup[formatDate(d)] || 0})) const max = d3.max(data, d => d.value) const color = d3.scaleSequential(d3.interpolatePiYG) .domain([-max, max]) const years = d3.nest() .key(d => d.date.getFullYear()) .entries(data) .reverse(); const svg = d3.select(DOM.svg(width, height * years.length)) .style("font", "10px sans-serif") .style("width", "100%") .style("height", "auto"); const year = svg.selectAll("g") .data(years) .enter().append("g") .attr("transform", (d, i) => `translate(40,${height * i + cellSize * 1.5})`); year.append("text") .attr("x", -5) .attr("y", -5) .attr("font-weight", "bold") .attr("text-anchor", "end") .text(d => d.key); year.append("g") .attr("text-anchor", "end") .selectAll("text") .data(d3.range(7).map(i => new Date(1995, 0, i))) .enter().append("text") .attr("x", -5) .attr("y", d => (countDay(d) + 0.5) * cellSize) .attr("dy", "0.31em") .text(formatDay); year.append("g") .selectAll("rect") .data(d => d.values) .enter().append("rect") .attr("width", cellSize - 1) .attr("height", cellSize - 1) .attr("x", d => timeWeek.count(d3.timeYear(d.date), d.date) * cellSize + 0.5) .attr("y", d => countDay(d.date) * cellSize + 0.5) .attr("fill", d => color(d.value)) .append("title") .text(d => `${formatDate(d.date)}: ${d.value}`); const month = year.append("g") .selectAll("g") .data(d => d3.timeMonths(d3.timeMonth(d.values[0].date), d.values[d.values.length - 1].date)) .enter().append("g"); month.filter((d, i) => i).append("path") .attr("fill", "none") .attr("stroke", "#fff") .attr("stroke-width", 3) .attr("d", pathMonth); month.append("text") .attr("x", d => timeWeek.count(d3.timeYear(d), timeWeek.ceil(d)) * cellSize + 2) .attr("y", -5) .text(formatMonth); return svg.node(); }33:[{"id":"b9467bf43b9f8282be74f712450fdee6509db4a5aae3dd19f53d58313cfb3b7402368933c344b1bebd3141f6d4f1359e452573840bd18780315e96c5a27f733f","href":"https://static.observableusercontent.com/files/b9467bf43b9f8282be74f712450fdee6509db4a5aae3dd19f53d58313cfb3b7402368933c344b1bebd3141f6d4f1359e452573840bd18780315e96c5a27f733f","name":"data.json","type":"application/json","lastModified":1585751229596.104,"size":364399}] 30:{"id":"648f1dddc9d45eb3","slug":"milestone-report-v1-9-0","title":"milestone report v1.9.0","thumbnail":"6de3556c3642c5b78a7398d5107a8d811204b0db5a6edd300f810aba68532922","access_level":"public","create_time":"$D2018-06-25T15:53:53.360Z","update_time":"$D2022-04-24T07:06:21.918Z","view_time":null,"first_public_time":"$D2018-07-04T08:53:46.786Z","fork":true,"stars":2,"starred":false,"owner":{"type":"team","id":"56a62604da372f41","login":"chitacan","name":"KyungYeol Kim","avatar_url":"https://avatars-next.observableusercontent.com/ebe2bc4618021a6392db1d0169bbe2af3520871861d6f0659384f97da78200ce","tier":"starter_2024"},"version":843,"publish_version":843,"role":null,"authored":false,"authors":[{"type":"individual","id":"e4a45eb07cd703f7","login":"chitacan","name":"KyungYeol Kim","avatar_url":"https://avatars-next.observableusercontent.com/ebe2bc4618021a6392db1d0169bbe2af3520871861d6f0659384f97da78200ce","tier":null}],"members":[{"type":"individual","id":"e4a45eb07cd703f7","login":"chitacan","name":"KyungYeol Kim","avatar_url":"https://avatars-next.observableusercontent.com/ebe2bc4618021a6392db1d0169bbe2af3520871861d6f0659384f97da78200ce","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"subscribed":null,"forks":4,"collection":{"id":"6d39e1a0c0d88bcd","slug":"blog","title":"Blog","owner":{"id":"56a62604da372f41","login":"chitacan","name":"KyungYeol Kim"}},"type":"notebook","body":{"title":"milestone report v1.9.0","cells":[{"id":0,"value":"md`# milestone report v1.9.0\n\n*${icon({text: 'subscribe me'})}*\n\n마일스톤 ${data.title} 는 ${dayCount} 일 동안 진행되었으며, ${authors.length} 명의 \\`riiider\\` 가 협업하여 ${data.issues.totalCount} 개의 issue 와 ${data.pullRequests.totalCount} 개의 pull request 를 처리했습니다.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":162,"value":"table([\n ...data.issues.nodes,\n ...data.pullRequests.nodes\n]\n.map(({number, title, comments, state}) => ({title, number, comments: comments.totalCount, state}))\n.sort((a, b) => b.comments - a.comments), {\n sortable: true,\n compact: true,\n columns: {\n state: {\n formatter(v) {\n switch (v) {\n case 'OPEN':\n return html`${v}`\n case 'CLOSED':\n return html`${v}`\n case 'MERGED':\n return html`${v}`\n }\n }\n },\n number: {\n title: '#',\n formatter(v) {\n return html`${v}`\n }\n }\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":588,"value":"md`${hl('주영님')}이 가장 많은 6개의 pull request 를 등록해주셨습니다. ${hl('혜림님')}이 생성한 이슈들이 이번 버전에 가장 많이 반영되었습니다.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":87,"value":"vl({\n data: {\n values: issues\n },\n hconcat: [{\n mark: 'bar',\n encoding: {\n x: {field: 'name', type: 'nominal'},\n y: {field: '*', aggregate: 'count', type: 'quantitative', axis: {title: 'number of issues'}}\n }\n }, {\n mark: 'bar',\n encoding: {\n x: {field: 'name', type: 'nominal'},\n y: {field: '*', aggregate: 'count', type: 'quantitative', axis: {title: 'number of issues'}},\n color: {field: 'type', type: 'nominal', scale: {scheme: 'accent'}}\n }\n }]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":592,"value":"md`${hl('순우님')}이 이번 버전에서 가장 많은 코멘트를 작성해 주셨습니다. 개발팀 보다도 더 적극적으로 코멘트를 작성해 주신 분들이 돋보입니다. 🙇‍`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":122,"value":"vl({\n data: {\n values: comments\n },\n mark: 'bar',\n encoding: {\n x: {field: 'name', type: 'nominal'},\n y: {field: '*', aggregate: 'count', type: 'quantitative', axis: {title: 'number of comments'}}\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":608,"value":"md`코멘트가 가장 활발했던 이슈는 #677 과 #522 pull request 였습니다. 둘다 ${hl('주영님')}이 작성하였고, 7명 이상의 분들로 부터 피드백을 받았습니다. 버전 준비 pull request 인 #640 을 제외하면, ${hl('주영님')}의 pull request 들이 가장 많은 코멘트를 받았습니다.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":406,"value":"vl({\n data: {\n values: comments\n },\n mark: 'bar',\n encoding: {\n x: {field: 'number', type: 'nominal', axis: {title: 'issue number'}},\n y: {field: '*', aggregate: 'count', type: 'quantitative', axis: {title: 'number of comments'}},\n color: {field: 'name', type: 'nominal', scale: {scheme: 'paired'}}\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":602,"value":"vl({\n width: width / 2,\n data: {\n values: issues\n },\n mark: 'point',\n encoding: {\n x: {field: 'comments', type: 'quantitative', axis: {title: 'number of comments'}},\n color: {value: 'red'},\n opacity: {value: .4}\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":612,"value":"md`${data.title} 에서 가장 많이 사용된 리액션은 👍 였습니다. 긍정적인 리액션들이 많이 사용된 것은 좋은 징조지만, 부정적(👎) 또는 중립적인(😕) 리액션들이 전혀 사용되지 않은 부분에 대한 의견이 궁금합니다. 👍 를 가장 많이 날린(남발한) 사람은 ${hl('경열님')}이었습니다. 🤔`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":289,"value":"vl({\n data: {\n values: reactions\n },\n hconcat: [{\n mark: 'bar',\n encoding: {\n x: {\n field: 'content',\n type: 'nominal',\n axis: {title: 'emoji'}\n },\n y: {\n field: '*',\n aggregate: 'count',\n type: 'quantitative',\n axis: {title: 'number of reactions'}\n }\n }\n }, {\n mark: 'bar',\n encoding: {\n x: {field: 'name', type: 'nominal'},\n y: {field: '*', aggregate: 'count', type: 'quantitative', axis: {title: 'number of reactions'}},\n color: {field: 'content', type: 'nominal', scale: {scheme: 'accent'}}\n }\n }]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":621,"value":"md`버전 준비와 관련된 #640, #665 를 제외하고 가장 많은 👍 리액션을 받은 이슈는 #522 (issue-363 고객센터에 이벤트 탭을 생성한다.) 였습니다. 다양한 의견이 코멘트로 작성되면서, 리액션도 가장 많이 이루어졌다고 판단됩니다.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":331,"value":"vl({\n data: {\n values: reactions\n },\n hconcat: [{\n mark: 'bar',\n encoding: {\n x: {field: 'number', type: 'nominal', axis: {title: 'issue number'}},\n y: {field: '*', aggregate: 'count', type: 'quantitative', axis: {title: 'number of reactions'}},\n color: {field: 'content', type: 'nominal', scale: {scheme: 'accent'}}\n }\n }, {\n mark: 'bar',\n encoding: {\n x: {field: 'author', type: 'nominal', axis: {title: 'author'}},\n y: {field: '*', aggregate: 'count', type: 'quantitative', axis: {title: 'number of reactions'}},\n color: {field: 'content', type: 'nominal', scale: {scheme: 'accent'}}\n }\n }]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":657,"value":"md`리뷰의 갯수와 커밋의 갯수의 그래프는 상당히 유사한 것을 볼 수 있습니다. 둘의 상관관계를 계산해보니 실제로 아주 강한 양의 상관관계(*${corr}*)가 있음을 확인할 수 있었습니다. 리뷰를 가장 많이 받고 작성한 \\`riiider\\`는 (역시...) ${hl('주영님')} 이었습니다.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":346,"value":"vl({\n data: {\n values: data.pullRequests.nodes.map(({number, reviews, commits}) => ({number, reviews: reviews.totalCount, commits: commits.totalCount}))\n },\n hconcat: [{\n mark: 'bar',\n encoding: {\n x: {field: 'number', type: 'nominal', axis: {title: 'pull request'}},\n y: {field: 'reviews', type: 'quantitative', axis: {title: 'number of reviews'}}\n }\n }, {\n mark: 'bar',\n encoding: {\n x: {field: 'number', type: 'nominal', axis: {title: 'pull request'}},\n y: {field: 'commits', type: 'quantitative', axis: {title: 'number of commits'}}\n }\n }]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":384,"value":"vl({\n data: {\n values: reviews\n },\n mark: 'bar',\n encoding: {\n x: {field: 'name', type: 'nominal'},\n y: {field: '*', type: 'quantitative', aggregate: 'count', axis: {title: 'number of reviews'}},\n color: {field: 'state', scale: {scheme: 'accent'}}\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":676,"value":"md`issue & pull request 생성, 코멘트 작성, 리액션 갯수를 날짜별로 모아보니, \\`riiid/www\\` 저장소에서 피드백이 가장 활발하게 이루어지는 날은 수요일 또는 목요일인 걸로 나타났습니다. 이걸 잘 염두해서 pull request 를 등록하면 좀 더 빠른 리뷰를 진행할 수 있지 않을까 생각합니다.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":508,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":752,"value":"md`유저별로 버전에 기여한 형태(\\`comment\\`, \\`issue\\`, \\`pull request\\`, \\`reaction\\`)를 모아보면, ${hl('주영님')}, ${hl('경열님')}, ${hl('순현님')}, ${hl('순우님')} 순으로 많은 기여를 하고 있는 것을 확인할 수 있습니다. 분석전에는 이모지 리액션의 순위가 높을거라 생각했는데, 코멘트와 리뷰가 더 많이 활용되고 있는 부분이 고무적입니다. 이번에는 버전에 포함이 결정된 issue, pull request 항목들을 분석했는데, 마일스톤 기간에 생성된 issue, pull request 도 포함이되어야 다양한 기여 형태를 반영할 수 있다는 생각이 들었습니다.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":733,"value":"vl({\n data: {\n values: actions\n },\n hconcat: [{\n mark: 'bar',\n encoding: {\n x: {field: 'name', type: 'nominal'},\n y: {field: '*', type: 'quantitative', aggregate: 'count', axis: {title: 'number of actions'}},\n color: {field: 'type', scale: {scheme: 'accent'}}\n }\n }, {\n mark: 'bar',\n encoding: {\n x: {field: 'type', type: 'nominal'},\n y: {field: '*', type: 'quantitative', aggregate: 'count', axis: {title: 'number of actions'}},\n color: {field: 'name', scale: {scheme: 'accent'}}\n }\n }],\n resolve: {scale: {color: 'independent'}}\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":723,"value":"corr = {\n const d = data.pullRequests.nodes.map(({number, reviews, commits}) => ({number, reviews: reviews.totalCount, commits: commits.totalCount})).filter(d => d.number !== 640)\n return correlation(d, 'reviews', 'commits').toFixed(2)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":737,"value":"actions = [...issues, ...comments, ...reviews, ...reactions]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":115,"value":"comments = _.chain([...data.issues.nodes, ...data.pullRequests.nodes])\n .map(({comments, number}) => comments.nodes.map(d => ({number, ...d})))\n .flatten()\n .map(({author, createdAt, number}) => ({...author, createdAt, number, type: 'comment'}))\n .map(d => d.name ? d : {...d, name: d.login})\n .filter(d => d.name)\n .value()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":77,"value":"authors = _.chain([...data.issues.nodes, ...data.pullRequests.nodes])\n .map(({author, comments}) => [author.name, ...comments.nodes.map(d => d.author.name)])\n .flatten()\n .filter()\n .uniq()\n .value()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":88,"value":"issues = [\n ...data.issues.nodes.map(({author, number, comments, createdAt}) => ({...author, type: 'issue', number, comments: comments.totalCount, createdAt})),\n ...data.pullRequests.nodes.map(({author, number, comments, createdAt}) => ({...author, type: 'pull requests', number, comments: comments.totalCount, createdAt}))\n].map(d => d.name ? d : {...d, name: d.login})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":265,"value":"reactions = _.chain([\n ...data.issues.nodes,\n ...data.pullRequests.nodes\n])\n.map(({reactions, comments, number, author}) => [\n ...reactions.nodes.map(d => ({...d, number, author: author.name})),\n ...comments.nodes.map(d => d.reactions.nodes.map(d => ({...d, number, author: author.name})))\n])\n.flattenDeep()\n.map(({content, number, user, createdAt, author}) => ({content: emoji(content), number, name: user.name, createdAt, author, type: 'reaction'}))\n.value()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":614,"value":"emoji = content => {\n switch(content) {\n case 'HEART':\n return '❤️'\n case 'THUMBS_UP':\n return '👍'\n case 'LAUGH':\n return '😄'\n case 'HOORAY':\n return '🎉'\n case 'CONFUSED':\n return '😕'\n case 'THUMBS_DOWN':\n return '👎'\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":376,"value":"reviews = _.chain(data.pullRequests.nodes)\n .map('reviews.nodes')\n .flatten()\n .map(({state, author, createdAt}) => ({...author, state, createdAt, type: 'review'}))\n .map(d => d.name ? d : {...d, name: d.login})\n .value()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":266,"value":"dayCount = d3.timeDay.count(new Date(data.createdAt), new Date(data.closedAt))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":23,"value":"data = await FileAttachment(\"data.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":664,"value":"correlation = (data, keyX, keyY) => {\n const x = _.map(data, keyX)\n const y = _.map(data, keyY)\n \n const sumX = _.reduce(x, (acc, v) => acc + v, 0)\n const sumY = _.reduce(y, (acc, v) => acc + v, 0)\n \n const sumX2 = _.reduce(x, (acc, v) => acc + v * v, 0)\n const sumY2 = _.reduce(y, (acc, v) => acc + v * v, 0)\n const sumXY = _.reduce(x, (acc, v, i) => acc + v * y[i], 0)\n \n const n = data.length\n const ntor = sumXY - (sumX * sumY / n)\n const dtorX = sumX2 - (sumX * sumX / n)\n const dtorY = sumY2 - (sumY * sumY / n)\n \n const r = ntor / Math.sqrt(dtorX * dtorY)\n return r\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":832,"value":"import {icon} from '@chitacan/rss'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":8,"value":"_ = require('lodash')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":6,"value":"d3 = require(\"d3@5\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":817,"value":"hl = name => `${name}`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":85,"value":"vl = require(\"vega-embed@3\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":160,"value":"import {table} from \"@tmcw/tables\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2,"value":"import {slider} from '@jashkenas/inputs'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 31:"$30:body"