31:[] 2f:{"title":"Questions and askers","cells":[{"id":0,"value":"md`# Questions and askers`","pinned":false,"hidden":false,"mode":"ojs"},{"id":6,"value":"viewof feedback = lever(`\n select \n f.fields->0->>'value' as rating,\n f.text,\n i.date,\n i.interviewers->0->>'name' as interviewer,\n f.fields\n from feedback f\n join interviews i on f.interview = i.id\n where text in ('Systems Design', 'Tech Phone Interview', 'Pair Eng Problem', 'Pair Eng w/ Hiring Manager') --, 'New Grad TPS', 'Intern TPS')\n -- where i.interviewers->0->>'name' = 'Josh Wang'\n and f.fields->0->>'value' is not null\n`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":294,"value":"md`## Questions\n\nHow are different questions rating candidates?`","pinned":false,"hidden":false,"mode":"ojs"},{"id":241,"value":"viewof interview = {\n const interviews = _.uniq(_.map(feedback.rows, 'text'))\n return html`\n \n `\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":29,"value":"{\n const y = { field: 'question', type: 'nominal', sort: { op: 'count', order: 'descending' } }\n const x = { aggregate: 'count', type: 'quantitative', stack: 'normalize' }\n\n return vegaEmbed({\n data: { values: withQuestions.filter(q => counts[q.question] > minCount) },\n layer: [{\n mark: 'bar',\n encoding: {\n x, y,\n color: { field: 'rating', type: 'ordinal', scale: { range: 'diverging' }, sort: 'descending' },\n }\n }, {\n mark: { type: 'text', dy: 4, dx: -2, align: 'right' },\n encoding: {\n x, y,\n text: { aggregate: 'count', type: 'quantitative' },\n detail: { field: 'rating', type: 'ordinal' },\n }\n }, {\n mark: 'rule',\n encoding: {\n x: { value: 100 },\n }\n }]\n })\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":375,"value":"md`### Over time\n\nHow have certain questions performed over time?`","pinned":false,"hidden":false,"mode":"ojs"},{"id":383,"value":"viewof questionByTime = html`\n \n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":415,"value":"vegaEmbed({\n data: { values: withQuestions.filter(q => !questionByTime || q.question === questionByTime) },\n mark: 'bar',\n height: 150,\n encoding: {\n x: { field: 'date', type: 'temporal', timeUnit: 'yearmonth' },\n y: { aggregate: 'count', type: 'quantitative' },\n color: { field: 'rating', type: 'ordinal', scale: { range: 'diverging', reverse: true } },\n },\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":378,"value":"vegaEmbed({\n data: { values: withQuestions.filter(q => !questionByTime || q.question === questionByTime) },\n mark: 'bar',\n height: 150,\n encoding: {\n x: { field: 'date', type: 'temporal', timeUnit: 'yearmonth' },\n y: { aggregate: 'count', type: 'quantitative', stack: 'normalize' },\n color: { field: 'rating', type: 'ordinal', scale: { range: 'diverging', reverse: true } },\n },\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":296,"value":"md`## Askers\n\nHow are different people rating candidates using the same question?`","pinned":false,"hidden":false,"mode":"ojs"},{"id":158,"value":"viewof questionByAsker = html`\n \n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":198,"value":"vegaEmbed({\n data: { values: withQuestions.filter(q => !questionByAsker || q.question === questionByAsker) },\n encoding: {\n x: { aggregate: 'count', type: 'quantitative', stack: 'normalize' },\n y: { field: 'interviewer', type: 'nominal', sort: { op: 'count', order: 'descending' } },\n },\n layer: [{\n mark: 'bar',\n encoding: {\n color: { field: 'rating', type: 'ordinal', scale: { range: 'diverging' }, sort: 'descending' },\n }\n }, {\n mark: { type: 'text', dy: 4, dx: -2, align: 'right' },\n encoding: {\n text: { aggregate: 'count', type: 'quantitative' },\n detail: { field: 'rating', type: 'ordinal' },\n }\n }, {\n mark: 'rule',\n encoding: {\n x: { value: 100 },\n y: null,\n }\n }]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":424,"value":"vegaEmbed({\n data: { values: withQuestions.filter(q => !questionByAsker || q.question === questionByAsker) },\n encoding: {\n x: { field: 'rating', type: 'ordinal', sort: 'descending' },\n y: { field: 'interviewer', type: 'nominal', sort: { op: 'count', order: 'descending' } },\n },\n layer: [{\n mark: 'square',\n encoding: {\n size: { aggregate: 'count', type: 'quantitative', legend: false },\n color: { field: 'rating', type: 'ordinal', scale: { range: 'diverging' }, sort: 'descending', legend: false },\n }\n }, {\n mark: { type: 'text', dy: 4, dx: 24, align: 'right' },\n encoding: {\n text: { aggregate: 'count', type: 'quantitative' },\n detail: { field: 'rating', type: 'ordinal' },\n }\n }]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":41,"value":"lever(`\n select text, count(*)\n from feedback\n group by 1\n order by 2 desc\n`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":15,"value":"withQuestions = _(feedback.rows)\n .filter(f => !interview || f.text === interview)\n .filter(f => _.some(f.fields, f => f.text === 'Question Asked' && f.value))\n .map(f => {\n let question = _.find(f.fields, f => f.text === 'Question Asked')\n switch (typeof(question.value)) {\n case 'string':\n question = question.value.toLowerCase()\n break\n case 'object':\n question = question.value[0] && question.value[0].toLowerCase()\n break\n }\n if (question)\n for (let key in corrections)\n if (question.match(key))\n question = corrections[key]\n \n return { ...f, question }\n })\n .value()","pinned":false,"hidden":false,"mode":"ojs"},{"id":218,"value":"corrections = ({\n other: 'other',\n spellcheck: 'spell check',\n markov: 'markov chain',\n babynames: 'baby names',\n autocomplete: 'autocomplete',\n webcrawler: 'web crawler',\n 'key value database': 'key value store',\n // 'speed limit': 'speed limit',\n // scrabble: 'scrabble',\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":95,"value":"counts = _.countBy(withQuestions, 'question')","pinned":false,"hidden":false,"mode":"ojs"},{"id":181,"value":"viewof minCount = html``","pinned":false,"hidden":false,"mode":"ojs"},{"id":176,"value":"questions = _(counts)\n .entries()\n .filter(([_, count]) => count > minCount)\n .map(0)\n .sort()\n .value()","pinned":false,"hidden":false,"mode":"ojs"},{"id":288,"value":"import { lever } from '@visnup/lever'","pinned":false,"hidden":false,"mode":"ojs"},{"id":448,"value":"vegaEmbed = require('vega-embed')","pinned":false,"hidden":false,"mode":"ojs"},{"id":17,"value":"_ = require('lodash')","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W31","stdlib":"1","titling":"auto"}