3f:null 40:["$","title",null,{"children":"🍕 Pizzeria Observable | Patrik Plesky | Observable"}] 46:[] 44:{"id":"5e31246ea3e0308e","slug":"pizzeria-observable","title":"🍕 Pizzeria Observable","thumbnail":"a6ed931cb3107f7b75e755fa49047ef11df0ad48625969de9a9e378f4ebec571","access_level":"public","create_time":"$D2023-03-26T10:33:29.246Z","update_time":"$D2023-04-06T19:26:09.408Z","view_time":null,"first_public_time":"$D2023-03-30T16:23:03.730Z","has_unpublished_edits":null,"fork":true,"stars":0,"starred":false,"owner":{"type":"team","id":"ba38878a90770345","login":"pplesky","name":"Patrik Plesky","avatar_url":"https://avatars-next.observableusercontent.com/d5a9726b6a437f58cdd6322368c7aea8033760a90ef3c4132ffa843c1fa32f82","tier":"starter_2024","bio":"","following":false},"version":573,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"99963bdc7bcca746","login":"pplesky","name":"Patrik Plesky","avatar_url":"https://avatars-next.observableusercontent.com/d5a9726b6a437f58cdd6322368c7aea8033760a90ef3c4132ffa843c1fa32f82","tier":null,"bio":"","following":false}],"members":[{"type":"individual","id":"99963bdc7bcca746","login":"pplesky","name":"Patrik Plesky","avatar_url":"https://avatars-next.observableusercontent.com/d5a9726b6a437f58cdd6322368c7aea8033760a90ef3c4132ffa843c1fa32f82","tier":null,"role":"editor"}],"comments":[{"id":"46f5b0c11ed063e7","reply_to_id":null,"content":"Nice, good choice on the color schemes! Pie charts would have been totally appropriate in this case, though :D","create_time":"$D2023-04-17T23:41:54.870Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"ce771552211c04ab","login":"rkosara","name":"Robert Kosara","avatar_url":"https://avatars-next.observableusercontent.com/105903f7d3ac285a1489b547eecce8f57bd15052862a307c4c2242f847d44a67","tier":null}}],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"🍕 Pizzeria Observable","cells":[{"id":0,"value":"# 🍕 Pizzeria Observable","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":344,"value":"Tasks:\n1. compare performance of CA vs. NV branches during the period\n2. how well various pizza categories perform during the period\n3. compare performance on a day-of-week basis\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":500,"value":"### Data Set ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":13,"value":"data","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":392,"value":"## Task 1 - CA vs. NV Performance","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":394,"value":"First, a chart comparing CA vs. NV branches by month (while also testing facets) was created:\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":396,"value":"Plot.plot({\n grid: true,\n color: { scheme: \"blues\" },\n margin: 100,\n x: { tickRotate: -45 },\n facet: { data: pizzaorders, y: \"state\", marginRight: 90 },\n marks: [\n Plot.barY(\n pizzaorders,\n Plot.groupX(\n { y: \"sum\" },\n {\n x: (d) => d3.utcMonth(d.orderDate),\n y: \"total\",\n fill: \"state\"\n }\n )\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":403,"value":"The performance seems to be very closely related - while visually comparing the data, the Nevada branch always makes about 1/3 of the California revenue. Let us try to make a rough estimate by dividing CA/NV revenue:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":73,"value":"nv_total = pizzaorders\n .filter((d) => d.state == \"NV\")\n .reduce((acc, v) => acc + v.total, 0)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":76,"value":"ca_total = pizzaorders\n .filter((d) => d.state == \"CA\")\n .reduce((acc, v) => acc + v.total, 0)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":82,"value":"factor = ca_total / nv_total","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":413,"value":"Next, I tried to simply multiply NV revenue by the calculated factor and displayed it in the chart. Clearly, the data are almost linearly dependent.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":115,"value":"Plot.plot({\n grid: true,\n margin: 100,\n color: { scheme: \"blues\" },\n x: { tickRotate: -90 },\n y: { tickRotate: -45 },\n facet: {\n data: data,\n x: (d) => d.orderDate.toISOString().substring(5, 7),\n margin: 10,\n labelRotate: -90\n },\n marks: [\n Plot.barY(\n data,\n Plot.groupX(\n { y: \"sum\" },\n {\n x: \"state\",\n y: \"total\",\n fill: \"state\"\n }\n )\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":440,"value":"To dive deeper into this relationship, a scatter plot has been created to compare CA vs. NV performance of various pizza categories on each day.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":198,"value":"Plot.plot({\n grid: true,\n color: { legend: true },\n marginLeft: 100,\n marks: [\n Plot.frame(),\n Plot.dot(CA_vs_NV, {\n x: \"CA\",\n y: \"NV\",\n title: (d) => `${d.date}\\n${d.category}`,\n stroke: \"category\",\n r: 1,\n opacity: 0.8\n }),\n Plot.linearRegressionY(CA_vs_NV, {\n x: \"CA\",\n y: \"NV\",\n stroke: \"steelblue\",\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":442,"value":"Here, we can see that this close relationship holds even across the pizza portfolio.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":444,"value":"

Conclusion 1

\n Revenue of the Nevada branch is about 1/3 of the California branch revenue - not only on a month level, but also on each date and for each pizza category\n

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":454,"value":"## Task 2 - Pizza Categories - Performance Comparison","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":467,"value":"Here, the area chart with offset = \"expand\" has been used to show the share of the revenues for each pizza category on each day in the period:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":217,"value":"{\n const xy = {\n x: \"orderDate\",\n y: \"total\",\n fill: \"category\",\n offset: \"expand\"\n };\n return Plot.plot({\n y: {\n grid: true,\n label: \"↑ Share\"\n },\n marks: [\n Plot.areaY(ordersByCategory, Plot.stackY({ ...xy })) /*,\n Plot.lineY(\n ordersByCategory,\n Plot.stackY2({ ...xy, stroke: \"white\", strokeWidth: 1 })\n ),\n Plot.ruleY([0])*/\n ],\n color: { legend: true }\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":471,"value":"

Conclusion 2

\n The performance of the pizza categories is more or less the same across the period. No major developments here.\n

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":100,"value":"## Task 3 - Days of Week - Performance Comparison","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":502,"value":"Another interesting point of view might be comparing performance on a day-of-week basis. Used a stacked bar chart to see the overall result and the performance of pizza categories on each day:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":335,"value":"{\n const xy = {\n x: d => [\"0 (Sun)\",\"1 (Mon)\",\"2 (Tue)\",\"3 (Wed)\",\"4 (Thu)\",\"5 (Fri)\",\"6 (Sat)\"][d.day_of_week],\n y: \"total\",\n fill: \"category\",\n marginLeft: 100,\n };\n return Plot.plot({\n y: {\n grid: true,\n label: \"↑ Revenue\"\n },\n marks: [Plot.barY(revenueByDay, Plot.stackY({ ...xy }))],\n color: { legend: true }\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":504,"value":"

Conclusion 3

In terms of revenue, Saturday, Sunday and Friday are the top three days of week.

Performance on Monday - Thursday is flat.

Relative performance of pizza categories is more or less the same on each day.

\nPizza image:
\nhttps://commons.wikimedia.org/wiki/File:20200719_180910_Suduch_Pizza,_Pizzeria_Yoav_Tel_Aviv_anagoria.jpg\n
Anagoria, CC BY 3.0 , via Wikimedia Commons\n

\n## Internals","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":5,"value":"import {pizzaorders} from \"@observablehq/data-vis-course-assignment\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":10,"value":"data = pizzaorders.map((d) => ({\n ...d,\n total: d.state == \"NV\" ? factor * d.total : d.total\n}))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":183,"value":"import { aq, op } from \"@uwdata/arquero\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":150,"value":"Object.entries(\n _.groupBy(\n pizzaorders.map((d) => ({\n ...d,\n date: d.orderDate.toISOString().substring(0, 10)\n })),\n \"date\"\n )\n).flatMap((entry) => {\n let [d, records] = entry;\n let results_state = _.groupBy(records, \"state\");\n return Object.entries(results_state).map((rec) => ({\n date: d,\n state: rec[0],\n total: rec[1].reduce((acc, v) => acc + v.total, 0)\n }));\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":170,"value":"orders = aq.from(\n pizzaorders.map((rec) => ({\n ...rec,\n date: rec.orderDate.toISOString().substring(0, 10)\n }))\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":189,"value":"CA_vs_NV = orders\n .groupby(\"date\", \"category\")\n .pivot(\"state\", { revenue: op.sum(\"total\") })\n .objects()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":331,"value":"revenueByDay = aq\n .from(pizzaorders)\n .groupby(\"day_of_week\", \"category\")\n .rollup({ total: op.sum(\"total\") })\n .orderby(\"day_of_week\", \"category\")\n .objects()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":225,"value":"ordersByCategory = aq\n .from(pizzaorders)\n .groupby(\"orderDate\", \"category\")\n .rollup({ total: op.sum(\"total\") })\n .orderby(\"orderDate\", \"category\")\n .objects()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":347,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"}],"files":"$W46","stdlib":"1"}} 45:"$44:body"