2d:null 2e:["$","title",null,{"children":"📑 CSV Reading 2 | Olga Belitskaya | Observable"}] 33:[] 31:{"id":"eba4095024e11705","slug":"csv-reading-2","title":"📑 CSV Reading 2","thumbnail":"d692c1811eca2280cc3f3707af186b8f9833b761eccba26c8e4d753bfac3cd37","access_level":"public","create_time":"$D2023-12-03T04:24:32.350Z","update_time":"$D2023-12-03T20:59:43.209Z","view_time":null,"first_public_time":"$D2023-12-03T04:24:32.350Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"98198089abd4b9a8","login":"olgabelitskaya","name":"Olga Belitskaya","avatar_url":"https://avatars-next.observableusercontent.com/efc5a1fdd47c22643bdfdce309fc023e67a3769736526e3805f1df287d3c1b68","tier":"starter_2024"},"version":279,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"f76f5ed10936f426","login":"olgabelitskaya","name":"Olga Belitskaya","avatar_url":"https://avatars-next.observableusercontent.com/efc5a1fdd47c22643bdfdce309fc023e67a3769736526e3805f1df287d3c1b68","tier":null}],"members":[{"type":"individual","id":"f76f5ed10936f426","login":"olgabelitskaya","name":"Olga Belitskaya","avatar_url":"https://avatars-next.observableusercontent.com/efc5a1fdd47c22643bdfdce309fc023e67a3769736526e3805f1df287d3c1b68","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"📑 CSV Reading 2","cells":[{"id":0,"value":"# 📑 CSV Reading 2","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":11,"value":"

Data Loading

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":7,"value":"url = 'https://raw.githubusercontent.com/OlgaBelitskaya/' + \n 'machine_learning_engineer_nd009/master/' +\n 'Machine_Learning_Engineer_ND_P3/customers.csv';","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"customers = d3.csv(url, d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":175,"value":"Inputs.table(customers, {rows: 5})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":74,"value":" product_lst = ['Fresh', 'Milk', 'Grocery', 'Frozen', 'Detergents_Paper', 'Delicatessen']","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":165,"value":"viewof product = Inputs.select(product_lst, {value: \"Fresh\", label: \"product\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":61,"value":"

Histograms

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":125,"value":"Plot.plot({\n y: {grid: true},\n marks: [\n Plot.rectY(customers.map(d => Math.log(d[product])), \n Plot.binX({ y: \"count\", fill: \"count\"})),\n Plot.ruleY([0])\n ],\n color: {scheme: \"Cool\", legend: true},\n title: 'The Histogram for Logarithmic Values for the Column: ' + product,\n height: 400,\n width: 900\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":269,"value":"

Box Plots

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":251,"value":"Plot.plot({\n marks: [Plot.boxY(customers, {x: \"Channel\", y: product, fill: \"Channel\", opacity: .7})],\n y: {domain: [0, 50000]},\n color: {scheme: \"Cool\"},\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":83,"value":"

Area Plots

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":70,"value":"Plot.plot({\n marks: [\n Plot.ruleY([0]),\n Array.from({length: 6}, (_, i) => {\n return Plot.areaY(customers, {y: product_lst[i], fill: i+1, opacity: 1-.05*i})})\n ],\n color: {scheme: \"Turbo\", domain: [0, 7]},\n height: 400,\n width: 900\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":244,"value":"

Density Plots

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":199,"value":"Plot.density(customers, {x: \"Milk\", y: \"Fresh\", stroke: \"Channel\"}).plot({\n x: {domain: [-1000, 18000]}, \n y: {domain: [-3000, 50000]},\n color: {scheme: \"Cool\"},\n style: {paddingBottom: 20}\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":278,"value":"d3 = require('d3@7')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 32:"$31:body"