3f:null 40:["$","title",null,{"children":"NotebookTitle | PQI Queryous Templates | Observable"}] 46:[] 44:{"id":"4c64412ef0575941","slug":"notebook-template","title":" NotebookTitle ","thumbnail":"ad80eb20a35771b6ebfbdf12c404a2b38f1baf64ec5eee6a89305387723db8eb","access_level":"public","create_time":"$D2023-10-27T06:45:06.754Z","update_time":"$D2023-10-28T12:16:22.949Z","view_time":null,"first_public_time":"$D2023-10-27T06:45:06.754Z","has_unpublished_edits":null,"fork":false,"stars":1,"starred":false,"owner":{"type":"team","id":"8535cc563d5b77a4","login":"pbiqueryous-templates","name":"PQI Queryous Templates","avatar_url":"https://avatars-next.observableusercontent.com/e3a2189fd81678648eff738d75076b3733798cad11fd9bdd3c061359ff64372d","tier":"starter_2024","bio":"","following":false},"version":198,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"095ccf69e3466ab9","login":"pbi-queryous","name":"PBI Queryous","avatar_url":"https://avatars-next.observableusercontent.com/0e362e0326315a8b72bf30cfe2bf107a47fb597d0f8798eeb7f6330b2bbb725a","tier":null,"bio":"","following":false}],"members":[{"type":"individual","id":"095ccf69e3466ab9","login":"pbi-queryous","name":"PBI Queryous","avatar_url":"https://avatars-next.observableusercontent.com/0e362e0326315a8b72bf30cfe2bf107a47fb597d0f8798eeb7f6330b2bbb725a","tier":null,"role":"editor"},{"type":"team","id":"8535cc563d5b77a4","login":"pbiqueryous-templates","name":"PQI Queryous Templates","avatar_url":"https://avatars-next.observableusercontent.com/e3a2189fd81678648eff738d75076b3733798cad11fd9bdd3c061359ff64372d","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":3,"collection":{"id":"82c612f588f72b41","slug":"collection-of-templates","title":"Collection of Templates","owner":{"id":"8535cc563d5b77a4","login":"pbiqueryous-templates","name":"PQI Queryous Templates"}},"type":"notebook","body":{"titling":"auto","title":" NotebookTitle ","cells":[{"id":0,"value":"# **NotebookTitle**
\n _NotebookSubtitle_","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":11,"value":"md`🧙‍♂️ [GitHub Repos](https://github.com/PBIQueryous) | 🕊️ [Twitter](https://twitter.com/PBIQueryous)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"---\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":59,"value":"contents(\"h1, h2, h3\", \"My Table of Contents\", true)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":62,"value":"indenttoc({\n headers: \"h2,h3,h4,h5,h6\",\n title: \"My ToC\",\n skip: [\"Template Header\", \"Hidden-Sub-header\"],\n hideStartingFrom: \"Appendix\"\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":154,"value":"

\n
\n# Level 1\n## Level 2\n### Level 3\n#### Level 4\n##### Level 5\n###### Level 6","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":125,"value":"mdhl` \n##

Level2Header\n### Level3Header\n\nWe can also utilise Vega's data repository from Github...\n\n~~~js \n • vegaData = require(\"vega-datasets@1\", \"vega-datasets@2\") // import vega_datasets \n~~~\n\n...and then select a dataset\n\n~~~js\n • exampleDataCars = vegaData[\"cars.json\"]() // load and parse cars data\n~~~\n\n...and display the top, slicing for the top 20 rows\n\n~~~js\n • show(exampleDataCars.slice(0, 20))\n • exampleDataCars = vegaData[\"cars.json\"]() // load and parse cars data\n~~~\n${show(exampleDataCars.slice(0, 20), undefined, \"*\")}\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":153,"value":"mdhl`\nInputDummyData - formatted markdown:\n\n~~~js\n\"data\": {\n \"values\": [\n {\"Column1\": \"A\", \"Column2\": 28}, {\"Column1\": \"B\", \"Column2\": 55}, {\"Column1\": \"C\", \"Column2\": 43}, \n {\"Column1\": \"D\", \"Column2\": 91}, {\"Column1\": \"E\", \"Column2\": 81}, {\"Column1\": \"F\", \"Column2\": 53},\n {\"Column1\": \"G\", \"Column2\": 19}, {\"Column1\": \"H\", \"Column2\": 87}, {\"Column1\": \"I\", \"Column2\": 52}\n ]\n}\n~~~\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":152,"value":"
\nDummyText","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":151,"value":"dataObject = // \"data\": {\n\n/* \"values\" */ [\n { Column1: \"A\", Column2: 28 },\n { Column1: \"B\", Column2: 55 },\n { Column1: \"C\", Column2: 43 },\n { Column1: \"D\", Column2: 91 },\n { Column1: \"E\", Column2: 81 },\n { Column1: \"F\", Column2: 53 },\n { Column1: \"G\", Column2: 19 },\n { Column1: \"H\", Column2: 87 },\n { Column1: \"I\", Column2: 52 }\n]\n// }","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":149,"value":"showtypes(dataObject)","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":143,"value":"##### I'll try and alternative method using _viewof_","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":142,"value":"viewof selection = Inputs.table(dataObject, { width: 200, required: false })","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":141,"value":"selection // now I can return the columns as an array","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":140,"value":"mdhl`
\n\nWe can rename the columns as necessary\n> **Renamed Table:**\n>\n${Inputs.table(dataObject, {\n columns: [\"Column1\", \"Column2\"],\n header: {\n Column1: \"Category\",\n Column2: \"Value\"\n },\n width: 200,\n required: false\n})}\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":139,"value":"mdhl`#### Example\nReturn the table as a **_viewof_** object\n~~~js\n import {textcolor} from \"@observablehq/text-color-annotations-in-markdown\"\n viewof viewDataObject = Inputs.table(dataObject, { width: 200 })\n~~~\n${Inputs.table(dataObject, { width: 200 })}\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":138,"value":"viewof dataObjectAndColumns = Inputs.table(dataObject, { width: 200 })","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":137,"value":"#### Example:\nReturn the table as an array object, including the data and list of columns","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":135,"value":"viewof dummyDataView = Inputs.table(dummyData, { width: 500 })","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":134,"value":"
\nDisplay the table as a proper Table and derive new columns!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":133,"value":"DummyDataTable = dummyDataView","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"DummyDataTable","database":"$undefined"},{"id":132,"value":"
\nDisplay the data as a SQL table and use SQL to add columns!","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":131,"value":"SELECT Product, Company, Sales, CASE WHEN Sales > 1500 THEN 'Expensive' ELSE 'Cheap' END AS \"NewCol\"\n FROM \"dummyDataView\"\nWHERE \"Sales\" >= ${1500}\nORDER BY \"Company\" ASC\nLIMIT 5 OFFSET 0","pinned":true,"hidden":false,"mode":"sql","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"var:dummyDataView"},{"id":130,"value":"// Here I am definine my data as a JSON array\ndummyData = [\n { Product: \"Tasmanian Tiger Laptop\", Company: \"Falcon Systems\", Sales: 1500 }, // row 1\n { Product: \"Quagga Pro Laptop\", Company: \"Hawk Electronics\", Sales: 2200 }, // row 2\n { Product: \"DodoBook Laptop\", Company: \"Eagle Computing\", Sales: 1800 }, // row 3 etc...\n {\n Product: \"Thylacine Elite Laptop\",\n Company: \"Owl Innovations\",\n Sales: 2700\n },\n { Product: \"Saber-Toothed Tiger PC\", Company: \"Falcon Systems\", Sales: 1300 },\n { Product: \"Megalodon Max PC\", Company: \"Eagle Computing\", Sales: 2100 },\n { Product: \"Dire Wolf Laptop\", Company: \"Hawk Electronics\", Sales: 2400 },\n {\n Product: \"Giant Sloth Pro Laptop\",\n Company: \"Owl Innovations\",\n Sales: 1900\n },\n { Product: \"QuokkaBook Pro Laptop\", Company: \"Owl Innovations\", Sales: 2800 },\n { Product: \"Aurochs Plus PC\", Company: \"Falcon Systems\", Sales: 1400 }\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":129,"value":"Object.keys(dummyDataView[0])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":124,"value":"show(exampleDataCars.slice(0, 20), undefined, \"*\")","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":123,"value":"mdhl`\nHere we can:\n\\* display the table\n\\* filter top 20 rows\n\\* select columns\n\\* define the width of the table view\n\n~~~js\n • show(exampleDataCars.slice(0, 20), [\"Name\", \"Horsepower\"], 200)\n • show(exampleDataCars.slice(start as int, end as int), [\"Column1\", \"Column2\"], width as integer)\n~~~\n\n> **block quote** this and try this \n${show(exampleDataCars.slice(0, 20), [\"Name\", \"Horsepower\"], 200)}\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":122,"value":"show(exampleDataCars.slice(0, 20), [\"Name\", \"Horsepower\"], 200)","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":21,"value":"

\n# Appendix","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":54,"value":"#### _datasets_","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":101,"value":"vegaData = require(\"vega-datasets@1\", \"vega-datasets@2\") // import vega_datasets","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":103,"value":"Object.keys(vegaData) // view object names as list","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":107,"value":"exampleDataCars = vegaData[\"cars.json\"]() // load and parse cars data","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":109,"value":"vegaData[\"cars.json\"].url","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":98,"value":"#### external libraries","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":47,"value":"#### _my libraries_","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":56,"value":"import { showMe } from \"@pbiqueryous-repo/show-me\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":42,"value":"import {\n try_it as addNote,\n note as note,\n details as details\n} from \"@pbiqueryous-repo/callout-boxes\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":49,"value":"import { style, selectingCells } from \"@pbiqueryous-repo/keyboard-shortcuts\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":40,"value":"import { vegaDataViewer } from \"@pbiqueryous-repo/vega-data-viewer\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":23,"value":"import {\n toc as contents, // src = import { toc as contents } from \"@jonfroehlich/collapsible-toc\"\n indenttoc as indenttoc,\n fmt as fmt,\n hl as mdhl,\n printVegaJSON as printVega,\n vegalite as VegaLite,\n vegaEmbed as Vega,\n printTableTypes as showtypes, // src = import { printTableTypes } from \"@jonfroehlich/data-utilities\"\n printTable as show, // src = import { printTable as showtable } from \"@jonfroehlich/data-utilities\"\n note as note\n} from \"@pbiqueryous-repo/tools\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":17,"value":"---\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"}],"files":"$W46","stdlib":"1"}} 45:"$44:body"