2b:null 2c:["$","title",null,{"children":"Tool MVP | Akhila Sulgante | Observable"}] 31:[{"id":"01bf47ad7ad377136982413d2fb1dba478112e5dbc4c6abe6fd7bb15b952a7c98d23d148f5223c77b90663cc88b50eff174a8f1e728b38d7e9c52aacba835cd3","href":"https://static.observableusercontent.com/files/01bf47ad7ad377136982413d2fb1dba478112e5dbc4c6abe6fd7bb15b952a7c98d23d148f5223c77b90663cc88b50eff174a8f1e728b38d7e9c52aacba835cd3","name":"adult@2.data","type":"application/octet-stream","lastModified":1701990716053.802,"size":3518611},{"id":"6282897e9cc54bb1c6a0ec320afb2b82c12f0a977b207bd80900a44a61ee85688c44abf7106d8b66d0ca0f8f1cab87c88565913b4c2b3deb49f9fd7c6f72b9cb","href":"https://static.observableusercontent.com/files/6282897e9cc54bb1c6a0ec320afb2b82c12f0a977b207bd80900a44a61ee85688c44abf7106d8b66d0ca0f8f1cab87c88565913b4c2b3deb49f9fd7c6f72b9cb","name":"adult@3.data","type":"application/octet-stream","lastModified":1701993257965.681,"size":3518610},{"id":"5342a8ffa63bce45bcfa21ba0f9105cae079ec14b9d8d96060dc51e073ca2a6b02c9989c9dd8b7052b665fb3d9c0b9f1cef80c5bb5cae46f588cf477d688450f","href":"https://static.observableusercontent.com/files/5342a8ffa63bce45bcfa21ba0f9105cae079ec14b9d8d96060dc51e073ca2a6b02c9989c9dd8b7052b665fb3d9c0b9f1cef80c5bb5cae46f588cf477d688450f","name":"adult@1.data","type":"application/octet-stream","lastModified":1701905508125.819,"size":3974478}] 2f:{"id":"04f091b1f688339c","slug":null,"title":"Tool MVP","thumbnail":"e6202c5f0ee362e73d7a0d550fa3f47d52a107eab653b340e1a57aaea7aabffb","access_level":"public","create_time":"$D2023-12-06T22:45:07.692Z","update_time":"$D2023-12-10T22:04:10.138Z","view_time":null,"first_public_time":"$D2023-12-06T22:45:07.692Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"e76678b312b62ab3","login":"akhila","name":"Akhila Sulgante","avatar_url":"https://avatars-next.observableusercontent.com/2e264e285632a44937edf6eb6b531fffbd152d07233e70f4c70c2cd9a5cd9e09","tier":"starter_2024"},"version":364,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"667daa7e86be0e8e","login":"akhila","name":"Akhila Sulgante","avatar_url":"https://avatars-next.observableusercontent.com/2e264e285632a44937edf6eb6b531fffbd152d07233e70f4c70c2cd9a5cd9e09","tier":null}],"members":[{"type":"individual","id":"667daa7e86be0e8e","login":"akhila","name":"Akhila Sulgante","avatar_url":"https://avatars-next.observableusercontent.com/2e264e285632a44937edf6eb6b531fffbd152d07233e70f4c70c2cd9a5cd9e09","tier":null,"role":"editor"},{"type":"individual","id":"fcd94e1c1ca12ae9","login":"kasivisu4","name":"Kasi Viswanath","avatar_url":"https://avatars-next.observableusercontent.com/48e36723913e7e5b18b906e1d7cde12fad4146715e78bbf74d3db7969a248b56","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":{"id":"d8769175c5a80da4","slug":"identifying-biases-in-ml-datasets","title":"Identifying biases in ML datasets","owner":{"id":"e76678b312b62ab3","login":"akhila","name":"Akhila Sulgante"}},"type":"notebook","body":{"title":"Tool MVP","cells":[{"id":0,"value":"# Tool MVP\n1. Upload your data(Prof. John data input)\n2. Selecting attributes for viewing data distribution(prof. John searchbox)\n3. Selecting attributes and chart type for viewing data composition()\n4. Applying ML classification model(TBD)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":141,"value":"1. ~~Creating histogram\n x- axis: categories in that column and y-axis:record count\n How to group age~~\n2. ~~Data composition and seeing how to change charts~~\n\nTomorrow(9th dec)\n1. ~~Adding tooltip~~\n2. ~~Integrating ML model result~~","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":6,"value":"## Uploading data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":29,"value":"By default [UCI Census Income dataset](http://archive.ics.uci.edu/dataset/20/census+income) is being used","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":18,"value":"viewof data = dataInput({\n value: default_data,\n delimiter: ',', // Optional\n format: \"auto\" // Optional, one of MongoExport, JSON, CSV, CSVNoAutoType\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":33,"value":"## Data Distribution","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":41,"value":"viewof selected_columns = searchCheckbox(\n Object.keys(data[0]), // What elements to chose from\n {// Any other options you pass here will be passed to the checkbox and search inputs\n value: Object.keys(data[0]), // Start with everything selected\n label: \"Variables\",\n height: 200\n // You can also pass specific options for the search and the checkboxes\n // optionsSearch: {\n // filter: fullSearchFilter\n // }\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":315,"value":"viewof chart_type = Inputs.select([\"Distribution\", \"Composition\"], {label:\"Select chart type\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":184,"value":"htl.html`${await Promise.all(selected_columns.map((d)=> {\n if(chart_type === \"Distribution\"){\n return display_histogram(data, d)\n } else {\n return display_pieChart(data, d)\n }\n \n}))}`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":220,"value":"## Attribute Co-relation","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":234,"value":"viewof y_axis = Inputs.select(Object.keys(data[0]),{label:\"Y-axis\",value:\"sex\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":230,"value":"viewof x_axis = Inputs.select(Object.keys(data[0]),{label: \"X-axis\",value:\"age\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":267,"value":"barChart(data,x_axis,y_axis)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":252,"value":"function barChart(data,x_axis,y_axis){\n let x = vl.x().fieldN(x_axis)\n let y = vl.y().fieldN(y_axis)\n\n if(x_axis === \"fnlwgt\"){\n x = vl.x().fieldQ(x_axis)\n }\n if(y_axis === \"fnlwgt\"){\n y = vl.y().fieldQ(y_axis)\n }\n return vl.markRect()\n .encode(\n x,y,\n vl.color().count()\n )\n .data(data)\n .height(900)\n .width(width-200)\n .render()\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":131,"value":"function displayColumn(data,attr){\n let target = SummarizeColumn(data, attr)\n return htl.html`

${target.childNodes[3]} ${target.childNodes[1]}

`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":36,"value":"import {searchCheckbox} from \"@john-guerra/search-checkbox\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":25,"value":"default_data = FileAttachment(\"adult@3.data\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":14,"value":"import {dataInput} from \"@john-guerra/data-input\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":63,"value":"values = {\n let result = new Map()\n selected_columns.forEach(\n (d)=>{\n result.set(d, d3.flatRollup(data, (l)=> l.length ,(v)=>v[d]))\n }\n )\n return result\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":76,"value":"d3.flatRollup(data, (l)=> l.length ,(v)=>v.age)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":89,"value":"temp = [{\n attribute: \"age\",\n values: {\n 20: 500,\n 30:400,\n 50:400\n }\n},\n{\n attribute: \"education\",\n values: {\n highSchool: 400,\n masters: 500\n }\n}]\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":103,"value":"import { SummarizeColumn } from \"@observablehq/summary-table\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":172,"value":"function display_histogram(data, attr) {\n \n let x = vl.x().field(attr)\n \n\n if(attr === \"fnlwgt\"){\n x = vl.x().fieldQ(attr)\n }\n \n return vl.markBar({tooltip: true})\n.encode(\n x, vl.y().count()\n \n)\n .height(400)\n .width(width)\n.data(data)\n.render()\n \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":303,"value":"function display_pieChart(data, attr) {\n\n return vl.markArc({tooltip: true})\n.encode(\n vl.color().field(attr),\n vl.theta().count()\n)\n .height(400)\n .width(width-200)\n.data(data)\n.render()\n \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W31","stdlib":"1","titling":"auto"}} 30:"$2f:body"