40:null 41:["$","title",null,{"children":"Final Project (Static Visual) | Victoria Ok | Observable"}] 47:T6f7,

Data Maketh (Hu)man

Is our data really an accurate representation of ourselves? Enough to determine if we are trustworthy enough to own a credit card?

· Clustered based on a combination of the individual's ethnicity and whether they were approved.
· Sized based on the amount of debt the individual has.
· Colored based on what industry the individual works in.

48:T73b,{ for (let i = 0; i < data.length; i++) { if (data[i]["Approved"] == "1" && data[i]["Ethnicity"] == "White") { data[i]["Approved_Ethnicity"] = "white_approved" } else if (data[i]["Approved"] == "0" && data[i]["Ethnicity"] == "White") { data[i]["Approved_Ethnicity"] = "white_rejected" } else if (data[i]["Approved"] == "1" && data[i]["Ethnicity"] == "Black") { data[i]["Approved_Ethnicity"] = "black_approved" } else if (data[i]["Approved"] == "0" && data[i]["Ethnicity"] == "Black") { data[i]["Approved_Ethnicity"] = "black_rejected" } else if (data[i]["Approved"] == "1" && data[i]["Ethnicity"] == "Asian") { data[i]["Approved_Ethnicity"] = "asian_approved" } else if (data[i]["Approved"] == "0" && data[i]["Ethnicity"] == "Asian") { data[i]["Approved_Ethnicity"] = "asian_rejected" } else if (data[i]["Approved"] == "1" && data[i]["Ethnicity"] == "Latino") { data[i]["Approved_Ethnicity"] = "latino_approved" } else if (data[i]["Approved"] == "0" && data[i]["Ethnicity"] == "Latino") { data[i]["Approved_Ethnicity"] = "latino_rejected" } else if (data[i]["Approved"] == "1" && data[i]["Ethnicity"] == "Other") { data[i]["Approved_Ethnicity"] = "other_approved" } else if (data[i]["Approved"] == "0" && data[i]["Ethnicity"] == "Other") { data[i]["Approved_Ethnicity"] = "other_rejected" } // if (data[i]["PriorDefault"] == "0") { // data[i]["PriorDefault"] = "NoPriorDefault" // } else { // data[i]["PriorDefault"] = "YesPriorDefault" // } if (data[i]["Employed"] == "0") { data[i]["Employed"] = "Unemployed" } else { data[i]["Employed"] = "Employed" } if (data[i]["Industry"] == "Real Estate") { data[i]["Industry"] = "RealEstate" } } }49:[{"id":"3f86597c798cc33ccda7f50d5fbb6b4339ad7fb16cfe4cfc0d5fe8eff47c7a948cfe63196c342ff4a2b7eb5f49bc0923d7773a2b85e1a92fe02bfcc1626405b1","href":"https://static.observableusercontent.com/files/3f86597c798cc33ccda7f50d5fbb6b4339ad7fb16cfe4cfc0d5fe8eff47c7a948cfe63196c342ff4a2b7eb5f49bc0923d7773a2b85e1a92fe02bfcc1626405b1","name":"credit_card_approvals_dataset.csv","type":"text/csv","lastModified":1683529441918.849,"size":45288}] 45:{"id":"41963d52ecc5c9d8","slug":null,"title":"Final Project (Static Visual)","thumbnail":"7e58b327fe180cfdc85aab204384fe315d9c8756382df1593a862a3ad6c7bd16","access_level":"public","create_time":"$D2023-04-25T19:25:03.973Z","update_time":"$D2023-05-08T23:27:36.090Z","view_time":null,"first_public_time":"$D2023-04-25T19:25:03.973Z","has_unpublished_edits":null,"fork":{"id":"4298732f59e560a1","slug":"clusters","title":"Clusters","owner":{"id":"58dc22f5e2929ad2","login":"emfielduva","name":"Eric Field"}},"stars":0,"starred":false,"owner":{"type":"team","id":"1a1a36b86df429e6","login":"vyo7tv","name":"Victoria Ok","avatar_url":"https://avatars-next.observableusercontent.com/20842b298900500b6ffc849cc98a6080baa5673642a71fcab490dd694e4a85fb","tier":"starter_2024","bio":"","following":false},"version":528,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"4209726d3b9cf6e0","login":"vyo7tv","name":"Victoria Ok","avatar_url":"https://avatars-next.observableusercontent.com/20842b298900500b6ffc849cc98a6080baa5673642a71fcab490dd694e4a85fb","tier":null,"bio":"","following":false}],"members":[{"type":"individual","id":"4209726d3b9cf6e0","login":"vyo7tv","name":"Victoria Ok","avatar_url":"https://avatars-next.observableusercontent.com/20842b298900500b6ffc849cc98a6080baa5673642a71fcab490dd694e4a85fb","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":2,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Final Project (Static Visual)","cells":[{"id":0,"value":"# Final Project (Static Visual)\n- Clustered based on a combination of the individual's ethnicity and whether they were approved.\n- Sized based on the amount of debt the individual has.\n- Colored based on what industry the individual works in.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":29,"value":"$47","pinned":true,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"svgContainer","database":"$undefined"},{"id":22,"value":"data = FileAttachment(\"credit_card_approvals_dataset.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":380,"value":"$48","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":116,"value":"fociFeatures = ({\n \"white_approved\":{x: 200, y: 200},\"white_rejected\":{x: 450, y: 200},\"black_approved\":{x: 700, y: 200},\"black_rejected\":{x: 950, y: 200},\n \"asian_approved\":{x: 200, y: 450},\"asian_rejected\":{x: 450, y: 450},\"latino_approved\":{x: 700, y: 450},\"latino_rejected\":{x: 950, y: 450},\n \"other_approved\":{x: 200, y: 700},\"other_rejected\":{x: 450, y: 700}\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":35,"value":"clElem = d3.select(svgContainer).select(\"#layer1\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":113,"value":"options = ({\n \"startFoci\": fociFeatures,\n \"fociField\": \"Approved_Ethnicity\",\n \"classField\": \"Industry\",\t\t// to set their class/color\n \"dotScaleFactor\": 5,\n \"strength\": -1,\n \"alphaTarget\": 0.09,\n \"collisionFactor\": 1.5\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":59,"value":"clusters = dvCluster(clElem,data,800,800,\"Debt\",options)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":375,"value":"labelLayer = clElem.append(\"g\").attr(\"id\",\"labels\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":400,"value":"dvClusterFociLabels(labelLayer,fociFeatures,{offsetY:155})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":82,"value":"-----","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":267,"value":"import {dvCluster, dvClusterFociLabels} from \"@emfielduva/dvlib_layout\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W49","stdlib":"1"}} 46:"$45:body"