2a:null 2b:["$","title",null,{"children":"FA2024 Women in Sports (plot) | Angie Hjort | Observable"}] 31:T644,chart = Plot.plot({ width, height: 700, y: {type: "linear", label: "Gender Discrepency", grid: true, domain: [-65,80]}, x: {grid: true}, r: {domain: rDomain, range: [2, 50]}, margin: 40, paddingOuter: 300, marks: [ Plot.ruleY([0], { stroke: "#d3d3d3" }), Plot.dot(medal_data, { x: "GDP per capita (2023)", y: (d) => d[radioMapping[SelectedMedal]], r: "Total Medals", stroke: "#333", fill: "Gender Diff", fillOpacity: d => SelectedCountry.includes(d.Country) ? 1: 0.2, strokeOpacity: d => SelectedCountry.includes(d.Country) ? 1: 0.2, channels: {Country: "Country", ["Gender Diff"]: {value: (d) => d[radioMapping[SelectedMedal]], label: "Gender Difference"}, ["GDP per capita (2023)"]: {value: "GDP per capita (2023)", label: "GDP"}}, tip: { format: { Country: true, r: true, ["Gender Diff"]: true, ["GDP per capita (2023)"]: (d) => `$${d}`, y: false, x: false, fill: false, fillOpacity: false, strokeOpacity: false } } }), Plot.crosshair(medal_data, {x: "GDP per capita (2023)", y: (d) => d[radioMapping[SelectedMedal]]}) ], color: { type: "diverging-symlog", scheme: "RdYlGn", legend: true, label: "More Male Medals More Female Medals", pivot: 0, symmetric: true } }) 32:[{"id":"7236696928084c886391d387a5fd32cddcb2d914f7653ad2ab9e7c319bc0d6d12362f54f74be82d5fef3df70cb6abf9536d33f765b1d748cc4bc32160d024ec3","href":"https://static.observableusercontent.com/files/7236696928084c886391d387a5fd32cddcb2d914f7653ad2ab9e7c319bc0d6d12362f54f74be82d5fef3df70cb6abf9536d33f765b1d748cc4bc32160d024ec3","name":"Data_Olympics.xlsx","type":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","lastModified":1737038831863.636,"size":19467}] 2e:{"id":"57e53c98afd14fc9","slug":"fa2024-women-in-sports","title":"FA2024 Women in Sports (plot)","thumbnail":"5bdb59d69351a74b32d44e0d09f360bb30a1ab689522e56819da9f67f7f9e08c","access_level":"public","create_time":"$D2025-01-16T14:47:11.863Z","update_time":"$D2025-01-20T08:43:44.191Z","view_time":null,"first_public_time":"$D2025-01-16T14:47:11.863Z","fork":{"id":"56b7a329fba7a492","slug":null,"title":"Women in Sport Final Project","owner":{"id":"c9e6070fd9224ac1","login":"dis-2024-fall","name":"🪦 dis-2024-fall"}},"stars":0,"starred":false,"owner":{"type":"team","id":"c555e02063f451b5","login":"angiehjort","name":"Angie Hjort","avatar_url":"https://avatars-next.observableusercontent.com/d3c0d6d22f1525b9f9f1d4c8187de1dc20adc65c5baeb538c15672fb523883fa","tier":"starter_2024"},"version":593,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"1245953aabb247aa","login":"angiehjort","name":"Angie Hjort","avatar_url":"https://avatars-next.observableusercontent.com/d3c0d6d22f1525b9f9f1d4c8187de1dc20adc65c5baeb538c15672fb523883fa","tier":null}],"members":[{"type":"individual","id":"1245953aabb247aa","login":"angiehjort","name":"Angie Hjort","avatar_url":"https://avatars-next.observableusercontent.com/d3c0d6d22f1525b9f9f1d4c8187de1dc20adc65c5baeb538c15672fb523883fa","tier":null,"role":"editor"},{"type":"team","id":"c555e02063f451b5","login":"angiehjort","name":"Angie Hjort","avatar_url":"https://avatars-next.observableusercontent.com/d3c0d6d22f1525b9f9f1d4c8187de1dc20adc65c5baeb538c15672fb523883fa","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"subscribed":null,"forks":0,"collection":{"id":"c2b96431d92a6fa1","slug":"dis-course-projects","title":"Course projects archive","owner":{"id":"c555e02063f451b5","login":"angiehjort","name":"Angie Hjort"}},"type":"notebook","body":{"title":"FA2024 Women in Sports (plot)","cells":[{"id":0,"value":"# FA2024 Women in Sports (plot)","pinned":false,"hidden":false,"mode":"md"},{"id":490,"value":"htmlCell = html`\n

\n Gender Difference in Total Medals by GDP Per Capita\n

\n Paris Summer Olympics 2024\n

\n Choose Medal Type\n ${viewof SelectedMedal}\n

\n Search Country\n ${viewof SelectedCountry}\n

\n Circle Size - Total Medals\n ${sizeLegend}\n

\n ${chart}\n

\n`\n","pinned":true,"hidden":false,"mode":"ojs"},{"id":357,"value":"workbook1 = FileAttachment(\"Data_Olympics.xlsx\").xlsx()","pinned":true,"hidden":false,"mode":"ojs"},{"id":358,"value":"workbook1.sheetNames","pinned":true,"hidden":false,"mode":"ojs"},{"id":359,"value":"medal_data = workbook1.sheet(0, {\n headers: true,\n })","pinned":true,"hidden":false,"mode":"ojs"},{"id":375,"value":"medal_data","pinned":true,"hidden":false,"mode":"ojs"},{"id":19,"value":"Plot.plot({\n marks: [\n Plot.auto(medal_data, {x: \"GDP per capita (2023)\", y: \"Gender Diff\"})\n ]\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":418,"value":"radioMapping = ({\n \"Total\": \"Gender Diff\", \n \"Gold\":\"Gold Diff\", \n \"Silver\":\"Silver Diff\", \n \"Bronze\": \"Bronze Diff\",\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":315,"value":"viewof SelectedCountry = Inputs.search(medal_data.map(d => d.Country))","pinned":false,"hidden":false,"mode":"ojs"},{"id":386,"value":"viewof SelectedMedal = Inputs.radio([\"Total\", \"Gold\", \"Silver\", \"Bronze\"], {value: \"Total\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":309,"value":"$31","pinned":true,"hidden":false,"mode":"ojs"},{"id":442,"value":"rDomain = d3.extent(medal_data, d => d[\"Total Medals\"])","pinned":true,"hidden":false,"mode":"ojs"},{"id":448,"value":"sizeLegend = Plot.plot({\n height: 110,\n r: {domain: rDomain, range: [2, 50]},\n x: {domain: [-2, 80*5], ticks: false},\n y: {ticks: false},\n marks: [\n Plot.dot([1, 10, 50, 125, 300], {x: (d, i) => i+9*Math.sqrt(d-1), y: 0, r: d => d, fill: \"#A0E775\", stroke: \"#333\"}),\n Plot.text([1, 10, 50, 125, 300], {x: (d, i) => i == 0? 4 : i == 1? 40: i + 9*Math.sqrt(d-1), y: 0, text: d => d, fontSize: 16}),\n \n ]\n})","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}} 2f:"$2e:body"