34:["$","title",null,{"children":"Made Invisible: European Population by Gender | Luc Guillemot | Observable"}] 3c:[] 38:{"id":"52a4e2193ff1db30","slug":"european-population-by-gender","title":"Made Invisible: European Population by Gender","thumbnail":"3a6bf0100a3ecb1c1f31ab09b8bf91b4b7e7ff1e4df355511ae5ead82fef91c9","access_level":"public","create_time":"$D2021-04-04T20:45:59.286Z","update_time":"$D2021-05-11T19:09:13.597Z","view_time":null,"first_public_time":"$D2021-04-05T09:02:54.522Z","has_unpublished_edits":null,"fork":{"id":"3c31ae9c4462b0e9","slug":"starter/2","title":"Starter","owner":{"id":"4eed1ed0ec8c7a2c","login":"lucguillemot","name":"Luc Guillemot"}},"stars":3,"starred":false,"owner":{"type":"team","id":"4eed1ed0ec8c7a2c","login":"lucguillemot","name":"Luc Guillemot","avatar_url":"https://avatars-next.observableusercontent.com/692f83824eae0715a07f9a04941a73318aad7b915db8ddda53058c392957fc6f","tier":"starter_2024","bio":"","followed_by_you":false,"follows_you":false},"version":223,"publish_version":223,"role":null,"authored":false,"authors":[{"type":"individual","id":"dbce705bc4e76709","login":"lucguillemot","name":"Luc Guillemot","avatar_url":"https://avatars-next.observableusercontent.com/692f83824eae0715a07f9a04941a73318aad7b915db8ddda53058c392957fc6f","tier":null,"bio":"","followed_by_you":false,"follows_you":false}],"members":[{"type":"individual","id":"dbce705bc4e76709","login":"lucguillemot","name":"Luc Guillemot","avatar_url":"https://avatars-next.observableusercontent.com/692f83824eae0715a07f9a04941a73318aad7b915db8ddda53058c392957fc6f","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":{"id":"2aaf9ec71cbec838","slug":"30-day-chart-challenge-2021","title":"30 Day Chart Challenge 2021","owner":{"id":"4eed1ed0ec8c7a2c","login":"lucguillemot","name":"Luc Guillemot"}},"type":"notebook","body":{"titling":"auto","title":"Made Invisible: European Population by Gender","cells":[{"id":0,"value":"md`# Made Invisible: European Population by Gender\n> «What is counted—like being a man or a woman—often becomes the basis for policymaking and ressource allocation. By contrast, what is not counted—like being nonbinary—becomes invisible […]». *Data Feminism*, Catherine D'Ignazio & Lauren F. Klein (2020), p.97`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":149,"value":"md`Gender repartition of EU28 population, according to Eurostat. The collected data includes data for ${highlightedText(\n { background: women, text: \"women\" }\n)} and ${highlightedText({\n background: men,\n text: \"men\"\n})}. The category ${highlightedText({\n background: nonbinary,\n text: \"non-binary\"\n})} is not included in the dataset, and therefore made invisible.\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":197,"value":"key = legend({color: colorScale, tickSize: 0, width: 180})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":54,"value":"chart = {\n const svg = d3.create(\"svg\")\n .attr(\"viewBox\", [0, 0, width, height])\n .style(\"overflow\", \"visible\");\n\n svg.append(\"g\")\n .attr(\"transform\", `translate(${margins.left}, ${margins.top})`)\n .selectAll(\"g\")\n .data(series)\n .enter().append(\"g\")\n .attr(\"fill\", d => colorScale(d.key))\n .selectAll(\"rect\")\n .data(d => d)\n .join(\"rect\")\n .attr(\"x\", d => xScale(d[0]))\n .attr(\"y\", 0)\n .attr(\"width\", d => xScale(d[1]) - xScale(d[0]))\n .attr(\"height\", 28);\n\n svg.append(\"g\")\n .call(xAxis);\n\n return svg.node();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":207,"value":"attribution({\n source: {\n label: \"Eurostats CENS_HNMGA (08/02/2021)\",\n link:\n \"https://ec.europa.eu/eurostat/databrowser/view/cens_hnmga/default/table?lang=en\"\n },\n day: \"04\",\n category: \"Comparisons\",\n prompt: \"Magical\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":90,"value":"series = d3.stack()\n .keys([\"Women\", \"Men\", \"Non-Binary\"])\n .offset(d3.stackOffsetExpand)\n (data)\n ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":52,"value":"xAxis = g => g\n .attr(\"transform\", `translate(${margins.left}, ${margins.top})`)\n .call(d3.axisTop(xScale).ticks(3, \"%\"))\n .call(g => g.selectAll(\".domain\").remove())","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":51,"value":"xScale = d3.scaleLinear().domain([0, 1]).range([0, bounds.chartWidth])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":41,"value":"colorScale = d3.scaleOrdinal()\n .domain([\"Women\", \"Men\", \"Non-Binary\"])\n .range([women, men, nonbinary])\n .unknown(\"#ccc\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":98,"value":"data = [{Women: 0.514, Men: 0.486, \"Non-Binary\": 0}]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":36,"value":"data2 = [{gender: \"Women\", percent: 0.514}, {gender: \"Men\", percent: 0.486}, {gender: \"Non-Binary\", percent: 0}]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":19,"value":"md`## Visualization Assets`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":131,"value":"nonbinary = \"#ffe600\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"men = \"#abf5ed\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":46,"value":"women = \"#f59994\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":13,"value":"bounds = ({ margins, \n chartWidth: width - 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\n ${note ? `

${note}

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**Source**: ${\n source.link ? `[${source.label}](${source.link})` : source.label\n}

**Creator**: [Luc Guillemot](https://lucguillemot.com/)

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