2f:T564,{ const width = 900; const height = 300; const marginTop = 25; const marginRight = 20; const marginBottom = 35; const marginLeft = 60; const x = d3.scaleBand() .domain(Array.from(new Set(populationData.map(d => d.name)))) .range([0, width]) const y = d3.scaleLinear() // .domain([0, d3.max(stackLayout, d => d3.max(d, d => d[1]))]) .range([height, 0]) const color = d3.scaleOrdinal() .domain(keys) .range(d3.schemeSpectral[keys.length]) const svg = d3.create("svg") .attr("width", width + marginLeft + marginRight) .attr("height", height + marginTop + marginBottom); const g = svg.append("g") .attr("transform", `translate(${marginLeft}, ${marginTop})`); // Append a group for each series, and a rect for each element in the series. // g.append("g") // .selectAll(".bucket") // .data(stackLayout) // .join("g") // .attr("class", "bucket") // .attr("fill", (_, i) => color(keys[i])) // .selectAll("rect") // .data(d => d) // .join("rect") // .attr("x", d => x(d.data.name)) // .attr("y", d => y(d[1])) // .attr("height", d => y(d[0]) - y(d[1])) // .attr("width", x.bandwidth()) g.append("g") .attr("transform", `translate(0,${height})`) .call(d3.axisBottom(x)) g.append("g") .call(d3.axisLeft(y)) return svg.node(); }30:Tb35,{ const width = 600; const height = 400; const margin = { top: 30, bottom: 20, left: 50, right: 50 }; const div = htl.html`

`; const categories = d3.groups(iris, (d) => d.species); const buttons = d3 .select(div) .selectAll("button") .data(categories) .join("button"); buttons.text((d) => d[0]); const svg = d3 .select(div) .append("div") .append("svg") .attr("width", width + margin.left + margin.right) .attr("height", height + margin.top + margin.bottom); const g = svg .append("g") .attr("transform", `translate(${margin.left}, ${margin.top})`); g.append("rect") .attr('width', width) .attr("height", height) .style("fill", "#eee") const text = svg.append("text") .style("font", "12px sans-serif") .attr("y", 15) .text("Click on a circle to read the data!") const x = d3 .scaleLinear() .domain(d3.extent(iris, (d) => d["sepalLength"])).nice() .range([0, width]); const y = d3 .scaleLinear() .domain(d3.extent(iris, (d) => d["sepalWidth"])).nice() .range([height, 0]); const color = d3 .scaleOrdinal() .domain(categories.map((d) => d[0])) .range(d3.schemeDark2); const yAxis = g.append("g").call(d3.axisLeft(y).tickSize(-width)); const xAxis = g.append("g") .attr("transform", `translate(0, ${height})`) .call(d3.axisBottom(x).tickSize(-height)); yAxis.selectAll("line").style("stroke", "#fff"); xAxis.selectAll("line").style("stroke", "#fff"); const circles = g .selectAll("circle") .data(iris.filter((d) => d.species == "setosa")) .join("circle") .attr("r", 4) .style("stroke", "#000") .attr("cx", (d) => x(d.sepalLength)) .attr("cy", (d) => y(d.sepalWidth)) .style("fill", (d) => color(d.species)) // .style("cursor", "pointer") // .on("click", (event, d) => { // text.text(JSON.stringify(d)) // }) buttons.on("click", (event, d) => { g.selectAll("circle") .data(d[1], (d) => d) .join( (enter) => enter .append("circle") .attr("r", 4) .style("stroke", "#000") .attr("cx", (d) => x(d.sepalLength)) .attr("cy", (d) => y(d.sepalWidth)) .style("fill", (d) => color(d.species) // .style("cursor", "pointer") // .on("click", (event, d) => { // text.text(JSON.stringify(d)) // }) ), (update) => update .attr("cx", (d) => x(d.sepalLength)) .attr("cy", (d) => y(d.sepalWidth)) .style("fill", (d) => color(d.species)), (exit) => exit .attr("fill", "red") .call((exit) => exit.transition().duration(1000).attr("r", 0).remove() ) ); }); return div; }31:T4b2,testYourKnowledge([ { title: 'Data Structures', backText: [`Converting a tabular data structure to a hierarchical data structures is about creating a structure better suited for your visualization, not about creating efficiency.`, `A hierarchical data structure can introduct complexity which may not be best for all situations.`], question: "Hierarchical data structres are more efficient that tabular data structures", answer: false }, { title: 'Thinking in D3', backText: ['SVG (scalable vector graphics) are a common way to build images for the Web.', 'SVG works quite well with D3 given how D3 generates data-driven documents.'], question: 'SVG is a text-based open Web standard for generating images.', answer: true }, { title: 'Interaction', backText: [`D3 adds a lot of complexity to developing data visualizations, and is often a more difficult to use for basic chart forms.`, `Where D3 shines is when you get into features that can't be done with other frameworks, like bespoke data visualization forms, animation and interactivity.`], question: `D3 is often the simplest way to make a bar chart or scatterplot.`, answer: false }, ], 300, 300)32:[{"id":"3ea96de39eb40936da1c5e7bf932e124861c50b9e45569cb17e694e9b9ed462c79684b2ede7266422ee880930d43408010a4741695709c094f9f6827c62534db","href":"https://static.observableusercontent.com/files/3ea96de39eb40936da1c5e7bf932e124861c50b9e45569cb17e694e9b9ed462c79684b2ede7266422ee880930d43408010a4741695709c094f9f6827c62534db","name":"us-population-state-age.csv","type":"text/csv","lastModified":1696003889068.432,"size":3516},{"id":"a2810faa56f2edca2606a76bffb24e6c150fbf4b70512f35fd794a3c52144d51dbc70db3c4d3158c935f13fba1f66ca3425cc65f7e8bea9c70a493b532fabbdc","href":"https://static.observableusercontent.com/files/a2810faa56f2edca2606a76bffb24e6c150fbf4b70512f35fd794a3c52144d51dbc70db3c4d3158c935f13fba1f66ca3425cc65f7e8bea9c70a493b532fabbdc","name":"iris.csv","type":"text/csv","lastModified":1696003889068.432,"size":3712}] 2d:{"title":"Introduction to D3 Course: Lesson 5","cells":[{"id":5,"value":"# Introduction to D3 Course: Lesson 5\n## Thinking in D3\n\n[Session 5 slide deck](https://docs.google.com/presentation/d/1obvcXsmiuH-xOQh3v3ItjSmDRjNU0u4bcEaK0wCNr8U/edit?usp=sharing)","pinned":false,"hidden":false,"mode":"md"},{"id":6,"value":"---\n## Activity 1\n
","pinned":false,"hidden":false,"mode":"md"},{"id":42,"value":"### Hierarchical Data with Stack Layout\n- Create a new stack layout function, using the population dataset by state, making the keys the various age buckets.\n - Compare datasets to see what changed. Is the data set the same structure? Is it smaller or larger?\n- Create a stacked bar chart with the x-axis being each state, and the y axis being the total population, bars colored by their key.\n - Use a band scale to handle for the bar widths\n - Nest a d3.max within the d3.max to get the max y scale value.\n - Use a nested structure to our elements, so that there is a group for each key.","pinned":false,"hidden":false,"mode":"md"},{"id":152,"value":"populationData","pinned":true,"hidden":false,"mode":"ojs"},{"id":43,"value":"populationData","pinned":true,"hidden":false,"mode":"ojs"},{"id":44,"value":"keys = [\"<10\", \"10-19\", \"20-29\", \"30-39\", \"40-49\", \"50-59\", \"60-69\", \"70-79\", \"≥80\"]","pinned":true,"hidden":false,"mode":"ojs"},{"id":45,"value":"stackLayout = d3.stack().keys(keys)(populationData)","pinned":true,"hidden":false,"mode":"ojs"},{"id":46,"value":"$2f","pinned":true,"hidden":false,"mode":"ojs"},{"id":25,"value":"---\n## Activity 2\n
","pinned":false,"hidden":false,"mode":"md"},{"id":117,"value":"### Interaction with Event Listeners\n- Make the rectangle turn yellow when you enter the rectangle.\n- Make the rectangle turn blue when you leave the rectangle.\n- Make the rectangle shrink into nothingness when you click on the rectangle.","pinned":false,"hidden":false,"mode":"md"},{"id":111,"value":"{\n const width = 200;\n const height = 200;\n const margin = {top: 20, bottom: 20, left: 20, right: 20};\n\n const svg = d3.create(\"svg\")\n .attr(\"width\", width + margin.left + margin.right)\n .attr(\"height\", height + margin.top + margin.bottom);\n\n const g = svg.append(\"g\")\n .attr(\"transform\", `translate(${margin.left}, ${margin.top})`);\n\n const rectangle = g.append(\"rect\")\n .attr(\"width\", width)\n .attr(\"height\", height)\n .style(\"fill\", \"#ddd\")\n .style(\"stroke\", \"#000\")\n .on(\"\", (event) => {\n rectangle\n })\n\n return svg.node()\n\n\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":26,"value":"---\n## Activity 3\n
","pinned":false,"hidden":false,"mode":"md"},{"id":145,"value":"### Interaction with Event Listeners\n- Add an click event listener to the circles so you can read the data bound to each element.","pinned":false,"hidden":false,"mode":"md"},{"id":123,"value":"$30","pinned":true,"hidden":false,"mode":"ojs"},{"id":7,"value":"---\n## Wrap Up\nTest your knowledge from session one with these short questions.","pinned":false,"hidden":false,"mode":"md"},{"id":8,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"

","pinned":false,"hidden":false,"mode":"md"},{"id":10,"value":"

","pinned":false,"hidden":false,"mode":"md"},{"id":11,"value":"

","pinned":false,"hidden":false,"mode":"md"},{"id":12,"value":"

","pinned":false,"hidden":false,"mode":"md"},{"id":13,"value":"---\n## Appendix","pinned":false,"hidden":false,"mode":"md"},{"id":14,"value":"import {note} from \"@observablehq/callout-boxes\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":15,"value":"import { showMe } from \"@observablehq/show-me\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":16,"value":"import {testYourKnowledge} from \"@observablehq/test-your-knowledge-cards\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":17,"value":"color = d3.schemeBlues[7]","pinned":false,"hidden":false,"mode":"ojs"},{"id":76,"value":"populationData = await FileAttachment(\"us-population-state-age.csv\").csv({typed: true});","pinned":false,"hidden":false,"mode":"ojs"},{"id":125,"value":"iris = await FileAttachment(\"iris.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":true,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}