2b:null 2c:["$","title",null,{"children":"Western US States Report Higher Rates of Veteran Suicides | Harshit Gajjar | Observable"}] 31:T1168,## Made-up Insights (Hypothesis) * Texas has weaker gun laws and Texas has the highest veteran population in the United States. Suicide by firearms is common in the state. Hence Texas should have highest veteran suicide rates in United States. * **Considerations** * I will need enough data of all the suicide cases in United States from 2005 to 2011 * I need to iterate all the records and group all the suicides by state * In terms of the idiom (visualization), I would need to display the veteran suicides rate for each state. Plotting a BarChart will help me determine the state with highest suicide rate * Veteran suicide rates tend to be higher in the southern regions of the United States when compared to the other regions. This disparity may be influenced by several factors, including access to mental health resources, availability of firearms, and cultural attitudes towards seeking help for mental health concerns. [**Selected**] * **Considerations** * I will need enough data of all the suicide cases in India from 2005 to 2011 * I need to iterate all the records and group all the suicides by state * In terms of the idiom (visualization), I would need to display the veteran suicide rate for each state. Plotting a grid map visualization with tiles of States along with color hue and area will help me determine the region and the states with highest veteran suicide rates ## Target Audience * Mental health professionals and researchers who study suicide rates and trends in the United States * Policymakers who are responsible for implementing suicide prevention programs and policies at the national, state, and local levels * Journalists and media professionals who report on public health issues and may be interested in visualizing suicide rates in different regions of the country or among different demographic groups ## Data Abstraction (What) * **Dataset type:** Table (converted to map) * **Attributes used:** * state * Attribute Type - Categorical * vet_rate * Attribute type - Quantitative * Orientation - Sequential * **Derived Attributes:** * Regions - Dividing the states of US map in different geographical regions * Attribute Type - Categorical * avg_vet_rate - Average suicide rate among veterans from 2005 to 2011 * Attribute type - Quantitative * Orientation - Sequential * **Availability:** Static * **Time frame of Data:** 2005 - 2011 * **Data Source:** [Veteran suicides in United States](https://www.kaggle.com/datasets/residentmario/us-veteran-suicides) ## Task Abstraction (Why) To determine if my selected insight was correct, I need to perform the following tasks: * T1: Summarize the color of US state based on regions **[Summarize, Feature]** * T2: Summarize the veteran suicide rate in all US state **[Summarize, Feature]** * T3: Identify the regions with highest number of veterans suicide rate **[Identify, Extreme]** ## Marks and Channels (How) * **Marks:** Point * **Channel:** * Position: The position of the node determined by the sparse matrix, positioning the US states based on their geographical location * Attribute: State * Task: T1 * Used to separate different states * **Expressiveness principle** - "State" and "Race" is a categorical attribute and they are represented by node * **Effectiveness principle** - The best way to show red and blue states and race/ethnicity is to use the position. The nodes can be aligned as the outcome of the force simulation algorithm and we can place the nodes depending upon forces applied * Color Hue: This denotes the region, where the state belongs to. * Attribute: regions * Task: T2 * Using **express** * **Expressiveness principle** - "regions" is a categorical attribute so it is represented with color hue * **Effectiveness principle** - The best way to see determine region of the US state is to use color saturation. The color denotes us the state, making it easier to locate * Area: This denotes the average suicide rate. * Attribute: avg_vet_rate * Task: T2, T3 * Using **express** * **Expressiveness principle** - "avg_vet_rate" is a quantitative attribute so it is represented with area * **Effectiveness principle** - The best way to see show avg_vet_rate is using area, since avg_suicide_rate is directly proportional to the area. Higher the suicide rate, bigger the area. 32:T1007,function displaySparseMatrixGridMap({ sparseMatrix = requiredParam("sparseMatrix", "displaySparseMatrixGridMap"), height = 360, colorLookup, numRows, numCols } = {}) { if (typeof colorLookup === "undefined") { let color = d3 .scaleLinear() .domain([1, 20]) .range([ "#b2ddf0", "#92bcd8", "#769cbf", "#5d7da7", "#46608f", "#334577", "#232d5f" ]); colorLookup = {}; sparseMatrix.forEach((e) => (colorLookup[e.key] = color(e.key.length))); } if (typeof numRows === "undefined") { let count = countColsRowsFromSparseMatrix(sparseMatrix); numRows = count.rows.num; } if (typeof numCols === "undefined") { let count = countColsRowsFromSparseMatrix(sparseMatrix); numCols = count.cols.num; } let hRectSide = width / numCols; let vRectSide = height / numRows; let rectSide = hRectSide > vRectSide ? vRectSide : hRectSide; const svg = d3.select(DOM.svg(width / 1.5, height)).attr("class", "gridmap"); // svg.style("background", "#4D4D4D"); let sEnter = svg .append("g") .selectAll("g") .data(sparseMatrix) .enter() .append("g") .attr("transform", (d) => { return "translate(" + d.col * rectSide + "," + d.row * rectSide + ")"; }); // sEnter // .append("rect") // .attr("width", rectSide) // .attr("height", rectSide) // .attr("vector-effect", "non-scaling-stroke") // .style("opacity", 0.5) // .style("stroke", "#aaa") // .style("fill", (d) => { // console.log(d) // return colorLookup[d.key]; // }); sEnter .append("circle") .attr("r", (d) => final_avg.get(state_name_map.get(d.key)) / 1.7) .attr("vector-effect", "non-scaling-stroke") .style("opacity", 0.8) .style("stroke", "#aaa") .style("fill", (d) => { return color_state_map.get(d.key); }) .attr("transform", `translate(${rectSide / 2},${rectSide / 2})`) .style("margin-botto", "2px") .on("mouseover", (event, d) => { tooltip .html( "

" + "State: " + state_name_map.get(d.key) + "

" + // "
" + "

" + "Avg. Suicide Rate (per 100k): " + final_avg.get(state_name_map.get(d.key)) + "

" ) .style("pointer-events", "none") .style("visibility", "visible") // make the tooltip visible on hover .style("top", event.pageY + "px") // position the tooltip with its top at the same pixel location as the mouse on the screen .style("left", event.pageX + "px") .style("border-width", "2pt") .style("border-color", "black"); }) .on("mouseout", (event, d) => { tooltip .transition() .style("pointer-events", "none") .duration(50) // give the hide behavior a 50 milisecond delay so that it doesn't jump around as the network moves .style("visibility", "hidden"); }); sEnter .append("text") .attr("x", rectSide / 2) .attr("y", rectSide / 2 + 2) .style("text-anchor", "middle") .style("font-size", (d) => // final_avg.get(state_name_map.get(d.key)) / 2.5 Math.max("10px", final_avg.get(state_name_map.get(d.key)) / 2.5) ) .style("font-family", "sans-serif") .style("pointer-events", "none") .attr("color", "white") .text((d) => { // if (final_avg.get(state_name_map.get(d.key)) / 1.7 >= 15) return d.key; // return ""; }); sEnter .append("text") .attr("x", rectSide / 2) .attr("y", rectSide / 2 + rectSide / 4) .style("text-anchor", "middle") .style("font-size", "10px") .style("font-family", "sans-serif") .style("pointer-events", "none") .style("color", "white") .text((d) => { if (d.key === "DC") return "No data"; // if (final_avg.get(state_name_map.get(d.key)) / 1.7 >= 15) // return final_avg.get(state_name_map.get(d.key)); return final_avg.get(state_name_map.get(d.key)); }); return svg.node(); }33:T400,function mapStateColor() { let region_color_map = new Map(); pacific.forEach((r) => { region_color_map.set(r, "rgb(254, 200, 104)"); // rgb(244, 188, 65) }); mountain.forEach((r) => { region_color_map.set(r, "rgb(254, 200, 104)"); }); west_north_central.forEach((r) => { region_color_map.set(r, "rgb(199, 232, 202)"); // rgb(114, 188, 73) }); east_north_central.forEach((r) => { region_color_map.set(r, "rgb(199, 232, 202)"); }); mid_atlantic.forEach((r) => { region_color_map.set(r, "rgb(246, 225, 195)"); // rgb(224, 104, 42) }); new_england.forEach((r) => { region_color_map.set(r, "rgb(246, 225, 195)"); }); west_South_central.forEach((r) => { region_color_map.set(r, "rgb(180, 228, 255)"); // rgb(103, 175, 240) }); east_south_central.forEach((r) => { region_color_map.set(r, "rgb(180, 228, 255)"); // rgb(65, 146, 231) }); south_atlantic.forEach((r) => { region_color_map.set(r, "rgb(180, 228, 255)"); }); return region_color_map; }34:Tb55,function treeMapGenerator() { const svg = d3 .create("svg") .style("font-family", "sans-serif") // .attr("width", 1400) // .attr("height", 1100); .attr("viewBox", [-20, -20, width + 20 * 2, 1100 + 20 * 2]); const g = svg.append("g").attr("class", "treemap-container"); // Place the labels for our countries g.selectAll("text.country") // The data is the first "generation" of children .data(root.children) .join("text") .attr("class", "country") // The rest is just placement/styling .attr("x", (d) => d.x0) .attr("y", (d) => d.y0) .attr("dy", "0.6em") .attr("dx", 3) .style("font-size", 12) // Remember, the data on the original node is available on node.data (d.data here) .text((d) => d.data.name); // Now, we place the groups for all of the leaf nodes const leaf = g .selectAll("g.leaf") // root.leaves() returns all of the leaf nodes .data(root.leaves()) .join("g") .attr("class", "leaf") // position each group at the top left corner of the rect .attr("transform", (d) => `translate(${d.x0},${d.y0})`) .style("font-size", 10); // A title element tells the browser to display its text value // in a popover when the cursor is held over a rect. This is a simple // way to add some interactivity leaf .append("title") .text( (d) => `${d.parent.data.name}-${d.data.name}\n${ d.value.toLocaleString() + " cases" }` ); // Now we append the rects. Nothing crazy here leaf .append("rect") .attr("fill", (d) => color_Scale(d.parent.data.name)) .attr("opacity", 0.7) // the width is the right edge position - the left edge position .attr("width", (d) => d.x1 - d.x0) // same for height, but bottom - top .attr("height", (d) => d.y1 - d.y0) // make corners rounded .attr("rx", 3) .attr("ry", 3); // This next section checks the width and height of each rectangle // If it's big enough, it places labels. If not, it doesn't. leaf.each((d, i, arr) => { // The current leaf element const current = arr[i]; const left = d.x0, right = d.x1, // calculate its width from the data width = right - left, top = d.y0, bottom = d.y1, // calculate its height from the data height = d.y1 - d.y0; // too small to show text const tooSmall = width < 34 || height < 25; // and append the text (you saw something similar with the pie chart (day 6) const text = d3 .select(current) .append("text") // If it's too small, don't show the text .attr("opacity", tooSmall ? 0 : 0.9) .selectAll("tspan") .data((d) => [d.data.name, d.value.toLocaleString()]) .join("tspan") .attr("x", 3) .attr("y", (d, i) => (i ? "2.5em" : "1.15em")) .text((d) => d); }); return svg.node(); 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2f:{"id":"74f1ce5c78dabdce","slug":null,"title":"Western US States Report Higher Rates of Veteran Suicides","thumbnail":"2d0351da7132e8ca261d4c42835c0e388d4b73bee1d65131a208845492a9a0c0","access_level":"public","create_time":"$D2023-04-03T23:31:56.788Z","update_time":"$D2023-04-26T07:15:22.302Z","view_time":null,"first_public_time":"$D2023-04-03T23:31:56.788Z","has_unpublished_edits":null,"fork":{"id":"357fbd205ce34638","slug":null,"title":"Western US States Report Higher Rates of Veteran Suicides","owner":{"id":"666e343e9fc70af6","login":"hg24","name":"Harshit Gajjar"}},"stars":0,"starred":false,"owner":{"type":"team","id":"666e343e9fc70af6","login":"hg24","name":"Harshit Gajjar","avatar_url":"https://avatars-next.observableusercontent.com/6f17a096ab3d83e4a953387b0069b305478a67613578aa9ebebb8eaa88a66abb","tier":"starter_2024"},"version":435,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"5e2ba07857faed1b","login":"hg24","name":"Harshit Gajjar","avatar_url":"https://avatars-next.observableusercontent.com/6f17a096ab3d83e4a953387b0069b305478a67613578aa9ebebb8eaa88a66abb","tier":null}],"members":[{"type":"individual","id":"5e2ba07857faed1b","login":"hg24","name":"Harshit Gajjar","avatar_url":"https://avatars-next.observableusercontent.com/6f17a096ab3d83e4a953387b0069b305478a67613578aa9ebebb8eaa88a66abb","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Western US States Report Higher Rates of Veteran Suicides","cells":[{"id":0,"value":"# Western US States Report Higher Rates of Veteran Suicides\nSpanning across years 2005 to 2011\n---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":340,"value":"**insight:** Mountain states in the west of US, are having higher veteran suicide rate as compared to other US states.

\nContinue reading the story..","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":406,"value":"### Average Veteran suicide rates per 100k across different states in US","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":254,"value":"legend = Swatches(\n d3.scaleOrdinal(\n [\"West\", \"Midwest\", \"Northeast\", \"South\"],\n [\n \"rgb(254, 200, 104)\",\n \"rgb(199, 232, 202)\",\n \"rgb(246, 225, 195)\",\n \"rgb(180, 228, 255)\"\n ]\n )\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"withColor2 = displayGridMap({\n gridMap: NYTGridMap,\n height: 500,\n colorLookup: colorLookup\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":146,"value":"md`\nCreated by [Harshit Gajjar](https://observablehq.com/@5e2ba07857faed1b?tab=profile)
\nClass: [Data Visualization](https://johnguerra.co/classes/data_visualization_spring_2023/)
\nInstructor: [John Alexis Guerra Gomez](https://observablehq.com/@john-guerra)
\n[Dataset](https://www.kaggle.com/datasets/residentmario/us-veteran-suicides)
\n[Video](https://youtu.be/QOo9Ecb5cow)
\n[Tweet](https://twitter.com/HarshitSFHusky/status/1641124688138207236)\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":127,"value":"## Introduction\nSuicide is the act of intentionally taking one's own life, and it is a complex and serious issue that affects individuals, families, and communities worldwide. The causes of suicide are often complex and multifaceted, involving a range of individual, societal, and environmental factors. This notebook delves into veteran suicide cases in United States between 2005 and 2011, examining patterns and trends among different states.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":350,"value":"Swatches(\n d3.scaleOrdinal(\n [\"West\", \"Midwest\", \"Northeast\", \"South\"],\n [\n \"rgb(254, 200, 104)\",\n \"rgb(199, 232, 202)\",\n \"rgb(246, 225, 195)\",\n \"rgb(180, 228, 255)\"\n ]\n )\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":347,"value":"withColor3 = displayGridMap({\n gridMap: NYTGridMap,\n height: 500,\n colorLookup: colorLookup\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":163,"value":"## Actual Insights\n* Suicides rate among veterans was highest in the US states in the West and among the mountain states such as Montana, Nevada, Arizona, Colorado\n* Suicides rate among veterans was lowest in the US states in the Northeast such New Jersey, New York\n* Montana has highest veteran suicide rates in the country and Massachusetts and Nebraska has lowest veteran suicide rate ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":130,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":159,"value":"### Functions for the grid map","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":8,"value":"function displayGridMap({\n gridMap = requiredParam(\"gridMap\", \"displayGridMap\"),\n height,\n colorLookup,\n numRows,\n numCols\n} = {}) {\n gridMap = addSparseMatrix(gridMap, numRows);\n return displaySparseMatrixGridMap({\n sparseMatrix: gridMap.sparseMatrix,\n height: height,\n colorLookup: colorLookup,\n numRows: numRows,\n numCols: numCols\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":10,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":300,"value":"tooltip = d3\n .select(\"body\")\n .append(\"div\") // the tooltip always \"exists\" as its own html div, even when not visible\n .style(\"position\", \"absolute\") // the absolute position is necessary so that we can manually define its position later\n .style(\"visibility\", \"hidden\") // hide it from default at the start so it only appears on hover\n .style(\"background-color\", \"#eee\")\n .attr(\"class\", \"tooltip\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":25,"value":"colorLookup = {\n let c = {};\n usStates.forEach(function (e) {\n c[e.key] = colorScale(parseFloat(final_avg.get(e.name))); // d3.interpolateRdYlGn(1 - e.name.length / 20);\n });\n return c;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"// colorScale = d3\n// .scaleSequential(d3.interpolatePuRd) //interpolateRdYlBu\n// .domain([0, d3.max([...vet_suicide_arr], (d) => d[\"vet_suicide_rate\"])])\ncolorScale = d3\n .scaleSequential(d3.interpolateReds)\n .domain(d3.extent(vet_suicide_arr, (d) => d[\"vet_suicide_rate\"]))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":97,"value":"vet_suicide_arr = mapToArray(final_avg)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":95,"value":"function mapToArray(map) {\n let arr = [];\n\n for (let [k, v] of map.entries()) {\n arr.push({ state: k.replaceAll(\"*\", \"\"), vet_suicide_rate: parseFloat(v) });\n }\n\n return arr;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":199,"value":"### US states division into regions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":201,"value":"pacific = [\"WA\", \"OR\", \"CA\", \"AK\", \"HI\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":203,"value":"mountain = [\"MT\", \"ID\", \"WY\", \"NV\", \"UT\", \"CO\", \"AZ\", \"NM\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":205,"value":"west_north_central = [\"ND\", \"SD\", \"NE\", \"KS\", \"MN\", \"IA\", \"MO\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":210,"value":"east_north_central = [\"WI\", \"IL\", \"IN\", \"MI\", \"OH\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":212,"value":"mid_atlantic = [\"PA\", \"NY\", \"NJ\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":214,"value":"new_england = [\"VT\", \"NH\", \"ME\", \"MA\", \"RI\", \"CT\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":216,"value":"west_South_central = [\"TX\", \"OK\", \"AR\", \"LA\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":218,"value":"east_south_central = [\"KY\", \"TN\", \"MS\", \"AL\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":220,"value":"south_atlantic = [\"WV\", \"DC\", \"DE\", \"MD\", \"VA\", \"NC\", \"SC\", \"GA\", \"FL\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":37,"value":"## Data Preprocessing","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":40,"value":"### Import data for all years from 2005 to 2011","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":42,"value":"year_2005 = FileAttachment(\"2005.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":44,"value":"year_2006 = FileAttachment(\"2006.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":46,"value":"year_2007 = FileAttachment(\"2007.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"year_2008 = FileAttachment(\"2008.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":50,"value":"year_2009 = FileAttachment(\"2009.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":52,"value":"year_2010 = FileAttachment(\"2010.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":54,"value":"year_2011 = FileAttachment(\"2011.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":56,"value":"all_data_combined = [\n ...year_2005.map((h) => ({ ...h, year: \"2005\" })),\n ...year_2006.map((h) => ({ ...h, year: \"2006\" })),\n ...year_2007.map((h) => ({ ...h, year: \"2007\" })),\n ...year_2008.map((h) => ({ ...h, year: \"2008\" })),\n ...year_2009.map((h) => ({ ...h, year: \"2009\" })),\n ...year_2010.map((h) => ({ ...h, year: \"2010\" })),\n ...year_2011.map((h) => ({ ...h, year: \"2011\" }))\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":58,"value":"all_data_combined","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":161,"value":"### Compute the average suicide rate across for each state from 2005 to 2011","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":60,"value":"final_avg = d3.rollup(\n all_data_combined,\n (v) => d3.mean(v, (d) => d[\"vet_rate\"]).toFixed(1),\n (d) => d.state.replaceAll(\"*\", \"\")\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":188,"value":"### Function to map states and their abbreviations","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":190,"value":"function mapStateNames(arr) {\n let map = new Map();\n\n arr.forEach((d) => {\n map.set(d.key, d.name);\n });\n\n return map;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":192,"value":"state_name_map = mapStateNames(usStates)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":233,"value":"### Function to map color to states based on region","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":235,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":240,"value":"color_state_map = mapStateColor()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":358,"value":"### Import statements","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":17,"value":"import { NYTGridMap } from \"@severo/examples-of-grid-maps\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":23,"value":"import {\n countColsRowsFromSparseMatrix,\n addSparseMatrix\n} from \"@severo/helper-functions-for-manipulating-grid-maps\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":15,"value":"usStates = d3.csv(\n \"https://raw.githubusercontent.com/kristw/gridmap-layout-usa/master/src/input/states.csv\"\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":12,"value":"import { requiredParam } from \"@severo/generic-helper-functions\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":176,"value":"import { Legend, Swatches } from \"@d3/color-legend\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":371,"value":"## Visual Exploration","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":403,"value":"### Treemap for States and Top methods of committing suicides from 2016 to 2020","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":373,"value":"treeMapGenerator()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":375,"value":"color_Scale = d3.scaleOrdinal(d3.schemeSet3)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":398,"value":"height = 1100","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":377,"value":"hierarchy = {\n const dataCopy = JSON.parse(JSON.stringify(state_age_suicide_data));\n\n return d3\n .hierarchy(dataCopy)\n .sum((d) => d.value)\n .sort((a, b) => b.value - a.value);\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":379,"value":"treemap = d3\n .treemap()\n // set the size of the treemap render area\n .size([width, height])\n // set the padding between every rectangle in px\n .padding(2)\n // set the padding at the top of each group of rectangles\n // so that we can fit the country labels\n .paddingTop(10)\n // Set the generator to round pixel values to the nearest value\n // (makes things look better)\n .round(true)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":381,"value":"root = treemap(hierarchy)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":383,"value":"// fdata = {\n// const d = d3.csvParse(\n// await FileAttachment(\"Electricity generation by source-1.csv\").text()\n// );\n\n// const children = d.map((country) => ({\n// name: country.Country,\n// children: Object.entries(country)\n// .map((c) => {\n// if (c[0] == \"\" || c[0] == \"Country\" || c[0] == \"Year\") return;\n// else\n// return {\n// name: c[0],\n// value: c[1]\n// };\n// })\n// .filter((d) => d)\n// }));\n\n// return {\n// children\n// };\n// }","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":385,"value":"function mapToTreeFormat(map) {\n let arr = [];\n\n for (let [key, val] of map.entries()) {\n let obj = {};\n\n obj = {\n name: key\n };\n\n let child = [];\n let obj2 = {};\n\n for (let [k, v] of val.entries()) {\n obj2 = {\n name: k.split(\" \")[0],\n value: v\n };\n\n child.push(obj2);\n }\n\n obj = {\n ...obj,\n children: child\n };\n\n arr.push(obj);\n }\n\n return arr;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":387,"value":"sdata = FileAttachment(\"usa_suicides_2016_onwards.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":389,"value":"mapped_data = d3.rollup(\n sdata,\n (v) =>\n d3.mean(\n v,\n (d) =>\n (parseInt(d.Count) * 100000) / parseInt(d.Population.replace(\",\", \"\"))\n ),\n (d) => d.Race, // State.replace(/ *\$[^)]*\$ */g, \"\")\n // (d) => d[\"Age Groups\"]\n (d) => d[\"Method\"]\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":391,"value":"mapped_data.delete(\"\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":393,"value":"state_age_suicide_data = ({\n children: mapToTreeFormat(mapped_data)\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":395,"value":"$34","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W35","stdlib":"1","titling":"auto"}} 30:"$2f:body"