2e:null 2f:["$","title",null,{"children":"GEOG 5540 Assignment 2: Classification and Colors | Haofeng Ma | Observable"}] 34:T5a4,function showScaleGrouping(data, scales) { const margins = { left: 130 }; const x = d3 .scaleLinear() .domain(d3.extent(data)) .range([margins.left, width - 5]); const r = 3; const rectHeight = 10; const chart = svg` `; return chart; }35:[{"id":"df85f37761596bd300e9570b9b4a89a069aeeefca0e1dbe733a03d2803beed9154b79b06f98bf1dce7c71fc6885bbc8fdce34fe21c8c7d3f348b6dc46ca16b65","href":"https://static.observableusercontent.com/files/df85f37761596bd300e9570b9b4a89a069aeeefca0e1dbe733a03d2803beed9154b79b06f98bf1dce7c71fc6885bbc8fdce34fe21c8c7d3f348b6dc46ca16b65","name":"india.json","type":"application/json","lastModified":1645026182985.596,"size":3453712},{"id":"29d99ad69f64c6ba83750fe5d3dfd7bbe1b16e232ba26a721ceb07394bb2b264ad0db896a37e1bef051483e8a183072f9a32c1ec1f89e26a75bbc44977a13640","href":"https://static.observableusercontent.com/files/29d99ad69f64c6ba83750fe5d3dfd7bbe1b16e232ba26a721ceb07394bb2b264ad0db896a37e1bef051483e8a183072f9a32c1ec1f89e26a75bbc44977a13640","name":"india_data.csv","type":"text/csv","lastModified":1645026204183.52,"size":15906}] 32:{"id":"260b4be85e9500f5","slug":"geog-5540-assignment-2","title":"GEOG 5540 Assignment 2: Classification and Colors","thumbnail":"8a364014e15778dca8cd00a7b0b3e753bb092911cc8ccc476a94ef5c19c888f6","access_level":"public","create_time":"$D2022-02-16T15:42:17.502Z","update_time":"$D2022-03-11T19:29:17.867Z","view_time":null,"first_public_time":"$D2022-02-16T16:05:26.862Z","has_unpublished_edits":null,"fork":{"id":"c68fb87dffeeb9bc","slug":"second-exercise-on-observable","title":"Second Exercise on Observable: Classification and Colors","owner":{"id":"22130e106df70095","login":"geoviz","name":"Geographic Visualization (GEOG 3540) - 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Rather, I will use the variable in the next cell, because it is the variable of my interest and I plan to use it in the future assignments and the project.\npop_den = Array.from(csv_data.values(), d => d[1][10])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":483,"value":"// This variable is the share of the subnational population who use the main language in India. It is also a normalized variable (share = number of the main language speaker/total population in the subnational unit).\nmain_language_share = Array.from(csv_data.values(), d => d[1][3])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":545,"value":"viewof bins = Inputs.range([0, 20], {step: 1, label: \"Bins\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":394,"value":"Plot.plot({\n marks: [\n Plot.rectY(csv_data_objects, Plot.binX({y: \"count\"}, {x: \"main_language_share\", thresholds: bins})),\n Plot.ruleY([0])\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":536,"value":"md`The distribution of the variable:\n\\n The distribution of the variable is not normal. Rather, it is extremely left-skewed. The values for nearly half of the observations fall into the largest group (when the number of group is fixed at 6; When adding the number of groups, most observations fall into the group that is close to the largest value). Then, the number of observations declines as the group value declines (from right to left along the horizontal axis). \n\\n It can be seen that classification does not influence the pattern shown on the histogram too much. If we have more than 2 groups, adding more classes does not change right-skewed distribution pattern shown on the historgram.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":28,"value":"data = Object.assign(new Map(csv_data), {title: [\"Area\", \"Number of Named Languages\",\t\"Main Language\",\t\"Main Language Share\", \"Total Population\", \"Male Population\", \"Female Population\",\t\"Total Literacy\",\t\"Male Literacy\", \"Female Literacy\", \"Population Density\"]})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":174,"value":"md`# Linear Scale (Unclassed)`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":242,"value":"linear = d3.scaleLinear()\n .domain(d3.extent(main_language_share))\n .range([\"#fee0d2\", \"#de2d26\"])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":199,"value":"chart(numericSort(main_language_share), linear)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":267,"value":"md`# Quantile Classification`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":272,"value":"quantile = d3.scaleQuantile()\n .domain(main_language_share)\n .range([\"#fee0d2\", \"#fc9272\", \"#de2d26\"])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":274,"value":"chart(numericSort(main_language_share), quantile)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":323,"value":"md`# Jenks Natural Breaks Classification`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":373,"value":"naturalbreaks = simple.ckmeans(main_language_share, 3).map(v => v.pop())","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":319,"value":"jenks = d3\n .scaleThreshold()\n .domain(naturalbreaks)\n .range([\"#fee0d2\", \"#fc9272\", \"#de2d26\"])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":330,"value":"chart(numericSort(main_language_share), jenks)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":280,"value":"md`# Equal Interval Classification (Quantize)`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":276,"value":"quantize = d3.scaleQuantize()\n .domain([d3.min(main_language_share),d3.max(main_language_share)])\n .range([\"#fee0d2\", \"#fc9272\", \"#de2d26\"])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":282,"value":"chart(numericSort(main_language_share), quantize)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":295,"value":"md`# Threshold`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":289,"value":"threshold = d3.scaleThreshold()\n .domain([0.5, 0.8])\n .range([\"#fee0d2\", \"#fc9272\", \"#de2d26\"])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":297,"value":"chart(numericSort(main_language_share), threshold)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":355,"value":"showScaleGrouping(main_language_share, {\n scaleQuantile: quantile,\n scaleThreshold: threshold,\n scaleJenks: jenks,\n scaleQuantize: quantize,\n scaleQuantizeNice: quantize.copy().nice()\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":129,"value":"md`# Annex`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":261,"value":"function numericSort(x) {\n return (\n x\n // ensure the array is not changed in-place\n .slice()\n // comparator function that treats input as numeric\n .sort((a, b) => a - b)\n );\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":201,"value":"function chart(data, scale) {\n const w = 20,\n cols = Math.floor(Math.min(600, width) / w),\n lines = Math.ceil(200 / cols);\n const chart = d3\n .create(\"svg\")\n .attr(\"width\", cols * w)\n .attr(\"height\", lines * w);\n\n chart\n .append(\"g\")\n .attr(\"transform\", \"translate(2,2)\")\n .attr(\"style\", \"stroke:black; fill:white;\")\n .selectAll(\"rect\")\n .data(data)\n .join(\"rect\")\n .attr(\"width\", w - 3)\n .attr(\"height\", w - 3)\n .attr(\"x\", (_, i) => w * (i % cols))\n .attr(\"y\", (_, i) => w * ((i / cols) | 0))\n .style(\"fill\", d => (scale ? scale(d) : \"#ddd\"));\n return chart.node();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":313,"value":"simple = require(\"simple-statistics@7.0.7/dist/simple-statistics.min.js\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":357,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W35","stdlib":"1","titling":"auto"}} 33:"$32:body"