31:Tf23,games = [{"game":"Wii Sports","rank":1,"sales":82.74},{"game":"Super Mario Bros.","rank":2,"sales":40.24},{"game":"Mario Kart Wii","rank":3,"sales":35.82},{"game":"Wii Sports Resort","rank":4,"sales":33},{"game":"Pokemon Red/Pokemon Blue","rank":5,"sales":31.37},{"game":"Tetris","rank":6,"sales":30.26},{"game":"New Super Mario Bros.","rank":7,"sales":30.01},{"game":"Wii Play","rank":8,"sales":29.02},{"game":"New Super Mario Bros. Wii","rank":9,"sales":28.62},{"game":"Duck Hunt","rank":10,"sales":28.31},{"game":"Brain Age: Train Your Brain in Minutes a Day","rank":20,"sales":20.22},{"game":"Call of Duty: Modern Warfare 3","rank":30,"sales":14.76},{"game":"Super Smash Bros. Brawl","rank":40,"sales":13.04},{"game":"Pokemon Omega Ruby/Pokemon Alpha Sapphire","rank":50,"sales":11.33},{"game":"Super Mario 64","rank":60,"sales":10.42},{"game":"Gran Turismo 2","rank":70,"sales":9.49},{"game":"Halo 2","rank":80,"sales":8.49},{"game":"Pac-Man","rank":90,"sales":7.81},{"game":"Battlefield 3","rank":100,"sales":7.34},{"game":"FIFA Soccer 11","rank":200,"sales":5.08},{"game":"Fallout 3","rank":300,"sales":4.01},{"game":"Professor Layton and the Unwound Future","rank":400,"sales":3.36},{"game":"Hot Shots Golf 3","rank":500,"sales":2.89},{"game":"Dragon Age: Origins","rank":600,"sales":2.57},{"game":"Just Dance 2015","rank":700,"sales":2.28},{"game":"Metal Gear Solid: Peace Walker","rank":800,"sales":2.09},{"game":"The Sims: Makin' Magic","rank":900,"sales":1.92},{"game":"2 Games in 1 Double Pack: The Incredibles / Finding Nemo: The Continuing Adventures","rank":1000,"sales":1.76},{"game":"Heavenly Sword","rank":1100,"sales":1.66},{"game":"Active Life: Outdoor Challenge","rank":1200,"sales":1.55},{"game":"The SpongeBob SquarePants Movie","rank":1300,"sales":1.46},{"game":"Deus Ex: Human Revolution","rank":1400,"sales":1.39},{"game":"LEGO Batman: The Videogame","rank":1500,"sales":1.32},{"game":"Baldur's Gate: Dark Alliance","rank":1600,"sales":1.24},{"game":"FIFA 14","rank":1700,"sales":1.19},{"game":"Guitar Hero 5","rank":1800,"sales":1.14},{"game":"Fisherman's Bass Club","rank":1900,"sales":1.08},{"game":"Dance Dance Revolution SuperNOVA","rank":2000,"sales":1.04},{"game":"Guitar Hero: Aerosmith","rank":2100,"sales":0.99},{"game":"The SpongeBob SquarePants Movie","rank":2200,"sales":0.94},{"game":"SOCOM 4: U.S. Navy SEALs","rank":2300,"sales":0.9},{"game":"Wizards of Waverly Place","rank":2400,"sales":0.87},{"game":"I Spy: Fun House","rank":2500,"sales":0.83},{"game":"The Walking Dead: Season One","rank":2600,"sales":0.79},{"game":"SoulCalibur V","rank":2700,"sales":0.76},{"game":"Yoshi","rank":2800,"sales":0.73},{"game":"NBA Live 09","rank":2900,"sales":0.71},{"game":"Red Steel","rank":3000,"sales":0.68},{"game":"The Evil Within","rank":3100,"sales":0.65},{"game":"Disney Universe","rank":3200,"sales":0.63},{"game":"Cooking Mama 4: Kitchen Magic!","rank":3300,"sales":0.61},{"game":"Total War: Shogun 2","rank":3400,"sales":0.59},{"game":"Tetris Party Deluxe","rank":3500,"sales":0.58},{"game":"Lips: Number One Hits","rank":3600,"sales":0.56},{"game":"System 3 presents Ferrari Challenge Trofeo Pirelli","rank":3700,"sales":0.54},{"game":"Alice in Wonderland","rank":3800,"sales":0.53},{"game":"Summoner","rank":3900,"sales":0.51},{"game":"Cars 2","rank":4000,"sales":0.5},{"game":"You're in the Movies","rank":4100,"sales":0.48},{"game":"Need for Speed Carbon","rank":4200,"sales":0.47},{"game":"iCarly","rank":4300,"sales":0.46},{"game":"Sled Storm","rank":4400,"sales":0.45},{"game":"Need for Speed Underground 2","rank":4500,"sales":0.43},{"game":"SpongeBob's Truth or Square (US sales)","rank":4600,"sales":0.42},{"game":"Destiny: The Taken King","rank":4700,"sales":0.41},{"game":"WipeOut 3 The Game","rank":4800,"sales":0.4},{"game":"NBA Live 09","rank":4900,"sales":0.39},{"game":"The Cat in the Hat","rank":5000,"sales":0.38}]32:[] 2f:{"title":"Power Law Regression","cells":[{"id":0,"value":"md`# Power Law Regression\n\nPower law regressions take the form ${tex`y = ax^b`}. Use [d3-regression](https://github.com/HarryStevens/d3-regression)'s d3.[regressionPow()](https://github.com/HarryStevens/d3-regression#regressionPow) like this:`","pinned":false,"hidden":false,"mode":"ojs"},{"id":29,"value":"regressionGenerator = d3.regressionPow()\n .x(d => d.rank)\n .y(d => d.sales);","pinned":true,"hidden":false,"mode":"ojs"},{"id":194,"value":"md`d3.regressionPow() returns a configurable function with x- and y- accessors (which default to d => d[0] and d => d[1], respectively). If you want the resulting line to extend beyond the extents of your input data, you can specify a domain.\n\nWhen you pass data to the regression generator, you'll get back an array of points representing a curved line. You can use a d3.[line()](https://github.com/d3/d3-shape#line) to render it in SVG or Canvas:`","pinned":false,"hidden":false,"mode":"ojs"},{"id":64,"value":"lineGenerator = d3.line()\n .x(d => xScale(d[0]))\n .y(d => yScale(d[1]));","pinned":true,"hidden":false,"mode":"ojs"},{"id":85,"value":"{\n const svg = d3.select(DOM.svg(innerWidth + margin.left + margin.right, innerHeight + margin.top + margin.bottom))\n \n const g = svg.append(\"g\")\n .attr(\"transform\", `translate(${margin.left}, ${margin.top})`)\n\n g.append(\"g\")\n .attr(\"class\", \"axis\")\n .call(xAxisGenerator)\n .selectAll(\".tick line\")\n .classed(\"baseline\", d => d === 0);\n \n g.append(\"g\")\n .attr(\"class\", \"axis\")\n .attr(\"transform\", `translate(${innerWidth})`)\n .call(yAxisGenerator)\n .selectAll(\".tick line\")\n .classed(\"baseline\", d => d === 0);\n\n g.selectAll(\"circle\")\n .data(games)\n .enter().append(\"circle\")\n .attr(\"r\", 2)\n .attr(\"cx\", d => xScale(d.rank))\n .attr(\"cy\", d => yScale(d.sales));\n\n g.append(\"path\")\n .attr(\"class\", \"regression\")\n .datum(regressionGenerator(games))\n .attr(\"d\", lineGenerator);\n\n return svg.node();\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":32,"value":"md`This example comes from [\"Power Law in Popular Media\"](https://medium.com/@michaeltauberg/power-law-in-popular-media-7d7efef3fb7c) by Michael Tauberg. The regression is described by the equation ${tex`y = ${regressionGenerator(games).a.toFixed(3)}x^{${regressionGenerator(games).b.toFixed(3)}}`}. The coefficient of determination, or ${tex`R^2`}, is ${regressionGenerator(games).rSquared.toFixed(3)}.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":202,"value":"md`[**d3-regression**](https://github.com/harrystevens/d3-regression) is a [D3.js](https://d3js.org/) module for calculating statistical regressions from two-dimensional data. It is dependency-free, and its API exposes configurable functions that transform input data, in the manner of other D3 modules.\n\nFor an explanation of all of d3-regression's capabilities, see [this tutorial](https://observablehq.com/d/7b51129a2feec1d0).`","pinned":false,"hidden":false,"mode":"ojs"},{"id":58,"value":"md`## Data`","pinned":false,"hidden":false,"mode":"ojs"},{"id":106,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":87,"value":"md`## Dimensions`","pinned":false,"hidden":false,"mode":"ojs"},{"id":89,"value":"margin = ({left: 30, right: 9, top: 18, bottom: 21})","pinned":false,"hidden":false,"mode":"ojs"},{"id":90,"value":"base = Math.min(width, 400)","pinned":false,"hidden":false,"mode":"ojs"},{"id":93,"value":"innerWidth = base - margin.left - margin.right","pinned":false,"hidden":false,"mode":"ojs"},{"id":95,"value":"innerHeight = base - margin.top - margin.bottom","pinned":false,"hidden":false,"mode":"ojs"},{"id":66,"value":"md`## Scales`","pinned":false,"hidden":false,"mode":"ojs"},{"id":68,"value":"xScale = d3.scaleLinear()\n .domain([0, 5e3])\n .range([0, innerWidth]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":71,"value":"yScale = d3.scaleLinear()\n .domain([100, 0])\n .range([0, innerHeight])","pinned":false,"hidden":false,"mode":"ojs"},{"id":74,"value":"md`## Axes`","pinned":false,"hidden":false,"mode":"ojs"},{"id":76,"value":"xAxisGenerator = d3.axisBottom(xScale)\n .tickSize(innerHeight + 10)\n .tickValues(d3.range(0, 6e3, 1e3))\n .tickFormat(d => d >= 1e3 ? `${d / 1e3}k` : d)","pinned":false,"hidden":false,"mode":"ojs"},{"id":78,"value":"yAxisGenerator = d3.axisLeft(yScale)\n .tickSize(innerWidth + 10)","pinned":false,"hidden":false,"mode":"ojs"},{"id":62,"value":"md`## Styles`","pinned":false,"hidden":false,"mode":"ojs"},{"id":60,"value":"html`\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":54,"value":"md`## Imports`","pinned":false,"hidden":false,"mode":"ojs"},{"id":52,"value":"d3 = require(\"d3-array@3\", \"d3-axis@3\", \"d3-regression@2\", \"d3-scale@4\", \"d3-shape@3\", \"d3-selection@3\")","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}