30:T600,chart = { const svg = d3.select(DOM.svg(width,height)) .style("viewBox",[0,0,width,height]) .style("background-color","#eadde6") svg.append("text") .attr("x",width/2) .attr("y",50) .style("text-anchor","middle") .text("Seoul Bike Sharing") .style("fill","#d96d3c") .style("font-size","2em") .style("font-weight","bold") svg.append("g") .call(xAxis) .style("color","#d96d3c") .style("font-size","0.9em") .style("font-weight","bold") svg.append("g") .call(yAxis) .style("color","#d96d3c") .style("font-size","0.8em") .style("font-weight","bold") svg.append("g") .selectAll("circle") .data(data) .join("circle") .attr("cx",d=>tempScale(d.Temperature)) .attr("cy",d=>y(d.RentedBikeCount)) .attr("r",1.2) .style("fill","#d96d3c") svg.append("path") .datum(point) .attr("d",regressionLine) .attr("fill","none") .attr("stroke","white") .style("stroke-width",2.5 ) svg.append("text") .attr("x",-height/2+80) .attr("y",25) .text("Number of bikes rented") .style("text-anchor","end") .attr("transform","rotate(-90)") .style("fill","#d96d3c") .style("font-weight","normal") svg.append("text") .attr("x",width/2) .attr("y",height-20) .style("text-anchor","middle") .text("Temperature in °C") .style("fill","#d96d3c") .style("font-weight","normal") return svg.node() }31:[{"id":"14c995a7a89b917470c829fdd503691f1dca2dbc61f2657fe1983306ccc2fdf83e9a74623e37067936719c2cc4ec4bf602a5601d668cc3e066f44122d8f38c61","href":"https://static.observableusercontent.com/files/14c995a7a89b917470c829fdd503691f1dca2dbc61f2657fe1983306ccc2fdf83e9a74623e37067936719c2cc4ec4bf602a5601d668cc3e066f44122d8f38c61","name":"SeoulBikeSharing.csv","type":"text/csv","lastModified":1618340120270.579,"size":604111}] 2e:{"title":"Seoul Bike Sharing","cells":[{"id":6,"value":"html`

Seoul Bike Sharing

Week 3:Relationships. Day 13:Correlation.

#30daychartchallenge

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":337,"value":"html`

Data Credit:\nUCI Machine Learning Repository: Seoul Bike Sharing Demand Data Set

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":71,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":87,"value":"xAxis = g => g.attr(\"transform\",`translate(0,${height-margin.left})`)\n .call(d3.axisBottom(tempScale))","pinned":false,"hidden":false,"mode":"ojs"},{"id":132,"value":"tempScale = d3.scaleLinear()\n .domain(d3.extent(data,d=>d.Temperature))\n .range([margin.top,width-margin.top])","pinned":false,"hidden":false,"mode":"ojs"},{"id":106,"value":"yAxis = g => g.attr(\"transform\",`translate(${margin.top},0)`)\n .call(d3.axisLeft(y))","pinned":false,"hidden":false,"mode":"ojs"},{"id":104,"value":"y = d3.scaleLinear()\n .domain(d3.extent(data,d=>d.RentedBikeCount))\n .range([height-margin.left,margin.top])","pinned":false,"hidden":false,"mode":"ojs"},{"id":210,"value":"point = {\n const firstX = -12\n const lastX = 39.4\n const xCoordinates = [firstX, lastX]\n \n return xCoordinates.map(d=>({\n x: d,\n y: line(d)\n }))\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":212,"value":"regressionLine = d3.line()\n .x(d=>tempScale(d.x))\n .y(d=>y(d.y))","pinned":false,"hidden":false,"mode":"ojs"},{"id":208,"value":"line = stats.linearRegressionLine(linearRegression)","pinned":false,"hidden":false,"mode":"ojs"},{"id":206,"value":"linearRegression = stats.linearRegression(data.map(d=>[d.Temperature,d.RentedBikeCount]))","pinned":false,"hidden":false,"mode":"ojs"},{"id":85,"value":"margin = ({top: 90, right: 5, bottom: 10, left: 60})","pinned":false,"hidden":false,"mode":"ojs"},{"id":73,"value":"height = 550","pinned":false,"hidden":false,"mode":"ojs"},{"id":24,"value":"data = FileAttachment(\"SeoulBikeSharing.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":204,"value":"stats = require('simple-statistics')","pinned":false,"hidden":false,"mode":"ojs"},{"id":22,"value":"d3 = require(\"d3@6\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W31","stdlib":"1","titling":"auto"}