1. 前言
色階圖適合二維的數據,而且橫軸跟縱軸的標簽都比較多。本期的數據:
Example data shows concurrent user sessions over time, taken from a development environment.
翻譯過來大意就是:展示的是隨着時間的推移用戶會話並發的個數
數據結構:
星期數 | 時間點 | 會話數 |
day | hour | value |
1 | 1 | 16 |
圖形:
2. 色階圖
1)本地鏈接:本地色階圖demo展示
2)知識點: 1. 怎么畫色階圖
2. 讀取csv格式數據畫圖,並且解決中文亂碼問題
3. 圖形的轉變效果: d3.transition().duration()
4. x軸文字豎放以及標簽突出重點
3)圖形效果:
自己應用的場景:某品牌商想重點關注自己的產品型號在重點電商店鋪的銷量情況,這里涉及的型號和店鋪都很多,導致excel數據表非常的龐大而稀疏,所以用色階圖會比較直觀的展示出top-N的店鋪里哪種型號賣的好,某些特定的型號會在哪些店鋪買的好。顏色的深淺就代表銷量的多少,越深越多,越淺越少。
4)完整的網頁代碼(內含詳細解釋):

1 <!DOCTYPE html> 2 <meta charset="utf-8"> 3 <html> 4 <head> 5 <style> //css樣式區 6 rect.bordered {stroke: #E6E6E6;stroke-width:2px;} 7 text.mono {font-size: 9pt;font-family: Consolas, courier;fill: #aaa;} 8 text.axis-workweek {fill: #000;} 9 text.axis-worktime {fill: #000;} 10 </style> 11 <script src="http://d3js.org/d3.v3.js"></script> 12 </head> 13 <body> 14 <div id="chart"></div> 15 <div id="dataset-picker"> 16 </div> 17 <script type="text/javascript"> 18 //1. 先定義一些全局變量 19 var margin = { top: 80, right: 0, bottom: 100, left: 150 }, 20 width = 1000 - margin.left - margin.right, 21 height = 800 - margin.top - margin.bottom, 22 gridSize = Math.floor(width / 73),//格子的大小 23 legendElementWidth = gridSize*5, //圖例的寬度 24 buckets = 9, 25 colors = ["#ffffd9","#edf8b1","#c7e9b4","#7fcdbb","#41b6c4","#1d91c0","#225ea8","#253494","#081d58"], // alternatively colorbrewer.YlGnBu[9] 26 times=[['E408','0'],['E488','0'],['E518','0'],['E568','0'],['G1800','1'],['G2800','1'],['G3800','1'],['IP110','0'],['IP1188','0'],['IP2780','1'],['IP2880S','1'],['IP7280','1'],['IP8780','0'],['IX6580','0'],['IX6780','0'],['IX6880','0'],['LBP151dw','0'],['LBP2900+','0'],['LBP5960(A3)','0'],['LBP6018L','1'],['LBP6018W','0'],['LBP6230dn','1'],['LBP6230dw','0'],['LBP6300dn','0'],['LBP7010C','1'],['LBP7100Cn','0'],['LBP7200Cd','0'],['LBP8100n(A3)','0'],['LBP9100Cdn(A3)','0'],['MF211','0'],['MF212w','1'],['MF215','0'],['MF216n','0'],['MF226dn','0'],['MF229dw','0'],['MF3010','0'],['MF4712','1'],['MF4752','1'],['MF6140dn','0'],['MF621Cn','0'],['MF623Cn','0'],['MF628Cw','0'],['MF725Cdn','0'],['MF727Cdw','0'],['MF810Cdn','0'],['MG2400','0'],['MG2580S','1'],['MG2980','0'],['MG3680','1'],['MG5780','0'],['MG6880','0'],['MG7780','1'],['MP236','0'],['MP288','1'],['MX498','0'],['MX538','0'],['MX728','0'],['MX928','0'],['PRO-1','0'],['PRO-10','0'],['PRO-100','0'],['PRO-500','0']] 27 days = ['店鋪1','店鋪2','店鋪3','店鋪4','店鋪5','店鋪6','店鋪7','店鋪8','店鋪9','店鋪10','店鋪11','店鋪12','店鋪13','店鋪14','店鋪15','店鋪16','店鋪17','店鋪18','店鋪19','店鋪20','店鋪21','店鋪22','店鋪23','店鋪24','店鋪25','店鋪26','店鋪27','店鋪28','店鋪29','店鋪30','店鋪31','店鋪32','店鋪33','店鋪34','店鋪35','店鋪36','店鋪37','店鋪38','店鋪39','店鋪40','店鋪41','店鋪42','店鋪43','店鋪44','店鋪45','店鋪46','店鋪47','店鋪48','店鋪49','店鋪50','店鋪51','店鋪52','店鋪53','店鋪54','店鋪55','店鋪56','店鋪57','店鋪58','店鋪59','店鋪60','店鋪61','店鋪62','店鋪63','店鋪64','店鋪65','店鋪66','店鋪67','店鋪68','店鋪69','店鋪70','店鋪71','店鋪72','店鋪73','店鋪74','店鋪75','店鋪76','店鋪77','店鋪78','店鋪79','店鋪80','店鋪81','店鋪82','店鋪83','店鋪84','店鋪85','店鋪86','店鋪87','店鋪88','店鋪89','店鋪90','店鋪91','店鋪92','店鋪93','店鋪94','店鋪95','店鋪96','店鋪97','店鋪98','店鋪99','店鋪100','店鋪101','店鋪102','店鋪103','店鋪104','店鋪105','店鋪106','店鋪107','店鋪108','店鋪109','店鋪110','店鋪111','店鋪112','店鋪113','店鋪114','店鋪115','店鋪116','店鋪117','店鋪118','店鋪119','店鋪120'] 28 datasets = ["data.csv", "data2.csv"]; //數據文件變量 29 //2. 畫布 30 var svg = d3.select("#chart").append("svg") 31 .attr("width", width + margin.left + margin.right) 32 .attr("height", height + margin.top + margin.bottom) 33 .append("g") 34 .attr("transform", "translate(" + margin.left + "," + margin.top + ")"); 35 //3. 軸Y 36 var dayLabels = svg.selectAll(".dayLabel") 37 .data(days) 38 .enter().append("text") 39 .text(function (d) { return d; }) 40 .attr("x", 0) 41 .attr("y", function (d, i) { return i * gridSize; }) 42 .style("text-anchor", "end") 43 .attr("transform", "translate(-6," + gridSize / 1.5 + ")") 44 .attr("class", function (d, i) { return ((i >= 0 && i <= 29) ? "dayLabel mono axis axis-workweek" : "dayLabel mono axis"); }) ;//軸標簽是否明顯顯示 45 //4. 軸X 46 var timeLabels = svg.selectAll(".timeLabel") 47 .data(times) 48 .enter().append("text") 49 .text(function(d) { return d[0]; }) 50 .attr("x",gridSize) 51 .attr("y", 0) 52 .style("text-anchor", "start") 53 .attr("transform",function(d,i) { return "translate(" + gridSize*(i+1) + ", 8)rotate(" + (- 90) + ")"}) //x軸文字豎放 54 .attr("class", function(d, i) {console.log(d);return ((d[1]==1) ? "timeLabel mono axis axis-worktime" : "timeLabel mono axis"); })//軸標簽是否明顯顯示 55 56 //5. 定義heatmapChart函數,輸入文件路徑即可畫圖 57 var heatmapChart = function(tsvFile) { 58 var csv = d3.dsv(",", "text/csv;charset=gb2312"); //解決中文轉碼 59 csv(tsvFile,function(d) { return {day: +d.day,hour: +d.hour,value: +d.value};}, 60 61 function(error, data) { 62 var colorScale = d3.scale.quantile() //比例尺:與quantize類似,但輸入值域是獨立的值,適合已經對數據分類的情形。 63 .domain([0, buckets - 1, d3.max(data, function (d) { return d.value; })]) 64 .range(colors); 65 66 var cards = svg.selectAll(".hour") 67 .data(data, function(d) {return d.day+':'+d.hour;}); 68 69 cards.append("title"); 70 71 cards.enter().append("rect") 72 .attr("x", function(d) { return (d.hour - 1) * gridSize; }) 73 .attr("y", function(d) { return (d.day - 1) * gridSize; }) 74 .attr("rx", 4) 75 .attr("ry", 4) 76 .attr("class", "hour bordered") 77 .attr("width", gridSize) 78 .attr("height", gridSize) 79 .style("fill", colors[0]); 80 81 //顏色漸變效果 82 cards.transition().duration(1000) 83 .style("fill", function(d) { return colorScale(d.value); }); 84 85 cards.select("title").text(function(d) { return d.value; }); 86 87 cards.exit().remove(); 88 89 //添加圖例 90 var legend = svg.selectAll(".legend") 91 .data([0].concat(colorScale.quantiles()), function(d) { return d; }); 92 93 legend.enter().append("g") 94 .attr("class", "legend"); 95 96 legend.append("rect") 97 .attr("x", width-150) 98 .attr("y",function(d, i) { return legendElementWidth * i; }) 99 .attr("width", legendElementWidth) 100 .attr("height", gridSize / 2) 101 .style("fill", function(d, i) { return colors[i]; }); 102 103 legend.append("text") 104 .attr("class", "mono") 105 .text(function(d) { return "≥ " + Math.round(d); }) 106 .attr("x", width-150+gridSize*2) 107 .attr("y",function(d, i) { return legendElementWidth * i-gridSize; }) 108 .style("fill", "black"); 109 legend.exit().remove(); 110 111 }); 112 }; 113 114 //6. 調用前面的heatmapChart函數,輸入數據文件名稱 115 heatmapChart(datasets[0]); 116 117 //7. 按鈕 118 var datasetpicker = d3.select("#dataset-picker").selectAll(".dataset-button") 119 .data(datasets); 120 121 datasetpicker.enter() 122 .append("input") 123 .attr("value", function(d){ return "Dataset " + d }) 124 .attr("type", "button") 125 .attr("class", "dataset-button") 126 .on("click", function(d) { 127 heatmapChart(d); 128 }); 129 </script> 130 </body> 131 </html>