使用嵌套元素数据的双变量线图

时间：2014-01-28 21:03:00

标签： csv d3.js nested graphing

我只需要几天时间学习d3.js，现在我正在尝试通过重新创建此图表来学习如何使用嵌套数据结构创建图形http://bl.ocks.org/mbostock/3894205

enter image description here

...使用不同的数据集。我希望有人能告诉我这样做的正确方法。

这是我的图表的dataset ...即：

date,value,graph
2014-01-28 09:59:00,57.86,0
2014-01-28 09:33:00,56.83,0
2014-01-28 09:17:00,55.82,0
...    
2014-01-27 10:50:00,50.65,1
2014-01-27 10:39:00,49.65,1
2014-01-27 10:19:00,48.64,1

我已经成功创建了一个嵌套数据结构，即：

My Object Preview

现在，我坚持完成显示数据的最后步骤。我认为它可能与这些'NaN'出现在我的svg路径中有关。出于某种原因，我认为我的x轴域可能没有正确设置。这有意义吗？ 

<path class="line"    d="MNaN,125.9725400457666LNaN,128.91876430205951CNaN,131.86498855835242,NaN,137.75743707093827,NaN,143.59267734553782CNaN,149.42791762013735,NaN,155.20594965675062,NaN,163.90160183066365CNaN,172.59725400457668,NaN,184.21052631578948,NaN,189.6453089244851CNaN,195.08009153318076,NaN,194.33638443935922,NaN,193.96453089244847CNaN,193.59267734553768,NaN,193.59267734553768,NaN,202.14530892448505CNaN,210.69794050343245,NaN,227.80320366132722,NaN,231.06407322654462CNaN,234.32494279176203,NaN,223.74141876430207,NaN,2...739130434784CNaN,150.28604118993135,NaN,156.06407322654462,NaN,160.35469107551486CNaN,164.64530892448514,NaN,167.44851258581235,NaN,169.6796338672769CNaN,171.91075514874143,NaN,173.56979405034326,NaN,187.07093821510296CNaN,200.57208237986268,NaN,225.91533180778026,NaN,226.63043478260863CNaN,227.345537757437,NaN,203.43249427917615,NaN,194.45080091533177CNaN,185.46910755148735,NaN,191.41876430205946,NaN,197.3398169336384CNaN,203.26086956521735,NaN,209.1533180778032,NaN,212.0995423340961LNaN,215.045766590389">

感谢。

1 个答案:

答案 0 :(得分：0)

有趣的是，问题不在于线条或数据对象，而在于我的轴的域。我通过调整我的x.domain和y.domain来解决这个问题。最终代码：

<!DOCTYPE html>
<meta charset="utf-8">
<style>
body {
font: 10px sans-serif;
}

.axis path,
.axis line {
fill: none;
stroke: #000;
shape-rendering: crispEdges;
}


.area.above { 
fill: rgb(252,141,89);
}

.area.below {
fill: rgb(145,207,96);
}

.line {
fill: none;
stroke: #000;
stroke-width: 1.5px;
}

body{margin:0px;}
rect {stroke:black;fill:white;}
circle {fill:steelblue;opacity:.5;}


</style>
<body>
<script src="http://d3js.org/d3.v3.min.js"></script>
<script>

var margin = {top: 20, right: 20, bottom: 30, left: 50},
width = 960 - margin.left - margin.right,
height = 500 - margin.top - margin.bottom;

var parseDate = d3.time.format("%Y-%m-%d %H:%M:%S").parse;  

var x = d3.time.scale()
.range([0, width]);

var y = d3.scale.linear()
.range([height, 0]);

var xAxis = d3.svg.axis()
.scale(x)
.orient("bottom");

var yAxis = d3.svg.axis()
.scale(y)
.orient("left");

var color = d3.scale.category10();


var line = d3.svg.line()
.interpolate("basis")
.x(function(d) { return x(d.date); })
.y(function(d) { return y(d.value); });


var svg = d3.select("body").append("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom)
.append("g")
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");

var data;   
d3.csv("tempdifference.csv",function(csv) {

csv.forEach(function(d) {
d.date = parseDate(d.date);
});

data=d3.nest()
.key(function(d) {return d.graph;})
.entries(csv);
console.log(data);


x.domain(d3.extent(csv, function(d) { return d.date; }));
y.domain([
d3.min(data, function(c) { return d3.min(c.values, function(v) { return v.value; }); }),
d3.max(data, function(c) { return d3.max(c.values, function(v) { return v.value; }); })
]);



svg.append("g")
  .attr("class", "x axis")
  .attr("transform", "translate(0," + height + ")")
  .call(xAxis);

svg.append("g")
  .attr("class", "y axis")
  .call(yAxis)
.append("text")
  .attr("transform", "rotate(-90)")
  .attr("y", 6)
  .attr("dy", ".71em")
  .style("text-anchor", "end")
  .text("Temperature (°F)");      


var graph = svg.selectAll(".graph")
  .data(data)
.enter().append("g")
  .attr("class", "graph");

graph.append("path")
  .attr("class", "line")
  .attr("d", function(d) { return line(d.values); })


  console.log(graph);


console.log(svg);
});



</script>
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