D3带有图表或JSON数据的堆积图 [英] D3 Stacked Chart with array or JSON data

查看:183
本文介绍了D3带有图表或JSON数据的堆积图的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我想创建一个堆积的条形图,例如 http://bl.ocks.org/mbostock/3886208 .但是我不想使用CSV文件.

I want to create a Stacked bar chart like http://bl.ocks.org/mbostock/3886208 . But I don't want to use CSV file.

如何使用数组或JSON数据创建堆积图?

How can I create Stacked chart using array or JSON data?

在csv中,我们这样使用:

In csv we are using like this :

State,Post,Comment    
AL,310504,552339
AK,52083,85640

如何定义数组或json之类的数据

How can I define data in array or json like

var data = []

推荐答案

做到这一点

<!DOCTYPE html>
<meta charset="utf-8">
<style>

body {
  font: 10px sans-serif;
}

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

.bar {
  fill: steelblue;
}

.x.axis path {
  display: none;
}

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

var margin = {top: 20, right: 20, bottom: 30, left: 40},
    width = 960 - margin.left - margin.right,
    height = 500 - margin.top - margin.bottom;

var x = d3.scale.ordinal()
    .rangeRoundBands([0, width], .1);

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

var color = d3.scale.ordinal()
    .range(["#98abc5", "#8a89a6", "#7b6888", "#6b486b", "#a05d56", "#d0743c", "#ff8c00"]);

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

var yAxis = d3.svg.axis()
    .scale(y)
    .orient("left")
    .tickFormat(d3.format(".2s"));

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 = [
    {
    "State": "AL",
    "Under 5 Years": 10,
    "5 to 13 Years": 20,
    "14 to 17 Years": 30,
    "18 to 24 Years": 40,
    "25 to 44 Years": 50,
    "45 to 64 Years": 60,
    "65 Years and Over": 70
  },{
    "State": "AK",
    "Under 5 Years": 15,
    "5 to 13 Years": 25,
    "14 to 17 Years": 35,
    "18 to 24 Years": 45,
    "25 to 44 Years": 55,
    "45 to 64 Years": 65,
    "65 Years and Over": 75
  }];
  color.domain(d3.keys(data[0]).filter(function(key) { return key !== "State"; }));

  data.forEach(function(d) {
    var y0 = 0;
    d.ages = color.domain().map(function(name) { return {name: name, y0: y0, y1: y0 += +d[name]}; });
    d.total = d.ages[d.ages.length - 1].y1;
  });

  data.sort(function(a, b) { return b.total - a.total; });

  x.domain(data.map(function(d) { return d.State; }));
  y.domain([0, d3.max(data, function(d) { return d.total; })]);

  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("Population");

  var state = svg.selectAll(".state")
      .data(data)
    .enter().append("g")
      .attr("class", "g")
      .attr("transform", function(d) { return "translate(" + x(d.State) + ",0)"; });

  state.selectAll("rect")
      .data(function(d) { return d.ages; })
    .enter().append("rect")
      .attr("width", x.rangeBand())
      .attr("y", function(d) { return y(d.y1); })
      .attr("height", function(d) { return y(d.y0) - y(d.y1); })
      .style("fill", function(d) { return color(d.name); });

  var legend = svg.selectAll(".legend")
      .data(color.domain().slice().reverse())
    .enter().append("g")
      .attr("class", "legend")
      .attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });

  legend.append("rect")
      .attr("x", width - 18)
      .attr("width", 18)
      .attr("height", 18)
      .style("fill", color);

  legend.append("text")
      .attr("x", width - 24)
      .attr("y", 9)
      .attr("dy", ".35em")
      .style("text-anchor", "end")
      .text(function(d) { return d; });


</script>

这篇关于D3带有图表或JSON数据的堆积图的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

查看全文
登录 关闭
扫码关注1秒登录
发送“验证码”获取 | 15天全站免登陆