javascript - 堆叠条形图 24 小时 @ 15 分钟数据，仅显示 2 小时刻度

Question

我一直在寻找如何处理堆叠条形图中的 X 轴(因为数据集与单个条形图略有不同)。

基本上，我有 24 小时内每隔 15 分钟的数据。但是，我只想以 2 小时为单位显示 x 轴。

现有 fiddle :[ https://jsfiddle.net/lucksp/crwb4v5u/][1]

它当前打印所有间隔。

我已经尝试了 time 的各种缩放选项，但有些东西无法按照我的设置方式进行转换。

var xScale = d3.scale.ordinal()
  .domain(dataset[0].map(function(d) {
    return d.x;
  }))
  .rangeRoundBands([0, width - margin.left]);

var xAxis = d3.svg.axis()
  .scale(xScale)
  .orient('bottom')
  .tickSize(0)
  .ticks(12)
  .tickFormat(function(d) {
    return d;
  });
var rect = groups.selectAll('rect')
  .data(function(d) {
    return d;
  })
  .enter()
  .append('rect')
  .attr('class', function(d, i) {
    return 'stacks ' + d.type;
  })
  .classed('stacks', true)
  .attr('id', function(d, i) {
    return d.type + '_' + i;
  })
  .attr('x', function(d) {
    return xScale(d.x);
  })
  .attr('y', function(d) {
    return yScale(d.y0 + d.y);
  })
  .attr('height', function(d) {
    return yScale(d.y0) - yScale(d.y0 + d.y);
  })
  .attr('width', xScale.rangeBand());

  [1]: https://jsfiddle.net/lucksp/crwb4v5u/

我知道这是用户错误，但在过去两天查看此问题后，我现在才提出这个问题。谢谢!

Answer 1

您当前正在尝试使用.ticks，只有当您使用的秤具有内置刻度功能时，该功能才有效。在这种情况下，您的序数尺度不会。默认情况下，它将使用域中的所有值。

为了解决这个问题，我们可以使用 xAxis.tickValues(["与域值匹配的自定义刻度值"]) 手动设置刻度。检查下面的代码片段。

var data = [{"hour":"0:00","inProgress":3,"inQueue":0},{"hour":"0:15","inProgress":5,"inQueue":3},{"hour":"0:30","inProgress":1,"inQueue":1},{"hour":"0:45","inProgress":1,"inQueue":0},{"hour":"1:00","inProgress":2,"inQueue":0},{"hour":"1:15","inProgress":8,"inQueue":2},{"hour":"1:30","inProgress":5,"inQueue":3},{"hour":"1:45","inProgress":5,"inQueue":1},{"hour":"2:00","inProgress":6,"inQueue":0},{"hour":"2:15","inProgress":6,"inQueue":0},{"hour":"2:30","inProgress":7,"inQueue":0},{"hour":"2:45","inProgress":7,"inQueue":0},{"hour":"3:00","inProgress":8,"inQueue":0},{"hour":"3:15","inProgress":8,"inQueue":0},{"hour":"3:30","inProgress":9,"inQueue":1},{"hour":"3:45","inProgress":9,"inQueue":4},{"hour":"4:00","inProgress":10,"inQueue":6},{"hour":"4:15","inProgress":10,"inQueue":2},{"hour":"4:30","inProgress":10,"inQueue":1},{"hour":"4:45","inProgress":11,"inQueue":0},{"hour":"5:00","inProgress":11,"inQueue":0},{"hour":"5:15","inProgress":12,"inQueue":0},{"hour":"5:30","inProgress":12,"inQueue":0},{"hour":"5:45","inProgress":13,"inQueue":0},{"hour":"6:00","inProgress":13,"inQueue":0},{"hour":"6:15","inProgress":14,"inQueue":0},{"hour":"6:30","inProgress":14,"inQueue":0},{"hour":"6:45","inProgress":15,"inQueue":0},{"hour":"7:00","inProgress":15,"inQueue":3},{"hour":"7:15","inProgress":15,"inQueue":1},{"hour":"7:30","inProgress":16,"inQueue":0},{"hour":"7:45","inProgress":16,"inQueue":0},{"hour":"8:00","inProgress":17,"inQueue":2},{"hour":"8:15","inProgress":17,"inQueue":3},{"hour":"8:30","inProgress":18,"inQueue":1},{"hour":"8:45","inProgress":18,"inQueue":0},{"hour":"9:00","inProgress":19,"inQueue":0},{"hour":"9:15","inProgress":19,"inQueue":0},{"hour":"9:30","inProgress":20,"inQueue":0},{"hour":"9:45","inProgress":20,"inQueue":0},{"hour":"10:00","inProgress":20,"inQueue":0},{"hour":"10:15","inProgress":21,"inQueue":1},{"hour":"10:30","inProgress":21,"inQueue":4},{"hour":"10:45","inProgress":22,"inQueue":6},{"hour":"11:00","inProgress":22,"inQueue":2},{"hour":"11:15","inProgress":23,"inQueue":1},{"hour":"11:30","inProgress":23,"inQueue":0},{"hour":"11:45","inProgress":3,"inQueue":0},{"hour":"12:00","inProgress":5,"inQueue":0},{"hour":"12:15","inProgress":1,"inQueue":0},{"hour":"12:30","inProgress":1,"inQueue":0},{"hour":"12:45","inProgress":2,"inQueue":0},{"hour":"13:00","inProgress":8,"inQueue":0},{"hour":"13:15","inProgress":5,"inQueue":0},{"hour":"13:30","inProgress":5,"inQueue":0},{"hour":"13:45","inProgress":6,"inQueue":3},{"hour":"14:00","inProgress":6,"inQueue":1},{"hour":"14:15","inProgress":7,"inQueue":0},{"hour":"14:30","inProgress":7,"inQueue":0},{"hour":"14:45","inProgress":8,"inQueue":2},{"hour":"15:00","inProgress":8,"inQueue":3},{"hour":"15:15","inProgress":9,"inQueue":1},{"hour":"15:30","inProgress":9,"inQueue":0},{"hour":"15:45","inProgress":10,"inQueue":0},{"hour":"16:00","inProgress":10,"inQueue":0},{"hour":"16:15","inProgress":10,"inQueue":0},{"hour":"16:30","inProgress":11,"inQueue":0},{"hour":"16:45","inProgress":11,"inQueue":0},{"hour":"17:00","inProgress":12,"inQueue":1},{"hour":"17:15","inProgress":12,"inQueue":4},{"hour":"17:30","inProgress":13,"inQueue":6},{"hour":"17:45","inProgress":13,"inQueue":2},{"hour":"18:00","inProgress":14,"inQueue":1},{"hour":"18:15","inProgress":14,"inQueue":0},{"hour":"18:30","inProgress":15,"inQueue":0},{"hour":"18:45","inProgress":15,"inQueue":0},{"hour":"19:00","inProgress":15,"inQueue":0},{"hour":"19:15","inProgress":16,"inQueue":0},{"hour":"19:30","inProgress":16,"inQueue":0},{"hour":"19:45","inProgress":17,"inQueue":0},{"hour":"20:00","inProgress":17,"inQueue":0},{"hour":"20:15","inProgress":18,"inQueue":0},{"hour":"20:30","inProgress":18,"inQueue":3},{"hour":"20:45","inProgress":19,"inQueue":1},{"hour":"21:00","inProgress":19,"inQueue":0},{"hour":"21:15","inProgress":20,"inQueue":0},{"hour":"21:30","inProgress":20,"inQueue":2},{"hour":"21:45","inProgress":20,"inQueue":3},{"hour":"22:00","inProgress":21,"inQueue":1},{"hour":"22:15","inProgress":21,"inQueue":0},{"hour":"22:30","inProgress":22,"inQueue":0},{"hour":"22:45","inProgress":22,"inQueue":0},{"hour":"23:00","inProgress":23,"inQueue":0},{"hour":"23:15","inProgress":23,"inQueue":0},{"hour":"23:30","inProgress":1,"inQueue":0},{"hour":"23:45","inProgress":2,"inQueue":1}];

var margin = {top: 20, right: 50, bottom: 30, left: 20},
    width = 500,
    height = 300;

// Transpose the data into layers
var dataset = d3.layout.stack()(['inProgress', 'inQueue'].map(function(types) {
  return data.map(function(d) {
    return {
      x: d.hour,
      y: +d[types],
      type: types
    };
  });
}));

var svg = d3.select('svg'),
    margin = {top: 40, right: 10, bottom: 20, left: 10},
    width = +svg.attr("width") - margin.left - margin.right,
    height = +svg.attr("height") - margin.top - margin.bottom,
    g = svg.append("g").attr("transform", "translate(" + margin.left + "," + margin.top + ")");

// Set x, y and colors
var xScale = d3.scale.ordinal()
  .domain(dataset[0].map(function(d) {
    return d.x;
  }))
  .rangeRoundBands([0, width - margin.left]);

var yScale = d3.scale.linear()
  .domain([0, d3.max(dataset, function(d) {
    return d3.max(d, function(d) {
      return d.y0 + d.y;
    });
  })])
  .range([height, 0]);

var colors = ['#56a8f8', '#c34434'];

// Define and draw axes
var yAxis = d3.svg.axis()
  .scale(yScale)
  .orient('left')
  .ticks(5)
  .tickSize(0)
  .tickFormat(function(d) {
    return d;
  });

var xAxis = d3.svg.axis()
  .scale(xScale)
  .orient('bottom')
  .tickSize(0)
  .ticks(12) // this 
  .tickFormat(function(d) {
    return d; // and this will not work with an ordinal scale
  });
    
  
xAxis.tickValues(["0:00", "2:00", "4:00", "6:00", "8:00", "10:00", "12:00", "14:00", "16:00", "18:00", "20:00", "22:00"]);

svg.append('g')
  .attr('class', 'y axis')
  .call(yAxis);

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

// Create groups for each series, rects for each segment
var groups = svg.selectAll('g.bar-stacks')
  .data(dataset)
  .enter().append('g')
  .attr('class', function(d, i) {
    return 'bar-stacks ' + d[i].type;
  })
  .classed('bar-stacks', true)
  .style('fill', function(d, i) {
    return colors[i];
  });

var rect = groups.selectAll('rect')
  .data(function(d) {
    return d;
  })
  .enter()
  .append('rect')
  .attr('class', function(d, i) {
    return 'stacks ' + d.type;
  })
  .classed('stacks', true)
  .attr('id', function(d, i) {
    return d.type + '_' + i;
  })
  .attr('x', function(d) {
    return xScale(d.x);
  })
  .attr('y', function(d) {
    return yScale(d.y0 + d.y);
  })
  .attr('height', function(d) {
    return yScale(d.y0) - yScale(d.y0 + d.y);
  })
  .attr('width', xScale.rangeBand());

<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.4.11/d3.min.js"></script>
<div>
<svg width="600" height="300"></svg>
</div>