d3.js - 堆积条形图中的第 2 组数据值

我有以下 csv 数据，

date,scanned,unscanned,compid,sbu
01/2014,10,90,101,f&r
02/2014,55,40,101,f&r
03/2014,45,23,101,f&r
04/2014,65,35,101,f&r
05/2014,100,20,101,f&r
06/2014,50,30,101,f&r
07/2014,10,90,101,f&r
08/2014,22,48,101,f&r
09/2014,0,100,101,f&r
10/2014,3,97,101,f&r
11/2014,22,60,101,f&r
12/2014,57,37,101,f&r
01/2014,30,100,101,ip
02/2014,130,10,101,ip

有没有一种方法可以将 2014 年 1 月的 f&r 和 ip sbu 值的数据合并起来，并在堆积栏中显示这些值。例如，如果我选中一个复选框进行分组，我需要在 2014 年 1 月的 x 轴堆栈中显示扫描为 30+10=40，未扫描为 100+90= 190。

我构建堆栈栏的代码如下：

var w = 960,
    h = 500,
    p = [20, 50, 30, 20],

    x = d3.time.scale().range([1, 80]);
    y = d3.scale.linear().range([0, h - p[0] - p[2]]),
    z = d3.scale.ordinal().range(["#819FF7", "#CB491A"]),
    parse = d3.time.format("%m/%Y").parse,
    format = d3.time.format("%b-%y");

    var xAxis=d3.svg.axis()
          .scale(x)
          .orient("bottom")
          .ticks(d3.time.month, 1)
              //.ticks(12)



   xAxis.tickFormat(d3.time.format("%b-%y"));


    /*var yAxis = d3.svg.axis()
    .scale(y)
    .ticks(12)
    .orient("left");*/

var svg = d3.select("#container").append("svg:svg")
    .attr("width", w)
    .attr("height", h)
  .append("svg:g")
    .attr("transform", "translate(" + p[3] + "," + (h - p[2]) + ")");

d3.csv("scandata.csv", function(scan) {

  // Transpose the data into layers by cause.
  var scantypes = d3.layout.stack()(["scanned", "unscanned"].map(function(scans) {
    return scan.map(function(d) {
      return {x: parse(d.date), y: +d[scans],z:d.compid,typescan:scans};
    });
  }));




  // Compute the x-domain (by date) and y-domain (by top).
  x.domain(scantypes [0].map(function(d) { return d.x; }));
  y.domain([0, d3.max(scantypes[scantypes .length - 1], function(d) { return d.y0 + d.y; })]);

  // Add a group for each scan.
  var cause = svg.selectAll("g.scan")
      .data(scantypes)
    .enter().append("svg:g")
      .attr("class", "scan")
      .style("fill", function(d, i) { return z(i); })
      .style("stroke", function(d, i) { return d3.rgb(z(i)).darker(); });

  // Add a rect for each date.
  var rect = cause.selectAll("rect")
      .data(Object)
    .enter().append("svg:rect")
      .attr("id", function(d,i) { return i + " comp " + d.z;  })
      .attr("x", function(d,i) { 
                        if (i ==0) 
                        { 
                            return x(d.x) ;
                        } 
                        else 
                        {
                            return x(d.x);
                        }} )
      .attr("y", function(d) { return -y(d.y0) - y(d.y); })
      .attr("height", function(d) { return y(d.y); })
      .attr("width", 30)//x.rangeBand()/2
    .on("mouseover", function(d){

                   return tooltip.style("visibility", "visible")
                                   .text((d.y))//d.typescan + " -  " + 
                                   .style("left", (d3.event.pageX) + "px") 
                                   .style("top", (d3.event.pageY - 20) + "px");      ;})
      .on("mousemove", function(d){

                      return tooltip.style("visibility", "visible")
                                   .text((d.y)) //d.typescan + " -  " + 
                                   .style("left", (d3.event.pageX) + "px") 
                                   .style("top", (d3.event.pageY - 20) + "px");      ;})

      .on("mouseout", function(d){return tooltip.style("visibility", "hidden");}) 
      .on("click", function(d){});



  var tooltip = d3.select("#container")
    .append("div")
    .style("position", "absolute")
    .style("z-index", "10")
    .style("visibility", "visible")
    .text("Scanned vs UnScanned")
    .style("font", "Arial")
      .style("color", "white")
    .style("font-size", "14px");

  //Add x-Axis
    svg.append("g")
    .attr("class", "x axis")
    //.attr("transform", function(d) { return "translate(0,80)"; })
    .call(xAxis)




  // Add a label per date.
  var label = svg.selectAll("text")
      .data(x.domain())
    .enter().append("svg:text")
      .attr("x", function(d) { return x(d.x); })//x.rangeBand() / 4
      .attr("y", 6)
      .attr("text-anchor", "middle")
      .attr("dy", ".71em")
      .text(format);

  // Add y-axis rules.
  var rule = svg.selectAll("g.rule")
      .data(y.ticks(5))
    .enter().append("svg:g")
      .attr("class", "rule")
      .attr("transform", function(d) { return "translate(0," + -y(d) + ")"; });

  rule.append("svg:line")
      .attr("x2", w - p[1] - p[3])
      .style("stroke", function(d) { return d ? "#fff" : "#000"; })
      .style("stroke-opacity", function(d) { return d ? .7 : null; });

  rule.append("svg:text")
      .attr("x", -15)
      .style("font-family","Arial 12px")
      .attr("dy", ".25em")
      .text(d3.format(",d"));

您似乎对 SVG 应该是什么样子感到困惑，因此不知道如何实现它。

SVG 中的条形只是矩形。您需要告诉他们应该放置在哪里（始终由栏的左上角定义）以及它们应该有多大。

要使条形在堆叠图中对齐，您需要根据该堆叠的所有值计算出它们的位置和大小。

我创建了一个非常简化使用您的数据的堆积条形图的示例（只是扫描/未扫描的数据，我没有通过 sbu 变量将数据分开）。

这是工作中的example

这是带注释的代码：

var width = 400;
    height = 500;

var svg = d3.select("body").append("svg")
            .attr("width", width)
            .attr("height", height);

var xScale = d3.scale.ordinal()
               .rangeRoundBands([0,width], 0.1);
var yScale = d3.scale.linear()
               .range([height, 0]);
        //note the inverted range, so that small values
        //scale to the bottom of the SVG

var data = d3.csv.parse( d3.select("pre#data").text() );
//this just grabs the text from the preformatted block
//and parses it as if it was a csv file
//in your real code, you would use d3.csv(filename, callbackFunction) 
//and the rest would be inside your callback function:

xScale.domain( data.map(function(d){return d.date;}) );
//the xScale domain is the list of all categorical values.
//The map function grabs all the date values from the data
//and returns them as a new array.
//I'm not worrying about parsing dates, since
//strings work fine with an ordinal scale
//(although you'd want to parse them if you wanted to reformat them).

yScale.domain( [0,
                d3.max(data,
                       function(d){
                           return +d.scanned + +d.unscanned;
                       })
                ]);
//The yScale domain starts at 0 (since it's a bar chart)
//and goes to the maximum *total* value for each date.
//The d3.max function finds the maximum for an array
//based on the result returned by the function for each
//element of the array.  This function just finds the sum
//of the scanned and unscanned values 
//(after converting them from strings to numbers with "+").


var dateGroups = svg.selectAll("g") 
        //create an empty selection of groups
   .data(data); //join to the data, each row will get a group

dateGroups.enter().append("g")
    //create the actual <g> elements for each row of data
    .attr("class", "dateGroup"); 
    //give them a meaningful class

//Now, within each group create a rectangle 
//for each category (scanned and unscanned).
//If you had lots of categories, you'd want to 
//use a nested selection and a second data join.
//However, to do that you'd need to do a lot of 
//data manipulation to create an array of 
//separate data objects for each category.
//
//With only two categories, it's easier to just
//do each one separately, and let them inherit
//the data from the parent <g> element.

//For the bottom of the stack:
var bottom = dateGroups.append("rect")
    .attr("class", "data scanned");

bottom.attr("y", function(d){
        return yScale(+d.scanned);
    } )
        //y is the TOP of the rectangle
        //i.e., the position of this data value
        //on the scale
    .attr("height", function(d){
        return Math.abs( yScale(+d.scanned) - yScale(0) );
        //The height of the rectangle is the difference between
        //its data value and the zero line.
        //Note that the yScale value of zero is 
        //bigger than the yScale value of the data
        //because of the inverted scale, so we use
        //absolute value to always get a positive height.
    } );

//For the top of the stack:
var top = dateGroups.append("rect")
    .attr("class", "data unscanned");

top.attr("y", function(d){
        return yScale(+d.unscanned + +d.scanned);
    } )
        //y is the TOP of the rectangle
        //i.e., the position on the scale of 
        //the *total* of the two data categories
    .attr("height", function(d){
        return Math.abs( yScale(+d.unscanned) - yScale(0) );
        //The height of this bar is just based on 
        //its value.  However, this could also be 
        //written as
        //Math.abs(+yScale(+d.scanned + +d.unscanned) 
        //              - yScale(+d.scanned) )
        //i.e., as the difference between the total
        //(top of the bar) and the other category's 
        //value (bottom of the bar)
    } );

//The x value and width are the same for both bars
//so we can re-select all the rectangles and 
//set these attributes at the same time:
dateGroups.selectAll("rect.data")
    .attr("x", function(d){
        return xScale(d.date);
    })
    .attr("width", xScale.rangeBand() );
    //don't need a function for width,
    //since it doesn't depend on the data

一旦您确定了解该程序的每一步发生的情况，您就可以开始添加额外的功能，例如轴或工具提示。您还可以很好地调整代码以处理许多类别，尽管在这种情况下您可能需要创建一个代表每个类别数据的子数组，并使用嵌套选择来创建矩形。这是大多数堆叠条形图示例所使用的方法；在使用这个非常简化的版本后，它们有望更容易理解。

Edit

如果您满足以下条件，则上述解决方案有效know每个堆栈中只有两个值，这两个值的数据来自数据表的同一行。如果你可能有many每个堆栈中的条形，和/或如果它们来自数据表的多行，您将需要使用嵌套选择将数据与各个条形图相匹配。

为了使用嵌套选择方法，您首先必须对数据进行一些操作。您需要将其转换为嵌套数组格式。外部数组必须代表每个stack，并且每个堆栈数据对象必须包含一个代表每个堆栈数据对象的子数组bar.

如何制作嵌套数组取决于您的原始数据格式。当要堆叠的值位于不同行时，d3.nest运算符可以将它们组合成子数组。当堆叠的值与数据表同一行的不同数字时，您必须使用forEach()函数循环遍历数据的所有行并从每行构造一个数组。

在您的示例中，您想要同时执行这两项操作，因此我们将把嵌套操作与 forEach 操作结合起来。同时，我们将计算堆栈的运行总计：为了正确定位每个条形，我们不仅需要知道其自身的计数，还需要知道堆栈中其下方所有值的总计数。

这是一个工作fiddle

数据操作代码是

/*Nest data by date string */
var nestFunction = d3.nest().key( function(d){return d.date;} );
var nestedData = nestFunction.entries(data);

var maxTotal = 0; //maximum count per date, 
                  //for setting the y domain
nestedData.forEach(function(dateGroup) {
   //for each entry in the nested array,
   //each of which contains all the rows for a given date,
   //calculate the total count,
   //and the before-and-after counts for each category.  

    dateGroup.date = dateGroup.key;
    //just using the original strings here, but you could
    //parse the string date value to create a date object

    dateGroup.bars = [];
        //create an array to hold one value for each bar
        //(i.e., two values for each of the original rows)

    var total = 0; //total count per date


    dateGroup.values.forEach(function(row) {
        //the values array created by the nest function
        //contians all the original row data objects
        //that match this date (i.e., the nesting key)

        //create an object representing the bar for
        //the scanned count, and add to the bars array
        dateGroup.bars.push(
            {date:dateGroup.date,
             type: "scanned",
             count: +row.scanned,
             compid: row.compid,
             sbu: row.sbu,
             y0: total, //total value *before* this bar
             y1: (total = total + +row.scanned) //new total
            }
            );

        //create an object representing the bar for
        //the UNscanned count, and add to the bars array
        dateGroup.bars.push(
            {date:dateGroup.date,
             type: "unscanned",
             count: +row.unscanned,
             compid: row.compid,
             sbu: row.sbu,
             y0: total, //total value *before* this bar
             y1: (total = total + +row.unscanned) //new total
            }
            );
    });

    maxTotal = Math.max(maxTotal, total); //update max

});

If you didn't想要将某些类型的条形堆叠在一起 - 例如，如果您想保留不同类型的值compids 位于不同的堆栈中 - 那么您可以将该参数作为嵌套函数的第二个键。仅当值匹配时才嵌套在一起all嵌套键。当然，那么您还必须修改 x 比例以通过两个键分离堆栈。查看分组条形图的示例以了解如何执行此操作。

一旦你有了正确的嵌套数据，你就可以加入外层数组（嵌套对象数组）<g>代表每个堆栈的元素，然后在每个组中创建矩形的嵌套选择并加入内部数组（条形数据）：

var dateGroups = svg.selectAll("g") 
        //create an empty selection of groups
   .data(nestedData); //join to the data, 
    //each nested object (i.e., date) will get a group

dateGroups.enter().append("g")
    //create the actual <g> elements for each row of data
    .attr("class", "dateGroup"); 
    //give them a meaningful class

//Now, within each group create a rectangle 
//for each category from the "bars" array created earlier.
//This uses a nested selection, since we don't know
//how many bars there will be for a given date.


var bars = dateGroups.selectAll("rect")
    .data( function(d) {return d.bars;})
        //the 'd' value passed in is the data for each
        //dateGroup, each of which will now have a 
        //nested selection of bars

bars.enter().append("rect"); //create the rectangles

bars.attr("class", function(d){
        //assign classes for all the categorical values
        //(after stripping out non-word characters)
        //so they can be styled with CSS

        var specialchars = /\W+/g; 
             //regular expression to match all non-letter, non-digit characters

        return ["data",
                "type-" + d.type.replace(specialchars, ""), 
                "compid-" + d.compid.replace(specialchars, ""),
                "sbu-" + d.sbu.replace(specialchars, "")
               ].join(" "); //class list is space-separated

    })
    .attr("y", function(d){
        return yScale(d.y1);
        //y is the TOP of the rectangle
        //i.e., the position of the *total* value
        //for this bar and all others under it in the stack
    } )
    .attr("height", function(d){
        return Math.abs( yScale(d.y1) - yScale(d.y0) );
        //the height of the rectangle is the difference 
        //between the total *after* 
        //this value is added to the stack
        // (top of the bar, y1)
        //and the total *before* it is added 
        // (bottom of the bar, y0)

        //Since this is a linear scale, this could also 
        //be written as
        //Math.abs( yScale(d.count) - yScale(0) )
        //i.e., as the difference between
        //its data value and zero line.

        //Note the use of absolute value to
        //compensate for a possibly inverted scale.
    } )
    .attr("x", function(d){
        return xScale(d.date);
    })
    .attr("width", xScale.rangeBand() )
    //don't need a function for width,
    //since it doesn't depend on the data
    .append("title") //add a tooltip title
        .text(function(d) {
            return d.sbu + ", " +d.type +":" + d.count;
        });