D3直方图，来自时间戳的日期出现次数

Question

Newb here. I have a csv with this data:

date, lat, lon
01/01/2015 09:38:14 AM,37.973424,-87.575423
01/01/2015 09:48:27 PM,37.385218,-122.11413
01/01/2015 10:17:34 AM,39.081712,-76.554603
01/02/2015 01:27:17 PM,40.216204,-74.619533

I want to have a histogram where the x axis is by date and the y axis is by number of occurrences.

So Jan 1 would have a column height of 3 and Jan 2 would have a column height of 1. The time of day is irrelevant.

Do I need to parse the dates, or set a time interval of "day" somehow, or create an array? It seems there are two steps: "filter" the data into chunks, and count the chunks, but I'm not sure how to do it.

I found this example , but the dates are already "rounded" nicely to dates, and the data is in the file, not external.

Thanks for any help!

Answer 1

All you need to do is iterate through your data and keep a tally of the frequencies. I modified this bar chart example to use your data. You need to use the Time Formatting methods D3 provides.

var formatDate = d3.time.format("%m/%d/%Y %I:%M:%S %p");

// line = "01/01/2015 09:38:14 AM,37.973424,-87.575423"

var parts = line.split(',');
var datetime = formatDate.parse(parts[0]);
var date = formatDate(datetime).split(' ')[0]; // "01/01/2015"

Full example:

 var margin = { top: 20, right: 20, bottom: 30, left: 40 }, width = 250 - margin.left - margin.right, height = 200 - margin.top - margin.bottom; var x = d3.scale.ordinal() .rangeRoundBands([0, width], .1); 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") .ticks(10); 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 csv = [ '01/01/2015 09:38:14 AM,37.973424,-87.575423', '01/01/2015 09:48:27 PM,37.385218,-122.11413', '01/01/2015 10:17:34 AM,39.081712,-76.554603', '01/02/2015 01:27:17 PM,40.216204,-74.619533' ]; var formatDate = d3.time.format("%m/%d/%Y %I:%M:%S %p"); var tally = {}; csv.forEach(function(line) { var parts = line.split(','); var datetime = formatDate.parse(parts[0]); var date = formatDate(datetime).split(' ')[0]; tally[date] = (tally[date]||0) + 1; }); var data = []; for (var date in tally) { if (tally.hasOwnProperty(date)) { data.push({ date: date, frequency: tally[date] }); } } x.domain(data.map(function (d) { return d.date; })); y.domain([0, d3.max(data, function (d) { return d.frequency; })]); 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("Frequency"); svg.selectAll(".bar") .data(data) .enter().append("rect") .attr("class", "bar") .attr("x", function (d) { return x(d.date); }) .attr("width", x.rangeBand()) .attr("y", function (d) { return y(d.frequency); }) .attr("height", function (d) { return height - y(d.frequency); }); function type(d) { d.frequency = +d.frequency; return d; } 

 .bar { fill: steelblue; } .bar:hover { fill: brown; } .axis { font: 10px sans-serif; } .axis path, .axis line { fill: none; stroke: #000; shape-rendering: crispEdges; } .x.axis path { display: none; } 

 <script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.4.11/d3.min.js"></script> 

JSFiddle Demo

Loading from CSV file:

var formatDate = d3.time.format("%m/%d/%Y %I:%M:%S %p");

var tally = {};
var data = [];

d3.csv('./data.csv')
.get(function(error, rows) {

  rows.forEach(function(obj, i) {
    var datetime = formatDate.parse(obj.date);
    var date = formatDate(datetime).split(' ')[0];
    tally[date] = (tally[date]||0) + 1;
  });

  for (var date in tally) {
    if (tally.hasOwnProperty(date)) {
        data.push({
            date: date,
            frequency: tally[date]
        });
    }
  }

  console.log(data);
});