我有一个简单的数据集，其中包含时间序列数据点，我希望以每秒精度绘制。但数据是股票数据，因此不是每个点都代表价格变化。
这是一个价格为14:08, 14:09, 14:10 ... 14:15
https://playground.anychart.com/ZIT0QuAF/1
是否可以显示数据点之间传递的间隙/时间，可以是空格，也可能是每秒的x轴更好，只是连接点的延长线（可能是点线或不同的颜色）。
谢谢。
答案 0 :(得分：1)
现在我看到了你的要求。你可以轻松实现这一目标。默认情况下，如您提供的示例中所示，您使用基于序数的比例。为了更好地说明在股票代码点之间传递了一些时间，您应该使用基于分散的比例。只需在代码中使用以下行：
chart.xScale('scatter');
现在所有点都严格遵循时间坐标，并显示所有间隙。此外，所有点都用虚线连接。请检查下面的示例
anychart.onDocumentReady(function() {
// create data table on loaded data
var table = anychart.data.table("epoch");
table.addData([
{
last: 0.00000462,
epoch: 1520260206263,
vol: 0,
volBase: 0,
prcnt: 0,
volDiff: 0,
percentFromStart: 0.00000000
},
{
last: 0.00000558,
epoch: 1520260207391,
vol: 0,
volBase: 0,
prcnt: -17.20430108,
volDiff: NaN,
percentFromStart: 20.77922078
},
{
last: 0.00000585,
epoch: 1520260208131,
vol: 0,
volBase: 0,
prcnt: -4.61538462,
volDiff: NaN,
percentFromStart: 26.62337662
},
{
last: 0.00000680,
epoch: 1520260209293,
vol: 0,
volBase: 0,
prcnt: -13.97058824,
volDiff: NaN,
percentFromStart: 47.18614719
},
{
last: 0.00000693,
epoch: 1520260210752,
vol: 0,
volBase: 0,
prcnt: -1.87590188,
volDiff: NaN,
percentFromStart: 50.00000000
},
{
last: 0.00000657,
epoch: 1520260215326,
vol: 0,
volBase: 0,
prcnt: 5.47945205,
volDiff: NaN,
percentFromStart: 42.20779221
},
{
last: 0.00000700,
epoch: 1520260225028,
vol: 0,
volBase: 0,
prcnt: -6.14285714,
volDiff: NaN,
percentFromStart: 51.51515152
},
{
last: 0.00000657,
epoch: 1520260239317,
vol: 0,
volBase: 0,
prcnt: 6.54490107,
volDiff: NaN,
percentFromStart: 42.20779221
},
{
last: 0.00000624,
epoch: 1520260240762,
vol: 0,
volBase: 0,
prcnt: 5.28846154,
volDiff: NaN,
percentFromStart: 35.06493506
},
{
last: 0.00000723,
epoch: 1520260244015,
vol: 0,
volBase: 0,
prcnt: -13.69294606,
volDiff: NaN,
percentFromStart: 56.49350649
},
{
last: 0.00000740,
epoch: 1520260245557,
vol: 0,
volBase: 0,
prcnt: -2.29729730,
volDiff: NaN,
percentFromStart: 60.17316017
},
{
last: 0.00000740,
epoch: 1520260247146,
vol: 0,
volBase: 0,
prcnt: 0.00000000,
volDiff: NaN,
percentFromStart: 60.17316017
},
{
last: 0.00000740,
epoch: 1520260258519,
vol: 0,
volBase: 0,
prcnt: 0.00000000,
volDiff: NaN,
percentFromStart: 60.17316017
},
{
last: 0.00000740,
epoch: 1520260261733,
vol: 0,
volBase: 0,
prcnt: 0.00000000,
volDiff: NaN,
percentFromStart: 60.17316017
},
{
last: 0.00000713,
epoch: 1520260262192,
vol: 0,
volBase: 0,
prcnt: 3.78681627,
volDiff: NaN,
percentFromStart: 54.32900433
},
{
last: 0.00000700,
epoch: 1520260263087,
vol: 0,
volBase: 0,
prcnt: 1.85714286,
volDiff: NaN,
percentFromStart: 51.51515152
},
{
last: 0.00000657,
epoch: 1520260264653,
vol: 0,
volBase: 0,
prcnt: 6.54490107,
volDiff: NaN,
percentFromStart: 42.20779221
},
{
last: 0.00000614,
epoch: 1520260288009,
vol: 0,
volBase: 0,
prcnt: 7.00325733,
volDiff: NaN,
percentFromStart: 32.90043290
},
{
last: 0.00000614,
epoch: 1520260295191,
vol: 0,
volBase: 0,
prcnt: 0.00000000,
volDiff: NaN,
percentFromStart: 32.90043290
},
{
last: 0.00000740,
epoch: 1520260296127,
vol: 0,
volBase: 0,
prcnt: -17.02702703,
volDiff: NaN,
percentFromStart: 60.17316017
},
{
last: 0.00000749,
epoch: 1520260299736,
vol: 0,
volBase: 0,
prcnt: -1.20160214,
volDiff: NaN,
percentFromStart: 62.12121212
},
{
last: 0.00000749,
epoch: 1520260302084,
vol: 0,
volBase: 0,
prcnt: 0.00000000,
volDiff: NaN,
percentFromStart: 62.12121212
},
{
last: 0.00000562,
epoch: 1520260304974,
vol: 0,
volBase: 0,
prcnt: 33.27402135,
volDiff: NaN,
percentFromStart: 21.64502165
},
{
last: 0.00000375,
epoch: 1520260323816,
vol: 0,
volBase: 0,
prcnt: 49.86666667,
volDiff: NaN,
percentFromStart: -18.83116883
},
{
last: 0.00000749,
epoch: 1520260327149,
vol: 0,
volBase: 0,
prcnt: -49.93324433,
volDiff: NaN,
percentFromStart: 62.12121212
},
{
last: 0.00000749,
epoch: 1520260328543,
vol: 0,
volBase: 0,
prcnt: 0.00000000,
volDiff: NaN,
percentFromStart: 62.12121212
},
{
last: 0.00000749,
epoch: 1520260335547,
vol: 0,
volBase: 0,
prcnt: 0.00000000,
volDiff: NaN,
percentFromStart: 62.12121212
},
{
last: 0.00000749,
epoch: 1520260338101,
vol: 0,
volBase: 0,
prcnt: 0.00000000,
volDiff: NaN,
percentFromStart: 62.12121212
}
]);
chart = anychart.stock();
chart.xScale('scatter');
var mappingLastPrice = table.mapAs({
'value': "last"
});
var series1 = chart.plot(0).line(mappingLastPrice);
series1.stroke('red','1', '2 10');
series1.markers(true);
series1.markers().fill('blue');
series1.name("Last Price");
chart.container('container').draw();
});html, body, #container {
width: 100%;
height: 100%;
margin: 0;
padding: 0;
}<script src="https://cdn.anychart.com/releases/8.1.0/js/anychart-base.min.js"></script>
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<link href="https://cdn.anychart.com/releases/8.1.0/css/anychart-ui.min.css" rel="stylesheet"/>
<div id="container"></div>