数据来自beck end,但有时候图表显示不正确。有时为什么会这样?我提到this code.
这是我的代码:
{
"results": [
{
"date": "2017-04-06 11:57:48",
"value": 302
},
{
"date": "2017-04-06 11:58:18",
"value": 329
},
{
"date": "2017-04-06 11:58:48",
"value": 344
},
{
"date": "2017-04-06 11:59:18",
"value": 372
},
{
"date": "2017-04-06 11:59:48",
"value": 391
},
{
"date": "2017-04-06 00:00:18",
"value": 428
},
{
"date": "2017-04-06 00:00:48",
"value": 445
},
{
"date": "2017-04-06 00:01:18",
"value": 287
},
{
"date": "2017-04-06 00:01:48",
"value": 302
},
{
"date": "2017-04-06 00:02:18",
"value": 331
},
{
"date": "2017-04-06 00:02:48",
"value": 346
},
{
"date": "2017-04-06 00:03:18",
"value": 374
},
{
"date": "2017-04-06 00:03:48",
"value": 388
},
{
"date": "2017-04-06 00:04:18",
"value": 417
},
{
"date": "2017-04-06 00:04:48",
"value": 433
},
{
"date": "2017-04-06 00:05:18",
"value": 461
},
{
"date": "2017-04-06 00:05:48",
"value": 474
},
{
"date": "2017-04-06 00:06:18",
"value": 316
},
{
"date": "2017-04-06 00:06:48",
"value": 330
},
{
"date": "2017-04-06 00:07:18",
"value": 357
},
{
"date": "2017-04-06 00:07:48",
"value": 374
},
{
"date": "2017-04-06 00:08:18",
"value": 402
},
{
"date": "2017-04-06 00:08:48",
"value": 415
},
{
"date": "2017-04-06 00:09:18",
"value": 443
},
{
"date": "2017-04-06 00:09:48",
"value": 460
},
{
"date": "2017-04-06 00:10:18",
"value": 301
},
{
"date": "2017-04-06 00:10:48",
"value": 314
},
{
"date": "2017-04-06 00:11:18",
"value": 344
},
{
"date": "2017-04-06 00:11:48",
"value": 359
},
{
"date": "2017-04-06 00:12:18",
"value": 385
},
{
"date": "2017-04-06 00:12:48",
"value": 400
},
{
"date": "2017-04-06 00:13:18",
"value": 429
},
{
"date": "2017-04-06 00:13:48",
"value": 444
},
{
"date": "2017-04-06 00:14:18",
"value": 470
},
{
"date": "2017-04-06 00:14:48",
"value": 301
},
{
"date": "2017-04-06 00:15:18",
"value": 331
},
{
"date": "2017-04-06 00:15:48",
"value": 346
},
{
"date": "2017-04-06 00:16:18",
"value": 373
},
{
"date": "2017-04-06 00:16:48",
"value": 425
},
{
"date": "2017-04-06 00:17:18",
"value": 453
},
{
"date": "2017-04-06 00:17:48",
"value": 468
},
{
"date": "2017-04-06 00:18:18",
"value": 307
},
{
"date": "2017-04-06 00:18:48",
"value": 322
},
{
"date": "2017-04-06 00:19:18",
"value": 350
},
{
"date": "2017-04-06 00:19:48",
"value": 365
},
{
"date": "2017-04-06 00:20:18",
"value": 393
},
{
"date": "2017-04-06 00:20:48",
"value": 408
},
{
"date": "2017-04-06 00:21:18",
"value": 436
},
{
"date": "2017-04-06 00:21:48",
"value": 449
},
{
"date": "2017-04-06 00:22:18",
"value": 291
},
{
"date": "2017-04-06 00:22:48",
"value": 306
},
{
"date": "2017-04-06 00:23:18",
"value": 333
},
{
"date": "2017-04-06 00:23:48",
"value": 346
},
{
"date": "2017-04-06 00:24:18",
"value": 375
},
{
"date": "2017-04-06 00:24:48",
"value": 392
},
{
"date": "2017-04-06 00:25:18",
"value": 419
},
{
"date": "2017-04-06 00:25:48",
"value": 434
},
{
"date": "2017-04-06 00:26:18",
"value": 462
},
{
"date": "2017-04-06 00:26:48",
"value": 476
},
{
"date": "2017-04-06 00:27:18",
"value": 317
},
{
"date": "2017-04-06 00:27:48",
"value": 332
},
{
"date": "2017-04-06 00:28:18",
"value": 359
},
{
"date": "2017-04-06 00:28:48",
"value": 374
},
{
"date": "2017-04-06 00:29:18",
"value": 406
},
{
"date": "2017-04-06 00:29:48",
"value": 421
},
{
"date": "2017-04-06 00:30:18",
"value": 449
},
{
"date": "2017-04-06 00:30:48",
"value": 463
},
{
"date": "2017-04-06 00:31:18",
"value": 305
},
{
"date": "2017-04-06 00:31:48",
"value": 319
},
{
"date": "2017-04-06 00:32:18",
"value": 346
},
{
"date": "2017-04-06 00:32:48",
"value": 361
},
{
"date": "2017-04-06 00:33:18",
"value": 389
},
{
"date": "2017-04-06 00:33:48",
"value": 404
},
{
"date": "2017-04-06 00:34:18",
"value": 433
},
{
"date": "2017-04-06 00:34:48",
"value": 447
},
{
"date": "2017-04-06 00:35:18",
"value": 476
},
{
"date": "2017-04-06 00:35:48",
"value": 303
},
{
"date": "2017-04-06 00:36:18",
"value": 331
},
{
"date": "2017-04-06 00:36:48",
"value": 347
},
{
"date": "2017-04-06 00:37:18",
"value": 374
},
{
"date": "2017-04-06 00:37:48",
"value": 389
},
{
"date": "2017-04-06 00:38:18",
"value": 416
},
{
"date": "2017-04-06 00:38:48",
"value": 432
},
{
"date": "2017-04-06 00:39:18",
"value": 461
},
{
"date": "2017-04-06 00:39:48",
"value": 475
},
{
"date": "2017-04-06 00:40:18",
"value": 318
},
{
"date": "2017-04-06 00:40:48",
"value": 332
},
{
"date": "2017-04-06 00:41:18",
"value": 360
},
{
"date": "2017-04-06 00:41:48",
"value": 373
},
{
"date": "2017-04-06 00:42:18",
"value": 403
},
{
"date": "2017-04-06 00:42:48",
"value": 418
},
{
"date": "2017-04-06 00:43:18",
"value": 446
},
{
"date": "2017-04-06 00:43:48",
"value": 459
},
{
"date": "2017-04-06 00:44:18",
"value": 305
},
{
"date": "2017-04-06 00:44:48",
"value": 320
},
{
"date": "2017-04-06 00:45:18",
"value": 347
},
{
"date": "2017-04-06 00:45:48",
"value": 364
},
{
"date": "2017-04-06 00:46:18",
"value": 391
},
{
"date": "2017-04-06 00:46:48",
"value": 444
},
{
"date": "2017-04-06 00:47:18",
"value": 475
}
]
}
我从后端动态获取x和y的数据。不要考虑上面的x和y数据。
我从后端获取x和y的数据: x的日期 和Y的值
{{1}}
答案 0 :(得分:1)
在此代码中似乎工作正常。我收到一个错误,没有定义server1,但是否则它似乎按预期工作。我最初的想法是你的x轴出现了问题,但是这里的一切看起来都很好。您使用的是哪个版本的d3?还有什么浏览器?我在Ubuntu上使用Chrome。
<强>更新强>
我添加了更新的数据。日期附近有一个丢失的逗号&#34; 2017-04-06 00:44:18&#34;这导致解析它的一些问题。我修复了这个问题,但是能够使用与以前相同的代码渲染它。新图表如下所示:
我仍然无法重现您的渲染错误,但我会看看是否可以通过玩边距来实现。
<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.4.11/d3.min.js"></script>
<script type="text/javascript" src="https://cdn.plot.ly/plotly-latest.min.js"></script>
<body>
<div id="myDiv" style="width: 480px; height: 400px;"><!-- Plotly chart will be drawn inside this DIV --></div>
<script>
var realData = {
"results": [
{
"date": "2017-04-06 11:57:48",
"value": 302
},
{
"date": "2017-04-06 11:58:18",
"value": 329
},
{
"date": "2017-04-06 11:58:48",
"value": 344
},
{
"date": "2017-04-06 11:59:18",
"value": 372
},
{
"date": "2017-04-06 11:59:48",
"value": 391
},
{
"date": "2017-04-06 00:00:18",
"value": 428
},
{
"date": "2017-04-06 00:00:48",
"value": 445
},
{
"date": "2017-04-06 00:01:18",
"value": 287
},
{
"date": "2017-04-06 00:01:48",
"value": 302
},
{
"date": "2017-04-06 00:02:18",
"value": 331
},
{
"date": "2017-04-06 00:02:48",
"value": 346
},
{
"date": "2017-04-06 00:03:18",
"value": 374
},
{
"date": "2017-04-06 00:03:48",
"value": 388
},
{
"date": "2017-04-06 00:04:18",
"value": 417
},
{
"date": "2017-04-06 00:04:48",
"value": 433
},
{
"date": "2017-04-06 00:05:18",
"value": 461
},
{
"date": "2017-04-06 00:05:48",
"value": 474
},
{
"date": "2017-04-06 00:06:18",
"value": 316
},
{
"date": "2017-04-06 00:06:48",
"value": 330
},
{
"date": "2017-04-06 00:07:18",
"value": 357
},
{
"date": "2017-04-06 00:07:48",
"value": 374
},
{
"date": "2017-04-06 00:08:18",
"value": 402
},
{
"date": "2017-04-06 00:08:48",
"value": 415
},
{
"date": "2017-04-06 00:09:18",
"value": 443
},
{
"date": "2017-04-06 00:09:48",
"value": 460
},
{
"date": "2017-04-06 00:10:18",
"value": 301
},
{
"date": "2017-04-06 00:10:48",
"value": 314
},
{
"date": "2017-04-06 00:11:18",
"value": 344
},
{
"date": "2017-04-06 00:11:48",
"value": 359
},
{
"date": "2017-04-06 00:12:18",
"value": 385
},
{
"date": "2017-04-06 00:12:48",
"value": 400
},
{
"date": "2017-04-06 00:13:18",
"value": 429
},
{
"date": "2017-04-06 00:13:48",
"value": 444
},
{
"date": "2017-04-06 00:14:18",
"value": 470
},
{
"date": "2017-04-06 00:14:48",
"value": 301
},
{
"date": "2017-04-06 00:15:18",
"value": 331
},
{
"date": "2017-04-06 00:15:48",
"value": 346
},
{
"date": "2017-04-06 00:16:18",
"value": 373
},
{
"date": "2017-04-06 00:16:48",
"value": 425
},
{
"date": "2017-04-06 00:17:18",
"value": 453
},
{
"date": "2017-04-06 00:17:48",
"value": 468
},
{
"date": "2017-04-06 00:18:18",
"value": 307
},
{
"date": "2017-04-06 00:18:48",
"value": 322
},
{
"date": "2017-04-06 00:19:18",
"value": 350
},
{
"date": "2017-04-06 00:19:48",
"value": 365
},
{
"date": "2017-04-06 00:20:18",
"value": 393
},
{
"date": "2017-04-06 00:20:48",
"value": 408
},
{
"date": "2017-04-06 00:21:18",
"value": 436
},
{
"date": "2017-04-06 00:21:48",
"value": 449
},
{
"date": "2017-04-06 00:22:18",
"value": 291
},
{
"date": "2017-04-06 00:22:48",
"value": 306
},
{
"date": "2017-04-06 00:23:18",
"value": 333
},
{
"date": "2017-04-06 00:23:48",
"value": 346
},
{
"date": "2017-04-06 00:24:18",
"value": 375
},
{
"date": "2017-04-06 00:24:48",
"value": 392
},
{
"date": "2017-04-06 00:25:18",
"value": 419
},
{
"date": "2017-04-06 00:25:48",
"value": 434
},
{
"date": "2017-04-06 00:26:18",
"value": 462
},
{
"date": "2017-04-06 00:26:48",
"value": 476
},
{
"date": "2017-04-06 00:27:18",
"value": 317
},
{
"date": "2017-04-06 00:27:48",
"value": 332
},
{
"date": "2017-04-06 00:28:18",
"value": 359
},
{
"date": "2017-04-06 00:28:48",
"value": 374
},
{
"date": "2017-04-06 00:29:18",
"value": 406
},
{
"date": "2017-04-06 00:29:48",
"value": 421
},
{
"date": "2017-04-06 00:30:18",
"value": 449
},
{
"date": "2017-04-06 00:30:48",
"value": 463
},
{
"date": "2017-04-06 00:31:18",
"value": 305
},
{
"date": "2017-04-06 00:31:48",
"value": 319
},
{
"date": "2017-04-06 00:32:18",
"value": 346
},
{
"date": "2017-04-06 00:32:48",
"value": 361
},
{
"date": "2017-04-06 00:33:18",
"value": 389
},
{
"date": "2017-04-06 00:33:48",
"value": 404
},
{
"date": "2017-04-06 00:34:18",
"value": 433
},
{
"date": "2017-04-06 00:34:48",
"value": 447
},
{
"date": "2017-04-06 00:35:18",
"value": 476
},
{
"date": "2017-04-06 00:35:48",
"value": 303
},
{
"date": "2017-04-06 00:36:18",
"value": 331
},
{
"date": "2017-04-06 00:36:48",
"value": 347
},
{
"date": "2017-04-06 00:37:18",
"value": 374
},
{
"date": "2017-04-06 00:37:48",
"value": 389
},
{
"date": "2017-04-06 00:38:18",
"value": 416
},
{
"date": "2017-04-06 00:38:48",
"value": 432
},
{
"date": "2017-04-06 00:39:18",
"value": 461
},
{
"date": "2017-04-06 00:39:48",
"value": 475
},
{
"date": "2017-04-06 00:40:18",
"value": 318
},
{
"date": "2017-04-06 00:40:48",
"value": 332
},
{
"date": "2017-04-06 00:41:18",
"value": 360
},
{
"date": "2017-04-06 00:41:48",
"value": 373
},
{
"date": "2017-04-06 00:42:18",
"value": 403
},
{
"date": "2017-04-06 00:42:48",
"value": 418
},
{
"date": "2017-04-06 00:43:18",
"value": 446
},
{
"date": "2017-04-06 00:43:48",
"value": 459
},
{
"date": "2017-04-06 00:44:18",
"value": 305
},
{
"date": "2017-04-06 00:44:48",
"value": 320
},
{
"date": "2017-04-06 00:45:18",
"value": 347
},
{
"date": "2017-04-06 00:45:48",
"value": 364
},
{
"date": "2017-04-06 00:46:18",
"value": 391
},
{
"date": "2017-04-06 00:46:48",
"value": 444
},
{
"date": "2017-04-06 00:47:18",
"value": 475
}
]
}
var abc = ['2013-10-04 02:23:00', '2013-10-22 12:23:00', '2013-11-04 20:23:00', '2013-11-020 10:23:00','2013-12-04 15:10:45', '2013-12-26 06:03:00'];
abc[6]='2014-05-02 20:23:00';
var dates = [];
var vals = [];
realData.results.forEach( function(m) { dates.push(m.date); vals.push(m.value);});
var trace1 = {
x: dates,
y: vals,
fill: 'tozeroy',
fillcolor: 'red',
text: "server1",
hoverinfo: "x+y+text",
name:"Server 1",
type: 'scatter',
mode:"markers",
marker:
{
size:4,
color:"gray"
},
uid:"c2e171",
dragmode:"turntable"
};
var layout = {
margin: {
l: 35,
r: 40,
b: 50,
t: 10
},
legend: {
"orientation": "h"
},
xaxis: {
showgrid: false,
showline: true,
ticks: "outside"
},
yaxis : {
fixedrange: true,
showgrid: false,
showline: true,
ticks: "outside"
},
dragmode:false,
};
var data = [trace1];
Plotly.newPlot('myDiv', data,layout, {modeBarButtonsToRemove: ['sendDataToCloud','hoverCompareCartesian','zoom2d','pan2d','select2d','lasso2d','autoScale2d','hoverClosestCartesian','toggleSpikelines']});
var plotDiv = document.getElementById('myDiv');
plotDiv.on('plotly_relayout',
function(eventdata){
alert( 'ZOOM!' + '\n\n' +
'Event data:' + '\n' +
JSON.stringify(eventdata) + '\n\n' +
'x-axis start:' + new Date(eventdata['xaxis.range[0]'])+ '\n' +
'x-axis end:' + new Date(eventdata['xaxis.range[1]']));
var xVal = new Date(eventdata['xaxis.range[0]']);
var yVal = new Date(eventdata['xaxis.range[1]']);
});
</script>
</body>
&#13;