Example shows Python Dashed Line Chart where the connecting line between the datapoints are drawn with a dashed line. Library also supports other line types like dotted, solid, long-dash, etc. Below demo also includes Django MVT source code that you can try running locally.
<!-- index.html -->
{% load static %} 
<html>
<head>
<script>
window.onload = function () {
  var chart = new CanvasJS.Chart("chartContainer", {
    exportEnabled: true,
    animationEnabled: true,
    theme: "light1",
    title: {
      text: "Analysis of AdWords Click"
    },
    subtitles: [{
      text: "Click Legend to Hide or Unhide Data Series"
    }],
    axisY: {
      title: "Cost Per Click",
      titleFontColor: "#4F81BC",
      lineColor: "#4F81BC",
      labelFontColor: "#4F81BC",
      tickColor: "#4F81BC",
      includeZero: true,
      prefix: "$"
    },
    axisY2: {
      title: "Clicks",
      titleFontColor: "#C0504E",
      lineColor: "#C0504E",
      labelFontColor: "#C0504E",
      tickColor: "#C0504E"
    },
    toolTip: {
      shared: true
    },
    legend: {
      cursor: "pointer",
      itemclick: toggleDataSeries
    },
    data: [{
      type: "spline",
      name: "Cost Per Click",
      lineDashType: "dot",
      showInLegend: true,
      yValueFormatString: "$#,##0.00",
      dataPoints: {{ cost_per_click_data|safe }}
    },{
      type: "spline",
      lineDashType: "dashDot",
      name: "Click",
      axisYType: "secondary",
      showInLegend: true,
      dataPoints: {{ click_data|safe }}
    }]
  });
  chart.render();
  function toggleDataSeries(e) {
    if (typeof (e.dataSeries.visible) === "undefined" || e.dataSeries.visible) {
      e.dataSeries.visible = false;
    } else {
      e.dataSeries.visible = true;
    }
    e.chart.render();
  }
}
</script>    
</head>
<body>
    <div id="chartContainer" style="width: 100%; height: 360px;"></div>
    <script src="{% static 'canvasjs.min.js' %}"></script>
</body>
</html>                              
                                
from django.shortcuts import render
def index(request):
  cost_per_click_data = [
    { "label": "Oct 1", "y": 2.2984482 },
    { "label": "Oct 2", "y": 1.6430263 },
    { "label": "Oct 3", "y": 1.7507812 },
    { "label": "Oct 4", "y": 1.5731722 },
    { "label": "Oct 5", "y": 1.1773170 },
    { "label": "Oct 6", "y": 1.2797851 },
    { "label": "Oct 7", "y": 1.4864893 },
    { "label": "Oct 8", "y": 1.7770796 },
    { "label": "Oct 9", "y": 1.4806903 },
    { "label": "Oct 10", "y": 1.5376530 }
  ]
  click_data = [
    { "label": "Oct 1", "y": 15 },
    { "label": "Oct 2", "y": 57 },
    { "label": "Oct 3", "y": 96 },
    { "label": "Oct 4", "y": 119 },
    { "label": "Oct 5", "y": 144 },
    { "label": "Oct 6", "y": 128 },
    { "label": "Oct 7", "y": 47 },
    { "label": "Oct 8", "y": 57 },
    { "label": "Oct 9", "y": 120 },
    { "label": "Oct 10", "y": 123 }
  ]
  
  return render(request, 'index.html', { "cost_per_click_data": cost_per_click_data, "click_data": click_data })                        
                            You can choose between different types of line using lineDashType property. You can also customize the color & thickness of the line by setting lineColor & lineThickness properties.