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Home  >  Article  >  Web Front-end  >  Clustered Scatter Chart

Clustered Scatter Chart

Linda Hamilton
Linda HamiltonOriginal
2024-10-31 20:37:02886browse

Clustered Scatter Chart

Visualizing Distance Traveled by Football Players with ZingChart

In this tutorial, we’ll create a scatter plot using ZingChart to visualize the distance traveled by players in different football games. The chart shows simulated data across multiple games, giving insight into the distances covered minute by minute.

Code Explanation

This code snippet uses JavaScript to generate fake data for eight games, then configures and renders a scatter plot using ZingChart.

  • Games Data: Each game is represented as a unique data series.
  • Randomized Distances: Distances for each minute in the game are randomized to mimic real-world distribution.
  • Chart Configuration: The chart is set up with ZingChart’s scatter plot type, customizable markers, and axes.

Below is the full HTML and JavaScript code for creating this chart.

Code Snippet 

<!DOCTYPE html>
<html>
  <head>
    <meta charset="utf-8">
    <title>ZingSoft Demo</title>
    <script src="https://cdn.zingchart.com/zingchart.min.js"></script>
    <script>
// CHART CONFIG
// -----------------------------
let chartConfig = {
    type: 'hbar',
    theme: 'dark',
    title: {
        text: 'Average Temperatures',
        marginLeft: '20px',
    },
    legend: {
        align: 'left',
        backgroundColor: 'none',
        borderWidth: '0px',
        item: {
            cursor: 'hand',
            fontColor: '#E3E3E5',
        },
        marker: {
            type: 'circle',
            borderWidth: '0px',
            cursor: 'hand',
        },
        offsetY: '25px',
        verticalAlign: 'top',
    },
    plot: {
        tooltip: {
            text: '%data-city<br>High: %data-highs<br>Low: %data-lows',
        },
    },
    plotarea: {
        margin: '120px 50px 60px 85px',
    },
    scaleX: {
        label: {
            text: '2020',
            fontSize: '14px',
        },
        labels: [
            'Jan',
            'Feb',
            'Mar',
            'Apr',
            'May',
            'Jun',
            'Jul',
            'Aug',
            'Sep',
            'Oct',
            'Nov',
            'Dec',
        ],
        zooming: true,
        zoomTo: [0, 5],
    },
    scaleY: {
        format: '%v°F',
        guide: {
            lineStyle: 'solid',
        },
        label: {
            text: 'Temperature',
            fontSize: '14px',
        },
    },
    shapes: [
        {
            type: 'rectangle',
            id: 'view_all',
            backgroundColor: '#5e5e5e',
            borderColor: '#E3E3E5',
            borderRadius: '3px',
            borderWidth: '1px',
            cursor: 'hand',
            height: '20px',
            label: {
                text: 'View All',
                bold: true,
                fontColor: '#E3E3E5',
                fontSize: '12px',
            },
            width: '75px',
            x: '89%',
            y: '7%',
        },
    ],
    series: [
        {
            text: 'New Orleans Average Temps 2020',
            values: [17, 17, 19, 18, 17, 15, 16, 16, 15, 17, 19, 17],
            dataCity: 'New Orleans',
            dataHighs: [62, 65, 72, 78, 85, 89, 91, 91, 87, 80, 72, 64],
            dataLows: [45, 48, 53, 60, 68, 74, 75, 75, 72, 63, 53, 47],
            offsetValues: [45, 48, 53, 60, 68, 74, 75, 75, 72, 63, 53, 47],
        },
        {
            text: 'San Diego Average Temps 2020',
            values: [16, 14, 13, 11, 10, 9, 10, 9, 9, 12, 15, 17],
            dataCity: 'San Diego',
            dataHighs: [65, 65, 66, 67, 69, 71, 75, 76, 76, 73, 69, 65],
            dataLows: [49, 51, 53, 56, 59, 62, 65, 67, 65, 61, 54, 48],
            offsetValues: [49, 51, 53, 56, 59, 62, 65, 67, 65, 61, 54, 48],
        },
        {
            text: 'Denver Average Temps 2020',
            values: [27, 27, 27, 27, 29, 30, 31, 31, 31, 29, 27, 27],
            dataCity: 'Denver',
            dataHighs: [45, 46, 54, 61, 72, 82, 90, 88, 79, 66, 52, 45],
            dataLows: [18, 19, 27, 34, 43, 52, 59, 57, 48, 37, 25, 18],
            offsetValues: [18, 19, 27, 34, 43, 52, 59, 57, 48, 37, 25, 18],
        },
    ],
    scrollX: {},
};
// RENDER CHARTS
// -----------------------------
zingchart.render({
    id: 'myChart',
    data: chartConfig,
    height: '100%',
    width: '100%',
});
// EVENTS
// -----------------------------
// store the original zoom level info
const origin_zoomin_level = zingchart.exec('myChart', 'getzoom');
// a flag to control the view
let switch_view = 'viewall';
zingchart.shape_click = (p) => {
    if (p.shapeid == 'view_all') {
        switch (switch_view) {
            case 'viewall':
                // change zoom level to viewall
                zingchart.exec(p.id, 'viewall');
                // update the switch button text label
                // to Previous View
                zingchart.exec(p.id, 'updateobject', {
                    type: 'shape',
                    data: {
                        id: 'view_all',
                        label: {
                            text: 'Original View',
                        },
                        width: '110px',
                    }
                });
                // set the flag to previous_view 
                switch_view = 'original_view';
                break;
            case 'original_view':
                // scale-x and scale-y are array from 
                // origina_zoomin_level object
                let scale_x = origin_zoomin_level['scale-x'];
                let scale_y = origin_zoomin_level['scale-y'];
                // use zoomtovalues to get back to original zoom
                // level, pass attributes from origin_zoomin_level 
                // object xmin, xmax, ymin, ymax as parameter
                zingchart.exec(p.id, 'zoomtovalues', {
                    graphid: 0,
                    xmin: scale_x.xmin,
                    xmax: scale_x.xmax,
                    ymin: scale_y.ymin,
                    ymax: scale_y.ymax
                });
                // update the switch button text label
                // to View All
                zingchart.exec(p.id, 'updateobject', {
                    type: 'shape',
                    data: {
                        id: 'view_all',
                        label: {
                            text: 'View All',
                        },
                        width: '75px',
                    }
                });
                // change the flag back to viewall
                switch_view = 'viewall';
                break;
        }
    }
};

    </script>
    <style>
      .zc-body { background:#000; }

.chart--container {
  height: 100%;
  width: 100%;
  min-height: 530px;
}

.zc-ref {
  display: none;
}
    </style>
  </head>
  <body class="zc-body">
  ​
    <div id="myChart" class="chart--container">
      <a href="https://www.zingchart.com/" rel="noopener" class="zc-ref">Powered by ZingChart</a>
    </div>

  </body>
</html>

Running the Code

  1. Copy the code into an HTML file and open it in your browser.
  2. You should see a scatter plot with each game represented, showing random distances traveled by players across 90 minutes.

Conclusion

This chart provides a clear and customizable way to represent time-based data, such as player movements, with ZingChart. Happy coding!

NEvolution #nabegh_anane

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