Home Java javaTutorial Implement adaptive responsive statistical chart design using ECharts and Java interfaces

Implement adaptive responsive statistical chart design using ECharts and Java interfaces

Dec 18, 2023 am 11:18 AM
echarts Responsive statistical charts java interface

Implement adaptive responsive statistical chart design using ECharts and Java interfaces

Use ECharts and Java interface to implement adaptive responsive statistical chart design

In the field of modern data visualization, the design and display of statistical charts is very important. ring. In web applications, we often need to use some open source tools to help us implement such functions. ECharts is a very popular open source charting library that provides a wealth of chart types and various custom configuration options. This article will introduce how to use ECharts and Java interfaces to implement adaptive responsive statistical chart design, and give specific code examples.

First, we need to build a basic web application. Here we choose to use Java to build the back-end interface and HTML, CSS and JavaScript to build the front-end page. We can use Spring Boot to create a simple Java interface to provide data to the front-end page.

The following is a simple Java interface example:

@RestController
public class ChartController {

    @GetMapping("/data")
    public List<DataPoint> getData() {
        // 数据获取逻辑
        // 返回一个包含数据点的List
    }
}
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In the above code, we create a ChartController class and mark it as a controller using the @RestController annotation. Then we use the @GetMapping annotation to specify the URL path of the interface as "/data", and write the data acquisition logic in the getData() method.

Next, we need to introduce the ECharts JavaScript library into the front-end page, and write code to obtain the data from the back-end interface and render it into a statistical chart.

The following is a simple HTML page example:

<!DOCTYPE html>
<html>
<head>
    <meta charset="UTF-8">
    <title>统计图表</title>
    <script src="https://cdn.jsdelivr.net/npm/echarts@5.0.2/dist/echarts.min.js"></script>
</head>
<body>
    <div id="chart" style="height: 400px"></div>

    <script>
        var chart = echarts.init(document.getElementById('chart'));

        // 使用Ajax来获取后端接口的数据
        $.ajax({
            url: '/data',
            type: 'GET',
            dataType: 'json',
            success: function (data) {
                // 将数据渲染成统计图表
                var option = {
                    // 根据数据构造图表的配置
                };
                chart.setOption(option);
            }
        });
    </script>
</body>
</html>
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In the above code, we first introduced ECharts' JavaScript library through the <script> tag. Then a div element is created in the page with the id "chart" to accommodate the statistical chart. Next, we use Ajax to obtain data from the backend interface, and after successfully obtaining the data, use the chart.setOption() method to render the data into a statistical chart.

Finally, we need to write the actual data acquisition logic in the backend interface and return a List containing the data points. Here we can use Java collections to store information about data points. The following is a simple example:

public class DataPoint {
    private String name;
    private int value;

    // getter和setter方法
}
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In the above code, we created a DataPoint class to represent the information of a data point, including name and value.

Then we can write the actual data acquisition logic in the getData() method in the ChartController class. The following is a simple example:

@GetMapping("/data")
public List<DataPoint> getData() {
    List<DataPoint> data = new ArrayList<>();

    // 模拟生成一些数据点
    for (int i = 1; i <= 10; i++) {
        data.add(new DataPoint("数据点" + i, i));
    }

    return data;
}
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In the above code, we simulate generating some data points, adding them to a List, and then returning the List as response data.

Through the above steps, we have realized the use of ECharts and Java interfaces to implement adaptive responsive statistical chart design. By modifying the data acquisition logic and the configuration of statistical charts, we can flexibly achieve various types of chart display effects.

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