ECharts 및 Java 인터페이스: 지능형 제조 분야에서 통계 분석을 적용하는 방법

import java.sql.*;

public class DataAnalysis {
    public static void main(String[] args) {
        try {
            // 连接数据库
            Connection conn = DriverManager.getConnection("jdbc:mysql://localhost:3306/production", "username", "password");
            
            // 执行SQL语句获取温度数据
            Statement stmt = conn.createStatement();
            String sql = "SELECT temperature FROM production_data WHERE production_line = 'A'";
            ResultSet rs = stmt.executeQuery(sql);
            
            // 处理数据
            while (rs.next()) {
                double temperature = rs.getDouble("temperature");
                // 对数据进行统计分析或其他处理
            }
            
            // 关闭数据库连接
            rs.close();
            stmt.close();
            conn.close();
        } catch (SQLException e) {
            e.printStackTrace();
        }
    }
}

import com.github.abel533.echarts.Option;
import com.github.abel533.echarts.axis.CategoryAxis;
import com.github.abel533.echarts.code.Magic;

public class DataVisualization {
    public static void main(String[] args) {
        // 创建Option对象
        Option option = new Option();
        
        // 创建X轴和Y轴
        CategoryAxis xAxis = new CategoryAxis();
        xAxis.setName("时间");
        xAxis.setData(new String[]{"09:00", "09:10", "09:20", "09:30", "09:40"});
        option.xAxis(xAxis);
        
        com.github.abel533.echarts.axis.ValueAxis yAxis = new com.github.abel533.echarts.axis.ValueAxis();
        yAxis.setName("温度");
        yAxis.setMax(100);
        option.yAxis(yAxis);
        
        // 添加数据
        option.series(Magic.bar, new com.github.abel533.echarts.series.Bar().setData(new int[]{20, 30, 40, 50, 60}));
        
        // 输出JSON格式
        System.out.println(option.toString());
    }
}