Echarts+vue+java+mysql实现数据可视化-阿里云开发者社区

一、折线图，柱状图

https://echarts.apache.org/zh/index.html echarts 官网

更多配置项可以去官网查看

在开始项目之前，确保您已经安装了以下工具和技术：

MySQL 数据库：用于存储和管理数据。
Java 后端：用于创建后端应用程序，提供数据 API 和数据库连接。

Vue.js 前端：用于构建前端界面，呈现数据可视化图表。
ECharts：用于创建各种类型的图表和数据可视化。

步骤 1: 创建表以及生成数据

-- 创建产品表
CREATE TABLE a_products (
  product_id INT PRIMARY KEY COMMENT '产品ID',
  product_name VARCHAR(255) COMMENT '产品名称',
  unit_price DECIMAL(10, 2) COMMENT '产品单价（带两位小数）'
) COMMENT '存储产品信息';


-- 创建销售表
CREATE TABLE a_sales (
  sale_id INT PRIMARY KEY COMMENT '销售ID',
  product_id INT COMMENT '产品ID（外键，关联到products表）',
  sale_date DATE COMMENT '销售日期',
  quantity INT COMMENT '销售数量',
  revenue DECIMAL(10, 2) COMMENT '销售收入（带两位小数）'
) COMMENT '存储销售数据';

-- 插入产品数据
INSERT INTO a_products (product_id, product_name, unit_price) VALUES
(1, 'Product A', 10.50),
(2, 'Product B', 15.75);

-- 插入销售数据
INSERT INTO a_sales (sale_id, product_id, sale_date, quantity, revenue)
VALUES
  (1, 1, '2023-11-01', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (2, 1, '2023-11-02', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (3, 1, '2023-11-03', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (4, 1, '2023-11-04', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (5, 1, '2023-11-05', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (6, 1, '2023-11-01', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (7, 1, '2023-11-02', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (8, 1, '2023-11-03', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (9, 1, '2023-11-04', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (10, 1, '2023-11-05', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2));

-- For product_id 2
INSERT INTO a_sales (sale_id, product_id, sale_date, quantity, revenue)
VALUES
  (11, 2, '2023-11-01', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (12, 2, '2023-11-02', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (13, 2, '2023-11-03', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (14, 2, '2023-11-04', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (15, 2, '2023-11-05', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (16, 2, '2023-11-01', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (17, 2, '2023-11-02', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (18, 2, '2023-11-03', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (19, 2, '2023-11-04', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2)),
  (20, 2, '2023-11-05', FLOOR(RAND() * 20) + 1, ROUND(RAND() * 100, 2));

步骤2.数据库查询 SQL

--  查询销售数据
SELECT
        s.sale_date AS saleDate,
        p.product_name AS productName,
        COALESCE(SUM(s.quantity), 0) AS totalQuantity,
        COALESCE(SUM(s.revenue), 0) AS totalRevenue
        FROM a_products p
        LEFT JOIN a_sales s ON p.product_id = s.product_id
 GROUP BY s.sale_date, p.product_name

查询结果:

步骤3. 创建实体类

import lombok.Data;
import java.util.List;
@Data
public class SalesDTO {

    @ApiModelProperty(value = "日期")
    private String saleDate;
    @ApiModelProperty(value = "产品名")
    private String productName;
    @ApiModelProperty(value = "销售数量")
    private int totalQuantity;
    @ApiModelProperty(value = "销售额")
    private double totalRevenue;

// 省略构造函数、getter和setter 如果引入了lombok.Data不需要
}

步骤四: SalesMapper

public interface SalesMapper {


    /**
     * 根据产品名称统计产品售出数量
     * @param
     * @return
     */
    List<SalesDTO> getProductSalesSummary(@Param("productName") String productName);


    /**
     * 获取所有产品
     * @return
     */
    List<String> getAllProductName();
}

步骤五:SalesMapper.xml

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
<mapper namespace="org.jeecg.modules.statistics.mapper.SalesMapper">
    <resultMap id="SalesDTOResultMap" type="org.jeecg.modules.statistics.entity.SalesDTO">
        <id property="saleDate" column="saleDate"/>
        <result property="productName" column="productName"/>
        <result property="totalQuantity" column="totalQuantity"/>
        <result property="totalRevenue" column="totalRevenue"/>
    </resultMap>

    <select id="getProductSalesSummary" resultMap="SalesDTOResultMap">
        SELECT
        s.sale_date AS saleDate,
        p.product_name AS productName,
        COALESCE(SUM(s.quantity), 0) AS totalQuantity,
        COALESCE(SUM(s.revenue), 0) AS totalRevenue
        FROM a_products p
        LEFT JOIN a_sales s ON p.product_id = s.product_id


        <where>
            <if test="productName != null and productName != ''">
                and p.product_name =#{productName}
            </if>

        </where>
        GROUP BY s.sale_date, p.product_name
    </select>

    <select id="getAllProductName" resultType="java.lang.String">
      SELECT product_name FROM  a_products  GROUP BY product_name
    </select>
</mapper>

步骤七:SalesController

package org.jeecg.modules.statistics.controller;

import groovyjarjarpicocli.CommandLine;
import io.swagger.annotations.Api;
import io.swagger.annotations.ApiOperation;
import lombok.extern.slf4j.Slf4j;
import org.apache.xmlbeans.impl.inst2xsd.SalamiSliceStrategy;
import org.jeecg.common.api.vo.Result;
import org.jeecg.modules.statistics.entity.SalesDTO;
import org.jeecg.modules.statistics.mapper.SalesMapper;
import org.jeecg.modules.statistics.service.IKgOrderService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;

import java.time.LocalDate;
import java.time.format.DateTimeFormatter;
import java.util.*;
import java.util.stream.Collectors;

@RestController
@RequestMapping("/sales")
@Api(tags = "统计图表示例")
@Slf4j
public class SalesController {


    @Autowired
    private SalesMapper salesMapper;

    @ApiOperation(value = "统计图表示例-A", notes = "统计图表示例-A")
    @GetMapping(value = "/summary")
    public Result<Map<String, Object>> getSalesSummary() {
       //也可以包装一个实体类返回
        Result<Map<String, Object>> result = new Result<>();
        Map<String, Object> resultMap = new HashMap<>();
        // 获取所有产品名称列表
        List<String> distinctProductNames = salesMapper.getAllProductName();
        // 设置起始日期为 "2023-11-01" 也可以获取系统时间
        LocalDate startDate = LocalDate.parse("2023-11-01");
        // 生成近五天的日期列表
        List<String> distinctSaleDates = new ArrayList<>();
        for (int i = 0; i < 5; i++) {
            LocalDate date = startDate.plusDays(i);
            distinctSaleDates.add(date.format(DateTimeFormatter.ISO_DATE));
        }

        List<Map<String, Object>> seriesData = new ArrayList<>();
        // 遍历每个产品名称
        for (String distinctProductName : distinctProductNames) {
            // 根据产品名称获取产品销售数据
            List<SalesDTO> productSalesSummary = salesMapper.getProductSalesSummary(distinctProductName);

            Map<String, Object> seriesItem = new HashMap<>();
            seriesItem.put("name", distinctProductName);

            List<Integer> quantityList = new ArrayList<>();

            // 遍历日期列表
            for (String distinctSaleDate : distinctSaleDates) {
                // 使用 Optional 包装以处理空值情况
                Optional<SalesDTO> matchingSale = productSalesSummary.stream()
                        .filter(dto -> dto.getSaleDate().equals(distinctSaleDate))
                        .findFirst();

                if (matchingSale.isPresent()) {
                    // 如果存在匹配的销售数据，添加到数量列表中
                    quantityList.add(matchingSale.get().getTotalQuantity());
                } else {
                    // 如果没有匹配的销售数据 设置为0
                    quantityList.add(0);
                }
            }
            seriesItem.put("data", quantityList);
            seriesData.add(seriesItem);
        }

        resultMap.put("dates", distinctSaleDates);
        resultMap.put("series", seriesData);

        result.setResult(resultMap);

        return result;
    }
}

响应结果

步骤8:通过cdn引入echarts --解决打包过大问题

找到index.html

在index.html 加入以下代码

<script src="https://cdn.jsdelivr.net/npm/echarts@5.3.0/dist/echarts.min.js"></script>

步骤9:vue.js 加载数据与Echarts 图表

<template>
  <!-- 柱状图容器 -->
  <div class="bar-chart-container">
    <div ref="barChart" class="echarts-chart"></div>
  </div>
</template>

<script>
// 导入 API 请求方法
import {
  getAction
} from '@/api/manage';

export default {
  data() {
    return {
      // API 请求的 URL 集合
      url: {
        getSalesSummary: '/jeecg-customers/sales/summary',
      },
      // 数据对象
      data: {},
      // ECharts 实例
      chart: null,
      // ECharts 图表配置
     chartOptions: {
       // 图表标题
       title: {
         text: '销售数据统计',
       },
       // X 轴配置
       xAxis: {
         type: "category", // X 轴类型为类别
         data: [], // X 轴的数据，即日期
       },
       // Y 轴配置
       yAxis: {
         type: "value", // Y 轴类型为值
         name: '销售数量', // Y 轴的名称
       },
       // 系列数据，即图表的线条/柱状等配置
       series: [],
       // 提示框配置
       tooltip: {
         trigger: 'axis', // 提示框触发方式为坐标轴触发
         axisPointer: {
           type: 'cross', // 十字准星指示器
         },
       },
       // 图例配置(鼠标覆盖上去有详情信息的)
       legend: {
         icon: 'rect', // 图例项的图标形状
         orient: 'horizontal', // 图例的布局方向
         itemWidth: 20, // 图例项的宽度
         itemHeight: 10, // 图例项的高度
         textStyle: {
           fontSize: 12, // 图例项的字体大小
         },
         right: '30%', // 图例相对于容器右侧的距离
       },
       // 工具箱配置 就是右上角可以下载原图 展示数据视图那个工具
       toolbox: {
         show: true, // 是否显示工具箱
         feature: {
           dataZoom: {}, // 数据区域缩放工具
           dataView: {
             readOnly: false // 是否只读
           },
           magicType: {
             type: ['line', 'bar'] // 切换图表类型工具
           },
           restore: {}, // 还原工具
           saveAsImage: {} // 保存为图片工具
         },
         right: '10%', // 工具箱相对于容器右侧的距离
       },
     },

    };
  },
  mounted() {
    // 页面加载后调用获取销售数据的方法
    this.getSalesSummaryLoad();
  },
  methods: {
    // 获取销售数据的方法
    getSalesSummaryLoad() {
      // 调用 API 请求获取销售数据
      getAction(this.url.getSalesSummary, {}).then((res) => {
        if (res.success) {
          console.log(res)
          const data = res.result;
          // 更新图表的 X 轴和 Series 数据
          this.chartOptions.xAxis.data = data.dates;
          this.chartOptions.series = data.series.map(item => {
            return {
              ...item,
              type: "line"
            };
          });
          // 初始化图表
          this.initChart();
        }
      });
    },
    // 初始化 ECharts 图表的方法
    initChart() {
      // 创建 ECharts 实例
      this.chart = echarts.init(this.$refs.barChart);
      // 设置图表宽度和高度
      const chartWidth = 1200;
      const chartHeight = 500;
      // 调整图表大小
      this.chart.resize({
        width: chartWidth,
        height: chartHeight
      });
      // 设置图表配置
      this.chart.setOption(this.chartOptions);
    },
  },
};
</script>

<style scoped>
  .bar-chart-container {}
</style>

步骤10:echarts各项配置

配置项	描述
title	配置图表的主标题。可以包括副标题和文本样式。
legend	配置图例，显示图例数据的区域。可以自定义位置、方向和文本样式。
tooltip	配置提示框，当悬停在数据点上时显示额外信息。可以自定义格式和内容。

grid	配置网格组件，定义图表网格的大小和位置。可以设置左、右、上、下，并包含标签样式。
xAxis	配置 x 轴，包括类型、数据、轴标签和轴刻度设置。
yAxis	配置 y 轴，与 xAxis 类似，包括类型、数据、轴标签和轴刻度设置。

series	配置要在图表上绘制的数据系列，如线条、柱状图、散点图等。每种系列类型都有自己的一组选项。
toolbox	配置工具箱，提供与图表交互的工具，如数据缩放、保存为图像等。

dataZoom	配置数据缩放组件，允许用户缩放到特定范围的数据。可以应用于 x 轴和 y 轴。
visualMap	配置视觉映射组件，将数据值映射到颜色等视觉属性。适用于显示数据强度或分布。
color	指定图表的颜色调色板。可以是颜色数组或预定义的颜色主题。

textStyle

配置图表中各种文本元素的默认文本样式，如标题、标签和提示框。

二、echarts 中国地图，china.json文件

1.效果图

2.引入china.json文件

找个地方写个china.json文件。内容复制这个代码。

{
    "type": "FeatureCollection",
    "features":
      [
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        { "type": "Feature", "properties": { "id": "50", "size": "2380", "name": "重庆", "cp": [107.7539, 29.8904], "childNum": 40 }, "geometry": { "type": "Polygon", "coordinates": [[[108.5449, 31.6846], [108.2813, 31.9043], [108.3691, 32.168], [108.5449, 32.2119], [109.0723, 31.9482], [109.248, 31.7285], [109.5996, 31.7285], [109.7754, 31.6846], [109.6875, 31.5527], [110.127, 31.377], [110.2148, 31.1572], [110.0391, 30.8057], [109.8633, 30.8936], [109.4238, 30.542], [109.248, 30.6299], [109.1602, 30.542], [109.0723, 30.6299], [108.8086, 30.498], [108.6328, 30.5859], [108.457, 30.4102], [108.5449, 30.2344], [108.457, 29.7949], [108.6328, 29.8389], [108.9844, 29.3115], [109.0723, 29.3555], [109.248, 29.1357], [109.248, 28.4766], [109.0723, 28.2129], [108.7207, 28.2129], [108.7207, 28.4766], [108.5449, 28.3887], [108.5449, 28.6523], [108.3691, 28.6523], [108.2813, 29.0918], [107.8418, 29.0039], [107.8418, 29.1357], [107.5781, 29.2236], [107.4023, 29.1797], [107.4023, 28.8721], [106.875, 28.7842], [106.6992, 28.4766], [106.6113, 28.5205], [106.6113, 28.6523], [106.5234, 28.7842], [106.4355, 28.7842], [106.5234, 28.5645], [106.3477, 28.5205], [106.2598, 28.8721], [105.8203, 28.96], [105.7324, 29.2676], [105.4688, 29.3115], [105.293, 29.5313], [105.7324, 29.8828], [105.5566, 30.1025], [105.6445, 30.2783], [105.8203, 30.4541], [106.2598, 30.1904], [106.6113, 30.3223], [106.7871, 30.0146], [107.0508, 30.0146], [107.4902, 30.6299], [107.4023, 30.7617], [107.4902, 30.8496], [107.9297, 30.8496], [108.1934, 31.5088], [108.5449, 31.6846]]] } },
        { "type": "Feature", "properties": { "id": "64", "size": "2100", "name": "宁夏", "cp": [105.9961, 37.1096], "childNum": 5 }, "geometry": { "type": "Polygon", "coordinates": [[[104.3262, 37.4414], [105.8203, 37.793], [105.9082, 38.7158], [106.3477, 39.2871], [106.7871, 39.375], [106.9629, 38.9795], [106.5234, 38.3203], [106.7871, 38.1885], [107.3145, 38.1006], [107.666, 37.8809], [107.3145, 37.6172], [107.3145, 37.0898], [106.6113, 37.0898], [106.6113, 36.7822], [106.4355, 36.5625], [106.5234, 36.4746], [106.5234, 36.2549], [106.875, 36.123], [106.9629, 35.8154], [106.6992, 35.6836], [106.4355, 35.6836], [106.5234, 35.332], [106.3477, 35.2441], [106.2598, 35.4199], [106.084, 35.376], [105.9961, 35.4199], [106.084, 35.4639], [105.9961, 35.4639], [105.8203, 35.5518], [105.7324, 35.7275], [105.3809, 35.7715], [105.293, 35.9912], [105.4688, 36.123], [105.2051, 36.6943], [105.293, 36.8262], [104.8535, 37.2217], [104.5898, 37.2217], [104.5898, 37.4414], [104.3262, 37.4414]]] } },
        { "type": "Feature", "properties": { "id": "46", "size": "4500", "name": "海南", "cp": [109.9512, 19.2041], "childNum": 18 }, "geometry": { "type": "Polygon", "coordinates": [[[108.6328, 19.3799], [109.0723, 19.6436], [109.248, 19.9512], [109.5996, 20.0391], [110.0391, 20.127], [110.3906, 20.127], [110.5664, 20.2588], [110.6543, 20.2588], [111.0938, 19.9512], [111.2695, 19.9951], [110.6543, 19.1602], [110.5664, 18.6768], [110.2148, 18.5889], [110.0391, 18.3691], [109.8633, 18.3691], [109.6875, 18.1055], [108.9844, 18.2813], [108.6328, 18.457], [108.6328, 19.3799]]] } },
        { "type": "Feature", "properties": { "id": "71", "size": "3000", "name": "台湾", "cp": [120.8254, 23.5986], "childNum": 1 }, "geometry": { "type": "Polygon", "coordinates": [[[121.9043, 25.0488], [121.9922, 25.0049], [121.8164, 24.7412], [121.9043, 24.5654], [121.6406, 24.0381], [121.377, 23.1152], [121.0254, 22.6758], [120.8496, 22.0605], [120.7617, 21.9287], [120.6738, 22.3242], [120.2344, 22.5879], [120.0586, 23.0713], [120.1465, 23.6865], [121.0254, 25.0488], [121.5527, 25.3125], [121.9043, 25.0488]]] } },
        { "type": "Feature", "properties": { "id": "11", "size": "5000", "name": "北京", "cp": [116.4551, 40.2539], "childNum": 19 }, "geometry": { "type": "Polygon", "coordinates": [[[117.4219, 40.21], [117.334, 40.1221], [117.2461, 40.0781], [116.8066, 39.9902], [116.8945, 39.8145], [116.8945, 39.6826], [116.8066, 39.5947], [116.543, 39.5947], [116.3672, 39.4629], [116.1914, 39.5947], [115.752, 39.5068], [115.4883, 39.6387], [115.4004, 39.9463], [115.9277, 40.2539], [115.752, 40.5615], [116.1035, 40.6055], [116.1914, 40.7813], [116.4551, 40.7813], [116.3672, 40.9131], [116.6309, 41.0449], [116.9824, 40.6934], [117.4219, 40.6494], [117.2461, 40.5176], [117.4219, 40.21]]] } },
        { "type": "Feature", "properties": { "id": "12", "size": "5000", "name": "天津", "cp": [117.4219, 39.4189], "childNum": 18 }, "geometry": { "type": "Polygon", "coordinates": [[[116.8066, 39.5947], [116.8945, 39.6826], [117.1582, 39.6387], [117.1582, 39.8145], [117.2461, 40.0781], [117.334, 40.1221], [117.4219, 40.21], [117.6855, 40.0781], [117.6855, 39.9902], [117.5098, 39.9902], [117.5098, 39.7705], [117.6855, 39.5947], [117.9492, 39.5947], [117.8613, 39.4189], [118.0371, 39.2432], [118.0371, 39.1992], [117.8613, 39.1113], [117.5977, 38.6279], [117.2461, 38.54], [116.7188, 38.8037], [116.7188, 38.9355], [116.8945, 39.1113], [116.8066, 39.5947]]] } },
        { "type": "Feature", "properties": { "id": "31", "size": "7500", "name": "上海", "cp": [121.4648, 31.2891], "childNum": 19 }, "geometry": { "type": "Polygon", "coordinates": [[[120.9375, 31.0254], [121.2012, 31.4648], [121.377, 31.5088], [121.1133, 31.7285], [121.2012, 31.8604], [121.9922, 31.5967], [121.9043, 31.1572], [121.9922, 30.8057], [121.2891, 30.6738], [120.9375, 31.0254]]] } },
        { "type": "Feature", "properties": { "id": "81", "size": "18000", "name": "香港", "cp": [114.6178, 22.3242], "childNum": 1 }, "geometry": { "type": "Polygon", "coordinates": [[[114.6094, 22.4121], [114.5215, 22.1484], [114.3457, 22.1484], [113.9063, 22.1484], [113.8184, 22.1924], [113.9063, 22.4121], [114.1699, 22.5439], [114.3457, 22.5439], [114.4336, 22.5439], [114.4336, 22.4121], [114.6094, 22.4121]]] } },
        { "type": "Feature", "properties": { "id": "82", "size": "27", "name": "澳门", "cp": [113.5547, 21.6484], "childNum": 1 }, "geometry": { "type": "Polygon", "coordinates": [[[113.5986, 22.1649], [113.6096, 22.1265], [113.5547, 22.11], [113.5437, 22.2034], [113.5767, 22.2034], [113.5986, 22.1649]]] } }
      ]
  }

3:地图的代码

  
 <template>
   <div class="chartBox">
     <div id="mapChart" style="width: 800px;height: 700px;"></div>
   </div>
 </template>
 
 <script>
 import china from "../../utils/china.json";
 export default {
   data() {
     return {};
   },
   mounted() {
     this.getMapChart();
   },
   methods: {
     getMapChart() {
        echarts.registerMap('china', china)
       var dataValue = this.dealWithData();
       var data1 = dataValue.splice(0, 6);
       var myChart = echarts.init(document.getElementById("mapChart"));
       var option = {
         tooltip: {
           show: false,
         },
         backgroundColor: "#fff",
         geo: {
           map: "china",
           roam: false, // 一定要关闭拖拽
           zoom: 1.23,
           center: [105, 36], // 调整地图位置
           label: {
             normal: {
               show: false, //关闭省份名展示
               fontSize: "10",
               color: "rgba(0,0,0,0.7)",
             },
             emphasis: {
               show: false,
             },
           },
           itemStyle: {
             normal: {
               areaColor: "#0d0059",
               borderColor: "#389dff",
               borderWidth: 1, //设置外层边框
               shadowBlur: 5,
               shadowOffsetY: 8,
               shadowOffsetX: 0,
               shadowColor: "#01012a",
             },
             emphasis: {
               areaColor: "#184cff",
               shadowOffsetX: 0,
               shadowOffsetY: 0,
               shadowBlur: 5,
               borderWidth: 0,
               shadowColor: "rgba(0, 0, 0, 0.5)",
             },
           },
         },
         legend: {
           orient: "horizontal",
           height: "50%",
           top: "0%",
           right: "10%",
         },
         series: [
           {
             type: "map",
             map: "china",
             roam: false,
             zoom: 1.23,
             center: [105, 36],
             // geoIndex: 1,
             // aspectScale: 0.75, //长宽比
             showLegendSymbol: false, // 存在legend时显示
             label: {
               // 显示地图省名称
               normal: {
                 color: "#389dff",
                 formatter: "{b}",
                 position: [-12, -1],
                 show: true,
               },
               emphasis: {
                 show: false,
               },
             },
             itemStyle: {
               normal: {
                 areaColor: "#0d0059",
                 borderColor: "#389dff",
                 borderWidth: 0.5,
               },
               emphasis: {
                 areaColor: "#17008d",
                 shadowOffsetX: 0,
                 shadowOffsetY: 0,
                 shadowBlur: 5,
                 borderWidth: 0,
                 shadowColor: "rgba(0, 0, 0, 0.5)",
               },
             },
           },
           {
             name: "",
             type: "scatter",
             coordinateSystem: "geo",
             data: dataValue,
             symbol: "circle",
             symbolSize: 5,
             hoverSymbolSize: 10,
             tooltip: {
               formatter(value) {
                 return (
                   value.data.name + "<br/>" + "物流量：" + value.data.value[2]
                 );
               },
               show: true,
             },
             encode: {
               value: 2,
             },
             label: {
               formatter: "{b}",
               position: "right",
               show: false,
             },
             itemStyle: {
               color: "#0efacc",
             },
             emphasis: {
               label: {
                 show: false,
               },
             },
           },
           {
             name: "前五城市标记点动画",
             type: "effectScatter",
             coordinateSystem: "geo",
             data: data1,
             symbolSize: 8,
             tooltip: {
               formatter(value) {
                 return (
                   value.data.name + "<br/>" + "访问量：" + value.data.value[2]
                 );
               },
               show: true,
             },
             encode: {
               value: 2,
             },
             showEffectOn: "render",
             rippleEffect: {
               brushType: "stroke",
               color: "#0efacc",
               period: 9,
               scale: 5,
             },
             hoverAnimation: true,
             label: {
               formatter: "{b}",
               position: "right",
               show: true,
             },
             itemStyle: {
               color: "#0efacc",
               shadowBlur: 2,
               shadowColor: "#333",
             },
             zlevel: 1,
           },
         ],
       };
       myChart.setOption(option);
       window.onresize = () => {
         myChart.resize();
       };
     },
     dealWithData() {
       var geoCoordMap = [
         {
           name: "广州",
           value: [113.23, 23.16, 20],
         },
         {
           name: "深圳",
           value: [114.07, 22.62, 60],
         },
         {
           name: "呼和浩特",
           value: [111.65, 40.82, 20],
         },
         {
           name: "宁波",
           value: [121.56, 29.86, 10],
         },
         {
           name: "珠海",
           value: [113.52, 22.3, 10],
         },
         {
           name: "重庆",
           value: [106.54, 29.59, 11],
         },
         {
           name: "杭州",
           value: [120.19, 30.26, 12],
         },
         {
           name: "九江",
           value: [115.97, 29.71, 13],
         },
         {
           name: "哈尔滨",
           value: [126.63, 45.75, 14],
         },
         {
           name: "合肥",
           value: [117.27, 31.86, 15],
         },
         {
           name: "义乌",
           value: [120.06, 29.32],
         },
       ];
       return geoCoordMap;
     },
   },
 };
 </script>
 
 <style lang="less" scoped>
 .chartBox {
   width: 100%;
   height: 100vh;
 }
 
 #mapChart {
   width: 100%;
   height: 100%;
 }
 </style>

Echarts+vue+java+mysql实现数据可视化

一、折线图，柱状图

步骤 1: 创建表以及生成数据

步骤2.数据库查询 SQL

步骤3. 创建实体类

步骤四: SalesMapper

步骤五:SalesMapper.xml

步骤七:SalesController

步骤8:通过cdn引入echarts --解决打包过大问题

步骤9:vue.js 加载数据与Echarts 图表

步骤10:echarts各项配置

二、echarts 中国地图，china.json文件

1.效果图

2.引入china.json文件

3:地图的代码

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Echarts+vue+java+mysql实现数据可视化

一、折线图，柱状图

步骤 1: 创建表 以及生成数据

步骤2.数据库查询 SQL

步骤3. 创建实体类

步骤四: SalesMapper

步骤五:SalesMapper.xml

步骤七:SalesController

步骤8:通过cdn引入echarts --解决打包过大问题

步骤9:vue.js 加载数据与Echarts 图表

步骤10:echarts各项配置

二、echarts 中国地图，china.json文件

1.效果图

2.引入china.json文件

3:地图的代码

热门文章

最新文章

相关课程

相关电子书

相关实验场景

推荐镜像

步骤 1: 创建表以及生成数据