8天Python从入门到精通第十一章 Python基础综合案例数据可视化 - 地图可视化 11.2 疫情地图 - 国内疫情地图

拼搏现实的明天。 2024-03-27 14:00 70阅读 0赞

#### 8天Python从入门到精通 ####

[【黑马程序员python教程，8天python从入门到精通，学python看这套就够了】][python_8_python_python]

#### 文章目录 ####

*   *   *  8天Python从入门到精通
         *  第十一章 Python基础综合案例 数据可视化 - 地图可视化
         *   *  11.2 疫情地图 - 国内疫情地图
             *   *  11.2.1 案例效果
                 *  11.2.2 数据整理
                 *  11.2.3 国内疫情地图

#### 第十一章 Python基础综合案例 数据可视化 - 地图可视化 ####

##### 11.2 疫情地图 - 国内疫情地图 #####

###### 11.2.1 案例效果 ######

![在这里插入图片描述][cccddf4e512c4516881ab0552563a84b.png_pic_center]

###### 11.2.2 数据整理 ######

**获取数据**

![在这里插入图片描述][d0a9e02b38b4424ab2107b80da2e85d7.png_pic_center]

![在这里插入图片描述][ea030952df2a43a8bcf0d3cd88d5e204.png_pic_center]

**数据整体结构（全国）**

![在这里插入图片描述][7502defdf2924a12a371918fd258e9ee.png_pic_center]

**省数据结构**

![在这里插入图片描述][249bec9aef414221a377e041f6cb63e4.png_pic_center]

**获取每个省份的确诊数据:**

![在这里插入图片描述][26268e01e7624213b5ebbc205498a5b7.png_pic_center]

上述代码执行后输出，每个省的确诊数据:

![在这里插入图片描述][b71d88ec365f421f9774f4473517f9b0.png_pic_center]

###### 11.2.3 国内疫情地图 ######

创建地图并添加数据

导入模块:

![在这里插入图片描述][dd1414d92b044bf1976d220ac3973485.png_pic_center]

创建地图:

![在这里插入图片描述][afb43340a6f0457d988a22b7391e97a6.png_pic_center]

添加数据:

![在这里插入图片描述][e21ad795604546dea81b6c2c66b07760.png_pic_center]

![在这里插入图片描述][1b737f06fd294765a0950bb2437faacc.png_pic_center]

![在这里插入图片描述][85cad64d8089419caa7f548ca267e2e5.png_pic_center]

![在这里插入图片描述][190a9aea4a6b4c528e82e9c33eefafae.png_pic_center]

![在这里插入图片描述][ab4c18d74b2f4173b9cec81277288f0f.png_pic_center]

![在这里插入图片描述][5ca770b7ea3b479ab0a3628efd14818a.png_pic_center]

设置全局配置选项

![在这里插入图片描述][537af5ed870345b2b4e35ad287b6311e.png_pic_center]

![在这里插入图片描述][a1b1a502f56046fda6f7a306010c94e7.png_pic_center]

![在这里插入图片描述][5fadc21ab77a4f8fb5e33c42caa49e23.png_pic_center]

![在这里插入图片描述][3eaa44b085134d5f908ec2015e420d41.png_pic_center]

import json
    from pyecharts.charts import Map
    from pyecharts.options import *
    
    f = open("疫情.txt", 'r', encoding="UTF-8")
    data = f.read()
    f.close()
    
    data_dict = json.loads(data)
    
    province_data_list = data_dict["areaTree"][0]['children']
    
    data_list = []
    for province_data in province_data_list:
        province_name = province_data["name"]
        province_confirm = province_data["total"]["confirm"]
    
        data_list.append((province_name, province_confirm))
    print(data_list)
    
    map = Map()
    map.add("各省份确诊人数", data_list, "china")
    map.set_global_opts(
        title_opts=TitleOpts(title="全国疫情地图"),
        visualmap_opts=VisualMapOpts(
            is_show=True,
            is_piecewise=True,
            pieces=[
                {
        "min": 1, "max": 99, "label": "1-99人", "color": "#CCFFFF"},
                {
        "min": 100, "max": 999, "label": "100-999人", "color": "#FFFF99"},
                {
        "min": 1000, "max": 4999, "label": "1000-4999人", "color": "#FF9966"},
                {
        "min": 5000, "max": 9999, "label": "5000-9999人", "color": "#FF6666"},
                {
        "min": 10000, "max": 99999, "label": "10000-99999人", "color": "#CC3333"},
                {
        "min": 100000, "label": "100000+", "color": "#990033"}
            ]
        )
    )
    
    map.render("全国疫情地图.html")

运行结果

![在这里插入图片描述][f29388902b534db587ea0c23314078d3.png_pic_center]

[python_8_python_python]: https://www.bilibili.com/video/BV1qW4y1a7fU
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[d0a9e02b38b4424ab2107b80da2e85d7.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/95bda6a1227d43ac9224269da8d23101.png
[ea030952df2a43a8bcf0d3cd88d5e204.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/f0aab0c7fca940b1a052a2aa5e6ebbcf.png
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[26268e01e7624213b5ebbc205498a5b7.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/3fa06beaef7d4dcca4b7c72577a8d47d.png
[b71d88ec365f421f9774f4473517f9b0.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/0712178866224bbaa124ba392179e504.png
[dd1414d92b044bf1976d220ac3973485.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/8f61d495644c4b25b7e48b569c1bb359.png
[afb43340a6f0457d988a22b7391e97a6.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/7bf16a7e8dcb4a9f9a6cc91d4fb39b1a.png
[e21ad795604546dea81b6c2c66b07760.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/6cd272911400401dbf59e0bac72b4de0.png
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[85cad64d8089419caa7f548ca267e2e5.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/b3685e6ceaa54464aa16225d2b23a641.png
[190a9aea4a6b4c528e82e9c33eefafae.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/6d26453780e9467db62f6aebbb02244d.png
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[537af5ed870345b2b4e35ad287b6311e.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/a69332e58c944f9b88638035be6754a1.png
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[5fadc21ab77a4f8fb5e33c42caa49e23.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/a54981dab6a9410eb42e0141ee5af7b4.png
[3eaa44b085134d5f908ec2015e420d41.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/cffc4c0a1dc14db586997e5acfe75865.png
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