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 11.3 疫情地图 - 省级疫情地图

桃扇骨 2024-03-27 14:00 66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
         *   *  11.3 疫情地图 - 省级疫情地图
             *   *  11.3.1 省疫情地图

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

##### 11.3 疫情地图 - 省级疫情地图 #####

###### 11.3.1 省疫情地图 ######

效果展示

![在这里插入图片描述][0fb0b86f640a4334842ead5aee1e0f7f.png_pic_center]

获取河南省各市数据

![在这里插入图片描述][e7e355f5e3624f9fb3c9680346fb32eb.png_pic_center]

省数据结构:

![在这里插入图片描述][a60df42da86341f08843bc60ca85c713.png_pic_center]

把各市数据汇总到一个列表中:

![在这里插入图片描述][baf4091aa9f74d6fb07057db5fccfc59.png_pic_center]

![在这里插入图片描述][ed895931cc0d4de5894440c0165b9bba.png_pic_center]

参考国内疫情地图生成河南省疫情地图:

![在这里插入图片描述][82bd9a8a0db4458e91c1f5d1c9555575.png_pic_center]

![在这里插入图片描述][e7c633ef23e84224ae02353d5aff12d7.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)
    
    cities_data = data_dict["areaTree"][0]['children'][3]["children"]
    
    data_list = []
    for city_data in cities_data:
        city_name = city_data["name"] + "市"
        city_confirm = city_data["total"]["confirm"]
        data_list.append((city_name, city_confirm))
    
    data_list.append(("济源市", 5))
    
    map = Map()
    map.add("河南省疫情分布", data_list, "河南")
    map.set_global_opts(
        title_opts=TitleOpts(title="河南疫情地图"),
        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("河南省疫情地图.html")

运行结果

![在这里插入图片描述][6e2f3df7fd584a7e887b7bc7437e653f.png_pic_center]

[python_8_python_python]: https://www.bilibili.com/video/BV1qW4y1a7fU
[0fb0b86f640a4334842ead5aee1e0f7f.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/10687d94c7d749f3a2f7a0528ee40055.png
[e7e355f5e3624f9fb3c9680346fb32eb.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/4a2bcbf5ba9149959b23e7b07224f5a1.png
[a60df42da86341f08843bc60ca85c713.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/efd1c295c2e248d3aeff85efc052afd0.png
[baf4091aa9f74d6fb07057db5fccfc59.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/cd7393a099bd459f8bd8ebebe8244b9f.png
[ed895931cc0d4de5894440c0165b9bba.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/abc14e06bf3546448556b7f6dab0509e.png
[82bd9a8a0db4458e91c1f5d1c9555575.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/0f84f6540690467e8758828eab6f25b3.png
[e7c633ef23e84224ae02353d5aff12d7.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/852bdfaba9e64c9dbeac4dcd20dba516.png
[6e2f3df7fd584a7e887b7bc7437e653f.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/ecf579fd536c4ec4b307ee99d9c46b91.png