Python-地图可视化

地图可视化

  • 1.基础地图使用
    • 1.1基础地图演示
    • 1.2视觉映射器
  • 2.全国疫情地图
    • 2.1数据整理
    • 2.2创建地图并添加数据
    • 2.3设置全局配置
  • 3.省级疫情图

1.基础地图使用

1.1基础地图演示

# 导入模块
from pyecharts.charts import Map
# 绘图
map = Map()
# 构建数据
data = [
    ("北京市",99),
    ("上海市",199),
    ("湖南省",299),
    ("台湾省",199),
    ("安徽省",299),
    ("广州省",399),
    ("湖北省",599)
]
map.add("地图",data,"china")
map.render("基础地图.html")

Python-地图可视化_第1张图片

1.2视觉映射器

# 导入模块
from pyecharts.charts import Map
from pyecharts.options import VisualMapOpts
# 绘图
map = Map()
# 构建数据
data = [
    ("北京市",99),
    ("上海市",199),
    ("湖南省",299),
    ("台湾省",199),
    ("安徽省",299),
    ("广州省",399),
    ("湖北省",599)
]
map.add("地图",data,"china")
# 设置全局选项
map.set_global_opts(
    visualmap_opts=VisualMapOpts(
        is_show=True,
        is_piecewise=True,  # 允许手动校准范围
        pieces=[
            {"min":1,"max":9,"label":"1-9","color":"#CCFFFF"},
            {"min":10,"max":99,"label":"10-99","color":"#FF6666"},
            {"min":100,"max":500,"label":"100-500","color":"#990033"}
        ]
    )
)
# 绘图
map.render("基础地图.html")

Python-地图可视化_第2张图片

2.全国疫情地图

2.1数据整理

# 导入json模块
import json
# 读取文件
f = open("D:/疫情.txt","r",encoding="UTF-8")
data = f.read() # 获取全部数据
# 关闭文件
f.close()
# 将字符串json转换成python的字典
data_dict = json.loads(data)   # 基础数据字典

Python-地图可视化_第3张图片
Python-地图可视化_第4张图片

# 取到各省数据
# 将字符串json转换成python的字典
data_dict = json.loads(data)   # 基础数据字典
# 从字典中取出省份的数据
province_data_list = data_dict["areaTree"][0]["children"]
# 组装每个省份和确诊人数为元组,将各个省的数据都封装如列表中
data_list = []  # 绘图需要的数据列表
for province_data in province_data_list:
    province_name = province_data["name"]  # 各省份名称
    province_confirm = province_data["total"]["confirm"]  # 各省份确诊人数
    data_list.append((province_name,province_confirm))

2.2创建地图并添加数据

# 绘制地图对象
map = Map()
# 添加数据
map.add("各省份确诊人数",data_list,"china")

2.3设置全局配置

# 设置全局配置,定制分段的视觉映射
map.set_global_opts(
    title_opts=TitleOpts(title="全国疫情图"),
    visualmap_opts=VisualMapOpts(
        is_show=True,      # 是否显示
        is_piecewise=True, # 是否分段
        pieces=[
        {"min":1,"max":9,"label":"1-9","color":"#CCFFFF"},
        {"min":100,"max":999,"label":"100-999","color":"#FFFF99"},
        {"min":1000,"max":4999,"label":"1000-4999","color":"#FF9966"},
        {"min":5000,"max":9999,"label":"5000-9999","color":"#FF6666"},
        {"min":10000,"max":99999,"label":"10000-99999","color":"#CC3333"},
        {"min":100000,"label":"100000+","color":"#990033"},
        ]
    )
)
# 绘图
map.render("全国疫情地图.html")

Python-地图可视化_第5张图片

3.省级疫情图

import json
from pyecharts.charts import Map
from pyecharts.options import *
f = open("D:/疫情.txt","r",encoding="UTF-8")
data = f.read()
data = json.loads(data)
Tianjin_data_list = data["areaTree"][0]["children"][13]["children"]
data_list = []
for Tianjin_data in Tianjin_data_list:
    name = Tianjin_data["name"]
    confirm = Tianjin_data["total"]["confirm"]
    data_list.append((name,confirm))
print(data_list)
map = Map()
map.add("天津市疫情地图",data_list,"天津")
map.set_global_opts(
    title_opts=TitleOpts(title="天津市疫情地图"),
    visualmap_opts=VisualMapOpts(
        is_show=True,
        is_piecewise=True,
        pieces=[
        {"min":1,"max":9,"label":"1-9","color":"#CCFFFF"},
        {"min":10,"max":99,"label":"100-999","color":"#FFFF99"},
        {"min":100,"max":500,"label":"1000-4999","color":"#FF9966"},
        {"min":501,"max":999,"label":"5000-9999","color":"#FF6666"},
        {"min":10000,"label":"10000-99999","color":"#CC3333"}
        ]
    )
)
map.render("省级疫情地图.html")

Python-地图可视化_第6张图片

你可能感兴趣的:(Python学习,python,信息可视化,开发语言)