应用实例(二)：地图

• 基础使用

from pyecharts.charts import Map
from pyecharts.options import VisualMapOpts
 
# 准备地图对象
map = Map()
# 准备数据
data = [
    ("北京", 99),
    ("上海", 199),
    ("湖南", 299),
    ("台湾", 399),
    ("广东", 499)
]
# 添加数据
map.add("测试地图", data, "china")
 
# 设置全局选项
map.set_global_opts(
    visualmap_opts=VisualMapOpts(
        is_show=True,
        is_piecewise=True,
        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()

• 案例2

import json
from pyecharts.charts import Map
from pyecharts.options import *
 
# 读取数据文件
f = open("D:/疫情.txt", "r", encoding="UTF-8")
data = f.read()     # 全部数据
# 关闭文件
f.close()
# 取到各省数据
# 将字符串json转换为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，并各个省的数据都封装入列表内
data_list = []      # 绘图需要用的数据列表
for province_data in province_data_list:
    province_name = province_data["name"]                   # 省份名称
    province_confirm = province_data["total"]["confirm"]    # 确诊人数
    data_list.append((province_name, province_confirm))
 
# 创建地图对象
map = Map()
# 添加数据
map.add("各省份确诊人数", data_list, "china")
# 设置全局配置，定制分段的视觉映射
map.set_global_opts(
    title_opts=TitleOpts(title="全国疫情地图"),
    visualmap_opts=VisualMapOpts(
        is_show=True,           # 是否显示
        is_piecewise=True,      # 是否分段
        pieces=[
            {"min": 1, "max": 99, "lable": "1~99人", "color": "#CCFFFF"},
            {"min": 100, "max": 999, "lable": "100~9999人", "color": "#FFFF99"},
            {"min": 1000, "max": 4999, "lable": "1000~4999人", "color": "#FF9966"},
            {"min": 5000, "max": 9999, "lable": "5000~99999人", "color": "#FF6666"},
            {"min": 10000, "max": 99999, "lable": "10000~99999人", "color": "#CC3333"},
            {"min": 100000, "lable": "100000+", "color": "#990033"},
        ]
    )
)
# 绘图
map.render("全国疫情地图.html")

• 案例3

import json
from pyecharts.charts import Map
from pyecharts.options import *
 
# 读取文件
f = open("D:/疫情.txt", "r", encoding="UTF-8")
data = f.read()
# 关闭文件
f.close()
# 获取河南省数据
# json数据转换为python字典
data_dict = json.loads(data)
# 取到河南省数据
cities_data = data_dict["areaTree"][0]["children"][3]["children"]
# 准备数据为元组并放入list
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))
# 手动添加济源市的数据
data_list.append(("济源市", 5))
 
# 构建地图
map = Map()
map.add("河南省疫情分布", data_list, "河南")
# 设置全局选项
map.set_global_opts(
    title_opts=TitleOpts(title="河南省疫情地图"),
    visualmap_opts=VisualMapOpts(
        is_show=True,           # 是否显示
        is_piecewise=True,      # 是否分段
        pieces=[
            {"min": 1, "max": 99, "lable": "1~99人", "color": "#CCFFFF"},
            {"min": 100, "max": 999, "lable": "100~9999人", "color": "#FFFF99"},
            {"min": 1000, "max": 4999, "lable": "1000~4999人", "color": "#FF9966"},
            {"min": 5000, "max": 9999, "lable": "5000~99999人", "color": "#FF6666"},
            {"min": 10000, "max": 99999, "lable": "10000~99999人", "color": "#CC3333"},
            {"min": 100000, "lable": "100000+", "color": "#990033"},
        ]
    )
)
# 绘图
map.render("河南省疫情地图.html")