数据可视化:地图

1.基础地图的使用

如何添加颜色表示层级

代码实现

"""基础地图的使用
"""
from pyecharts.charts import Map
from pyecharts.options import VisualMapOpts# 准备地图对象
map = Map()
# 准备数据
data = [("北京市", 9),("上海市", 59),("甘肃省", 812),("黑龙江省", 313),("四川省", 1999),("台湾省", 19999)
]
# 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": "#38f55c"},{"min": 10, "max": 99, "label": "10-99", "color": "#f5ad38"},{"min": 100, "max": 499, "label": "100-500", "color": "#f54a38"},{"min": 500, "max": 998, "label": "500-998", "color": "#9d38f5"},{"min": 999, "label": ">999", "color": "#201641"}])
)# 绘图
map.render()

2.疫情地图——国内疫情地图

代码实现

"""演示全国疫情可视化地图开发
"""
import json
from pyecharts.charts import Map
from pyecharts.options import *# 读取数据文件
f = open("D:\\IOText\\DataDoing\\疫情.txt", "r", encoding="UTF-8")
china_data_json = f.read()
# 关闭文件
f.close()
# 取到各省数据
china_data_dict = json.loads(china_data_json)
province_data_list = china_data_dict["areaTree"][0]["children"]
# 地图最终所需的数据
map_list = list()
# 组装每一省份和确诊人数为元组，并各个省的数据都封装入列表内
for province_data in province_data_list:# 省份名称province_name = province_data["name"]# 确诊人数province_confirm = province_data["total"]["confirm"]map_list.append((province_name, province_confirm))
print(map_list)
# 创建地图对象
map = Map()# 添加数据
map.add("全国身份确诊人数", map_list, "china")# 设置全局配置，指定分段的视觉映射
map.set_global_opts(title_opts=TitleOpts(title="全国疫情地图"),visualmap_opts=VisualMapOpts(is_show=True,is_piecewise=True,pieces=[{"min": 1, "max": 99, "label": "1-99", "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")

相关数据文件在文章开头出获取

3.疫情地图——省级疫情地图

但是我直接演示四川的地图

代码示例

"""省级疫情地图
"""
import json
from pyecharts.charts import Map
from pyecharts.options import *# 读取数据文件
f = open("D:\\IOText\\DataDoing\\疫情.txt", "r", encoding="UTF-8")
sichuan_data_json = f.read()
# 关闭文件
f.close()
# 取到各省数据
sichuan_data_dict = json.loads(sichuan_data_json)
sichuan_children_data_list = sichuan_data_dict["areaTree"][0]["children"][12]["children"]
# 地图最终所需的数据
map_list = list()
# 组装每一省份和确诊人数为元组，并各个省的数据都封装入列表内
for province_data in sichuan_children_data_list:# 省份名称if province_data["name"] == "阿坝":province_name = province_data["name"] + "藏族羌族自治州"elif province_data["name"] == "甘孜":province_name = province_data["name"] + "藏族自治州"elif province_data["name"] == "凉山":province_name = province_data["name"] + "彝族自治州"else:province_name = province_data["name"] + "市"# 确诊人数province_confirm = province_data["total"]["confirm"]map_list.append((province_name, province_confirm))
print(map_list)
# 创建地图对象
map = Map()# 添加数据
map.add("全国身份确诊人数", map_list, "四川")# 设置全局配置，指定分段的视觉映射
map.set_global_opts(title_opts=TitleOpts(title="四川省疫情地图"),visualmap_opts=VisualMapOpts(is_show=True,is_piecewise=True,pieces=[{"min": 1, "max": 9, "label": "1-9", "color": "#57fa66"},{"min": 10, "max": 99, "label": "10-99", "color": "#faf857"},{"min": 100, "max": 499, "label": "100-499", "color": "#FF9966"},{"min": 500, "max": 999, "label": "500-999", "color": "#FF6666"},{"min": 1000, "max": 9999, "label": "1000-9999", "color": "#CC3333"},{"min": 10000, "label": ">9999", "color": "#990033"}])
)# 绘图
map.render("四川疫情地图.html")

结果示例