构建地图

# 地图可视化基本使用
from pyecharts.charts import Map
from pyecharts.options import *
​
# 准备地图对象
map = Map()
# 准备数据
data = [("北京市", 99),("上海市", 199),("湖南省", 299),("台湾省", 399),("广东省", 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,  # 开启手动校准范围pieces=[{"min": 1, "max":9, "label": "1-9", "color": "#CCCFFFF"},{"min": 10, "max":99, "label": "10-99", "color": "#FF6666"},{"min": 100, "max":500, "label": "100-500", "color": "#990033"}  # 颜色代码在ab173网站查看])
)
map.render()
​
# 国内疫情地图
# 读取数据文件
f = open("D:/BaiduNetdiskDownload/资料/可视化案例数据/地图数据/疫情.txt", "r", encoding="utf-8")
data = f.read()
# 关闭文件
f.close()
# 将json转换为字典
import json
data_dict = json.loads(data)
# 从字典中取出省份数据
province_data_list = data_dict["areaTree"][0]["children"]
data_list = []  # 绘图需要的数据列表
# 组装每个省份和确诊人数为元组
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))
print(data_list)
​
# 创建地图对象
map1 = Map()
map1.add("各省份确诊人数", data_list, "china")
# 设置全局选项
map1.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": "#CCCFFFF"},{"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+人", "color": "#990033"}])
)
map1.render("全国疫情地图.html")  # 控制生成文件名
​
# 省级疫情地图绘制
f1 = open("D:/BaiduNetdiskDownload/资料/可视化案例数据/地图数据/疫情.txt", "r", encoding="utf-8")
data = f1.read()
f1.close()
data_dict = json.loads(data)
Hennan_data = data_dict["areaTree"][0]["children"][3]["children"]
data_list2 = []
for city in Hennan_data:city_name = city["name"]city_confirm = city["total"]["confirm"]data_list2.append((city_name, city_confirm))
print(data_list)
map3 = Map()
map3.add("河南省疫情分布", data_list2, "河南")
map3.set_global_opts(title_opts=TitleOpts(title="河南省疫情地图"),visualmap_opts=VisualMapOpts(is_show=True,is_piecewise=True,pieces=[{"min": 1, "max":99, "label": "1-99人", "color": "#CCCFFFF"},{"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+人", "color": "#990033"}])
)
map1.render("河南省疫情地图.html")  # 控制生成文件名

构建柱状图

# 构建柱状图
from pyecharts.charts import Bar, Timeline
from pyecharts.options import *
from pyecharts.globals import ThemeType
​
bar1 = Bar()
# 添加x轴数据
bar1.add_xaxis(["中国", "美国", "英国"])
# 添加y轴数据
bar1.add_yaxis("GDP", [30, 20, 10], label_opts=LabelOpts(position="right"))  # 让数字标签在右侧
# 反转x、y轴
bar1.reversal_axis()
bar1.render("基础柱状图.html")
​
# 基础时间线柱状图绘制: 在不同的时间点显示不同的图
bar2 = Bar()
# 添加x轴数据
bar2.add_xaxis(["中国", "美国", "英国"])
# 添加y轴数据
bar2.add_yaxis("GDP", [50, 30, 20], label_opts=LabelOpts(position="right"))  # 让数字标签在右侧
# 反转x、y轴
bar2.reversal_axis()
bar2.render("基础柱状图.html")
​
bar3 = Bar()
# 添加x轴数据
bar3.add_xaxis(["中国", "美国", "英国"])
# 添加y轴数据
bar3.add_yaxis("GDP", [70, 50, 30], label_opts=LabelOpts(position="right"))  # 让数字标签在右侧
# 反转x、y轴
bar3.reversal_axis()
bar3.render("基础柱状图.html")
​
# 构建时间线对象
# 主题设置
timeline = Timeline({"theme": ThemeType.LIGHT})
# 在时间线上添加柱状图
timeline.add(bar1, "点1")
timeline.add(bar2, "点2")
timeline.add(bar3, "点3")
# 自动播放设置
timeline.add_schema(play_interval=1000,  # 时间间隔为1000msis_timeline_show=True,  # 显示时间线is_auto_play=True,  # 自动播放is_loop_play=True  # 循环播放
)
​
timeline.render("基础时间线柱状图")