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# 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 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1000ms is_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")
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