我们这里使用pyecharts模块进行绘图。
pyecharts 项目包含了一系列的地理地图数据，这些数据或者已经内置，或者需要额外安装和加载，我们需要下载下面六个包。
选择自己需要的安装 pip install echarts-countries-pypkg pip install echarts-china-provinces-pypkg pip install echarts-china-cities-pypkg pip install echarts-china-counties-pypkg pip install echarts-china-misc-pypkg pip install echarts-united-kingdom-pypkg
pyecharts中Geo表达和城市关联的数据,Map表达和国家和省份关联的数据。
世界地图
from pyecharts import Map, Geo # 世界地图数据 value = [95.1, 23.2, 43.3, 66.4, 88.5] attr= ["China", "Canada", "Brazil", "Russia", "United States"] map0 = Map("世界地图示例", width=1200, height=600) map0.add("世界地图", attr, value, maptype="world", is_visualmap=True, visual_text_color='#000') map0.render(path="世界地图.html")
中国地图
from pyecharts import Map, Geo # 中国地图 province_distribution = {'河南': 45.23, '北京': 37.56, '河北': 21, '辽宁': 12, '江西': 6, '上海': 20, '安徽': 10, '江苏': 16, '湖南': 9, '浙江': 13, '海南': 2, '广东': 22, '湖北': 8, '黑龙江': 11, '澳门': 1, '陕西': 11, '四川': 7, '内蒙古': 3, '重庆': 3, '云南': 6, '贵州': 2, '吉林': 3, '山西': 12, '山东': 11, '福建': 4, '青海': 1, '舵主科技，质量保证': 1, '天津': 1, '其他': 1} provice = list(province_distribution.keys()) values = list(province_distribution.values()) map = Map("中国地图",'中国地图', width=1200, height=600) map.add("", provice, values, visual_range=[0, 50], maptype='china', is_visualmap=True, visual_text_color='#000') map.show_config() map.render(path="中国地图.html")
省份地图
from pyecharts import Map, Geo # 城市 -- 指定省的城市 xx市 city = ['郑州市', '安阳市', '洛阳市', '濮阳市', '南阳市', '开封市', '商丘市', '信阳市', '新乡市'] values2 = [1.07, 3.85, 6.38, 8.21, 2.53, 4.37, 9.38, 4.29, 6.1] map2 = Map("河南地图",'河南', width=1200, height=600) map2.add('河南', city, values2, visual_range=[1, 10], maptype='河南', is_visualmap=True, visual_text_color='#000') map2.show_config() map2.render(path="河南地图.html")
市区地图
from pyecharts import Map, Geo # 区县 -- 具体城市内的区县 xx县 quxian = ['夏邑县', '民权县', '梁园区', '睢阳区', '柘城县', '宁陵县'] values3 = [3, 5, 7, 8, 2, 4] map3 = Map("商丘地图",'商丘', width=1200, height=600) map3.add("商丘", quxian, values3, visual_range=[1, 10], maptype='商丘', is_visualmap=True, visual_text_color='#000') map3.render(path="商丘地图.html")
热力图
from pyecharts import Map, Geo data = [ ("海门", 9), ("鄂尔多斯", 12), ("招远", 12), ("舟山", 12), ("齐齐哈尔", 14), ("盐城", 15), ("赤峰", 16), ("青岛", 18), ("乳山", 18), ("金昌", 19), ("泉州", 21), ("莱西", 21), ("日照", 21), ("胶南", 22), ("南通", 23), ("拉萨", 24), ("云浮", 24), ("梅州", 25)] attr, value = Geo.cast(data) geo = Geo("全国主要城市空气质量热力图", "data from pm2.5", title_color="#fff", title_pos="center", width=1200, height=600, background_color='#404a59') geo.add("空气质量热力图", attr, value, visual_range=[0, 25], type='heatmap', visual_text_color="#fff", symbol_size=15, is_visualmap=True, is_roam=False) geo.show_config() geo.render(path="空气质量热力图.html")
from pyecharts import Map, Geo indexs = ['上海', '北京', '合肥', '哈尔滨', '广州', '成都', '无锡', '杭州', '武汉', '深圳', '西安', '郑州', '重庆', '长沙'] values = [4.07, 1.85, 4.38, 2.21, 3.53, 4.37, 1.38, 4.29, 4.1, 1.31, 3.92, 4.47, 2.40, 3.60] geo = Geo("全国主要城市空气质量评分", "data from pm2.5", title_color="#fff", title_pos="center", width=1200, height=600, background_color='#404a59') # type="effectScatter", is_random=True, effect_scale=5 使点具有发散性 geo.add("空气质量评分", indexs, values, type="effectScatter", is_random=True, effect_scale=5, visual_range=[0, 5], visual_text_color="#fff", symbol_size=15, is_visualmap=True, is_roam=False) geo.show_config() geo.render(path="空气质量评分.html")
from pyecharts import Map, Geo data = [ ("海门", 9), ("鄂尔多斯", 12), ("招远", 12), ("舟山", 12), ("齐齐哈尔", 14), ("盐城", 15), ("赤峰", 16), ("青岛", 18), ("乳山", 18), ("金昌", 19), ("泉州", 21), ("莱西", 21), ("日照", 21), ("胶南", 22), ("南通", 23), ("拉萨", 24), ("云浮", 24), ("梅州", 25)] attr, value = Geo.cast(data) geo = Geo("全国主要城市空气质量热力图", "data from pm2.5", title_color="#fff", title_pos="center", width=1200, height=600, background_color='#404a59') geo.add("空气质量热力图", attr, value, visual_range=[0, 25], type='scatter', visual_text_color="#fff", symbol_size=15, is_visualmap=True, is_roam=False) geo.show_config() geo.render(path="质量热力图.html")
示例：获取冠状病毒感染数据并可视化
import urllib import urllib.request import json import os import prettytable as pt from pyecharts import Map, Geo class Searchdata(object): def __init__(self,url): self.url = url self.china_list = {} self.china_data = {} self.province_list = {} self.province_data = {} def get_data(self): try: data = urllib.request.urlopen(self.url) data = json.loads(data.read()) self.save(data) return data except: print("请求数据出错！") def is_exist(self): for i in os.listdir(os.getcwd()): if i == "data.txt": return 1 return 0 def save(self,data): if self.is_exist() == 0: with open("data.txt",'w') as fp: fp.write(str(data)) def get_china(self,data): data = data['data'] self.china_data['total'] = data['gntotal'] self.china_data['deathNum'] = data['deathtotal'] self.china_data['susNum'] = data['sustotal'] self.china_data['cureNum'] = data['curetotal'] for i in data['list']: dic ={} dic['total'] = i['value'] dic['deathNum'] = i['deathNum'] dic['susNum'] = i['susNum'] dic['cureNum'] = i['cureNum'] self.china_list[i['name']] = dic def get_province(self,data): data = data['data'] for i in data['list']: if i['name'] == '湖北': self.province_data['total'] = i['value'] self.province_data['deathNum'] = i['deathNum'] self.province_data['susNum'] = i['susNum'] self.province_data['cureNum'] = i['cureNum'] for temp in i['city']: dic = {} dic['total'] = temp['conNum'] dic['deathNum'] = temp['deathNum'] dic['susNum'] = temp['susNum'] dic['cureNum'] = temp['cureNum'] self.province_list[temp['name']] = dic return def get_sheet1(self): self.tb = pt.PrettyTable() self.tb.field_names = ["省份", "总数", "死亡", "疑似", "治愈"] for k, v in self.china_list.items(): self.tb.add_row([k, v['total'], v['deathNum'], v['susNum'],v['cureNum']]) self.tb.add_row(['合计', self.china_data['total'],self.china_data['deathNum'], self.china_data['susNum'], self.china_data['cureNum']]) print(self.tb) def get_sheet2(self): self.tb = pt.PrettyTable() self.tb.field_names = ["地级市", "总数", "死亡", "疑似", "治愈"] for k, v in self.province_list.items(): self.tb.add_row([k, v['total'], v['deathNum'], v['susNum'], v['cureNum']]) self.tb.add_row(['合计', self.province_data['total'], self.province_data['deathNum'], self.province_data['susNum'], self.province_data['cureNum']]) print(self.tb) def get_graph1(self): provice = list(self.china_list.keys()) values = [] for k, v in self.china_list.items(): values.append(v['total']) # 中国地图 map = Map("中国地图", '中国地图', width=1200, height=600) map.add("", provice, values, visual_range=[0, 20000], maptype='china', is_visualmap=True, visual_text_color='#000') map.show_config() map.render(path="地图.html") def get_graph2(self): city = list(self.province_list.keys()) new_city = [] for str in city: if len(str) == 2: str = str+"市" new_city.append(str) elif len(str) == 3: str = "恩施土家族苗族自治州" new_city.append(str) else: new_city.append(str) values = [] for k, v in self.province_list.items(): values.append(v['total']) map2 = Map("湖北地图", '湖北', width=1200, height=600) map2.add('', new_city, values, visual_range=[0,10000], maptype='湖北', is_visualmap=True, visual_text_color='#000') map2.show_config() map2.render(path="湖北地图.html") Searchtool =Searchdata('http://43.250.238.179:9090/showData') data = Searchtool.get_data() Searchtool.get_province(data) Searchtool.get_sheet2() Searchtool.get_graph2()
refer：
http://pyecharts.herokuapp.com/