python全国城市按经纬度分布在excel中

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import pandas as pd
#元数据
dict_map= {                           
    '海门':[121.15,31.89],
     '鄂尔多斯':[109.781327,39.608266],
     '招远':[120.38,37.35],
     '舟山':[122.207216,29.985295],
     '齐齐哈尔':[123.97,47.33],
     '盐城':[120.13,33.38],
     '赤峰':[118.87,42.28],
     '青岛':[120.33,36.07],
     '乳山':[121.52,36.89],
     '金昌':[102.188043,38.520089],
     '泉州':[118.58,24.93],
     '莱西':[120.53,36.86],
     '日照':[119.46,35.42],
     '胶南':[119.97,35.88],
     '南通':[121.05,32.08],
     '拉萨':[91.11,29.97],
     '云浮':[112.02,22.93],
     '梅州':[116.1,24.55],
     '文登':[122.05,37.2],
     '上海':[121.48,31.22],
     '攀枝花':[101.718637,26.582347],
     '威海':[122.1,37.5],
     '承德':[117.93,40.97],
     '厦门':[118.1,24.46],
     '汕尾':[115.375279,22.786211],
     '潮州':[116.63,23.68],
     '丹东':[124.37,40.13],
     '太仓':[121.1,31.45],
     '曲靖':[103.79,25.51],
     '烟台':[121.39,37.52],
     '福州':[119.3,26.08],
     '瓦房店':[121.979603,39.627114],
     '即墨':[120.45,36.38],
     '抚顺':[123.97,41.97],
     '玉溪':[102.52,24.35],
     '张家口':[114.87,40.82],
     '阳泉':[113.57,37.85],
     '莱州':[119.942327,37.177017],
     '湖州':[120.1,30.86],
     '汕头':[116.69,23.39],
     '昆山':[120.95,31.39],
     '宁波':[121.56,29.86],
     '湛江':[110.359377,21.270708],
     '揭阳':[116.35,23.55],
     '荣成':[122.41,37.16],
     '连云港':[119.16,34.59],
     '葫芦岛':[120.836932,40.711052],
     '常熟':[120.74,31.64],
     '东莞':[113.75,23.04],
     '河源':[114.68,23.73],
     '淮安':[119.15,33.5],
     '泰州':[119.9,32.49],
     '南宁':[108.33,22.84],
     '营口':[122.18,40.65],
     '惠州':[114.4,23.09],
     '江阴':[120.26,31.91],
     '蓬莱':[120.75,37.8],
     '韶关':[113.62,24.84],
     '嘉峪关':[98.289152,39.77313],
     '广州':[113.23,23.16],
     '延安':[109.47,36.6],
     '太原':[112.53,37.87],
     '清远':[113.01,23.7],
     '中山':[113.38,22.52],
     '昆明':[102.73,25.04],
     '寿光':[118.73,36.86],
     '盘锦':[122.070714,41.119997],
     '长治':[113.08,36.18],
     '深圳':[114.07,22.62],
     '珠海':[113.52,22.3],
     '宿迁':[118.3,33.96],
     '咸阳':[108.72,34.36],
     '铜川':[109.11,35.09],
     '平度':[119.97,36.77],
     '佛山':[113.11,23.05],
     '海口':[110.35,20.02],
     '江门':[113.06,22.61],
     '章丘':[117.53,36.72],
     '肇庆':[112.44,23.05],
     '大连':[121.62,38.92],
     '临汾':[111.5,36.08],
     '吴江':[120.63,31.16],
     '石嘴山':[106.39,39.04],
     '沈阳':[123.38,41.8],
     '苏州':[120.62,31.32],
     '茂名':[110.88,21.68],
     '嘉兴':[120.76,30.77],
     '长春':[125.35,43.88],
     '胶州':[120.03336,36.264622],
     '银川':[106.27,38.47],
     '张家港':[120.555821,31.875428],
     '三门峡':[111.19,34.76],
     '锦州':[121.15,41.13],
     '南昌':[115.89,28.68],
     '柳州':[109.4,24.33],
     '三亚':[109.511909,18.252847],
     '自贡':[104.778442,29.33903],
     '吉林':[126.57,43.87],
     '阳江':[111.95,21.85],
     '泸州':[105.39,28.91],
     '西宁':[101.74,36.56],
     '宜宾':[104.56,29.77],
     '呼和浩特':[111.65,40.82],
     '成都':[104.06,30.67],
     '大同':[113.3,40.12],
     '镇江':[119.44,32.2],
     '桂林':[110.28,25.29],
     '张家界':[110.479191,29.117096],
     '宜兴':[119.82,31.36],
     '北海':[109.12,21.49],
     '西安':[108.95,34.27],
     '金坛':[119.56,31.74],
     '东营':[118.49,37.46],
     '牡丹江':[129.58,44.6],
     '遵义':[106.9,27.7],
     '绍兴':[120.58,30.01],
     '扬州':[119.42,32.39],
     '常州':[119.95,31.79],
     '潍坊':[119.1,36.62],
     '重庆':[106.54,29.59],
     '台州':[121.420757,28.656386],
     '南京':[118.78,32.04],
     '滨州':[118.03,37.36],
     '贵阳':[106.71,26.57],
     '无锡':[120.29,31.59],
     '本溪':[123.73,41.3],
     '克拉玛依':[84.77,45.59],
     '渭南':[109.5,34.52],
     '马鞍山':[118.48,31.56],
     '宝鸡':[107.15,34.38],
     '焦作':[113.21,35.24],
     '句容':[119.16,31.95],
     '北京':[116.46,39.92],
     '徐州':[117.2,34.26],
     '衡水':[115.72,37.72],
     '包头':[110,40.58],
     '绵阳':[104.73,31.48],
     '乌鲁木齐':[87.68,43.77],
     '枣庄':[117.57,34.86],
     '杭州':[120.19,30.26],
     '淄博':[118.05,36.78],
     '鞍山':[122.85,41.12],
     '溧阳':[119.48,31.43],
     '库尔勒':[86.06,41.68],
     '安阳':[114.35,36.1],
     '开封':[114.35,34.79],
     '济南':[117,36.65],
     '德阳':[104.37,31.13],
     '温州':[120.65,28.01],
     '九江':[115.97,29.71],
     '邯郸':[114.47,36.6],
     '临安':[119.72,30.23],
     '兰州':[103.73,36.03],
     '沧州':[116.83,38.33],
     '临沂':[118.35,35.05],
     '南充':[106.110698,30.837793],
     '天津':[117.2,39.13],
     '富阳':[119.95,30.07],
     '泰安':[117.13,36.18],
     '诸暨':[120.23,29.71],
     '郑州':[113.65,34.76],
     '哈尔滨':[126.63,45.75],
     '聊城':[115.97,36.45],
     '芜湖':[118.38,31.33],
     '唐山':[118.02,39.63],
     '平顶山':[113.29,33.75],
     '邢台':[114.48,37.05],
     '德州':[116.29,37.45],
     '济宁':[116.59,35.38],
     '荆州':[112.239741,30.335165],
     '宜昌':[111.3,30.7],
     '义乌':[120.06,29.32],
     '丽水':[119.92,28.45],
     '洛阳':[112.44,34.7],
     '秦皇岛':[119.57,39.95],
     '株洲':[113.16,27.83],
     '石家庄':[114.48,38.03],
     '莱芜':[117.67,36.19],
     '常德':[111.69,29.05],
     '保定':[115.48,38.85],
     '湘潭':[112.91,27.87],
     '金华':[119.64,29.12],
     '岳阳':[113.09,29.37],
     '长沙':[113,28.21],
     '衢州':[118.88,28.97],
     '廊坊':[116.7,39.53],
     '菏泽':[115.480656,35.23375],
     '合肥':[117.27,31.86],
     '武汉':[114.31,30.52],
     '大庆':[125.03,46.58]
 }

#经纬度四舍五入
dict_map_round={}
for (key,value) in dict_map.items():
    dict_map_round[key]=[round(value[0]),round(value[1])]

#创建datafarme
dict_test={}
for i in range(15,50):
    dict_test[i]=[0]*80

#核心  同经纬度字符串连接
for (key,value) in dict_map_round.items():
    if dict_test[value[1]][value[0]-80]==0:

        dict_test[value[1]][value[0]-80]=key
    else:
        dict_test[value[1]][value[0]-80]=dict_test[value[1]][value[0]-80]+key    

#存储，并且按纬度倒叙
frame = pd.DataFrame.from_dict(dict_test, orient='index')
frame=frame.reindex(index=frame.index[::-1])
#本地存储输出
frame.to_excel('21213.xlsx')

效果图:

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