var data = [{name: '海门', value: 9},{name: '鄂尔多斯', value: 12},{name: '招远', value: 12},{name: '舟山', value: 12},{name: '齐齐哈尔', value: 14},{name: '盐城', value: 15},{name: '赤峰', value: 16},{name: '青岛', value: 18},{name: '乳山', value: 18},{name: '金昌', value: 19},{name: '泉州', value: 21},{name: '莱西', value: 21},{name: '日照', value: 21},{name: '胶南', value: 22},{name: '南通', value: 23},{name: '拉萨', value: 24},{name: '云浮', value: 24},{name: '梅州', value: 25},{name: '文登', value: 25},{name: '上海', value: 25},{name: '攀枝花', value: 25},{name: '威海', value: 25},{name: '承德', value: 25},{name: '厦门', value: 26},{name: '汕尾', value: 26},{name: '潮州', value: 26},{name: '丹东', value: 27},{name: '太仓', value: 27},{name: '曲靖', value: 27},{name: '烟台', value: 28},{name: '福州', value: 29},{name: '瓦房店', value: 30},{name: '即墨', value: 30},{name: '抚顺', value: 31},{name: '玉溪', value: 31},{name: '张家口', value: 31},{name: '阳泉', value: 31},{name: '莱州', value: 32},{name: '湖州', value: 32},{name: '汕头', value: 32},{name: '昆山', value: 33},{name: '宁波', value: 33},{name: '湛江', value: 33},{name: '揭阳', value: 34},{name: '荣成', value: 34},{name: '连云港', value: 35},{name: '葫芦岛', value: 35},{name: '常熟', value: 36},{name: '东莞', value: 36},{name: '河源', value: 36},{name: '淮安', value: 36},{name: '泰州', value: 36},{name: '南宁', value: 37},{name: '营口', value: 37},{name: '惠州', value: 37},{name: '江阴', value: 37},{name: '蓬莱', value: 37},{name: '韶关', value: 38},{name: '嘉峪关', value: 38},{name: '广州', value: 38},{name: '延安', value: 38},{name: '太原', value: 39},{name: '清远', value: 39},{name: '中山', value: 39},{name: '昆明', value: 39},{name: '寿光', value: 40},{name: '盘锦', value: 40},{name: '长治', value: 41},{name: '深圳', value: 41},{name: '珠海', value: 42},{name: '宿迁', value: 43},{name: '咸阳', value: 43},{name: '铜川', value: 44},{name: '平度', value: 44},{name: '佛山', value: 44},{name: '海口', value: 44},{name: '江门', value: 45},{name: '章丘', value: 45},{name: '肇庆', value: 46},{name: '大连', value: 47},{name: '临汾', value: 47},{name: '吴江', value: 47},{name: '石嘴山', value: 49},{name: '沈阳', value: 50},{name: '苏州', value: 50},{name: '茂名', value: 50},{name: '嘉兴', value: 51},{name: '长春', value: 51},{name: '胶州', value: 52},{name: '银川', value: 52},{name: '张家港', value: 52},{name: '三门峡', value: 53},{name: '锦州', value: 54},{name: '南昌', value: 54},{name: '柳州', value: 54},{name: '三亚', value: 54},{name: '自贡', value: 56},{name: '吉林', value: 56},{name: '阳江', value: 57},{name: '泸州', value: 57},{name: '西宁', value: 57},{name: '宜宾', value: 58},{name: '呼和浩特', value: 58},{name: '成都', value: 58},{name: '大同', value: 58},{name: '镇江', value: 59},{name: '桂林', value: 59},{name: '张家界', value: 59},{name: '宜兴', value: 59},{name: '北海', value: 60},{name: '西安', value: 61},{name: '金坛', value: 62},{name: '东营', value: 62},{name: '牡丹江', value: 63},{name: '遵义', value: 63},{name: '绍兴', value: 63},{name: '扬州', value: 64},{name: '常州', value: 64},{name: '潍坊', value: 65},{name: '重庆', value: 66},{name: '台州', value: 67},{name: '南京', value: 67},{name: '滨州', value: 70},{name: '贵阳', value: 71},{name: '无锡', value: 71},{name: '本溪', value: 71},{name: '克拉玛依', value: 72},{name: '渭南', value: 72},{name: '马鞍山', value: 72},{name: '宝鸡', value: 72},{name: '焦作', value: 75},{name: '句容', value: 75},{name: '北京', value: 79},{name: '徐州', value: 79},{name: '衡水', value: 80},{name: '包头', value: 80},{name: '绵阳', value: 80},{name: '乌鲁木齐', value: 84},{name: '枣庄', value: 84},{name: '杭州', value: 84},{name: '淄博', value: 85},{name: '鞍山', value: 86},{name: '溧阳', value: 86},{name: '库尔勒', value: 86},{name: '安阳', value: 90},{name: '开封', value: 90},{name: '济南', value: 92},{name: '德阳', value: 93},{name: '温州', value: 95},{name: '九江', value: 96},{name: '邯郸', value: 98},{name: '临安', value: 99},{name: '兰州', value: 99},{name: '沧州', value: 100},{name: '临沂', value: 103},{name: '南充', value: 104},{name: '天津', value: 105},{name: '富阳', value: 106},{name: '泰安', value: 112},{name: '诸暨', value: 112},{name: '郑州', value: 113},{name: '哈尔滨', value: 114},{name: '聊城', value: 116},{name: '芜湖', value: 117},{name: '唐山', value: 119},{name: '平顶山', value: 119},{name: '邢台', value: 119},{name: '德州', value: 120},{name: '济宁', value: 120},{name: '荆州', value: 127},{name: '宜昌', value: 130},{name: '义乌', value: 132},{name: '丽水', value: 133},{name: '洛阳', value: 134},{name: '秦皇岛', value: 136},{name: '株洲', value: 143},{name: '石家庄', value: 147},{name: '莱芜', value: 148},{name: '常德', value: 152},{name: '保定', value: 153},{name: '湘潭', value: 154},{name: '金华', value: 157},{name: '岳阳', value: 169},{name: '长沙', value: 175},{name: '衢州', value: 177},{name: '廊坊', value: 193},{name: '菏泽', value: 194},{name: '合肥', value: 229},{name: '武汉', value: 273},{name: '大庆', value: 279}
];
var geoCoordMap = {'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]
};var convertData = function (data) {var res = [];for (var i = 0; i < data.length; i++) {var geoCoord = geoCoordMap[data[i].name];if (geoCoord) {res.push({name: data[i].name,value: geoCoord.concat(data[i].value)});}}return res;
};
console.log(convertData(data))

打印:

(190) [{…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, …]

  1. [0 … 99]

    1. 0:

      1. name:"海门"
      2. value:Array(3)
        1. 0:121.15
        2. 1:31.89
        3. 2:9
        4. length:3
        5. __proto__:Array(0)
      3. __proto__:Object
    2. 1:
      1. name:"鄂尔多斯"
      2. value:Array(3)
        1. 0:109.781327
        2. 1:39.608266
        3. 2:12
        4. length:3
        5. __proto__:Array(0)
      3. __proto__:Object
    3. 2:
      1. name:"招远"
      2. value:Array(3)
        1. 0:120.38
        2. 1:37.35
        3. 2:12
        4. length:3
        5. __proto__:Array(0)
      3. __proto__:Object
    4. 3:{name: "舟山", value: Array(3)}
    5. 4:{name: "齐齐哈尔", value: Array(3)}
    6. 5:{name: "盐城", value: Array(3)}
    7. 6:{name: "赤峰", value: Array(3)}
    8. 7:{name: "青岛", value: Array(3)}
    9. 8:{name: "乳山", value: Array(3)}
    10. 9:{name: "金昌", value: Array(3)}
    11. 10:{name: "泉州", value: Array(3)}
    12. 11:{name: "莱西", value: Array(3)}
    13. 12:{name: "日照", value: Array(3)}
    14. 13:{name: "胶南", value: Array(3)}
    15. 14:{name: "南通", value: Array(3)}
    16. 15:{name: "拉萨", value: Array(3)}
    17. 16:{name: "云浮", value: Array(3)}
    18. 17:{name: "梅州", value: Array(3)}
    19. 18:{name: "文登", value: Array(3)}
    20. 19:{name: "上海", value: Array(3)}

转载于:https://www.cnblogs.com/mmzuo-798/p/9367574.html

数据合并处理concat相关推荐

  1. 【Python】图解Pandas数据合并:concat、join、append

    公众号:尤而小屋 作者:Peter 编辑:Peter 图解pandas数据合并:concat+join+append 在上一篇文章中介绍过pandas中最为常用的一个合并函数merge的使用,本文中介 ...

  2. pandas数据合并:concat、join、append

    公众号:尤而小屋 作者:Peter 编辑:Peter 大家好,我是Peter~ 图解pandas数据合并:concat+join+append 在上一篇文章中介绍过pandas中最为常用的一个合并函数 ...

  3. 数据合并之concat、append、merge和join

    Pandas 是一套用于 Python 的快速.高效的数据分析工具.它可以用于数据挖掘和数据分析,同时也提供数据清洗功能.本文将详细讲解数据合并与连接,目录如下: ① concat 一.定义 conc ...

  4. 【Python数据分析】之数据合并的concat函数与merge函数

    文章目录 系列文章 一.concat函数 1)横向堆叠与外连接 横向堆叠合并df1和df2,采用==外连接==的方式 2) 纵向堆叠与内链接 二.merge()函数 1)根据行索引合并数据 2)合并重 ...

  5. Python之数据合并——【concat()函数、merge()函数、join()方法、combine_first()方法】

    文章目录 轴向堆叠数据--concat()函数 横向堆叠与外连接 纵向堆叠与内连接 主键合并数据--merge()函数 内连接方式 外连接方式 左连接方式 右连接方式 其他 根据行索引合并数据--jo ...

  6. Pandas8_高级处理-数据离散化和数据合并

    import numpy as np import pandas as pd 数据离散化 什么是数据离散化? 连续属性的离散化就是在连续属性的值域上,将值域划分为若干个离散的区间,最后用不同的符号或整 ...

  7. PANDAS 数据合并与重塑(concat篇) 原创 2016年09月13日 19:26:30 47784 pandas作者Wes McKinney 在【PYTHON FOR DATA ANALYS

    PANDAS 数据合并与重塑(concat篇) 原创 2016年09月13日 19:26:30 标签: 47784 编辑 删除 pandas作者Wes McKinney 在[PYTHON FOR DA ...

  8. 04_pandas字符串函数;数据合并concat、merge;分组groupby;Reshaping;Pivot tables;时间处理(date_range、tz_localize等)

    字符串函数,Series的lower()函数 Series在str属性中提供了一组字符串处理方法,可以方便地对数组中的每个元素进行操作,如下面的代码片段所示.请注意,str中的模式匹配通常默认使用正则 ...

  9. python concat去除重复值语句_Python数据处理从零开始----第二章(pandas)④数据合并和处理重复值...

    目录 第二章(pandas) Python数据处理从零开始----第二章(pandas)④数据合并和处理重复值 ============================================ ...

最新文章

  1. daily scrum 12.1
  2. 云原生推动全云开发与实践
  3. 【干货】迅雷产品经理:浅析用户成长体系
  4. 手把手教你webpack3(3)入口(多入口)entry
  5. git 创建webpack项目_Webpack入门:从安装到配置
  6. MFC子线程访问主线程对话框程序的控件对象
  7. 第 20 次 CSP认证 202009-3 点亮数字人生
  8. 谷歌返华或联手腾讯;华为否认5G专利收费;滴滴外挂让车费翻倍 | 极客头条...
  9. 系统类配置(一)【安装windows10与ubuntu16.04双系统-附镜像资源】
  10. 一家胡三家的人工智能来了
  11. 堆排序和优先队列的python实现
  12. Gallery3d 学习笔记(14)
  13. Linux自动启动ssh方法
  14. 怎么使用pyd 文件
  15. IdentityHashMap 源代码
  16. Shell小技巧(一百零五)脚本中的空格小结
  17. 看了就会的浏览器帧原理
  18. Wopus问答第一期
  19. 常用数据集预处理(dota)
  20. 程序员的蜕变之旅-健身

热门文章

  1. Bootstrap-selectpicker与v-if一起使用select不显示
  2. Word2007转PDF
  3. CRC校验工具 校验码自动生成软件支持十几种CRC计算方式
  4. 有利网荣获“2016年度科技金融风控品牌”奖
  5. live555的使用
  6. UE4实时抠图,直播,绿幕
  7. 中国鲜花电商行业及用户研究报告
  8. 透传模块赋能物联网时代
  9. 计算机网络读后感500字,骆驼祥子读后感500字
  10. -------如何消除打印机的字迹(字迹打印机消除即)--------