291 lines
17 KiB
Plaintext
291 lines
17 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "888d089c-a9c8-4d2d-af74-dff1a8ccfefd",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"import json\n",
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"import time\n",
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"from typing import List\n",
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"import requests\n",
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"import pandas as pd\n",
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"\n",
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"\n",
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"class GetElevation:\n",
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"\n",
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" @classmethod\n",
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" def __SendQuery(cls, latLngString: str) -> json:\n",
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" query = ('https://api.opentopodata.org/v1/mapzen?locations={}&interpolation=bilinear'.format(latLngString))\n",
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" res = requests.get(query).json()\n",
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" if res[\"status\"] != \"OK\":\n",
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" raise Exception(res[\"error\"])\n",
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" return res\n",
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"\n",
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" def GetSingleElevation(self, latitude: float, longitude: float) -> float:\n",
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" \"\"\"\n",
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" 获取单个高程,输入经纬度格式为数值类型,返回值为高程float类型\n",
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" :param latitude: 纬度\n",
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" :param longitude: 经度\n",
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" :return: 高程\n",
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" \"\"\"\n",
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" if latitude < -90 or latitude > 90:\n",
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" raise Exception(\"纬度的范围应在-90-90之间!请检查数据源!\")\n",
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" latLngString = str(latitude) + \",\" + str(longitude)\n",
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" res = self.__SendQuery(latLngString)\n",
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" elevation = res[\"results\"][0][\"elevation\"]\n",
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" return elevation\n",
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"\n",
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" def GetMultiElevation(self, latitude: List[float], longitude: List[float]) -> List[float]:\n",
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" \"\"\"\n",
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" 获取数组类型的高程,输入经纬度格式为经度数组和纬度数组,返回值为高程数组\n",
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" :param latitude:纬度数组\n",
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" :param longitude:经度数组\n",
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" :return:高程数组\n",
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" \"\"\"\n",
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" if len(latitude) != len(longitude):\n",
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" raise Exception(\"纬度数组和经度数组长度不一致!请检查数据源!\")\n",
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" for lat in latitude:\n",
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" if lat < -90 or lat > 90:\n",
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" raise Exception(\"纬度的范围应在-90-90之间!请检查数据源!\")\n",
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" elevationList = []\n",
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" hundredNums = len(latitude) // 100\n",
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" # 查询整百的高程\n",
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" for i in range(hundredNums):\n",
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" latLngString = \"\"\n",
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" for idx in range(100 * i, 100 * (i + 1)):\n",
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" latLngString += (str(latitude[idx]) + \",\" + str(longitude[idx]) + \"|\")\n",
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" res = self.__SendQuery(latLngString)\n",
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" for idx in range(100):\n",
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" elevationList.append(res[\"results\"][idx][\"elevation\"])\n",
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" time.sleep(1)\n",
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" # 查询剩余的不到100的高程\n",
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" latLngString = \"\"\n",
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" for i in range(hundredNums * 100, len(latitude)):\n",
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" latLngString += (str(latitude[i]) + \",\" + str(longitude[i]) + \"|\")\n",
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" res = self.__SendQuery(latLngString)\n",
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" for i in range(len(latitude) - hundredNums * 100):\n",
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" elevationList.append(res[\"results\"][i][\"elevation\"])\n",
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" return elevationList\n",
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"\n",
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" def ExportToXlsx(self, latLongDf: pd.DataFrame, elevationList: List[float], outputPath: str) -> None:\n",
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" \"\"\"\n",
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" 如果用户可以传入一个DataFrame数据,可以将返回得到的高程拼接并输出\n",
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" :param latLongDf: DataFrame数据\n",
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" :param elevationList: 高程数组\n",
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" :param outputPath: 输出路径\n",
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" :return: 无返回值\n",
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" \"\"\"\n",
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" latLongDf[\"elevation\"] = elevationList\n",
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" latLongDf.to_excel(outputPath, index=False)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "2a226b08-0c92-483e-b590-29a39dce6298",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": " plant longitude latitude\n0 万方发电厂(焦作爱依斯万方电力有限公司) 113.381649 35.255622\n1 三河发电有限责任公司 116.860260 39.953617\n2 上海上电漕泾发电有限公司 121.407593 30.765242\n3 上海吴泾发电有限责任公司 121.471140 31.065113\n4 上海吴泾第二发电有限责任公司 121.471340 31.062532",
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"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>plant</th>\n <th>longitude</th>\n <th>latitude</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>万方发电厂(焦作爱依斯万方电力有限公司)</td>\n <td>113.381649</td>\n <td>35.255622</td>\n </tr>\n <tr>\n <th>1</th>\n <td>三河发电有限责任公司</td>\n <td>116.860260</td>\n <td>39.953617</td>\n </tr>\n <tr>\n <th>2</th>\n <td>上海上电漕泾发电有限公司</td>\n <td>121.407593</td>\n <td>30.765242</td>\n </tr>\n <tr>\n <th>3</th>\n <td>上海吴泾发电有限责任公司</td>\n <td>121.471140</td>\n <td>31.065113</td>\n </tr>\n <tr>\n <th>4</th>\n <td>上海吴泾第二发电有限责任公司</td>\n <td>121.471340</td>\n <td>31.062532</td>\n </tr>\n </tbody>\n</table>\n</div>"
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"data = pd.read_excel('./lat_lon.xlsx')\n",
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"data.columns = ['plant', 'longitude', 'latitude']\n",
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"data = data.groupby('plant').mean().reset_index()\n",
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"data.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"outputs": [],
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"source": [
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"ele = GetElevation()"
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],
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"metadata": {
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"collapsed": false,
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"pycharm": {
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"name": "#%%\n"
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}
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}
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "c1671bcd-bd33-40dd-82b5-a487801045c0",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Help on method GetMultiElevation in module __main__:\n",
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"\n",
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"GetMultiElevation(latitude: List[float], longitude: List[float]) -> List[float] method of __main__.GetElevation instance\n",
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" 获取数组类型的高程,输入经纬度格式为经度数组和纬度数组,返回值为高程数组\n",
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" :param latitude:纬度数组\n",
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" :param longitude:经度数组\n",
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" :return:高程数组\n",
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"\n"
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]
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}
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],
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"source": [
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"help(ele.GetMultiElevation)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "91afb581-1994-47c4-85ca-d3ea3e13e95d",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[88.0, 27.0, 4.0, 3.0, 4.0, 2.0, 8.0, -2.0, 5.0, 7.0, 3.0, 58.0, 55.0, 775.0, 594.0, -3.0, 1273.0, 145.0, 145.0, 548.0, 21.0, 28.0, 48.0, 1117.0, 14.0, 1172.0, 387.0, 124.0, 1391.0, 1708.0, 1278.0, 440.0, 135.0, 494.0, 1143.0, 1869.0, 1656.0, 1873.0, 124.0, 361.0, 30.0, 971.0, -3.0, 80.0, 475.0, 1622.0, 292.0, 1317.0, 1385.0, 247.0, 1312.0, 1106.0, 1225.0, 1006.0, 1237.0, 1151.0, 555.0, 1024.0, 694.0, 1226.0, 1050.0, 1162.0, 285.0, 1007.0, 1207.0, 1023.0, 178.0, 861.0, 1171.0, 1069.0, 1015.0, 90.0, 1.0, 83.0, 1037.0, 1037.0, 1114.0, 1069.0, 1107.0, 1076.0, 1054.0, 1165.0, 1255.0, 14.0, 52.0, 171.0, 351.0, 49.0, -5.0, 7.0, -2.0, 152.0, 2.0, -2.0, 5.0, 51.0, 51.0, 606.0, 270.0, 1031.0, 1017.0, 595.0, 65.0, 279.0, 1089.0, 218.0, 57.0, 777.0, 9.0, 84.0, 520.0, 622.0, 574.0, 724.0, 582.0, 1010.0, 505.0, 1010.0, 1.0, 1.0, 59.0, 72.0, 10.0, 65.0, 64.0, 75.0, 57.0, 80.0, 118.0, 151.0, 250.0, 0.0, 1459.0, 1036.0, 1884.0, 286.0, 27.0, 2.0, 13.0, 6.0, 65.0, 3.0, 1331.0, 675.0, 240.0, 2007.0, 1590.0, 1532.0, 1545.0, 36.0, 6.0, 7.0, 199.0, 38.0, 76.0, 0.0, 73.0, 4.0, 1.0, 22.0, -2.0, 40.0, 2.0, 148.0, -1.0, 7.0, 22.0, 1149.0, 154.0, 27.0, 24.0, 44.0, 1130.0, 1277.0, 34.0, 154.0, 718.0, 1504.0, 1034.0, 19.0, 5.0, 172.0, 160.0, 27.0, 26.0, 26.0, 206.0, 19.0, 507.0, 75.0, 177.0, 102.0, 6.0, 30.0, 93.0, 218.0, -34.0, 67.0, 131.0, 1544.0, 708.0, 199.0, 119.0, 99.0, 14.0, 6.0, 11.0, 5.0, 9.0, 8.0, 130.0, 133.0, 180.0, 26.0, 1048.0, 73.0, 326.0, 192.0, 175.0, 185.0, 151.0, 151.0, 18.0, 308.0, 404.0, 360.0, 296.0, 208.0, 45.0, 46.0, 136.0, 573.0, 144.0, 147.0, -4.0, 86.0, 68.0, 167.0, 1479.0, 123.0, 35.0, 55.0, 1.0, 112.0, 8.0, 16.0, 20.0, 6.0, 19.0, 47.0, 528.0, 17.0, 627.0, -3.0, -1.0, 1459.0, 81.0, 91.0, 1122.0, 7.0, 1087.0, 1174.0, 81.0, 1349.0, 788.0, 451.0, 361.0, 65.0, 147.0, 25.0, 545.0, 1466.0, 264.0, 223.0, 56.0, 1327.0, 45.0, 45.0, 1052.0, 5.0, 1052.0, 180.0, 35.0, 1087.0, 1.0, 32.0, 1405.0, 699.0, 699.0, 1266.0, 35.0, 18.0, 116.0, 221.0, 186.0, 184.0, 7.0, 132.0, 1165.0, 1118.0, 1252.0, 29.0, 0.0, 7.0, 1184.0, 93.0, 91.0, 32.0, 849.0, 58.0, 7.0, 1.0, -6.0, -5.0, 39.0, 16.0, 12.0, 13.0, 9.0, 0.0, 132.0, 52.0, 7.0, 25.0, 32.0, 83.0, 1787.0, 0.0, 69.0, 24.0, 1.0, 3.0, -2.0, 1096.0, 207.0, 375.0, -8.0, 33.0, 94.0, 45.0, 83.0, 253.0, 24.0, 119.0, 118.0, 563.0, 468.0, 233.0, 26.0, 687.0, 1067.0, 46.0, 35.0, 30.0, 83.0, 562.0, 718.0, 426.0, 212.0, 853.0, 452.0, 294.0, 148.0, 123.0, 117.0, 25.0, 30.0, 17.0, 85.0, 7.0, 49.0, 89.0, 972.0, 56.0, 352.0, 185.0, 1113.0, 261.0, 1877.0, 222.0, 692.0, 1112.0, 395.0, 412.0, 395.0, 394.0, 8.0, 183.0, 6.0, 34.0, 19.0, 454.0, 1.0, 6.0, 8.0, 38.0, 4.0, 3.0, 6.0, 4.0, 4.0, 786.0, 1247.0, 1157.0, 1318.0, 1339.0, 1151.0, 1329.0, 46.0, 30.0, 9.0, 30.0, 9.0, 16.0, 1987.0, 151.0, 35.0, 8.0, 1353.0, 480.0, 539.0, 1010.0, 819.0, 1061.0, 371.0, 803.0, 717.0, 916.0, 918.0, 696.0, 998.0, 878.0, 28.0, 95.0, 88.0, 16.0, 93.0, 0.0, 177.0, 1.0, 9.0, 192.0, 5.0, -2.0, 5.0, -1.0, -1.0, 10.0, 2.0, 5.0, 79.0, 98.0, 338.0, 41.0, 46.0, 3.0, 35.0, 42.0, 2.0, 78.0, 54.0, 798.0, 63.0, 1288.0, 1066.0, -53.0, 705.0, 757.0, 903.0, 547.0, 1267.0, 1267.0, 355.0, 401.0, 916.0, 233.0, 6.0, 1151.0, 937.0, 940.0, 23.0, 1.0, 9.0, 9.0, 11.0, 5.0, 4.0, 7.0, -3.0, 5.0, 22.0, 4.0, 27.0, 23.0, 29.0, 10.0, 51.0, 3.0, 8.0, 63.0, 122.0, 67.0, 32.0, 28.0, 714.0, 4.0, 7.0, 604.0, 115.0, 31.0, 938.0, 21.0, 121.0, 314.0, 55.0, 70.0, 186.0, 61.0, 76.0, 154.0, 117.0, 395.0, 255.0, 40.0, 37.0, 5.0, -7.0, 3.0, 45.0, 2.0, 4.0, 6.0, 8.0, 73.0, -3.0, 4.0, 4.0, 11.0, 637.0, 30.0, 28.0, 31.0, 21.0, 23.0, 8.0, 34.0, 32.0, 1007.0, 954.0, 31.0, 31.0, 39.0, 10.0, 137.0, 31.0, 56.0, 110.0, 1.0, 592.0, 401.0, 48.0, 140.0, 171.0, 1414.0, 1455.0, 1707.0, 1707.0, 564.0, 992.0, 342.0, 35.0, 61.0, 9.0, 57.0, 41.0, 1442.0, 699.0, 1064.0, 191.0, 251.0, -11.0, 181.0, 215.0, 302.0, 1.0, 2.0, 1376.0, 2.0, 9.0, 798.0, 335.0, 21.0, 11.0, 1049.0, 1002.0, 21.0, 33.0, 75.0, 152.0, 38.0, 1266.0, 360.0, 1029.0, 1477.0, 901.0, 899.0, 1284.0, 862.0, 1205.0, 905.0, 489.0, 1205.0, 160.0, 98.0, 74.0, -2.0, 44.0, 103.0, 121.0, 443.0, 57.0, 93.0, 179.0, 175.0, 178.0, 828.0, 75
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]
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}
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],
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"source": [
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"multiEle = ele.GetMultiElevation(data[\"latitude\"], data[\"longitude\"])\n",
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"print(multiEle)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "555559ea-7e35-4062-a21e-e5275b8da9cd",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": "669"
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"len(multiEle)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "74fced56-47e8-43cc-b412-af40fcb3eedd",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"data['altitude'] = multiEle"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "61704866-2b97-4bd0-ac0c-f2708ef52094",
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|||
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"metadata": {
|
|||
|
"pycharm": {
|
|||
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"name": "#%%\n"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": " plant longitude latitude altitude\n0 万方发电厂(焦作爱依斯万方电力有限公司) 113.381649 35.255622 88.0\n1 三河发电有限责任公司 116.860260 39.953617 27.0\n2 上海上电漕泾发电有限公司 121.407593 30.765242 4.0\n3 上海吴泾发电有限责任公司 121.471140 31.065113 3.0\n4 上海吴泾第二发电有限责任公司 121.471340 31.062532 4.0\n.. ... ... ... ...\n664 鹤壁丰鹤发电有限责任公司 114.192184 35.850766 182.0\n665 鹤壁同力发电有限责任公司 114.191246 35.860822 145.0\n666 黄冈大别山发电有限责任公司 114.915181 31.144568 53.0\n667 黑龙江华电齐齐哈尔热电有限公司 124.063322 47.387983 147.0\n668 黔桂发电有限责任公司 106.630029 26.607537 1265.0\n\n[669 rows x 4 columns]",
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"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>plant</th>\n <th>longitude</th>\n <th>latitude</th>\n <th>altitude</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>万方发电厂(焦作爱依斯万方电力有限公司)</td>\n <td>113.381649</td>\n <td>35.255622</td>\n <td>88.0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>三河发电有限责任公司</td>\n <td>116.860260</td>\n <td>39.953617</td>\n <td>27.0</td>\n </tr>\n <tr>\n <th>2</th>\n <td>上海上电漕泾发电有限公司</td>\n <td>121.407593</td>\n <td>30.765242</td>\n <td>4.0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>上海吴泾发电有限责任公司</td>\n <td>121.471140</td>\n <td>31.065113</td>\n <td>3.0</td>\n </tr>\n <tr>\n <th>4</th>\n <td>上海吴泾第二发电有限责任公司</td>\n <td>121.471340</td>\n <td>31.062532</td>\n <td>4.0</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>664</th>\n <td>鹤壁丰鹤发电有限责任公司</td>\n <td>114.192184</td>\n <td>35.850766</td>\n <td>182.0</td>\n </tr>\n <tr>\n <th>665</th>\n <td>鹤壁同力发电有限责任公司</td>\n <td>114.191246</td>\n <td>35.860822</td>\n <td>145.0</td>\n </tr>\n <tr>\n <th>666</th>\n <td>黄冈大别山发电有限责任公司</td>\n <td>114.915181</td>\n <td>31.144568</td>\n <td>53.0</td>\n </tr>\n <tr>\n <th>667</th>\n <td>黑龙江华电齐齐哈尔热电有限公司</td>\n <td>124.063322</td>\n <td>47.387983</td>\n <td>147.0</td>\n </tr>\n <tr>\n <th>668</th>\n <td>黔桂发电有限责任公司</td>\n <td>106.630029</td>\n <td>26.607537</td>\n <td>1265.0</td>\n </tr>\n </tbody>\n</table>\n<p>669 rows × 4 columns</p>\n</div>"
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},
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"execution_count": 13,
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"metadata": {},
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{
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"cell_type": "code",
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"execution_count": 14,
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"outputs": [],
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"source": [
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"data.to_csv('./电厂机组地理信息.csv', encoding='utf-8-sig', index=False)"
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"execution_count": null,
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