{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "",
   "id": "1581ab9b41bf8ced"
  },
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-05-07T09:59:05.954334Z",
     "start_time": "2025-05-07T09:58:58.593181Z"
    }
   },
   "source": [
    "import requests\n",
    "import pandas as pd\n",
    "from difflib import SequenceMatcher\n",
    "\n",
    "\n",
    "# 相似度计算函数\n",
    "def similarity(a, b):\n",
    "    return SequenceMatcher(None, a, b).ratio()\n",
    "\n",
    "\n",
    "# 地址是否匹配\n",
    "def is_address_match(detail, addr):\n",
    "    if len(detail) < 4:\n",
    "        return detail in addr\n",
    "    else:\n",
    "        return similarity(detail, addr) >= 0.6\n",
    "\n",
    "\n",
    "# 店名是否匹配\n",
    "def is_name_match(store_name, poi_name):\n",
    "    if len(store_name) < 4:\n",
    "        return store_name in poi_name\n",
    "    else:\n",
    "        return similarity(store_name, poi_name) >= 0.6\n",
    "\n",
    "\n",
    "# 读取 Excel 数据\n",
    "df = pd.read_excel(r\"C:\\Users\\Administrator.DESKTOP-7IC2USJ\\Desktop\\地址.xlsx\", sheet_name=\"Sheet2\")\n",
    "url = \"https://restapi.amap.com/v5/place/text\"\n",
    "all_data = []\n",
    "\n",
    "for index, row in df.iterrows():\n",
    "\n",
    "    # 处理详细地址\n",
    "    cleaned = row['地址'].replace(row['市'], '').strip()\n",
    "    cleaned = cleaned.replace(row['区/县'], '').strip()\n",
    "    cleaned = ' '.join(cleaned.split())\n",
    "    row[\"详细地址\"] = cleaned\n",
    "\n",
    "    # 特殊处理直辖市\n",
    "    if row[\"省\"] in [\"天津市\", \"上海市\", \"重庆市\", \"北京市\"] and row[\"市\"] == \"市辖区\":\n",
    "        row[\"市\"] = row[\"省\"]\n",
    "\n",
    "    key_words = row[\"门店店名\"]\n",
    "    region = row[\"市\"]\n",
    "    detail_address = row[\"详细地址\"]\n",
    "\n",
    "    def search_amap(keywords, region, page_num):\n",
    "        params = {\n",
    "            \"key\": \"f61b09d406ac49f8a034bf585e60c442\",\n",
    "            \"keywords\": keywords,\n",
    "            \"types\": \"010400|010500|010800|020000|030000\",\n",
    "            \"region\": region,\n",
    "            \"city_limit\": \"true\",\n",
    "            \"page_size\": \"20\",\n",
    "            \"page_num\": str(page_num)\n",
    "        }\n",
    "        res = requests.get(url=url, params=params)\n",
    "        return res.json().get(\"pois\", [])\n",
    "\n",
    "    # 初始搜索关键词\n",
    "    current_keywords = key_words\n",
    "    max_pages = 3  # 最多请求3页\n",
    "    found = False\n",
    "\n",
    "    for page_num in range(1, max_pages + 1):\n",
    "        pois = search_amap(current_keywords, region, page_num)\n",
    "\n",
    "        for poi in pois:\n",
    "            addr = poi.get(\"address\", \"\")\n",
    "            name = poi.get(\"name\", \"\")\n",
    "\n",
    "            if is_address_match(detail_address, addr) and is_name_match(key_words, name):\n",
    "                poi.update({\"搜索门店\": row[\"门店店名\"]})\n",
    "                all_data.append(poi)\n",
    "                found = True\n",
    "                break  # 找到就停止当前页面遍历\n",
    "\n",
    "        if found:\n",
    "            break  # 停止分页循环\n",
    "\n",
    "    if not found:\n",
    "        # 如果仍未找到，尝试使用 更详细的地址 + 店名 重新搜索多个页面\n",
    "        current_keywords = detail_address + \" \" + key_words\n",
    "        for page_num in range(1, max_pages + 1):\n",
    "            pois = search_amap(current_keywords, region, page_num)\n",
    "\n",
    "            for poi in pois:\n",
    "                addr = poi.get(\"address\", \"\")\n",
    "                name = poi.get(\"name\", \"\")\n",
    "\n",
    "                if is_address_match(detail_address, addr) and is_name_match(key_words, name):\n",
    "                    poi.update({\"搜索门店\": row[\"门店店名\"]})\n",
    "                    all_data.append(poi)\n",
    "                    found = True\n",
    "                    break  # 找到就停止当前页面遍历\n",
    "\n",
    "            if found:\n",
    "                break  # 停止分页循环\n",
    "\n",
    "    if not found:\n",
    "        print(f\"{row['门店店名']} 没有找到符合要求的地址或店名\")\n",
    "\n",
    "# 保存结果到 Excel\n",
    "df2 = pd.DataFrame(all_data)\n",
    "df2.to_excel(r\"C:\\Users\\Administrator.DESKTOP-7IC2USJ\\Desktop\\返回结果地址.xlsx\", index=False)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "上海车杰汽车服务 没有找到符合要求的地址或店名\n",
      "SunRise Garage汽美工作室 没有找到符合要求的地址或店名\n",
      "上海 11区洗美工作室 没有找到符合要求的地址或店名\n",
      "上海龙腾汽车用品批发 没有找到符合要求的地址或店名\n",
      "膜幻视佳量子膜上海中心店 没有找到符合要求的地址或店名\n",
      "科奇装具 没有找到符合要求的地址或店名\n",
      "博士汽车音响改装 没有找到符合要求的地址或店名\n"
     ]
    },
    {
     "ename": "PermissionError",
     "evalue": "[Errno 13] Permission denied: 'C:\\\\Users\\\\Administrator.DESKTOP-7IC2USJ\\\\Desktop\\\\返回结果地址.xlsx'",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mPermissionError\u001B[0m                           Traceback (most recent call last)",
      "Cell \u001B[1;32mIn[14], line 106\u001B[0m\n\u001B[0;32m    104\u001B[0m \u001B[38;5;66;03m# 保存结果到 Excel\u001B[39;00m\n\u001B[0;32m    105\u001B[0m df2 \u001B[38;5;241m=\u001B[39m pd\u001B[38;5;241m.\u001B[39mDataFrame(all_data)\n\u001B[1;32m--> 106\u001B[0m df2\u001B[38;5;241m.\u001B[39mto_excel(\u001B[38;5;124mr\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mC:\u001B[39m\u001B[38;5;124m\\\u001B[39m\u001B[38;5;124mUsers\u001B[39m\u001B[38;5;124m\\\u001B[39m\u001B[38;5;124mAdministrator.DESKTOP-7IC2USJ\u001B[39m\u001B[38;5;124m\\\u001B[39m\u001B[38;5;124mDesktop\u001B[39m\u001B[38;5;124m\\\u001B[39m\u001B[38;5;124m返回结果地址.xlsx\u001B[39m\u001B[38;5;124m\"\u001B[39m, index\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mFalse\u001B[39;00m)\n",
      "File \u001B[1;32mD:\\ProgramTools\\Anaconda\\Lib\\site-packages\\pandas\\util\\_decorators.py:333\u001B[0m, in \u001B[0;36mdeprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper\u001B[1;34m(*args, **kwargs)\u001B[0m\n\u001B[0;32m    327\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mlen\u001B[39m(args) \u001B[38;5;241m>\u001B[39m num_allow_args:\n\u001B[0;32m    328\u001B[0m     warnings\u001B[38;5;241m.\u001B[39mwarn(\n\u001B[0;32m    329\u001B[0m         msg\u001B[38;5;241m.\u001B[39mformat(arguments\u001B[38;5;241m=\u001B[39m_format_argument_list(allow_args)),\n\u001B[0;32m    330\u001B[0m         \u001B[38;5;167;01mFutureWarning\u001B[39;00m,\n\u001B[0;32m    331\u001B[0m         stacklevel\u001B[38;5;241m=\u001B[39mfind_stack_level(),\n\u001B[0;32m    332\u001B[0m     )\n\u001B[1;32m--> 333\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m func(\u001B[38;5;241m*\u001B[39margs, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkwargs)\n",
      "File \u001B[1;32mD:\\ProgramTools\\Anaconda\\Lib\\site-packages\\pandas\\core\\generic.py:2417\u001B[0m, in \u001B[0;36mNDFrame.to_excel\u001B[1;34m(self, excel_writer, sheet_name, na_rep, float_format, columns, header, index, index_label, startrow, startcol, engine, merge_cells, inf_rep, freeze_panes, storage_options, engine_kwargs)\u001B[0m\n\u001B[0;32m   2404\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01mpandas\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mio\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mformats\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mexcel\u001B[39;00m \u001B[38;5;28;01mimport\u001B[39;00m ExcelFormatter\n\u001B[0;32m   2406\u001B[0m formatter \u001B[38;5;241m=\u001B[39m ExcelFormatter(\n\u001B[0;32m   2407\u001B[0m     df,\n\u001B[0;32m   2408\u001B[0m     na_rep\u001B[38;5;241m=\u001B[39mna_rep,\n\u001B[1;32m   (...)\u001B[0m\n\u001B[0;32m   2415\u001B[0m     inf_rep\u001B[38;5;241m=\u001B[39minf_rep,\n\u001B[0;32m   2416\u001B[0m )\n\u001B[1;32m-> 2417\u001B[0m formatter\u001B[38;5;241m.\u001B[39mwrite(\n\u001B[0;32m   2418\u001B[0m     excel_writer,\n\u001B[0;32m   2419\u001B[0m     sheet_name\u001B[38;5;241m=\u001B[39msheet_name,\n\u001B[0;32m   2420\u001B[0m     startrow\u001B[38;5;241m=\u001B[39mstartrow,\n\u001B[0;32m   2421\u001B[0m     startcol\u001B[38;5;241m=\u001B[39mstartcol,\n\u001B[0;32m   2422\u001B[0m     freeze_panes\u001B[38;5;241m=\u001B[39mfreeze_panes,\n\u001B[0;32m   2423\u001B[0m     engine\u001B[38;5;241m=\u001B[39mengine,\n\u001B[0;32m   2424\u001B[0m     storage_options\u001B[38;5;241m=\u001B[39mstorage_options,\n\u001B[0;32m   2425\u001B[0m     engine_kwargs\u001B[38;5;241m=\u001B[39mengine_kwargs,\n\u001B[0;32m   2426\u001B[0m )\n",
      "File \u001B[1;32mD:\\ProgramTools\\Anaconda\\Lib\\site-packages\\pandas\\io\\formats\\excel.py:943\u001B[0m, in \u001B[0;36mExcelFormatter.write\u001B[1;34m(self, writer, sheet_name, startrow, startcol, freeze_panes, engine, storage_options, engine_kwargs)\u001B[0m\n\u001B[0;32m    941\u001B[0m     need_save \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mFalse\u001B[39;00m\n\u001B[0;32m    942\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[1;32m--> 943\u001B[0m     writer \u001B[38;5;241m=\u001B[39m ExcelWriter(\n\u001B[0;32m    944\u001B[0m         writer,\n\u001B[0;32m    945\u001B[0m         engine\u001B[38;5;241m=\u001B[39mengine,\n\u001B[0;32m    946\u001B[0m         storage_options\u001B[38;5;241m=\u001B[39mstorage_options,\n\u001B[0;32m    947\u001B[0m         engine_kwargs\u001B[38;5;241m=\u001B[39mengine_kwargs,\n\u001B[0;32m    948\u001B[0m     )\n\u001B[0;32m    949\u001B[0m     need_save \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mTrue\u001B[39;00m\n\u001B[0;32m    951\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n",
      "File \u001B[1;32mD:\\ProgramTools\\Anaconda\\Lib\\site-packages\\pandas\\io\\excel\\_xlsxwriter.py:204\u001B[0m, in \u001B[0;36mXlsxWriter.__init__\u001B[1;34m(self, path, engine, date_format, datetime_format, mode, storage_options, if_sheet_exists, engine_kwargs, **kwargs)\u001B[0m\n\u001B[0;32m    201\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m mode \u001B[38;5;241m==\u001B[39m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124ma\u001B[39m\u001B[38;5;124m\"\u001B[39m:\n\u001B[0;32m    202\u001B[0m     \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mAppend mode is not supported with xlsxwriter!\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n\u001B[1;32m--> 204\u001B[0m \u001B[38;5;28msuper\u001B[39m()\u001B[38;5;241m.\u001B[39m\u001B[38;5;21m__init__\u001B[39m(\n\u001B[0;32m    205\u001B[0m     path,\n\u001B[0;32m    206\u001B[0m     engine\u001B[38;5;241m=\u001B[39mengine,\n\u001B[0;32m    207\u001B[0m     date_format\u001B[38;5;241m=\u001B[39mdate_format,\n\u001B[0;32m    208\u001B[0m     datetime_format\u001B[38;5;241m=\u001B[39mdatetime_format,\n\u001B[0;32m    209\u001B[0m     mode\u001B[38;5;241m=\u001B[39mmode,\n\u001B[0;32m    210\u001B[0m     storage_options\u001B[38;5;241m=\u001B[39mstorage_options,\n\u001B[0;32m    211\u001B[0m     if_sheet_exists\u001B[38;5;241m=\u001B[39mif_sheet_exists,\n\u001B[0;32m    212\u001B[0m     engine_kwargs\u001B[38;5;241m=\u001B[39mengine_kwargs,\n\u001B[0;32m    213\u001B[0m )\n\u001B[0;32m    215\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[0;32m    216\u001B[0m     \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_book \u001B[38;5;241m=\u001B[39m Workbook(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_handles\u001B[38;5;241m.\u001B[39mhandle, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mengine_kwargs)\n",
      "File \u001B[1;32mD:\\ProgramTools\\Anaconda\\Lib\\site-packages\\pandas\\io\\excel\\_base.py:1246\u001B[0m, in \u001B[0;36mExcelWriter.__init__\u001B[1;34m(self, path, engine, date_format, datetime_format, mode, storage_options, if_sheet_exists, engine_kwargs)\u001B[0m\n\u001B[0;32m   1242\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_handles \u001B[38;5;241m=\u001B[39m IOHandles(\n\u001B[0;32m   1243\u001B[0m     cast(IO[\u001B[38;5;28mbytes\u001B[39m], path), compression\u001B[38;5;241m=\u001B[39m{\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mcompression\u001B[39m\u001B[38;5;124m\"\u001B[39m: \u001B[38;5;28;01mNone\u001B[39;00m}\n\u001B[0;32m   1244\u001B[0m )\n\u001B[0;32m   1245\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(path, ExcelWriter):\n\u001B[1;32m-> 1246\u001B[0m     \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_handles \u001B[38;5;241m=\u001B[39m get_handle(\n\u001B[0;32m   1247\u001B[0m         path, mode, storage_options\u001B[38;5;241m=\u001B[39mstorage_options, is_text\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mFalse\u001B[39;00m\n\u001B[0;32m   1248\u001B[0m     )\n\u001B[0;32m   1249\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_cur_sheet \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mNone\u001B[39;00m\n\u001B[0;32m   1251\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m date_format \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n",
      "File \u001B[1;32mD:\\ProgramTools\\Anaconda\\Lib\\site-packages\\pandas\\io\\common.py:882\u001B[0m, in \u001B[0;36mget_handle\u001B[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001B[0m\n\u001B[0;32m    873\u001B[0m         handle \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mopen\u001B[39m(\n\u001B[0;32m    874\u001B[0m             handle,\n\u001B[0;32m    875\u001B[0m             ioargs\u001B[38;5;241m.\u001B[39mmode,\n\u001B[1;32m   (...)\u001B[0m\n\u001B[0;32m    878\u001B[0m             newline\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124m\"\u001B[39m,\n\u001B[0;32m    879\u001B[0m         )\n\u001B[0;32m    880\u001B[0m     \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m    881\u001B[0m         \u001B[38;5;66;03m# Binary mode\u001B[39;00m\n\u001B[1;32m--> 882\u001B[0m         handle \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mopen\u001B[39m(handle, ioargs\u001B[38;5;241m.\u001B[39mmode)\n\u001B[0;32m    883\u001B[0m     handles\u001B[38;5;241m.\u001B[39mappend(handle)\n\u001B[0;32m    885\u001B[0m \u001B[38;5;66;03m# Convert BytesIO or file objects passed with an encoding\u001B[39;00m\n",
      "\u001B[1;31mPermissionError\u001B[0m: [Errno 13] Permission denied: 'C:\\\\Users\\\\Administrator.DESKTOP-7IC2USJ\\\\Desktop\\\\返回结果地址.xlsx'"
     ]
    }
   ],
   "execution_count": 14
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-05-07T09:59:23.174447Z",
     "start_time": "2025-05-07T09:59:23.134858Z"
    }
   },
   "cell_type": "code",
   "source": [
    "df2 = pd.DataFrame(all_data)\n",
    "df2.to_excel(r\"C:\\Users\\Administrator.DESKTOP-7IC2USJ\\Desktop\\返回结果地址.xlsx\", index=False)"
   ],
   "id": "ffd7630ac0346d03",
   "outputs": [],
   "execution_count": 15
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "处理数据",
   "id": "f148b0790bde7067"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-05-07T09:37:22.583854Z",
     "start_time": "2025-05-07T09:37:22.343548Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pandas as pd\n",
    "\n",
    "df3 = pd.read_excel(r\"C:\\Users\\Administrator.DESKTOP-7IC2USJ\\Desktop\\返回结果地址.xlsx\")\n",
    "df = pd.read_excel(r\"C:\\Users\\Administrator.DESKTOP-7IC2USJ\\Desktop\\地址.xlsx\", sheet_name=\"Sheet2\")\n",
    "\n",
    "for index, row in df.iterrows():\n",
    "    cleaned = row['地址'].replace(row['市'], '').strip()\n",
    "    # 再删除 c\n",
    "    cleaned = cleaned.replace(row['区/县'], '').strip()\n",
    "    # 删除多余空格（如 \"apple  banana\" → \"apple banana\"）\n",
    "    cleaned = ' '.join(cleaned.split())\n",
    "    # 更新到新列\n",
    "    df.at[index, '详细地址'] = cleaned\n",
    "    \n",
    "\n"
   ],
   "id": "8c61c7db7bda3982",
   "outputs": [],
   "execution_count": 9
  }
 ],
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