데이터전처리.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.stats import norm\n",
    "from haversine import haversine\n",
    "from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "city_list=[\"광주\", \"울산\", \"전주\", \"창원\"]\n",
    "i=2\n",
    "fire_incident_df=pd.read_csv(city_list[i]+\" data 경도 위도 매핑/\"+city_list[i]+\" 화재 정보.csv\")\n",
    "accident_df=pd.read_csv(city_list[i]+\" data 경도 위도 매핑/\"+city_list[i]+\"_교통사고_통계.csv\")\n",
    "school_df=pd.read_csv(city_list[i]+\" data 경도 위도 매핑/\"+city_list[i]+\" 초중고.csv\")\n",
    "bus_station_df=pd.read_csv(city_list[i]+\" data 경도 위도 매핑/\"+city_list[i]+\"시_버스 정류장.csv\")\n",
    "gas_station_df=pd.read_csv(city_list[i]+\" data 경도 위도 매핑/\"+city_list[i]+\"_충전소_주유소.csv\")\n",
    "weight_df=pd.DataFrame([[0]*7]*len(gas_station_df), columns=['주유소명', '버스정류장개수', '상호개수', '교통사고건수','보호구역개수','화재발생건수','총 가중치'])\n",
    "weight_df['주유소명']=gas_station_df['상호'][:]\n",
    "## 추가추가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>주유소명</th>\n",
       "      <th>버스정류장개수</th>\n",
       "      <th>상호개수</th>\n",
       "      <th>교통사고건수</th>\n",
       "      <th>보호구역개수</th>\n",
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       "      <th>총 가중치</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>직영충전소</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(유)삼영에너지</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(유)푸른기업충전소</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>㈜진성에너지 색장충전소</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>전주유성LPG충전소</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>(주)안국에너지 호반주유소</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>동아주유소</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>중앙주유소</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>덕산주유소</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>새로운주유소</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>198 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               주유소명  버스정류장개수  상호개수  교통사고건수  보호구역개수  화재발생건수  총 가중치\n",
       "0             직영충전소        0     0       0       0       0      0\n",
       "1          (유)삼영에너지        0     0       0       0       0      0\n",
       "2        (유)푸른기업충전소        0     0       0       0       0      0\n",
       "3      ㈜진성에너지 색장충전소        0     0       0       0       0      0\n",
       "4        전주유성LPG충전소        0     0       0       0       0      0\n",
       "..              ...      ...   ...     ...     ...     ...    ...\n",
       "193  (주)안국에너지 호반주유소        0     0       0       0       0      0\n",
       "194           동아주유소        0     0       0       0       0      0\n",
       "195           중앙주유소        0     0       0       0       0      0\n",
       "196           덕산주유소        0     0       0       0       0      0\n",
       "197          새로운주유소        0     0       0       0       0      0\n",
       "\n",
       "[198 rows x 7 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>조사서번호</th>\n",
       "      <th>시도</th>\n",
       "      <th>시군구</th>\n",
       "      <th>읍면동</th>\n",
       "      <th>주소</th>\n",
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       "      <th>0</th>\n",
       "      <td>'170101093018530</td>\n",
       "      <td>전라북도</td>\n",
       "      <td>전주시덕진구</td>\n",
       "      <td>호성동2가</td>\n",
       "      <td>전라북도 전주시덕진구 호성동2가</td>\n",
       "      <td>35.876378</td>\n",
       "      <td>127.146907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>'170101100618186</td>\n",
       "      <td>전라북도</td>\n",
       "      <td>전주시덕진구</td>\n",
       "      <td>송천동2가</td>\n",
       "      <td>전라북도 전주시덕진구 송천동2가</td>\n",
       "      <td>35.876378</td>\n",
       "      <td>127.146907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>'170101135933896</td>\n",
       "      <td>전라북도</td>\n",
       "      <td>전주시완산구</td>\n",
       "      <td>평화동2가</td>\n",
       "      <td>전라북도 전주시완산구 평화동2가</td>\n",
       "      <td>35.876378</td>\n",
       "      <td>127.146907</td>\n",
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      "text/plain": [
       "              조사서번호    시도     시군구    읍면동                 주소         위도  \\\n",
       "0  '170101093018530  전라북도  전주시덕진구  호성동2가  전라북도 전주시덕진구 호성동2가  35.876378   \n",
       "1  '170101100618186  전라북도  전주시덕진구  송천동2가  전라북도 전주시덕진구 송천동2가  35.876378   \n",
       "2  '170101135933896  전라북도  전주시완산구  평화동2가  전라북도 전주시완산구 평화동2가  35.876378   \n",
       "\n",
       "           경도  \n",
       "0  127.146907  \n",
       "1  127.146907  \n",
       "2  127.146907  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fire_incident_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>시군구</th>\n",
       "      <th>도로명</th>\n",
       "      <th>주소</th>\n",
       "      <th>사고건수</th>\n",
       "      <th>사망자수</th>\n",
       "      <th>중상자수</th>\n",
       "      <th>경상자수</th>\n",
       "      <th>부상신고자수</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>전주시</td>\n",
       "      <td>백제대로</td>\n",
       "      <td>전주시 백제대로</td>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>0</td>\n",
       "      <td>35.842997</td>\n",
       "      <td>127.139671</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>전주시</td>\n",
       "      <td>기린대로</td>\n",
       "      <td>전주시 기린대로</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>35.847457</td>\n",
       "      <td>127.112191</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>전주시</td>\n",
       "      <td>기린대로</td>\n",
       "      <td>전주시 기린대로</td>\n",
       "      <td>87</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>102</td>\n",
       "      <td>1</td>\n",
       "      <td>35.847457</td>\n",
       "      <td>127.112191</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  시군구   도로명        주소  사고건수  사망자수  중상자수  경상자수  부상신고자수         위도  \\\n",
       "0           0  전주시  백제대로  전주시 백제대로    63     1    23    94       0  35.842997   \n",
       "1           1  전주시  기린대로  전주시 기린대로    15     1     3    14       0  35.847457   \n",
       "2           2  전주시  기린대로  전주시 기린대로    87     1    23   102       1  35.847457   \n",
       "\n",
       "           경도  \n",
       "0  127.139671  \n",
       "1  127.112191  \n",
       "2  127.112191  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accident_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>설치 지점명</th>\n",
       "      <th>지역(구)</th>\n",
       "      <th>지역(동)</th>\n",
       "      <th>세부주소</th>\n",
       "      <th>행정동</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>우아롯데아파트</td>\n",
       "      <td>덕진구</td>\n",
       "      <td>우아동</td>\n",
       "      <td>우아동 2동 887</td>\n",
       "      <td>우아2동</td>\n",
       "      <td>35.832510</td>\n",
       "      <td>127.167824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>여의동우체국전북은행</td>\n",
       "      <td>덕진구</td>\n",
       "      <td>여의동</td>\n",
       "      <td>여의동2가 696</td>\n",
       "      <td>여의동</td>\n",
       "      <td>35.871416</td>\n",
       "      <td>127.076584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>기린대로경제통상진흥원</td>\n",
       "      <td>덕진구</td>\n",
       "      <td>팔복동</td>\n",
       "      <td>팔복동2가 550</td>\n",
       "      <td>팔복동</td>\n",
       "      <td>35.859761</td>\n",
       "      <td>127.092527</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "        설치 지점명 지역(구) 지역(동)        세부주소          행정동         위도          경도\n",
       "0      우아롯데아파트   덕진구  우아동   우아동 2동 887  우아2동         35.832510  127.167824\n",
       "1   여의동우체국전북은행   덕진구   여의동   여의동2가 696  여의동          35.871416  127.076584\n",
       "2  기린대로경제통상진흥원   덕진구   팔복동   팔복동2가 550  팔복동          35.859761  127.092527"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bus_station_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>지역</th>\n",
       "      <th>상호</th>\n",
       "      <th>타입</th>\n",
       "      <th>주소</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>전라북도</td>\n",
       "      <td>직영충전소</td>\n",
       "      <td>충전소</td>\n",
       "      <td>전북 전주시 덕진구  혁신로 360번지</td>\n",
       "      <td>35.864542</td>\n",
       "      <td>127.069401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>전라북도</td>\n",
       "      <td>(유)삼영에너지</td>\n",
       "      <td>충전소</td>\n",
       "      <td>전북 전주시 완산구 쑥고개로 11 (용복동)</td>\n",
       "      <td>35.790810</td>\n",
       "      <td>127.068859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>전라북도</td>\n",
       "      <td>(유)푸른기업충전소</td>\n",
       "      <td>충전소</td>\n",
       "      <td>전북 전주시 완산구  모악로 4483 (석구동)</td>\n",
       "      <td>35.786460</td>\n",
       "      <td>127.128841</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     지역          상호   타입                          주소         위도          경도\n",
       "0  전라북도       직영충전소  충전소       전북 전주시 덕진구  혁신로 360번지  35.864542  127.069401\n",
       "1  전라북도    (유)삼영에너지  충전소    전북 전주시 완산구 쑥고개로 11 (용복동)  35.790810  127.068859\n",
       "2  전라북도  (유)푸른기업충전소  충전소  전북 전주시 완산구  모악로 4483 (석구동)  35.786460  127.128841"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gas_station_df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 가산"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "가능 : 타 주유소, 교통량(교통 사고), 버스 정류장"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "working on : 차고지 위치"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 거리 총합 리스트\n",
    "def 거리총합리스트(data1, data2, name_col):\n",
    "    # distance_list=[]\n",
    "\n",
    "    for i in range(len(data1)):\n",
    "        total=0\n",
    "        for j in range(len(data2)):\n",
    "            total+=haversine((data1.loc[i]['위도'],data1.loc[i]['경도']),(data2.loc[j]['위도'],data2.loc[j]['경도']), unit = 'km')\n",
    "        # distance_list.append((data1.loc[i][name_col],total))\n",
    "        weight_df['버정거리총합'][i]=total\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# p 반경 이내 개수 리스트(타 주유소)\n",
    "def 반경이내_개수_리스트(p, data1, data2, name_col):\n",
    "    count_list=[]\n",
    "    for i in range(len(data1)):\n",
    "        count=0\n",
    "        for j in range(len(data2)):\n",
    "            dist=haversine((data1.loc[i]['위도'],data1.loc[i]['경도']),(data2.loc[j]['위도'],data2.loc[j]['경도']), unit = 'km')\n",
    "            if dist<=p:\n",
    "                # 교통사고 데이터 사고 건수로 count!\n",
    "                if ('사고건수' in data2.columns):\n",
    "                    count+=data2.loc[j,'사고건수']\n",
    "                else:\n",
    "                    count+=1\n",
    "        #count_list.append((data1.loc[i][name_col],count-1)) 상호명 매핑 화긴~\n",
    "        if (count == 0):\n",
    "            count_list.append(count)\n",
    "        else:\n",
    "            count_list.append(count-1)# 자기 자신 제외\n",
    "\n",
    "    return count_list\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>주유소명</th>\n",
       "      <th>버정거리총합</th>\n",
       "      <th>상호개수</th>\n",
       "      <th>교통사고건수</th>\n",
       "      <th>보호구역개수</th>\n",
       "      <th>화재발생건수</th>\n",
       "      <th>총 가중치</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>직영충전소</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(유)삼영에너지</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(유)푸른기업충전소</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>㈜진성에너지 색장충전소</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>전주유성LPG충전소</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>(주)안국에너지 호반주유소</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>동아주유소</td>\n",
       "      <td>76</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>중앙주유소</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>덕산주유소</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>새로운주유소</td>\n",
       "      <td>121</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>198 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               주유소명  버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수  총 가중치\n",
       "0             직영충전소      27     0       0       0       0      0\n",
       "1          (유)삼영에너지       2     0       0       0       0      0\n",
       "2        (유)푸른기업충전소      59     0       0       0       0      0\n",
       "3      ㈜진성에너지 색장충전소       3     0       0       0       0      0\n",
       "4        전주유성LPG충전소       4     0       0       0       0      0\n",
       "..              ...     ...   ...     ...     ...     ...    ...\n",
       "193  (주)안국에너지 호반주유소      79     0       0       0       0      0\n",
       "194           동아주유소      76     0       0       0       0      0\n",
       "195           중앙주유소      14     0       0       0       0      0\n",
       "196           덕산주유소       3     0       0       0       0      0\n",
       "197          새로운주유소     121     0       0       0       0      0\n",
       "\n",
       "[198 rows x 7 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\" 이건 km\n",
    "거리총합리스트(gas_station_df, bus_station_df, '상호')\n",
    "weight_df['버정거리총합']=max(weight_df['버정거리총합'])-weight_df['버정거리총합']\n",
    "weight_df\n",
    "\"\"\" # 이건 개수\n",
    "버스정류장개수 = 반경이내_개수_리스트(2, gas_station_df, bus_station_df,'상호')\n",
    "weight_df['버스정류장개수']=버정거버스정류장개수리총합\n",
    "weight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>보호구역개수</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>27</td>\n",
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       "      <th>1</th>\n",
       "      <td>(유)삼영에너지</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(유)푸른기업충전소</td>\n",
       "      <td>59</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>㈜진성에너지 색장충전소</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>전주유성LPG충전소</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>(주)안국에너지 호반주유소</td>\n",
       "      <td>79</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>동아주유소</td>\n",
       "      <td>76</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>중앙주유소</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>덕산주유소</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>새로운주유소</td>\n",
       "      <td>121</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>198 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               주유소명  버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수  총 가중치\n",
       "0             직영충전소      27    29       0       0       0      0\n",
       "1          (유)삼영에너지       2     3       0       0       0      0\n",
       "2        (유)푸른기업충전소      59    19       0       0       0      0\n",
       "3      ㈜진성에너지 색장충전소       3     7       0       0       0      0\n",
       "4        전주유성LPG충전소       4     9       0       0       0      0\n",
       "..              ...     ...   ...     ...     ...     ...    ...\n",
       "193  (주)안국에너지 호반주유소      79    20       0       0       0      0\n",
       "194           동아주유소      76    16       0       0       0      0\n",
       "195           중앙주유소      14    13       0       0       0      0\n",
       "196           덕산주유소       3     7       0       0       0      0\n",
       "197          새로운주유소     121    18       0       0       0      0\n",
       "\n",
       "[198 rows x 7 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "상호개수 = 반경이내_개수_리스트(2, gas_station_df, gas_station_df,'상호')\n",
    "weight_df['상호개수']=상호개수\n",
    "weight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>주유소명</th>\n",
       "      <th>버정거리총합</th>\n",
       "      <th>상호개수</th>\n",
       "      <th>교통사고건수</th>\n",
       "      <th>보호구역개수</th>\n",
       "      <th>화재발생건수</th>\n",
       "      <th>총 가중치</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>직영충전소</td>\n",
       "      <td>27</td>\n",
       "      <td>29</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(유)삼영에너지</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(유)푸른기업충전소</td>\n",
       "      <td>59</td>\n",
       "      <td>19</td>\n",
       "      <td>185</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>㈜진성에너지 색장충전소</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>전주유성LPG충전소</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>(주)안국에너지 호반주유소</td>\n",
       "      <td>79</td>\n",
       "      <td>20</td>\n",
       "      <td>423</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>동아주유소</td>\n",
       "      <td>76</td>\n",
       "      <td>16</td>\n",
       "      <td>228</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>중앙주유소</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>덕산주유소</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>새로운주유소</td>\n",
       "      <td>121</td>\n",
       "      <td>18</td>\n",
       "      <td>445</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>198 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               주유소명  버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수  총 가중치\n",
       "0             직영충전소      27    29      62       0       0      0\n",
       "1          (유)삼영에너지       2     3       2       0       0      0\n",
       "2        (유)푸른기업충전소      59    19     185       0       0      0\n",
       "3      ㈜진성에너지 색장충전소       3     7      12       0       0      0\n",
       "4        전주유성LPG충전소       4     9      12       0       0      0\n",
       "..              ...     ...   ...     ...     ...     ...    ...\n",
       "193  (주)안국에너지 호반주유소      79    20     423       0       0      0\n",
       "194           동아주유소      76    16     228       0       0      0\n",
       "195           중앙주유소      14    13      26       0       0      0\n",
       "196           덕산주유소       3     7      12       0       0      0\n",
       "197          새로운주유소     121    18     445       0       0      0\n",
       "\n",
       "[198 rows x 7 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "교통사고건수=반경이내_개수_리스트(2, gas_station_df, accident_df,'상호')\n",
    "weight_df['교통사고건수']=교통사고건수\n",
    "weight_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 감점"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "가능 : 어린이집, 유초중고(2km)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "working on : 화재"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>'170101093018530</td>\n",
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       "      <td>전주시덕진구</td>\n",
       "      <td>호성동2가</td>\n",
       "      <td>전라북도 전주시덕진구 호성동2가</td>\n",
       "      <td>35.876378</td>\n",
       "      <td>127.146907</td>\n",
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       "      <th>1</th>\n",
       "      <td>'170101100618186</td>\n",
       "      <td>전라북도</td>\n",
       "      <td>전주시덕진구</td>\n",
       "      <td>송천동2가</td>\n",
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       "      <td>35.876378</td>\n",
       "      <td>127.146907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>'170101135933896</td>\n",
       "      <td>전라북도</td>\n",
       "      <td>전주시완산구</td>\n",
       "      <td>평화동2가</td>\n",
       "      <td>전라북도 전주시완산구 평화동2가</td>\n",
       "      <td>35.876378</td>\n",
       "      <td>127.146907</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              조사서번호    시도     시군구    읍면동                 주소         위도  \\\n",
       "0  '170101093018530  전라북도  전주시덕진구  호성동2가  전라북도 전주시덕진구 호성동2가  35.876378   \n",
       "1  '170101100618186  전라북도  전주시덕진구  송천동2가  전라북도 전주시덕진구 송천동2가  35.876378   \n",
       "2  '170101135933896  전라북도  전주시완산구  평화동2가  전라북도 전주시완산구 평화동2가  35.876378   \n",
       "\n",
       "           경도  \n",
       "0  127.146907  \n",
       "1  127.146907  \n",
       "2  127.146907  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fire_incident_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>타입</th>\n",
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       "      <th>위도</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>전라북도</td>\n",
       "      <td>직영충전소</td>\n",
       "      <td>충전소</td>\n",
       "      <td>전북 전주시 덕진구  혁신로 360번지</td>\n",
       "      <td>35.864542</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>전라북도</td>\n",
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       "      <td>전북 전주시 완산구 쑥고개로 11 (용복동)</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>전라북도</td>\n",
       "      <td>(유)푸른기업충전소</td>\n",
       "      <td>충전소</td>\n",
       "      <td>전북 전주시 완산구  모악로 4483 (석구동)</td>\n",
       "      <td>35.786460</td>\n",
       "      <td>127.128841</td>\n",
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      ],
      "text/plain": [
       "     지역          상호   타입                          주소         위도          경도\n",
       "0  전라북도       직영충전소  충전소       전북 전주시 덕진구  혁신로 360번지  35.864542  127.069401\n",
       "1  전라북도    (유)삼영에너지  충전소    전북 전주시 완산구 쑥고개로 11 (용복동)  35.790810  127.068859\n",
       "2  전라북도  (유)푸른기업충전소  충전소  전북 전주시 완산구  모악로 4483 (석구동)  35.786460  127.128841"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gas_station_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>시도</th>\n",
       "      <th>행정구</th>\n",
       "      <th>교육\\n(지원)청</th>\n",
       "      <th>학교급</th>\n",
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       "      <th>우편번호</th>\n",
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       "      <th>위도</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>전북</td>\n",
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       "      <td>54896</td>\n",
       "      <td>전라북도 전주시 덕진구 백제대로 567(금암동. 전북대학교)</td>\n",
       "      <td>35.846732</td>\n",
       "      <td>127.129367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>전북</td>\n",
       "      <td>전주시</td>\n",
       "      <td>전북</td>\n",
       "      <td>고등학교</td>\n",
       "      <td>일반고</td>\n",
       "      <td>일반고등학교</td>\n",
       "      <td>전라고등학교</td>\n",
       "      <td>54836</td>\n",
       "      <td>전라북도 전주시 덕진구 솔내7길 25(송천동1가. 전라고등학교)</td>\n",
       "      <td>35.859966</td>\n",
       "      <td>127.124891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>전북</td>\n",
       "      <td>전주시</td>\n",
       "      <td>전북</td>\n",
       "      <td>고등학교</td>\n",
       "      <td>일반고</td>\n",
       "      <td>일반고등학교</td>\n",
       "      <td>전주고등학교</td>\n",
       "      <td>55007</td>\n",
       "      <td>전라북도 전주시 완산구 권삼득로 2(중노송동. 전주고등학교)</td>\n",
       "      <td>35.825388</td>\n",
       "      <td>127.151833</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "   시도  행정구 교육\\n(지원)청   학교급 고등학교\\n유형 KEDI 학제              학교명   우편번호  \\\n",
       "0  전북  전주시        전북  고등학교      일반고  일반고등학교  전북대학교사범대학부설고등학교  54896   \n",
       "1  전북  전주시        전북  고등학교      일반고  일반고등학교           전라고등학교  54836   \n",
       "2  전북  전주시        전북  고등학교      일반고  일반고등학교           전주고등학교  55007   \n",
       "\n",
       "                                    주소         위도          경도  \n",
       "0    전라북도 전주시 덕진구 백제대로 567(금암동. 전북대학교)  35.846732  127.129367  \n",
       "1  전라북도 전주시 덕진구 솔내7길 25(송천동1가. 전라고등학교)  35.859966  127.124891  \n",
       "2    전라북도 전주시 완산구 권삼득로 2(중노송동. 전주고등학교)  35.825388  127.151833  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "school_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#kinder_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#유치원,,\n",
    "#보호구역개수=반경이내_개수_리스트(2, gas_station_df, kinder_df, '상호')\n",
    "#weight_df['보호구역개수']=보호구역개수"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>주유소명</th>\n",
       "      <th>버정거리총합</th>\n",
       "      <th>상호개수</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>직영충전소</td>\n",
       "      <td>27</td>\n",
       "      <td>29</td>\n",
       "      <td>62</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
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       "      <td>12</td>\n",
       "      <td>0</td>\n",
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       "      <th>4</th>\n",
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       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>(주)안국에너지 호반주유소</td>\n",
       "      <td>79</td>\n",
       "      <td>20</td>\n",
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       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>동아주유소</td>\n",
       "      <td>76</td>\n",
       "      <td>16</td>\n",
       "      <td>228</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>중앙주유소</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>196</th>\n",
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       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>197</th>\n",
       "      <td>새로운주유소</td>\n",
       "      <td>121</td>\n",
       "      <td>18</td>\n",
       "      <td>445</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>198 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               주유소명  버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수  총 가중치\n",
       "0             직영충전소      27    29      62      11       0      0\n",
       "1          (유)삼영에너지       2     3       2       4       0      0\n",
       "2        (유)푸른기업충전소      59    19     185      37       0      0\n",
       "3      ㈜진성에너지 색장충전소       3     7      12       0       0      0\n",
       "4        전주유성LPG충전소       4     9      12       1       0      0\n",
       "..              ...     ...   ...     ...     ...     ...    ...\n",
       "193  (주)안국에너지 호반주유소      79    20     423      34       0      0\n",
       "194           동아주유소      76    16     228      47       0      0\n",
       "195           중앙주유소      14    13      26       3       0      0\n",
       "196           덕산주유소       3     7      12       0       0      0\n",
       "197          새로운주유소     121    18     445      55       0      0\n",
       "\n",
       "[198 rows x 7 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "보호구역개수=반경이내_개수_리스트(2, gas_station_df, school_df, '상호')\n",
    "weight_df['보호구역개수']=보호구역개수\n",
    "weight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>...</th>\n",
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       "      <td>34</td>\n",
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       "      <th>194</th>\n",
       "      <td>동아주유소</td>\n",
       "      <td>76</td>\n",
       "      <td>16</td>\n",
       "      <td>228</td>\n",
       "      <td>47</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>중앙주유소</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>덕산주유소</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>새로운주유소</td>\n",
       "      <td>121</td>\n",
       "      <td>18</td>\n",
       "      <td>445</td>\n",
       "      <td>55</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>198 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               주유소명  버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수  총 가중치\n",
       "0             직영충전소      27    29      62      11       8      0\n",
       "1          (유)삼영에너지       2     3       2       4       1      0\n",
       "2        (유)푸른기업충전소      59    19     185      37      34      0\n",
       "3      ㈜진성에너지 색장충전소       3     7      12       0       3      0\n",
       "4        전주유성LPG충전소       4     9      12       1       3      0\n",
       "..              ...     ...   ...     ...     ...     ...    ...\n",
       "193  (주)안국에너지 호반주유소      79    20     423      34      43      0\n",
       "194           동아주유소      76    16     228      47      37      0\n",
       "195           중앙주유소      14    13      26       3      16      0\n",
       "196           덕산주유소       3     7      12       0       3      0\n",
       "197          새로운주유소     121    18     445      55      58      0\n",
       "\n",
       "[198 rows x 7 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "화재발생건수=반경이내_개수_리스트(2, gas_station_df, fire_incident_df, '상호')\n",
    "weight_df['화재발생건수']=화재발생건수\n",
    "weight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "weight_df.to_csv(city_list[i]+\" 최종가중치_df.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <가중 구간>\n",
    "- 버정거리총합 : [0.3, 0.5, 0.7, 0.9, 1.0]\n",
    "- 상호개수 : [0.5, 0.63, 0.76, 0.89, 1.0]\n",
    "- 교통사고건수 : [0.2, 0.4, 0.6, 0.8, 1.0]\n",
    "- 보호구역개수 : [0.5, 0.63, 0.76, 0.89, 1.0]\n",
    "- 화재 발생건수 : [0.25,0.45,0.65,0.85,1.0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <최종 가중치>\n",
    "1. 화재발생건수 : 0.503\n",
    "2. 교통사고건수 : 0.260\n",
    "3. 보호구역개수 : 0.134\n",
    "4. 버스정류장수 : 0.068\n",
    "5. 상호개수 : 0.035"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 칼럼별로 정규 분포로 변경하여 그리기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# city_list=[\"광주\", \"울산\", \"전주\", \"창원\"]\n",
    "\n",
    "# 도시별 주유소\n",
    "Gwangju_weight_df=pd.read_csv(\"광주 최종가중치_df.csv\")\n",
    "Ulsan_weight_df=pd.read_csv(\"울산 최종가중치_df.csv\")\n",
    "Changwon_weight_df=pd.read_csv(\"창원 최종가중치_df.csv\")\n",
    "\n",
    "# 도시별 충전소\n",
    "Gwangju_hydro_weight_df=pd.read_csv(\"광주수소충전소 전처리.csv\")\n",
    "Ulsan_hydro_weight_df=pd.read_csv(\"울산수소충전소 전처리.csv\")\n",
    "Changwon_hydro_weight_df=pd.read_csv(\"창원수소충전소 전처리.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>반디석유시청점</td>\n",
       "      <td>86</td>\n",
       "      <td>20</td>\n",
       "      <td>409</td>\n",
       "      <td>13</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(주)아프리카주유소</td>\n",
       "      <td>96</td>\n",
       "      <td>23</td>\n",
       "      <td>520</td>\n",
       "      <td>16</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>한강주유소</td>\n",
       "      <td>212</td>\n",
       "      <td>33</td>\n",
       "      <td>983</td>\n",
       "      <td>47</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>우리셀프주유소</td>\n",
       "      <td>193</td>\n",
       "      <td>26</td>\n",
       "      <td>1120</td>\n",
       "      <td>44</td>\n",
       "      <td>107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>풍암LPG충전소</td>\n",
       "      <td>91</td>\n",
       "      <td>11</td>\n",
       "      <td>217</td>\n",
       "      <td>20</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>주식회사대동가스</td>\n",
       "      <td>95</td>\n",
       "      <td>12</td>\n",
       "      <td>223</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>목포도시가스(주)MC에너지</td>\n",
       "      <td>157</td>\n",
       "      <td>20</td>\n",
       "      <td>1252</td>\n",
       "      <td>52</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>대양케미칼주유소/충전소</td>\n",
       "      <td>91</td>\n",
       "      <td>16</td>\n",
       "      <td>224</td>\n",
       "      <td>23</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>315</th>\n",
       "      <td>(유)남악 청기와충전소</td>\n",
       "      <td>202</td>\n",
       "      <td>24</td>\n",
       "      <td>1257</td>\n",
       "      <td>52</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>316 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               주유소명  버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수\n",
       "0       (주)대원 강변주유소     154    20    1262      48     103\n",
       "1           반디석유시청점      86    20     409      13      67\n",
       "2        (주)아프리카주유소      96    23     520      16      67\n",
       "3             한강주유소     212    33     983      47      58\n",
       "4           우리셀프주유소     193    26    1120      44     107\n",
       "..              ...     ...   ...     ...     ...     ...\n",
       "311        풍암LPG충전소      91    11     217      20      31\n",
       "312        주식회사대동가스      95    12     223      25      23\n",
       "313  목포도시가스(주)MC에너지     157    20    1252      52     122\n",
       "314    대양케미칼주유소/충전소      91    16     224      23      44\n",
       "315    (유)남악 청기와충전소     202    24    1257      52      89\n",
       "\n",
       "[316 rows x 6 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Gwangju_weight_df.iloc[:,1:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "4             4       내트럭(주) 울산신항사업소     울산 남구 신항로716번길 13      13     0   \n",
       "..          ...                  ...                   ...     ...   ...   \n",
       "271         271              울산가스충전소   울산 울주군 언양읍 반구대로 960      78     4   \n",
       "272         272              언양가스충전소    울산 울주군 언양읍 언양로 102      88     7   \n",
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       "274         274              태화가스충전소      울산 중구 북부순환도로 165     215    12   \n",
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       "\n",
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  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>우정혁신도시충전소</td>\n",
       "      <td>울산 중구 성안로 131 (성안동)</td>\n",
       "      <td>175</td>\n",
       "      <td>9</td>\n",
       "      <td>198</td>\n",
       "      <td>35</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    주유소명                    주소  버정거리총합  상호개수  교통사고건수  보호구역개수  \\\n",
       "0            내트럭(주)울산사업소         울산 남구 산업로 100      78    18      75       6   \n",
       "1                  강변주유소    울산 남구 남산로 17 (무거동)     160    11     265      32   \n",
       "2               (주)일광주유소          울산 남구 산업로 93      68    19      74       5   \n",
       "3          ㈜좋은기름나라 상개주유소    울산 남구 산업로 92 (상개동)      92    17      88      12   \n",
       "4         내트럭(주) 울산신항사업소     울산 남구 신항로716번길 13      13     0       9       0   \n",
       "..                   ...                   ...     ...   ...     ...     ...   \n",
       "271              울산가스충전소   울산 울주군 언양읍 반구대로 960      78     4      61       8   \n",
       "272              언양가스충전소    울산 울주군 언양읍 언양로 102      88     7      72       7   \n",
       "273  ㈜오일석유 언양(서울)주유소/충전소  울산 울주군 언양읍 경부고속도로 44      35     2      20       1   \n",
       "274              태화가스충전소      울산 중구 북부순환도로 165     215    12     287      41   \n",
       "275            우정혁신도시충전소   울산 중구 성안로 131 (성안동)     175     9     198      35   \n",
       "\n",
       "     화재발생건수  \n",
       "0        39  \n",
       "1        51  \n",
       "2        41  \n",
       "3         9  \n",
       "4         7  \n",
       "..      ...  \n",
       "271      28  \n",
       "272      28  \n",
       "273       0  \n",
       "274      76  \n",
       "275      60  \n",
       "\n",
       "[276 rows x 7 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ulsan_weight_df.iloc[:,1:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>주유소명</th>\n",
       "      <th>버정거리총합</th>\n",
       "      <th>상호개수</th>\n",
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       "      <th>화재발생건수</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>SK행복충전 불모가스충전소</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>동부2</td>\n",
       "      <td>78</td>\n",
       "      <td>10</td>\n",
       "      <td>172</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(유)공단가스산업</td>\n",
       "      <td>68</td>\n",
       "      <td>18</td>\n",
       "      <td>127</td>\n",
       "      <td>11</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>광신직영(두대충전소)</td>\n",
       "      <td>86</td>\n",
       "      <td>14</td>\n",
       "      <td>177</td>\n",
       "      <td>17</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SK행복충전 유남충전소(주)배성에너지</td>\n",
       "      <td>90</td>\n",
       "      <td>15</td>\n",
       "      <td>203</td>\n",
       "      <td>17</td>\n",
       "      <td>43</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>판도라주유소</td>\n",
       "      <td>32</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
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       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>진웅</td>\n",
       "      <td>48</td>\n",
       "      <td>5</td>\n",
       "      <td>150</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>광신직영(호원셀프)</td>\n",
       "      <td>65</td>\n",
       "      <td>10</td>\n",
       "      <td>33</td>\n",
       "      <td>5</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>야구장주유소</td>\n",
       "      <td>152</td>\n",
       "      <td>30</td>\n",
       "      <td>308</td>\n",
       "      <td>45</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>광신석유(주)직영 산호주유소</td>\n",
       "      <td>132</td>\n",
       "      <td>28</td>\n",
       "      <td>293</td>\n",
       "      <td>32</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>221 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     주유소명  버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수\n",
       "0          SK행복충전 불모가스충전소       7     3       0       0       1\n",
       "1                     동부2      78    10     172      25      26\n",
       "2               (유)공단가스산업      68    18     127      11      17\n",
       "3             광신직영(두대충전소)      86    14     177      17      30\n",
       "4    SK행복충전 유남충전소(주)배성에너지      90    15     203      17      43\n",
       "..                    ...     ...   ...     ...     ...     ...\n",
       "216                판도라주유소      32     4      20       4      16\n",
       "217                    진웅      48     5     150       3       6\n",
       "218            광신직영(호원셀프)      65    10      33       5      30\n",
       "219                야구장주유소     152    30     308      45      51\n",
       "220       광신석유(주)직영 산호주유소     132    28     293      32      34\n",
       "\n",
       "[221 rows x 6 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Changwon_weight_df.iloc[:,1:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "Gwangju_weight_df=Gwangju_weight_df.iloc[:,2:-1]\n",
    "Ulsan_weight_df=Ulsan_weight_df.iloc[:,3:-1]\n",
    "Changwon_weight_df=Changwon_weight_df.iloc[:,2:-1]\n",
    "Gwangju_hydro_weight_df=Gwangju_hydro_weight_df.iloc[:,2:-1]\n",
    "Ulsan_hydro_weight_df=Ulsan_hydro_weight_df.iloc[:,2:-1]\n",
    "Changwon_hydro_weight_df=Changwon_hydro_weight_df.iloc[:,2:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "   버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수\n",
       "0      43    18      82       4      25\n",
       "1     102    17     250      26      26\n",
       "2     111     8     159       3      30\n",
       "3      63    12      94       3      12"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Gwangju_hydro_weight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
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       "      <th>7</th>\n",
       "      <td>31</td>\n",
       "      <td>13</td>\n",
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       "      <td>29</td>\n",
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      "text/plain": [
       "   버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수\n",
       "0      37     0      20       1      10\n",
       "1      91     7     138      16      13\n",
       "2     173    23     615      28      47\n",
       "3      22     0      30       0      12\n",
       "4     144    13     210      29      40\n",
       "5      35     2      20       1       0\n",
       "6      41     5      16       0       0\n",
       "7      31    13      34       4      29\n",
       "8      29     9       6       0       0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ulsan_hydro_weight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>4</th>\n",
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      "text/plain": [
       "   버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수\n",
       "0      23     4       6       2       1\n",
       "1      91    15      99      24      13\n",
       "2      25     4       6       3       4\n",
       "3      93     4     355      34      48\n",
       "4      45     1      17       1       9"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Changwon_hydro_weight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nminMaxScaler = MinMaxScaler()\\nprint(minMaxScaler.fit(weight_df.iloc[:,[1,2,3,4,5]]))\\nweight_df_stdScaled = minMaxScaler.transform(weight_df.iloc[:,[1,2,3,4,5]])\\nweight_df_stdScaled=pd.DataFrame(weight_df_stdScaled, columns=[\"버정거리총합\",\"상호개수\",\"교통사고건수\",\"보호구역개수\",\"화재발생건수\"])\\nweight_df_stdScaled[\"주유소명\"]=weight_df[\"주유소명\"][:]\\nweight_df_stdScaled\\n\\n# 정규화\\nrv = norm(loc=0,scale=1)\\nweight_df_stdScaled[\"상호개수\"] = weight_df_stdScaled[\"상호개수\"].apply(lambda x : round(rv.cdf(x),2))\\n\\nweight_df_stdScaled\\n'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### 스케일링해서 상위 퍼센테이지 나오게 하는건데,, 일단 보류\n",
    "\"\"\"\n",
    "minMaxScaler = MinMaxScaler()\n",
    "print(minMaxScaler.fit(weight_df.iloc[:,[1,2,3,4,5]]))\n",
    "weight_df_stdScaled = minMaxScaler.transform(weight_df.iloc[:,[1,2,3,4,5]])\n",
    "weight_df_stdScaled=pd.DataFrame(weight_df_stdScaled, columns=[\"버정거리총합\",\"상호개수\",\"교통사고건수\",\"보호구역개수\",\"화재발생건수\"])\n",
    "weight_df_stdScaled[\"주유소명\"]=weight_df[\"주유소명\"][:]\n",
    "weight_df_stdScaled\n",
    "\n",
    "# 정규화\n",
    "rv = norm(loc=0,scale=1)\n",
    "weight_df_stdScaled[\"상호개수\"] = weight_df_stdScaled[\"상호개수\"].apply(lambda x : round(rv.cdf(x),2))\n",
    "\n",
    "weight_df_stdScaled\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "def histo_norm_vline(data_df, xlist, city):\n",
    "    for column in list(data_df.columns):\n",
    "        print(column)\n",
    "        mu = data_df[column].mean()\n",
    "        sigma = data_df[column].std()\n",
    "        \n",
    "        #이게 뭘까\n",
    "        nbins = 21\n",
    "        n, bins, patches = plt.hist(data_df[column], bins = nbins, density = 1)\n",
    "\n",
    "        y = ((1 / (np.sqrt(2 * np.pi) * sigma)) * np.exp(-0.5 * (1 / sigma * (bins - mu))**2))\n",
    "        plt.plot(bins, y, '--')\n",
    "        \n",
    "        for target_column in xlist.loc[:,column]:\n",
    "            plt.axvline(x=target_column, color='r', linestyle='--', linewidth=1)\n",
    "            print()\n",
    "        # 한글 깨짐 해결하기 귀찮아요,,, ㅈㅅ,,,,\n",
    "        #plt.xlabel(city+\" \"+column)\n",
    "        #plt.title(city+\" \"+column+\" 히스토그램\")\n",
    "        \n",
    "        plt.show()\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "버정거리총합\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "상호개수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교통사고건수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "보호구역개수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "화재발생건수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "histo_norm_vline(Gwangju_weight_df, Gwangju_hydro_weight_df,'Gwangju')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "버정거리총합\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "상호개수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교통사고건수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "보호구역개수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "화재발생건수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "histo_norm_vline(Ulsan_weight_df, Ulsan_hydro_weight_df,'Ulsan')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "버정거리총합\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "상호개수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교통사고건수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "보호구역개수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "화재발생건수\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "histo_norm_vline(Changwon_weight_df, Changwon_hydro_weight_df,'Changwon')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 스케일링"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MinMaxScaler()\n"
     ]
    },
    {
     "data": {
      "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>버정거리총합</th>\n",
       "      <th>상호개수</th>\n",
       "      <th>교통사고건수</th>\n",
       "      <th>보호구역개수</th>\n",
       "      <th>화재발생건수</th>\n",
       "      <th>주유소명</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.006667</td>\n",
       "      <td>0.09375</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013699</td>\n",
       "      <td>SK행복충전 불모가스충전소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.31250</td>\n",
       "      <td>0.320896</td>\n",
       "      <td>0.431034</td>\n",
       "      <td>0.356164</td>\n",
       "      <td>동부2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.413333</td>\n",
       "      <td>0.56250</td>\n",
       "      <td>0.236940</td>\n",
       "      <td>0.189655</td>\n",
       "      <td>0.232877</td>\n",
       "      <td>(유)공단가스산업</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.533333</td>\n",
       "      <td>0.43750</td>\n",
       "      <td>0.330224</td>\n",
       "      <td>0.293103</td>\n",
       "      <td>0.410959</td>\n",
       "      <td>광신직영(두대충전소)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.560000</td>\n",
       "      <td>0.46875</td>\n",
       "      <td>0.378731</td>\n",
       "      <td>0.293103</td>\n",
       "      <td>0.589041</td>\n",
       "      <td>SK행복충전 유남충전소(주)배성에너지</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>0.173333</td>\n",
       "      <td>0.12500</td>\n",
       "      <td>0.037313</td>\n",
       "      <td>0.068966</td>\n",
       "      <td>0.219178</td>\n",
       "      <td>판도라주유소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>0.280000</td>\n",
       "      <td>0.15625</td>\n",
       "      <td>0.279851</td>\n",
       "      <td>0.051724</td>\n",
       "      <td>0.082192</td>\n",
       "      <td>진웅</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>0.393333</td>\n",
       "      <td>0.31250</td>\n",
       "      <td>0.061567</td>\n",
       "      <td>0.086207</td>\n",
       "      <td>0.410959</td>\n",
       "      <td>광신직영(호원셀프)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>0.973333</td>\n",
       "      <td>0.93750</td>\n",
       "      <td>0.574627</td>\n",
       "      <td>0.775862</td>\n",
       "      <td>0.698630</td>\n",
       "      <td>야구장주유소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>0.840000</td>\n",
       "      <td>0.87500</td>\n",
       "      <td>0.546642</td>\n",
       "      <td>0.551724</td>\n",
       "      <td>0.465753</td>\n",
       "      <td>광신석유(주)직영 산호주유소</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>221 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       버정거리총합     상호개수    교통사고건수    보호구역개수    화재발생건수                  주유소명\n",
       "0    0.006667  0.09375  0.000000  0.000000  0.013699        SK행복충전 불모가스충전소\n",
       "1    0.480000  0.31250  0.320896  0.431034  0.356164                   동부2\n",
       "2    0.413333  0.56250  0.236940  0.189655  0.232877             (유)공단가스산업\n",
       "3    0.533333  0.43750  0.330224  0.293103  0.410959           광신직영(두대충전소)\n",
       "4    0.560000  0.46875  0.378731  0.293103  0.589041  SK행복충전 유남충전소(주)배성에너지\n",
       "..        ...      ...       ...       ...       ...                   ...\n",
       "216  0.173333  0.12500  0.037313  0.068966  0.219178                판도라주유소\n",
       "217  0.280000  0.15625  0.279851  0.051724  0.082192                    진웅\n",
       "218  0.393333  0.31250  0.061567  0.086207  0.410959            광신직영(호원셀프)\n",
       "219  0.973333  0.93750  0.574627  0.775862  0.698630                야구장주유소\n",
       "220  0.840000  0.87500  0.546642  0.551724  0.465753       광신석유(주)직영 산호주유소\n",
       "\n",
       "[221 rows x 6 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "minMaxScaler = MinMaxScaler()\n",
    "print(minMaxScaler.fit(weight_df.iloc[:,[1,2,3,4,5]]))\n",
    "weight_df_stdScaled = minMaxScaler.transform(weight_df.iloc[:,[1,2,3,4,5]])\n",
    "weight_df_stdScaled=pd.DataFrame(weight_df_stdScaled, columns=[\"버정거리총합\",\"상호개수\",\"교통사고건수\",\"보호구역개수\",\"화재발생건수\"])\n",
    "weight_df_stdScaled[\"주유소명\"]=weight_df[\"주유소명\"][:]\n",
    "weight_df_stdScaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "weight_df_stdScaled.to_csv(city_list[i]+\" 스케일링완료.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ########## 여기까지1 - 스케일링 완, 가중치 미완(lr용) ############"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 가중치 매핑 함수\n",
    "새로운 데이터 프레임 만들어서 '상호'와 가중치1,2,3,4,5 넣고 총합 마지막에 하고 sort해서 [:20] 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 가산\n",
    "주유소_count_list=반경이내_개수_리스트(2, gas_station_df, gas_station_df,'상호')\n",
    "\n",
    "distance_list=거리총합리스트(gas_station_df, bus_station_df, '상호')\n",
    "\n",
    "교통사고_count_list=반경이내_개수_리스트(2, gas_station_df, accident_df,'상호')\n",
    "### 감점\n",
    "유치원_count_list=반경이내_개수_리스트(2, gas_station_df, kinder_df, '상호')\n",
    "\n",
    "유초중고_count_list=반경이내_개수_리스트(2, gas_station_df, school_df, '상호')\n",
    "\n",
    "화재_count_list=반경이내_개수_리스트(2, gas_station_df, fire_incident_df, '상호')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# **주유소 순서 헤치지 말 것**\n",
    "#columns=['버정거리총합', '상호개수', '교통사고건수','보호구역개수','화재발생건수',주유소명'])\n",
    "def 가중치추가(df, ratio_list):\n",
    "    for i in range(0,len(df.loc[0])-2):\n",
    "        df['총 가중치']+=df.iloc[:,i]*ratio_list[i]# weight_df는 주유소명부터, ratio_list는 버정거리총합부터 시작하므로\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\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>버정거리총합</th>\n",
       "      <th>상호개수</th>\n",
       "      <th>교통사고건수</th>\n",
       "      <th>보호구역개수</th>\n",
       "      <th>화재발생건수</th>\n",
       "      <th>주유소명</th>\n",
       "      <th>총 가중치</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.006667</td>\n",
       "      <td>0.09375</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013699</td>\n",
       "      <td>SK행복충전 불모가스충전소</td>\n",
       "      <td>0.008012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.31250</td>\n",
       "      <td>0.320896</td>\n",
       "      <td>0.431034</td>\n",
       "      <td>0.356164</td>\n",
       "      <td>동부2</td>\n",
       "      <td>-0.014900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.413333</td>\n",
       "      <td>0.56250</td>\n",
       "      <td>0.236940</td>\n",
       "      <td>0.189655</td>\n",
       "      <td>0.232877</td>\n",
       "      <td>(유)공단가스산업</td>\n",
       "      <td>0.038104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.533333</td>\n",
       "      <td>0.43750</td>\n",
       "      <td>0.330224</td>\n",
       "      <td>0.293103</td>\n",
       "      <td>0.410959</td>\n",
       "      <td>광신직영(두대충전소)</td>\n",
       "      <td>0.006899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.560000</td>\n",
       "      <td>0.46875</td>\n",
       "      <td>0.378731</td>\n",
       "      <td>0.293103</td>\n",
       "      <td>0.589041</td>\n",
       "      <td>SK행복충전 유남충전소(주)배성에너지</td>\n",
       "      <td>-0.002906</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     버정거리총합     상호개수    교통사고건수    보호구역개수    화재발생건수                  주유소명  \\\n",
       "0  0.006667  0.09375  0.000000  0.000000  0.013699        SK행복충전 불모가스충전소   \n",
       "1  0.480000  0.31250  0.320896  0.431034  0.356164                   동부2   \n",
       "2  0.413333  0.56250  0.236940  0.189655  0.232877             (유)공단가스산업   \n",
       "3  0.533333  0.43750  0.330224  0.293103  0.410959           광신직영(두대충전소)   \n",
       "4  0.560000  0.46875  0.378731  0.293103  0.589041  SK행복충전 유남충전소(주)배성에너지   \n",
       "\n",
       "      총 가중치  \n",
       "0  0.008012  \n",
       "1 -0.014900  \n",
       "2  0.038104  \n",
       "3  0.006899  \n",
       "4 -0.002906  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weight_df_stdScaled[\"총 가중치\"]=0 # 혹시 모를 사고에 대비\n",
    "ratio_list=[0.001,0.1,0.1,-0.1,-0.1] # 뒤에 두개 음수 필수\n",
    "가중치추가(weight_df_stdScaled, ratio_list)\n",
    "weight_df_stdScaled.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\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>버정거리총합</th>\n",
       "      <th>상호개수</th>\n",
       "      <th>교통사고건수</th>\n",
       "      <th>보호구역개수</th>\n",
       "      <th>화재발생건수</th>\n",
       "      <th>주유소명</th>\n",
       "      <th>총 가중치</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.733333</td>\n",
       "      <td>0.71875</td>\n",
       "      <td>0.809701</td>\n",
       "      <td>0.431034</td>\n",
       "      <td>0.369863</td>\n",
       "      <td>CJ대한통운㈜ 오동동셀프주유소</td>\n",
       "      <td>0.073489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.893333</td>\n",
       "      <td>0.90625</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.689655</td>\n",
       "      <td>0.506849</td>\n",
       "      <td>금강주유소</td>\n",
       "      <td>0.071868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.65625</td>\n",
       "      <td>0.800373</td>\n",
       "      <td>0.431034</td>\n",
       "      <td>0.369863</td>\n",
       "      <td>지에스칼텍스㈜ 마산월드주유소</td>\n",
       "      <td>0.066273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.853333</td>\n",
       "      <td>0.87500</td>\n",
       "      <td>0.930970</td>\n",
       "      <td>0.758621</td>\n",
       "      <td>0.506849</td>\n",
       "      <td>성운주유소</td>\n",
       "      <td>0.054903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.880000</td>\n",
       "      <td>0.90625</td>\n",
       "      <td>0.936567</td>\n",
       "      <td>0.706897</td>\n",
       "      <td>0.602740</td>\n",
       "      <td>합포주유소</td>\n",
       "      <td>0.054198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>0.793333</td>\n",
       "      <td>0.18750</td>\n",
       "      <td>0.598881</td>\n",
       "      <td>0.844828</td>\n",
       "      <td>0.767123</td>\n",
       "      <td>신월주유소</td>\n",
       "      <td>-0.081764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.15625</td>\n",
       "      <td>0.335821</td>\n",
       "      <td>0.793103</td>\n",
       "      <td>0.534247</td>\n",
       "      <td>지에스칼텍스㈜ 감동주유소</td>\n",
       "      <td>-0.082861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>0.706667</td>\n",
       "      <td>0.15625</td>\n",
       "      <td>0.333955</td>\n",
       "      <td>0.810345</td>\n",
       "      <td>0.534247</td>\n",
       "      <td>남창원농협주유소</td>\n",
       "      <td>-0.084732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>0.733333</td>\n",
       "      <td>0.21875</td>\n",
       "      <td>0.647388</td>\n",
       "      <td>0.931034</td>\n",
       "      <td>0.890411</td>\n",
       "      <td>동부3</td>\n",
       "      <td>-0.094797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>0.773333</td>\n",
       "      <td>0.15625</td>\n",
       "      <td>0.337687</td>\n",
       "      <td>0.913793</td>\n",
       "      <td>0.616438</td>\n",
       "      <td>SK창성가스(주)배성 SK행복충전</td>\n",
       "      <td>-0.102856</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>221 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       버정거리총합     상호개수    교통사고건수    보호구역개수    화재발생건수                주유소명  \\\n",
       "0    0.733333  0.71875  0.809701  0.431034  0.369863    CJ대한통운㈜ 오동동셀프주유소   \n",
       "1    0.893333  0.90625  1.000000  0.689655  0.506849               금강주유소   \n",
       "2    0.700000  0.65625  0.800373  0.431034  0.369863     지에스칼텍스㈜ 마산월드주유소   \n",
       "3    0.853333  0.87500  0.930970  0.758621  0.506849               성운주유소   \n",
       "4    0.880000  0.90625  0.936567  0.706897  0.602740               합포주유소   \n",
       "..        ...      ...       ...       ...       ...                 ...   \n",
       "216  0.793333  0.18750  0.598881  0.844828  0.767123               신월주유소   \n",
       "217  0.666667  0.15625  0.335821  0.793103  0.534247       지에스칼텍스㈜ 감동주유소   \n",
       "218  0.706667  0.15625  0.333955  0.810345  0.534247            남창원농협주유소   \n",
       "219  0.733333  0.21875  0.647388  0.931034  0.890411                 동부3   \n",
       "220  0.773333  0.15625  0.337687  0.913793  0.616438  SK창성가스(주)배성 SK행복충전   \n",
       "\n",
       "        총 가중치  \n",
       "0    0.073489  \n",
       "1    0.071868  \n",
       "2    0.066273  \n",
       "3    0.054903  \n",
       "4    0.054198  \n",
       "..        ...  \n",
       "216 -0.081764  \n",
       "217 -0.082861  \n",
       "218 -0.084732  \n",
       "219 -0.094797  \n",
       "220 -0.102856  \n",
       "\n",
       "[221 rows x 7 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weight_df_stdScaled.sort_values(by=[\"총 가중치\", \"주유소명\"], ascending=[False, False], inplace=True) \n",
    "weight_df_stdScaled = weight_df_stdScaled.reset_index(drop=True)\n",
    "weight_df_stdScaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#weight_df_stdScaled_sorted.to_csv(city_list[2]+\" 가중치.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ########## 여기까지2 - 스케일링, 가중치 모두 완 (f1용)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 정확도 나타내기\n",
    "- lr\n",
    "- f1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "list index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-49-c538206fbb1b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# 실제 data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mguess_df\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcity_list\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;34m\" data 경도 위도 매핑/\"\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mcity_list\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;34m\"_충전소.csv\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[0mguess_df\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIndexError\u001b[0m: list index out of range"
     ]
    }
   ],
   "source": [
    "# 실제 data\n",
    "guess_df=pd.read_csv(city_list[i]+\" data 경도 위도 매핑/\"+city_list[i]+\"_충전소.csv\")\n",
    "guess_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>주유소명</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CJ대한통운㈜ 오동동셀프주유소</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>금강주유소</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>지에스칼텍스㈜ 마산월드주유소</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>성운주유소</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>합포주유소</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>신월주유소</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>지에스칼텍스㈜ 감동주유소</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>남창원농협주유소</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>동부3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>SK창성가스(주)배성 SK행복충전</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>221 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   주유소명  label\n",
       "0      CJ대한통운㈜ 오동동셀프주유소      0\n",
       "1                 금강주유소      0\n",
       "2       지에스칼텍스㈜ 마산월드주유소      0\n",
       "3                 성운주유소      0\n",
       "4                 합포주유소      0\n",
       "..                  ...    ...\n",
       "216               신월주유소      0\n",
       "217       지에스칼텍스㈜ 감동주유소      0\n",
       "218            남창원농협주유소      0\n",
       "219                 동부3      0\n",
       "220  SK창성가스(주)배성 SK행복충전      0\n",
       "\n",
       "[221 rows x 2 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 실제를 전체 주유소에 대입\n",
    "labels_df=pd.DataFrame([[0]*2]*len(weight_df_stdScaled), columns=['주유소명','label'])\n",
    "labels_df['주유소명']=weight_df_stdScaled['주유소명']\n",
    "for i in range(len(guess_df)):\n",
    "    if labels_df['주유소명'][i]==guess_df['충전소'][i]:\n",
    "        labels_df['label'][i]+=1\n",
    "labels_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "weight_df_stdScaled_sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-52-fa74eba53aec>:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  eval_df['label'][:len(guess_df)]=1#일단 그냥 추측 개수 같게 했다,,\n",
      "C:\\Users\\user\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:670: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  iloc._setitem_with_indexer(indexer, value)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>주유소명</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CJ대한통운㈜ 오동동셀프주유소</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>금강주유소</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>지에스칼텍스㈜ 마산월드주유소</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>성운주유소</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>합포주유소</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>신월주유소</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>지에스칼텍스㈜ 감동주유소</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>남창원농협주유소</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>동부3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>SK창성가스(주)배성 SK행복충전</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>221 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   주유소명  label\n",
       "0      CJ대한통운㈜ 오동동셀프주유소      1\n",
       "1                 금강주유소      1\n",
       "2       지에스칼텍스㈜ 마산월드주유소      1\n",
       "3                 성운주유소      1\n",
       "4                 합포주유소      1\n",
       "..                  ...    ...\n",
       "216               신월주유소      0\n",
       "217       지에스칼텍스㈜ 감동주유소      0\n",
       "218            남창원농협주유소      0\n",
       "219                 동부3      0\n",
       "220  SK창성가스(주)배성 SK행복충전      0\n",
       "\n",
       "[221 rows x 2 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# weight_df_sorted 상위 10개 label에 1 넣음\n",
    "eval_df=pd.DataFrame([[0]*2]*len(weight_df_stdScaled), columns=['주유소명','label'])\n",
    "weight_df_stdScaled.sort_values(by=[\"총 가중치\", \"주유소명\"], ascending=[False, False], inplace=True) \n",
    "eval_df['주유소명']=weight_df_stdScaled['주유소명'][:]\n",
    "eval_df['label'][:len(guess_df)]=1#일단 그냥 추측 개수 같게 했다,,\n",
    "eval_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      0\n",
       "1      0\n",
       "2      0\n",
       "3      0\n",
       "4      0\n",
       "      ..\n",
       "216    0\n",
       "217    0\n",
       "218    0\n",
       "219    0\n",
       "220    0\n",
       "Name: label, Length: 221, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 전체 충전소 개수 중 guess의 개수 안에 있는 충전소 개수\n",
    "from sklearn.metrics import accuracy_score, recall_score, precision_score, f1_score\n",
    "eval_df['label']=0\n",
    "# eval_df.columns=['주유소명','label']\n",
    "for i in range(len(guess_df)):\n",
    "    if guess_df['충전소'][i]==eval_df['주유소명'][i]:\n",
    "        eval_df['label'][i]+=1\n",
    "\n",
    "eval_df.sort_values(by=[\"주유소명\"], ascending=[False]) \n",
    "guess_df.sort_values(by=[\"충전소\"], ascending=[False]) \n",
    "# 원래 친구\n",
    "labels=labels_df['label']\n",
    "# 추정한 친구\n",
    "guesses=eval_df['label']\n",
    "guesses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0\n",
      "0.0\n",
      "0.0\n",
      "0.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\user\\anaconda3\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1221: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 due to no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "C:\\Users\\user\\anaconda3\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1221: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "C:\\Users\\user\\anaconda3\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1464: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 due to no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(\n"
     ]
    }
   ],
   "source": [
    "print(accuracy_score(labels, guesses))\n",
    "print(recall_score(labels, guesses))\n",
    "print(precision_score(labels, guesses))\n",
    "print(f1_score(labels, guesses))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 동 매핑"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "동이랑 통행속도 매핑\n",
    "\n",
    "gas_station_df['주소']-도로 이름 나오니까 그냥 사용\n",
    "\n",
    "travel_speed['도로명'], ['속도']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>도로명</th>\n",
       "      <th>속도</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>혁신로</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>기지로</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>쑥고개로</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>권삼득로</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    도로명  속도\n",
       "0   혁신로  20\n",
       "1   기지로  30\n",
       "2  쑥고개로  10\n",
       "3  권삼득로  33"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 그냥 대충 만든 거\n",
    "travel_speed=pd.DataFrame([['혁신로', 20],['기지로', 30],['쑥고개로', 10],['권삼득로', 33]], columns=['도로명','속도'])\n",
    "travel_speed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <td>경남 창원시 성산구 창원대로 1310 (불모산동)</td>\n",
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       "      <td>동부2</td>\n",
       "      <td>경남 창원시 진해구 진해대로 732 (석동)</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(유)공단가스산업</td>\n",
       "      <td>경남 창원시 마산회원구 봉암공단8길 2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>광신직영(두대충전소)</td>\n",
       "      <td>경남 창원시 의창구 남면로 3 (대원동)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SK행복충전 유남충전소(주)배성에너지</td>\n",
       "      <td>경남 창원시 의창구 창원대로 314 (팔용동)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>판도라주유소</td>\n",
       "      <td>경남 창원시 마산합포구 진동면 삼진의거대로 753</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>진웅</td>\n",
       "      <td>경남 창원시 진해구 웅천로 156 (북부동)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>광신직영(호원셀프)</td>\n",
       "      <td>경남 창원시 마산회원구 내서읍 호원로 141</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>야구장주유소</td>\n",
       "      <td>경남 창원시 마산합포구 용마로 62</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>광신석유(주)직영 산호주유소</td>\n",
       "      <td>경남 창원시 마산합포구 합포로 191 (산호동)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>221 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   주유소_이름                           주소  통행속도_w  a  b\n",
       "0          SK행복충전 불모가스충전소  경남 창원시 성산구 창원대로 1310 (불모산동)       0  0  0\n",
       "1                     동부2     경남 창원시 진해구 진해대로 732 (석동)       0  0  0\n",
       "2               (유)공단가스산업        경남 창원시 마산회원구 봉암공단8길 2       0  0  0\n",
       "3             광신직영(두대충전소)       경남 창원시 의창구 남면로 3 (대원동)       0  0  0\n",
       "4    SK행복충전 유남충전소(주)배성에너지    경남 창원시 의창구 창원대로 314 (팔용동)       0  0  0\n",
       "..                    ...                          ...     ... .. ..\n",
       "216                판도라주유소  경남 창원시 마산합포구 진동면 삼진의거대로 753       0  0  0\n",
       "217                    진웅     경남 창원시 진해구 웅천로 156 (북부동)       0  0  0\n",
       "218            광신직영(호원셀프)     경남 창원시 마산회원구 내서읍 호원로 141       0  0  0\n",
       "219                야구장주유소          경남 창원시 마산합포구 용마로 62       0  0  0\n",
       "220       광신석유(주)직영 산호주유소   경남 창원시 마산합포구 합포로 191 (산호동)       0  0  0\n",
       "\n",
       "[221 rows x 5 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 가중치 데이터 프레임\n",
    "weight_df=pd.DataFrame([[0]*5]*len(gas_station_df), columns=['주유소_이름', '주소','통행속도_w', 'a', 'b'])\n",
    "weight_df['주유소_이름']=gas_station_df['상호'][:]\n",
    "weight_df['주소']=gas_station_df['주소'][:]\n",
    "weight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndentationError",
     "evalue": "expected an indented block (<ipython-input-32-3dfeeb1f015a>, line 7)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"<ipython-input-32-3dfeeb1f015a>\"\u001b[1;36m, line \u001b[1;32m7\u001b[0m\n\u001b[1;33m    weight_df\u001b[0m\n\u001b[1;37m             ^\u001b[0m\n\u001b[1;31mIndentationError\u001b[0m\u001b[1;31m:\u001b[0m expected an indented block\n"
     ]
    }
   ],
   "source": [
    "for i in range(len(travel_speed)):\n",
    "    for j in range(len(gas_station_df)):\n",
    "        if travel_speed.loc[i]['도로명'] in gas_station_df.loc[j]['주소']:\n",
    "            # gas_station_df.loc[j]['상호']\n",
    "            # 하는 중\n",
    "            # weight_df.iloc['주유소_이름']['통행속도_w']+=1\n",
    "weight_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\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>Unnamed: 0</th>\n",
       "      <th>주유소명</th>\n",
       "      <th>버정거리총합</th>\n",
       "      <th>상호개수</th>\n",
       "      <th>교통사고건수</th>\n",
       "      <th>보호구역개수</th>\n",
       "      <th>화재발생건수</th>\n",
       "      <th>총 가중치</th>\n",
       "      <th>주소</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>직영충전소</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1.604</td>\n",
       "      <td>전북 전주시 덕진구  혁신로 360번지</td>\n",
       "      <td>35.864542</td>\n",
       "      <td>127.069401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>(유)삼영에너지</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5.000</td>\n",
       "      <td>전북 전주시 완산구 쑥고개로 11 (용복동)</td>\n",
       "      <td>35.790810</td>\n",
       "      <td>127.068859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>(유)푸른기업충전소</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.105</td>\n",
       "      <td>전북 전주시 완산구  모악로 4483 (석구동)</td>\n",
       "      <td>35.786460</td>\n",
       "      <td>127.128841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>㈜진성에너지 색장충전소</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4.204</td>\n",
       "      <td>전북 전주시 완산구 춘향로 4900 (색장동)</td>\n",
       "      <td>35.785086</td>\n",
       "      <td>127.195279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>전주유성LPG충전소</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4.740</td>\n",
       "      <td>전북 전주시 완산구  춘향로 4981</td>\n",
       "      <td>35.786834</td>\n",
       "      <td>127.193891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>193</td>\n",
       "      <td>(주)안국에너지 호반주유소</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.105</td>\n",
       "      <td>전북 전주시 덕진구 기린대로 600 (덕진동2가)</td>\n",
       "      <td>35.846412</td>\n",
       "      <td>127.110653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>194</td>\n",
       "      <td>동아주유소</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000</td>\n",
       "      <td>전북 전주시 완산구 모악로 4741 (평화동2가)</td>\n",
       "      <td>35.792515</td>\n",
       "      <td>127.131511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>195</td>\n",
       "      <td>중앙주유소</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2.886</td>\n",
       "      <td>전북 전주시 덕진구 전미로 148 (전미동2가)</td>\n",
       "      <td>35.882328</td>\n",
       "      <td>127.110466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>196</td>\n",
       "      <td>덕산주유소</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4.204</td>\n",
       "      <td>전북 전주시 완산구 춘향로 4923 (색장동)</td>\n",
       "      <td>35.782581</td>\n",
       "      <td>127.197516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>197</td>\n",
       "      <td>새로운주유소</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.105</td>\n",
       "      <td>전북 전주시 완산구 문화광장로 22</td>\n",
       "      <td>35.822560</td>\n",
       "      <td>127.146518</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>198 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0            주유소명  버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수  총 가중치  \\\n",
       "0             0           직영충전소       2     1       1       5       1  1.604   \n",
       "1             1        (유)삼영에너지       5     5       5       5       5  5.000   \n",
       "2             2      (유)푸른기업충전소       1     4       1       1       1  1.105   \n",
       "3             3    ㈜진성에너지 색장충전소       5     5       4       1       5  4.204   \n",
       "4             4      전주유성LPG충전소       5     5       4       5       5  4.740   \n",
       "..          ...             ...     ...   ...     ...     ...     ...    ...   \n",
       "193         193  (주)안국에너지 호반주유소       1     4       1       1       1  1.105   \n",
       "194         194           동아주유소       1     1       1       1       1  1.000   \n",
       "195         195           중앙주유소       4     5       1       5       3  2.886   \n",
       "196         196           덕산주유소       5     5       4       1       5  4.204   \n",
       "197         197          새로운주유소       1     4       1       1       1  1.105   \n",
       "\n",
       "                              주소         위도          경도  \n",
       "0          전북 전주시 덕진구  혁신로 360번지  35.864542  127.069401  \n",
       "1       전북 전주시 완산구 쑥고개로 11 (용복동)  35.790810  127.068859  \n",
       "2     전북 전주시 완산구  모악로 4483 (석구동)  35.786460  127.128841  \n",
       "3      전북 전주시 완산구 춘향로 4900 (색장동)  35.785086  127.195279  \n",
       "4           전북 전주시 완산구  춘향로 4981  35.786834  127.193891  \n",
       "..                           ...        ...         ...  \n",
       "193  전북 전주시 덕진구 기린대로 600 (덕진동2가)  35.846412  127.110653  \n",
       "194  전북 전주시 완산구 모악로 4741 (평화동2가)  35.792515  127.131511  \n",
       "195   전북 전주시 덕진구 전미로 148 (전미동2가)  35.882328  127.110466  \n",
       "196    전북 전주시 완산구 춘향로 4923 (색장동)  35.782581  127.197516  \n",
       "197          전북 전주시 완산구 문화광장로 22  35.822560  127.146518  \n",
       "\n",
       "[198 rows x 11 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score_df=pd.read_csv(\"점수계산끝.csv\")\n",
    "score_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
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       "      <th>경도</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>(유)삼영에너지</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>전북 전주시 완산구 쑥고개로 11 (용복동)</td>\n",
       "      <td>35.790810</td>\n",
       "      <td>127.068859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>159</td>\n",
       "      <td>동양주유소</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>전북 전주시 덕진구 전미로 231 (전미동2가)</td>\n",
       "      <td>35.888497</td>\n",
       "      <td>127.105103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>179</td>\n",
       "      <td>석구주유소</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>전북 전주시 완산구 구이로 1828 (석구동)</td>\n",
       "      <td>35.761439</td>\n",
       "      <td>127.125947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>94</td>\n",
       "      <td>서린2주유소</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>전북 전주시 완산구 선비로 1444 (용복동)</td>\n",
       "      <td>35.790174</td>\n",
       "      <td>127.068150</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0      주유소명  버정거리총합  상호개수  교통사고건수  보호구역개수  화재발생건수  총 가중치  \\\n",
       "1             1  (유)삼영에너지       5     5       5       5       5    5.0   \n",
       "159         159     동양주유소       5     5       5       5       5    5.0   \n",
       "179         179     석구주유소       5     5       5       5       5    5.0   \n",
       "94           94    서린2주유소       5     5       5       5       5    5.0   \n",
       "\n",
       "                             주소         위도          경도  \n",
       "1      전북 전주시 완산구 쑥고개로 11 (용복동)  35.790810  127.068859  \n",
       "159  전북 전주시 덕진구 전미로 231 (전미동2가)  35.888497  127.105103  \n",
       "179   전북 전주시 완산구 구이로 1828 (석구동)  35.761439  127.125947  \n",
       "94    전북 전주시 완산구 선비로 1444 (용복동)  35.790174  127.068150  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score_df.sort_values(by=[\"총 가중치\"], ascending=[False], inplace=True) \n",
    "score_df[:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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