11-national-pension.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PUnYQI8bKSVR"
   },
   "source": [
    "## 국민연금 가입자 조회"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "pEHzGi-9KSVT"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import warnings\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "pd.set_option('display.float_format',  '{:.1f}'.format)\n",
    "pd.set_option('display.max_columns', None)\n",
    "\n",
    "plt.rcParams['font.family'] = \"AppleGothic\"\n",
    "\n",
    "DATA_DIR = '.'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NclkdShPKq-P"
   },
   "source": [
    "\n",
    "### 데이터 (국민연금공단_국민연금 가입 사업장 내역)\n",
    "\n",
    "- 데이터셋 출처: 공공 데이터 포털(data.go.kr) **2022년 12월 19일 기준** 데이터\n",
    "- 형태: 파일데이터 (csv)\n",
    "\n",
    "사업장 컬럼별 상세설명\n",
    "\n",
    "- 자료생성년월 → 자격마감일(사유발생일이 속하는 달의 다음달 15일)까지 신고분 반영\n",
    "- 당월고지금액 → 국민연금법 시행령 제5조에 의거 기준소득월액 상한액 적용으로 실제소득과 고지금액은 상이할 수 있음\n",
    "\n",
    "  - ■ 상한액 2019.7.~2020.6. 4,860,000원(2019.7.1.기준)\n",
    "  - ■ 상한액 2020.7.~2021.6. 5,030,000원(2020.7.1.기준)\n",
    "  - ■ 상한액 2021.7.~2022.6. 5,240,000원(2021.7.1.기준)\n",
    "\n",
    "- 신규취득자수 → 납부재개 포함 : ※ 전달 고지대상자와 비교하므로 실제 취득자와 상이할 수 있음 (초일취득 (고지)초일이 아닌경우 (당월 미고지되며 다음달 취득자수에 반영)\n",
    "- 상실가입자수 → 납부예외 포함 : ※ 전달 고지대상자와 비교하므로 실제 퇴사자와 상이할 수 있음 (초일이 아닌 상실자는 다음달 상실자수에 반영)\n",
    "\n",
    "※ 국민연금법 제6조, 8조, 동법 시행령 제18조에 의거 60세 도달하거나 퇴직연금수급자, 조기노령연금 수급권을 취득한 자는 가입대상에서 제외되며, 18세미만, 기초수급자는 본인희망에 의해 제외될 수 있음"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "id": "9q5F8utUKSVY"
   },
   "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>자료생성년월</th>\n",
       "      <th>사업장명</th>\n",
       "      <th>사업자등록번호</th>\n",
       "      <th>사업장가입상태코드 1 등록 2 탈퇴</th>\n",
       "      <th>우편번호</th>\n",
       "      <th>사업장지번상세주소</th>\n",
       "      <th>사업장도로명상세주소</th>\n",
       "      <th>고객법정동주소코드</th>\n",
       "      <th>고객행정동주소코드</th>\n",
       "      <th>법정동주소광역시도코드</th>\n",
       "      <th>법정동주소광역시시군구코드</th>\n",
       "      <th>법정동주소광역시시군구읍면동코드</th>\n",
       "      <th>사업장형태구분코드 1 법인 2 개인</th>\n",
       "      <th>사업장업종코드</th>\n",
       "      <th>사업장업종코드명</th>\n",
       "      <th>적용일자</th>\n",
       "      <th>재등록일자</th>\n",
       "      <th>탈퇴일자</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>당월고지금액</th>\n",
       "      <th>신규취득자수</th>\n",
       "      <th>상실가입자수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-12</td>\n",
       "      <td>우성기전(주)</td>\n",
       "      <td>126811</td>\n",
       "      <td>1</td>\n",
       "      <td>12816</td>\n",
       "      <td>경기도 광주시 도척면</td>\n",
       "      <td>경기도 광주시 도척면 도척윗로</td>\n",
       "      <td>4161033025</td>\n",
       "      <td>4161033025</td>\n",
       "      <td>41</td>\n",
       "      <td>610</td>\n",
       "      <td>330</td>\n",
       "      <td>1</td>\n",
       "      <td>292201</td>\n",
       "      <td>동력식 수지 공구 제조업</td>\n",
       "      <td>1988-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>899980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-12</td>\n",
       "      <td>서능공원묘지운영회(재)</td>\n",
       "      <td>102820</td>\n",
       "      <td>1</td>\n",
       "      <td>11191</td>\n",
       "      <td>경기도 포천시 내촌면</td>\n",
       "      <td></td>\n",
       "      <td>4165032022</td>\n",
       "      <td>4165032022</td>\n",
       "      <td>41</td>\n",
       "      <td>650</td>\n",
       "      <td>320</td>\n",
       "      <td>1</td>\n",
       "      <td>701700</td>\n",
       "      <td>화장터 운영  묘지 분양 및 관리업</td>\n",
       "      <td>1988-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11</td>\n",
       "      <td>3278020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-12</td>\n",
       "      <td>노들새마을금고</td>\n",
       "      <td>108820</td>\n",
       "      <td>1</td>\n",
       "      <td>06923</td>\n",
       "      <td>서울특별시 동작구 노량진동</td>\n",
       "      <td>서울특별시 동작구 만양로</td>\n",
       "      <td>1159010100</td>\n",
       "      <td>1159051000</td>\n",
       "      <td>11</td>\n",
       "      <td>590</td>\n",
       "      <td>101</td>\n",
       "      <td>1</td>\n",
       "      <td>659202</td>\n",
       "      <td>신용조합</td>\n",
       "      <td>1988-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>4956440</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    자료생성년월          사업장명  사업자등록번호  사업장가입상태코드 1 등록 2 탈퇴   우편번호       사업장지번상세주소  \\\n",
       "0  2022-12       우성기전(주)   126811                    1  12816     경기도 광주시 도척면   \n",
       "1  2022-12  서능공원묘지운영회(재)   102820                    1  11191     경기도 포천시 내촌면   \n",
       "2  2022-12       노들새마을금고   108820                    1  06923  서울특별시 동작구 노량진동   \n",
       "\n",
       "         사업장도로명상세주소   고객법정동주소코드   고객행정동주소코드  법정동주소광역시도코드  법정동주소광역시시군구코드  \\\n",
       "0  경기도 광주시 도척면 도척윗로  4161033025  4161033025           41            610   \n",
       "1                    4165032022  4165032022           41            650   \n",
       "2     서울특별시 동작구 만양로  1159010100  1159051000           11            590   \n",
       "\n",
       "   법정동주소광역시시군구읍면동코드  사업장형태구분코드 1 법인 2 개인 사업장업종코드             사업장업종코드명  \\\n",
       "0               330                    1  292201        동력식 수지 공구 제조업   \n",
       "1               320                    1  701700  화장터 운영  묘지 분양 및 관리업   \n",
       "2               101                    1  659202                 신용조합   \n",
       "\n",
       "         적용일자 재등록일자 탈퇴일자  가입자수   당월고지금액  신규취득자수  상실가입자수  \n",
       "0  1988-01-01   NaN  NaN     4   899980       0       0  \n",
       "1  1988-01-01   NaN  NaN    11  3278020       0       0  \n",
       "2  1988-01-01   NaN  NaN    12  4956440       0       0  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(os.path.join(DATA_DIR, 'national-pension.csv'), encoding='cp949')\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "원본 DataFrame을 다음의 컬럼명으로 변경하세요\n",
    "- **삭제**로 표기된 컬럼은 삭제 합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "|                          변경 전 | 변경 후                 |\n",
    "| -------------------------------: | ----------------------- |\n",
    "|                     자료생성년월 | **삭제**                |\n",
    "|                         사업장명 | 사업장명                |\n",
    "|                   사업자등록번호 | 사업자등록번호          |\n",
    "| 사업장가입상태코드 1 등록 2 탈퇴 | 가입상태                |\n",
    "|                         우편번호 | **우편번호**            |\n",
    "|               사업장지번상세주소 | **삭제**                |\n",
    "|             사업장도로명상세주소 | 주소                    |\n",
    "|               고객법정동주소코드 | **삭제**                |\n",
    "|               고객행정동주소코드 | **삭제**                |\n",
    "|           법정동주소광역시도코드 | 시도코드                |\n",
    "|       법정동주소광역시시군구코드 | 시군구코드              |\n",
    "| 법정동주소광역시시군구읍면동코드 | 읍면동코드              |\n",
    "| 사업장형태구분코드 1 법인 2 개인 | **삭제**                |\n",
    "|                   사업장업종코드 | 업종코드                |\n",
    "|                 사업장업종코드명 | 업종코드명              |\n",
    "|                         적용일자 | **삭제**                |\n",
    "|                       재등록일자 | **삭제**                |\n",
    "|                         탈퇴일자 | 탈퇴일자                |\n",
    "|                         가입자수 | 가입자수                |\n",
    "|                     당월고지금액 | 금액                    |\n",
    "|                     신규취득자수 | 신규                    |\n",
    "|                     상실가입자수 | 상실                    |\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>사업장명</th>\n",
       "      <th>사업자등록번호</th>\n",
       "      <th>가입상태</th>\n",
       "      <th>주소</th>\n",
       "      <th>시도코드</th>\n",
       "      <th>시군구코드</th>\n",
       "      <th>읍면동코드</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>업종코드명</th>\n",
       "      <th>탈퇴일자</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>금액</th>\n",
       "      <th>신규</th>\n",
       "      <th>상실</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>우성기전(주)</td>\n",
       "      <td>126811</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 광주시 도척면 도척윗로</td>\n",
       "      <td>41</td>\n",
       "      <td>610</td>\n",
       "      <td>330</td>\n",
       "      <td>292201</td>\n",
       "      <td>동력식 수지 공구 제조업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>899980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>서능공원묘지운영회(재)</td>\n",
       "      <td>102820</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td>41</td>\n",
       "      <td>650</td>\n",
       "      <td>320</td>\n",
       "      <td>701700</td>\n",
       "      <td>화장터 운영  묘지 분양 및 관리업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11</td>\n",
       "      <td>3278020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>노들새마을금고</td>\n",
       "      <td>108820</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 동작구 만양로</td>\n",
       "      <td>11</td>\n",
       "      <td>590</td>\n",
       "      <td>101</td>\n",
       "      <td>659202</td>\n",
       "      <td>신용조합</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>4956440</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>유창성업(주)</td>\n",
       "      <td>122812</td>\n",
       "      <td>1</td>\n",
       "      <td>인천광역시 서구 갑문2로</td>\n",
       "      <td>28</td>\n",
       "      <td>260</td>\n",
       "      <td>119</td>\n",
       "      <td>749604</td>\n",
       "      <td>그 외 기타 분류 안된 사업 지원 서비스업(기타임가공</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24</td>\n",
       "      <td>5371000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>희성전자(주)</td>\n",
       "      <td>106810</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 용산구 독서당로14길</td>\n",
       "      <td>11</td>\n",
       "      <td>170</td>\n",
       "      <td>131</td>\n",
       "      <td>701201</td>\n",
       "      <td>비주거용 건물 임대업(점포  자기땅)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>395</td>\n",
       "      <td>187943100</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           사업장명  사업자등록번호  가입상태                 주소  시도코드  시군구코드  읍면동코드    업종코드  \\\n",
       "0       우성기전(주)   126811     1   경기도 광주시 도척면 도척윗로    41    610    330  292201   \n",
       "1  서능공원묘지운영회(재)   102820     1                       41    650    320  701700   \n",
       "2       노들새마을금고   108820     1      서울특별시 동작구 만양로    11    590    101  659202   \n",
       "3       유창성업(주)   122812     1      인천광역시 서구 갑문2로    28    260    119  749604   \n",
       "4       희성전자(주)   106810     1  서울특별시 용산구 독서당로14길    11    170    131  701201   \n",
       "\n",
       "                           업종코드명 탈퇴일자  가입자수         금액  신규  상실  \n",
       "0                  동력식 수지 공구 제조업  NaN     4     899980   0   0  \n",
       "1            화장터 운영  묘지 분양 및 관리업  NaN    11    3278020   0   0  \n",
       "2                           신용조합  NaN    12    4956440   0   0  \n",
       "3  그 외 기타 분류 안된 사업 지원 서비스업(기타임가공  NaN    24    5371000   0   0  \n",
       "4           비주거용 건물 임대업(점포  자기땅)  NaN   395  187943100   0   1  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 코드를 입력해 주세요\n",
    "df.columns = [\n",
    "    '자료생성년월', '사업장명', '사업자등록번호', '가입상태', '우편번호',\n",
    "    '사업장지번상세주소', '주소', '고객법정동주소코드', '고객행정동주소코드', \n",
    "    '시도코드', '시군구코드', '읍면동코드', \n",
    "    '사업장형태구분코드 1 법인 2 개인', '업종코드', '업종코드명', \n",
    "    '적용일자', '재등록일자', '탈퇴일자',\n",
    "    '가입자수', '금액', '신규', '상실'\n",
    "]\n",
    "df = df.drop(['자료생성년월', '우편번호', '사업장지번상세주소', '고객법정동주소코드', '고객행정동주소코드', '사업장형태구분코드 1 법인 2 개인', '적용일자', '재등록일자'], axis=1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 사업장명 클린징\n",
    "\n",
    "- 다음의 예제을 확인한 후 아래 지시사항을 수행해 주세요"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>사업장명</th>\n",
       "      <th>사업자등록번호</th>\n",
       "      <th>가입상태</th>\n",
       "      <th>주소</th>\n",
       "      <th>시도코드</th>\n",
       "      <th>시군구코드</th>\n",
       "      <th>읍면동코드</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>업종코드명</th>\n",
       "      <th>탈퇴일자</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>금액</th>\n",
       "      <th>신규</th>\n",
       "      <th>상실</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>우성기전(주)</td>\n",
       "      <td>126811</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 광주시 도척면 도척윗로</td>\n",
       "      <td>41</td>\n",
       "      <td>610</td>\n",
       "      <td>330</td>\n",
       "      <td>292201</td>\n",
       "      <td>동력식 수지 공구 제조업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>899980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>유창성업(주)</td>\n",
       "      <td>122812</td>\n",
       "      <td>1</td>\n",
       "      <td>인천광역시 서구 갑문2로</td>\n",
       "      <td>28</td>\n",
       "      <td>260</td>\n",
       "      <td>119</td>\n",
       "      <td>749604</td>\n",
       "      <td>그 외 기타 분류 안된 사업 지원 서비스업(기타임가공</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24</td>\n",
       "      <td>5371000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>희성전자(주)</td>\n",
       "      <td>106810</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 용산구 독서당로14길</td>\n",
       "      <td>11</td>\n",
       "      <td>170</td>\n",
       "      <td>131</td>\n",
       "      <td>701201</td>\n",
       "      <td>비주거용 건물 임대업(점포  자기땅)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>395</td>\n",
       "      <td>187943100</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>동성교역(주)</td>\n",
       "      <td>120810</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 강남구 테헤란로87길</td>\n",
       "      <td>11</td>\n",
       "      <td>680</td>\n",
       "      <td>105</td>\n",
       "      <td>171109</td>\n",
       "      <td>화학섬유직물 직조업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>1255560</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>(주)태평양그랜드</td>\n",
       "      <td>105815</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 파주시 직지길</td>\n",
       "      <td>41</td>\n",
       "      <td>480</td>\n",
       "      <td>115</td>\n",
       "      <td>222102</td>\n",
       "      <td>스크린 인쇄업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20</td>\n",
       "      <td>5787280</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        사업장명  사업자등록번호  가입상태                 주소  시도코드  시군구코드  읍면동코드    업종코드  \\\n",
       "0    우성기전(주)   126811     1   경기도 광주시 도척면 도척윗로    41    610    330  292201   \n",
       "3    유창성업(주)   122812     1      인천광역시 서구 갑문2로    28    260    119  749604   \n",
       "4    희성전자(주)   106810     1  서울특별시 용산구 독서당로14길    11    170    131  701201   \n",
       "5    동성교역(주)   120810     1  서울특별시 강남구 테헤란로87길    11    680    105  171109   \n",
       "6  (주)태평양그랜드   105815     1        경기도 파주시 직지길    41    480    115  222102   \n",
       "\n",
       "                           업종코드명 탈퇴일자  가입자수         금액  신규  상실  \n",
       "0                  동력식 수지 공구 제조업  NaN     4     899980   0   0  \n",
       "3  그 외 기타 분류 안된 사업 지원 서비스업(기타임가공  NaN    24    5371000   0   0  \n",
       "4           비주거용 건물 임대업(점포  자기땅)  NaN   395  187943100   0   1  \n",
       "5                     화학섬유직물 직조업  NaN     4    1255560   0   0  \n",
       "6                        스크린 인쇄업  NaN    20    5787280   0   0  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['사업장명'].str.contains('\\(주\\)')].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`우성기전(주)`에서 (주) 라는 글자는 제거하는 경우"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'우성기전'"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Regular Expression(정규화) 모듈 사용\n",
    "import re\n",
    "\n",
    "pattern1 = '(\\([^)]+\\))'\n",
    "re.sub(pattern1, '', '우성기전(주)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "사업장명에서 [] 특수문자를 포함하는 경우 []안쪽 글자까지 제거하는 경우"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>사업장명</th>\n",
       "      <th>사업자등록번호</th>\n",
       "      <th>가입상태</th>\n",
       "      <th>주소</th>\n",
       "      <th>시도코드</th>\n",
       "      <th>시군구코드</th>\n",
       "      <th>읍면동코드</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>업종코드명</th>\n",
       "      <th>탈퇴일자</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>금액</th>\n",
       "      <th>신규</th>\n",
       "      <th>상실</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>115006</th>\n",
       "      <td>에스티테크[주]</td>\n",
       "      <td>606817</td>\n",
       "      <td>1</td>\n",
       "      <td>부산광역시 사하구 감천항로419번길</td>\n",
       "      <td>26</td>\n",
       "      <td>380</td>\n",
       "      <td>107</td>\n",
       "      <td>291502</td>\n",
       "      <td>기타 물품 취급장비 제조업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11</td>\n",
       "      <td>3465060</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161699</th>\n",
       "      <td>게스트하우스 [특별자활]</td>\n",
       "      <td>206826</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 성동구 가람길</td>\n",
       "      <td>11</td>\n",
       "      <td>200</td>\n",
       "      <td>118</td>\n",
       "      <td>999999</td>\n",
       "      <td>BIZ_NO미존재사업장</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13</td>\n",
       "      <td>1671340</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163894</th>\n",
       "      <td>[주)한빛관리 은행대우 3차1단지/ 생활지원센타]</td>\n",
       "      <td>212813</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 시흥시 은행로</td>\n",
       "      <td>41</td>\n",
       "      <td>390</td>\n",
       "      <td>106</td>\n",
       "      <td>702003</td>\n",
       "      <td>비주거용 부동산 관리업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>728260</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168743</th>\n",
       "      <td>비전트레이닝센터[자활사업]</td>\n",
       "      <td>206826</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 성동구 자동차시장길</td>\n",
       "      <td>11</td>\n",
       "      <td>200</td>\n",
       "      <td>122</td>\n",
       "      <td>999999</td>\n",
       "      <td>BIZ_NO미존재사업장</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>467300</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187304</th>\n",
       "      <td>바이오코리아[BIOKOREA]</td>\n",
       "      <td>317826</td>\n",
       "      <td>1</td>\n",
       "      <td>충청북도 청주시 흥덕구 오송읍 오송생명2로</td>\n",
       "      <td>43</td>\n",
       "      <td>113</td>\n",
       "      <td>250</td>\n",
       "      <td>999999</td>\n",
       "      <td>BIZ_NO미존재사업장</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>584640</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               사업장명  사업자등록번호  가입상태                       주소  \\\n",
       "115006                     에스티테크[주]   606817     1      부산광역시 사하구 감천항로419번길   \n",
       "161699                게스트하우스 [특별자활]   206826     1            서울특별시 성동구 가람길   \n",
       "163894  [주)한빛관리 은행대우 3차1단지/ 생활지원센타]   212813     1              경기도 시흥시 은행로   \n",
       "168743               비전트레이닝센터[자활사업]   206826     1         서울특별시 성동구 자동차시장길   \n",
       "187304             바이오코리아[BIOKOREA]   317826     1  충청북도 청주시 흥덕구 오송읍 오송생명2로   \n",
       "\n",
       "        시도코드  시군구코드  읍면동코드    업종코드           업종코드명 탈퇴일자  가입자수       금액  신규  상실  \n",
       "115006    26    380    107  291502  기타 물품 취급장비 제조업  NaN    11  3465060   0   0  \n",
       "161699    11    200    118  999999    BIZ_NO미존재사업장  NaN    13  1671340   2   7  \n",
       "163894    41    390    106  702003    비주거용 부동산 관리업  NaN     3   728260   0   0  \n",
       "168743    11    200    122  999999    BIZ_NO미존재사업장  NaN     7   467300   4   6  \n",
       "187304    43    113    250  999999    BIZ_NO미존재사업장  NaN     3   584640   0   0  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['사업장명'].str.contains('\\[')].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(예시) `에스티테크[주]`에서 [주]를 삭제 하고 싶은 경우"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'에스티테크'"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pattern2 = '(\\[[^)]+\\])'\n",
    "re.sub(pattern2, '', '에스티테크[주]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>사업장명</th>\n",
       "      <th>사업자등록번호</th>\n",
       "      <th>가입상태</th>\n",
       "      <th>주소</th>\n",
       "      <th>시도코드</th>\n",
       "      <th>시군구코드</th>\n",
       "      <th>읍면동코드</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>업종코드명</th>\n",
       "      <th>탈퇴일자</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>금액</th>\n",
       "      <th>신규</th>\n",
       "      <th>상실</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>(주)동양/건재부문</td>\n",
       "      <td>101853</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 영등포구 국제금융로2길</td>\n",
       "      <td>11</td>\n",
       "      <td>560</td>\n",
       "      <td>110</td>\n",
       "      <td>269401</td>\n",
       "      <td>시멘트 제조업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>300</td>\n",
       "      <td>128936960</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4694</th>\n",
       "      <td>(주)한영파트너스FH/월드컵현대아파트</td>\n",
       "      <td>138810</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 서대문구 수색로</td>\n",
       "      <td>11</td>\n",
       "      <td>410</td>\n",
       "      <td>119</td>\n",
       "      <td>702003</td>\n",
       "      <td>비주거용 부동산 관리업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>878660</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18171</th>\n",
       "      <td>의료법인해정의료재단/더좋은병원</td>\n",
       "      <td>502821</td>\n",
       "      <td>1</td>\n",
       "      <td>대구광역시 수성구 명덕로</td>\n",
       "      <td>27</td>\n",
       "      <td>260</td>\n",
       "      <td>105</td>\n",
       "      <td>851101</td>\n",
       "      <td>요양병원</td>\n",
       "      <td>NaN</td>\n",
       "      <td>158</td>\n",
       "      <td>36442640</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22815</th>\n",
       "      <td>안산시청(의료급여사례관리/장애인복지과)</td>\n",
       "      <td>134830</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 안산시 단원구 화랑로</td>\n",
       "      <td>41</td>\n",
       "      <td>273</td>\n",
       "      <td>101</td>\n",
       "      <td>701201</td>\n",
       "      <td>비주거용 건물 임대업(점포  자기땅)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>1716880</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23823</th>\n",
       "      <td>(주)영일에이치오엠/이동그린빌명품</td>\n",
       "      <td>506811</td>\n",
       "      <td>1</td>\n",
       "      <td>경상북도 포항시 남구 대이로</td>\n",
       "      <td>47</td>\n",
       "      <td>111</td>\n",
       "      <td>117</td>\n",
       "      <td>749300</td>\n",
       "      <td>건축물 일반 청소업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>757240</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25083</th>\n",
       "      <td>주/대명부품</td>\n",
       "      <td>204817</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 동대문구 한천로</td>\n",
       "      <td>11</td>\n",
       "      <td>230</td>\n",
       "      <td>105</td>\n",
       "      <td>503003</td>\n",
       "      <td>자동차 중고 부품 및 내장품 판매업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>1132260</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25632</th>\n",
       "      <td>열린노무법인/부산사무소</td>\n",
       "      <td>607851</td>\n",
       "      <td>1</td>\n",
       "      <td>부산광역시 부산진구 동평로</td>\n",
       "      <td>26</td>\n",
       "      <td>230</td>\n",
       "      <td>101</td>\n",
       "      <td>741109</td>\n",
       "      <td>기타 법무관련 서비스업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>687960</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26321</th>\n",
       "      <td>전용부품판매/주</td>\n",
       "      <td>204817</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 동대문구 전농로4길</td>\n",
       "      <td>11</td>\n",
       "      <td>230</td>\n",
       "      <td>105</td>\n",
       "      <td>503003</td>\n",
       "      <td>자동차 중고 부품 및 내장품 판매업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>1106360</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27793</th>\n",
       "      <td>중앙산업(자)/생활폐기물 수집운반 대행사업</td>\n",
       "      <td>138810</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 의왕시 부곡중앙북9길</td>\n",
       "      <td>41</td>\n",
       "      <td>430</td>\n",
       "      <td>103</td>\n",
       "      <td>900100</td>\n",
       "      <td>지정 외 폐기물 수집  운반업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17</td>\n",
       "      <td>7369540</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29327</th>\n",
       "      <td>한우개발(자)/생활폐기물 수집운반 대행사업</td>\n",
       "      <td>138810</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 의왕시 오전천로</td>\n",
       "      <td>41</td>\n",
       "      <td>430</td>\n",
       "      <td>101</td>\n",
       "      <td>900100</td>\n",
       "      <td>지정 외 폐기물 수집  운반업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9</td>\n",
       "      <td>2117980</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          사업장명  사업자등록번호  가입상태                  주소  시도코드  \\\n",
       "1284                (주)동양/건재부문   101853     1  서울특별시 영등포구 국제금융로2길    11   \n",
       "4694      (주)한영파트너스FH/월드컵현대아파트   138810     1      서울특별시 서대문구 수색로    11   \n",
       "18171         의료법인해정의료재단/더좋은병원   502821     1       대구광역시 수성구 명덕로    27   \n",
       "22815    안산시청(의료급여사례관리/장애인복지과)   134830     1     경기도 안산시 단원구 화랑로    41   \n",
       "23823       (주)영일에이치오엠/이동그린빌명품   506811     1     경상북도 포항시 남구 대이로    47   \n",
       "25083                   주/대명부품   204817     1      서울특별시 동대문구 한천로    11   \n",
       "25632             열린노무법인/부산사무소   607851     1      부산광역시 부산진구 동평로    26   \n",
       "26321                 전용부품판매/주   204817     1    서울특별시 동대문구 전농로4길    11   \n",
       "27793  중앙산업(자)/생활폐기물 수집운반 대행사업   138810     1     경기도 의왕시 부곡중앙북9길    41   \n",
       "29327  한우개발(자)/생활폐기물 수집운반 대행사업   138810     1        경기도 의왕시 오전천로    41   \n",
       "\n",
       "       시군구코드  읍면동코드    업종코드                 업종코드명 탈퇴일자  가입자수         금액  신규  \\\n",
       "1284     560    110  269401               시멘트 제조업  NaN   300  128936960   3   \n",
       "4694     410    119  702003          비주거용 부동산 관리업  NaN     3     878660   0   \n",
       "18171    260    105  851101                  요양병원  NaN   158   36442640   3   \n",
       "22815    273    101  701201  비주거용 건물 임대업(점포  자기땅)  NaN     6    1716880   0   \n",
       "23823    111    117  749300            건축물 일반 청소업  NaN     3     757240   0   \n",
       "25083    230    105  503003   자동차 중고 부품 및 내장품 판매업  NaN     3    1132260   0   \n",
       "25632    230    101  741109          기타 법무관련 서비스업  NaN     3     687960   1   \n",
       "26321    230    105  503003   자동차 중고 부품 및 내장품 판매업  NaN     4    1106360   0   \n",
       "27793    430    103  900100      지정 외 폐기물 수집  운반업  NaN    17    7369540   0   \n",
       "29327    430    101  900100      지정 외 폐기물 수집  운반업  NaN     9    2117980   0   \n",
       "\n",
       "       상실  \n",
       "1284    4  \n",
       "4694    0  \n",
       "18171   1  \n",
       "22815   0  \n",
       "23823   0  \n",
       "25083   0  \n",
       "25632   0  \n",
       "26321   0  \n",
       "27793  14  \n",
       "29327   6  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['사업장명'].str.contains('\\/')].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "그 밖의 모든 특수문자는 제거합니다. (제거한 특수문자에는 공백을 삽입합니다)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' 의료법인 해정 의료재단 더 좋은 병원'"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pattern3 = '[^A-Za-z0-9가-힣]'\n",
    "result = re.sub(pattern3, ' ', '*^%$^의료법인%해정^&*****%!@의료재단/더/좋은/병원')\n",
    "result = re.sub(' +', ' ', result)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>사업장명</th>\n",
       "      <th>사업자등록번호</th>\n",
       "      <th>가입상태</th>\n",
       "      <th>주소</th>\n",
       "      <th>시도코드</th>\n",
       "      <th>시군구코드</th>\n",
       "      <th>읍면동코드</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>업종코드명</th>\n",
       "      <th>탈퇴일자</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>금액</th>\n",
       "      <th>신규</th>\n",
       "      <th>상실</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>143146</th>\n",
       "      <td>(주)유원건축사사무소</td>\n",
       "      <td>135811</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 용인시 처인구 중부대로</td>\n",
       "      <td>41</td>\n",
       "      <td>461</td>\n",
       "      <td>102</td>\n",
       "      <td>742105</td>\n",
       "      <td>건축 설계 및 관련 서비스업(건축사)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>125</td>\n",
       "      <td>41319640</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>(주)동양/건재부문</td>\n",
       "      <td>101853</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 영등포구 국제금융로2길</td>\n",
       "      <td>11</td>\n",
       "      <td>560</td>\n",
       "      <td>110</td>\n",
       "      <td>269401</td>\n",
       "      <td>시멘트 제조업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>300</td>\n",
       "      <td>128936960</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24109</th>\n",
       "      <td>서천문화원</td>\n",
       "      <td>309820</td>\n",
       "      <td>1</td>\n",
       "      <td>충청남도 서천군 서천읍 화금서길</td>\n",
       "      <td>44</td>\n",
       "      <td>770</td>\n",
       "      <td>253</td>\n",
       "      <td>999999</td>\n",
       "      <td>BIZ_NO미존재사업장</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>778660</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23092</th>\n",
       "      <td>(주)진양종합건설</td>\n",
       "      <td>214873</td>\n",
       "      <td>1</td>\n",
       "      <td>부산광역시 연제구 중앙대로</td>\n",
       "      <td>26</td>\n",
       "      <td>470</td>\n",
       "      <td>102</td>\n",
       "      <td>451101</td>\n",
       "      <td>아파트 건설업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>887220</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548425</th>\n",
       "      <td>（주）동아산업/일용/평택전자 P3 복합동 신축공사 중 금속공사</td>\n",
       "      <td>312812</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 평택시 삼성로</td>\n",
       "      <td>41</td>\n",
       "      <td>220</td>\n",
       "      <td>128</td>\n",
       "      <td>452102</td>\n",
       "      <td>유리 및 창호 공사업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>1812600</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      사업장명  사업자등록번호  가입상태                  주소  \\\n",
       "143146                         (주)유원건축사사무소   135811     1    경기도 용인시 처인구 중부대로   \n",
       "1284                            (주)동양/건재부문   101853     1  서울특별시 영등포구 국제금융로2길   \n",
       "24109                                서천문화원   309820     1   충청남도 서천군 서천읍 화금서길   \n",
       "23092                            (주)진양종합건설   214873     1      부산광역시 연제구 중앙대로   \n",
       "548425  （주）동아산업/일용/평택전자 P3 복합동 신축공사 중 금속공사   312812     1         경기도 평택시 삼성로   \n",
       "\n",
       "        시도코드  시군구코드  읍면동코드    업종코드                 업종코드명 탈퇴일자  가입자수  \\\n",
       "143146    41    461    102  742105  건축 설계 및 관련 서비스업(건축사)  NaN   125   \n",
       "1284      11    560    110  269401               시멘트 제조업  NaN   300   \n",
       "24109     44    770    253  999999          BIZ_NO미존재사업장  NaN     3   \n",
       "23092     26    470    102  451101               아파트 건설업  NaN     3   \n",
       "548425    41    220    128  452102           유리 및 창호 공사업  NaN     4   \n",
       "\n",
       "               금액  신규  상실  \n",
       "143146   41319640   3   1  \n",
       "1284    128936960   3   4  \n",
       "24109      778660   0   1  \n",
       "23092      887220   0   0  \n",
       "548425    1812600   4   0  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 검증코드 (변경전)\n",
    "df.loc[[143146, 1284, 24109, 23092, 548425]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "위의 제공된 힌트를 참고하여 `사업장명` 컬럼에 대하여 다음 조건의 클린징을 적용해 주세요\n",
    "\n",
    "1. `(주)` 와 같은 문자열은 ()안에 문자를 포함하여 일괄 제거합니다.\n",
    "2. `[주식회사]`와 같이 [] 안에 문자열 포함하여 일괄 제거합니다.\n",
    "3. `숫자`, `한글`, `영어`를 제외한 특수문자는 공백으로 대체 합니다. 만약 공백이 1개 이상이 들어간 경우는 1개로 대체합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 코드를 입력해 주세요\n",
    "def preprocessing(x):\n",
    "    x = re.sub(pattern1, '', x)\n",
    "    x = re.sub(pattern2, '', x)\n",
    "    x = re.sub(pattern3, ' ', x)\n",
    "    x = re.sub(' +', ' ', x)\n",
    "    return x\n",
    "\n",
    "df['사업장명'] = df['사업장명'].apply(preprocessing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>사업장명</th>\n",
       "      <th>사업자등록번호</th>\n",
       "      <th>가입상태</th>\n",
       "      <th>주소</th>\n",
       "      <th>시도코드</th>\n",
       "      <th>시군구코드</th>\n",
       "      <th>읍면동코드</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>업종코드명</th>\n",
       "      <th>탈퇴일자</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>금액</th>\n",
       "      <th>신규</th>\n",
       "      <th>상실</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>143146</th>\n",
       "      <td>유원건축사사무소</td>\n",
       "      <td>135811</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 용인시 처인구 중부대로</td>\n",
       "      <td>41</td>\n",
       "      <td>461</td>\n",
       "      <td>102</td>\n",
       "      <td>742105</td>\n",
       "      <td>건축 설계 및 관련 서비스업(건축사)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>125</td>\n",
       "      <td>41319640</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>동양 건재부문</td>\n",
       "      <td>101853</td>\n",
       "      <td>1</td>\n",
       "      <td>서울특별시 영등포구 국제금융로2길</td>\n",
       "      <td>11</td>\n",
       "      <td>560</td>\n",
       "      <td>110</td>\n",
       "      <td>269401</td>\n",
       "      <td>시멘트 제조업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>300</td>\n",
       "      <td>128936960</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24109</th>\n",
       "      <td>서천문화원</td>\n",
       "      <td>309820</td>\n",
       "      <td>1</td>\n",
       "      <td>충청남도 서천군 서천읍 화금서길</td>\n",
       "      <td>44</td>\n",
       "      <td>770</td>\n",
       "      <td>253</td>\n",
       "      <td>999999</td>\n",
       "      <td>BIZ_NO미존재사업장</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>778660</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23092</th>\n",
       "      <td>진양종합건설</td>\n",
       "      <td>214873</td>\n",
       "      <td>1</td>\n",
       "      <td>부산광역시 연제구 중앙대로</td>\n",
       "      <td>26</td>\n",
       "      <td>470</td>\n",
       "      <td>102</td>\n",
       "      <td>451101</td>\n",
       "      <td>아파트 건설업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>887220</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548425</th>\n",
       "      <td>주 동아산업 일용 평택전자 P3 복합동 신축공사 중 금속공사</td>\n",
       "      <td>312812</td>\n",
       "      <td>1</td>\n",
       "      <td>경기도 평택시 삼성로</td>\n",
       "      <td>41</td>\n",
       "      <td>220</td>\n",
       "      <td>128</td>\n",
       "      <td>452102</td>\n",
       "      <td>유리 및 창호 공사업</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>1812600</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      사업장명  사업자등록번호  가입상태                  주소  \\\n",
       "143146                            유원건축사사무소   135811     1    경기도 용인시 처인구 중부대로   \n",
       "1284                               동양 건재부문   101853     1  서울특별시 영등포구 국제금융로2길   \n",
       "24109                                서천문화원   309820     1   충청남도 서천군 서천읍 화금서길   \n",
       "23092                               진양종합건설   214873     1      부산광역시 연제구 중앙대로   \n",
       "548425   주 동아산업 일용 평택전자 P3 복합동 신축공사 중 금속공사   312812     1         경기도 평택시 삼성로   \n",
       "\n",
       "        시도코드  시군구코드  읍면동코드    업종코드                 업종코드명 탈퇴일자  가입자수  \\\n",
       "143146    41    461    102  742105  건축 설계 및 관련 서비스업(건축사)  NaN   125   \n",
       "1284      11    560    110  269401               시멘트 제조업  NaN   300   \n",
       "24109     44    770    253  999999          BIZ_NO미존재사업장  NaN     3   \n",
       "23092     26    470    102  451101               아파트 건설업  NaN     3   \n",
       "548425    41    220    128  452102           유리 및 창호 공사업  NaN     4   \n",
       "\n",
       "               금액  신규  상실  \n",
       "143146   41319640   3   1  \n",
       "1284    128936960   3   4  \n",
       "24109      778660   0   1  \n",
       "23092      887220   0   0  \n",
       "548425    1812600   4   0  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 검증코드\n",
    "df.loc[[143146, 1284, 24109, 23092, 548425]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 분석"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2022년도에 탈퇴한 기업의 월별 탈퇴 수를 bar그래프로 출력합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 코드를 입력해 주세요\n",
    "df['탈퇴일자_연도'] =  pd.to_datetime(df['탈퇴일자']).dt.year\n",
    "df['탈퇴일자_월'] =  pd.to_datetime(df['탈퇴일자']).dt.month\n",
    "df.loc[(df['가입상태'] == 2) & (df['탈퇴일자_연도'] == 2022), '탈퇴일자_월'].astype('int').value_counts().plot(kind='bar')\n",
    "plt.title('월별 탈퇴 기업수')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2022년도에 탈퇴한 기업을 대상으로 시도별 탈퇴한 기업의 숫자를 bar 그래프로 출력하세요"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           경기도\n",
       "1              \n",
       "2         서울특별시\n",
       "3         인천광역시\n",
       "4         서울특별시\n",
       "          ...  \n",
       "550737         \n",
       "550738         \n",
       "550739         \n",
       "550740         \n",
       "550741         \n",
       "Name: 주소, Length: 550742, dtype: object"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['주소'].str.split(' ').str[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 코드를 입력해 주세요\n",
    "df['시도'] = df['주소'].str.split(' ').str[0]\n",
    "df.loc[(df['가입상태'] == 2) & (df['탈퇴일자_연도'] == 2022) & (df['시도'].apply(lambda x: len(x.strip())) > 0), '시도'].value_counts().plot(kind='bar')\n",
    "plt.title('시도별 탈퇴 기업 수')\n",
    "plt.xticks(rotation=60)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "탈퇴한 기업을 대상으로 상반기 / 하반기별 기업의 탈퇴 수를 비교합니다.\n",
    "- 비교대상은 2017년 ~ 2021년을 기준으로 산정합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 코드를 입력해 주세요\n",
    "cond1 = (df['가입상태'] == 2) & (df['탈퇴일자_연도'] >= 2017) & (df['탈퇴일자_연도'] <= 2021)\n",
    "tmp = df.loc[cond1].copy()\n",
    "tmp['반기'] = np.where(tmp['탈퇴일자_월'] <= 6, '상반기', '하반기')\n",
    "tmp['탈퇴일자_연도'] = tmp['탈퇴일자_연도'].astype('int')\n",
    "sns.countplot(x='탈퇴일자_연도', hue='반기', data=tmp)\n",
    "df = df.drop(['탈퇴일자_연도', '탈퇴일자_월','시도'], axis=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- `가입상태`가 2인 데이터는 삭제 합니다.\n",
    "- `가입상태`, `탈퇴일자` 컬럼을 제거하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape: 522066 행\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>사업장명</th>\n",
       "      <th>사업자등록번호</th>\n",
       "      <th>주소</th>\n",
       "      <th>시도코드</th>\n",
       "      <th>시군구코드</th>\n",
       "      <th>읍면동코드</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>업종코드명</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>금액</th>\n",
       "      <th>신규</th>\n",
       "      <th>상실</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>우성기전</td>\n",
       "      <td>126811</td>\n",
       "      <td>경기도 광주시 도척면 도척윗로</td>\n",
       "      <td>41</td>\n",
       "      <td>610</td>\n",
       "      <td>330</td>\n",
       "      <td>292201</td>\n",
       "      <td>동력식 수지 공구 제조업</td>\n",
       "      <td>4</td>\n",
       "      <td>899980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>서능공원묘지운영회</td>\n",
       "      <td>102820</td>\n",
       "      <td></td>\n",
       "      <td>41</td>\n",
       "      <td>650</td>\n",
       "      <td>320</td>\n",
       "      <td>701700</td>\n",
       "      <td>화장터 운영  묘지 분양 및 관리업</td>\n",
       "      <td>11</td>\n",
       "      <td>3278020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>노들새마을금고</td>\n",
       "      <td>108820</td>\n",
       "      <td>서울특별시 동작구 만양로</td>\n",
       "      <td>11</td>\n",
       "      <td>590</td>\n",
       "      <td>101</td>\n",
       "      <td>659202</td>\n",
       "      <td>신용조합</td>\n",
       "      <td>12</td>\n",
       "      <td>4956440</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>유창성업</td>\n",
       "      <td>122812</td>\n",
       "      <td>인천광역시 서구 갑문2로</td>\n",
       "      <td>28</td>\n",
       "      <td>260</td>\n",
       "      <td>119</td>\n",
       "      <td>749604</td>\n",
       "      <td>그 외 기타 분류 안된 사업 지원 서비스업(기타임가공</td>\n",
       "      <td>24</td>\n",
       "      <td>5371000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>희성전자</td>\n",
       "      <td>106810</td>\n",
       "      <td>서울특별시 용산구 독서당로14길</td>\n",
       "      <td>11</td>\n",
       "      <td>170</td>\n",
       "      <td>131</td>\n",
       "      <td>701201</td>\n",
       "      <td>비주거용 건물 임대업(점포  자기땅)</td>\n",
       "      <td>395</td>\n",
       "      <td>187943100</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        사업장명  사업자등록번호                 주소  시도코드  시군구코드  읍면동코드    업종코드  \\\n",
       "0       우성기전   126811   경기도 광주시 도척면 도척윗로    41    610    330  292201   \n",
       "1  서능공원묘지운영회   102820                       41    650    320  701700   \n",
       "2    노들새마을금고   108820      서울특별시 동작구 만양로    11    590    101  659202   \n",
       "3       유창성업   122812      인천광역시 서구 갑문2로    28    260    119  749604   \n",
       "4       희성전자   106810  서울특별시 용산구 독서당로14길    11    170    131  701201   \n",
       "\n",
       "                           업종코드명  가입자수         금액  신규  상실  \n",
       "0                  동력식 수지 공구 제조업     4     899980   0   0  \n",
       "1            화장터 운영  묘지 분양 및 관리업    11    3278020   0   0  \n",
       "2                           신용조합    12    4956440   0   0  \n",
       "3  그 외 기타 분류 안된 사업 지원 서비스업(기타임가공    24    5371000   0   0  \n",
       "4           비주거용 건물 임대업(점포  자기땅)   395  187943100   0   1  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 코드를 입력해 주세요\n",
    "df = df.loc[df['가입상태'] == 1].drop(['가입상태', '탈퇴일자'], axis=1).reset_index(drop=True)\n",
    "print(f'shape: {df.shape[0]} 행')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "dc7PdGqZKSVc"
   },
   "source": [
    "## 핵심 데이터 column 추출"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wSqrG5w-LJOu"
   },
   "source": [
    "- 수도권(서울, 경기도) 소재의 기업을 대상으로 합니다.\n",
    "- `가입자수`를 기준으로 내림차순 정렬하여 bar 그래프를 출력합니다.\n",
    "- 출력되는 사업장명은 상위 20개만 출력합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "id": "5wCszhCcKSVc"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 코드를 입력해 주세요\n",
    "plt.figure(figsize=(8, 10))\n",
    "tmp = df.loc[df['시도코드'].isin([11, 41]), ['사업장명', '가입자수']].sort_values('가입자수', ascending=False).head(20).reset_index()\n",
    "sns.barplot(y='사업장명', x='가입자수', data=tmp)\n",
    "plt.xticks(rotation=30)\n",
    "plt.title('수도권 소재 기업별 가입자수')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DXysLKjhKSVq"
   },
   "source": [
    "### 국민연금 납부액으로 기업별 평균 연봉 추정\n",
    "\n",
    "국민연금 보험률은 9%입니다. 쉽게 이야기 하면 급여(신고소득월액)의 9%를 국민연금으로 내는 것입니다. \n",
    "\n",
    "하지만 이를 절반으로 나누어 **4.5%는 회사가, 나머지 절반은 개인이 부담하는 구조**입니다. 회사는 급여 외에 추가로 금액을 부담합니다.\n",
    "\n",
    "국민연금 보험료는 **소득 상한선과 하한선이 설정되어 있어 소득 전체가 아닌 일부 소득에만 부과**됩니다.\n",
    "\n",
    "이를 역산하면 신고소득월액의 계산이 가능합니다. 하지만 **상한선과 하한선이 설정되어 있어 실제보다 과소계산**될 수 있습니다"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "11NxoFkQKSVr"
   },
   "source": [
    "[수식]\n",
    "\n",
    "- 인당금액 = 금액 / 가입자수\n",
    "- 월급여추정 = 인당금액 / 9% * 100%\n",
    "- 연간급여추정 = 임직원 평균 월급 * 12개월"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 금액을 가입자수로 나눈 금액을 산출하여 `인당금액`을 먼저 산출합니다.\n",
    "- `월급여추정`은 `인당금액` / 9% * 100% 한 값입니다.\n",
    "- `월급여추정`을 x12한 값을 `연간급여추정`에 대입합니다.\n",
    "- `가입자수` 기준 1000명을 초과하는 기업(중견기업)을 필터링 합니다.\n",
    "- 출력시 `사업장명`, `가입자수`, `월급여추정`, `연간급여추정` 컬럼만 출력합니다.\n",
    "- `연간급여추정`와 `가입자수`를 기준으로 내림차순하여 상위 10개 기업을 출력합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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>사업장명</th>\n",
       "      <th>사업자등록번호</th>\n",
       "      <th>주소</th>\n",
       "      <th>시도코드</th>\n",
       "      <th>시군구코드</th>\n",
       "      <th>읍면동코드</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>업종코드명</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>금액</th>\n",
       "      <th>신규</th>\n",
       "      <th>상실</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>우성기전</td>\n",
       "      <td>126811</td>\n",
       "      <td>경기도 광주시 도척면 도척윗로</td>\n",
       "      <td>41</td>\n",
       "      <td>610</td>\n",
       "      <td>330</td>\n",
       "      <td>292201</td>\n",
       "      <td>동력식 수지 공구 제조업</td>\n",
       "      <td>4</td>\n",
       "      <td>899980</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>서능공원묘지운영회</td>\n",
       "      <td>102820</td>\n",
       "      <td></td>\n",
       "      <td>41</td>\n",
       "      <td>650</td>\n",
       "      <td>320</td>\n",
       "      <td>701700</td>\n",
       "      <td>화장터 운영  묘지 분양 및 관리업</td>\n",
       "      <td>11</td>\n",
       "      <td>3278020</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>노들새마을금고</td>\n",
       "      <td>108820</td>\n",
       "      <td>서울특별시 동작구 만양로</td>\n",
       "      <td>11</td>\n",
       "      <td>590</td>\n",
       "      <td>101</td>\n",
       "      <td>659202</td>\n",
       "      <td>신용조합</td>\n",
       "      <td>12</td>\n",
       "      <td>4956440</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>유창성업</td>\n",
       "      <td>122812</td>\n",
       "      <td>인천광역시 서구 갑문2로</td>\n",
       "      <td>28</td>\n",
       "      <td>260</td>\n",
       "      <td>119</td>\n",
       "      <td>749604</td>\n",
       "      <td>그 외 기타 분류 안된 사업 지원 서비스업(기타임가공</td>\n",
       "      <td>24</td>\n",
       "      <td>5371000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>희성전자</td>\n",
       "      <td>106810</td>\n",
       "      <td>서울특별시 용산구 독서당로14길</td>\n",
       "      <td>11</td>\n",
       "      <td>170</td>\n",
       "      <td>131</td>\n",
       "      <td>701201</td>\n",
       "      <td>비주거용 건물 임대업(점포  자기땅)</td>\n",
       "      <td>395</td>\n",
       "      <td>187943100</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        사업장명  사업자등록번호                 주소  시도코드  시군구코드  읍면동코드    업종코드  \\\n",
       "0       우성기전   126811   경기도 광주시 도척면 도척윗로    41    610    330  292201   \n",
       "1  서능공원묘지운영회   102820                       41    650    320  701700   \n",
       "2    노들새마을금고   108820      서울특별시 동작구 만양로    11    590    101  659202   \n",
       "3       유창성업   122812      인천광역시 서구 갑문2로    28    260    119  749604   \n",
       "4       희성전자   106810  서울특별시 용산구 독서당로14길    11    170    131  701201   \n",
       "\n",
       "                           업종코드명  가입자수         금액  신규  상실  \n",
       "0                  동력식 수지 공구 제조업     4     899980   0   0  \n",
       "1            화장터 운영  묘지 분양 및 관리업    11    3278020   0   0  \n",
       "2                           신용조합    12    4956440   0   0  \n",
       "3  그 외 기타 분류 안된 사업 지원 서비스업(기타임가공    24    5371000   0   0  \n",
       "4           비주거용 건물 임대업(점포  자기땅)   395  187943100   0   1  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "5K7V-RGzKSVr",
    "outputId": "90cfb490-aa38-40a3-cea6-5014a1c13b9c"
   },
   "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>사업장명</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>월급여추정</th>\n",
       "      <th>연간급여추정</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6652</th>\n",
       "      <td>기아 영업본부</td>\n",
       "      <td>2563</td>\n",
       "      <td>5529827.9</td>\n",
       "      <td>66357934.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227092</th>\n",
       "      <td>부산항만산업협회 화물고정업</td>\n",
       "      <td>1094</td>\n",
       "      <td>5517134.3</td>\n",
       "      <td>66205611.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3429</th>\n",
       "      <td>주식회사 현대케피코</td>\n",
       "      <td>1545</td>\n",
       "      <td>5507191.9</td>\n",
       "      <td>66086303.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271467</th>\n",
       "      <td>삼성물산건설부문 정규직</td>\n",
       "      <td>4484</td>\n",
       "      <td>5496792.8</td>\n",
       "      <td>65961514.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200140</th>\n",
       "      <td>삼성디스플레이</td>\n",
       "      <td>21458</td>\n",
       "      <td>5489918.2</td>\n",
       "      <td>65879018.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6306</th>\n",
       "      <td>기아 정비본부</td>\n",
       "      <td>1272</td>\n",
       "      <td>5487657.2</td>\n",
       "      <td>65851886.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142430</th>\n",
       "      <td>기아AutoLand화성</td>\n",
       "      <td>12296</td>\n",
       "      <td>5483301.6</td>\n",
       "      <td>65799618.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3417</th>\n",
       "      <td>삼성에스디에스</td>\n",
       "      <td>11682</td>\n",
       "      <td>5479750.5</td>\n",
       "      <td>65757006.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96919</th>\n",
       "      <td>기아 AutoLand광주</td>\n",
       "      <td>6815</td>\n",
       "      <td>5473123.4</td>\n",
       "      <td>65677481.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182394</th>\n",
       "      <td>KB국민카드</td>\n",
       "      <td>1518</td>\n",
       "      <td>5468282.8</td>\n",
       "      <td>65619393.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  사업장명   가입자수     월급여추정     연간급여추정\n",
       "6652           기아 영업본부   2563 5529827.9 66357934.7\n",
       "227092  부산항만산업협회 화물고정업   1094 5517134.3 66205611.2\n",
       "3429        주식회사 현대케피코   1545 5507191.9 66086303.3\n",
       "271467    삼성물산건설부문 정규직   4484 5496792.8 65961514.1\n",
       "200140         삼성디스플레이  21458 5489918.2 65879018.9\n",
       "6306           기아 정비본부   1272 5487657.2 65851886.8\n",
       "142430    기아AutoLand화성  12296 5483301.6 65799618.7\n",
       "3417           삼성에스디에스  11682 5479750.5 65757006.4\n",
       "96919    기아 AutoLand광주   6815 5473123.4 65677481.2\n",
       "182394          KB국민카드   1518 5468282.8 65619393.9"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 코드를 입력해 주세요\n",
    "df['인당금액'] = df['금액'] / df['가입자수']\n",
    "df['월급여추정'] =  df['인당금액'] / 9 * 100\n",
    "df['연간급여추정'] = df['월급여추정'] * 12\n",
    "\n",
    "cond = (df['가입자수'] > 1000)\n",
    "df.sort_values(['연간급여추정', '가입자수'], ascending=False).loc[cond, ['사업장명', '가입자수', '월급여추정', '연간급여추정']].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nt5iD9mCKSV_"
   },
   "source": [
    "### 업종별 가입자수 순유입 산정\n",
    "\n",
    "- `순유입`은 `신규` - `상실` 로 정의합니다.\n",
    "- `업종코드명`별 순유입의 합산을 구한 후 상위 20개 `업종코드명`에 대하여 bar 그래프로 출력합니다.\n",
    "- `순유입` 기준으로 내림차순 정렬합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "id": "jIuPYzbaKSV_"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 코드를 입력해 주세요\n",
    "plt.figure(figsize=(8, 10))\n",
    "df['순유입'] = df['신규'] - df['상실']\n",
    "df.groupby('업종코드명')['순유입'].sum().sort_values(ascending=False).head(20).sort_values().plot(kind='barh')\n",
    "plt.title('업종별 순유입 순')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 다음의 기능을 하는 함수를 완성하세요"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 사업자명을 검색한 후 결과를 return하는 함수를 완성합니다.\n",
    "- 함수명은 `find_company` 입니다.\n",
    "- 매개변수 contains: \n",
    "          True인 경우: string의 `contains`를 사용하여 포함하는 모든 회사를 찾습니다.\n",
    "          False인 경우: 정확히 일치하는 사업장명만 찾습니다.\n",
    "          \n",
    "- `def find_company(company_name, contains)`\n",
    "- `['사업장명', '월급여추정', '연간급여추정', '업종코드']` 정보를 보여주는 DataFrame을 return 합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>사업장명</th>\n",
       "      <th>사업자등록번호</th>\n",
       "      <th>주소</th>\n",
       "      <th>시도코드</th>\n",
       "      <th>시군구코드</th>\n",
       "      <th>읍면동코드</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>업종코드명</th>\n",
       "      <th>가입자수</th>\n",
       "      <th>금액</th>\n",
       "      <th>신규</th>\n",
       "      <th>상실</th>\n",
       "      <th>인당금액</th>\n",
       "      <th>월급여추정</th>\n",
       "      <th>연간급여추정</th>\n",
       "      <th>순유입</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>삼송</td>\n",
       "      <td>116810</td>\n",
       "      <td>서울특별시 서초구 마방로6길</td>\n",
       "      <td>11</td>\n",
       "      <td>650</td>\n",
       "      <td>102</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>164</td>\n",
       "      <td>60165420</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>366862.3</td>\n",
       "      <td>4076248.0</td>\n",
       "      <td>48914975.6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>장성</td>\n",
       "      <td>214815</td>\n",
       "      <td>경기도 성남시 분당구 판교로</td>\n",
       "      <td>41</td>\n",
       "      <td>135</td>\n",
       "      <td>107</td>\n",
       "      <td>172902</td>\n",
       "      <td>그 외 기타 분류 안된 섬유제품 제조업</td>\n",
       "      <td>4</td>\n",
       "      <td>1411360</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>352840.0</td>\n",
       "      <td>3920444.4</td>\n",
       "      <td>47045333.3</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>특수법인 총포 화약안전기술협회</td>\n",
       "      <td>118820</td>\n",
       "      <td>서울특별시 마포구 마포대로1길</td>\n",
       "      <td>11</td>\n",
       "      <td>440</td>\n",
       "      <td>105</td>\n",
       "      <td>742201</td>\n",
       "      <td>기타 기술 시험  검사 및 분석업</td>\n",
       "      <td>20</td>\n",
       "      <td>7398260</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>369913.0</td>\n",
       "      <td>4110144.4</td>\n",
       "      <td>49321733.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>서울명지초등학교</td>\n",
       "      <td>111820</td>\n",
       "      <td>서울특별시 서대문구 명지2길</td>\n",
       "      <td>11</td>\n",
       "      <td>410</td>\n",
       "      <td>118</td>\n",
       "      <td>999999</td>\n",
       "      <td>BIZ_NO미존재사업장</td>\n",
       "      <td>41</td>\n",
       "      <td>7886200</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>192346.3</td>\n",
       "      <td>2137181.6</td>\n",
       "      <td>25646178.9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>삼양건설산업</td>\n",
       "      <td>229810</td>\n",
       "      <td>서울특별시 서초구 동산로</td>\n",
       "      <td>11</td>\n",
       "      <td>650</td>\n",
       "      <td>102</td>\n",
       "      <td>451101</td>\n",
       "      <td>아파트 건설업</td>\n",
       "      <td>62</td>\n",
       "      <td>23659800</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>381609.7</td>\n",
       "      <td>4240107.5</td>\n",
       "      <td>50881290.3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               사업장명  사업자등록번호                주소  시도코드  시군구코드  읍면동코드    업종코드  \\\n",
       "0                삼송   116810   서울특별시 서초구 마방로6길    11    650    102           \n",
       "1                장성   214815   경기도 성남시 분당구 판교로    41    135    107  172902   \n",
       "2  특수법인 총포 화약안전기술협회   118820  서울특별시 마포구 마포대로1길    11    440    105  742201   \n",
       "3          서울명지초등학교   111820   서울특별시 서대문구 명지2길    11    410    118  999999   \n",
       "4            삼양건설산업   229810     서울특별시 서초구 동산로    11    650    102  451101   \n",
       "\n",
       "                   업종코드명  가입자수        금액  신규  상실     인당금액     월급여추정  \\\n",
       "0                    NaN   164  60165420   2   1 366862.3 4076248.0   \n",
       "1  그 외 기타 분류 안된 섬유제품 제조업     4   1411360   0   1 352840.0 3920444.4   \n",
       "2     기타 기술 시험  검사 및 분석업    20   7398260   2   0 369913.0 4110144.4   \n",
       "3           BIZ_NO미존재사업장    41   7886200   1   1 192346.3 2137181.6   \n",
       "4                아파트 건설업    62  23659800   1   0 381609.7 4240107.5   \n",
       "\n",
       "      연간급여추정  순유입  \n",
       "0 48914975.6    1  \n",
       "1 47045333.3   -1  \n",
       "2 49321733.3    2  \n",
       "3 25646178.9    0  \n",
       "4 50881290.3    1  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 코드를 입력해 주세요\n",
    "def find_company(company_name, contains):\n",
    "    if contains:\n",
    "        return df.loc[df['사업장명'].str.contains(company_name), ['사업장명', '월급여추정', '연간급여추정', '업종코드', '가입자수']]\\\n",
    "              .sort_values('가입자수', ascending=False)\n",
    "    else:\n",
    "        return df.loc[df['사업장명']==company_name, ['사업장명', '월급여추정', '연간급여추정', '업종코드', '가입자수']]\\\n",
    "              .sort_values('가입자수', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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>사업장명</th>\n",
       "      <th>월급여추정</th>\n",
       "      <th>연간급여추정</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>가입자수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3225</th>\n",
       "      <td>에스케이텔레콤</td>\n",
       "      <td>5386506.9</td>\n",
       "      <td>64638083.2</td>\n",
       "      <td>642001</td>\n",
       "      <td>5270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388606</th>\n",
       "      <td>에스케이텔레콤씨에스티원</td>\n",
       "      <td>3278577.1</td>\n",
       "      <td>39342925.4</td>\n",
       "      <td>924101</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>457287</th>\n",
       "      <td>에스케이텔레콤 주 상용 4단계 운항통신시설 구매설치사업</td>\n",
       "      <td>3823948.7</td>\n",
       "      <td>45887384.6</td>\n",
       "      <td>642001</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507322</th>\n",
       "      <td>에스케이텔레콤 상용 경북 사업장 형태선LTE R</td>\n",
       "      <td>5530000.0</td>\n",
       "      <td>66360000.0</td>\n",
       "      <td>642001</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136325</th>\n",
       "      <td>주식회사 에스케이텔레콤봉화대리점</td>\n",
       "      <td>3043722.2</td>\n",
       "      <td>36524666.7</td>\n",
       "      <td>523323</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252008</th>\n",
       "      <td>에스케이텔레콤 철원동송대리점</td>\n",
       "      <td>3020000.0</td>\n",
       "      <td>36240000.0</td>\n",
       "      <td>515060</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503453</th>\n",
       "      <td>에스케이텔레콤 주 상용 경부선 추풍령 지천 개량 철도통합무선망 구매설치</td>\n",
       "      <td>4829333.3</td>\n",
       "      <td>57952000.0</td>\n",
       "      <td>642001</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           사업장명     월급여추정     연간급여추정    업종코드  \\\n",
       "3225                                    에스케이텔레콤 5386506.9 64638083.2  642001   \n",
       "388606                             에스케이텔레콤씨에스티원 3278577.1 39342925.4  924101   \n",
       "457287           에스케이텔레콤 주 상용 4단계 운항통신시설 구매설치사업 3823948.7 45887384.6  642001   \n",
       "507322               에스케이텔레콤 상용 경북 사업장 형태선LTE R 5530000.0 66360000.0  642001   \n",
       "136325                        주식회사 에스케이텔레콤봉화대리점 3043722.2 36524666.7  523323   \n",
       "252008                          에스케이텔레콤 철원동송대리점 3020000.0 36240000.0  515060   \n",
       "503453  에스케이텔레콤 주 상용 경부선 추풍령 지천 개량 철도통합무선망 구매설치 4829333.3 57952000.0  642001   \n",
       "\n",
       "        가입자수  \n",
       "3225    5270  \n",
       "388606    67  \n",
       "457287    13  \n",
       "507322     5  \n",
       "136325     4  \n",
       "252008     4  \n",
       "503453     3  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 검증코드\n",
    "find_company('에스케이텔레콤', True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>사업장명</th>\n",
       "      <th>월급여추정</th>\n",
       "      <th>연간급여추정</th>\n",
       "      <th>업종코드</th>\n",
       "      <th>가입자수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3026</th>\n",
       "      <td>에스케이텔레콤</td>\n",
       "      <td>5360663.7</td>\n",
       "      <td>64327964.8</td>\n",
       "      <td>642001</td>\n",
       "      <td>5298</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         사업장명     월급여추정     연간급여추정    업종코드  가입자수\n",
       "3026  에스케이텔레콤 5360663.7 64327964.8  642001  5298"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 검증코드\n",
    "find_company('에스케이텔레콤', False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 사업장명을 입력하면 사업장명과 정확히 일치하는 회사를 찾습니다. (find_company 함수 사용)\n",
    "- 함수명은 `compare_company` 입니다.\n",
    "- 매개변수명은 `company_name` 으로 지정하세요\n",
    "- `def compare_company(company_name)`\n",
    "\n",
    "기능\n",
    "- find_company로 부터 return 된 DataFrame의 업종코드와 동일한 회사를 모두 찾습니다.\n",
    "- 동일한 회사의 `월급여추정`, `연간급여추정`에 대한 ['mean', 'count', 'min', 'max']를 산출합니다.\n",
    "\n",
    "return 되는 DataFrame은 다음과 같이 구성합니다.\n",
    "- index: `월급여추정` -> `업종_월급여추정`, `연간급여추정` -> `업종_연간급여추정`으로 변경합니다.\n",
    "- 컬럼은 평균, 개수, 최소, 최대로 컬럼명을 변경 후 맨 끝열에는 찾은 회사명 컬럼을 추가하고, `월급여추정`, `연간급여추정` 데이터를 기입합니다.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "def company_info(company_name):\n",
    "    company = find_company(company_name, True)\n",
    "    return df.loc[company.iloc[0].name]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "사업장명            에스케이텔레콤\n",
       "사업자등록번호          104813\n",
       "주소         서울특별시 중구 을지로\n",
       "시도코드                 11\n",
       "시군구코드               140\n",
       "읍면동코드               105\n",
       "업종코드             642001\n",
       "업종코드명       무선 및 위성 통신업\n",
       "가입자수               5270\n",
       "금액           2554820240\n",
       "신규                   24\n",
       "상실                   78\n",
       "인당금액           484785.6\n",
       "월급여추정         5386506.9\n",
       "연간급여추정       64638083.2\n",
       "순유입                 -54\n",
       "Name: 3225, dtype: object"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "info = company_info('에스케이텔레콤')\n",
    "info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 코드를 입력해 주세요\n",
    "def compare_company(company_name):\n",
    "    company = find_company(company_name, True)\n",
    "    code = company['업종코드'].iloc[0]\n",
    "    df1 =df.loc[df['업종코드'] == code, ['월급여추정', '연간급여추정']].agg(['mean', 'count', 'min', 'max'])\n",
    "    df1.columns = ['업종_월급여추정', '업종_연간급여추정']\n",
    "    df1 = df1.T\n",
    "    df1.columns = ['평균', '개수', '최소', '최대']\n",
    "    df1.loc['업종_월급여추정', company_name] = company['월급여추정'].values[0]\n",
    "    df1.loc['업종_연간급여추정', company_name] = company['연간급여추정'].values[0]\n",
    "    return df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "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>평균</th>\n",
       "      <th>개수</th>\n",
       "      <th>최소</th>\n",
       "      <th>최대</th>\n",
       "      <th>삼성전자</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>업종_월급여추정</th>\n",
       "      <td>3170029.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>484994.9</td>\n",
       "      <td>5489918.2</td>\n",
       "      <td>5405548.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>업종_연간급여추정</th>\n",
       "      <td>38040348.1</td>\n",
       "      <td>273.0</td>\n",
       "      <td>5819939.4</td>\n",
       "      <td>65879018.9</td>\n",
       "      <td>64866586.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  평균    개수        최소         최대       삼성전자\n",
       "업종_월급여추정   3170029.0 273.0  484994.9  5489918.2  5405548.8\n",
       "업종_연간급여추정 38040348.1 273.0 5819939.4 65879018.9 64866586.0"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 검증코드\n",
    "result = compare_company('삼성전자')\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2)\n",
    "\n",
    "p1 = ax[0].bar(x=['평균', '에스케이텔레콤'], height=(result.iloc[0, 0], info['월급여추정']), width=0.7)\n",
    "ax[0].bar_label(p1, fmt='%d')\n",
    "p1[0].set_color('black')\n",
    "p1[1].set_color('red')\n",
    "ax[0].ticklabel_format(style='plain', axis='y')\n",
    "ax[0].set_title('월급여 비교')\n",
    "\n",
    "p2 = ax[1].bar(x=['평균', '에스케이텔레콤'], height=(result.iloc[1, 0], info['연간급여추정']), width=0.7)\n",
    "p2[0].set_color('black')\n",
    "p2[1].set_color('red')\n",
    "ax[1].bar_label(p2, fmt='%d')\n",
    "ax[1].ticklabel_format(style='plain', axis='y')\n",
    "ax[1].set_title('연봉 비교')\n",
    "\n",
    "ax[0].tick_params(axis='both', which='major', labelsize=8, rotation=0)\n",
    "ax[0].tick_params(axis='both', which='minor', labelsize=6)\n",
    "ax[1].tick_params(axis='both', which='major', labelsize=8)\n",
    "ax[1].tick_params(axis='both', which='minor', labelsize=6)\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "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>평균</th>\n",
       "      <th>개수</th>\n",
       "      <th>최소</th>\n",
       "      <th>최대</th>\n",
       "      <th>현대자동차</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>업종_월급여추정</th>\n",
       "      <td>3438728.5</td>\n",
       "      <td>173.0</td>\n",
       "      <td>1412383.6</td>\n",
       "      <td>5529827.9</td>\n",
       "      <td>5270905.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>업종_연간급여추정</th>\n",
       "      <td>41264742.2</td>\n",
       "      <td>173.0</td>\n",
       "      <td>16948602.7</td>\n",
       "      <td>66357934.7</td>\n",
       "      <td>63250868.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  평균    개수         최소         최대      현대자동차\n",
       "업종_월급여추정   3438728.5 173.0  1412383.6  5529827.9  5270905.7\n",
       "업종_연간급여추정 41264742.2 173.0 16948602.7 66357934.7 63250868.5"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 검증코드\n",
    "compare_company('현대자동차')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "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>평균</th>\n",
       "      <th>개수</th>\n",
       "      <th>최소</th>\n",
       "      <th>최대</th>\n",
       "      <th>버킷플레이스</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>업종_월급여추정</th>\n",
       "      <td>2717856.2</td>\n",
       "      <td>52261.0</td>\n",
       "      <td>350000.0</td>\n",
       "      <td>5530000.0</td>\n",
       "      <td>4222412.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>업종_연간급여추정</th>\n",
       "      <td>32614274.8</td>\n",
       "      <td>52261.0</td>\n",
       "      <td>4200000.0</td>\n",
       "      <td>66360000.0</td>\n",
       "      <td>50668951.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  평균      개수        최소         최대     버킷플레이스\n",
       "업종_월급여추정   2717856.2 52261.0  350000.0  5530000.0  4222412.6\n",
       "업종_연간급여추정 32614274.8 52261.0 4200000.0 66360000.0 50668951.7"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 검증코드\n",
    "compare_company('버킷플레이스')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "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>평균</th>\n",
       "      <th>개수</th>\n",
       "      <th>최소</th>\n",
       "      <th>최대</th>\n",
       "      <th>무신사</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>업종_월급여추정</th>\n",
       "      <td>3299384.1</td>\n",
       "      <td>5810.0</td>\n",
       "      <td>350000.0</td>\n",
       "      <td>5530000.0</td>\n",
       "      <td>4098412.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>업종_연간급여추정</th>\n",
       "      <td>39592608.7</td>\n",
       "      <td>5810.0</td>\n",
       "      <td>4200000.0</td>\n",
       "      <td>66360000.0</td>\n",
       "      <td>49180946.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  평균     개수        최소         최대        무신사\n",
       "업종_월급여추정   3299384.1 5810.0  350000.0  5530000.0  4098412.2\n",
       "업종_연간급여추정 39592608.7 5810.0 4200000.0 66360000.0 49180946.3"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 검증코드\n",
    "compare_company('무신사')"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "국민연금 데이터분석 (해설)",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}