data_ABC_10.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "9a28a40c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Malgun Gothic']\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "plt.rc('font', family='Malgun Gothic')\n",
    "print(plt.rcParams['font.family'])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "f514df32",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = 'C:/users/juwon/practice_aiffel/data_analysis_basic/'\n",
    "\n",
    "entry_data = pd.read_csv(file_path + 'entry_data.csv')\n",
    "sales_data = pd.read_csv(file_path + 'sales_data.csv')\n",
    "item_data = pd.read_csv(file_path + 'item_data.csv')\n",
    "item_entry_data = pd.read_csv(file_path + 'item_entry_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "15db2c1d",
   "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>요금제명</th>\n",
       "      <th>입실</th>\n",
       "      <th>퇴실</th>\n",
       "      <th>이용</th>\n",
       "      <th>위치</th>\n",
       "      <th>금액</th>\n",
       "      <th>구분</th>\n",
       "      <th>고객</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>시간요금제(1시간)</td>\n",
       "      <td>2022-04-01 23:39</td>\n",
       "      <td>2022-04-02 0:39</td>\n",
       "      <td>오전 1:00:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>3000</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer263717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>시간요금제(1시간)</td>\n",
       "      <td>2022-04-01 23:39</td>\n",
       "      <td>2022-04-02 0:39</td>\n",
       "      <td>오전 1:00:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>3000</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer263717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>무제한 입장권</td>\n",
       "      <td>2022-04-01 20:55</td>\n",
       "      <td>2022-04-01 21:41</td>\n",
       "      <td>오전 12:46:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>7400</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer247263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>무제한 입장권</td>\n",
       "      <td>2022-04-01 20:55</td>\n",
       "      <td>2022-04-01 21:41</td>\n",
       "      <td>오전 12:46:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>7400</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer247263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>한국대생 무제한 입장권</td>\n",
       "      <td>2022-04-01 19:54</td>\n",
       "      <td>2022-04-01 22:28</td>\n",
       "      <td>오전 2:33:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>7400</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer388928</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           요금제명                입실                퇴실           이용    위치    금액  \\\n",
       "0    시간요금제(1시간)  2022-04-01 23:39   2022-04-02 0:39   오전 1:00:00  선불기2  3000   \n",
       "1    시간요금제(1시간)  2022-04-01 23:39   2022-04-02 0:39   오전 1:00:00  선불기2  3000   \n",
       "2       무제한 입장권  2022-04-01 20:55  2022-04-01 21:41  오전 12:46:00  선불기2  7400   \n",
       "3       무제한 입장권  2022-04-01 20:55  2022-04-01 21:41  오전 12:46:00  선불기2  7400   \n",
       "4  한국대생 무제한 입장권  2022-04-01 19:54  2022-04-01 22:28   오전 2:33:00  선불기2  7400   \n",
       "\n",
       "   구분              고객  \n",
       "0  퇴실  customer263717  \n",
       "1  퇴실  customer263717  \n",
       "2  퇴실  customer247263  \n",
       "3  퇴실  customer247263  \n",
       "4  퇴실  customer388928  "
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# entry_data 데이터 정보 확인하기\n",
    "entry_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "a0415064",
   "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>결제일시</th>\n",
       "      <th>판매위치</th>\n",
       "      <th>상품명</th>\n",
       "      <th>결제방식</th>\n",
       "      <th>비고</th>\n",
       "      <th>판매수량</th>\n",
       "      <th>결제금액</th>\n",
       "      <th>고객</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>치킨카라아케 6pc</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>4,500</td>\n",
       "      <td>customer275507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>짜장라면(계란추가)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>5,500</td>\n",
       "      <td>customer275507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>라면</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>4,000</td>\n",
       "      <td>customer275507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>비엔나소세지(토핑)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>1,000</td>\n",
       "      <td>customer275507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>라면(계란/치즈추가)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>5,000</td>\n",
       "      <td>customer275507</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               결제일시  판매위치          상품명  결제방식    비고  판매수량   결제금액  \\\n",
       "0  2022-04-01 19:41  선불기1   치킨카라아케 6pc  신용카드  결제완료     1  4,500   \n",
       "1  2022-04-01 19:41  선불기1   짜장라면(계란추가)  신용카드  결제완료     1  5,500   \n",
       "2  2022-04-01 19:41  선불기1           라면  신용카드  결제완료     1  4,000   \n",
       "3  2022-04-01 19:41  선불기1   비엔나소세지(토핑)  신용카드  결제완료     1  1,000   \n",
       "4  2022-04-01 19:41  선불기1  라면(계란/치즈추가)  신용카드  결제완료     1  5,000   \n",
       "\n",
       "               고객  \n",
       "0  customer275507  \n",
       "1  customer275507  \n",
       "2  customer275507  \n",
       "3  customer275507  \n",
       "4  customer275507  "
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sales_data 데이터 정보 확인하기\n",
    "sales_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "68025e55",
   "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>구분</th>\n",
       "      <th>분류</th>\n",
       "      <th>상품명</th>\n",
       "      <th>판매금액</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>게임&amp;TV</td>\n",
       "      <td>이어폰(커널형)</td>\n",
       "      <td>3,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>디저트</td>\n",
       "      <td>초코머핀</td>\n",
       "      <td>3,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>디저트</td>\n",
       "      <td>쿠키(초코칩)</td>\n",
       "      <td>1,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>디저트</td>\n",
       "      <td>쿠키(마카다미아)</td>\n",
       "      <td>1,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>디저트</td>\n",
       "      <td>미니마카롱(3개)</td>\n",
       "      <td>2,000원</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   구분     분류        상품명    판매금액\n",
       "0   1  게임&TV   이어폰(커널형)  3,000원\n",
       "1   2    디저트       초코머핀  3,500원\n",
       "2   3    디저트    쿠키(초코칩)  1,500원\n",
       "3   4    디저트  쿠키(마카다미아)  1,500원\n",
       "4   5    디저트  미니마카롱(3개)  2,000원"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# item_data 데이터 정보 확인하기\n",
    "item_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "8dbbc250",
   "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>순위</th>\n",
       "      <th>분류</th>\n",
       "      <th>상품명</th>\n",
       "      <th>판매금액</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>한국대생</td>\n",
       "      <td>한국대생 요금제</td>\n",
       "      <td>2,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>심야-조조</td>\n",
       "      <td>심야-조조 요금제</td>\n",
       "      <td>5,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>일반인</td>\n",
       "      <td>일반요금제</td>\n",
       "      <td>2,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>한국대생</td>\n",
       "      <td>한국대생 요금제</td>\n",
       "      <td>2,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>일반인</td>\n",
       "      <td>일반요금제</td>\n",
       "      <td>2,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>한국대생</td>\n",
       "      <td>한국대생 요금제</td>\n",
       "      <td>1,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>18시이후</td>\n",
       "      <td>거리두기4단계</td>\n",
       "      <td>1,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>심야-조조</td>\n",
       "      <td>심야-조조 요금제</td>\n",
       "      <td>2,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>일반인</td>\n",
       "      <td>일반요금제</td>\n",
       "      <td>3,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>일반인</td>\n",
       "      <td>일반요금제</td>\n",
       "      <td>7,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>심야-조조</td>\n",
       "      <td>심야-조조 요금제</td>\n",
       "      <td>4,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>심야-조조</td>\n",
       "      <td>심야-조조 요금제</td>\n",
       "      <td>6,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>심야-조조</td>\n",
       "      <td>심야-조조 요금제</td>\n",
       "      <td>7,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>한국대생</td>\n",
       "      <td>한국대생 요금제</td>\n",
       "      <td>7,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>한국대생</td>\n",
       "      <td>한국대생 요금제</td>\n",
       "      <td>3,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>18시이후</td>\n",
       "      <td>거리두기4단계</td>\n",
       "      <td>2,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>심야-조조</td>\n",
       "      <td>심야-조조 요금제</td>\n",
       "      <td>3,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>18시이후</td>\n",
       "      <td>마감요금</td>\n",
       "      <td>2,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>기본</td>\n",
       "      <td>기본요금제</td>\n",
       "      <td>2,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>일반인</td>\n",
       "      <td>일반요금제</td>\n",
       "      <td>8,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>심야-조조</td>\n",
       "      <td>심야-조조 요금제</td>\n",
       "      <td>8,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>심야-조조</td>\n",
       "      <td>추석당일 요금제</td>\n",
       "      <td>5,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>심야-조조</td>\n",
       "      <td>추석당일 요금제</td>\n",
       "      <td>7,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>기본</td>\n",
       "      <td>기본요금제</td>\n",
       "      <td>2,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>한국대생</td>\n",
       "      <td>한국대생 요금제</td>\n",
       "      <td>8,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>18시이후</td>\n",
       "      <td>거리두기4단계</td>\n",
       "      <td>7,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>기본</td>\n",
       "      <td>기본요금제</td>\n",
       "      <td>2,400원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>기본그룹</td>\n",
       "      <td>기본요금제</td>\n",
       "      <td>2,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>일반인</td>\n",
       "      <td>일반요금제</td>\n",
       "      <td>6,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>심야-조조</td>\n",
       "      <td>추석당일 요금제</td>\n",
       "      <td>2,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>기본그룹</td>\n",
       "      <td>기본요금제</td>\n",
       "      <td>2,000원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>일반인</td>\n",
       "      <td>일반요금제</td>\n",
       "      <td>3,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>일반인</td>\n",
       "      <td>일반요금제</td>\n",
       "      <td>6,500원</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>한국대생</td>\n",
       "      <td>한국대생 요금제</td>\n",
       "      <td>4,900원</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    순위     분류        상품명    판매금액\n",
       "0    1   한국대생   한국대생 요금제  2,000원\n",
       "1    2  심야-조조  심야-조조 요금제  5,000원\n",
       "2    3    일반인      일반요금제  2,500원\n",
       "3    4   한국대생   한국대생 요금제  2,500원\n",
       "4    5    일반인      일반요금제  2,000원\n",
       "5    6   한국대생   한국대생 요금제  1,500원\n",
       "6    7  18시이후    거리두기4단계  1,000원\n",
       "7    8  심야-조조  심야-조조 요금제  2,500원\n",
       "8    9    일반인      일반요금제  3,000원\n",
       "9   10    일반인      일반요금제  7,000원\n",
       "10  11  심야-조조  심야-조조 요금제  4,000원\n",
       "11  12  심야-조조  심야-조조 요금제  6,000원\n",
       "12  13  심야-조조  심야-조조 요금제  7,000원\n",
       "13  14   한국대생   한국대생 요금제  7,000원\n",
       "14  15   한국대생   한국대생 요금제  3,000원\n",
       "15  16  18시이후    거리두기4단계  2,500원\n",
       "16  17  심야-조조  심야-조조 요금제  3,000원\n",
       "17  18  18시이후       마감요금  2,500원\n",
       "18  19     기본      기본요금제  2,500원\n",
       "19  20    일반인      일반요금제  8,000원\n",
       "20  21  심야-조조  심야-조조 요금제  8,000원\n",
       "21  22  심야-조조   추석당일 요금제  5,000원\n",
       "22  23  심야-조조   추석당일 요금제  7,000원\n",
       "23  24     기본      기본요금제  2,000원\n",
       "24  25   한국대생   한국대생 요금제  8,000원\n",
       "25  26  18시이후    거리두기4단계  7,000원\n",
       "26  27     기본      기본요금제  2,400원\n",
       "27  28   기본그룹      기본요금제  2,500원\n",
       "28  29    일반인      일반요금제  6,000원\n",
       "29  30  심야-조조   추석당일 요금제  2,500원\n",
       "30  31   기본그룹      기본요금제  2,000원\n",
       "31  32    일반인      일반요금제  3,500원\n",
       "32  33    일반인      일반요금제  6,500원\n",
       "33  34   한국대생   한국대생 요금제  4,900원"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_entry_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "9fb1a8d3",
   "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>결제일시</th>\n",
       "      <th>판매위치</th>\n",
       "      <th>상품명</th>\n",
       "      <th>결제방식</th>\n",
       "      <th>비고</th>\n",
       "      <th>판매수량</th>\n",
       "      <th>결제금액</th>\n",
       "      <th>고객</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>치킨카라아케 6pc</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>4,500</td>\n",
       "      <td>customer275507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>짜장라면(계란추가)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>5,500</td>\n",
       "      <td>customer275507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>라면</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>4,000</td>\n",
       "      <td>customer275507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>비엔나소세지(토핑)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>1,000</td>\n",
       "      <td>customer275507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>라면(계란/치즈추가)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>5,000</td>\n",
       "      <td>customer275507</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               결제일시  판매위치          상품명  결제방식    비고  판매수량   결제금액  \\\n",
       "0  2022-04-01 19:41  선불기1   치킨카라아케 6pc  신용카드  결제완료     1  4,500   \n",
       "1  2022-04-01 19:41  선불기1   짜장라면(계란추가)  신용카드  결제완료     1  5,500   \n",
       "2  2022-04-01 19:41  선불기1           라면  신용카드  결제완료     1  4,000   \n",
       "3  2022-04-01 19:41  선불기1   비엔나소세지(토핑)  신용카드  결제완료     1  1,000   \n",
       "4  2022-04-01 19:41  선불기1  라면(계란/치즈추가)  신용카드  결제완료     1  5,000   \n",
       "\n",
       "               고객  \n",
       "0  customer275507  \n",
       "1  customer275507  \n",
       "2  customer275507  \n",
       "3  customer275507  \n",
       "4  customer275507  "
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 활용할 데이터(sales_data)를 temp_var로 정의하기\n",
    "temp_var = sales_data\n",
    "temp_var.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "c2e642f8",
   "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>결제일시</th>\n",
       "      <th>판매위치</th>\n",
       "      <th>상품명</th>\n",
       "      <th>결제방식</th>\n",
       "      <th>비고</th>\n",
       "      <th>판매수량</th>\n",
       "      <th>결제금액</th>\n",
       "      <th>고객</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>치킨카라아케 6pc</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>4,500</td>\n",
       "      <td>customer275507</td>\n",
       "      <td>2022-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>짜장라면(계란추가)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>5,500</td>\n",
       "      <td>customer275507</td>\n",
       "      <td>2022-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>라면</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>4,000</td>\n",
       "      <td>customer275507</td>\n",
       "      <td>2022-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>비엔나소세지(토핑)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>1,000</td>\n",
       "      <td>customer275507</td>\n",
       "      <td>2022-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>라면(계란/치즈추가)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>5,000</td>\n",
       "      <td>customer275507</td>\n",
       "      <td>2022-04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               결제일시  판매위치          상품명  결제방식    비고  판매수량   결제금액  \\\n",
       "0  2022-04-01 19:41  선불기1   치킨카라아케 6pc  신용카드  결제완료     1  4,500   \n",
       "1  2022-04-01 19:41  선불기1   짜장라면(계란추가)  신용카드  결제완료     1  5,500   \n",
       "2  2022-04-01 19:41  선불기1           라면  신용카드  결제완료     1  4,000   \n",
       "3  2022-04-01 19:41  선불기1   비엔나소세지(토핑)  신용카드  결제완료     1  1,000   \n",
       "4  2022-04-01 19:41  선불기1  라면(계란/치즈추가)  신용카드  결제완료     1  5,000   \n",
       "\n",
       "               고객     date  \n",
       "0  customer275507  2022-04  \n",
       "1  customer275507  2022-04  \n",
       "2  customer275507  2022-04  \n",
       "3  customer275507  2022-04  \n",
       "4  customer275507  2022-04  "
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# temp_var의 date열을 만들고, sales_date의 결제일시 중 앞에서 7번째 값까지 할당\n",
    "temp_var['date'] = temp_var['결제일시'].str[:7]\n",
    "temp_var.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "11ffa25f",
   "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>결제일시</th>\n",
       "      <th>판매위치</th>\n",
       "      <th>상품명</th>\n",
       "      <th>결제방식</th>\n",
       "      <th>비고</th>\n",
       "      <th>판매수량</th>\n",
       "      <th>결제금액</th>\n",
       "      <th>고객</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>치킨카라아케 6pc</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>4500</td>\n",
       "      <td>customer275507</td>\n",
       "      <td>2022-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>짜장라면(계란추가)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>5500</td>\n",
       "      <td>customer275507</td>\n",
       "      <td>2022-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>라면</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>4000</td>\n",
       "      <td>customer275507</td>\n",
       "      <td>2022-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>비엔나소세지(토핑)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>1000</td>\n",
       "      <td>customer275507</td>\n",
       "      <td>2022-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-04-01 19:41</td>\n",
       "      <td>선불기1</td>\n",
       "      <td>라면(계란/치즈추가)</td>\n",
       "      <td>신용카드</td>\n",
       "      <td>결제완료</td>\n",
       "      <td>1</td>\n",
       "      <td>5000</td>\n",
       "      <td>customer275507</td>\n",
       "      <td>2022-04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               결제일시  판매위치          상품명  결제방식    비고  판매수량  결제금액  \\\n",
       "0  2022-04-01 19:41  선불기1   치킨카라아케 6pc  신용카드  결제완료     1  4500   \n",
       "1  2022-04-01 19:41  선불기1   짜장라면(계란추가)  신용카드  결제완료     1  5500   \n",
       "2  2022-04-01 19:41  선불기1           라면  신용카드  결제완료     1  4000   \n",
       "3  2022-04-01 19:41  선불기1   비엔나소세지(토핑)  신용카드  결제완료     1  1000   \n",
       "4  2022-04-01 19:41  선불기1  라면(계란/치즈추가)  신용카드  결제완료     1  5000   \n",
       "\n",
       "               고객     date  \n",
       "0  customer275507  2022-04  \n",
       "1  customer275507  2022-04  \n",
       "2  customer275507  2022-04  \n",
       "3  customer275507  2022-04  \n",
       "4  customer275507  2022-04  "
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# salse_data의 결제금액에 포함된 쉼표(,) 지우기\n",
    "sales_data['결제금액'] = sales_data['결제금액'].replace(',','',regex=True)\n",
    "sales_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "86746c6c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7105 entries, 0 to 7104\n",
      "Data columns (total 9 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   결제일시    7105 non-null   object\n",
      " 1   판매위치    7105 non-null   object\n",
      " 2   상품명     7105 non-null   object\n",
      " 3   결제방식    7105 non-null   object\n",
      " 4   비고      7105 non-null   object\n",
      " 5   판매수량    7105 non-null   int64 \n",
      " 6   결제금액    7105 non-null   int64 \n",
      " 7   고객      6300 non-null   object\n",
      " 8   date    7105 non-null   object\n",
      "dtypes: int64(2), object(7)\n",
      "memory usage: 499.7+ KB\n"
     ]
    }
   ],
   "source": [
    "# salse_data의 결제금액을 숫자형태로 바꾸기\n",
    "sales_data['결제금액'] = pd.to_numeric(sales_data['결제금액'])\n",
    "sales_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "5fc947c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date\n",
       "2021-02       7000\n",
       "2021-03    2104500\n",
       "2021-04    3116600\n",
       "2021-05    2537000\n",
       "2021-06    3621500\n",
       "2021-07    1215000\n",
       "2021-08    1229000\n",
       "2021-09    1197500\n",
       "2021-10    2138500\n",
       "2021-11    2748500\n",
       "2021-12    3290000\n",
       "2022-01    1430500\n",
       "2022-02    1181500\n",
       "2022-03    1870900\n",
       "2022-04      49900\n",
       "Name: 결제금액, dtype: int64"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# temp_var의 payment열을 date 기준으로 집계하기\n",
    "grouped = temp_var['결제금액'].groupby(temp_var['date']).sum()\n",
    "grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "c6bbffc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(rotation = 90 )\n",
    "ax = sns.barplot(data = grouped.reset_index(),x='date',y='결제금액')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "c5abfb18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "김치볶음밥          1204\n",
       "라면              749\n",
       "짜장라면            455\n",
       "치즈불고기볶음밥        420\n",
       "계란추가            314\n",
       "               ... \n",
       "라면(계란/치즈추가)       1\n",
       "녹차(HOT)           1\n",
       "짜장라면(계란추가)        1\n",
       "이어폰(커널형)          1\n",
       "오늘은 한돈간장불고기       1\n",
       "Name: 상품명, Length: 100, dtype: int64"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# temp_var의 상품명을 value_counts를 이용해 집계하기\n",
    "sales_item_count= temp_var['상품명'][temp_var['판매수량']!= -1].value_counts()\n",
    "sales_item_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "b94df5e4",
   "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>상품명</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>김치볶음밥</th>\n",
       "      <td>1204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>라면</th>\n",
       "      <td>749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>짜장라면</th>\n",
       "      <td>455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>치즈불고기볶음밥</th>\n",
       "      <td>420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>계란추가</th>\n",
       "      <td>314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>낙지볶음밥</th>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>새우볶음밥</th>\n",
       "      <td>309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>아메리카노(ICE)</th>\n",
       "      <td>284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>치즈감자튀김</th>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>감자튀김</th>\n",
       "      <td>242</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             상품명\n",
       "김치볶음밥       1204\n",
       "라면           749\n",
       "짜장라면         455\n",
       "치즈불고기볶음밥     420\n",
       "계란추가         314\n",
       "낙지볶음밥        312\n",
       "새우볶음밥        309\n",
       "아메리카노(ICE)   284\n",
       "치즈감자튀김       246\n",
       "감자튀김         242"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 집계 결과를 데이터프레임으로 변환하고, 상위 10개 선정하기\n",
    "sales_item_count = pd.DataFrame(sales_item_count)\n",
    "sales_item_count[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "1afcee66",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(rotation=90)\n",
    "ax=sns.barplot(data= sales_item_count[:10].T)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "16d2b737",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "상품명\n",
       "(면)계란추가-국물라면          5000\n",
       "(면)계란후라이 추가-불닭/짜장    20000\n",
       "(면)치즈추가              10500\n",
       "(밥)계란후라이 추가           3000\n",
       "(밥)슈레드치즈추가            4500\n",
       "Name: 결제금액, dtype: int64"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# temp_var의 payment열을 상품명을 기준으로 집계하기\n",
    "item_payment = temp_var['결제금액'].groupby(temp_var['상품명'][temp_var['판매수량']!= -1]).sum()\n",
    "item_payment.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "880fe063",
   "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>결제금액</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>상품명</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>김치볶음밥</th>\n",
       "      <td>6004400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>라면</th>\n",
       "      <td>2941500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>치즈불고기볶음밥</th>\n",
       "      <td>2292600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>짜장라면</th>\n",
       "      <td>2038500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>낙지볶음밥</th>\n",
       "      <td>1710700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>새우볶음밥</th>\n",
       "      <td>1539800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>치즈감자튀김</th>\n",
       "      <td>1354200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>감자튀김</th>\n",
       "      <td>1083800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>아메리카노(ICE)</th>\n",
       "      <td>1058100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>불닭볶음면</th>\n",
       "      <td>693000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               결제금액\n",
       "상품명                \n",
       "김치볶음밥       6004400\n",
       "라면          2941500\n",
       "치즈불고기볶음밥    2292600\n",
       "짜장라면        2038500\n",
       "낙지볶음밥       1710700\n",
       "새우볶음밥       1539800\n",
       "치즈감자튀김      1354200\n",
       "감자튀김        1083800\n",
       "아메리카노(ICE)  1058100\n",
       "불닭볶음면        693000"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_payment= item_payment.sort_values(ascending =False)\n",
    "item_payment_10 = pd.DataFrame(item_payment[:10])\n",
    "item_payment_10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "3fb3f974",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(rotation=90)\n",
    "ax=sns.barplot(data= item_payment_10.T)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "212b0063",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 22555 entries, 0 to 22554\n",
      "Data columns (total 8 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   요금제명    22292 non-null  object\n",
      " 1   입실      22555 non-null  object\n",
      " 2   퇴실      22555 non-null  object\n",
      " 3   이용      22533 non-null  object\n",
      " 4   위치      22555 non-null  object\n",
      " 5   금액      22555 non-null  int64 \n",
      " 6   구분      22555 non-null  object\n",
      " 7   고객      22555 non-null  object\n",
      "dtypes: int64(1), object(7)\n",
      "memory usage: 1.4+ MB\n"
     ]
    }
   ],
   "source": [
    "# 활용할 데이터(entry_data)를 temp_var로 정의하기\n",
    "temp_var = entry_data\n",
    "temp_var.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "4de8dd25",
   "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>금액</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>요금제명</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>한국대생 입장권(종일권)</th>\n",
       "      <td>70037000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>입장권(종일권)</th>\n",
       "      <td>23570500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>심야-조조무제한(06시까지)</th>\n",
       "      <td>11600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>심야-조조무제한</th>\n",
       "      <td>6221000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>한국대생 무제한 입장권</th>\n",
       "      <td>5207500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시간요금제(1시간)</th>\n",
       "      <td>2665500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시간요금제(3시간)</th>\n",
       "      <td>2042000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>무제한 입장권</th>\n",
       "      <td>1568600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18시이후 무제한</th>\n",
       "      <td>1330500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>조조무제한</th>\n",
       "      <td>693000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       금액\n",
       "요금제명                     \n",
       "한국대생 입장권(종일권)    70037000\n",
       "입장권(종일권)         23570500\n",
       "심야-조조무제한(06시까지)  11600000\n",
       "심야-조조무제한          6221000\n",
       "한국대생 무제한 입장권      5207500\n",
       "시간요금제(1시간)        2665500\n",
       "시간요금제(3시간)        2042000\n",
       "무제한 입장권           1568600\n",
       "18시이후 무제한         1330500\n",
       "조조무제한              693000"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tickets = temp_var['금액'].groupby(temp_var['요금제명']).sum()\n",
    "tickets = tickets.sort_values(ascending=False)\n",
    "tickets_10 = pd.DataFrame(tickets[:10])\n",
    "tickets_10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "3c7bb061",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(rotation = 90)\n",
    "ax=sns.barplot(data = tickets_10.T)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "e5f7cdec",
   "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>요금제명</th>\n",
       "      <th>입실</th>\n",
       "      <th>퇴실</th>\n",
       "      <th>이용</th>\n",
       "      <th>위치</th>\n",
       "      <th>금액</th>\n",
       "      <th>구분</th>\n",
       "      <th>고객</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18시이후 무제한</td>\n",
       "      <td>2021-07-31 20:25</td>\n",
       "      <td>2021-07-31 21:52</td>\n",
       "      <td>오전 1:27:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>4500</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer745742</td>\n",
       "      <td>2021-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18시이후 무제한</td>\n",
       "      <td>2021-07-31 20:25</td>\n",
       "      <td>2021-07-31 21:52</td>\n",
       "      <td>오전 1:27:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>4500</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer745742</td>\n",
       "      <td>2021-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>기간권</td>\n",
       "      <td>2021-07-31 18:50</td>\n",
       "      <td>2021-07-31 21:58</td>\n",
       "      <td>오전 3:08:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>0</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer490993</td>\n",
       "      <td>2021-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1시간</td>\n",
       "      <td>2021-07-31 18:08</td>\n",
       "      <td>2021-07-31 19:03</td>\n",
       "      <td>오전 12:55:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>2500</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer345478</td>\n",
       "      <td>2021-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1시간</td>\n",
       "      <td>2021-07-31 18:08</td>\n",
       "      <td>2021-07-31 19:03</td>\n",
       "      <td>오전 12:55:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>2500</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer345478</td>\n",
       "      <td>2021-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2444</th>\n",
       "      <td>입장권(종일권)</td>\n",
       "      <td>2021-09-01 12:49</td>\n",
       "      <td>2021-09-01 17:19</td>\n",
       "      <td>오전 4:30:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>6000</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer338849</td>\n",
       "      <td>2021-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2445</th>\n",
       "      <td>입장권(종일권)</td>\n",
       "      <td>2021-09-01 11:26</td>\n",
       "      <td>2021-09-01 20:02</td>\n",
       "      <td>오전 8:36:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>7500</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer971187</td>\n",
       "      <td>2021-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2446</th>\n",
       "      <td>입장권(종일권)</td>\n",
       "      <td>2021-09-01 11:25</td>\n",
       "      <td>2021-09-01 18:44</td>\n",
       "      <td>오전 7:19:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>5500</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer861314</td>\n",
       "      <td>2021-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2447</th>\n",
       "      <td>기간권</td>\n",
       "      <td>2021-09-01 9:50</td>\n",
       "      <td>2021-09-01 15:50</td>\n",
       "      <td>오전 6:00:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>0</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer440840</td>\n",
       "      <td>2021-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2448</th>\n",
       "      <td>조조무제한</td>\n",
       "      <td>2021-09-01 5:38</td>\n",
       "      <td>2021-09-01 21:18</td>\n",
       "      <td>오후 3:40:00</td>\n",
       "      <td>선불기2</td>\n",
       "      <td>4000</td>\n",
       "      <td>퇴실</td>\n",
       "      <td>customer667032</td>\n",
       "      <td>2021-09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2449 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           요금제명                입실                퇴실           이용    위치    금액  \\\n",
       "0     18시이후 무제한  2021-07-31 20:25  2021-07-31 21:52   오전 1:27:00  선불기2  4500   \n",
       "1     18시이후 무제한  2021-07-31 20:25  2021-07-31 21:52   오전 1:27:00  선불기2  4500   \n",
       "2           기간권  2021-07-31 18:50  2021-07-31 21:58   오전 3:08:00  선불기2     0   \n",
       "3           1시간  2021-07-31 18:08  2021-07-31 19:03  오전 12:55:00  선불기2  2500   \n",
       "4           1시간  2021-07-31 18:08  2021-07-31 19:03  오전 12:55:00  선불기2  2500   \n",
       "...         ...               ...               ...          ...   ...   ...   \n",
       "2444   입장권(종일권)  2021-09-01 12:49  2021-09-01 17:19   오전 4:30:00  선불기2  6000   \n",
       "2445   입장권(종일권)  2021-09-01 11:26  2021-09-01 20:02   오전 8:36:00  선불기2  7500   \n",
       "2446   입장권(종일권)  2021-09-01 11:25  2021-09-01 18:44   오전 7:19:00  선불기2  5500   \n",
       "2447        기간권   2021-09-01 9:50  2021-09-01 15:50   오전 6:00:00  선불기2     0   \n",
       "2448      조조무제한   2021-09-01 5:38  2021-09-01 21:18   오후 3:40:00  선불기2  4000   \n",
       "\n",
       "      구분              고객     date  \n",
       "0     퇴실  customer745742  2021-07  \n",
       "1     퇴실  customer745742  2021-07  \n",
       "2     퇴실  customer490993  2021-07  \n",
       "3     퇴실  customer345478  2021-07  \n",
       "4     퇴실  customer345478  2021-07  \n",
       "...   ..             ...      ...  \n",
       "2444  퇴실  customer338849  2021-09  \n",
       "2445  퇴실  customer971187  2021-09  \n",
       "2446  퇴실  customer861314  2021-09  \n",
       "2447  퇴실  customer440840  2021-09  \n",
       "2448  퇴실  customer667032  2021-09  \n",
       "\n",
       "[2449 rows x 9 columns]"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 매출이 많은 3~5월 입실기록 분류\n",
    "entry_data['date'] = entry_data['입실'].str[:7]\n",
    "entry_data\n",
    "entry_data_03 = pd.DataFrame(entry_data[entry_data['date']=='2021-03'])\n",
    "entry_data_04 = pd.DataFrame(entry_data[entry_data['date']=='2021-04'])\n",
    "entry_data_05 = pd.DataFrame(entry_data[entry_data['date']=='2021-05'])\n",
    "# entry_nv = pd.concat([entry_data_03,entry_data_04,entry_data_05])\n",
    "# entry_nv= entry_nv.reset_index(drop=True)\n",
    "# entry_nv\n",
    "\n",
    "# 매출이 적은 7~9월 입실기록 분류\n",
    "entry_data_07 = entry_data[entry_data['date']=='2021-07']\n",
    "entry_data_08 = entry_data[entry_data['date']=='2021-08']\n",
    "entry_data_09 = entry_data[entry_data['date']=='2021-09']\n",
    "# entry_v = pd.concat([entry_data_07,entry_data_08,entry_data_09])\n",
    "# entry_v = entry_v.reset_index(drop=True)\n",
    "# entry_v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "b89a87e2",
   "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>입실</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>요금제명</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>기간권</th>\n",
       "      <td>229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시간 요금제(1시간당)</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시간권</th>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시간요금제(1시간)</th>\n",
       "      <td>304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시간요금제(1시간당)</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시간요금제(3시간)</th>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>심야-조조무제한(06시까지)</th>\n",
       "      <td>1483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>이용권</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>입장권(종일권)</th>\n",
       "      <td>981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>한국대생 입장권(종일권)</th>\n",
       "      <td>4155</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   입실\n",
       "요금제명                 \n",
       "기간권               229\n",
       "시간 요금제(1시간당)       10\n",
       "시간권                55\n",
       "시간요금제(1시간)        304\n",
       "시간요금제(1시간당)         9\n",
       "시간요금제(3시간)         72\n",
       "심야-조조무제한(06시까지)  1483\n",
       "이용권                 5\n",
       "입장권(종일권)          981\n",
       "한국대생 입장권(종일권)    4155"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a=pd.DataFrame(entry_nv['입실'].groupby(entry_nv['요금제명']).count())\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "e177ebaa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(rotation=90)\n",
    "ax=sns.barplot(data = a.T)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "6d819ba7",
   "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>입실</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>요금제명</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18시이후 무제한</th>\n",
       "      <td>242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1시간</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3시간</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>기간권</th>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시간권</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시간요금제(1시간)</th>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시간요금제(3시간)</th>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>심야-조조무제한(06시까지)</th>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>이용권</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>입장권(종일권)</th>\n",
       "      <td>757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>조조무제한</th>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>한국대생 입장권(종일권)</th>\n",
       "      <td>794</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  입실\n",
       "요금제명                \n",
       "18시이후 무제한        242\n",
       "1시간               21\n",
       "3시간                3\n",
       "기간권              243\n",
       "시간권                5\n",
       "시간요금제(1시간)        94\n",
       "시간요금제(3시간)        51\n",
       "심야-조조무제한(06시까지)   87\n",
       "이용권                5\n",
       "입장권(종일권)         757\n",
       "조조무제한            113\n",
       "한국대생 입장권(종일권)    794"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b=pd.DataFrame(entry_v['입실'].groupby(entry_v['요금제명']).count())\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "id": "9ba3d7a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(rotation=90)\n",
    "ax=sns.barplot(data = b.T)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5aa562cf",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}