Data_visualization(1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "from matplotlib import font_manager\n",
    "f_path = \"C:\\Windows\\Fonts\\malgun.ttf\"\n",
    "font_manager.FontProperties(fname=f_path).get_name()\n",
    "from matplotlib import rc\n",
    "rc('font', family='Malgun Gothic')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "\n",
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       "        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>Code</th>\n",
       "      <th>Movie</th>\n",
       "      <th>Audience</th>\n",
       "      <th>Screen</th>\n",
       "      <th>genres</th>\n",
       "      <th>AgeRate</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>four_month</th>\n",
       "      <th>year_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20192193</td>\n",
       "      <td>도굴</td>\n",
       "      <td>565.469</td>\n",
       "      <td>1634</td>\n",
       "      <td>범죄</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>11</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20197121</td>\n",
       "      <td>삼진그룹 영어토익반</td>\n",
       "      <td>1257.444</td>\n",
       "      <td>1080</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20199816</td>\n",
       "      <td>담보</td>\n",
       "      <td>1702.252</td>\n",
       "      <td>407</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20208508</td>\n",
       "      <td>미스터트롯: 더 무비</td>\n",
       "      <td>140.594</td>\n",
       "      <td>159</td>\n",
       "      <td>공연</td>\n",
       "      <td>전체관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20194424</td>\n",
       "      <td>소리도 없이</td>\n",
       "      <td>401.759</td>\n",
       "      <td>126</td>\n",
       "      <td>범죄</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>352</th>\n",
       "      <td>20145501</td>\n",
       "      <td>돌연변이</td>\n",
       "      <td>100.498</td>\n",
       "      <td>7</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>353</th>\n",
       "      <td>20157465</td>\n",
       "      <td>그놈이다</td>\n",
       "      <td>1045.218</td>\n",
       "      <td>35</td>\n",
       "      <td>스릴러</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>20157464</td>\n",
       "      <td>더 폰</td>\n",
       "      <td>1593.592</td>\n",
       "      <td>7</td>\n",
       "      <td>스릴러</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>355</th>\n",
       "      <td>20142855</td>\n",
       "      <td>성난 변호사</td>\n",
       "      <td>1127.747</td>\n",
       "      <td>21</td>\n",
       "      <td>범죄</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>20149961</td>\n",
       "      <td>미안해 사랑해 고마워</td>\n",
       "      <td>50.571</td>\n",
       "      <td>5</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>357 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Code        Movie  Audience  Screen genres AgeRate  month  year  \\\n",
       "0    20192193           도굴   565.469    1634     범죄  청소년관람가     11  2020   \n",
       "1    20197121   삼진그룹 영어토익반  1257.444    1080    드라마  청소년관람가     10  2020   \n",
       "2    20199816           담보  1702.252     407    드라마  청소년관람가      9  2020   \n",
       "3    20208508  미스터트롯: 더 무비   140.594     159     공연   전체관람가     10  2020   \n",
       "4    20194424       소리도 없이   401.759     126     범죄  청소년관람가     10  2020   \n",
       "..        ...          ...       ...     ...    ...     ...    ...   ...   \n",
       "352  20145501         돌연변이   100.498       7    드라마  청소년관람가     10  2015   \n",
       "353  20157465         그놈이다  1045.218      35    스릴러  청소년관람가     10  2015   \n",
       "354  20157464          더 폰  1593.592       7    스릴러  청소년관람가     10  2015   \n",
       "355  20142855       성난 변호사  1127.747      21     범죄  청소년관람가     10  2015   \n",
       "356  20149961  미안해 사랑해 고마워    50.571       5    드라마  청소년관람가     10  2015   \n",
       "\n",
       "     four_month  year_cat  \n",
       "0             4        35  \n",
       "1             4        35  \n",
       "2             4        35  \n",
       "3             4        35  \n",
       "4             4        35  \n",
       "..          ...       ...  \n",
       "352           4        30  \n",
       "353           4        30  \n",
       "354           4        30  \n",
       "355           4        30  \n",
       "356           4        30  \n",
       "\n",
       "[357 rows x 10 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie = pd.read_csv(\"./datas/movie2015~2020.csv\", index_col=[0])\n",
    "movie.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. 연도별 총 영화 개봉 수\n",
    "### - 코로나 여파로 인해 2020년에는 영화가 많이 개봉하지 않았을 것으로 예상\n",
    "### - 2015~2020년 기간 중 가장 적진 않지만 지난 해에 비해 개봉 수가 21 감소하였음.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "       0\n",
       "year    \n",
       "2015  27\n",
       "2016  64\n",
       "2017  64\n",
       "2018  77\n",
       "2019  73\n",
       "2020  52"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 연도별 총 영화 개봉 수\n",
    "year_c = movie.groupby('year').size().to_frame()\n",
    "year_c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2018년에 77개로 가장 많았음\n",
    "sns.set_style('darkgrid')\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.plot(year_c);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "### 2. 연도 관계 없이 월별 총 영화 개봉 수\n",
    "# month_c = movie.groupby('month').size().to_frame()\n",
    "# month_c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# sns.set_style('darkgrid')\n",
    "# plt.figure(figsize=(10,6))\n",
    "# plt.plot(month_c);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 월별 총 영화 개봉 수\n",
    "### - 명절(1월, 9월), 크리스마스 시즌(12월) 등 연휴가 있는 달에는 외출과 만남이 더 자주 있어서 영화 개봉 수가 많을 것으로 예상\n",
    "### - 지난해에 비해 2020년 영화 개봉 수는 감소하였으나, 2020년 9월에 수가 전체에서 가장 많았음.\n",
    "### - 9월에 많다면 가족이 함께 관람할 수 있는 장르의 영화가 많을 것으로 예상하여 확인한 결과 드라마(2), 코미디(3) 장르의 영화가 많았음.\n",
    "### (담보, 오!문희, 국제수사, 죽지않는 인간들의 밤, 강철비2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "# my_c = movie.groupby(['month', 'year']).size().to_frame()\n",
    "# my_c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2020년 9월에 13개로 가장 많았음\n",
    "sns.set_style('whitegrid')\n",
    "plt.figure(figsize=(10,6))\n",
    "sns.countplot(x='year', hue='month', data=movie, palette='Spectral');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "scrolled": false
   },
   "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>0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genres</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>공연</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>공포(호러)</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다큐멘터리</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>드라마</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>뮤지컬</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>스릴러</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>애니메이션</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>액션</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>코미디</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        0\n",
       "genres   \n",
       "공연      1\n",
       "공포(호러)  1\n",
       "다큐멘터리   1\n",
       "드라마     2\n",
       "뮤지컬     1\n",
       "스릴러     1\n",
       "애니메이션   2\n",
       "액션      1\n",
       "코미디     3"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 가장 많이 개봉했던 2020년 9월 영화 장르\n",
    "m_20 = movie[movie['year'] == 2020]\n",
    "m_20_9 = m_20[m_20['month'] == 9]\n",
    "m_20_9.groupby('genres').size().to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "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>Code</th>\n",
       "      <th>Movie</th>\n",
       "      <th>Audience</th>\n",
       "      <th>Screen</th>\n",
       "      <th>genres</th>\n",
       "      <th>AgeRate</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>four_month</th>\n",
       "      <th>year_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20199816</td>\n",
       "      <td>담보</td>\n",
       "      <td>1702.252</td>\n",
       "      <td>407</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>20178401</td>\n",
       "      <td>검객</td>\n",
       "      <td>188.990</td>\n",
       "      <td>23</td>\n",
       "      <td>액션</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>20206588</td>\n",
       "      <td>극장판 미니특공대: 햄버거괴물의 습격</td>\n",
       "      <td>55.468</td>\n",
       "      <td>38</td>\n",
       "      <td>애니메이션</td>\n",
       "      <td>전체관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20206826</td>\n",
       "      <td>그대, 고맙소 : 김호중 생애 첫 팬미팅 무비</td>\n",
       "      <td>100.725</td>\n",
       "      <td>53</td>\n",
       "      <td>공연</td>\n",
       "      <td>전체관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>20193666</td>\n",
       "      <td>오! 문희</td>\n",
       "      <td>350.993</td>\n",
       "      <td>20</td>\n",
       "      <td>코미디</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>20204684</td>\n",
       "      <td>브레이크 더 사일런스: 더 무비</td>\n",
       "      <td>131.693</td>\n",
       "      <td>66</td>\n",
       "      <td>다큐멘터리</td>\n",
       "      <td>전체관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>20190601</td>\n",
       "      <td>디바</td>\n",
       "      <td>107.480</td>\n",
       "      <td>6</td>\n",
       "      <td>스릴러</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>20184482</td>\n",
       "      <td>국제수사</td>\n",
       "      <td>534.629</td>\n",
       "      <td>11</td>\n",
       "      <td>코미디</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>20190621</td>\n",
       "      <td>죽지않는 인간들의 밤</td>\n",
       "      <td>101.663</td>\n",
       "      <td>7</td>\n",
       "      <td>코미디</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>20208045</td>\n",
       "      <td>강철비2 : 정상회담 확장판</td>\n",
       "      <td>17.918</td>\n",
       "      <td>48</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20204643</td>\n",
       "      <td>다시 만난 날들</td>\n",
       "      <td>2.143</td>\n",
       "      <td>105</td>\n",
       "      <td>뮤지컬</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>20205284</td>\n",
       "      <td>매지컬: 공주를 웃겨라</td>\n",
       "      <td>3.901</td>\n",
       "      <td>22</td>\n",
       "      <td>애니메이션</td>\n",
       "      <td>전체관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>20206679</td>\n",
       "      <td>공포체험라디오 4DX</td>\n",
       "      <td>1.468</td>\n",
       "      <td>36</td>\n",
       "      <td>공포(호러)</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Code                      Movie  Audience  Screen  genres AgeRate  \\\n",
       "2   20199816                         담보  1702.252     407     드라마  청소년관람가   \n",
       "6   20178401                         검객   188.990      23      액션  청소년관람가   \n",
       "7   20206588       극장판 미니특공대: 햄버거괴물의 습격    55.468      38   애니메이션   전체관람가   \n",
       "9   20206826  그대, 고맙소 : 김호중 생애 첫 팬미팅 무비   100.725      53      공연   전체관람가   \n",
       "10  20193666                      오! 문희   350.993      20     코미디  청소년관람가   \n",
       "11  20204684          브레이크 더 사일런스: 더 무비   131.693      66   다큐멘터리   전체관람가   \n",
       "12  20190601                         디바   107.480       6     스릴러  청소년관람가   \n",
       "14  20184482                       국제수사   534.629      11     코미디  청소년관람가   \n",
       "15  20190621                죽지않는 인간들의 밤   101.663       7     코미디  청소년관람가   \n",
       "17  20208045            강철비2 : 정상회담 확장판    17.918      48     드라마  청소년관람가   \n",
       "19  20204643                   다시 만난 날들     2.143     105     뮤지컬  청소년관람가   \n",
       "22  20205284               매지컬: 공주를 웃겨라     3.901      22   애니메이션   전체관람가   \n",
       "25  20206679                공포체험라디오 4DX     1.468      36  공포(호러)  청소년관람가   \n",
       "\n",
       "    month  year  four_month  year_cat  \n",
       "2       9  2020           4        35  \n",
       "6       9  2020           4        35  \n",
       "7       9  2020           4        35  \n",
       "9       9  2020           4        35  \n",
       "10      9  2020           4        35  \n",
       "11      9  2020           4        35  \n",
       "12      9  2020           4        35  \n",
       "14      9  2020           4        35  \n",
       "15      9  2020           4        35  \n",
       "17      9  2020           4        35  \n",
       "19      9  2020           4        35  \n",
       "22      9  2020           4        35  \n",
       "25      9  2020           4        35  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m_20_9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 가장 많이 개봉했던 2020년 9월 영화 장르 그래프\n",
    "from matplotlib import font_manager\n",
    "f_path = \"C:\\Windows\\Fonts\\malgun.ttf\"\n",
    "font_manager.FontProperties(fname=f_path).get_name()\n",
    "from matplotlib import rc\n",
    "rc('font', family='Malgun Gothic')\n",
    "\n",
    "plt.figure(figsize=(10,6))\n",
    "m_20_9['genres'].value_counts().plot.pie();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 각 계절별 총 영화 개봉 수\n",
    "### - 월을 사계절로 묶은 후 월별 영화 개봉 수에 변화가 있는지 확인\n",
    "### - 전체 년도 합해서 각 계절을 살폈을 때 가을이 가장 많았음.\n",
    "### - 년도별로 각 계절을 확인했을 땐 2018년 겨울이 가장 많음.\n",
    "### - 겨울에는 로맨스 영화가 많을 것으로 예상했으나, 드라마와 범죄 영화가 가장 많았음.\n",
    "## - 전체적으로 추운 계절인 가을과 겨울에 영화가 가장 많이 개봉하는 것으로 보인다.\n",
    "\n",
    "```\n",
    "four_month\n",
    "4 : 9~11월\n",
    "3 : 6~8월\n",
    "2 : 3~5월\n",
    "1 : 12~2월\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "alignmentgroup": "True",
         "bingroup": "x",
         "histfunc": "sum",
         "hovertemplate": "four_month=%{x}<br>sum of Audience=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#636efa"
         },
         "name": "",
         "offsetgroup": "",
         "orientation": "v",
         "showlegend": false,
         "type": "histogram",
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   "source": [
    "# 봄에 영화를 보러 가는 사람이 가장 작다! 영화가 적은 것일까? 볼만한 영화가 별로 없는것일까?\n",
    "# 계절별 총관객수\n",
    "import plotly.express as px\n",
    "fig = px.histogram(movie, x=\"four_month\", y=\"Audience\").update_xaxes(categoryorder=\"total ascending\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
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       "        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>0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>four_month</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              0\n",
       "four_month     \n",
       "1            89\n",
       "2            79\n",
       "3            84\n",
       "4           105"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 전체 년도 합해서 각 계절에 개봉한 총 영화\n",
    "movie.groupby('four_month').size().to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 전체 년도 합해서 각 계절에 개봉한 총 영화 그래프\n",
    "sns.set_style('whitegrid')\n",
    "plt.figure(figsize=(10,6))\n",
    "sns.countplot(x='four_month', data=movie, palette='Spectral');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>four_month</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2015</th>\n",
       "      <th>1</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2016</th>\n",
       "      <th>1</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2017</th>\n",
       "      <th>1</th>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2018</th>\n",
       "      <th>1</th>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2019</th>\n",
       "      <th>1</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">2020</th>\n",
       "      <th>1</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  0\n",
       "year four_month    \n",
       "2015 1            7\n",
       "     2            3\n",
       "     3            3\n",
       "     4           14\n",
       "2016 1           17\n",
       "     2           15\n",
       "     3           16\n",
       "     4           16\n",
       "2017 1           14\n",
       "     2           18\n",
       "     3           12\n",
       "     4           20\n",
       "2018 1           22\n",
       "     2           19\n",
       "     3           19\n",
       "     4           17\n",
       "2019 1           20\n",
       "     2           16\n",
       "     3           19\n",
       "     4           18\n",
       "2020 1            9\n",
       "     2            8\n",
       "     3           15\n",
       "     4           20"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 년도별 각 계절의 총 영화 개봉 수\n",
    "movie.groupby(['year', 'four_month']).size().to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 년도별 각 계절의 총 영화 개봉 수 그래프\n",
    "sns.set_style('whitegrid')\n",
    "plt.figure(figsize=(10,6))\n",
    "sns.countplot(x='year', hue='four_month', data=movie, palette='Spectral');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "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>0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genres</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>가족</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다큐멘터리</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>드라마</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>범죄</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사극</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>스릴러</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>애니메이션</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>액션</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>코미디</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        0\n",
       "genres   \n",
       "가족      1\n",
       "다큐멘터리   2\n",
       "드라마     4\n",
       "범죄      4\n",
       "사극      2\n",
       "스릴러     1\n",
       "애니메이션   3\n",
       "액션      2\n",
       "코미디     3"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 가장 많이 개봉했던 2018년 겨울 영화 장르 그래프\n",
    "m_18 = movie[movie['year'] == 2018]\n",
    "m_18_1 = m_18[m_18['four_month'] == 1]\n",
    "m_18_1.groupby('genres').size().to_frame()\n",
    "# len(m_18_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. 장르별 총 영화 개봉 수\n",
    "### - 모든 영화 중 범죄, 액션, 스릴러 장르의 영화 가장 많이 개봉하는 것으로 예상\n",
    "### - 2015~2020년 개봉한 한국 영화에는 드라마(75)가 가장 많았고, 다음으로는 코미디(48), 범죄(43), 애니메이션(35)이었음."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 장르별 개봉한 총 영화 수 그래프\n",
    "from matplotlib import font_manager\n",
    "f_path = \"C:\\Windows\\Fonts\\malgun.ttf\"\n",
    "font_manager.FontProperties(fname=f_path).get_name()\n",
    "from matplotlib import rc\n",
    "rc('font', family='Malgun Gothic')\n",
    "\n",
    "plt.figure(figsize=(10,6))\n",
    "sns.countplot(x='genres', data=movie, palette='Spectral');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "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>0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genres</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SF</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>가족</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>공연</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>공포(호러)</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>기타</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다큐멘터리</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>드라마</th>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>멜로/로맨스</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>뮤지컬</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>미스터리</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>범죄</th>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>사극</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>스릴러</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>애니메이션</th>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>액션</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>어드벤처</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>전쟁</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>코미디</th>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>판타지</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         0\n",
       "genres    \n",
       "SF       2\n",
       "가족       4\n",
       "공연      12\n",
       "공포(호러)  11\n",
       "기타       2\n",
       "다큐멘터리   11\n",
       "드라마     75\n",
       "멜로/로맨스  12\n",
       "뮤지컬      4\n",
       "미스터리    21\n",
       "범죄      43\n",
       "사극      19\n",
       "스릴러     21\n",
       "애니메이션   35\n",
       "액션      27\n",
       "어드벤처     1\n",
       "전쟁       3\n",
       "코미디     48\n",
       "판타지      6"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 장르별 개봉한 총 영화 수\n",
    "movie.groupby('genres').size().to_frame()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. 계절별 각 장르의 총 영화 개봉 수\n",
    "### - 공포, 스릴러, 범죄, 액션은 여름에, 사극, 로맨스는 겨을에 가장 많이 개봉할 것으로 예상\n",
    "### - 년도를 나누지 않고 각 장르가 어느 계절에 많이 개봉했는지 확인한 결과 범죄: 가을, 드라마: 겨울, 액션: 여름, 코미디: 가을, 스릴러: 봄, 공포: 여름, 사극: 가을, 미스터리: 봄 으로 확인\n",
    "### - 전체적으로 드라마 장르의 영화가 가장 많이 개봉한 것으로 확인 했으며 각 계절로 확인해 보아도 언제나 드라마가 가장 많은 것으로 확인. 관람등급이 대부분 '청소년 관람가'로 분류되어 있으며 관람객들을 가장 많이 끌어드릴 수 있기 때문으로 보임.\n",
    "```\n",
    "four_month\n",
    "4 : 9~11월\n",
    "3 : 6~8월\n",
    "2 : 3~5월\n",
    "1 : 12~2월\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "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>Code</th>\n",
       "      <th>Movie</th>\n",
       "      <th>Audience</th>\n",
       "      <th>Screen</th>\n",
       "      <th>genres</th>\n",
       "      <th>AgeRate</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>four_month</th>\n",
       "      <th>year_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20197121</td>\n",
       "      <td>삼진그룹 영어토익반</td>\n",
       "      <td>1257.444</td>\n",
       "      <td>1080</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20199816</td>\n",
       "      <td>담보</td>\n",
       "      <td>1702.252</td>\n",
       "      <td>407</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>20206291</td>\n",
       "      <td>피원에이치 : 새로운 세계의 시작</td>\n",
       "      <td>1.912</td>\n",
       "      <td>21</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>20208045</td>\n",
       "      <td>강철비2 : 정상회담 확장판</td>\n",
       "      <td>17.918</td>\n",
       "      <td>48</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>20196271</td>\n",
       "      <td>강철비2: 정상회담</td>\n",
       "      <td>1789.780</td>\n",
       "      <td>9</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>7</td>\n",
       "      <td>2020</td>\n",
       "      <td>3</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392</th>\n",
       "      <td>20157466</td>\n",
       "      <td>로봇, 소리</td>\n",
       "      <td>475.622</td>\n",
       "      <td>49</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>1</td>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>20144442</td>\n",
       "      <td>조선마술사</td>\n",
       "      <td>627.379</td>\n",
       "      <td>53</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>12</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>399</th>\n",
       "      <td>20156748</td>\n",
       "      <td>열정같은소리하고있네</td>\n",
       "      <td>654.407</td>\n",
       "      <td>1</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>11</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411</th>\n",
       "      <td>20145501</td>\n",
       "      <td>돌연변이</td>\n",
       "      <td>100.498</td>\n",
       "      <td>7</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>20149961</td>\n",
       "      <td>미안해 사랑해 고마워</td>\n",
       "      <td>50.571</td>\n",
       "      <td>5</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>75 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Code                Movie  Audience  Screen genres AgeRate  month  \\\n",
       "1    20197121           삼진그룹 영어토익반  1257.444    1080    드라마  청소년관람가     10   \n",
       "2    20199816                   담보  1702.252     407    드라마  청소년관람가      9   \n",
       "16   20206291  피원에이치 : 새로운 세계의 시작      1.912      21    드라마  청소년관람가     10   \n",
       "17   20208045      강철비2 : 정상회담 확장판    17.918      48    드라마  청소년관람가      9   \n",
       "18   20196271           강철비2: 정상회담  1789.780       9    드라마  청소년관람가      7   \n",
       "..        ...                  ...       ...     ...    ...     ...    ...   \n",
       "392  20157466               로봇, 소리   475.622      49    드라마  청소년관람가      1   \n",
       "396  20144442                조선마술사   627.379      53    드라마  청소년관람가     12   \n",
       "399  20156748           열정같은소리하고있네   654.407       1    드라마  청소년관람가     11   \n",
       "411  20145501                 돌연변이   100.498       7    드라마  청소년관람가     10   \n",
       "415  20149961          미안해 사랑해 고마워    50.571       5    드라마  청소년관람가     10   \n",
       "\n",
       "     year  four_month  year_cat  \n",
       "1    2020           4        35  \n",
       "2    2020           4        35  \n",
       "16   2020           4        35  \n",
       "17   2020           4        35  \n",
       "18   2020           3        35  \n",
       "..    ...         ...       ...  \n",
       "392  2016           1        31  \n",
       "396  2015           1        30  \n",
       "399  2015           4        30  \n",
       "411  2015           4        30  \n",
       "415  2015           4        30  \n",
       "\n",
       "[75 rows x 10 columns]"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie[movie['genres'] == '드라마']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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aWSwWdevWzfjenD9/XmPGjNGWLVt03XXX6YMPPlBAQICWLl2qP//8U15euatunTt3Vp06dfLNGRwcrNOnTxu34+LijO9s7969lZ2dre3btys0NFSHDh3S2rVrNW3aNB07dkzHjh1TXFyc4uLiJEleXl46d+6cqlevro8//lgLFizItwI+bNgwnTx5UjabTWFhYdq2bZtuuOEG2e12JSUlacaMGerdu7fat2+vc+fOydfXV3FxcXr44YeVnZ0tT09PDR8+XNu3b9dzzz1XbBCZmZmZ7zPIY7PZ9OuvvxrvyeOPP25stFz699etWzd98cUXBcbfeeedOnz4sHbv3q3atWvL4XDowQcf1F133ZVvoz9Pdna2pkyZou3btys9PV233Xabjh49qr/++kt+fn7y8PDQ3Llzi3wdpVHafvvSSy8pJiam2A2aK9lzr1S/laRrr71WNWvWzNdvg4OD1a1bN504cUJLly7Nt3H+936ZkZGhZ599Vo888oj+85//OK3n7tq1S1LBjfC1a9dq9uzZxu2zZ8/qv//9rx577DEdO3ZM119/vaTcK2NaLBZJub2yevXqysjI0Ntvv61NmzZp7ty5Wrdunc6cOaMqVapIyu25O3fu1JAhQxQaGqoffvhB06ZN04kTJ4x58npumzZt5HA4CtROv811uX47Z84c3XLLLfn6rSS98sorRr+98cYb9c9//tPot+fOnVPXrl3Vr1+/y/bcHTt2KCMjQ2lpadq3b59OnDihuLg4Pfnkk0pJSdG8efP06aefas6cOfn67aRJk7Rnzx4NGDDAeH1/V5aeu3v3bq1fv16PPPKI6tatmy/ok3L7bYcOHTR+/HilpaWpQYMGbu23hB4AgBJ5/vnnjV8en3nmGfn7+8vX11fZ2dnGMidPntSKFSvk6+urCxcuFDvf+fPnlZGRISn3l9jSiI2NVUxMjF566SXdcMMN8vb21j//+U9jg2D27Nm6/fbb1aVLF6WlpSk6OlrXXXedzp07pzZt2kiSZs2apbi4OI0aNUqnTp1SbGysHnnkkUKfLzU1VVLuyt60adN06NAhde/evcByl24sxMTEFFn/J598oltvvVWPPfaYVq9erUmTJunixYtFLp+34nn69GktW7ZMhw8fVu3ateXh4SGr1ap169Zp165dxV75bODAgQVWQvKcPHlSBw4c0IoVK+Tn56du3brle7xOnTr5fpH66quvCszRtGlT41ccSdq4caP+9a9/Gbfvu+8+DRw4UD169NCCBQv0xx9/6IYbbtAPP/yg+Ph447O777771LRpU23ZskUpKSmKiorSgQMH5Ofnp4MHDxrzJSUladGiRRo5cqSSkpJks9kkSVarVVarVRs2bJAkNWvWzFgJ79atm6ZMmaLZs2dry5YtWrduXYHXMXv2bDVv3ly33XabcV/ehsXfrVq1qshf4mw2my5cuCCbzaaLFy/m+1U371fEJ554Qh4eHnrttdc0YsQIVa1aVbNmzVKnTp0UEhKijIwMvfHGG8ZK/6Xq1KlT6C7zl37vcnJydOzYMUm5G27vvfeeIiMj9eabb+rFF1/Ua6+9pipVqujw4cOaO3eujh07JofDofvvv19PPfWUkpOTi9wwnjJliiSpR48eio+PV+/evTV48GD16tVLderU0aRJk7RlyxYlJycrMDBQkuTt7a0WLVooIyNDU6ZMkdVqVdu2bQudPzMzU/3799ecOXPk7e1d6Gv9+4ZlzZo19eGHH0qSnnvuOeP+hISEAhsskvT555/r448/VnBwsCZOnChJ2rt3r8aNG6frr79ezz77bL7l16xZk29FOyMjQ2PGjNEbb7xx2V/NS6u0/Tbv+1+cK9lzK0K/feKJJ/Trr78qNjZWQ4YMUXp6eqHLHz9+3Hj+RYsW6dixY9qwYYOWLFmi06dPO6XnHj9+XD/++GOBjXCpZP1Wklq2bGn03LwfF7Zs2WI8funf6KhRo4zPrVu3bsZGa6dOneTj46NffvlFjRo10m+//aYmTZrogQce0P79+41f7+m3pe+3khQWFqaQkBA1atRIjRs3VocOHbRkyRJjT4e5c+fqyJEjio+PN/ptv379Cn2Nf++5Xbt21f79+3Xffffpiy++UJ8+ffL9N1KSNm3apObNm+frtxaLRbVq1Sowv7N67pkzZ9S2bVv997//zbfs4sWLtXv3bm3btk1Vq1bVc889p6SkJLf1W0IPAECJzJw5U4sXL5aUu+vuXXfdJX9/f2Oj6KuvvtKXX36p8ePHKygoSJ06ddK7775b6O7KkvTCCy8YuwJL0l133SUpdwN/4MCBuv3229WjR48i63E4HHrhhRf0zDPP6Nlnn1VAQIDxa9a2bduM/zj7+fnplltu0aOPPqozZ85o06ZNSk9PV3BwsKxWqy5evKjmzZvLbrfrwoULevHFF/M9z44dO3T69GkdPHhQXbp00aBBg/TDDz+U6D07ffq0scdDno8//lizZ89WkyZN9PXXXysgIEBbtmyRl5eXqlWrVmCOHTt2yOFw6Omnn1aDBg306KOPyuFwqFatWsYv5o888oheeOGFQn8tyfPBBx8U+evjd999p5kzZ+r6669X+/bt1alTJwUFBRkbGomJiVq+fLmqVKkiX19fBQcHq1mzZgXmuXjxorEhkbdHzd/t379fp06dUlxcnLHLuZ+fn/HZ+fv7q06dOoqLi9N9992nGjVq6K233lKzZs103XXXGfN89NFHRqiSt5fJhx9+mO+Xyeeee0633HKLcfuHH35Q7dq19eWXXyo4OFhS7vfo/fffV5UqVRQdHa2cnBx9+OGHatasmbHyffjwYUVHR6tv377q0KGDJOno0aP6/fffNXjw4EJf56pVq3TmzBmtWrVKDodDAQEBOn36tO6//35Vr15do0ePVvPmzSXlrlCPGTNGDRs21LZt2zR06FDt3r1bR48e1ebNm1WtWjUFBATop59+koeHh7p27Wo8z6hRo5SSkiJfX19JyhcipKen59udePjw4cYvunkhm5eXl0JCQtSgQQMFBQWpatWqevjhh5WWlqb9+/cXuWH498/T4XBo5syZGjRokN5//30999xzOnLkiO677z79+OOPxmeWt8J75513qlGjRsrJySn0e/v999+rU6dOxuvo169fgeV27txZ5AZSnmPHjun8+fPG7vd5/eXGG2/U9u3bjQ3OkSNH6tZbb1WnTp302GOPScr9+837nkhSvXr1NG/ePOP+4jZ4y6u0/faVV14psMHzd1eq5yYkJFyxfitJy5YtU0BAgL744gtZrVbt3LlT3t7eOnHihLHX2aXPf+jQITkcDk2cOFF16tTRddddpzvvvFOPPPKIli5dWu6em5mZqXfeeUfNmjWTp6enhg0bpszMTJ04cUJdu3ZVYmKivLy8tH79eqWmpio4OFiDBg1SWFhYgc8jb0+DovqtlPs3OmPGDE2ePFne3t7y8/PL9921Wq1KSkqSxWJRkyZNtGPHDlksFqWkpCgoKEgS/TZPafrtwIEDtWfPHvn6+qpmzZo6fPiwPD09NXLkSO3atUsHDx7UI488IpvNZvTbEydOGHtSFvd5HjlyRAcPHtSnn36qIUOGKDg4WC+88IImTJhgLPfxxx/rlltu0aJFi/L125ycHJ04caJA73RGz807zOfQoUOS/q+33HTTTYqIiNDPP/+szp07y2azadSoURoxYoTb+i2hBwDgsvJ2pf67a665xliRCA0N1Xvvvadt27YpKSlJrVu31s8//6yVK1cqJSXF+CVo1qxZxgrDmDFjCszp4eGhDz74oNA69uzZo8OHDxu/igQHByszM1Px8fEKCQnRJ598ovbt2ys0NFQ7duzQTTfdJCn3P9R79+41Ngp8fX2VlZWldevWKTU1Vbt27VLdunVVrVo1TZw4UVFRUfr444/lcDg0bdo0DRw4UN98843uu+8+/fDDD7LZbOrcuXOx75nD4VBsbKz27t2b7/5evXopISFBM2fOVGJionGug+zsbOPQkDyZmZmaNm2aqlatavzKO2vWLOXk5Mjb21tVq1aVxWLRzJkzZbFYjBVFf39/2e1245eXon5tlKT//e9/slgsmjRpkvFZtmjRQuPGjdOPP/6oyMhINW7cWBcuXFCLFi1UpUoVeXt7F1gB9/b21n333SeHw2EcHlOzZk3985//1NGjR9WiRQtNnjxZGRkZGj9+vA4cOKBPP/1Ue/bsUc2aNfXJJ5/otttuU1JSkpYsWSI/Pz8NHTpUUu5xvw888IDxK2ZaWposFovxa152drb+/e9/a+7cuapataqk3I2Anj17avHixfL09DR+xWvZsqWmTZumDh066N5779Wnn36q66+/XuHh4Ro4cKAk6Z133lH79u3VunXrQt+zlJQUjRkzRhMnTixyBXDgwIHasGGDBg4caOxuHRwcrHfffVf+/v75lm3WrJnefvttpaWladCgQcac3bp1M0KF33//Xd27d5eXl5cyMzPzjR87dqyuvfbaAjX4+fnplVdekZS7B8N7772nO+64w3jPfHx8jGVr1qyp/fv3q2HDhvr888+1adMmXbx4Uf/4xz8k5a6QDhw4UI8++qixYvznn3/KarVq+fLlOnz4sG688UatX79eDRo00NKlS/O9zoMHDyojI0MNGjTQhx9+qO3bt+u6667T0KFDjUMyLrV8+XK98847Rq15G1mlcfjwYR05ckQ9evQw/rY8PDzUokULJSYmKjw83FjJvvfee7Vq1Srt27fPOCwiKCgo30p448aNNWLECI0dO1ahoaHG92XkyJHy8/NTaGioXnvttVLVWJiy9Ntp06apd+/eev311/P1W+nK91wvL68r1m8lqUGDBpo5c6ak3AD3vffe04QJE7R9+/Z855PI67cLFy7UE088oRdffFFjxozRrl27ZLPZNGPGDEkqV899//339dNPP6lfv3564oknjPdqxowZqlmzpqTc79l3332nPXv2qE2bNqpevbrCwsIUGBiYb8+rpKQkPfzww0a/rV69uk6dOqV33nlHLVq0UHx8vI4dO6aMjAxt375dn376qXx8fHTNNdfot99+U6tWrdSoUSMlJyfLZrOpS5cueuyxxzRo0CD17t1bO3bs0Lp16+i3Zey3H3zwgXr16mXs9WG3242em5OTo5MnT+rQoUO6cOGCRo4cqYsXL6pevXo6evSoqlevXmTP9fLyUr9+/XTnnXdq8eLFql69unbs2KGwsDDj7/zChQvKzMzUgw8+qJUrV2rChAkF+u3fD2Mtb89NT0/XW2+9pRo1ahh7suT1lkmTJmnKlCm64447FBwcrNtvv12hoaF6++23VbNmTXXs2NHl/ZbQAwBQIr/99ptmzJiR7z+UDodDjz76qCQZG8HJyck6c+aMpk+fLklFntPj73JycgqsXOQ9xxtvvCEpd6WhWrVqatu2rb7++muNHz++wPI1a9ZUv3799Oqrr+rrr7/W8ePH1aZNG9ntdp0/f95Y6XjjjTe0YMECnTp1SgsWLJCnp6eys7Pl7+8vq9Wq1q1b6/XXX9ekSZN08uRJdenSRW+++aamT5+u77777rLvl4eHhyZPnlzoL31VqlTR2bNnNXXqVM2aNUsOh0NVqlQx9kQ5fPiwnnrqKe3du1etWrWSp6enXn75ZQ0ZMkQvvfSSMjIy9MUXXygqKko7duzQH3/8occff1xWq9XY3fzJJ58s0YnKWrVqpdatW6tevXo6c+aM7Ha7rr32WvXs2dPYBT4iIkLXX3+9goKCjBXfw4cP6/Dhw2ratKmk3F+mx4wZo379+qlevXr5niMhIUG//vqr/vjjD7322muaPXu2Xn31Vfn7+8tisSgjI0Nt27ZVrVq1tGDBAqWmpur06dPGr3wWi0U7d+40TnSWlJSkJk2aGPPnfSe3bt1qbHRt3bpVHh4exrlPxowZoyZNmmjEiBE6efKk3n33XUVERKhp06YaMGCANm3apNOnT2vIkCE6ffq0vv76a2PF1m636/PPP5eU+31+//33NXTo0AKvU8r9XiUlJen555/XqVOn9MMPPxi7GEsqsAJ+KT8/P/n4+Bi/2p49e1ZVqlTRyJEj9d///ldpaWnG3kCBgYGKjo7W3r17tW/fPuNXsEs3cNPS0oxfRrdv366hQ4cqIyNDo0ePVkpKisaOHWtsTB46dEjPPvusPvnkEy1atEienp75zvsQHBxcYMN41qxZ+uCDD/T6669rxowZCgwMNE5AGBkZqRkzZqhatWp66qmnVL9+ffXq1Uv33HOP7rrrLuM1OhwOjRo1yvgbl6Q//vhDTZo0yfcrfGJiYqGHMLz00kvGOR4CAwONjc6DBw9q9OjRCgsLU7du3YwNVik3ePT399fJkyc1bNgw4/4qVarowoULWrFiRZEhQLNmzfTuu+/ql19+0ahRo2S1Wl1yeEtp+60kzZkzp8T9VnJvz60I/bZ69ep6++23jUM7fH19lZKSojlz5ujQoUO6/fbbVaNGDS1cuFB+fn5688039dhjj2nbtm1q0aKFfvvtN915553l6rm9evUy9tRLTU1Vdna2qlWrpjFjxujnn39WTk6OIiIiFBAQoA0bNhg9N6/ftm/f3gjv//GPfxTbb9u2bavY2Fij57Zu3Vr+/v7KyMhQRkaGatasqc8++0wLFy5U9erVNXXqVE2dOlUWi0WRkZEKCwtT79696bcqfb/dtWuXduzYoR07dqhWrVpKSkpS7dq1jZ575MgR9enTR0uWLJG/v78WL15s9Nu8v+2ieu6MGTP02muv6bnnnlOtWrW0atUq2e121apVSyEhIapevbreffdd4zWtX79ev//+u6T/67fXXXed/vjjD6N3lrfnnjhxQgcPHtSSJUs0fvx4Pfroo/l67tChQ3Xx4sV8/VbK/dt0OByFhrySc/stoQcAoETOnDmjxx57LN9/nDZu3KgNGzbo3Llz+vbbb5Wdna2ffvpJf/zxh2bPnq2cnBz5+voqLS0t3y+Pffv2VePGjfXPf/5TFovF+KXl8ccfL/C8b731lux2u3Hb19dXBw8e1IEDB4xjXL29vTV48GBjRUeSpk+frpSUFFWpUsVYyb10I65q1aoKCAjQxYsX1a9fP3l7eyszM1PDhw+Xn5+fbrzxRkVEROimm27St99+q4SEBIWGhmrKlCnasWOHMjMzC/wHPCcnR6tWrZKUu7JRlK5du+qNN96Q3W7XO++8Y/zCtnTpUm3evFk9e/ZUVlaW0tLSFBoaqokTJ6pRo0aKiYmRl5eX8ctRmzZt5OnpqS1btigrK0tBQUG65pprjOfeuHGjNm/ebJyQbMiQIapXr55x/gJJuummm7RixQqtXLlSHh4e8vPzM/YGuHR30ho1auiXX36Rt7e38XlVq1ZNqampOnnypJYsWaI//vhDO3bskI+Pj3bv3q2QkBB5eXmpQ4cO+uOPP3TbbbepTp06slqtGjRokJo0aaLU1FTdc889xoreuHHjdPr0af35559av369srOzdfvtt2vv3r1GCJOWllZgt/Tp06fr448/1qRJk5STk6N27doZwduxY8d0xx13GHsTtGrVSkOGDClwErfg4GDNmzdPa9eu1bZt24wN6Es3pDZv3qy33nor3y9SeZ566injtZw6dUq33XabcWJAb29vnT17tthzD0jSLbfcosmTJys8PFxTp07VNddco+nTp+vgwYNq3ry5sRKe99r+/e9/a9++ffLx8ZHFYtHIkSN18803q0aNGnr++ecLrEw+++yzGj9+vGbMmGF8D+bPn6/ExES98847+vbbb/XMM8/oqaeeMo7pzztp4aU+/PBD3Xjjjbrhhhs0cuRITZs2TTVq1NDu3bsVGBho/NL3119/6eLFi3rkkUdUpUoVPfXUU6pVq5aqVq2q7OxsPfzww5o+fbr++usv3XzzzZJyr7Jw6cZjlSpVtH79ekm5hypkZ2cXupL85ptvKj09XRcuXNB//vMfRUdH64UXXiiwXN6GUM2aNS97nP6lTpw4oWrVqhkb6e+//75CQkIKXba8Stpvt23bpr179xbbb6Ur33MrQr99/vnndeDAAWPDdPDgwfrxxx918803KzQ0VCdOnFCtWrVUp04dJSUladasWQVOgFvenuvv768bb7yx0J5rtVqN9z0gIEB16tTJ13PPnTun3377zTgXUt734IYbbpAko+devHhRzZo10y+//KKGDRvqiy++kJeXlwYNGqTmzZurTZs2uu6661S9enVFRUUpKipKp0+f1uzZs41+K+XurfDzzz/r9ttvp9+Wsd82b95cY8eO1Ycffmh8B1atWqVz585p4MCB+vbbb/X666/rq6++0qFDh/TXX3/piy++MAL/S+X13LCwML366qsaOHCgnnvuOa1YsULZ2dnGjxA7d+7Ua6+9ptdee00ff/yxRowYoaioKH355ZfKyMjQwYMHVbdu3XxX9ylPzz137pw+/vhj9e3bt8D3JI+/v7/8/f2vaL8l9AAAlJvValWdOnVksVj07LPPytvbWz4+PvL399fx48e1cePGAr+AFfYfdUkFdqe85ppr8t12OBzq06ePGjdubBw/e/z4cT3//PPGMfCS8h17nadt27b5jsGNiopSly5d9O9//1vp6el6++23lZOTo6ioKFksFlWpUkXx8fG68cYbNWHCBHl4eMjb21u+vr6qUqVKgQ2Lp59+2tjYe/LJJwu8tl9//dXYzTo1NVVnz57VuXPntHXrVi1dulSpqalq1qyZETpIuceF551XIW9D5aGHHlJCQoLq16+v+vXra/Xq1erUqZOxYrhx40ZJubuoXvpLbkRERL561q1bV+jZz7dv366TJ08av0i2b99eDz74oHEp3TzHjh1TgwYNFBkZqc6dO+uJJ57QNddcI19fXx06dEj16tXTk08+qQsXLui3335T7969FRkZqTlz5ujgwYOqU6eOfvrpJ82ePTvfxunhw4cVFxenEydOKCcnRzt37tT58+eN9+Waa67Rr7/+mq+WunXr6tVXXy10Ba1evXqqV6+ekpKS9O9//1u+vr6yWq3y8PAwTpp4qePHjxd6ojdJhZ7RPk9AQIDxXJdKT0+Xp6enqlevnu9kr0VZt26d1q1bpxEjRhivOe/7vHPnTv3www8FNsbS0tKMfzds2NAIiDZs2KDff/9d/fv3l5S7q/ilG2Hnzp3T//t//0/Dhw+XJL388stat26djhw5YuyBdOlhMHljLBaL8V6Eh4fr2Wef1aeffqqjR4/q9OnTxjlDMjMz8111JzMzU0FBQcb30svLy7jqhJR7cs6MjIx8528pjcTERG3atMnYFXrAgAH5Xm9KSsplN4SK2oD+66+/9MYbb6hq1ary8PDQ4MGDtXz58jLVWR6X9tuGDRuWqN9KV77nurvfSv/Xc1NTU9WjRw/jyhx5/fbcuXPq0KGDcWWRDz74wOgPef22devWuuuuu/Tbb7+Vq+euW7euyMMF8npu+/btJeUeVnTu3DnjnClS7t9Kq1atdP3116thw4Y6ePCgFi9erFq1aslqterw4cPq16+f/P39jcu8bt68WXPmzFGNGjW0ZcsWeXt7a+jQoQVO1nn48GFjT5OdO3dKktFz6bdl77cvvPCCxowZY2zsnzt3TmvXrtXKlSslSffff7+OHj2qQ4cOKS0tTQ6HQ9dcc02Jeu5NN92k1NRU7du3Tw6Ho9Cem9dv877Lee9LXr+Vyt9zt2/fLi8vLyPwuLTnxsTEFPu9zxu/du1a47ufx9n9ltADAFBic+bMMS4nKuX+h/iee+6Rj4+Pcez/3/39PBXllXfiw0uP7c3bvbgsAgMD9e9//9u4nXcCrkv5+PgY15MvTt65AIpy++23G7+iFaa4y0heysPDI9/KcN5KQWGWLFlS4HwJQUFBmj59utq1a1fkiWa//vpr2e12Y0Xk5MmTevjhhwv82pO3nCSFhITo/fffl5T7K+ro0aMVGBiohIQEtWnTxvjsvL291apVK0n5L4+bt4Fy9uxZpae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\n",
      "text/plain": [
       "<Figure size 1080x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 계절별 각 장르의 영화 수\n",
    "plt.figure(figsize=(10,6))\n",
    "sns.catplot(data=movie, x='genres', col='four_month', kind='count', \n",
    "            col_wrap=3, palette='Spectral', legend=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. 년도별 각 장르의 영화 개봉 수\n",
    "### - 계절별로 확인했을 때는 매년 드라마가 가장 많지만 2020년에는 드라마와 코미디 개봉 수(10)가 같았다. 코로나로 힘들 때 코미디 영화로 위로를 얻을 수 있을 것이다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "scrolled": true
   },
   "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>Code</th>\n",
       "      <th>Movie</th>\n",
       "      <th>Audience</th>\n",
       "      <th>Screen</th>\n",
       "      <th>genres</th>\n",
       "      <th>AgeRate</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>four_month</th>\n",
       "      <th>year_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20192193</td>\n",
       "      <td>도굴</td>\n",
       "      <td>565.469</td>\n",
       "      <td>1634</td>\n",
       "      <td>범죄</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>11</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20197121</td>\n",
       "      <td>삼진그룹 영어토익반</td>\n",
       "      <td>1257.444</td>\n",
       "      <td>1080</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20199816</td>\n",
       "      <td>담보</td>\n",
       "      <td>1702.252</td>\n",
       "      <td>407</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>9</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20208508</td>\n",
       "      <td>미스터트롯: 더 무비</td>\n",
       "      <td>140.594</td>\n",
       "      <td>159</td>\n",
       "      <td>공연</td>\n",
       "      <td>전체관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20194424</td>\n",
       "      <td>소리도 없이</td>\n",
       "      <td>401.759</td>\n",
       "      <td>126</td>\n",
       "      <td>범죄</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411</th>\n",
       "      <td>20145501</td>\n",
       "      <td>돌연변이</td>\n",
       "      <td>100.498</td>\n",
       "      <td>7</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>412</th>\n",
       "      <td>20157465</td>\n",
       "      <td>그놈이다</td>\n",
       "      <td>1045.218</td>\n",
       "      <td>35</td>\n",
       "      <td>스릴러</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>20157464</td>\n",
       "      <td>더 폰</td>\n",
       "      <td>1593.592</td>\n",
       "      <td>7</td>\n",
       "      <td>스릴러</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>20142855</td>\n",
       "      <td>성난 변호사</td>\n",
       "      <td>1127.747</td>\n",
       "      <td>21</td>\n",
       "      <td>범죄</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>20149961</td>\n",
       "      <td>미안해 사랑해 고마워</td>\n",
       "      <td>50.571</td>\n",
       "      <td>5</td>\n",
       "      <td>드라마</td>\n",
       "      <td>청소년관람가</td>\n",
       "      <td>10</td>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>357 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Code        Movie  Audience  Screen genres AgeRate  month  year  \\\n",
       "0    20192193           도굴   565.469    1634     범죄  청소년관람가     11  2020   \n",
       "1    20197121   삼진그룹 영어토익반  1257.444    1080    드라마  청소년관람가     10  2020   \n",
       "2    20199816           담보  1702.252     407    드라마  청소년관람가      9  2020   \n",
       "3    20208508  미스터트롯: 더 무비   140.594     159     공연   전체관람가     10  2020   \n",
       "4    20194424       소리도 없이   401.759     126     범죄  청소년관람가     10  2020   \n",
       "..        ...          ...       ...     ...    ...     ...    ...   ...   \n",
       "411  20145501         돌연변이   100.498       7    드라마  청소년관람가     10  2015   \n",
       "412  20157465         그놈이다  1045.218      35    스릴러  청소년관람가     10  2015   \n",
       "413  20157464          더 폰  1593.592       7    스릴러  청소년관람가     10  2015   \n",
       "414  20142855       성난 변호사  1127.747      21     범죄  청소년관람가     10  2015   \n",
       "415  20149961  미안해 사랑해 고마워    50.571       5    드라마  청소년관람가     10  2015   \n",
       "\n",
       "     four_month  year_cat  \n",
       "0             4        35  \n",
       "1             4        35  \n",
       "2             4        35  \n",
       "3             4        35  \n",
       "4             4        35  \n",
       "..          ...       ...  \n",
       "411           4        30  \n",
       "412           4        30  \n",
       "413           4        30  \n",
       "414           4        30  \n",
       "415           4        30  \n",
       "\n",
       "[357 rows x 10 columns]"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "scrolled": false
   },
   "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></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>genres</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2015</th>\n",
       "      <th>공연</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>드라마</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>멜로/로맨스</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>미스터리</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>범죄</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2020</th>\n",
       "      <th>스릴러</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>애니메이션</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>액션</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>코미디</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>판타지</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>84 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              0\n",
       "year genres    \n",
       "2015 공연       2\n",
       "     드라마      5\n",
       "     멜로/로맨스   1\n",
       "     미스터리     2\n",
       "     범죄       4\n",
       "...          ..\n",
       "2020 스릴러      2\n",
       "     애니메이션    4\n",
       "     액션       6\n",
       "     코미디     10\n",
       "     판타지      1\n",
       "\n",
       "[84 rows x 1 columns]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 년도별 각 장르 개봉 수\n",
    "movie.groupby(['year', 'genres']).size().to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "genres\n",
       "공연         6\n",
       "공포(호러)     1\n",
       "다큐멘터리      3\n",
       "드라마       10\n",
       "뮤지컬        1\n",
       "미스터리       3\n",
       "범죄         4\n",
       "사극         1\n",
       "스릴러        2\n",
       "애니메이션      4\n",
       "액션         6\n",
       "코미디       10\n",
       "판타지        1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 2020년 장르별 영화 개봉 수\n",
    "movie[movie['year'] == 2020].groupby('genres').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 48276 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 51396 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 46300 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 46972 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 47560 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 44277 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 50672 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 50529 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 49496 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 50528 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 45768 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 47700 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 51060 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 53076 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 48120 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 46356 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 45796 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 53328 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 47704 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 53552 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 47532 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 49828 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 47540 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 47084 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 48036 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 51648 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 52972 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 54252 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 54840 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 49324 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 44537 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 44592 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 53440 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 50612 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 48292 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 52376 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 54032 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 51204 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 51137 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 47708 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 47196 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 47592 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 44032 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:238: RuntimeWarning: Glyph 51313 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 48276 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 51396 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 46300 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 46972 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 47560 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 44277 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 50672 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 50529 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 49496 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 50528 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 45768 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 47700 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 51060 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 53076 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 48120 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 46356 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 45796 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 53328 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 47704 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 53552 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 47532 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 49828 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 47540 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 47084 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 48036 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 51648 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 52972 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 54252 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 54840 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 49324 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 44537 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 44592 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 53440 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 50612 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 48292 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 52376 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 54032 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 51204 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 51137 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 47708 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 47196 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 47592 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 44032 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "c:\\users\\luvu1\\anaconda3\\envs\\dss15\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py:201: RuntimeWarning: Glyph 51313 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 년도별 각 장르의 개봉 수 그래프\n",
    "sns.set_style('whitegrid')\n",
    "plt.figure(figsize=(10,6))\n",
    "sns.catplot(data=movie, x='genres', col='year', kind='count', \n",
    "            col_wrap=3, palette='Spectral');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "movie.to_csv('./datas/movie2015~2020.csv', sep=',', encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 데이터 시각화 다시 하기\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}