EDA&시각화_과제.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "x0yoa3uTfcoz"
   },
   "source": [
    "# EDA 과제 \n",
    "#### <font color='orange'> - 약간 매운맛"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PfuUHX59fco0"
   },
   "source": [
    "by YBIGTA 16기 DA Team 김지환"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vfK2PJbOfco1"
   },
   "source": [
    "<img src='https://i.imgur.com/cqdVyfs.jpg'>\n",
    "\n",
    "\n",
    "---\n",
    "여러분은 Airbnb 런던 지사의 데이터 분석가입니다.\n",
    "\n",
    "이번에 호스트들에게 적정한 방 가격을 책정해주는 프로젝트를 진행할 예정입니다.\n",
    "\n",
    "이를 위해 기존에 런던에 있던 Airbnb 방 데이터를 분석할 것입니다.\n",
    "\n",
    "각 문제에 대해 적절한 코드 혹은 답변을 제시해보세요.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "tROG2Acf2eKM"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "# notebook을 실행한 브라우저에서 바로 그림을 볼 수 있게 해주는 코드. 버전에 따라 필요 없을 수도 있습니다.\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "Ay_oqYuW2eKP",
    "outputId": "e5424046-5395-4f0b-9443-21e9df6cba76"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3165: DtypeWarning: Columns (25,26,47) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  has_raised = await self.run_ast_nodes(code_ast.body, cell_name,\n"
     ]
    }
   ],
   "source": [
    "df = pd.read_csv('airbnb_listings.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PJLnjOfZfco8"
   },
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "W4Bydfl-fco9"
   },
   "source": [
    "### 1) 전체 데이터 확인"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "E3dSDYVGfco9"
   },
   "source": [
    "- #### <font color='orange'> Q1. 상위 5개의 데이터를 확인해보세요. 컬럼 수가 많으니 모든 컬럼을 표시하도록 조정하세요. </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "13sbz1b62eKT",
    "outputId": "8e3685b1-906b-43e8-cff5-7bcc3ada783f"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>host_response_time</th>\n",
       "      <th>host_response_rate</th>\n",
       "      <th>host_acceptance_rate</th>\n",
       "      <th>host_is_superhost</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <th>host_verifications</th>\n",
       "      <th>host_has_profile_pic</th>\n",
       "      <th>host_identity_verified</th>\n",
       "      <th>...</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>requires_license</th>\n",
       "      <th>license</th>\n",
       "      <th>jurisdiction_names</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>is_business_travel_ready</th>\n",
       "      <th>cancellation_policy</th>\n",
       "      <th>require_guest_profile_picture</th>\n",
       "      <th>require_guest_phone_verification</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2060</td>\n",
       "      <td>a few days or more</td>\n",
       "      <td>22%</td>\n",
       "      <td>50%</td>\n",
       "      <td>f</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>['reviews']</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>flexible</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2595</td>\n",
       "      <td>within a day</td>\n",
       "      <td>87%</td>\n",
       "      <td>38%</td>\n",
       "      <td>f</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>['email', 'phone', 'reviews', 'offline_governm...</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>strict_14_with_grace_period</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>0.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3831</td>\n",
       "      <td>within an hour</td>\n",
       "      <td>83%</td>\n",
       "      <td>96%</td>\n",
       "      <td>f</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>['email', 'phone', 'reviews', 'kba']</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>moderate</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>4.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5099</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>71%</td>\n",
       "      <td>f</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>['email', 'phone', 'reviews', 'jumio', 'govern...</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>moderate</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>0.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5114</td>\n",
       "      <td>within a day</td>\n",
       "      <td>50%</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>['email', 'phone', 'reviews']</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>strict_14_with_grace_period</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 54 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     id  host_response_time host_response_rate host_acceptance_rate  \\\n",
       "0  2060  a few days or more                22%                  50%   \n",
       "1  2595        within a day                87%                  38%   \n",
       "2  3831      within an hour                83%                  96%   \n",
       "3  5099                 NaN                NaN                  71%   \n",
       "4  5114        within a day                50%                  NaN   \n",
       "\n",
       "  host_is_superhost  host_listings_count  host_total_listings_count  \\\n",
       "0                 f                  0.0                        0.0   \n",
       "1                 f                  6.0                        6.0   \n",
       "2                 f                  1.0                        1.0   \n",
       "3                 f                  1.0                        1.0   \n",
       "4                 f                  3.0                        3.0   \n",
       "\n",
       "                                  host_verifications host_has_profile_pic  \\\n",
       "0                                        ['reviews']                    t   \n",
       "1  ['email', 'phone', 'reviews', 'offline_governm...                    t   \n",
       "2               ['email', 'phone', 'reviews', 'kba']                    t   \n",
       "3  ['email', 'phone', 'reviews', 'jumio', 'govern...                    t   \n",
       "4                      ['email', 'phone', 'reviews']                    t   \n",
       "\n",
       "  host_identity_verified  ... review_scores_value  requires_license  license  \\\n",
       "0                      f  ...                 NaN                 f      NaN   \n",
       "1                      t  ...                 9.0                 f      NaN   \n",
       "2                      t  ...                 8.0                 f      NaN   \n",
       "3                      f  ...                 9.0                 f      NaN   \n",
       "4                      f  ...                10.0                 f      NaN   \n",
       "\n",
       "  jurisdiction_names instant_bookable is_business_travel_ready  \\\n",
       "0                NaN                f                        f   \n",
       "1                NaN                f                        f   \n",
       "2                NaN                f                        f   \n",
       "3                NaN                f                        f   \n",
       "4                NaN                f                        f   \n",
       "\n",
       "           cancellation_policy  require_guest_profile_picture  \\\n",
       "0                     flexible                              f   \n",
       "1  strict_14_with_grace_period                              t   \n",
       "2                     moderate                              f   \n",
       "3                     moderate                              t   \n",
       "4  strict_14_with_grace_period                              f   \n",
       "\n",
       "   require_guest_phone_verification  reviews_per_month  \n",
       "0                                 f               0.01  \n",
       "1                                 t               0.38  \n",
       "2                                 f               4.71  \n",
       "3                                 t               0.59  \n",
       "4                                 f               0.56  \n",
       "\n",
       "[5 rows x 54 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q1\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bs39AwwafcpA"
   },
   "source": [
    "---\n",
    "### 2) 결측치 확인"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9-IpP0m4fcpA"
   },
   "source": [
    "- #### <font color='orange'> Q2. 각 컬럼의 결측치를 확인하고, 결측치가 많은 순서대로 결측치 비율과 함께 표로 나타내보세요.\n",
    "<font color='orange'> (결측치 0개인 컬럼은 나타내지 마세요)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "GN2gxJDifcpB",
    "outputId": "941793c4-8218-4fab-cb95-3ca6247e292f"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        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>missing_num</th>\n",
       "      <th>missing_%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>jurisdiction_names</th>\n",
       "      <td>50781</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>license</th>\n",
       "      <td>50759</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>square_feet</th>\n",
       "      <td>50407</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>monthly_price</th>\n",
       "      <td>46119</td>\n",
       "      <td>91.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weekly_price</th>\n",
       "      <td>45411</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_response_time</th>\n",
       "      <td>19006</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_response_rate</th>\n",
       "      <td>19006</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>security_deposit</th>\n",
       "      <td>17325</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>host_acceptance_rate</th>\n",
       "      <td>14015</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_location</th>\n",
       "      <td>11482</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_value</th>\n",
       "      <td>11482</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_checkin</th>\n",
       "      <td>11479</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_accuracy</th>\n",
       "      <td>11466</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_communication</th>\n",
       "      <td>11463</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_cleanliness</th>\n",
       "      <td>11452</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_scores_rating</th>\n",
       "      <td>11431</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reviews_per_month</th>\n",
       "      <td>10453</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beds</th>\n",
       "      <td>482</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             missing_num  missing_%\n",
       "jurisdiction_names                 50781      100.0\n",
       "license                            50759      100.0\n",
       "square_feet                        50407       99.0\n",
       "monthly_price                      46119       91.0\n",
       "weekly_price                       45411       89.0\n",
       "host_response_time                 19006       37.0\n",
       "host_response_rate                 19006       37.0\n",
       "security_deposit                   17325       34.0\n",
       "host_acceptance_rate               14015       28.0\n",
       "review_scores_location             11482       23.0\n",
       "review_scores_value                11482       23.0\n",
       "review_scores_checkin              11479       23.0\n",
       "review_scores_accuracy             11466       23.0\n",
       "review_scores_communication        11463       23.0\n",
       "review_scores_cleanliness          11452       23.0\n",
       "review_scores_rating               11431       23.0\n",
       "reviews_per_month                  10453       21.0\n",
       "beds                                 482        1.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q2\n",
    "data = pd.DataFrame()\n",
    "data['missing_num'] = df.isnull().sum()\n",
    "data['missing_%'] = (df.isnull().sum() / len(df) *100).round(0)\n",
    "\n",
    "data[data['missing_%']!=0].sort_values('missing_num', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "87TiQRKbfcpE"
   },
   "source": [
    "- #### <font color='orange'> Q3. 결측치가 있는 컬럼과 결측치 비율을 보기쉽게 그래프로 나타내 보세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "id": "1PVB7F3yfcpE",
    "outputId": "dcd3c658-2ddd-43bf-871f-629b886141bd"
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q3\n",
    "cata = data[data['missing_%']!=0].sort_values('missing_num', ascending=False)\n",
    "plt.figure(figsize = (15,4))\n",
    "\n",
    "iv = cata.index.values\n",
    "colors = sns.color_palette(\"husl\", len(iv))\n",
    "\n",
    "plt.xticks(np.arange(len(iv)),iv)\n",
    "plt.xticks(rotation = 45)\n",
    "plt.xlim(-0.5, 17.5)\n",
    "plt.bar(np.arange(len(iv)),cata['missing_%'],color = colors)\n",
    "\n",
    "plt.ylabel('missing_%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "D8Xr7__1fcpI"
   },
   "source": [
    "- #### <font color='orange'> Q4. 결측치가 적은 beds 컬럼을 좀 더 자세히 살펴보겠습니다. \n",
    "  #### <font color='orange'> 'beds' 컬럼이 결측치인 데이터의 상위 5개를 출력해주세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "52-Do2c_fcpJ",
    "outputId": "12ded756-c69a-4291-ad52-04318a2bd826"
   },
   "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>id</th>\n",
       "      <th>host_response_time</th>\n",
       "      <th>host_response_rate</th>\n",
       "      <th>host_acceptance_rate</th>\n",
       "      <th>host_is_superhost</th>\n",
       "      <th>host_listings_count</th>\n",
       "      <th>host_total_listings_count</th>\n",
       "      <th>host_verifications</th>\n",
       "      <th>host_has_profile_pic</th>\n",
       "      <th>host_identity_verified</th>\n",
       "      <th>...</th>\n",
       "      <th>review_scores_value</th>\n",
       "      <th>requires_license</th>\n",
       "      <th>license</th>\n",
       "      <th>jurisdiction_names</th>\n",
       "      <th>instant_bookable</th>\n",
       "      <th>is_business_travel_ready</th>\n",
       "      <th>cancellation_policy</th>\n",
       "      <th>require_guest_profile_picture</th>\n",
       "      <th>require_guest_phone_verification</th>\n",
       "      <th>reviews_per_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>808</th>\n",
       "      <td>321845</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>['email']</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>strict_14_with_grace_period</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1002</th>\n",
       "      <td>468613</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>['email', 'phone', 'facebook', 'reviews', 'kba']</td>\n",
       "      <td>t</td>\n",
       "      <td>t</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>flexible</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1058</th>\n",
       "      <td>499249</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0%</td>\n",
       "      <td>f</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>['email', 'phone', 'reviews', 'offline_governm...</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>strict_14_with_grace_period</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1074</th>\n",
       "      <td>505231</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>['email', 'phone', 'reviews']</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>moderate</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1208</th>\n",
       "      <td>587519</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0%</td>\n",
       "      <td>f</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>['email', 'phone', 'facebook', 'reviews']</td>\n",
       "      <td>t</td>\n",
       "      <td>f</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>flexible</td>\n",
       "      <td>f</td>\n",
       "      <td>f</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 54 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id host_response_time host_response_rate host_acceptance_rate  \\\n",
       "808   321845                NaN                NaN                  NaN   \n",
       "1002  468613                NaN                NaN                  NaN   \n",
       "1058  499249                NaN                NaN                   0%   \n",
       "1074  505231                NaN                NaN                  NaN   \n",
       "1208  587519                NaN                NaN                   0%   \n",
       "\n",
       "     host_is_superhost  host_listings_count  host_total_listings_count  \\\n",
       "808                  f                  0.0                        0.0   \n",
       "1002                 f                  1.0                        1.0   \n",
       "1058                 f                  1.0                        1.0   \n",
       "1074                 f                  1.0                        1.0   \n",
       "1208                 f                  1.0                        1.0   \n",
       "\n",
       "                                     host_verifications host_has_profile_pic  \\\n",
       "808                                           ['email']                    t   \n",
       "1002   ['email', 'phone', 'facebook', 'reviews', 'kba']                    t   \n",
       "1058  ['email', 'phone', 'reviews', 'offline_governm...                    t   \n",
       "1074                      ['email', 'phone', 'reviews']                    t   \n",
       "1208          ['email', 'phone', 'facebook', 'reviews']                    t   \n",
       "\n",
       "     host_identity_verified  ... review_scores_value  requires_license  \\\n",
       "808                       f  ...                 NaN                 f   \n",
       "1002                      t  ...                 NaN                 f   \n",
       "1058                      f  ...                10.0                 f   \n",
       "1074                      f  ...                10.0                 f   \n",
       "1208                      f  ...                 6.0                 f   \n",
       "\n",
       "      license jurisdiction_names instant_bookable is_business_travel_ready  \\\n",
       "808       NaN                NaN                f                        f   \n",
       "1002      NaN                NaN                f                        f   \n",
       "1058      NaN                NaN                t                        f   \n",
       "1074      NaN                NaN                f                        f   \n",
       "1208      NaN                NaN                f                        f   \n",
       "\n",
       "              cancellation_policy  require_guest_profile_picture  \\\n",
       "808   strict_14_with_grace_period                              f   \n",
       "1002                     flexible                              f   \n",
       "1058  strict_14_with_grace_period                              f   \n",
       "1074                     moderate                              f   \n",
       "1208                     flexible                              f   \n",
       "\n",
       "      require_guest_phone_verification  reviews_per_month  \n",
       "808                                  f                NaN  \n",
       "1002                                 f                NaN  \n",
       "1058                                 f               0.01  \n",
       "1074                                 f               0.01  \n",
       "1208                                 f               0.02  \n",
       "\n",
       "[5 rows x 54 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q4\n",
    "df[df['beds'].isnull()].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "aG4VKbWVfcpM"
   },
   "source": [
    "---\n",
    "### 3) 범주형 변수 확인\n",
    "<font color='gray'> - 편의를 위해 결측치가 있는 컬럼을 모두 제거하고 진행하겠습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "82BUbKO1fcpM"
   },
   "outputs": [],
   "source": [
    "drop_col = ['jurisdiction_names', 'license', 'square_feet', 'monthly_price',\n",
    "       'weekly_price', 'host_response_rate', 'host_response_time',\n",
    "       'security_deposit', 'host_acceptance_rate', 'review_scores_location',\n",
    "       'review_scores_value', 'review_scores_checkin',\n",
    "       'review_scores_accuracy', 'review_scores_communication',\n",
    "       'review_scores_cleanliness', 'review_scores_rating',\n",
    "       'reviews_per_month', 'beds']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "pgWTlyZ0fcpO"
   },
   "outputs": [],
   "source": [
    "df = df.drop(columns=drop_col)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9uEFs_yxfcpR"
   },
   "source": [
    "- #### 각 컬럼별 변수 타입 확인"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "C52vx5OEfcpR",
    "outputId": "c066d361-312e-4c28-d1d2-f87e244fc111"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 50796 entries, 0 to 50795\n",
      "Data columns (total 54 columns):\n",
      " #   Column                            Non-Null Count  Dtype  \n",
      "---  ------                            --------------  -----  \n",
      " 0   id                                50796 non-null  int64  \n",
      " 1   host_response_time                31790 non-null  object \n",
      " 2   host_response_rate                31790 non-null  object \n",
      " 3   host_acceptance_rate              36781 non-null  object \n",
      " 4   host_is_superhost                 50791 non-null  object \n",
      " 5   host_listings_count               50791 non-null  float64\n",
      " 6   host_total_listings_count         50791 non-null  float64\n",
      " 7   host_verifications                50796 non-null  object \n",
      " 8   host_has_profile_pic              50791 non-null  object \n",
      " 9   host_identity_verified            50791 non-null  object \n",
      " 10  neighborhood                      50796 non-null  object \n",
      " 11  latitude                          50796 non-null  float64\n",
      " 12  longitude                         50796 non-null  float64\n",
      " 13  is_location_exact                 50796 non-null  object \n",
      " 14  property_type                     50796 non-null  object \n",
      " 15  room_type                         50796 non-null  object \n",
      " 16  accommodates                      50796 non-null  int64  \n",
      " 17  bathrooms                         50742 non-null  float64\n",
      " 18  bedrooms                          50719 non-null  float64\n",
      " 19  beds                              50314 non-null  float64\n",
      " 20  bed_type                          50796 non-null  object \n",
      " 21  amenities                         50796 non-null  object \n",
      " 22  square_feet                       389 non-null    float64\n",
      " 23  price                             50796 non-null  int64  \n",
      " 24  weekly_price                      5385 non-null   object \n",
      " 25  monthly_price                     4677 non-null   object \n",
      " 26  security_deposit                  33471 non-null  object \n",
      " 27  guests_included                   50796 non-null  int64  \n",
      " 28  extra_people                      50796 non-null  object \n",
      " 29  minimum_nights                    50796 non-null  int64  \n",
      " 30  maximum_nights                    50796 non-null  int64  \n",
      " 31  has_availability                  50796 non-null  object \n",
      " 32  availability_30                   50796 non-null  int64  \n",
      " 33  availability_60                   50796 non-null  int64  \n",
      " 34  availability_90                   50796 non-null  int64  \n",
      " 35  availability_365                  50796 non-null  int64  \n",
      " 36  number_of_reviews                 50796 non-null  int64  \n",
      " 37  number_of_reviews_ltm             50796 non-null  int64  \n",
      " 38  review_scores_rating              39365 non-null  float64\n",
      " 39  review_scores_accuracy            39330 non-null  float64\n",
      " 40  review_scores_cleanliness         39344 non-null  float64\n",
      " 41  review_scores_checkin             39317 non-null  float64\n",
      " 42  review_scores_communication       39333 non-null  float64\n",
      " 43  review_scores_location            39314 non-null  float64\n",
      " 44  review_scores_value               39314 non-null  float64\n",
      " 45  requires_license                  50796 non-null  object \n",
      " 46  license                           37 non-null     object \n",
      " 47  jurisdiction_names                15 non-null     object \n",
      " 48  instant_bookable                  50796 non-null  object \n",
      " 49  is_business_travel_ready          50796 non-null  object \n",
      " 50  cancellation_policy               50796 non-null  object \n",
      " 51  require_guest_profile_picture     50796 non-null  object \n",
      " 52  require_guest_phone_verification  50796 non-null  object \n",
      " 53  reviews_per_month                 40343 non-null  float64\n",
      "dtypes: float64(16), int64(12), object(26)\n",
      "memory usage: 21.3+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wmmKNpDffcpT"
   },
   "source": [
    "- #### <font color='orange'> Q5. Room Type 에는 어떤 것들이 있는지 살펴보겠습니다. \n",
    "#### <font color='orange'> room_type의 종류별 갯수에 대한 그래프를 그려주세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "id": "L5NgpaZAfcpU",
    "outputId": "e6f75eb5-74cb-45c6-95fc-20942c14a401"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='room_type', ylabel='count'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q5\n",
    "sns.countplot(data = df, x = 'room_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>room_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Entire home/apt</th>\n",
       "      <td>0.517245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Private room</th>\n",
       "      <td>0.450724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shared room</th>\n",
       "      <td>0.024116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hotel room</th>\n",
       "      <td>0.007914</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 room_type\n",
       "Entire home/apt   0.517245\n",
       "Private room      0.450724\n",
       "Shared room       0.024116\n",
       "Hotel room        0.007914"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratio = df['room_type'].value_counts(normalize=True)\n",
    "ratio = pd.DataFrame(ratio)\n",
    "ratio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tDraukBJfcpW"
   },
   "source": [
    "- #### <font color='orange'> Q6. 위 그래프의 세로축이 갯수가 아닌 비율을 나타내도록 재구성해보세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "id": "0Sw6cCs0fcpW",
    "outputId": "89c9d5d7-c37e-49ff-a859-843816209bf3"
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAD4CAYAAADhNOGaAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAV00lEQVR4nO3dfbAldX3n8feHARQxwhqmjPLgjGaUYFSSDCgGFFMxguuCKApKVPKwZMyiWVPGkHLLaEwZiZUnCwhLGQo3iWJYBUYdHZ8ATZAwA+FBQNwJPjCSxBEfyPgADnz3j/5dOFzOvffMvdP3MtPvV9Wt093n193f06fP+fTT6ZuqQpI0XLstdQGSpKVlEEjSwBkEkjRwBoEkDZxBIEkDt/tSFzAf++23X61YsWKpy5CkncY111zzrapaPu65nTIIVqxYwcaNG5e6DEnaaST52kzPeWhIkgbOIJCkgTMIJGngDAJJGjiDQJIGziCQpIEzCCRp4AwCSRo4g0CSBm6n/GXxQqw442NLXcKS+uq7/utSlyDpYcY9AkkaOINAkgau1yBIckySW5NsSnLGmOePTvK9JNe1v7f2WY8k6aF6O0eQZBlwNvACYDOwIcnaqrp5WtPPV9WL+6pDkjS7PvcIDgc2VdVtVXUPcCFwfI/zkyTNQ59BsD9w+0j/5jZsuiOSXJ/k40me1mM9kqQx+rx8NGOG1bT+a4EnVtXWJC8CLgFWjZ1YchpwGsBBBx20A8uUpGHrc49gM3DgSP8BwB2jDarqrqra2rrXAXsk2W/cxKrqvKpaXVWrly8f+9/WJEnz0GcQbABWJVmZZE/gZGDtaIMkP5UkrfvwVs+dPdYkSZqmt0NDVbUtyenAemAZcH5V3ZRkTXv+XOBE4HVJtgE/BE6uqumHjyRJPer1FhPtcM+6acPOHek+CzirzxokSbPzl8WSNHAGgSQNnEEgSQNnEEjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLAGQSSNHAGgSQNXK+3odYu6G37LHUFS+tt31vqCqQdzj0CSRo4g0CSBs4gkKSBMwgkaeAMAkkaOINAkgbOIJCkgTMIJGngDAJJGjiDQJIGziCQpIEzCCRp4AwCSRo4g0CSBs4gkKSBMwgkaeB6DYIkxyS5NcmmJGfM0u6wJPcmObHPeiRJD9VbECRZBpwNHAscArwyySEztDsTWN9XLZKkmfW5R3A4sKmqbquqe4ALgePHtHs98CHgmz3WIkmaQZ9BsD9w+0j/5jbsfkn2B04Azu2xDknSLPoMgowZVtP6/xL4/aq6d86JJacl2Zhk45YtW3ZEfZIkYPcep70ZOHCk/wDgjmltVgMXJgHYD3hRkm1Vdcn0iVXVecB5AKtXr54eKJKkeeozCDYAq5KsBL4BnAy8arRBVa2c6k5yAfDRcSEgSepPb0FQVduSnE53NdAy4PyquinJmva85wUk6WGgzz0CqmodsG7asLEBUFWn9lmLJGk8f1ksSQNnEEjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLATRwESfbusxBJ0tKYMwiSPCfJzcAtrf+ZSc7pvTJJ0qKYZI/gL4AXAncCVNX1wHP7LEqStHgmOjRUVbdPG3RvD7VIkpbA7hO0uT3Jc4BKsifwBtphIknSzm+SPYI1wP8A9ge+ARza+iVJu4A59wiq6lvAKYtQiyRpCUxy1dCTknwkyZYk30xyaZInLUZxkqT+TXJo6P3APwCPB54AXAR8oM+iJEmLZ5IgSFX9bVVta39/B1TfhUmSFsckQXBZkjOSrEjyxCRvBj6W5LFJHjvbiEmOSXJrkk1Jzhjz/PFJbkhyXZKNSY6c7wuRJM3PJJePntQef2va8F+n2zMYe74gyTLgbOAFwGZgQ5K1VXXzSLPPAGurqpI8g+4Q1MHbUb8kaYEmuWpo5TynfTiwqapuA0hyIXA8cH8QVNXWkfZ74yEnSVp0k1w1tDHJbyfZdzunvT8w+ovkzW3Y9OmfkORLwMfo9jJmquO0VsvGLVu2bGcpkqSZTHKO4GS6L/CNSS5M8sIkmWC8cW0essVfVRdX1cHAS4B3zDSxqjqvqlZX1erly5dPMHtJ0iTmDIKq2lRVbwGeQncp6fnA15O8fY6TxZuBA0f6DwDumGU+nwOenGS/iSqXJO0QE910rp3I/TPg3cCHgBOBu4DPzjLaBmBVkpXtHkUnA2unTfenp/Yukvw8sCftLqeSpMUx58niJNcA3wX+Bjijqu5uT/1zkl+cabyq2pbkdGA9sAw4v6puSrKmPX8u8DLgNUl+DPwQOKmqPGEsSYtokstHXz515c+UJCur6itV9dLZRqyqdcC6acPOHek+EzhzO+qVJO1gkxwa+r8TDpMk7YRm3CNIcjDwNGCfJKNb/o8BHtl3YZKkxTHboaGnAi8G9gX+28jw/wT+e481SZIW0YxBUFWXApcmOaKqvjBTuyR/UFV/0kt1kqTeTfI7ghlDoHn5DqpFkrQEJvodwRwm+ZWxJOlhakcEgdf9S9JOzD0CSRq4HREEF+2AaUiSlsgkt5hYCbweWDHavqqOa4/v7Ks4SVL/JrnFxCV09xn6CHBfr9VIkhbdJEHwo6p6T++VSJKWxCRB8FdJ/hD4JDB151Gq6treqpIkLZpJguDpwKuBX+KBQ0PV+iVJO7lJguAE4ElVdU/fxUiSFt8kl49eT3fjOUnSLmiSPYLHAV9KsoEHnyM4rreqJEmLZpIg+MPeq5AkLZk5g6CqrkjyOOCwNujqqvpmv2VJkhbLnOcIkrwCuJrudtOvoPun9Sf2XZgkaXFMcmjoLcBhU3sBSZYDn8b/WyxJu4RJrhrabdqhoDsnHE+StBOYZI/gE0nWAx9o/ScB6/orSZK0mCY5Wfx7SV4KHEn3vwfOq6qLe69MkrQoJtkjAPgn4Md0t5a4ur9yJEmLbXuuGjoRrxqSpF2OVw1J0sB51ZAkDdysewRJAmzwqiFJ2nXNGgRVVUkOBf4YrxqSpF3SJOcIvgDcXlW/23cxkqTFN8mx/ucDX0jyr0lumPqbZOJJjklya5JNSc4Y8/wpI9O8Mskzt/cFSJIWZpI9gmPnM+Eky4CzgRcAm+nONaytqptHmn0FeF5VfSfJscB5wLPmMz9J0vxM8svir81z2ocDm6rqNoAkFwLHA/cHQVVdOdL+KuCAec5LkjRPfV4Guj9w+0j/5jZsJr8BfHymJ5OclmRjko1btmzZQSVKkvoMgowZVmMbJs+nC4Lfn2liVXVeVa2uqtXLly/fQSVKkia919B8bAYOHOk/ALhjeqMkzwDeCxxbVXf2WI8kaYw+9wg2AKuSrEyyJ3AysHa0QZKDgA8Dr66qL/dYiyRpBr3tEVTVtiSnA+uBZcD5VXVTkjXt+XOBtwI/CZzT/YiZbVW1uq+aJEkP1eehIapqHdNuR9ECYKr7N4Hf7LMGSdLsvHmcJA2cQSBJA2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwPUaBEmOSXJrkk1Jzhjz/MFJvpDk7iRv6rMWSdJ4u/c14STLgLOBFwCbgQ1J1lbVzSPNvg28AXhJX3VIkmbX5x7B4cCmqrqtqu4BLgSOH21QVd+sqg3Aj3usQ5I0iz6DYH/g9pH+zW3YvCQ5LcnGJBu3bNmy4OIkSZ0+gyBjhtV8J1ZV51XV6qpavXz58gWUJUka1WcQbAYOHOk/ALijx/lJkuahzyDYAKxKsjLJnsDJwNoe5ydJmoferhqqqm1JTgfWA8uA86vqpiRr2vPnJvkpYCPwGOC+JP8TOKSq7uqrLknSg/UWBABVtQ5YN23YuSPd/053yEiStET8ZbEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cAaBJA2cQSBJA2cQSNLAGQSSNHAGgSQNnEEgSQNnEEjSwBkEkjRwuy91AdKQPP19T1/qEpbUja+9calL0BjuEUjSwBkEkjRwBoEkDZxBIEkDZxBI0sAZBJI0cL1ePprkGOCvgGXAe6vqXdOeT3v+RcAPgFOr6to+a5K087rl4J9Z6hKW1M986ZZeptvbHkGSZcDZwLHAIcArkxwyrdmxwKr2dxrw133VI0kar89DQ4cDm6rqtqq6B7gQOH5am+OB/1Odq4B9kzy+x5okSdP0eWhof+D2kf7NwLMmaLM/8G/TJ5bkNLq9BoCtSW7dcaUuqv2Aby3VzHPmUs15h1nS5cfbs2Sz3kGWdv071eW3IFnQ8nviTE/0GQTjKq55tOkGVp0HnLfQopZako1VtXqp69hZufwWxuW3MLvq8uvz0NBm4MCR/gOAO+bRRpLUoz6DYAOwKsnKJHsCJwNrp7VZC7wmnWcD36uqhxwWkiT1p7dDQ1W1LcnpwHq6y0fPr6qbkqxpz58LrKO7dHQT3eWjv9ZXPQ8jO/3hrSXm8lsYl9/C7JLLL1VjD8lLkgbCXxZL0sAZBJI0cLtkECS5N8l1I39nzNH+6CTPGelfk+Q1C5j/BUlOnO/485znHkmumee4pyZ5wna0n1q+X0xyUZJHzdDuynnWsyLJq+Yz7s4gyVuS3JTkhrYcn9WGfzXJfosw/8uT7FKXQCbZOq3/1CRnzTHOS8bc7WBcu7cledNCa3w421X/VeUPq+rQ7Wh/NLAVuBLuP5H9EEl2r6ptC66uH0fS6p+HU4EvMvmlu/cv3yR/D6wB/nzqySTLqureqnrODOPPZQXwKuD98xm53cMqVXXfPOffmyRHAC8Gfr6q7m5f/HvugOnu0HVz6j3cUdN7mHoJ8FHg5oVO6GH+3TCnXXKPYCZti+vtSa5NcmOSg5OsoPsie2PbOjtqdAugbT29M8kVwO8k+YUkVyS5Jsn6WW6J8dwkVya5bWrvoF0m++62JX1jkpPa8KPbNP8hyZeTvCvJKUmubu2e3NotT/KhJBva3y+OzO8Y4OOt3SWtvpvaL7KnXv/WJH/WXv9n2vROBFYDf99e/17buVg/D/x0ew2XJXk/cOPU/NrjB5O8aKSOC5K8rG35f77Vc+3IXtm7gKNaPW9Msqwttw1tK/q3phfRpnVLknOAa4EDZ1jWC3oPdoDHA9+qqrsBqupbVTUawK8fXT9bbYe3delf2uNT2/BT0+2RfQT4ZJK9k5zfltO/JDm+tdsryYVt2X0QGPset8/HW5P8I/DyJK9sdXwxeeA36bMM35rkzLbufbrVfXn7DBy3g5bfdkvyxLa+39AeD2rr2nHAu9t69uT294lW/+enlv8s070gyZ8nuQw4M8mhSa5q87k4yX9p7WYafnmSv0jyubbuHpbkw0n+X5I/7n3BjKqqXe4PuBe4buTvpDb8q8DrW/dv090RFeBtwJtGxr+/H7gcOKd170G31b289Z9Ed1ns9PlfAFxEF7SH0N1zCeBlwKfoLqd9HPB1ui+Go4Hvtu5HAN8A3t7G+R3gL1v3+4EjW/dBwC0j87waeFTrfmx73ItuS/8nW38Bp7TutwJnjbzG1duxfLe2x92BS4HXtdfwfWDlmHYnAO9r3XvS3VZkL+BRwCPb8FXAxtZ9NPDRkemcBvyv1v0IYOPofNrwFcB9wLPnWNYLeg92wLr5aLp18svAOcDzRp77KuPXz8cAu7fuXwY+1LpPpftR5tT7/U7gV1v3vm0eewO/S1tPgWcA28a9323+b27dT2jLZnl7nz9LtwU9dvjI+nVs674Y+CTdZ+aZwHWL/Jn/Og+s3x8BXtu6fx24ZORzeuLIND4DrGrdzwI+O+77Ydrn/KPAstZ/w9T7CfwRD3xuZxp+OXDmyDp2x8j6t5n2uV2MvyEeGvpwe7wGeOmE0/tge3wq8LPAp9Ld82MZY+6L1FxS3aGJm5M8rg07EvhAdbvc/5FuL+Mw4C5gQ7Uf0yX5V7oPEXRb189v3b8MHJIH7jfymCQ/AfwE8O2q+kEb/oYkJ7TuA+m+ZO+k+6Kcei1/N7IsttdeSa5r3Z8H/gZ4DnB1VX1lTPuPA+9J8gi6PZfPVdUPk+wDnJXkULoP8lNmmN+vAM/IA+dd9mmvafq8vlbdzQth5mW90PdgQapqa5JfAI5q0/xgkjOq6oLWZNz6uQ/wviSr6L5s9xiZ5Keq6tut+1eA4/LA8exH0m0wPBd4T5v/DUlumKXEqfXjMODyqtoC9x8CfG6b/7jhlwD3AJ9o498I3F1VP05yI11Q9+lBn/kkp9Lt6QIcwQPL8m+BP50+cpJH063DF418vh4xwXwvqqp727q8b1Vd0Ya/r01r7PCR8ad+ZHsjcNPI+ncb3Wf3zglqWLBdNQhmc3d7vJfJX//322Po3qwjtmM+U+ONPs7V/r6R/vt4oM7dgCOq6oejIyZ5Bd0P90hyNF1gHFFVP0hyOd0Xwjjz/RHJQ4K2fXi+P65xVf2o1fFCur2oD7Sn3gj8B90W427Aj2aYX+i2lNfPUdfo/Gda1gt9DxashdDlwOXtS/K1dFuXozWMrp/vAC6rqhPSHcq8fGRy01/zy6rqQTdkbO/NpO/16Lo+zmzL78fVNm8ZWX5VdV+Sh9N3zbhlsRvw3Vk2IGcydp3fDqPr2PT1b9GW2aDOEcziP+m2qudyK7A83Qm/qSt1nrYd8/kccFK6Y97L6bakrt6O8T8JnD7V07akYeT8AN3W43daCBwMPHtk/N2Aqa3qVwH/2Lonff0LcSHdL8ePooVWq/Xf2p7Tq+n2sMbVsx54XZI9AJI8Jcnec8xvpmW90PdgQZI8tW3ZTzkU+Noco+1Dd6gKusNBM1lPd44hbV4/14Z/DjilDftZusNDc/ln4HlJ9kv3v0VeCVwxy/CHsyvpbnED3XJ4yHpfVXcBX0nycrj/XNIzJ51BVX0P+E6So9qgVwNXzDR8IS+mD7tqEOyVB18++q452n8EOKG1PWqmRtX9X4UT6U4MXU93LHJ7roy5mO544fV0x1bfXFX/vh3jvwFY3U463QysaR/GVVX1pdbmE8Dubff/HcBVI+N/H3haustMf4nueCV0W6PnZn4niyf1Sbov3U+35QjdMfLXJrmK7rDQ1NbVDcC2JNcneSPwXrorO65N8kXgfzP31tJMy3qh78FCPZruMM/N7T06hO4Y9Gz+FPiTJP/EA2E5zjvoDhvd0JbTO9rwvwYe3eb3ZiYIvnaI4g+Ay+iW1bVVdelMw+ea3hJ7A/Br7fW/mu54PHQbJ7+X7sT6k+lC4jfaZ/smHvr/U+byWrqTzzfQBfwfzTH8YcNbTOzkkhxJd4JwzQRtt1bVoxehLEk7EYNgQAwCSeMYBJI0cLvqOQJJ0oQMAkkaOINAkgbOIJCkgTMIJGng/j9pxFjaeeJ4pgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q6\n",
    "plt.figure(figsize = (6,4))\n",
    "\n",
    "label = ratio.index.values\n",
    "colors = sns.color_palette()\n",
    "\n",
    "plt.xticks(np.arange(len(label)),label)\n",
    "\n",
    "plt.bar(np.arange(len(label)),ratio['room_type'],color=colors)\n",
    "plt.ylabel('room_type')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iN06xvJufcpZ"
   },
   "source": [
    "- #### <font color='orange'> Q7. 각 지역별로 room_type의 비율이 어땠는 지 알고 싶습니다.\n",
    "#### <font color='orange'> 아래 그래프와 같이 각 지역별로 room_type의 갯수가 어땠는지 보여주세요.    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "wAXnxXDVfcpa",
    "outputId": "3f3af483-07a8-4a6d-920a-08fe3be1e1a8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='neighborhood', ylabel='count'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q7\n",
    "plt.figure(figsize=(15,6))\n",
    "\n",
    "sns.countplot(x='neighborhood', hue = 'room_type', data = df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UA5MIpa0fcpg"
   },
   "source": [
    "- #### <font color='orange'> Q8. 각 지역별로 가격의 분포가 어떤지 알고 싶습니다.\n",
    "#### <font color='orange'> 아래 그래프와 같이 각 지역별로 가격의 분포를 보여주세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "id": "7tcvOOZmfcpg",
    "outputId": "a3f6f467-c4cb-4949-9ddb-80d1b7d44e4b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='neighborhood', ylabel='price'>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q8\n",
    "# plt.figure() 여기부턴 직접 사이즈 조절해보세요\n",
    "plt.figure(figsize=(15,6))\n",
    "sns.stripplot(x = 'neighborhood', y = 'price', data = df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xVaZ98NWfcpj"
   },
   "source": [
    "- #### <font color='orange'> Q9. 위 그래프들로부터 알 수 있는 사실은 무엇인가요? 그 이유는 무엇이라고 생각하시나요?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "CjWumnVOfcpj"
   },
   "outputs": [],
   "source": [
    "# Q9\n",
    "Staten Island와 Bronx의 가격은 다른 지역에 비해 싸다.\n",
    "Manhatton에 10000달러의 상품이 꽤 있는데 아마도 hotel room의 비율이 조금 있기 때문인 것 같다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "orxw6U8C2eK5"
   },
   "source": [
    "---\n",
    "### 4) 연속형 변수 확인"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fnmWOYOnfcpn"
   },
   "source": [
    "- #### <font color='orange'> Q10. 각 방의 수용가능인원의 분포를 알고싶습니다.\n",
    "#### <font color='orange'> 'accommodates' 칼럼에 대한 히스토그램을 그려주세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "id": "P4Ttc5iGfcpo",
    "outputId": "797bee99-86e1-4edf-f6c1-41f8f34cb0e5"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q10\n",
    "plt.figure(figsize=(15,6))\n",
    "plt.hist(df['accommodates'], bins = 20, color = 'pink')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Likx5P43fcpr"
   },
   "source": [
    "- #### <font color='orange'> Q11. 각 방의 가격의 분포를 알고 싶습니다.\n",
    "#### <font color='orange'> 'price' 칼럼에 대한 히스토그램을 그려주세요. 범위는 0~1000까지만 보여주세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "id": "PM4oic9Ffcpr",
    "outputId": "714ab71b-ceb7-44fd-d64d-d92bfb9eccf5"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q11\n",
    "plt.figure(figsize=(15,6))\n",
    "plt.hist(df['price'], bins = 100, range=(0,1000) ,color = 'pink')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ZXHTpb4bfcpt"
   },
   "source": [
    "---\n",
    "\n",
    "EDA는 언뜻보면 불필요해 보이는 과정이지만, 실제 데이터를 다룰때 매우매우 중요한 과정입니다.\n",
    "\n",
    "때문에 기본적인 개념 및 시각화 방법은 숙지해 두시는 것이 좋습니다!\n",
    "\n",
    "시각화한 자료를 바탕으로 실제 특성들을 가공하는 방법에 대해서는 \n",
    "\n",
    "<font color='orange'> 다음 시간인 FE 시간에 배우게 될 예정입니다.\n",
    "\n",
    "다음 시간에 봐요!\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PCG3bSBpfcpu"
   },
   "source": [
    "  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "86rqFGIXfcpu"
   },
   "source": [
    "  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LnK6vNAQfcpu"
   },
   "source": [
    "  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MNkTCRuzfcpv"
   },
   "source": [
    "      "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ws-3Vawbfcpv"
   },
   "source": [
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "QCliOYxPfcpw"
   },
   "source": [
    "* Q2 hint\n",
    "\n",
    "<font color='white'> df의 null의 개수를 센 다음에, \".to_frame()\" 을 써보세요. </font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bhGUNQPlfcpw"
   },
   "source": [
    "* Q3 hint\n",
    "\n",
    "<font color='white'> x축 라벨을 45도 기울이려면 plot.set_xticklabels()을 찾아보세요. </font>\n",
    "\n"
   ]
  },
  {
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