NewYork City Airbnb Price Prediction/2022_01_03_New York City Airbnb Price Regression.ipynb

{"nbformat":4,"nbformat_minor":0,"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":"3.7.7"},"colab":{"name":"2022_01_03_New York City Airbnb Price Regression.ipynb","provenance":[],"collapsed_sections":[]}},"cells":[{"cell_type":"markdown","metadata":{"id":"NqqLNJZjfi8U"},"source":["## 데이터\n","    - New York City Airbnb Open Data을 이용해 가격 예측\n","    \n","    - 컬럼\n","    id: 항목의 ID\n","    name: 항목의 이름 (타이틀)\n","    host_id: 호스트 ID\n","    host_name: 호스트의 이름\n","    neighbourhood_group: 방이 있는 구역 그룹\n","    neighbourhood: 방이 있는 구역\n","    latitude: 방이 위치한 위도\n","    longitude: 방이 위치한 경도\n","    room_type: 방의 종류\n","    price: 가격 (미 달러)\n","    minimum_nights: 최소 숙박 일수\n","    number_of_reviews: 리뷰의 개수\n","    last_review: 마지막 리뷰 일자\n","    reviews_per_month: 월별 리뷰 개수\n","    calculated_host_listings_count: 호스트가 올린 방 개수\n","    availability_365: 365일 중 가능한 일수\n","\n","    \n","- 데이터 출처: https://www.kaggle.com/dgomonov/new-york-city-airbnb-open-data\n"]},{"cell_type":"markdown","metadata":{"id":"IRssoNrgP7So"},"source":["## Step 1. 데이터셋 로드"]},{"cell_type":"code","metadata":{"id":"g49RuFGrBvt7","executionInfo":{"status":"ok","timestamp":1641143503122,"user_tz":-540,"elapsed":410,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"source":["import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import seaborn as sns"],"execution_count":1,"outputs":[]},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Q0A48l7ZoFQ4","executionInfo":{"status":"ok","timestamp":1641141030019,"user_tz":-540,"elapsed":19985,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"6fe70d06-df42-4115-da73-aeef4924ee78"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","source":["df = pd.read_csv('/content/drive/MyDrive/data/AB_NYC_2019.csv')"],"metadata":{"id":"mlFUyYnioH9C","executionInfo":{"status":"ok","timestamp":1641143505893,"user_tz":-540,"elapsed":654,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"execution_count":2,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"9L3BNVM7tHN5"},"source":["## Step 2. EDA 및 데이터 기초 통계 분석\n"]},{"cell_type":"markdown","metadata":{"id":"HyFm33tNtVn7"},"source":["### 불필요한 데이터 데이터프레임에서 제거\n"]},{"cell_type":"code","metadata":{"id":"YcR9BX23DIFW","colab":{"base_uri":"https://localhost:8080/","height":312},"executionInfo":{"status":"ok","timestamp":1641143509821,"user_tz":-540,"elapsed":648,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"ef426178-0f78-4ea9-cc73-65907426794e"},"source":["df.head(3)"],"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"text/html":["\n","  <div id=\"df-704922b3-6fdc-4505-bd46-c17fe095a429\">\n","    <div class=\"colab-df-container\">\n","      <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>name</th>\n","      <th>host_id</th>\n","      <th>host_name</th>\n","      <th>neighbourhood_group</th>\n","      <th>neighbourhood</th>\n","      <th>latitude</th>\n","      <th>longitude</th>\n","      <th>room_type</th>\n","      <th>price</th>\n","      <th>minimum_nights</th>\n","      <th>number_of_reviews</th>\n","      <th>last_review</th>\n","      <th>reviews_per_month</th>\n","      <th>calculated_host_listings_count</th>\n","      <th>availability_365</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>2539</td>\n","      <td>Clean &amp; quiet apt home by the park</td>\n","      <td>2787</td>\n","      <td>John</td>\n","      <td>Brooklyn</td>\n","      <td>Kensington</td>\n","      <td>40.64749</td>\n","      <td>-73.97237</td>\n","      <td>Private room</td>\n","      <td>149</td>\n","      <td>1</td>\n","      <td>9</td>\n","      <td>2018-10-19</td>\n","      <td>0.21</td>\n","      <td>6</td>\n","      <td>365</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2595</td>\n","      <td>Skylit Midtown Castle</td>\n","      <td>2845</td>\n","      <td>Jennifer</td>\n","      <td>Manhattan</td>\n","      <td>Midtown</td>\n","      <td>40.75362</td>\n","      <td>-73.98377</td>\n","      <td>Entire home/apt</td>\n","      <td>225</td>\n","      <td>1</td>\n","      <td>45</td>\n","      <td>2019-05-21</td>\n","      <td>0.38</td>\n","      <td>2</td>\n","      <td>355</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>3647</td>\n","      <td>THE VILLAGE OF HARLEM....NEW YORK !</td>\n","      <td>4632</td>\n","      <td>Elisabeth</td>\n","      <td>Manhattan</td>\n","      <td>Harlem</td>\n","      <td>40.80902</td>\n","      <td>-73.94190</td>\n","      <td>Private room</td>\n","      <td>150</td>\n","      <td>3</td>\n","      <td>0</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>1</td>\n","      <td>365</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-704922b3-6fdc-4505-bd46-c17fe095a429')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n","  </svg>\n","      </button>\n","      \n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      flex-wrap:wrap;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","      <script>\n","        const buttonEl =\n","          document.querySelector('#df-704922b3-6fdc-4505-bd46-c17fe095a429 button.colab-df-convert');\n","        buttonEl.style.display =\n","          google.colab.kernel.accessAllowed ? 'block' : 'none';\n","\n","        async function convertToInteractive(key) {\n","          const element = document.querySelector('#df-704922b3-6fdc-4505-bd46-c17fe095a429');\n","          const dataTable =\n","            await google.colab.kernel.invokeFunction('convertToInteractive',\n","                                                     [key], {});\n","          if (!dataTable) return;\n","\n","          const docLinkHtml = 'Like what you see? Visit the ' +\n","            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","            + ' to learn more about interactive tables.';\n","          element.innerHTML = '';\n","          dataTable['output_type'] = 'display_data';\n","          await google.colab.output.renderOutput(dataTable, element);\n","          const docLink = document.createElement('div');\n","          docLink.innerHTML = docLinkHtml;\n","          element.appendChild(docLink);\n","        }\n","      </script>\n","    </div>\n","  </div>\n","  "],"text/plain":["     id  ... availability_365\n","0  2539  ...              365\n","1  2595  ...              355\n","2  3647  ...              365\n","\n","[3 rows x 16 columns]"]},"metadata":{},"execution_count":3}]},{"cell_type":"code","source":["df['room_type'].value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"BpTY0DklrfLy","executionInfo":{"status":"ok","timestamp":1641143509822,"user_tz":-540,"elapsed":13,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"f7a122d3-9b06-4803-a56c-2211d3f14859"},"execution_count":4,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Entire home/apt    25409\n","Private room       22326\n","Shared room         1160\n","Name: room_type, dtype: int64"]},"metadata":{},"execution_count":4}]},{"cell_type":"code","source":["df.info()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Xhz7ahotq5b8","executionInfo":{"status":"ok","timestamp":1641143510457,"user_tz":-540,"elapsed":46,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"d6b5ad21-2684-4615-f54a-7e81838501f5"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 48895 entries, 0 to 48894\n","Data columns (total 16 columns):\n"," #   Column                          Non-Null Count  Dtype  \n","---  ------                          --------------  -----  \n"," 0   id                              48895 non-null  int64  \n"," 1   name                            48879 non-null  object \n"," 2   host_id                         48895 non-null  int64  \n"," 3   host_name                       48874 non-null  object \n"," 4   neighbourhood_group             48895 non-null  object \n"," 5   neighbourhood                   48895 non-null  object \n"," 6   latitude                        48895 non-null  float64\n"," 7   longitude                       48895 non-null  float64\n"," 8   room_type                       48895 non-null  object \n"," 9   price                           48895 non-null  int64  \n"," 10  minimum_nights                  48895 non-null  int64  \n"," 11  number_of_reviews               48895 non-null  int64  \n"," 12  last_review                     38843 non-null  object \n"," 13  reviews_per_month               38843 non-null  float64\n"," 14  calculated_host_listings_count  48895 non-null  int64  \n"," 15  availability_365                48895 non-null  int64  \n","dtypes: float64(3), int64(7), object(6)\n","memory usage: 6.0+ MB\n"]}]},{"cell_type":"code","source":["df.isna().sum()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ji4ClUVyshm_","executionInfo":{"status":"ok","timestamp":1641143510457,"user_tz":-540,"elapsed":5,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"792d38e3-0ac9-48cc-ed6d-f3f2c4c34282"},"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["id                                    0\n","name                                 16\n","host_id                               0\n","host_name                            21\n","neighbourhood_group                   0\n","neighbourhood                         0\n","latitude                              0\n","longitude                             0\n","room_type                             0\n","price                                 0\n","minimum_nights                        0\n","number_of_reviews                     0\n","last_review                       10052\n","reviews_per_month                 10052\n","calculated_host_listings_count        0\n","availability_365                      0\n","dtype: int64"]},"metadata":{},"execution_count":6}]},{"cell_type":"code","source":["# reviews_per_month와 last_review 컬럼이 같은지 확인\n","print((df['reviews_per_month'].isna() & df['last_review'].isna()).sum())\n","print(df['reviews_per_month'].isna().sum())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"yOnQONsLrtBu","executionInfo":{"status":"ok","timestamp":1641143510999,"user_tz":-540,"elapsed":7,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"8aae5e9a-3150-49e3-ebf3-baa17d81e280"},"execution_count":7,"outputs":[{"output_type":"stream","name":"stdout","text":["10052\n","10052\n"]}]},{"cell_type":"code","source":["df['availability_365'].hist()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":284},"id":"MQmHF7xtsPFa","executionInfo":{"status":"ok","timestamp":1641143511522,"user_tz":-540,"elapsed":528,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"a8b7989a-b1e4-4b28-c449-c3c7f61c581a"},"execution_count":8,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f49bca3a910>"]},"metadata":{},"execution_count":8},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["# availability_365 컬럼 0 개수 확인\n","(df['availability_365'] == 0).sum()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"owmKw5aDsR4B","executionInfo":{"status":"ok","timestamp":1641143511523,"user_tz":-540,"elapsed":15,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"181c8746-8967-4a31-93d5-9d699a9438e3"},"execution_count":9,"outputs":[{"output_type":"execute_result","data":{"text/plain":["17533"]},"metadata":{},"execution_count":9}]},{"cell_type":"code","source":["df.describe()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":364},"id":"Kyc9rEjvrC_J","executionInfo":{"status":"ok","timestamp":1641143511525,"user_tz":-540,"elapsed":15,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"330ebc0d-3949-4c0c-95da-22dead261f10"},"execution_count":10,"outputs":[{"output_type":"execute_result","data":{"text/html":["\n","  <div id=\"df-77cc4cd0-692e-4123-8614-deeafb1a14e3\">\n","    <div class=\"colab-df-container\">\n","      <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_id</th>\n","      <th>latitude</th>\n","      <th>longitude</th>\n","      <th>price</th>\n","      <th>minimum_nights</th>\n","      <th>number_of_reviews</th>\n","      <th>reviews_per_month</th>\n","      <th>calculated_host_listings_count</th>\n","      <th>availability_365</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>4.889500e+04</td>\n","      <td>4.889500e+04</td>\n","      <td>48895.000000</td>\n","      <td>48895.000000</td>\n","      <td>48895.000000</td>\n","      <td>48895.000000</td>\n","      <td>48895.000000</td>\n","      <td>38843.000000</td>\n","      <td>48895.000000</td>\n","      <td>48895.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>1.901714e+07</td>\n","      <td>6.762001e+07</td>\n","      <td>40.728949</td>\n","      <td>-73.952170</td>\n","      <td>152.720687</td>\n","      <td>7.029962</td>\n","      <td>23.274466</td>\n","      <td>1.373221</td>\n","      <td>7.143982</td>\n","      <td>112.781327</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>1.098311e+07</td>\n","      <td>7.861097e+07</td>\n","      <td>0.054530</td>\n","      <td>0.046157</td>\n","      <td>240.154170</td>\n","      <td>20.510550</td>\n","      <td>44.550582</td>\n","      <td>1.680442</td>\n","      <td>32.952519</td>\n","      <td>131.622289</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>2.539000e+03</td>\n","      <td>2.438000e+03</td>\n","      <td>40.499790</td>\n","      <td>-74.244420</td>\n","      <td>0.000000</td>\n","      <td>1.000000</td>\n","      <td>0.000000</td>\n","      <td>0.010000</td>\n","      <td>1.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>9.471945e+06</td>\n","      <td>7.822033e+06</td>\n","      <td>40.690100</td>\n","      <td>-73.983070</td>\n","      <td>69.000000</td>\n","      <td>1.000000</td>\n","      <td>1.000000</td>\n","      <td>0.190000</td>\n","      <td>1.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>1.967728e+07</td>\n","      <td>3.079382e+07</td>\n","      <td>40.723070</td>\n","      <td>-73.955680</td>\n","      <td>106.000000</td>\n","      <td>3.000000</td>\n","      <td>5.000000</td>\n","      <td>0.720000</td>\n","      <td>1.000000</td>\n","      <td>45.000000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>2.915218e+07</td>\n","      <td>1.074344e+08</td>\n","      <td>40.763115</td>\n","      <td>-73.936275</td>\n","      <td>175.000000</td>\n","      <td>5.000000</td>\n","      <td>24.000000</td>\n","      <td>2.020000</td>\n","      <td>2.000000</td>\n","      <td>227.000000</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>3.648724e+07</td>\n","      <td>2.743213e+08</td>\n","      <td>40.913060</td>\n","      <td>-73.712990</td>\n","      <td>10000.000000</td>\n","      <td>1250.000000</td>\n","      <td>629.000000</td>\n","      <td>58.500000</td>\n","      <td>327.000000</td>\n","      <td>365.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-77cc4cd0-692e-4123-8614-deeafb1a14e3')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n","  </svg>\n","      </button>\n","      \n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      flex-wrap:wrap;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","      <script>\n","        const buttonEl =\n","          document.querySelector('#df-77cc4cd0-692e-4123-8614-deeafb1a14e3 button.colab-df-convert');\n","        buttonEl.style.display =\n","          google.colab.kernel.accessAllowed ? 'block' : 'none';\n","\n","        async function convertToInteractive(key) {\n","          const element = document.querySelector('#df-77cc4cd0-692e-4123-8614-deeafb1a14e3');\n","          const dataTable =\n","            await google.colab.kernel.invokeFunction('convertToInteractive',\n","                                                     [key], {});\n","          if (!dataTable) return;\n","\n","          const docLinkHtml = 'Like what you see? Visit the ' +\n","            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","            + ' to learn more about interactive tables.';\n","          element.innerHTML = '';\n","          dataTable['output_type'] = 'display_data';\n","          await google.colab.output.renderOutput(dataTable, element);\n","          const docLink = document.createElement('div');\n","          docLink.innerHTML = docLinkHtml;\n","          element.appendChild(docLink);\n","        }\n","      </script>\n","    </div>\n","  </div>\n","  "],"text/plain":["                 id  ...  availability_365\n","count  4.889500e+04  ...      48895.000000\n","mean   1.901714e+07  ...        112.781327\n","std    1.098311e+07  ...        131.622289\n","min    2.539000e+03  ...          0.000000\n","25%    9.471945e+06  ...          0.000000\n","50%    1.967728e+07  ...         45.000000\n","75%    2.915218e+07  ...        227.000000\n","max    3.648724e+07  ...        365.000000\n","\n","[8 rows x 10 columns]"]},"metadata":{},"execution_count":10}]},{"cell_type":"code","source":["df.columns"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"fETRDkf0tIz9","executionInfo":{"status":"ok","timestamp":1641143511526,"user_tz":-540,"elapsed":15,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"486fb146-ef02-414b-8f45-0114dcf8ca45"},"execution_count":11,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['id', 'name', 'host_id', 'host_name', 'neighbourhood_group',\n","       'neighbourhood', 'latitude', 'longitude', 'room_type', 'price',\n","       'minimum_nights', 'number_of_reviews', 'last_review',\n","       'reviews_per_month', 'calculated_host_listings_count',\n","       'availability_365'],\n","      dtype='object')"]},"metadata":{},"execution_count":11}]},{"cell_type":"code","source":["# 필요없는 칼럼 드랍\n","df.drop(['id', 'name', 'host_name', 'latitude', 'longitude'], axis=1, inplace=True)"],"metadata":{"id":"s9FybgcRtKXd","executionInfo":{"status":"ok","timestamp":1641143511527,"user_tz":-540,"elapsed":13,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"execution_count":12,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"HGHvPwkNtXgj"},"source":["### 수치형 데이터와 Price의 Jointplot 분석\n"]},{"cell_type":"markdown","source":["수치형 데이터를 가지고 Price를 잘 예측할 수 있는가 확인"],"metadata":{"id":"wqklHIAqtVEK"}},{"cell_type":"markdown","source":["#### host_id\n","상관성이 없어 보임\n","\n","price의 outlier가 심해서 일 것 같음"],"metadata":{"id":"aSbdLWohtkMs"}},{"cell_type":"code","metadata":{"id":"b_zcrUDF7khF","colab":{"base_uri":"https://localhost:8080/","height":459},"executionInfo":{"status":"ok","timestamp":1641143517596,"user_tz":-540,"elapsed":4862,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"f3c0554f-ea60-415a-f4f1-a18ec23e8edf"},"source":["sns.jointplot(x='host_id', y='price', data=df, kind='hex')"],"execution_count":13,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<seaborn.axisgrid.JointGrid at 0x7f49bb274d10>"]},"metadata":{},"execution_count":13},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAbgAAAGoCAYAAAA0HPAoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3de5DkV33f/fe3u+eyF+1KQosktBISWAEEiYzYkrjYmEIYZOJY1GPsQBwQWEHhMY+xXXY5mKQefImr7CrHxDy2ITKSEYRCXOwEOcGAAphLmdtyMSAI0VoYJAFm0RVJq92Z7u/zx+/XM9093bPduzPTM2fer6rZ7T59+vzO6dvndzn968hMJEkqTWPaHZAkaT0YcJKkIhlwkqQiGXCSpCIZcJKkIrWm3YEpcNqopJLEtDuwWbkFJ0kqkgEnSSrSdtxFeUKuefWv8e277usre9Qj9nLtG/5gSj2SJK3GgBvTt++6j90/9vP9ZR+9fkq9kSQdj7soJUlFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUVqTbsDW9lXvvxlfvLnXrGi/FGP2Mu1b/iDKfRIktRlwJ2EY9lg94/9/Iryb3/0+in0RpLUy12UkqQiGXCSpCIZcJKkIhlwkqQiGXCSpCIZcJKkIhlwkqQiGXCSpCL5Re91MOwMJ57dRJI2lgG3Doad4cSzm0jSxjLgNsio81be9n/+N4/5J4/vK3NrT5JOngG3QUadt/LeL/2qW3uStA6cZCJJKpIBJ0kqkgEnSSqSASdJKpKTTDYhZ1xK0skz4DahSWZcfvCPf2XsMBxWBoakpDIZcFvcJGE4rAz8WoKkMnkMTpJUJLfgNNQ1r/41vn3XfSvKN+vuzK3WX0nrz4DT0Ektt3zt61z2yt9fUXfYMb9Rx/Y2clLMt++6z92vBXGFRWvBgNPQ43hHv/SrY9cddWxvvSbFDCu/5Wtf57IfG9rlFUZ9eE6yvPUK9Un6tpk/7IeNY5L+jlphmWQFayMfn1Ket9IYcNpQazEpZlj5qECeZOt0kuWtV6hP0rf1WllYi7rDxjHx4zBkhWWSFayT3dsw8QrWST5vBt/ai8ycdh82VES8HzjjBO56BvD9Ne7OtDiWzamksUBZ49nMY/l+Zl4x7U5sRtsu4E5URBzMzAPT7sdacCybU0ljgbLGU9JYthO/JiBJKpIBJ0kqkgE3vmun3YE15Fg2p5LGAmWNZ83HEhHXR8T3IuIrY9Q9LyI+EhFfiIgvRcTz17o/JfIYnCRNQUQ8E3gAeGtmPuk4da8FvpCZb4yIi4D3Zeb5G9DNLc0tOEmagsz8GHB3b1lEPDYi3h8Rn4uIj0dE9/sICeypL+8Fvr2BXd2y/B6cJG0e1wKvzMxbI+Iy4E+BZwO/CXwwIn4R2AU8Z3pd3DoMOEnaBCJiN/B04N0R0S2eq/9/MfCWzPxPEfE04G0R8aTM7Eyhq1uGASdJm0MDuDczf3jIbVcDVwBk5icjYp7qy+ff28D+bTkeg5OkTSAz7we+ERE/AxCVi+ubvwVcXpc/AZgHDk+lo1vItgu4K664IqkO2Prnn3/+Te3vxS9+cZ511lnfaLVaT9y/f39ed911edtttz3tec973rsuvvjifMITntD5rd/6rS8Cecstt1zx9Kc//c8vvvjivPjii7/6gQ984Ox692QygUI//0badl8TOHDgQB48eHDa3ZCktRLHr1Ip9PNv5Pi33RacJGl7MOAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRVq3gBv2a7URcXpE3BwRt9b/n1aXR0S8ISIO1b9We0nPfa6q698aEVf1lD8lIr5c3+cN0XP6bUmS1nML7i3UZ7/u8RrgQ5l5IfCh+jrATwAX1n/XAG+EKhCB1wGXAZcCr+uGYl3nFT33G1yWJGkbW7eAG/ZrtcCVwA315RuAF/SUvzUrnwJOjYizgecBN2fm3Zl5D3AzcEV9257M/FRWJ9N8a09bkiRt+DG4MzPzO/Xl7wJn1pfPAW7vqXdHXbZa+R1DyiVJAqY4yaTe8tqQnzKIiGsi4mBEHDx82J9QkrR9bOfPv40OuH+sdy9S/9/9Ndo7gXN76u2vy1Yr3z+kfKjMvDYzD2TmgX379p30ICRpq9jOn38bHXA3Ad2ZkFcB7+0pf2k9m/KpwH31rswPAM+NiNPqySXPBT5Q33Z/RDy1nj350p62JEmitV4NR8Q7gGcBZ0TEHVSzIX8PeFdEXA18E/jZuvr7gOcDh4CHgJcDZObdEfE7wGfrer+dmd2JK79ANVNzB/DX9Z8kScA6BlxmvnjETZcPqZvAq0a0cz1w/ZDyg8CTTqaPkqRyeSYTSVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkaYScBHxKxFxS0R8JSLeERHzEXFBRHw6Ig5FxDsjYrauO1dfP1Tffn5PO79Rl389Ip43jbFIkjanDQ+4iDgHeDVwIDOfBDSBFwG/D7w+M38IuAe4ur7L1cA9dfnr63pExEX1/Z4IXAH8aUQ0N3IskqTNa1q7KFvAjohoATuB7wDPBt5T334D8IL68pX1derbL4+IqMtvzMyjmfkN4BBw6Qb1X5K0yW14wGXmncAfAN+iCrb7gM8B92bmYl3tDuCc+vI5wO31fRfr+o/oLR9yH0nSNjeNXZSnUW19XQA8CthFtYtxPZd5TUQcjIiDhw8fXs9FSdKmsp0//6axi/I5wDcy83BmLgB/CTwDOLXeZQmwH7izvnwncC5Affte4K7e8iH36ZOZ12bmgcw8sG/fvrUejyRtWtv5828aAfct4KkRsbM+lnY58FXgI8AL6zpXAe+tL99UX6e+/cOZmXX5i+pZlhcAFwKf2aAxSJI2udbxq6ytzPx0RLwH+DywCHwBuBb4n8CNEfEf67Lr6rtcB7wtIg4Bd1PNnCQzb4mId1GF4yLwqsxsb+hgJEmbVlQbQ9vHgQMH8uDBg9PuhiStlRi3YqGffyPH75lMJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRTLgJElFMuAkSUUy4CRJRZpKwEXEqRHxnoj43xHxtYh4WkScHhE3R8St9f+n1XUjIt4QEYci4ksRcUlPO1fV9W+NiKumMRZJ0uY0rS24PwLen5mPBy4Gvga8BvhQZl4IfKi+DvATwIX13zXAGwEi4nTgdcBlwKXA67qhKEnShgdcROwFnglcB5CZxzLzXuBK4Ia62g3AC+rLVwJvzcqngFMj4mzgecDNmXl3Zt4D3AxcsYFDkSRtYtPYgrsAOAz8eUR8ISLeHBG7gDMz8zt1ne8CZ9aXzwFu77n/HXXZqHJJkqYScC3gEuCNmflk4EGWd0cCkJkJ5FotMCKuiYiDEXHw8OHDa9WsJG162/nzbxoBdwdwR2Z+ur7+HqrA+8d61yP1/9+rb78TOLfn/vvrslHlK2TmtZl5IDMP7Nu3b80GIkmb3Xb+/NvwgMvM7wK3R8Tj6qLLga8CNwHdmZBXAe+tL98EvLSeTflU4L56V+YHgOdGxGn15JLn1mWSJNGa0nJ/EXh7RMwCtwEvpwrbd0XE1cA3gZ+t674PeD5wCHiorktm3h0RvwN8tq7325l598YNQZK0mU0l4DLzi8CBITddPqRuAq8a0c71wPVr2ztJUgk8k4kkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUhjB1xEPDoinlNf3hERp6xftyRJOjljBVxEvILql7f/S120H/jv69UpSZJO1rhbcK8CngHcD5CZtwKPXK9OSZJ0ssYNuKOZeax7JSJaQK5PlyRJOnnjBtxHI+K1wI6I+HHg3cBfrV+3JEk6OeMG3GuAw8CXgX8LvA/4D+vVKUmSTlZrzHo7gOsz888AIqJZlz20Xh2TJOlkjLsF9yGqQOvaAfyvte+OJElrY9yAm8/MB7pX6ss716dLkiSdvHED7sGIuKR7JSKeAhxZny5JknTyxj0G98vAuyPi20AAZwH/ct16JUnSSRor4DLzsxHxeOBxddHXM3Nh/bolSdLJWTXgIuLZmfnhiPi/Bm76JxFBZv7lOvZNkqQTdrwtuB8DPgz8iyG3JWDASZI2pVUDLjNfFxEN4K8z810b1CdJkk7acWdRZmYH+PUN6IskSWtm3K8J/K+I+LWIODciTu/+rWvPJEk6CeN+TeBfUh1z+4WB8sesbXckSVob4wbcRVTh9iNUQfdx4E3r1SlJkk7WuAF3A9WPnb6hvv6v6rKfXY9OSZJ0ssYNuCdl5kU91z8SEV9djw5JkrQWxp1k8vmIeGr3SkRcBhxcny5JknTyxt2CewrwtxHxrfr6ecDXI+LLQGbmP1uX3kmSdILGDbgr1rUXkiStsXFPtvzN9e6IJElradxjcJIkbSkGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUhTC7iIaEbEFyLif9TXL4iIT0fEoYh4Z0TM1uVz9fVD9e3n97TxG3X51yPiedMZiSRpM5rmFtwvAV/ruf77wOsz84eAe4Cr6/KrgXvq8tfX9YiIi4AXAU+kOhn0n0ZEc4P6Lkna5KYScBGxH/jnwJvr6wE8G3hPXeUG4AX15Svr69S3X17XvxK4MTOPZuY3gEPApRszAknSZjetLbj/DPw60KmvPwK4NzMX6+t3AOfUl88Bbgeob7+vrr9UPuQ+kqRtbsMDLiJ+EvheZn5uA5d5TUQcjIiDhw8f3qjFStLUbefPv2lswT0D+KmI+AfgRqpdk38EnBoR3d+n2w/cWV++EzgXoL59L3BXb/mQ+/TJzGsz80BmHti3b9/ajkaSNrHt/Pm34QGXmb+Rmfsz83yqSSIfzsyfAz4CvLCudhXw3vryTfV16ts/nJlZl7+onmV5AXAh8JkNGoYkaZMb6xe9N8i/A26MiP8IfAG4ri6/DnhbRBwC7qYKRTLzloh4F/BVYBF4VWa2N77bkqTNaKoBl5l/A/xNffk2hsyCzMyHgZ8Zcf/fBX53/XooSdqqPJOJJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSAacJKlIBpwkqUgGnCSpSBsecBFxbkR8JCK+GhG3RMQv1eWnR8TNEXFr/f9pdXlExBsi4lBEfCkiLulp66q6/q0RcdVGj0WStHlNYwtuEfjVzLwIeCrwqoi4CHgN8KHMvBD4UH0d4CeAC+u/a4A3QhWIwOuAy4BLgdd1Q1GSpA0PuMz8TmZ+vr78A+BrwDnAlcANdbUbgBfUl68E3pqVTwGnRsTZwPOAmzPz7sy8B7gZuGIDhyJJ2sSmegwuIs4Hngx8GjgzM79T3/Rd4Mz68jnA7T13u6MuG1UuSdL0Ai4idgN/AfxyZt7fe1tmJpBruKxrIuJgRBw8fPjwWjUrSZvedv78m0rARcQMVbi9PTP/si7+x3rXI/X/36vL7wTO7bn7/rpsVPkKmXltZh7IzAP79u1bu4FI0ia3nT//pjGLMoDrgK9l5h/23HQT0J0JeRXw3p7yl9azKZ8K3FfvyvwA8NyIOK2eXPLcukySJFpTWOYzgJcAX46IL9ZlrwV+D3hXRFwNfBP42fq29wHPBw4BDwEvB8jMuyPid4DP1vV+OzPv3pghSJI2uw0PuMz8BBAjbr58SP0EXjWireuB69eud5KkUngmE0lSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SVKRDDhJUpEMOElSkQw4SdomMnPaXdhQBpwkqUgGnCRtExEx7S5sKANOklQkA06SVCQD7jgyq79Rt41TJm1n221igzaP1rQ7sFllQt/bsr4S0R9iOaS8t0zazrrh1v1/ux0D2my228qGATfC4MsggaAnxHpu65aveOkYdNqmuh+knZ43RfU2MOi0cQy4CYxa91ltncj3sbajZOXu+u5KouGmjeIxOElSkdyCm0BmstiBVqN/LbR3v3Zfef1P7wpr71ptt3xY2Wrl0na1md8Tvo83HwNuDFWwJQud6vpCB2YaSTNixe7JBrki5EYe1x1y3G61GZvV7p3J+y9ttN7Xavc4XGNphS4n3k057Bj3ZnpPDPZvM7+PT+Tx36oMuBEasfyiPdrOvoPlUIVcNFa+ULLebBvnBbS95jNpO+m+/jNzKdhO5kN1M79Xhk4w26S+cfiBbRVwHoNbRcRy0K24beSdPIgudXXfC74nNocL9u3eVs+FW3CS1tV2+kDdCjJzad5Ao1H2Nk7Zo1sDmSt3T55oO+OW54RfSBjaxiTLm6BuVX5ydUe3sT51q/Jh456sjcmWd3J1J21jEmsx7knanrTd4fXHb2Qtvsw8eRPD7nAiXyzSWnILbhUPLXT4xwcWmW8Fu2erdYGIqNaAgHYGDZJGz/GGTIh6taH3OEQn+yeg9L4Je/eJL535oecLsUt162+Uj9NGdShwZRvd8hXLGzjTRG/5ctnyY5PZOwt0ZRuj665ePuzMMOPUHd3GqHGPv7xR1q/Pk7UxibUY92rtDrYxSZ9XfX1l/3ti8H6rvRZPdCyjnqv+suyZSDbsvXn89/FG676nS996AwNupLseWuTuIx0SWDiWHFlsc9p8k1aj+qrAA8c6dBJ2zgR75hoE1WSUY20Ikh0zwWyzenk/tNCh3YFmwI6ZBo2AdsKxdvWCbzVgpn6tdRLqyZo06zdCAoudqq1GwGwjl+vW75lGVAEKVdvd91KzMbyNFt0PguX1yeg5VUvvVmtjucbA6ctWttHoC5XeudIrLx7vzDCD5ZO1Ua1stBMW2tX4ex/n3r4db3mDn0Pr1+fV2xhVd5zPyRNZ3iTtjmpjnD6PbqO6dqydtLO6/0wjqIKkajEH6i6HTf/reaxJXxM9Rsvvk8Xue5Dl98qo90Qnq4YCaDZOPIRP1G2HH2BhYYFWq/roLz3kDLgRjiz07yhc7MDhh9rsaEKn58PxoYVksd1mthlL79qsy48u9rfRzioYZxr0vcMXO9DJpNnof6F3g6q3jU7C0Xb1Zup9X/SGXa/FOi0H21jIlW0MLqu3Pqz8wBu2vOW6A2vZQ9odVjZp+ai6vcHW1X0sWo3j961bPuyj52THslbjnmS6+aT9mOQjd9y2V+vzsPqDs5cTONZJ5pqxoofDXovdLbtJAmSwmVGPUW+wLZV1lzmk7rDltDv1CugGuuCMXTSbzeKDrWt7jHINtUe8WFcLhmH1xzVJ3fVsYyvaruOWjqfT6Sz93/0rkQE3gWPHjvGZT36CdrvdV374wQW+de+xvrLM5Ds/WODoYv8LZ6GdfO/BxRUHwu97uM0Pjva3m5ncf7RNZ6DuQjt54NjKF+SRhQ4LAwmcmTxwtL1ieQvt5OHFlW0ca+eK5XWy3hodKG93knZn5fKOtVfW7WT1ZflB7c7K5XW/WD+sjcHlddsYrJuZLA7pR3U8dLzl5SrLO9k+d3J031a0MeJxHtXnwb51y8dd3qg2JurziMd5kuVl9u++7NYd9loc3WfWrc/DHtNRr41Rr9Fhr431dNvhBzh69CgLCwt94Tbqb6tzF+UIu2YbHFlsL20FfPJjH+G1r34Fd33/MPvPO58/fOP1XHTxJfzFV+7hv91yDwDPfuwe/u2l+1hM+OChB/jODxZoNYLLH7OLx58xy50/aPOZO4/Q7iSn7WjyjPN2snOmwee+fYRDdx0F4ElnzvPkR+3g6GJy611HObKQtBrw2NPn2Dvf4HsPLPLN+xYgYe98gx86fZZmI7jz/gXuP1rtPD1zd5MzdrZ44FiHf7h3gYV2MtsMHn3aLDtngu8/tMj3H6zC9NT5BmefMgPA/Ufb9TFEOGU2mG8FR9twz8PV8cbZZnD6jiatBjy40OHheh/NfBN2zjRYTLj/4Q6LWR132DvXYLYZHF3s8FBdt9WAXTNNIuDoYmdpt+FsM5htBu2Ehxc6S7uzuscsj7Wz75jlfKs62vHwQmdpq3quGcw0g6Pt5L6H23SyOo65a7ZBoz7rTCdhoZO0IplpBp2Ehxer8QVVu81GVedYvb7RbFfHVKE6nrrQXl7eXKvq85GF5TZ2zjZoRrUS0V0PaUYy36raONaz67QV1a7pbr+oxz3TrP5/eLGz1I/ZZtW/wT7vmKmW1931DNWxoG4b7U7P8b+sjl8l/btwZ7t1c3kvRTOTmUa9a7Bnd+FMI2nVfe6OL4BWozqyudDOpd133cc5WT4GDNVx5KA6traw1EZVN1g+7gbLu/0WO8kPjlbPdzPg9J1N5pqx4nGea1atLSZ9j3OrHsvCkD4fay+fqagZ1fuF+vHottGkStwklup2H2uoXs/d8rlmMFe/vrrPd9SPcyOqx2LpMep0mG/F0mS1dZXJS679JG9/5TOWAqy7u3KSQIuILfH1j9huvw904MCBPHjw4Fh1jy4m331gkV9/9Su56T038vCRh5Zu2/WIs3nSv38vMb+bo/UrdbYZnL1nliedvbvveNZMAx65q0WzEUtv2uooQi7NYuuWtxpwxo4Wj9jV6tvFFtQHq+nf9VkFRqOvbgNoZ/Z9sHXbmGstHyfsLdtTfSr01R12DDCA+ZmVL+xOZ3lyTG/dmeaKqvUHy/q8OR7uCc2l5QWcMttY8YbsdIZ/IaM7gaHXpF8XqY6t9LcRjH/MpdoSHtK3pf71m2kO/8BpDanb7uSK5wpGj3uYWL5DX91hj1EAjcHjniPaHXUc+MFjyytUve3unV/5vAbQai71sq985YShXPF6oa634ljtiPF1Mlf0Dar34eBx9W7bw45y7pyJE31fjH2nU/dfmM989R/RmpsnGtVrJpaOx8WYE4uSd77yRzbTcbyRvXYLbhVzreC8vS3+5oP/sy/cANhzFkc7QfS8sI+1k9N3zgw9rVfSf/yuG1Qx8IZe7FRbAINvl8H7d3VDr1cHhr5pu+0MXp8Z8qYaDNKubiCvmHAyYlnD6q7net+wcTdHLHBUXg3r86SrgUPHPcHA12LPVTXfcMikhxH1h/V5lGHtrtqRk3RsyIt/VF9HBcgwox7mST66Rz1XI7NqxIO32Ml1W/HrW3ynQ/voUaLRoDHTgnYbEt76by5jdnZ26H0Gt9gy84R2YW50KBpwxxERo98q22zrV1IZkiQ7bXIhCaqtuJe8+VM0mwORUH/F4e2veNpSODUajaHHH9fbiewWNeDGsMHHgdd39t9Eq97r2ciadETH48O8dWzE50xWf9mutr6y3al2UbbbRKOxVE5QBV+9T/1fXfu3S+HSaAwcd4jlCxNsPE/W7Xq36LYLuIi4AvgjoAm8OTN/b63avudIm3d86V52X/Bk7r3/Yyw8vLybsv3AXRDVwf3u3pNGwN1HFjhrzyy9z3L3oHL3i9+9Bq83qCYyVJMajv9ktjssnZmgV3f31OCyqkPk/XUXOsn8kDaGGbXSNmx5I9tgst1h46vOXD+4QjJqBWX1Pg8kwwQfPlkPbvB56R5fGvXF8d7ykXu3Jvni8oj7TzTu1dofMr7h9erX3Zh9HvbamGlU3//s1ek+ngN36GTSWCrqludSX/r6MarPdMe33MZqr/1hOlQfSuOKqI4LT/rdvckkmf27FpdCrefxjUaj+uus3KXYPWYXVQpW1zN5y89fSqPRWLEbsvf6yeyibLfbdDqdpS25cdra0gEXEU3gT4AfB+4APhsRN2XmV0+27c/c8RD/9e/uo91Jfvw33szff/y9fOJNr6W9eIzWjt1cdvVvcdb+fXz/gaPce2SBRsCj9szyjEfvYbYZ3H2kTbsDBJy1u8W+nU0eXkwerKe5NQJ2zTVpRnUA/Vh9qoZT55s8cleLRtA3U2u2WU0YWOzQM2OsOjDdnSHY1QB2tKpTiR3tOXYx+EOtVbvB7tnm0ONkM43qQ6T38EerCcnygb/u/ZqNlV82b8bwN3/1AbuyjRPVe5aIVqMK/d7JPHOtxog+B0k1GWdlm3R7uRxKIyZAdOt0+9FOWGxXx1OaAx/sufRPz/X+hS6NZTmIcikcqw90+tpd7bBNG6oP+7qlzuAyR427/mDvO8XU0PrLtw0+Rt2buqHVe+aOwXa7F5dePwOL3DnbpCRuNokAAA09SURBVNVOHjrWWbpprhkstqtZqINHrRfqxz+iZxksRVW3xxDVfQdXgjKrx6rRe8/B85rVmo1gPvpnmjZi+dh231mBouf10lM212TpfZy58ncl10zfpJLVZadDrnKcrRuC1F+beumffarq8+BnSc8klqVQWvF5M96B+szkxgm25LZ0wAGXAocy8zaAiLgRuBI46YD72289tHRgOyL4oWe+gHOf8mxu/cyHOefAj9OanQfgzD3zPPaMec7a3eLsPXNL9z9zd9CMYPdcc2nK8c5ZmGt1ONqup2XXT9Ip803mGrB7rsnOmeUX32wjl2ZzdevONmCmfpP1BVbWp+sK6unGUc3iimoKdWNgrXCuWU0vn2str2N21+571yAbVNPFO9nfxrD1/O6bN1i5vCSXDtz3tRH9Zd1+rGawbu9U7oig1az63Ijoe+yyt4/d5RJEY/hMuu59lpfLyNNNkfRNS4dq0kBGd8r/8gy1UaOrvrPVOxaWZrP2di+pljXXhOYYxyU69Z1OdA/Y8UKuv27V587A8pJq5azV6K3bDYAcWn/QbDOYmW8sfXVm+f7dAO2vv9hJmg36pt93A6Tb124/mvXWU295t+3BurDyNdqI6ms13e969i6zG76D74mo31PNISue66l3y2fkDINxu9O3glM9EREDT0SnUx3H65l5udpW3rDrfV2b4FjcVg+4c4Dbe67fAVy2Xgub3XkKj376v1hRfspci7P39M8+igj2zjdXTBNuRDA35FHfMdPoC7duG8O2uhoRK97M0Rdu/W0Mm5reiGC2uXJ5vR/+fW2M+YKP6J4CbKAfq0xBnuTNPaxvwyb7x0C4Ha+NST7+h3U3YnQLwx7TUSYJocYEb/QTDbeuSULuRIzbckQM/erJWliLjBn2XbbR76uND7fHPPIU3v3Lz1m6PipI1mO24zS+O7fVA24sEXENcA3AeeedN+XeSNLGGfz8G/VVgBJtmm/qnaA7gXN7ru+vy/pk5rWZeSAzD+zbt2+shs/ZM7O0a7FrtlkdV5odWINc7KycuNH9svXglk/3uNTgA9/OXLFXoHt9sO5qK0HD2ogh5e0hB/IntSbr8xM3MmQNeZLFTThR4GT17oY9UaPuvhW/pTLqGOZ6tAsb/3xPYqOevhP5/CvFVg+4zwIXRsQFETELvAi4aS0afuET9/CyJ5/Krplgpv6Zlec89hT++CcfxY+dv3vp1FKn7Wjy85eczk8/cc/SaaxaDTjv1Bl+6nGncPFZc7Qa9b72gH961jw/+bjdnLOnRbMuO2WuwWX7d3LRI+eYa8bSsbR9u5r88NnznH1Ka+nYUTPg/FNneMIZs+yebSzV3TkTXPiIWc7dO7MUogGcsavFEx85xxk7m0tlrQbs3zPDvp2tahdoXT7XDPbtbLBndjmug+q0Xft2NpjvSetmwOk7mpw63+yb5DDfCk7b0WBHzyk0Atg1E5wyG33HYJoBu2eDHa3+1YO5ZlW3d0UiqE4Htmsm+pbXjOp0Y7tm+tvYORPsHlheADtmqlMo9dbt9mNuYG2k+h3A/jYaAbtnq93JvbVnm3DGjgY7B8Z9Sl13sM87WitXlLrj7t1THQGnzDXZO9f/OM81q8dt8EwlrYC5Rv/Ek6jHMji+VlSnWRtsY7YZzDb6H6MG1TG/gb3o1WnTmv1fpg9gRyvqCVCDdVf2eaYR7JphxeO8a6ZqI/rqwmnzseL1tXu2eg00Bx7nna1YsaLaalSP3+DKZ/f0WoOvjVF9nm+ufJx3zlTH4nqrtxrV890aeOxmmsNPzzV4rE4nbsufqising/8Z6oZuddn5u+uVn+SU3VBdeqnT91+hCc+co59u5b36N5+3zFuvesYP/roXczU75TM5O/vPsaOmQbn7JlZqnt0scPt9y2yf2+L+Z5X+fcfWuSBYx3O2zuz9ELvZHL4wTa7ZhtLP7LabePehzucsbP/uN79D7fpUJ33sfeg/T1H2uyebTDXs7wjCx0eXOhw+o5m34+0PrxYTa/vrdvJ5MhCdf7E3uUda1cniJ1v9UzeqNtoNWLpsYDqlFDH2sncwHn2uudAnOk5/pBZnQuwGf2nN2p3qpMKzzb7l7fYYWkCTm+fjy5WdQfbaOfK5XV/Y6w50Eb33J29HzKLPb8p19vGse5syZ42FjtVG4OP0fLp2JbrdsfdGpgMsdhJOp3sOwVXZnK0nTSj/3Hutt0c+GBsd1ZObug+doOTLzr1qd0Gx9edZNEc6POoNjoD/eiOrxErxz2sz9UJpFf2Y9RrY6F+fQ2OD1jxGE3S52GvjdUe52RlG4ud7iSS4z/OvU4g3Ma+w6Sff1vEyPFv+YCbVKFPsKTty4AbYavvopQkaSgDTpJUJANOklQkA06SVCQDTpJUJANOklQkA06SVCQDTpJUJANOklSkbXcmk4g4DHzzBO56BvD9Ne7OtDiWzamksUBZ49nMY/l+Zl4xTsWIeP+4dUuw7QLuREXEwcw8MO1+rAXHsjmVNBYoazwljWU7cRelJKlIBpwkqUgG3PiunXYH1pBj2ZxKGguUNZ6SxrJteAxOklQkt+AkSUUy4CRJRTLgekTEFRHx9Yg4FBGvGXL7XES8s7790xFx/sb3cnxjjOdlEXE4Ir5Y//2bafTzeCLi+oj4XkR8ZcTtERFvqMf5pYi4ZKP7OIkxxvOsiLiv53n5fze6j+OKiHMj4iMR8dWIuCUifmlInS3x/Iw5li3z3AjITP+q45BN4O+BxwCzwN8BFw3U+QXgTfXlFwHvnHa/T3I8LwP+eNp9HWMszwQuAb4y4vbnA39N9dP1TwU+Pe0+n+R4ngX8j2n3c8yxnA1cUl8+Bfg/Q15nW+L5GXMsW+a58S/dgutxKXAoM2/LzGPAjcCVA3WuBG6oL78HuDwiYgP7OIlxxrMlZObHgLtXqXIl8NasfAo4NSLO3pjeTW6M8WwZmfmdzPx8ffkHwNeAcwaqbYnnZ8yxaAsx4JadA9zec/0OVr64l+pk5iJwH/CIDend5MYZD8BP17uN3hMR525M19bcuGPdSp4WEX8XEX8dEU+cdmfGUe+yfzLw6YGbttzzs8pYYAs+N9uVAbe9/RVwfmb+M+BmlrdONV2fBx6dmRcD/x/w36fcn+OKiN3AXwC/nJn3T7s/J+M4Y9lyz812ZsAtuxPo3YLZX5cNrRMRLWAvcNeG9G5yxx1PZt6VmUfrq28GnrJBfVtr4zx3W0Zm3p+ZD9SX3wfMRMQZU+7WSBExQxUIb8/MvxxSZcs8P8cby1Z7brY7A27ZZ4ELI+KCiJilmkRy00Cdm4Cr6ssvBD6cmZv1m/LHHc/AcZCfojrmsBXdBLy0nq33VOC+zPzOtDt1oiLirO6x3Yi4lOp9uilXpOp+Xgd8LTP/cES1LfH8jDOWrfTcCFrT7sBmkZmLEfH/AB+gmoF4fWbeEhG/DRzMzJuoXvxvi4hDVJMEXjS9Hq9uzPG8OiJ+ClikGs/LptbhVUTEO6hmr50REXcArwNmADLzTcD7qGbqHQIeAl4+nZ6OZ4zxvBD4vyNiETgCvGgTr0g9A3gJ8OWI+GJd9lrgPNhyz884Y9lKz82256m6JElFchelJKlIBpwkqUgGnCSpSAacJKlIBpwkTcHxTro9UPe8+kTQX6jPPPT8jejjVmfASdJ0vAW4Ysy6/wF4V2Y+merrSX+6Xp0qiQEnDYiI88dZqz5OG8+KiKcfp84rI+Kl67F8bX7DTrodEY+NiPdHxOci4uMR8fhudWBPfXkv8O0N7OqW5Re9pfXxLOAB4G9HVai/OCz1uhZ4ZWbeGhGXUW2pPRv4TeCDEfGLwC7gOdPr4tbhFpw0XDMi/qz+4csPRsSOiPjhiPhUfQzkv0XEaQAR8er6RzK/FBE31meifyXwK/WPYv7osAVExG9GxK/Vl59Sn6H+74BXbdAYtYnUJ3l+OvDu+kwq/4XqN+oAXgy8JTP3U50V5m0R4ef3cfgAScNdCPxJZj4RuBf4aeCtwL+rf33hy1Sn2AJ4DfDkuvyVmfkPwJuA12fmD2fmx8dY3p8Dv1ifpV7bUwO4t37NdP+eUN92NfAugMz8JDAPeJLn4zDgpOG+kZnd8xF+DngscGpmfrQuu4Hql7kBvgS8PSL+NdV5PScSEafWbX+sLnrbiXdbW1X90zzfiIifgerkzxHRXeH5FnB5Xf4EqoA7PJWObiEGnDTc0Z7LbeDUVer+c+BPgEuAz9Y/pSStqj7p9ieBx0XEHRFxNfBzwNX1rupbqH4NHeBXgVfU5e8AXuZJno/PN6I0nvuAeyLiR+tdji8BPlofBzk3Mz8SEZ+gmsK9G/gBy7PeVpWZ90bEvRHxI5n5CaoPORUuM1884qYVXx3IzK9S/dqBJmDASeO7CnhTROwEbqP62Zcm8F8jYi8QwBvqwPor4D0RcSXVsbXjHYd7OXB9RCTwwfUbgrR9+HM5kqQieQxOklQkd1FK6ywi/j3wMwPF787M351Gf6Ttwl2UkqQiuYtSklQkA06SVCQDTpJUJANOklSk/x9KGddqphL/4gAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 432x432 with 3 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":["#### review_per_month"],"metadata":{"id":"l5jXU7kItsAn"}},{"cell_type":"code","source":["sns.jointplot(x='reviews_per_month', y='price', data=df, kind='hex')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":459},"id":"rYg1axittz7t","executionInfo":{"status":"ok","timestamp":1641143538190,"user_tz":-540,"elapsed":20596,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"d421c1bd-b941-461c-853c-f6f0ed17a754"},"execution_count":14,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<seaborn.axisgrid.JointGrid at 0x7f49b17b5910>"]},"metadata":{},"execution_count":14},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x432 with 3 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"amkU5Y6g7Dp4"},"source":["###  수치형 데이터와 Price의 상관성 분석"]},{"cell_type":"markdown","source":["현재로서 price와의 상관성이 높지 않음\n","\n","Outlier의 문제점일 수도"],"metadata":{"id":"EUufgkNCuHr6"}},{"cell_type":"code","metadata":{"id":"GZXSBFPyDh6R","colab":{"base_uri":"https://localhost:8080/","height":429},"executionInfo":{"status":"ok","timestamp":1641143539521,"user_tz":-540,"elapsed":1335,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"8eb4bd49-fbba-4194-e55d-a2e037e5c8a1"},"source":["sns.heatmap(df.corr(), annot=True, cmap='YlOrRd')"],"execution_count":15,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f49bb1a5310>"]},"metadata":{},"execution_count":15},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"Ga7Lzcw8TH0G"},"source":["### 범주형 데이터와 Price의 Boxplot 계열 및 Histogram 분석"]},{"cell_type":"code","metadata":{"id":"MPmzv61vTFiw","colab":{"base_uri":"https://localhost:8080/","height":298},"executionInfo":{"status":"ok","timestamp":1641143540356,"user_tz":-540,"elapsed":838,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"34029593-9daa-46d7-ca50-222037fa0561"},"source":["sns.boxplot(x='neighbourhood_group', y='price', data=df)"],"execution_count":16,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f49aface190>"]},"metadata":{},"execution_count":16},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAZEAAAEHCAYAAABvHnsJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3dfZxdVX3v8c93MgMEIgSY3IgEDZKARYxUYqClAkEmMlVAW9vq9VUHS4utElBrr2jBBEittLWWh+oFFT3eUrU+tATLCMNDArZKmPAQBDGZQpQgD5mA0ORFYcL87h97ncyZYWYyc2bm7LPnfN+v17xmr3X2Oee39+zZv732w1qKCMzMzKrRlHcAZmZWXE4iZmZWNScRMzOrmpOImZlVzUnEzMyq1px3ALXW2toa8+fPzzsMM7PCWL9+fW9EzBnutYZLIvPnz6e7uzvvMMzMCkPSz0d6zaezzMysak4iZmZWNScRMzOrmpOImZlVzUmkxnp7e1m+fDnbtm3LO5Tc3XzzzZxwwgncdttteYeSO28XVlRTlkQkXSPpKUk/qag7QFKXpE3p9/6pXpIul9QjaYOkN1W8pyPNv0lSR0X9MZLuT++5XJKmalkmU6lUYsOGDZRKpbxDyd1nPvMZAC655JKcI8mftwsrqqlsiXwNOHVI3fnALRGxELgllQHagYXp52zgi5AlHWAFcCywBFhRTjxpnj+peN/Q76o7vb29dHZ2EhF0dnY29FHnzTffzM6dOwHYuXNnQ7dGvF1YkU1ZEomI24Gnh1SfAZQPtUrAOyvqvx6ZHwOzJR0EvA3oioinI+IZoAs4Nb22b0T8OLK+7L9e8Vl1q1QqUe56v7+/v6GPOsutkLJGbo14u7Aiq/U1kbkR8XiafgKYm6YPBh6tmG9Lqhutfssw9cOSdLakbkndW7dundgSTEBXVxd9fX0A9PX1cdNNN+UWS97KrZCRyo3E24UVWW4X1lMLoiYjYkXE1RGxOCIWz5kz7JP7NdHW1kZLSwsALS0tLFu2LLdY8tbc3DxquZF4u7Aiq3USeTKdiiL9firVPwYcUjHfvFQ3Wv28YerrWkdHB+Xr/01NTXR0dOzmHdPXpz71qUHlCy+8MKdI8uftwoqs1klkNVD+D+kArquof3+6S+s44Nl02utGYJmk/dMF9WXAjem15yQdl+7Ken/FZ9Wt1tZW2tvbkUR7ezsHHnhg3iHl5pRTTtnV+mhubmbp0qU5R5QfbxdWZFN5i+83gB8BR0jaIuks4LNAm6RNwCmpDHAD8DDQA3wJ+BBARDwNXALclX4uTnWkeb6c3vNfQOdULctk6ujoYNGiRT7aZKA10sitkDJvF1ZUKt8V0igWL14c7sXXzGzsJK2PiMXDveYn1s3MrGpOImZmVjUnETMzq5qTiJmZVc1JxMzMquYkYmZmVXMSMTOzqjmJmJlZ1ZxEzMysak4iZmZWNScRMzOrmpOImZlVzUnEzMyq5iRiZmZVcxIxM7OqOYmYmVnVnETMzKxqTiJmZlY1JxEzM6uak4iZmVXNScRy09vby/Lly9m2bVveoZhZlZxELDelUokNGzZQKpXyDsXMquQkYrno7e2ls7OTiKCzs9OtEbOCchKxXJRKJSICgP7+frdGzArKScRy0dXVRV9fHwB9fX3cdNNNOUdkZtVwErFctLW10dLSAkBLSwvLli3LOSIzq4aTiOWio6MDSQA0NTXR0dGRc0RmVg0nEctFa2sr7e3tSKK9vZ0DDzww75DMrArNeQdgjaujo4PNmze7FWJWYE4ilpvW1lauuOKKvMMwswnw6awa81PaZjad5JJEJH1U0gOSfiLpG5L2knSopDsl9Uj6lqQ90rx7pnJPen1+xed8MtX/TNLb8liW8fJT2mY2ndQ8iUg6GDgXWBwRRwEzgPcAlwKfj4gFwDPAWektZwHPpPrPp/mQdGR63+uBU4EvSJpRy2UZLz+lbWbTTV6ns5qBmZKagb2Bx4GTge+k10vAO9P0GalMev2tyu4NPQP4ZkS8EBGPAD3AkhrFXxU/pW1m003Nk0hEPAb8HfALsuTxLLAe+FVE7EyzbQEOTtMHA4+m9+5M8x9YWT/MewaRdLakbkndW7dundwFGgc/pW1m000ep7P2J2tFHAq8CtiH7HTUlImIqyNicUQsnjNnzlR+1aj8lLaZTTd5nM46BXgkIrZGRB/wPeB4YHY6vQUwD3gsTT8GHAKQXt8P2FZZP8x76pKf0h7Md6qZFV8eSeQXwHGS9k7XNt4KPAjcBrw7zdMBXJemV6cy6fVbI7uwsBp4T7p761BgIbCuRstQFT+lPZjvVDMrvjyuidxJdoH8buD+FMPVwCeAj0nqIbvm8ZX0lq8AB6b6jwHnp895APgXsgT0A+DDEfFSDRelKh0dHSxatMitEN+pZjYtqHy3UKNYvHhxdHd35x1Gw/vc5z7HDTfcQF9fHy0tLbz97W/nYx/7WN5hmdkwJK2PiMXDveYn1mvM1wEyvlPNbHpwEqkxXwfItLW17brJQJLvVDMrKCeRGvJ1gAGnnXbargcvI4LTTz8954jMrBpOIjXkJ9YHXH/99YNaIqtXr845IjOrhpNIDfk6wICurq5BLZFGXhdmReYkUkN+Yn2A14XZ9OAkUkN+Yn2A14XZ9OAkUkN+Yn2A14XZ9ODhcWvM44oP8LowKz4/sW5mZqPyE+tmZjYlnETMzKxqTiJmZlY1JxEzM6uak4jlxj0amxWfk4jlxj0amxWfk4jlwj0am00PTiKWC/dobDY9OIlYLtyjsdn04CRiuXAvvmbTg5NIjfmOpMzQ/rLcf5ZZMTmJ1JjvSMq0trayxx57ALDHHnu4F1+zgnISqSHfkTRg48aN7NixA4AdO3bQ09OTc0RmVg0nkRryHUkDLrrookHlFStW5BSJmU2Ek0gN+Y6kAY8++uioZTMrBieRGvIdSWY23TiJ1JDHFR9w0kknDSovXbo0n0DMbEKcRGrI44oPOPfcc0ctm1kxOInUWEdHB4sWLWroVghkCbXcGlm6dGlDJ1SzInMSqbHW1lauuOIK7zSBd7zjHTQ1NXH66afnHYqZVSmXJCJptqTvSHpI0k8l/YakAyR1SdqUfu+f5pWkyyX1SNog6U0Vn9OR5t8kqbEP7QvoyiuvpL+/n8suuyzvUMysSnm1RC4DfhARrwPeCPwUOB+4JSIWArekMkA7sDD9nA18EUDSAcAK4FhgCbCinHis/m3cuJHNmzcDsHnzZj9saFZQNU8ikvYDTgC+AhARL0bEr4AzgPLTdyXgnWn6DODrkfkxMFvSQcDbgK6IeDoingG6gFNruCg2AatWrRpUvvjii3OKxMwmIo+WyKHAVuCrku6R9GVJ+wBzI+LxNM8TwNw0fTBQ+STallQ3Uv3LSDpbUrek7q1bt07ioli1yq2QkcpmVgx5JJFm4E3AFyPi14EdDJy6AiCyvkFisr4wIq6OiMURsXjOnDmT9bE2AfPnzx+1bGbFkEcS2QJsiYg7U/k7ZEnlyXSaivT7qfT6Y8AhFe+fl+pGqrcCuOCCCwaVP/3pT+cUiZlNRM2TSEQ8ATwq6YhU9VbgQWA1UL7DqgO4Lk2vBt6f7tI6Dng2nfa6EVgmaf90QX1ZqrMCOPzww3e1PubPn8+CBQvyDcjMqpLX3VnLgWslbQCOBj4DfBZok7QJOCWVAW4AHgZ6gC8BHwKIiKeBS4C70s/Fqc4K4oILLmCfffZxK8SswFTumrxRLF68OLq7u/MOw8ysMCStj4jFw73mJ9bNzKxqTiJmZlY1JxEzM6uak4iZmVVtzElE0msknZKmZ0p6xdSFZWZmRTCmJCLpT8geCrwqVc0D/m2qgrLG0Nvby/Lly9m2bVveoZhZlcbaEvkwcDzwHEBEbAL+11QFZY2hVCqxYcMGSqXS7mc2s7o01iTyQkS8WC5IamYS+7ayxtPb20tnZycRQWdnp1sjZgU11iSyVtKngJmS2oBvA9dPXVg23ZVKJfr7+wF46aWX3BoxK6ixJpHzybpvvx/4IFlXJBeM+g6zUXR1dbFz504Adu7cyU033ZRzRGZWjbEmkZnANRHxexHxbuCaVGfjtG7dOk466STWr1+fdyi5estb3jKofMIJJ+QUidUb33BRLGNNIrcwOGnMBG6e/HCmv5UrV9Lf38+FF16Ydyhmdck3XBTLWJPIXhGxvVxI03tPTUjT17p169i+PVuN27dvb+jWyNq1aweV16xZk08gVld8w0XxjDWJ7JD0pnJB0jHA81MT0vS1cuXKQeVGbo00NzePWrbGVCqVKPcs3t/f79ZIAYw1iXwE+LakOyT9EPgWcM7UhTU9lVshI5UbideFDaerq4u+vj4A+vr6fMNFAYwpiUTEXcDrgD8D/hT4tYho3HMxVZo1a9ao5UbiMdZtOG1tbbS0tADQ0tLCsmXLco7IdmfUJCLp5PT7d4DTgMPTz2mpzsZh6OmsSy65JJ9A6oDHWLfhdHR0IAmApqYmOjo6dvMOy9vuWiInpt+nDfPzjimMa1pasmTJrtbHrFmzOOaYY3KOKD8eY92G09raSnt7O5Job2/nwAMPzDsk241Rk0hErJDUBHRGxAeG/PxRjWKcVlauXElTU1NDt0LKPMa6Daejo4NFixa5FVIQYxpjXVL3SOPrFo3HWDczG5/JGGP9Zkkfl3SIpAPKP5MYY8PYuHEj7e3t9PT05B2KmdmEjTWJ/AHwIWAt0F3xY+O0atUqduzYwcUXX5x3KGZmEzbWJHIk8I/AfcC9wBXA66cqqOlq48aNbN68GYDNmze7NWJmhTfWJFICfg24nCyBHJnqbBxWrVo1qOzWiJkV3Vj7mjgqIo6sKN8m6cGpCGg6K7dCRiqbmRXNWFsid0s6rlyQdCy+JjJufkrbzKabsSaRY4D/lLRZ0mbgR8CbJd0vacOURTfN+CltM5tuxppETgUOJXuC/cQ0fSrZU+unTU1o08/hhx++q7fa5ubmhn9K24MPmRXfWDtg/PloP1Md5HSxcePGQUPCNvrdWVdddRX33XcfV111Vd6hmFmVxtoSsUngu7MG9Pb20tXVBcBNN93k1ohZQTmJ1JDvzhpw1VVX0d/fD2SDD7k1YlZMuSURSTMk3SPp+6l8qKQ7JfVI+pakPVL9nqnck16fX/EZn0z1P5P0tnyWZOx8d9aAm2++eVC53Coxs2LJsyVyHvDTivKlwOcjYgHwDHBWqj8LeCbVfz7Nh6QjgfeQPTl/KvAFSTNqFHtVzjln8GCQ5513Xk6RmJlNjlySiKR5wNuBL6eygJOB76RZSsA70/QZDDwd/x3grWn+M4BvRsQLEfEI0AMsqc0SVOeOO+4YVF67dm1OkeRvr732GrVsZsWQV0vkH4D/A/Sn8oHAryJiZypvAQ5O0wcDjwKk159N8++qH+Y9g0g6W1K3pO6tW7dO5nKMy9BTNo08fvSOHTtGLZtZMdQ8iUh6B/BULcdoj4irI2JxRCyeM2dOrb72ZTx+9ACPN282PeTREjkeOD09+f5NstNYlwGzJZX78poHPJamHwMOAUiv7wdsq6wf5j11yeNHD+jr6xu1bGbFUPMkEhGfjIh5ETGf7ML4rRHxPuA24N1ptg7gujS9OpVJr98a2XCMq4H3pLu3DgUWAutqtBhV8fjRA4YueyOvC7MiG2svvrXwCeCbklYB9wBfSfVfAf6fpB7gabLEQ0Q8IOlfgAeBncCHI+Kl2oc9Ph0dHWzevLmhWyEAv/zlL0ctm1kxjGmM9enEY6zXhxNOOOFldbfffnsOkZjZ7kzGGOtmk2ru3Lmjls2sGJxErC6Ubzgws2JxErFcPPnkk4PKTzzxRE6RmNlEOImYmVnVnEQsF01NTaOWzawY/J9ruWhraxtUbuSn982KzEnEcvHBD35w17SkQWUzKw4nEctFa2sr++yzDwB77723n1g3KygnEcvFxo0bd/Xcu2PHjoYfb96sqJxELBceb95senASqbHe3l6WL1/Otm3b8g4lVx5v3mx6cBKpsVKpxIYNGyiVSrufeRrzePNm04OTSA319vbS2dlJRNDZ2dnQrZF99913UPmAAw7IKRIzmwgnkRoqlUqUe03u7+9v6NbIhg0bBpXvvvvunCIxs4lwEqmhrq6uXSP49fX1NfQY62Y2PTiJ1JDHWDez6cZJpIY8xrqZTTdOIjXU2trK0qVLAVi6dGlDP6U9dPwQjydiVkxOIpaLocMyN9owzUP5+SErKieRGurt7eXWW28F4NZbb/UOw3bx80NWVE4iNVQqlXbdnfXiiy829A7D44kM8PNDNpIitFAb9z83B0Nv6b3xxhtziiR/Bx988KjlRuLnh2wkRWihOonU0P777z9quZE89thjo5YbiZ8fsuEUpYXqJFJDv/zlL0ctN5L+/v5Ry42kra2N5uZmAJqbm/38kAHFaaE6iZjlrKOjY1cS7e/v9/NDBhSnheokUkOHHHLIqGUzs7Ki9HDhJFJDK1asGFS+6KKLcookf37YcECpVNp1d1pTU1Pdnraw2ipKDxdOIjV0+OGHM3fuXADmzp3LggULco4oP6985StHLTeSrq4udu7cCcDOnTvr9rSF1VZrayvt7e1Ior29vW57uHASqbHKI85G9vjjj49abiRFOW1htdfR0cGiRYvqthUCTiI1tXHjxl07y8cff5yenp6cI7J60NHRMajbl3reYVhttba2csUVV9RtKwRySCKSDpF0m6QHJT0g6bxUf4CkLkmb0u/9U70kXS6pR9IGSW+q+KyONP8mSXX/n7dq1apB5YsvvjinSPLnayIDWltb2WuvvQDYc88963qHYTZUHi2RncCfR8SRwHHAhyUdCZwP3BIRC4FbUhmgHViYfs4GvghZ0gFWAMcCS4AV5cRTrzZv3jxquZGUT9+MVG4kGzduZPv27QBs377dLVQrlJonkYh4PCLuTtP/DfwUOBg4AyjfllIC3pmmzwC+HpkfA7MlHQS8DeiKiKcj4hmgCzi1hotiE/Diiy+OWm4kbqFakeV6TUTSfODXgTuBuRFRvrr6BDA3TR8MPFrxti2pbqT64b7nbEndkrq3bt06afGbTQa3UK3IcksikmYB3wU+EhHPVb4W2VXGSRtgIiKujojFEbF4zpw5k/WxZpNi/vz5o5bN6lkuSURSC1kCuTYivpeqn0ynqUi/n0r1jwGVj3bPS3Uj1det973vfYPKvgvHAM4555xB5fPOOy+nSMzGL4+7swR8BfhpRPx9xUurgfJetQO4rqL+/ekureOAZ9NprxuBZZL2TxfUl6W6uvXQQw8NKj/wwAM5RWL15I477hhUXrt2bU6RmI1fHi2R44E/BE6WdG/6+W3gs0CbpE3AKakMcAPwMNADfAn4EEBEPA1cAtyVfi5OdXVr/fr1g8rd3d05RWL1pKura1DZT6xbkTTX+gsj4ofASA8FvHWY+QP48AifdQ1wzeRFZ1Z7bW1t3HDDDfT19fmJdSscP7FulrPKruAjwtfKrFCcRMxy1traOuiJfT+xbkXiJGKWs3Xr1g3qxXfotTOzeuYkYpazlStXDipfeOGF+QRiVgUnEbOclfvNGqlsVs+cRMxyNmvWrFHLjaa3t5fly5ezbdu2vEOxMXASMcvZ0NNZl1xyST6B1IlSqcSGDRs8THBBOImY5ey1r33toHIj953V29tLZ2cnEUFnZ6dbIwXgJGKWs1KpNGjY5EY+Ai+VSrtGeezv72/odVEUTiJmOevq6tr1sGF/f39Dd3vS1dVFX18fAH19fQ29LorCScQsZ21tbYNaIo3c7UlbWxvNzVlvTM3NzQ29LqAYNxk4iZjlrLLbk/7+/obu9sTrYrAi3GTgJGKWs4cffnhQ2SMbGhTnJgMnEbOc+Yn1Ab7JYEBRbjJwEjHLmZ9YH9DV1TWoH7FGvrBelJsMnETMrG60tbXt6tFYUkNfWC/KunASMbO6cdppp+06hRMRnH766TlHlJ+irAsnETOrG9dff/2g8urVq3OKJH9FWRdOImY523PPPUctN5Kh5/1vvPHGnCLJX1dX16Cyr4mY2bBeeOGFUcuNZO7cuaOWG8mSJUsGlY899ticIhmdk4iZ1Y0nnnhi1HIjefDBB0ct1wsnETOrG6985StHLTeSp556alD5ySefzCmS0TmJmFndGLqjrNcdpw1wEjGzunHCCScMKp944ok5RZK/8pP7I5XrRX1GZWYNyTcZDCh3RDlSuV405x2ATQ+XX345PT09E/qMc889d0zzLViwYMzzWrH88Ic/HFS+4447corExsotETOrG+V+s0YqW/1xS2QCfPQ9YLyxDT33Ddn6NLNicUvEzMyqpnIHX41i8eLF0d3dnct3D3f0ffvtt+cQycgmo3U1Vvfee++u6aOPPnrKv69WrbnxrsPK9VA21vVR7y1Ur4sBRV4XktZHxOLhXvPpLGq74xxqqjf68W5Ma9as4enerew5oxYHF0q/g5/df/eUftMLL4ktW7bU9U7GrIgKn0QknQpcBswAvhwRnx3vZ6xZs4atvdtgxhSvjhkt8FLfoPI99z8wdd/30s663nE2pxzSUqcnVfM8uBirnp6eqv6+4z24qNW6aGlp2TUQU7k8VtNtXUxErdYFFDyJSJoB/CPQBmwB7pK0OiLqs5OZAjjppJNq9g+yadMmABYuXFiT71uwYMG45l+zZg29vb1TFM3ohjuVMZnGe3CR17ro6+vzuqhQb+sCCp5EgCVAT0Q8DCDpm8AZwLiSSLU7zi1btvD888+P6z3PP/8SADNnzhzX+2bOnMm8efPG9R4Y/46z2lZLLY/OanXue/bs2eP++0L2gNx4HwyrnH88TyY3NTVV1XX87Nmzxz2/18XA/F4XA4qeRA4GHq0obwFe1l+ypLOBswFe/epXv+xDarnj3LJlC8C4E0K9XzSsxngTaa1dc801Vb2vmu2i8ghz0aJFY35frbaLWq6LX/ziFzz33HMcccQR4zqdNR3XRXm7mDFjBm94wxvG/L5a7i8KfXeWpHcDp0bEH6fyHwLHRsQ5I70nz7uzzMyKaLS7s+r0kuaYPQYcUlGel+rMzKwGip5E7gIWSjpU0h7Ae4D6HIjYzGwaKvQ1kYjYKekc4EayW3yviYgpvGfWzMwqFTqJAETEDcANecdhZtaIin46y8zMcuQkYmZmVXMSMTOzqjmJmJlZ1Qr9sGE1JG0Ffp5zGK1APp3v1B+viwFeFwO8LgbUw7p4TUTMGe6Fhksi9UBS90hPfzYar4sBXhcDvC4G1Pu68OksMzOrmpOImZlVzUkkH1fnHUAd8boY4HUxwOtiQF2vC18TMTOzqrklYmZmVXMSMTOzqjmJ7IaklyTdK+k+SXdL+s1J+twzJV05TP1KSR+fjO+YCEkh6Z8qys2Stkr6/gQ+c/s45z+pcn1LeqekI6v9/qkiaZ6k6yRtkvSwpCsljX9s0joi6S8lPSBpQ9r+j031H5G09xjeP6b5xhjLSaNtd5LmS/pJLb5rgp89JfuSvDmJ7N7zEXF0RLwR+CTw10NnkFT43pCHsQM4SlJ5DNs2aj/g10lA5T/aO4G6SiKSBHwP+LeIWAgsBGYCf5NrYBMg6TeAdwBviohFwCkMDEP9EWAsyWGs8zWSabkvcRIZn32BZ2DXEcsdklYDD0raS9JXJd0v6R5JS9N8w9ZXkvR2ST+S1FpRd5ikuyvKC8tlSZslXZSOZu6X9LopWt4bgLen6fcC36iIZ0mK+R5J/ynpiFR/pqTvSfpBOjIftDOV9FfpSOzHkuamutMk3Zk+62ZJcyXNB/4U+Gg6ejsROB3421Q+TNKfSLorfd53y0e+kr4m6fIU18NpGOWpcjLwPxHxVYCIeAn4KPB+SedUtjYlfV/SSWl6WVp/d0v6tqRZqf4YSWslrZd0o6SDUv0aSZdKWidpo6S3pPrXp7p7U6th4SQs00FAb0S8kJapNyJ+Kelc4FXAbZJuS9//RUndqdVyUaobbr6Rlndc27KkE9Oy3pu2l1cMeX1++r+8u/JoP/2/rpH0HUkPSbo2HQAg6dRUdzfwO5Ow/saimn3JsP9bkl6Tyq2SmtJnLavRckBE+GeUH+Al4F7gIeBZ4JhUfxLZ0fqhqfznZINiAbwO+AWw1yj1ZwJXAu8C7gD2T/OsBD6epm8Djk7TnwGWp+nNFdMfAr48Bcu9HVgEfCfFe29a5u+n1/cFmtP0KcB30/SZwMPAful9PwcOSa8FcFqa/hvggjS9PwN3Cv4x8Lmh6yKVvwa8u6J8YMX0qop18jXg22QHSUcCPVO4fZwLfH6Y+nvIjsavrKj7flqHrcDtwD6p/hPAp4EW4D+BOan+Dyq2nTUV6+W3gZvT9BXA+9L0HsDMSVimWenvvRH4AnBixWubgdaK8gHp94wU46Kh8420vGPdlodsd9cDx1fE2QzMB36S6vYG9krTC4Huis94lmwI7SbgR8BvkW2jj6Z5BfxL+bumYFuZ6L7kTEb+3/pjsm3+L4Crpmp7H+6ncE2nHDwfEUfDrmb+1yUdlV5bFxGPpOnfIvuHJiIekvRz4PBR6iE7il0MLIuI54b57i8DH5D0MbIdypKK176Xfq9nio6eImJDahG8l5cP/LUfUEpHvkG2Ayy7JSKeBZD0IPAasn/UF8l2pOW429L0POBb6ah7D+ARxuYoSauA2WQ7lBsrXvu3iOgnO7KbO8bPq5XjyJLbf6SD4T3IdmpHAEcBXal+BvB4xfsq/+bz0/SPgL+UNA/4XkRsmmhwEbFd0jHAW4ClZH+b8yPia8PM/vuSzibbmR+UlmvDkHlGWt7hlmt32/J/AH8v6Vqy5d2SPrOsBbhS0tFkO+3DK15bFxFbACTdS7YOtwOPlNebsuuAZ+8mhmpNdF8CI/xvRcSXJf0eWev96CmKf1g+nTUOEfEjsqOqckdkOyb4kf8FvILBG3ql7wLtZOen10fEtorXXki/X2JqR6hcDfwdFaeykkuA2yLiKOA0siOjobENja8v0mHTkPoryI7Y3wB8cMhnjeZrwDnpfReNEsOgvcwkexA4prJC0r7AK4FtDP4fK8cnoCuy8+NHR8SREXFWqn+gov4NEVF5WuJlf/OI+Gey03zPAzdIOnkyFtkPqMkAAAYNSURBVCoiXoqINRGxAjgH+N2h80g6FPg48NbIrp38O8P/7UZa3hGXa5S4Pkt21D2TLCkNPf31UeBJ4I1kB2h7DPM9Y/quqTSBfcmwy5BO5c5L9bMmI8axchIZh7TBziDbOQx1B/C+NN/hwKuBn41SD1lz9HfJjkheP/QDI+J/yI6uvwh8dTKXZRyuAS6KiPuH1O/HwIX2Myf4HZWf1VFR/99kSXak8iuAxyW1kNZxDm4B9pb0fgBJM4DPkZ2qfAQ4Op2nPoSBluSPgeMlLUjv2SdtGz8D5qSjVCS1DLddVJL0WuDhiLgcuI7sFOSESDpiyLWVoxno+bryb7Av2c7v2dTaa694T+V8Iy1vNbEdFhH3R8SlwF1kp3sq7Qc8nlqhf0j2/zqah4D5kg5L5fdWE9d4VbkvGc2lwLVkp0W/NHmR7p6TyO7NLF/IA74FdER28XSoLwBNku5P850Z2YXJkeqBrLlKtsF8u2JDrnQt0A/cNKlLNUYRsSXtoIb6G+CvJd3DxI/oVpIt/3oGd3l9PfCutP7fAnwT+It0sfEw4ELgTrJTHA9NMIaqpJbVu4B3S9pEtlPoj4i/SnE9QtZauRy4O71nK1ni/YakDWSndl4XES8C7wYulXQf2fnz3d0G+vvAT9L2eRTw9UlYrFlkpyofTPEdSfY3gqwLjh9Iui0i7iO79vMQ8M9peRlmvmGXt8rYPiLpJ+lz+oDOIa9/AehI6+917OYIPx2onQ38e7qw/lSVcY3FRPclw1J208mbgUsj4lrgRUkfmIL4h//+gbMLVo+UPTOyX0RcmHcstnvpbqBvAO+KiLt3N79Z0TmJ1DFJ/wocBpwcEXkPSmNm9jJOImZmVjVfEzEzs6o5iZiZWdWcRMzMrGpOImZmVjUnEZv2JP1p+WHAUeYZtmv+9Nq4urAfR1wjfmc9fq7ZcNx3lk17EfF/845hKNV5l9+SmiNiZ95xWP1zS8QKR1l33z+V9CVlXZDfJGmmsu7hf6CsG/U7yv0qqWKgL0lv1sBAS3+rwYMZvUojd2H/+fRdt0iak+qOVtal/QZJ/ypp/1S/RtLiNN0qaXOaPlPSakm3knWXMuJ3Snqvsq7AfyLp0jHUf0BZF/HrgON3s/4OS3HfL2lVuaWl8XVJPlIX99uHW1c2fTmJWFEtBP4xIl4P/IqsD7KryboVP4asY8AvDPO+rwIfTL2pDu1y4miy3pLfAPyBsv6uAPYh61L89cBaYEWq/zrwidT54P0V9aN5E1l39ieO9J2SXkXWF9LJ6fU3KxvVcaT6g8g6oDyerAfY3Q3cdRlwWeq4cssw8Z0XEYcDHybr2eUNZH1KlSTtrnPMkdaVTVNOIlZUj0TEvWm63DX6b5L1wXUvcBVZ1+S7SJoNvCL1oApZf0+VbomIZ1N/SuVutiHru+xbafqfgN+StB8wOyLWpvoScMIY4u6KiKd3851vBtZExNZ0Suna9Nkj1R9bUf9iRawj+Q2ysSeGWwdDuyT/J9jVx1tll+Qjedm62s38VnB1fV7WbBRDu8SeC/yqPF7DJH3mSP8fu+vmYScDB2hDj9yHdghYN92TJ2Ppkrxy+WD0rvvdJcY055aITRfPAY8oG5gHZd5YOUNE/Ar4b0nHpqr3jPGzm8h61wX438AP08BAzygNU0vW7Xi5VbKZgTFGqhmadx1wYrqeMoPsVNLaUervTPUHKusW//d28/k/ZmB8kNHWwUhdkm9m+C7uYZh1NYbltQJzErHp5H3AWakb8AeAM4aZ5yzgS+mU1z5kw5Tuzg5gSboIfzJwcarvIBvzfQPZNYpy/d8Bf6asm/zW8S5ERDwOnE82PPJ9ZAOSXbeb+pVkXaz/B/DT3XzFR4CPpbgXMPI6GKlL8mG7uE9GWlc2TbkDRmsokmZFRPlupPOBgyLivJzDqillo+A9HxEh6T3AeyNiuIRbzWdvj4iajqxn+cr7/KtZrb1d0ifJtv2fM/FRGYvoGLJxyEV2Z9sf5RyPFZhbImbTlKS/5OXXR76dRl00mxROImZmVjVfWDczs6o5iZiZWdWcRMzMrGpOImZmVrX/D9vaueh6SKDQAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":["price의 outlier 때문에 해석하기가 어려움"],"metadata":{"id":"EHuKyzPwup0L"}},{"cell_type":"code","source":["sns.boxplot(x='room_type', y='price', data=df)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":298},"id":"sHo6vlf2uho3","executionInfo":{"status":"ok","timestamp":1641143541043,"user_tz":-540,"elapsed":695,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"ea7a0bf1-2df9-4618-e9bc-ed83e35c9c2f"},"execution_count":17,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f49b0a2cb90>"]},"metadata":{},"execution_count":17},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"izztXKpllMss"},"source":["## Step 3. 데이터 클리닝 "]},{"cell_type":"markdown","metadata":{"id":"KywGh9sjtYl9"},"source":["### 미기입, 오기입 데이터 확인"]},{"cell_type":"code","metadata":{"id":"TqXkwW8JDxhH","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1641143541044,"user_tz":-540,"elapsed":24,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"49fe2caa-1c58-42ba-8fca-5cd54d62a080"},"source":["df.columns"],"execution_count":18,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['host_id', 'neighbourhood_group', 'neighbourhood', 'room_type', 'price',\n","       'minimum_nights', 'number_of_reviews', 'last_review',\n","       'reviews_per_month', 'calculated_host_listings_count',\n","       'availability_365'],\n","      dtype='object')"]},"metadata":{},"execution_count":18}]},{"cell_type":"code","source":["# 미기입 데이터 확인\n","df.isna().sum()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ar0FCBrJvBGc","executionInfo":{"status":"ok","timestamp":1641143541045,"user_tz":-540,"elapsed":21,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"6dacb798-e1d5-4a02-dd2d-f1d47a73c31d"},"execution_count":19,"outputs":[{"output_type":"execute_result","data":{"text/plain":["host_id                               0\n","neighbourhood_group                   0\n","neighbourhood                         0\n","room_type                             0\n","price                                 0\n","minimum_nights                        0\n","number_of_reviews                     0\n","last_review                       10052\n","reviews_per_month                 10052\n","calculated_host_listings_count        0\n","availability_365                      0\n","dtype: int64"]},"metadata":{},"execution_count":19}]},{"cell_type":"markdown","source":["#### 범주형 데이터 과도한 클래스 개수를 줄여줌"],"metadata":{"id":"x9PBT9-nwFq7"}},{"cell_type":"code","source":["df['neighbourhood_group'].value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"1ccViqhzvFtL","executionInfo":{"status":"ok","timestamp":1641143541046,"user_tz":-540,"elapsed":18,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"ff184f0e-fe69-4c08-dc01-5ee39506ff02"},"execution_count":20,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Manhattan        21661\n","Brooklyn         20104\n","Queens            5666\n","Bronx             1091\n","Staten Island      373\n","Name: neighbourhood_group, dtype: int64"]},"metadata":{},"execution_count":20}]},{"cell_type":"code","source":["df['neighbourhood'].value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jJ07kZz3vyov","executionInfo":{"status":"ok","timestamp":1641143541048,"user_tz":-540,"elapsed":16,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"3b7aaf0d-dd1b-49bf-8ec9-5b6dcdc7b91b"},"execution_count":21,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Williamsburg          3920\n","Bedford-Stuyvesant    3714\n","Harlem                2658\n","Bushwick              2465\n","Upper West Side       1971\n","                      ... \n","Woodrow                  1\n","Rossville                1\n","Richmondtown             1\n","New Dorp                 1\n","Willowbrook              1\n","Name: neighbourhood, Length: 221, dtype: int64"]},"metadata":{},"execution_count":21}]},{"cell_type":"code","source":["neigh = df['neighbourhood'].value_counts()\n","plt.plot(range(len(neigh)), neigh)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":284},"id":"NO3gp5AavFm_","executionInfo":{"status":"ok","timestamp":1641143541605,"user_tz":-540,"elapsed":570,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"4eb4e110-36a1-486d-c62a-0fa4277f6315"},"execution_count":22,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[<matplotlib.lines.Line2D at 0x7f49af7b0190>]"]},"metadata":{},"execution_count":22},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["df['neighbourhood'] = df['neighbourhood'].apply(lambda s: s if str(s) not in neigh[50:] else 'others')"],"metadata":{"id":"8kUCg1Bovg8C","executionInfo":{"status":"ok","timestamp":1641143546833,"user_tz":-540,"elapsed":5231,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"execution_count":23,"outputs":[]},{"cell_type":"code","source":["df['neighbourhood'].value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"QByTVx62v5Uq","executionInfo":{"status":"ok","timestamp":1641143546833,"user_tz":-540,"elapsed":9,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"3bbcc0d2-a5c3-4688-c36e-535631c0da08"},"execution_count":24,"outputs":[{"output_type":"execute_result","data":{"text/plain":["others                       6248\n","Williamsburg                 3920\n","Bedford-Stuyvesant           3714\n","Harlem                       2658\n","Bushwick                     2465\n","Upper West Side              1971\n","Hell's Kitchen               1958\n","East Village                 1853\n","Upper East Side              1798\n","Crown Heights                1564\n","Midtown                      1545\n","East Harlem                  1117\n","Greenpoint                   1115\n","Chelsea                      1113\n","Lower East Side               911\n","Astoria                       900\n","Washington Heights            899\n","West Village                  768\n","Financial District            744\n","Flatbush                      621\n","Clinton Hill                  572\n","Long Island City              537\n","Prospect-Lefferts Gardens     535\n","Park Slope                    506\n","East Flatbush                 500\n","Fort Greene                   489\n","Murray Hill                   485\n","Kips Bay                      470\n","Flushing                      426\n","Ridgewood                     423\n","Greenwich Village             392\n","Sunset Park                   390\n","Chinatown                     368\n","Sunnyside                     363\n","SoHo                          358\n","Prospect Heights              357\n","Morningside Heights           346\n","Gramercy                      338\n","Ditmars Steinway              309\n","Theater District              288\n","South Slope                   284\n","Nolita                        253\n","Inwood                        252\n","Gowanus                       247\n","Elmhurst                      237\n","Woodside                      235\n","Carroll Gardens               233\n","Jamaica                       231\n","East New York                 218\n","Jackson Heights               186\n","East Elmhurst                 185\n","Name: neighbourhood, dtype: int64"]},"metadata":{},"execution_count":24}]},{"cell_type":"code","source":["df['room_type'].value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"C4VFZlnYv9cZ","executionInfo":{"status":"ok","timestamp":1641143546834,"user_tz":-540,"elapsed":8,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"0dacf8f3-3b86-4841-d7a1-416e7d87560d"},"execution_count":25,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Entire home/apt    25409\n","Private room       22326\n","Shared room         1160\n","Name: room_type, dtype: int64"]},"metadata":{},"execution_count":25}]},{"cell_type":"markdown","source":["#### 수치형 데이터 아웃라이어 확인"],"metadata":{"id":"rC9Mbi5HwOA6"}},{"cell_type":"code","source":["sns.rugplot(x='price', data=df, height=1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":297},"id":"AknNoByywQVj","executionInfo":{"status":"ok","timestamp":1641143551850,"user_tz":-540,"elapsed":5020,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"05f01135-8308-4c77-f3ce-d35e783bf2f2"},"execution_count":26,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f49af779c10>"]},"metadata":{},"execution_count":26},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAXwAAAEGCAYAAABmXi5tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAQbUlEQVR4nO3df5CdVX3H8ffHpIEWkR8SIQI1MKXaWFulCwPT1nZKVLAd8A+s0B/GVkvH1o6tf3TCMONM+Uul01pbqmTQlvoLlNqaQSyD0T/6S2RRRH5FAlKBAllpBQYLiHz7xz0bLutusrv3hpvseb9m7ux5znPuc865Z/PZu89z90mqCknSyve8SQ9AkvTcMPAlqRMGviR1wsCXpE4Y+JLUidWTHsBCjjjiiFq/fv2yn/+N+x4e32DmeF7C07v5dNOLDj6AnY8+sas88+gTFPCKow/ZNa6D1qzmyR88DcDLjjqYBx95nJ2PPsErjj7kWWWAm+97mLXtOEl4+YtfAMDtDzzKy446GOCHnnPXzGMcv/agXfsee+IHHL/2IB585HEAjnzBgTz4yOMc+YIDgcHr9aKDD3jWPGbbLFQefu5sv8OGx7A7s+2Gjz+876ADVu2qG+537vyHx7WYvhc7vvkMz3l4TPNtj9NyxrzQa7aY9uOy0LgX09co49mba7E3LfRvajFuuOGG71TV2vn2ZV/9WObU1FRNT08v+/nrN39ujKMZj7vf86vzjmu4fm4Zfnguw/Vz2+xp39zyQn3saVxznztbHrZQ/ULt5s5hMfOaW577dTH9Lsfu5j/KcZfS73Kes7dfl6Ue87lcp/3JKONOckNVTc23z1M6ktQJA1+SOmHgS1InDHxJ6oSBL0mdMPAlqRMGviR1wsCXpE4Y+JLUCQNfkjph4EtSJwx8SeqEgS9JnTDwJakTBr4kdcLAl6ROGPiS1AkDX5I6YeBLUifGEvhJTk+yPcmOJJvn2f+uJLcmuSnJtiQvGUe/kqTFGznwk6wCLgbOADYA5ybZMKfZ14CpqvoZ4ErgfaP2K0lamnG8wz8Z2FFVd1XVk8DlwFnDDarqS1X1vbb5ZeCYMfQrSVqCcQT+0cA9Q9v3trqFvBX4/Hw7kpyXZDrJ9MzMzBiGJkma9ZxetE3yW8AUcNF8+6tqS1VNVdXU2rVrn8uhSdKKt3oMx7gPOHZo+5hW9yxJNgIXAL9UVU+MoV9J0hKM4x3+9cAJSY5LsgY4B9g63CDJq4BLgDOraucY+pQkLdHIgV9VTwHvAK4BbgM+VVW3JLkwyZmt2UXA84FPJ7kxydYFDidJ2kvGcUqHqroauHpO3buHyhvH0Y8kafn8S1tJ6oSBL0mdMPAlqRMGviR1wsCXpE4Y+JLUCQNfkjph4EtSJwx8SeqEgS9JnTDwJakTBr4kdcLAl6ROGPiS1AkDX5I6YeBLUicMfEnqhIEvSZ0w8CWpEwa+JHXCwJekThj4ktQJA1+SOmHgS1InDHxJ6oSBL0mdMPAlqRMGviR1wsCXpE4Y+JLUCQNfkjph4EtSJwx8SerEWAI/yelJtifZkWTzPPtfneSrSZ5KcvY4+pQkLc3IgZ9kFXAxcAawATg3yYY5zb4NvAX4xKj9SZKWZ/UYjnEysKOq7gJIcjlwFnDrbIOqurvte3oM/UmSlmEcp3SOBu4Z2r631S1ZkvOSTCeZnpmZGcPQJEmz9qmLtlW1paqmqmpq7dq1kx6OJK0o4wj8+4Bjh7aPaXWSpH3IOAL/euCEJMclWQOcA2wdw3ElSWM0cuBX1VPAO4BrgNuAT1XVLUkuTHImQJKTktwLvBG4JMkto/YrSVqacXxKh6q6Grh6Tt27h8rXMzjVI0makH3qoq0kae8x8CWpEwa+JHXCwJekThj4ktQJA1+SOmHgS1InDHxJ6oSBL0mdMPAlqRMGviR1wsCXpE4Y+JLUCQNfkjph4EtSJwx8SeqEgS9JnTDwJakTBr4kdcLAl6ROGPiS1AkDX5I6YeBLUicMfEnqhIEvSZ0w8CWpEwa+JHXCwJekThj4ktQJA1+SOmHgS1InDHxJ6oSBL0mdMPAlqRNjCfwkpyfZnmRHks3z7D8gyRVt/3VJ1o+jX0nS4o0c+ElWARcDZwAbgHOTbJjT7K3A/1bVTwB/Cbx31H4lSUszjnf4JwM7ququqnoSuBw4a06bs4DLWvlK4LQkGUPfkqRFGkfgHw3cM7R9b6ubt01VPQU8DLxw7oGSnJdkOsn0zMzMGIYmSZq1T120raotVTVVVVNr166d9HAkaUUZR+DfBxw7tH1Mq5u3TZLVwCHAQ2PoW5K0SOMI/OuBE5Icl2QNcA6wdU6brcCmVj4b+GJV1Rj6liQt0upRD1BVTyV5B3ANsAr4SFXdkuRCYLqqtgIfBj6aZAfwPwx+KEiSnkMjBz5AVV0NXD2n7t1D5ceBN46jL0nS8uxTF20lSXuPgS9JnTDwJakTBr4kdcLAl6ROGPiS1AkDX5I6YeBLUicMfEnqhIEvSZ0w8CWpEwa+JHXCwJekThj4ktQJA1+SOmHgS1InDHxJ6oSBL0mdMPAlqRMGviR1wsCXpE4Y+JLUCQNfkjph4EtSJwx8SeqEgS9JnTDwJakTBr4kdcLAl6ROGPiS1AkDX5I6YeBLUicMfEnqhIEvSZ0YKfCTHJ7k2iR3tK+HLdDuX5J8N8lVo/QnSVq+Ud/hbwa2VdUJwLa2PZ+LgN8esS9J0ghGDfyzgMta+TLgDfM1qqptwKMj9iVJGsGogX9kVd3fyg8AR45ysCTnJZlOMj0zMzPi0CRJw1bvqUGSLwBHzbPrguGNqqokNcpgqmoLsAVgampqpGNJkp5tj4FfVRsX2pfkwSTrqur+JOuAnWMdnSRpbEY9pbMV2NTKm4DPjng8SdJeMmrgvwd4TZI7gI1tmyRTSS6dbZTkX4FPA6cluTfJ60bsV5K0RHs8pbM7VfUQcNo89dPA24a2f3GUfiRJo/MvbSWpEwa+JHXCwJekThj4ktQJA1+SOmHgS1InDHxJ6oSBL0mdMPAlqRMGviR1wsCXpE4Y+JLUCQNfkjph4EtSJwx8SeqEgS9JnTDwJakTBr4kdcLAl6ROGPiS1AkDX5I6YeBLUicMfEnqhIEvSZ0w8CWpEwa+JHXCwJekThj4ktQJA1+SOmHgS1InDHxJ6oSBL0mdMPAlqRMjBX6Sw5Ncm+SO9vWwedq8Msl/JrklyU1J3jRKn5Kk5Rn1Hf5mYFtVnQBsa9tzfQ94c1W9HDgdeH+SQ0fsV5K0RKMG/lnAZa18GfCGuQ2q6ptVdUcr/zewE1g7Yr+SpCUaNfCPrKr7W/kB4MjdNU5yMrAGuHOB/eclmU4yPTMzM+LQJEnDVu+pQZIvAEfNs+uC4Y2qqiS1m+OsAz4KbKqqp+drU1VbgC0AU1NTCx5LkrR0ewz8qtq40L4kDyZZV1X3t0DfuUC7FwCfAy6oqi8ve7SSpGUb9ZTOVmBTK28CPju3QZI1wD8B/1BVV47YnyRpmUYN/PcAr0lyB7CxbZNkKsmlrc2vA68G3pLkxvZ45Yj9SpKWaI+ndHanqh4CTpunfhp4Wyt/DPjYKP1IkkbnX9pKUicMfEnqhIEvSZ0w8CWpEwa+JHXCwJekThj4ktQJA1+SOmHgS1InDHxJ6oSBL0mdMPAlqRMGviR1wsCXpE4Y+JLUCQNfkjph4EtSJwx8SepEqmrSY5hXkhngv0Y4xBHAd8Y0nP1Fb3Pubb7gnHsxypxfUlVr59uxzwb+qJJMV9XUpMfxXOptzr3NF5xzL/bWnD2lI0mdMPAlqRMrOfC3THoAE9DbnHubLzjnXuyVOa/Yc/iSpGdbye/wJUlDDHxJ6sSKC/wkpyfZnmRHks2THs8okhyb5EtJbk1yS5J3tvrDk1yb5I729bBWnyQfaHO/KcmJQ8fa1NrfkWTTpOa0GElWJflakqva9nFJrmvzuiLJmlZ/QNve0favHzrG+a1+e5LXTWYmi5Pk0CRXJrk9yW1JTu1gjf+kfU/fnOSTSQ5caeuc5CNJdia5eahubOua5OeSfKM95wNJssdBVdWKeQCrgDuB44E1wNeBDZMe1wjzWQec2MoHA98ENgDvAza3+s3Ae1v59cDngQCnANe1+sOBu9rXw1r5sEnPbzfzfhfwCeCqtv0p4JxW/hDw9lb+A+BDrXwOcEUrb2hrfwBwXPueWDXpee1mvpcBb2vlNcChK3mNgaOBbwE/OrS+b1lp6wy8GjgRuHmobmzrCnyltU177hl7HNOkX5Qxv8CnAtcMbZ8PnD/pcY1xfp8FXgNsB9a1unXA9la+BDh3qP32tv9c4JKh+me125cewDHANuBXgKvaN/N3gNVz1xi4Bji1lVe3dpm77sPt9rUHcEgLv8ypX8lrfDRwTwux1W2dX7cS1xlYPyfwx7Kubd/tQ/XParfQY6Wd0pn9Rpp1b6vb77VfY18FXAccWVX3t10PAEe28kLz359el/cDfwo83bZfCHy3qp5q28Nj3zWvtv/h1n5/mu9xwAzwd+001qVJDmIFr3FV3Qf8OfBt4H4G63YDK3udZ41rXY9u5bn1u7XSAn9FSvJ84B+BP66qR4b31eDH+4r4bG2SXwN2VtUNkx7Lc2g1g1/7P1hVrwIeY/Cr/i4raY0B2nnrsxj8sHsxcBBw+kQHNQGTWNeVFvj3AccObR/T6vZbSX6EQdh/vKo+06ofTLKu7V8H7Gz1C81/f3ldfh44M8ndwOUMTuv8FXBoktWtzfDYd82r7T8EeIj9Z74weGd2b1Vd17avZPADYKWuMcBG4FtVNVNV3wc+w2DtV/I6zxrXut7XynPrd2ulBf71wAntav8aBhd4tk54TMvWrrp/GLitqv5iaNdWYPZq/SYG5/Zn69/crvifAjzcfn28BnhtksPau6vXtrp9SlWdX1XHVNV6Bmv3xar6TeBLwNmt2dz5zr4OZ7f21erPaZ/uOA44gcEFrn1OVT0A3JPkpa3qNOBWVugaN98GTknyY+17fHbOK3adh4xlXdu+R5Kc0l7DNw8da2GTvqixFy6SvJ7Bp1nuBC6Y9HhGnMsvMPiV7ybgxvZ4PYPzl9uAO4AvAIe39gEubnP/BjA1dKzfBXa0x+9Mem6LmPsv88yndI5n8A95B/Bp4IBWf2Db3tH2Hz/0/Ava67CdRXx6YcJzfSUw3db5nxl8GmNFrzHwZ8DtwM3ARxl80mZFrTPwSQbXKL7P4De5t45zXYGp9vrdCfwNcy78z/fw1gqS1ImVdkpHkrQAA1+SOmHgS1InDHxJ6oSBL0mdMPClJUhyYZKNkx6HtBx+LFNapCSrquoHkx6HtFy+w5cY3Jyu3Y/+4+2e9Fe2vwS9O8l7k3wVeGOSv09ydnvOSUn+I8nXk3wlycEZ3Mv/oiTXt/ua//6EpybtYuBLz3gp8LdV9VPAIwzuww7wUFWdWFWXzzZst+64AnhnVf0sg/vD/B+Dv6Z8uKpOAk4Cfq/92b80cQa+9Ix7qurfW/ljDG5tAYNgn+ulwP1VdT1AVT1Sg1v3vpbBPVFuZHAr6xcyuMeLNHGr99xE6sbcC1qz248t4RgB/qiq9tUbl6ljvsOXnvHjSU5t5d8A/m03bbcD65KcBNDO369mcHfDt7fbWpPkJ9t/aCJNnIEvPWM78IdJbmNwx8oPLtSwqp4E3gT8dZKvA9cyuKvjpQxu9fvV9p9XX4K/SWsf4ccyJXb9F5JXVdVPT3go0l7jO3xJ6oTv8CWpE77Dl6ROGPiS1AkDX5I6YeBLUicMfEnqxP8D4onldeoUY0wAAAAASUVORK5CYII=\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["# 상위 5%\n","print(df['price'].quantile(0.95))\n","# 하위 0.5%\n","print(df['price'].quantile(0.005)) # price min 값이 0이므로 너무 낮은 하위값을 제거"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"GX28INYIwVSj","executionInfo":{"status":"ok","timestamp":1641143551851,"user_tz":-540,"elapsed":7,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"56b2553a-7865-46d2-c54e-3c2d0dd0b65d"},"execution_count":27,"outputs":[{"output_type":"stream","name":"stdout","text":["355.0\n","26.0\n"]}]},{"cell_type":"code","source":["sns.rugplot(x='minimum_nights', data=df, height=1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":298},"id":"KWzPCCAswVNP","executionInfo":{"status":"ok","timestamp":1641143555119,"user_tz":-540,"elapsed":3272,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"0f4ac3af-37e2-49fb-9ec5-2fb60e517584"},"execution_count":28,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f49afad7210>"]},"metadata":{},"execution_count":28},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["print(df['minimum_nights'].quantile(0.98))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9i-ZsAUzwuod","executionInfo":{"status":"ok","timestamp":1641143555119,"user_tz":-540,"elapsed":6,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"864ba831-b237-46cd-e625-cefdebd2b274"},"execution_count":29,"outputs":[{"output_type":"stream","name":"stdout","text":["30.0\n"]}]},{"cell_type":"code","source":["sns.rugplot(x='availability_365', data=df, height=1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":298},"id":"DFgNRBlew302","executionInfo":{"status":"ok","timestamp":1641143558859,"user_tz":-540,"elapsed":3744,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"ccaa14d9-8f26-4243-95a3-91d7849b276b"},"execution_count":30,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f49ac3f2090>"]},"metadata":{},"execution_count":30},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["print(df['availability_365'].quantile(0.3))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"OYO-QF9ww5xC","executionInfo":{"status":"ok","timestamp":1641143558861,"user_tz":-540,"elapsed":25,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"3a081427-4995-4f84-f44e-71f96121a344"},"execution_count":31,"outputs":[{"output_type":"stream","name":"stdout","text":["0.0\n"]}]},{"cell_type":"markdown","source":["0인지 아닌지 표기하는 카테고리컬 데이터를 만들어주어야 할 것같음"],"metadata":{"id":"lqmdvAzFxIyN"}},{"cell_type":"markdown","metadata":{"id":"CXLd43EZ9EgS"},"source":["### 아웃라이어를 제거하고 통계 재분석"]},{"cell_type":"code","metadata":{"id":"8HbUtvqs9C-C","executionInfo":{"status":"ok","timestamp":1641143558862,"user_tz":-540,"elapsed":22,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"source":["p1 = df['price'].quantile(0.95)\n","p2 = df['price'].quantile(0.005)\n","\n","df = df[(df['price'] < p1) & (df['price'] > p2)]"],"execution_count":32,"outputs":[]},{"cell_type":"code","source":["df['price'].hist()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":284},"id":"GgybCLzkxXcS","executionInfo":{"status":"ok","timestamp":1641143558863,"user_tz":-540,"elapsed":23,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"19ff56af-7b3f-4a77-a6c4-341e51c17004"},"execution_count":33,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f49aaa45890>"]},"metadata":{},"execution_count":33},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["mn1 = df['minimum_nights'].quantile(0.98)\n","\n","df = df[df['minimum_nights'] < mn1]"],"metadata":{"id":"6uaRb9bsxaw5","executionInfo":{"status":"ok","timestamp":1641143560423,"user_tz":-540,"elapsed":5,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"execution_count":34,"outputs":[]},{"cell_type":"code","source":["df['minimum_nights'].hist()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":284},"id":"dzLmf1tQxzAF","executionInfo":{"status":"ok","timestamp":1641143562754,"user_tz":-540,"elapsed":858,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"45773284-5452-4c39-86d3-c7a7df6fe16b"},"execution_count":35,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f49aa945b50>"]},"metadata":{},"execution_count":35},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["# availabiltiy 0 은 따로 카테고리컬 데이터로 처리\n","df['is_avail_zero'] = df['availability_365'].apply(lambda x: 'Zero' if x == 0 else 'Nonzero')"],"metadata":{"id":"tUNeT0enyAwM","executionInfo":{"status":"ok","timestamp":1641143671466,"user_tz":-540,"elapsed":535,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"execution_count":36,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"2Z62otW9lgtX"},"source":["### 미기입 데이터 처리"]},{"cell_type":"code","metadata":{"id":"NW-QEym6lgtX","executionInfo":{"status":"ok","timestamp":1641143792897,"user_tz":-540,"elapsed":408,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"source":["# review_per_month 가 None인 값을 따로 카테고리컬 데이터로 처리\n","df['review_exists'] = df['reviews_per_month'].isna().apply(lambda x: 'No' if x is True else 'Yes')"],"execution_count":37,"outputs":[]},{"cell_type":"code","source":["df.fillna(0, inplace=True)"],"metadata":{"id":"Ad1_ORkIyvqo","executionInfo":{"status":"ok","timestamp":1641143805503,"user_tz":-540,"elapsed":410,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"execution_count":38,"outputs":[]},{"cell_type":"code","source":["df.isna().sum()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jxZ2r9X6yykW","executionInfo":{"status":"ok","timestamp":1641143813019,"user_tz":-540,"elapsed":481,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"1c018765-301b-422e-c00e-1b79c5071276"},"execution_count":39,"outputs":[{"output_type":"execute_result","data":{"text/plain":["host_id                           0\n","neighbourhood_group               0\n","neighbourhood                     0\n","room_type                         0\n","price                             0\n","minimum_nights                    0\n","number_of_reviews                 0\n","last_review                       0\n","reviews_per_month                 0\n","calculated_host_listings_count    0\n","availability_365                  0\n","is_avail_zero                     0\n","review_exists                     0\n","dtype: int64"]},"metadata":{},"execution_count":39}]},{"cell_type":"markdown","metadata":{"id":"FRfd7ABjepBS"},"source":["## Step 4. 모델 학습을 위한 데이터 전처리 "]},{"cell_type":"markdown","metadata":{"id":"sWIF67-8lr4C"},"source":["### get_dummies를 이용한 범주형 데이터 전처리"]},{"cell_type":"code","metadata":{"id":"wVmEa1ChlrTc","executionInfo":{"status":"ok","timestamp":1641143874207,"user_tz":-540,"elapsed":415,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"source":["X_cat = df[['neighbourhood_group', 'neighbourhood', 'room_type', 'is_avail_zero', 'review_exists']]\n","X_cat = pd.get_dummies(X_cat)"],"execution_count":40,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"Dev2yLeMta85"},"source":["### StandardScaler를 이용해 수치형 데이터 표준화\n"]},{"cell_type":"code","metadata":{"id":"_k_SDCh5xMgD","executionInfo":{"status":"ok","timestamp":1641143891863,"user_tz":-540,"elapsed":418,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"source":["from sklearn.preprocessing import StandardScaler"],"execution_count":42,"outputs":[]},{"cell_type":"code","metadata":{"id":"W3EO22NCE3wG","executionInfo":{"status":"ok","timestamp":1641144015903,"user_tz":-540,"elapsed":429,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"source":["# StandardScaler를 이용해 수치형 데이터를 표준화\n","scaler = StandardScaler()\n","X_num = df.drop(['neighbourhood_group', 'neighbourhood', 'room_type', 'price', \n","                 'last_review', 'is_avail_zero', 'review_exists'], axis=1)\n","\n","scaler.fit(X_num)\n","X_scaled = scaler.transform(X_num)\n","X_scaled = pd.DataFrame(X_scaled, index=X_num.index, columns=X_num.columns)\n","\n","X = pd.concat([X_scaled, X_cat], axis=1)\n","y = df['price']"],"execution_count":43,"outputs":[]},{"cell_type":"code","source":["X.head(3)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":225},"id":"-RHnJ5M2zmUf","executionInfo":{"status":"ok","timestamp":1641144023293,"user_tz":-540,"elapsed":421,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"807b230b-4608-4a2d-a3e1-e4ef2d44d868"},"execution_count":44,"outputs":[{"output_type":"execute_result","data":{"text/html":["\n","  <div id=\"df-270b7a99-c30c-4a2c-8c0e-4a8dd0c773aa\">\n","    <div class=\"colab-df-container\">\n","      <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>host_id</th>\n","      <th>minimum_nights</th>\n","      <th>number_of_reviews</th>\n","      <th>reviews_per_month</th>\n","      <th>calculated_host_listings_count</th>\n","      <th>availability_365</th>\n","      <th>neighbourhood_group_Bronx</th>\n","      <th>neighbourhood_group_Brooklyn</th>\n","      <th>neighbourhood_group_Manhattan</th>\n","      <th>neighbourhood_group_Queens</th>\n","      <th>neighbourhood_group_Staten Island</th>\n","      <th>neighbourhood_Astoria</th>\n","      <th>neighbourhood_Bedford-Stuyvesant</th>\n","      <th>neighbourhood_Bushwick</th>\n","      <th>neighbourhood_Carroll Gardens</th>\n","      <th>neighbourhood_Chelsea</th>\n","      <th>neighbourhood_Chinatown</th>\n","      <th>neighbourhood_Clinton Hill</th>\n","      <th>neighbourhood_Crown Heights</th>\n","      <th>neighbourhood_Ditmars Steinway</th>\n","      <th>neighbourhood_East Elmhurst</th>\n","      <th>neighbourhood_East Flatbush</th>\n","      <th>neighbourhood_East Harlem</th>\n","      <th>neighbourhood_East New York</th>\n","      <th>neighbourhood_East Village</th>\n","      <th>neighbourhood_Elmhurst</th>\n","      <th>neighbourhood_Financial District</th>\n","      <th>neighbourhood_Flatbush</th>\n","      <th>neighbourhood_Flushing</th>\n","      <th>neighbourhood_Fort Greene</th>\n","      <th>neighbourhood_Gowanus</th>\n","      <th>neighbourhood_Gramercy</th>\n","      <th>neighbourhood_Greenpoint</th>\n","      <th>neighbourhood_Greenwich Village</th>\n","      <th>neighbourhood_Harlem</th>\n","      <th>neighbourhood_Hell's Kitchen</th>\n","      <th>neighbourhood_Inwood</th>\n","      <th>neighbourhood_Jackson Heights</th>\n","      <th>neighbourhood_Jamaica</th>\n","      <th>neighbourhood_Kips Bay</th>\n","      <th>neighbourhood_Long Island City</th>\n","      <th>neighbourhood_Lower East Side</th>\n","      <th>neighbourhood_Midtown</th>\n","      <th>neighbourhood_Morningside Heights</th>\n","      <th>neighbourhood_Murray Hill</th>\n","      <th>neighbourhood_Nolita</th>\n","      <th>neighbourhood_Park Slope</th>\n","      <th>neighbourhood_Prospect Heights</th>\n","      <th>neighbourhood_Prospect-Lefferts Gardens</th>\n","      <th>neighbourhood_Ridgewood</th>\n","      <th>neighbourhood_SoHo</th>\n","      <th>neighbourhood_South Slope</th>\n","      <th>neighbourhood_Sunnyside</th>\n","      <th>neighbourhood_Sunset Park</th>\n","      <th>neighbourhood_Theater District</th>\n","      <th>neighbourhood_Upper East Side</th>\n","      <th>neighbourhood_Upper West Side</th>\n","      <th>neighbourhood_Washington Heights</th>\n","      <th>neighbourhood_West Village</th>\n","      <th>neighbourhood_Williamsburg</th>\n","      <th>neighbourhood_Woodside</th>\n","      <th>neighbourhood_others</th>\n","      <th>room_type_Entire home/apt</th>\n","      <th>room_type_Private room</th>\n","      <th>room_type_Shared room</th>\n","      <th>is_avail_zero_Nonzero</th>\n","      <th>is_avail_zero_Zero</th>\n","      <th>review_exists_No</th>\n","      <th>review_exists_Yes</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>-0.848227</td>\n","      <td>-0.588004</td>\n","      <td>-0.352358</td>\n","      <td>-0.588299</td>\n","      <td>0.066069</td>\n","      <td>2.132586</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>-0.848227</td>\n","      <td>-0.588004</td>\n","      <td>0.419649</td>\n","      <td>-0.485721</td>\n","      <td>-0.084134</td>\n","      <td>2.052616</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>-0.848204</td>\n","      <td>-0.119342</td>\n","      <td>-0.545360</td>\n","      <td>-0.715013</td>\n","      <td>-0.121684</td>\n","      <td>2.132586</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-270b7a99-c30c-4a2c-8c0e-4a8dd0c773aa')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n","  </svg>\n","      </button>\n","      \n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      flex-wrap:wrap;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","      <script>\n","        const buttonEl =\n","          document.querySelector('#df-270b7a99-c30c-4a2c-8c0e-4a8dd0c773aa button.colab-df-convert');\n","        buttonEl.style.display =\n","          google.colab.kernel.accessAllowed ? 'block' : 'none';\n","\n","        async function convertToInteractive(key) {\n","          const element = document.querySelector('#df-270b7a99-c30c-4a2c-8c0e-4a8dd0c773aa');\n","          const dataTable =\n","            await google.colab.kernel.invokeFunction('convertToInteractive',\n","                                                     [key], {});\n","          if (!dataTable) return;\n","\n","          const docLinkHtml = 'Like what you see? Visit the ' +\n","            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","            + ' to learn more about interactive tables.';\n","          element.innerHTML = '';\n","          dataTable['output_type'] = 'display_data';\n","          await google.colab.output.renderOutput(dataTable, element);\n","          const docLink = document.createElement('div');\n","          docLink.innerHTML = docLinkHtml;\n","          element.appendChild(docLink);\n","        }\n","      </script>\n","    </div>\n","  </div>\n","  "],"text/plain":["    host_id  minimum_nights  ...  review_exists_No  review_exists_Yes\n","0 -0.848227       -0.588004  ...                 0                  1\n","1 -0.848227       -0.588004  ...                 0                  1\n","2 -0.848204       -0.119342  ...                 1                  0\n","\n","[3 rows x 69 columns]"]},"metadata":{},"execution_count":44}]},{"cell_type":"markdown","metadata":{"id":"x93Tb6lptcA2"},"source":["### 학습데이터와 테스트데이터 분리하기\n"]},{"cell_type":"code","metadata":{"id":"C9kMQI8SEche","executionInfo":{"status":"ok","timestamp":1641144038671,"user_tz":-540,"elapsed":410,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"source":["from sklearn.model_selection import train_test_split"],"execution_count":45,"outputs":[]},{"cell_type":"code","metadata":{"id":"F07QjOFwFNEw","executionInfo":{"status":"ok","timestamp":1641144056894,"user_tz":-540,"elapsed":469,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"source":["# train_test_split() 함수로 학습 데이터와 테스트 데이터 분리\n","X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=1)"],"execution_count":46,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"RrWrE8Z4exup"},"source":["## Step 5. Regression 모델 학습"]},{"cell_type":"markdown","metadata":{"id":"NypEtNhdfCow"},"source":["### XGBoost Regression 모델 학습"]},{"cell_type":"code","metadata":{"id":"ow28ZRL4F7D5","executionInfo":{"status":"ok","timestamp":1641144063082,"user_tz":-540,"elapsed":405,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"source":["from xgboost import XGBRegressor"],"execution_count":47,"outputs":[]},{"cell_type":"code","metadata":{"id":"LSSNqFUrGM6R","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1641144097958,"user_tz":-540,"elapsed":8687,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"e4bef95b-d70f-45d9-c448-8c7b084a693f"},"source":["# XGBRegressor 모델 생성/학습\n","model_reg = XGBRegressor()\n","model_reg.fit(X_train, y_train)"],"execution_count":48,"outputs":[{"output_type":"stream","name":"stdout","text":["[17:21:27] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n"]},{"output_type":"execute_result","data":{"text/plain":["XGBRegressor()"]},"metadata":{},"execution_count":48}]},{"cell_type":"markdown","metadata":{"id":"gUo8NmHkfIpf"},"source":["### 모델 학습 결과 평가"]},{"cell_type":"code","metadata":{"id":"rxvf1vgmfLs-","executionInfo":{"status":"ok","timestamp":1641144101343,"user_tz":-540,"elapsed":539,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}}},"source":["from sklearn.metrics import mean_absolute_error, mean_squared_error\n","from math import sqrt"],"execution_count":49,"outputs":[]},{"cell_type":"code","metadata":{"id":"KDVy7fFGfUP1","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1641144122857,"user_tz":-540,"elapsed":401,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"4d29f2a8-7f56-4101-b864-8d940dc39de9"},"source":["# Predict를 수행하고 mean_absolute_error, rmse 결과 출력\n","pred = model_reg.predict(X_test)\n","print(mean_absolute_error(y_test, pred))\n","print(sqrt(mean_squared_error(y_test, pred)))"],"execution_count":50,"outputs":[{"output_type":"stream","name":"stdout","text":["35.37089085317669\n","49.393558422539826\n"]}]},{"cell_type":"markdown","metadata":{"id":"DTqb-HqPtc4I"},"source":["## 모델 학습 결과 심화 분석\n"]},{"cell_type":"markdown","metadata":{"id":"xTRTOLTNto3h"},"source":["### 실제 값과 추측 값의 Scatter plot 시각화\n"]},{"cell_type":"code","metadata":{"id":"kKEP06-OmrBs","colab":{"base_uri":"https://localhost:8080/","height":284},"executionInfo":{"status":"ok","timestamp":1641144162858,"user_tz":-540,"elapsed":765,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"7aea0f4f-e63f-42ce-cf79-5c9f3ee37e64"},"source":["# y_test vs. pred Scatter 플랏으로 시각적으로 분석하기\n","\n","plt.scatter(x=y_test, y=pred, alpha=0.1)\n","plt.plot([0,350], [0, 350], 'r-')"],"execution_count":51,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[<matplotlib.lines.Line2D at 0x7f499af5c9d0>]"]},"metadata":{},"execution_count":51},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":["categorical feature에 의존하다보니 수직선 형태로 나타난다."],"metadata":{"id":"OMw4zm100Ofp"}},{"cell_type":"markdown","metadata":{"id":"kAisZoSEtp35"},"source":["### 에러율 값 히스토그램 확인"]},{"cell_type":"code","metadata":{"id":"WLnyYNJwGRgd","colab":{"base_uri":"https://localhost:8080/","height":279},"executionInfo":{"status":"ok","timestamp":1641144267328,"user_tz":-540,"elapsed":1787,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"14b5cb8a-ab9e-4cde-da4a-4eb728d83165"},"source":["# 에러율 히스토그램\n","err = (pred - y_test) / y_test\n","sns.histplot(err)\n","plt.grid()"],"execution_count":53,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["# 에러값 히스토그램\n","err = (pred - y_test)\n","sns.histplot(err)\n","plt.grid()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":279},"id":"qeRrxEhz0vFr","executionInfo":{"status":"ok","timestamp":1641144326193,"user_tz":-540,"elapsed":1717,"user":{"displayName":"김별희","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"06602448826503759202"}},"outputId":"d2b1c6ec-10f9-4ac5-e7ac-3fd43bb4d29e"},"execution_count":54,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]}]}