{"cells":[{"cell_type":"code","source":"#Importamos librerías\nimport pandas as pd\nimport seaborn as sns","metadata":{"id":"4FSi4TkR1KAF","cell_id":"978f268cbdb54f7ab968834c6dabbdd1","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":1112,"user_tz":180,"timestamp":1650392585934},"deepnote_cell_type":"code"},"outputs":[],"execution_count":1},{"cell_type":"code","source":"from google.colab import drive\nimport os\ndrive.mount('/content/gdrive')\n# Establecer ruta de acceso en dr\nimport os\nprint(os.getcwd())\nos.chdir(\"/content/gdrive/My Drive\")","metadata":{"id":"Qq3PanNw1NNr","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"bfce0e46a3134cc4a71d73cfa562aec8","outputId":"528aca58-3e5a-46fa-e56f-19f04d1de824","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":41554,"user_tz":180,"timestamp":1650392627759},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"Mounted at /content/gdrive\n/content\n"}],"execution_count":2},{"cell_type":"code","source":"#Cargamos los datos y los preparamos!\ndata = pd.read_csv(\"hotels.csv\", sep = \",\")","metadata":{"id":"ePQ6BUgX1KAR","cell_id":"e4e9f21a487245b398a5a6834466a983","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":1184,"user_tz":180,"timestamp":1650392628934},"deepnote_cell_type":"code"},"outputs":[],"execution_count":3},{"cell_type":"code","source":"data.head()","metadata":{"id":"VoO93XPA6DZ0","colab":{"height":386,"base_uri":"https://localhost:8080/"},"cell_id":"ed714e30324c4fb4a718a483d716ad1d","outputId":"91665f64-fd84-46e0-9185-992e1a802041","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":30,"user_tz":180,"timestamp":1650392628935},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"          hotel  is_canceled  lead_time  arrival_date_year arrival_date_month  \\\n0  Resort Hotel            0        342               2015               July   \n1  Resort Hotel            0        737               2015               July   \n2  Resort Hotel            0          7               2015               July   \n3  Resort Hotel            0         13               2015               July   \n4  Resort Hotel            0         14               2015               July   \n\n   arrival_date_week_number  arrival_date_day_of_month  \\\n0                        27                          1   \n1                        27                          1   \n2                        27                          1   \n3                        27                          1   \n4                        27                          1   \n\n   stays_in_weekend_nights  stays_in_week_nights  adults  ...  deposit_type  \\\n0                        0                     0       2  ...    No Deposit   \n1                        0                     0       2  ...    No Deposit   \n2                        0                     1       1  ...    No Deposit   \n3                        0                     1       1  ...    No Deposit   \n4                        0                     2       2  ...    No Deposit   \n\n   agent company days_in_waiting_list customer_type   adr  \\\n0    NaN     NaN                    0     Transient   0.0   \n1    NaN     NaN                    0     Transient   0.0   \n2    NaN     NaN                    0     Transient  75.0   \n3  304.0     NaN                    0     Transient  75.0   \n4  240.0     NaN                    0     Transient  98.0   \n\n   required_car_parking_spaces  total_of_special_requests  reservation_status  \\\n0                            0                          0           Check-Out   \n1                            0                          0           Check-Out   \n2                            0                          0           Check-Out   \n3                            0                          0           Check-Out   \n4                            0                          1           Check-Out   \n\n  reservation_status_date  \n0              2015-07-01  \n1              2015-07-01  \n2              2015-07-02  \n3              2015-07-02  \n4              2015-07-03  \n\n[5 rows x 32 columns]","text/html":"\n  <div id=\"df-7e21177f-d94f-4d50-95db-316d4cfd0df1\">\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>hotel</th>\n      <th>is_canceled</th>\n      <th>lead_time</th>\n      <th>arrival_date_year</th>\n      <th>arrival_date_month</th>\n      <th>arrival_date_week_number</th>\n      <th>arrival_date_day_of_month</th>\n      <th>stays_in_weekend_nights</th>\n      <th>stays_in_week_nights</th>\n      <th>adults</th>\n      <th>...</th>\n      <th>deposit_type</th>\n      <th>agent</th>\n      <th>company</th>\n      <th>days_in_waiting_list</th>\n      <th>customer_type</th>\n      <th>adr</th>\n      <th>required_car_parking_spaces</th>\n      <th>total_of_special_requests</th>\n      <th>reservation_status</th>\n      <th>reservation_status_date</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Resort Hotel</td>\n      <td>0</td>\n      <td>342</td>\n      <td>2015</td>\n      <td>July</td>\n      <td>27</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2</td>\n      <td>...</td>\n      <td>No Deposit</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n      <td>Transient</td>\n      <td>0.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>Check-Out</td>\n      <td>2015-07-01</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Resort Hotel</td>\n      <td>0</td>\n      <td>737</td>\n      <td>2015</td>\n      <td>July</td>\n      <td>27</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2</td>\n      <td>...</td>\n      <td>No Deposit</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n      <td>Transient</td>\n      <td>0.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>Check-Out</td>\n      <td>2015-07-01</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Resort Hotel</td>\n      <td>0</td>\n      <td>7</td>\n      <td>2015</td>\n      <td>July</td>\n      <td>27</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>...</td>\n      <td>No Deposit</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n      <td>Transient</td>\n      <td>75.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>Check-Out</td>\n      <td>2015-07-02</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Resort Hotel</td>\n      <td>0</td>\n      <td>13</td>\n      <td>2015</td>\n      <td>July</td>\n      <td>27</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>...</td>\n      <td>No Deposit</td>\n      <td>304.0</td>\n      <td>NaN</td>\n      <td>0</td>\n      <td>Transient</td>\n      <td>75.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>Check-Out</td>\n      <td>2015-07-02</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Resort Hotel</td>\n      <td>0</td>\n      <td>14</td>\n      <td>2015</td>\n      <td>July</td>\n      <td>27</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>2</td>\n      <td>...</td>\n      <td>No Deposit</td>\n      <td>240.0</td>\n      <td>NaN</td>\n      <td>0</td>\n      <td>Transient</td>\n      <td>98.0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>Check-Out</td>\n      <td>2015-07-03</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 32 columns</p>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7e21177f-d94f-4d50-95db-316d4cfd0df1')\"\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-7e21177f-d94f-4d50-95db-316d4cfd0df1 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-7e21177f-d94f-4d50-95db-316d4cfd0df1');\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  "},"metadata":{},"execution_count":4}],"execution_count":4},{"cell_type":"code","source":"#Hacemos una copia del dataset y me quedo con algunas variables\ndata2 = data[['total_of_special_requests','deposit_type','customer_type', 'stays_in_weekend_nights', 'stays_in_week_nights', 'required_car_parking_spaces','arrival_date_month',\n'arrival_date_day_of_month','hotel']].copy()","metadata":{"id":"UddUkeBO1KAS","cell_id":"34572037ca1e4f50b02c4bae889e8e75","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":26,"user_tz":180,"timestamp":1650392628935},"deepnote_cell_type":"code"},"outputs":[],"execution_count":5},{"cell_type":"code","source":"#Veamos que tenemos!\ndata2.head()","metadata":{"id":"UeOSBlji1KAT","colab":{"height":206,"base_uri":"https://localhost:8080/"},"cell_id":"62b5ef2f603544ddb5b5c2d237245c26","outputId":"2b783387-a805-43f8-8105-60f078a985f1","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":26,"user_tz":180,"timestamp":1650392628936},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"   total_of_special_requests deposit_type customer_type  \\\n0                          0   No Deposit     Transient   \n1                          0   No Deposit     Transient   \n2                          0   No Deposit     Transient   \n3                          0   No Deposit     Transient   \n4                          1   No Deposit     Transient   \n\n   stays_in_weekend_nights  stays_in_week_nights  required_car_parking_spaces  \\\n0                        0                     0                            0   \n1                        0                     0                            0   \n2                        0                     1                            0   \n3                        0                     1                            0   \n4                        0                     2                            0   \n\n  arrival_date_month  arrival_date_day_of_month         hotel  \n0               July                          1  Resort Hotel  \n1               July                          1  Resort Hotel  \n2               July                          1  Resort Hotel  \n3               July                          1  Resort Hotel  \n4               July                          1  Resort Hotel  ","text/html":"\n  <div id=\"df-e581d1e5-fe52-4ba8-a551-b724d4b427b0\">\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>total_of_special_requests</th>\n      <th>deposit_type</th>\n      <th>customer_type</th>\n      <th>stays_in_weekend_nights</th>\n      <th>stays_in_week_nights</th>\n      <th>required_car_parking_spaces</th>\n      <th>arrival_date_month</th>\n      <th>arrival_date_day_of_month</th>\n      <th>hotel</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>No Deposit</td>\n      <td>Transient</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>July</td>\n      <td>1</td>\n      <td>Resort Hotel</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>No Deposit</td>\n      <td>Transient</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>July</td>\n      <td>1</td>\n      <td>Resort Hotel</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0</td>\n      <td>No Deposit</td>\n      <td>Transient</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>July</td>\n      <td>1</td>\n      <td>Resort Hotel</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>No Deposit</td>\n      <td>Transient</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>July</td>\n      <td>1</td>\n      <td>Resort Hotel</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1</td>\n      <td>No Deposit</td>\n      <td>Transient</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>July</td>\n      <td>1</td>\n      <td>Resort Hotel</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e581d1e5-fe52-4ba8-a551-b724d4b427b0')\"\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-e581d1e5-fe52-4ba8-a551-b724d4b427b0 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-e581d1e5-fe52-4ba8-a551-b724d4b427b0');\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  "},"metadata":{},"execution_count":6}],"execution_count":6},{"cell_type":"code","source":"data2.shape","metadata":{"id":"sJ66hRv01Wm8","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"1068f483d25e4819a7d4419f8cc60bef","outputId":"4bc3e41c-bc9f-46af-bc35-0c3fba3cecbf","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":24,"user_tz":180,"timestamp":1650392628936},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"(119390, 9)"},"metadata":{},"execution_count":7}],"execution_count":7},{"cell_type":"markdown","source":"Creamos la variable target: \n    ","metadata":{"id":"RibhORoH1KAV","cell_id":"94fb202326084e0b93ee49a7911c5c14","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"data2['total_stay'] = data2['stays_in_week_nights'] + data2['stays_in_weekend_nights']\n\n# Eliminamos las var q usamos...\ndata3 = data2.drop(['stays_in_week_nights','stays_in_weekend_nights'], axis=1)","metadata":{"id":"8vLTz6oa1KAW","cell_id":"ee2f63180ae3475d90f3ac62ac35156e","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":21,"user_tz":180,"timestamp":1650392628937},"deepnote_cell_type":"code"},"outputs":[],"execution_count":8},{"cell_type":"code","source":"data3.head()","metadata":{"id":"UB-sGHbi1KAX","colab":{"height":206,"base_uri":"https://localhost:8080/"},"cell_id":"871a25afc0634e49ac6e852ed542064c","outputId":"541b4ab6-9f12-4dc2-c7b6-5dcd53359b9d","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":21,"user_tz":180,"timestamp":1650392628937},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"   total_of_special_requests deposit_type customer_type  \\\n0                          0   No Deposit     Transient   \n1                          0   No Deposit     Transient   \n2                          0   No Deposit     Transient   \n3                          0   No Deposit     Transient   \n4                          1   No Deposit     Transient   \n\n   required_car_parking_spaces arrival_date_month  arrival_date_day_of_month  \\\n0                            0               July                          1   \n1                            0               July                          1   \n2                            0               July                          1   \n3                            0               July                          1   \n4                            0               July                          1   \n\n          hotel  total_stay  \n0  Resort Hotel           0  \n1  Resort Hotel           0  \n2  Resort Hotel           1  \n3  Resort Hotel           1  \n4  Resort Hotel           2  ","text/html":"\n  <div id=\"df-c8644b53-be3c-40dd-af29-e41ff4474e32\">\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>total_of_special_requests</th>\n      <th>deposit_type</th>\n      <th>customer_type</th>\n      <th>required_car_parking_spaces</th>\n      <th>arrival_date_month</th>\n      <th>arrival_date_day_of_month</th>\n      <th>hotel</th>\n      <th>total_stay</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>No Deposit</td>\n      <td>Transient</td>\n      <td>0</td>\n      <td>July</td>\n      <td>1</td>\n      <td>Resort Hotel</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>No Deposit</td>\n      <td>Transient</td>\n      <td>0</td>\n      <td>July</td>\n      <td>1</td>\n      <td>Resort Hotel</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0</td>\n      <td>No Deposit</td>\n      <td>Transient</td>\n      <td>0</td>\n      <td>July</td>\n      <td>1</td>\n      <td>Resort Hotel</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>No Deposit</td>\n      <td>Transient</td>\n      <td>0</td>\n      <td>July</td>\n      <td>1</td>\n      <td>Resort Hotel</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1</td>\n      <td>No Deposit</td>\n      <td>Transient</td>\n      <td>0</td>\n      <td>July</td>\n      <td>1</td>\n      <td>Resort Hotel</td>\n      <td>2</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c8644b53-be3c-40dd-af29-e41ff4474e32')\"\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 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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  "},"metadata":{},"execution_count":9}],"execution_count":9},{"cell_type":"code","source":"grafico_df=data3[['total_stay','arrival_date_month']].groupby('arrival_date_month').count()\ngrafico_df\nimport seaborn as sns\nimport matplotlib.pyplot as plt\ngrafico_df.plot(kind='bar')\nplt.title('Distribucion de noches por mes')\nplt.xlabel('Mes')\nplt.ylabel('Frecuencia')","metadata":{"id":"qr5Z_6jw69zx","colab":{"height":357,"base_uri":"https://localhost:8080/"},"cell_id":"9ffe0d9432a54fd7be6cf30f1f073ef4","outputId":"94559520-ceae-4de0-cbb2-72f61cd52429","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":483,"user_tz":180,"timestamp":1650392629401},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Text(0, 0.5, 'Frecuencia')"},"metadata":{},"execution_count":10},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 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cnOWmVknc+ONN3L88ccvVzZ06FCuvvrqwvvccsstmT59+qpW7W2cRMzMOpndd9+9bh3fZXNzlpl1ed2tb7dMK/tZOomYWZfWu3dvXnjhBSeSOqjclKqj162Am7PMrIsbPHgws2fPxvcKqo/K7XE7yknEzLq0Xr16dfhWrlZ/bs4yM7PCnETMzKwwN2eZFeDZBswSn4mYmVlhTiJmZlaYk4iZmRXmJGJmZoU5iZiZWWFOImZmVlhpSUTSBZKel/RIVdkPJf1d0kOSrpbUr2rdiZKmSXpC0u5V5WNy2TRJJ1SVD5V0Ty6/UtIaZb0XMzOrrcwzkYuAMa3KJgJbRcRw4B/AiQCStgT2A96fX3OOpBZJLcDPgT2ALYFxeVuA7wNnRsQWwIvAYSW+FzMzq6G0JBIRtwPzW5X9OSIW58W7gcosX2OBKyLi9Yh4CpgG7JAf0yJiekS8AVwBjJUkYFfgqvz6i4FPlfVezMystmb2iXwB+FN+vjEwq2rd7FzWVvkAYEFVQqqU1yTpCEmTJU32TJ9mZvXTlCQi6WRgMXBpI+JFxHkRMTIiRg4cOLARIc3MuoWGz50l6RBgL2B0LLuLzBxgk6rNBucy2ih/AegnqWc+G6ne3szMGqShSUTSGOAbwIciYlHVqmuByyT9GNgIGAbcCwgYJmkoKUnsB+wfESHpVmBfUj/JwcA1jXsnZlZPntCy6ypziO/lwF3AeyTNlnQYcDbQB5go6QFJvwSIiEeBCcBjwA3AURGxJJ9lfAW4EXgcmJC3BTge+JqkaaQ+kvPLei9mZlZbaWciETGuRnGbX/QRcTpweo3y64Hra5RPJ43eMjOzJvEV62ZmVpiTiJmZFeYkYmZmhTmJmJlZYU4iZmZWmJOImZkV5iRiZmaFNXzaEzOz7mZ1viLfSaTK6vwfbWZWBjdnmZlZYT4TMesCfJZsnZXPRMzMrDAnETMzK8xJxMzMCnMSMTOzwpxEzMysMI/OMjNbzTRyNJ/PRMzMrDAnETMzK8xJxMzMCistiUi6QNLzkh6pKusvaaKkqfnf9XK5JP1U0jRJD0kaUfWag/P2UyUdXFX+b5Iezq/5qSSV9V7MzKy2Ms9ELgLGtCo7Abg5IoYBN+dlgD2AYflxBPALSEkHOAXYEdgBOKWSePI2X6x6XetYZmZWstKSSETcDsxvVTwWuDg/vxj4VFX5+EjuBvpJ2hDYHZgYEfMj4kVgIjAmr+sbEXdHRADjq/ZlZmYN0ug+kUER8Ux+/iwwKD/fGJhVtd3sXNZe+ewa5WZm1kBN61jPZxDRiFiSjpA0WdLkuXPnNiKkmVm30Ogk8lxuiiL/+3wunwNsUrXd4FzWXvngGuU1RcR5ETEyIkYOHDhwld+EmZkljU4i1wKVEVYHA9dUlR+UR2mNAl7KzV43ArtJWi93qO8G3JjXvSxpVB6VdVDVvszMrEFKm/ZE0uXAh4H1Jc0mjbL6HjBB0mHATOCzefPrgT2BacAi4FCAiJgv6TRgUt7u1IiodNYfSRoBthbwp/wwszrwTbCso0pLIhExro1Vo2tsG8BRbeznAuCCGuWTga1WpY5mZrZqfMW6mZkV5iRiZmaFOYmYmVlhTiJmZlaYk4iZmRXmJGJmZoU5iZiZWWFOImZmVpiTiJmZFeYkYmZmhTmJmJlZYU4iZmZWWIeSSJ5yfZKkVyS9IWmJpJfLrpyZmXVuHT0TORsYB0wlTb1+OPDzsiplZmZdQ4ebsyJiGtASEUsi4kJgTHnVMjOzrqCj9xNZJGkN4AFJPwCewf0pZmbdXkcTwYFAC/AV4FXSfc/3KatSZmbWNXToTCQiZuan/wL+p7zqmJlZV9JuEpE0ISI+K+lhIFqvj4jhpdXMzMw6vRWdiRyb/92r7IqYmVnX024SiYhn8tMewDMR8RqApLWAQSXXzczMOrmOdqz/FlhatbwklxUi6auSHpX0iKTLJfWWNFTSPZKmSboyjwZD0pp5eVpeP6RqPyfm8ick7V60PmZmVkxHk0jPiHijspCfr1EkoKSNgWOAkRGxFWnU137A94EzI2IL4EXgsPySw4AXc/mZeTskbZlf937SNSvnSGopUiczMyumo0lkrqRPVhYkjQXmrULcnsBaknoCa5OuO9kVuCqvvxj4VH4+Ni+T14+WpFx+RUS8HhFPAdOAHVahTmZmtpI6erHhl4FLJZ0NCJgFHFQkYETMkXQG8DRpyPCfgSnAgohYnDebDWycn2+c4xERiyW9BAzI5XdX7br6NdZkQ074Y6HXzfjex+tcEzMrU0evE3kSGCVp3bz8StGAktYjnUUMBRaQ+lZKnUJF0hHAEQCbbrppmaHMzLqVDiURSWuSrlAfAvRMrUkQEacWiPlR4KmImJv3/XtgZ6CfpJ75bGQwMCdvP4d0hfzs3Pz1DuCFqvKK6tcsJyLOA84DGDly5NuudzEzs2I62idyDensYTFp2pPKo4inSWc1a+e+jdHAY8CtwL55m4NzTIBr8zJ5/S0REbl8vzx6aygwDLi3YJ3MzKyAjvaJDI6IujQ5RcQ9kq4C7iMlpftJZwl/BK6Q9J1cdn5+yfnAJZKmAfNJI7KIiEclTSAloMXAURGxpB51NDOzjuloErlT0tYR8XA9gkbEKcAprYqnU2N0Vb7A8TNt7Od04PR61MnMzFZeR5PIB4FDJD0FvE4aoRWeO8vMrHvraBLZo9RamJlZl9ShjvU8FfwmwK75+aKOvtbMzFZfHUoEkk4BjgdOzEW9gN+UVSkzM+saOno28Wngk+RhvRHxT6BPWZUyM7OuoaNJ5I18bUYASFqnvCqZmVlX0dEkMkHSuaSryr8I3AT8qrxqmZlZV9DRubPOkPQx4GXgPcC3ImJiqTUzM7NOr6NDfMlJw4nDzMze0tEJGBeS+0NIN6PqBbwaEX3LqpiZmXV+HW3OemskVtUNoUaVVSkzM+saVvqCwUj+APie5mZm3VxHm7P2rlrsAYwEXiulRmZm1mV0tGP9E1XPFwMzSE1a1kX4drVmy/h4qJ+O9okcWnZFzMys6+no3FkXS+pXtbyepAvKq5aZmXUFHe1YHx4RCyoLEfEisF05VTIzs66io0mkh6T1KguS+rMSFyqamdnqqaOJ4EfAXZJ+m5c/g29La2bW7XW0Y328pMnArrlo74h4rLxqmZlZV7AyFxv2J011cjYwV9LQkupkZmZdRFPubCipn6SrJP1d0uOSdpLUX9JESVPzv+vlbSXpp5KmSXpI0oiq/Ryct58q6eCi9TEzs2KadWfDs4AbIuK9wDbA48AJwM0RMQy4OS8D7AEMy48jgF/AW537pwA7AjsAp1R3/puZWfkafmdDSe8A/h04HyAi3sjDh8cCF+fNLgY+lZ+PBcbnObvuJt0Ya0PS3F0TI2J+HnI8ERhTtF5mZrbymnFnw6HAXOBCSfdL+nVOSoMi4pm8zbPAoPx8Y2BW1etn57K2ys3MrEFWODorT/1+JfBe6nNnw57ACODoiLhH0lksa7oC0kzBkqLmqwuQdASpKYxNN920Xrs1M+v2VphE8hf69RGxNfW5s+FsYHZE3JOXryIlkeckbRgRz+Tmqufz+jnAJlWvH5zL5gAfblX+lzbew3nAeQAjR46sW3KyzsMT6pk1R0ebs+6TtH09AkbEs8AsSe/JRaOBx4BrgcoIq4OBa/Lza4GD8iitUcBLudnrRmC3PI/XesBuuczMzBqko1es7wh8XtIM0ggtkU5ShheMezRwqaQ1gOnAoaSENkHSYcBM4LN52+uBPYFpwKK8LRExX9JpwKS83akRMb9gfczMrIB2k4ikTSPiaep8F8OIeIB0Y6vWRtfYNoCj2tjPBYBnEzYza5IVnYn8ARgRETMl/S4i9mlEpczMrGtYUZ+Iqp5vXmZFzMys61lREok2npuZma2wOWsbSS+TzkjWys9hWcd631JrZ2ZmnVq7SSQiWhpVETMz63pWZip4MzOz5TiJmJlZYU4iZmZWmJOImZkV5iRiZmaFOYmYmVlhTiJmZlaYk4iZmRXmJGJmZoU5iZiZWWFOImZmVpiTiJmZFeYkYmZmhTmJmJlZYU4iZmZWmJOImZkV1rQkIqlF0v2SrsvLQyXdI2mapCslrZHL18zL0/L6IVX7ODGXPyFp9+a8EzOz7quZZyLHAo9XLX8fODMitgBeBA7L5YcBL+byM/N2SNoS2A94PzAGOEeS78RoZtZATUkikgYDHwd+nZcF7ApclTe5GPhUfj42L5PXj87bjwWuiIjXI+IpYBqwQ2PegZmZQfPORH4CfANYmpcHAAsiYnFeng1snJ9vDMwCyOtfytu/VV7jNcuRdISkyZImz507t57vw8ysW2t4EpG0F/B8RExpVMyIOC8iRkbEyIEDBzYqrJnZaq9nE2LuDHxS0p5Ab6AvcBbQT1LPfLYxGJiTt58DbALMltQTeAfwQlV5RfVrzMysARp+JhIRJ0bE4IgYQuoYvyUiDgBuBfbNmx0MXJOfX5uXyetviYjI5fvl0VtDgWHAvQ16G2ZmRnPORNpyPHCFpO8A9wPn5/LzgUskTQPmkxIPEfGopAnAY8Bi4KiIWNL4apuZdV9NTSIR8RfgL/n5dGqMroqI14DPtPH604HTy6uhmZm1x1esm5lZYU4iZmZWmJOImZkV5iRiZmaFOYmYmVlhTiJmZlaYk4iZmRXmJGJmZoU5iZiZWWFOImZmVpiTiJmZFeYkYmZmhTmJmJlZYU4iZmZWmJOImZkV5iRiZmaFOYmYmVlhTiJmZlaYk4iZmRXmJGJmZoU5iZiZWWENTyKSNpF0q6THJD0q6dhc3l/SRElT87/r5XJJ+qmkaZIekjSial8H5+2nSjq40e/FzKy7a8aZyGLg6xGxJTAKOErSlsAJwM0RMQy4OS8D7AEMy48jgF9ASjrAKcCOwA7AKZXEY2ZmjdHwJBIRz0TEffn5QuBxYGNgLHBx3uxi4FP5+VhgfCR3A/0kbQjsDkyMiPkR8SIwERjTwLdiZtbtNbVPRNIQYDvgHmBQRDyTVz0LDMrPNwZmVb1sdi5rq7xWnCMkTZY0ee7cuXWrv5lZd9e0JCJpXeB3wH9GxMvV6yIigKhXrIg4LyJGRsTIgQMH1mu3ZmbdXlOSiKRepARyaUT8Phc/l5upyP8+n8vnAJtUvXxwLmur3MzMGqQZo7MEnA88HhE/rlp1LVAZYXUwcE1V+UF5lNYo4KXc7HUjsJuk9XKH+m65zMzMGqRnE2LuDBwIPCzpgVx2EvA9YIKkw4CZwGfzuuuBPYFpwCLgUICImC/pNGBS3u7UiJjfmLdgZmbQhCQSEXcAamP16BrbB3BUG/u6ALigfrUzM7OV4SvWzcysMCcRMzMrzEnEzMwKcxIxM7PCnETMzKwwJxEzMyvMScTMzApzEjEzs8KcRMzMrDAnETMzK8xJxMzMCnMSMTOzwpxEzMysMCcRMzMrzEnEzMwKcxIxM7PCnETMzKwwJxEzMyvMScTMzApzEjEzs8KcRMzMrLAun0QkjZH0hKRpkk5odn3MzLqTLp1EJLUAPwf2ALYExknasrm1MjPrPrp0EgF2AKZFxPSIeAO4Ahjb5DqZmXUbiohm16EwSfsCYyLi8Lx8ILBjRHyl1XZHAEfkxfcATxQItz4wbxWq25njrc7vzfEcz/HqE2+ziBjYurDnqten84uI84DzVmUfkiZHxMg6ValTxVud35vjOZ7jlRuvqzdnzQE2qVoenMvMzKwBunoSmQQMkzRU0hrAfsC1Ta6TmVm30aWbsyJisaSvADcCLcAFEfFoSeFWqTmsk8dbnd+b4zme45UYr0t3rJuZWXN19eYsMzNrIicRMzMrzEnErAuStJak9zS7HmZOIt2QpBZJZzS7HmWRdLSk9RoY70eS3t/AeJ8AHgBuyMvbSlqtRiVK2rqBsRp2PDT62MvxLi0zRpcenVUGSf3bWx8R80uKe3NEjF5RWT1ExBJJH6z3ftsjaQpwAXBZRLxYcrhBwCRJ9+WYN0a5I0geB86T1BO4ELg8Il4qMd63SVP+/AUgIh6QNLTEeEgaCHwRGELV90ZEfKGkkOdIWhO4CLi0zM+zkcdDo4+9HG8zSWvkqaHqzknk7aYAAajGugA2r2cwSb2BtYH186/nSty+wMb1jNXK/cd+gbYAABNUSURBVPnX62+BVyuFEfH7kuJ9DjiU9OU+mfRl++cyvtwj4puS/hvYLcc8W9IE4PyIeLKEeL8Gfp2blw4FHpL0N+BXEXFrveMBb0bES9Jyf6JlD7O8BvgrcBOwpORYRMQukoYBXwCmSLoXuDAiJpYUspHHQ6OPvenA33LM6ng/rsfOnURaiYhSf9HV8CXgP4GNSAms8s3wMnB2iXF7Ay8Au1aVBVDKH3JETANOzl/ue5HOEJZIuhA4q95neBERkp4FngUWA+sBV0maGBHfqGcseGtG6ffmxzzgQeBrkr4UEfvVOdyjkvYHWvIX7THAnXWO0draEXF8yTGWExFTJX0TmAz8FNhOKXOeVMIXbiOPh4Yee8CT+dED6FPvnfs6kVYkvTci/i5pRK31EXFfSXGPjoiflbHvzkLScNIv9T1JF4heCnwQODAitq1jnGOBg0hf5r8G/hARb0rqAUyNiHfVK1aOdybwCeBm0tnOvVXrnoiIunaAS1obOJl0piXSZ3laRLxWzzitYn4HuDMiri8rRqt4lb+VjwMTSZ/rfZI2Au6KiM0aUY/ViaS1I2JR3XccEX5UPYDz8r+31njcUmLczwB98vNvkn6VjCgx3rtJX3qP5OXhwDdLjDclx9sfWLPVut/XOda3STOO1lr3vhLe26HAOm2se0dZn2kjHsBC0lnxQmAp8K+q5ZdLjHsbcCCwVo11B5YQr2HHQxOOvZ2Ax4Cn8/I2wDn12r/PRGrIv1h3ioi/NTDmQxExPHe6fQf4IfCtiNixpHi3AccB50bEdrnskYjYqoRYPYATIuJ/673vGrFagEcj4r0NiFXzbLUiyjtrfTfwX7y9k3vXtl5j7Wvw8dCwWHnf9wD7AteWEc99IjVExFJJZwPbNTBspbPy46SzoT/mJoSyrB0R97bqnF1cRqD8ee4NlJ5EIo1GeULSphHxdMnhftReVVi+zbuefgv8ktRUV3onN4CkT5POxF/Ky/2AD0fEH0qKNwz4LumOpb0r5RFR14EtVRp2PDQ4FgARMatVvLr93TiJtO1mSfuQmloacbo2R9K5wMeA7+fhjWVexzNP0rvIo3ryDb6eKTHeTZL+C7iS5UeIlDFkej1S5/O9rWJ9sp5BIuIj9dzfSlgcEb9ocMxTIuLqykJELJB0ClBKEiGN3jsFOBP4CKnJcHU5Hhp97M2S9AEgJPUCjiUNS68LN2e1QdJCYB1Sxv4XqQMzIqJvSfHWBsYAD0calbIhsHVE/LmkeJuTZvP8APAi8BRwQETMLCneUzWKo4xflpI+VKs8Im6rd6wc76A24o0vKd63geeBq4HXq+KVcg1TjvlQRAxvVfZwRJRyUaCkKRHxb9UxKmUlxWvY8dCEY2994Czgo6REfCNwbES8UJf9O4l0DpI2rVVedpOMpHWAHhGxsMw4qzNJ1aPqegOjgfsiYt+S4jUsIVfFvABYAPw8Fx0F9I+IQ0qKdydp5N5VwC2km819L+o80q1G3IYdD6vLseck0o7cjv9B0mnnX8tq/82xHmbZRY69gaHAExFRynQakgaQmgsq7+8O4NR6/TppI+ZWvL2Nu+6/1iWNAn4GvA9Yg3SvmVfLOousEb8fcEVEjGlEvEbIX3j/Tfo1G6Rht6dHxKvtvrB4vO1JTS79gNOAdwA/iIi7S4rXsOOh0cdePvM5CxiV490FfDUiptdl/04itUk6B9gCuDwXfQ54MiKOalD8EcCREXF4SfufCNwO/CYXHUDqKP1oSfFOAT5MSiLXA3sAd5Txaz1fEb8fqQN6JOmakXdHxIn1jtVG/F6k4Zul/GpuQvNZC3BTE/uAStfI46EJx97dpDPIynfZfsDR9Rr56STSBkl/J11TUOn86kEaOvq+BtahzDbntw3xKznew6Tx6fdHxDaSBgG/iYiPlRBrckSMrG7Hl3R/ZXhjCfH+j2XTjrSQEuWEKOkK70Y3n+WYNwN7R7lzgqEVTCRZ78ERVXEbdjw04dir1Z/1YERsU4/9e3RW26YBmwKVzq5NclkpJH2tarEHMAL4Z1nxgD9L2g+YkJf3JXW4leVfeajvYkl9SR3Dm5QUa5GkNYAHJP2ANPKlzJE9Z7AsiSwGZkbEnLKCRcTR1cuV5rOy4mWvAA/nX9HVI96OqXOcnYBZpF/N91B7DrsyNPJ4aEgsLZtM9k+STiD9jQSpVaVuMw/4TKQN+YKg7YHKFBbbA5NIV+vW/RdRbu6pWAzMAH4XdZ7KIo86q/S9rEO6ChnSl+wrJY4+Owc4iXQq/XXSl9IDEXFoCbE2IyWpXsBXSe3p50Sav6uecao/y2pBGjX1JHByRNxcz7g16lFq81mOcXCt8oi4uM5xWkjD3MeRruT+I2lW5EfrGacqXsOOh0Yfe3kARpuTydZrIIaTSBtaDRMVsAvpC/BIKG+4aHcgaQjQNyIeanJVSpO/DLciTWNe1yuRG9181iz5WqlxpNkb/iciypyQ1ApyEmmHpO1Icz19hjSW+/dR0iSJrb4YKl4izWB6br3PSHLM4bx96oxSZhKV9O+1yiPi9hJiVX6BtY5V2hDYdurypYg4t877/BANbD7LMRt2BXlOHh8nJZAhwLXABQ14j408Hj4JVI6Jv0TEdWXEybFaSJ/nEJZ/b54KvgxK8xKNy495pCus1YCRKdOBgSw/GmwhabK2X5Emo6ubPO5/OPAoy06ry5yO+riq571JN1WaQjlTg4xsFeszQLs3GytLPRNIe81nkspuPmvIFeSSxpPO4K4nnX08Uu8YbcRt2PEg6Xuk5vHKHQePlbRziaMH/w94DXiYZe+tbnwm0oqkpaSb7xxWaUOXNL3sX7GSJkXE9rXKJD1a7+tFJD0WEVvWc58rGX8T4CcRsU+D4pV2tXNnUGbzWd5/Q64gz8dfpeO++sup7BkjGnY8SHoI2DYilublFtKoxeHtv7J4vLL2DT4TqWVvUt/HrZJuII1oaMQIkXVVNWlgvoJ93byujNta3iVpy4h4rIR9d8Rs0sWAdaflZ9ftQTozWa3/1iNiCfBgq+G/9fR6HuY+VdJXSFeQr7uC16y0iChzFF17Gn089AMq09S8o+RYf5K0W5Q0hdJqfWAVka9K/0O+Qncs6a6D75T0C+Dqsv4jSCOW7pD0JClpDQWOzPWo6wiYbDzpwHmWNJKo8kuvrF9DP2PZL8sewLZAKVOls/zsupWRbp8tKVanUu/+lyrHkm7jfAzpCvJdgZojtrqoRh4P3yXdIvfWHOffgTIvhL0buDr/CHiTOp/VuTmrA5Tuff4Z4HMRMbrEOGuSbq8KacqTMu9UNw34Gq3aSaO8SeCqv3AWAzOigfdrMWtPE46HDUn9IgD3RsSzZcTJsZ4i/SB+OEr4wncS6SSaMJXFXRGxUxn7rhGrBRgfEQc0KN6awD68fTTKqY2Ivzpp1hXkjdbg4+Hm1j9Ga5XVMd7tpGlV6t6pDm7O6kyqO9XfmsqCdJpdhvslXUYauVE9nXjdR6NEulHUZpLWiIgy+ndau4Y0PHoKVe/NCmnWFeSNVvrxIKk3qUlw/dy6Ufks+wIb1ytODdOBv0j6E8u/Nw/xXZ00YSqLtUh/ULtVV4PyhvhOB/6Wf9lWT5tRlz/kVgbHajSDbpNtwLIryPen5CvIm6gRx8OXSH2sG5F+4FSSyMtAmRdSPpUfa+RHXbk5q5PKU1k8GhHvbnZd6qHVtC5viYj/KSHWecDPIuLheu+7O/MV5PUh6eiyLlpeQdy1I2JRvffrM5FOosZUFu9j2QRtZcR7N/ALYFBEbJWv1v1kRJRyX/dKssiTL0aUeyOeDwKH5A7F0keere5qXEH+U9JdFVcbDT4elkrqFxELcuz1gHERcU4JsZC0E3A+aUj2ppK2Ab4UEUfWZf8+E+kcWs3VtZiUSD4XJd2/JE8weRxpSpXtctnbpqiuY7yRpKue++Sil4AvRMSUEmJtVqu8rJE2q7NWV5Bf0agryButkceDpAciYttWZWXequAe0kzB15bx3nwm0klExG015ur6XYkh146Ie6Xl+kkXlxjvAtJNtv4KIOmDpKRS97ODSrKQ9E6q5nmyQj5P6sM6Fjim6u+l1CvIm6CRx0OLJFWG2+bRi3Xvq6gWEbNavbcl9dq3k0iTNXGurnmS3kVuQpO0L+m+G2VZUkkgABFxh6RSDtI8ud2PSB2YzwObkW61WsqthldnTbyCvNEaeTzcCFwpqXJh6JeBG0qKBTBL0gdIc6z1Iv0geLxeO3dzVpM1ca6uzYHzgA8AL5LOfD4fETPqHKcyBclBpBEwl7PsxjivRcTX2nrtKsR8kHRF9U0RsZ2kj5De22H1jmWrhzaOhwPKaAKVtBbwRaDShH0jcH6euqbuJK1Pusf6R0lnkH8GjomI+e2+sIN8JtJ8TZmrKyKmAx/N06r0KLGj+0etlqtHaZX1C+bNiHhBUg9JPSLiVkk/KSmWrR5mRkSpx4OknsD/kmZAnpWLNyUNf+9BHZuYWnlP6wt9Je0M1GXGCJ+JdBJVc3WNI/2KHk+Jc3VJ+l/gB61GiHw9Ir5ZRrxGknQT8Cnge8AAUpPW9hHxgaZWzDotSU+TmpSuBG4pZXoQ6UzSwJKvVpKUpD6kH1r/iohj6x0zx7gvIkasqKzw/p1EOp9GzNVVazRIPf+wasQbRPoVtlFE7CFpS2CniDi/hFhrk+6fIFLHcF/SFOl1OX231U/+m9mL1CowAriONBrtjjrGmAq8u3WCyh3rf4+IYfWKlfe7E6l57j9J94Gp6At8OiK2qUec7tJp1qVExIsRcV6Zkz2SRoisWVnI7bRrtrP9qrqI1Pa7UV7+B+mPu24kLZT0MvAssIDUtn02KXk9IeluSWV+ptZFRcSiiJgQEXsD25G+aOt9C+yodYaT+0LK+DW/BunakJ6kM6DK42XSkN+6cJ9I93UpcLOkC/PyoZQz5XzF+hExQdKJABGxWFJd24Ajok9b61R106b8r9ly8rVanwPGkG5LXe/bBzwm6aDWk6pK+jzw9zrHIiJuA26TdFFEzCzrQl8nkW4qIr6fRzF9NBedFhE3lhjyVUkDWDaEchTpgsOGiPJv2mRdmKQZwP2kWSKOi4hX239FIUcBv5f0BdLcWZBumLYW8OkS4lUMlHQd+UJfSXW90Nd9It1YvrJ7WETclNuEW8oapZWH+v6MdBbwCOl+8vtGxENlxDNbGZL6RsTLDYq1K8uuWXosIm4uOd5DwFGtLvQ9p17TADmJdFOSvggcAfSPiHdJGgb8st79MFr+lr89gfeQOryfiIg36xnLrChJg0k/cnbORX8Fjo2I2c2rVX2UPYjGHevd11GkA+ZlgIiYCryzhDh/qHp+ZUQ8GhGPOIFYJ3MhcC1p4MdGpPuKXNjuK7qO2ySdK+nDkj4k6RzS/UVGVF0MXJj7RLqv1yPijcp8OvksoYzT0uoLJ0u9Ct9sFQyMiOqkcZGkuo4ebKLKUN7Wt2PYjnTM77oqO3cS6b5uk3QSsJakjwFHkn591Vu08dysM3khj5K6PC+PA15oYn3qpux5+Nwn0k1J6gEcRrqTm0jXcPy63lfq5mG8r+YYawGVm+KsbrPAWheWB5n8jHQ74ADuJM0v9XRTK1YHZV/o6yTSjUkaCBARc5tdFzMrh9K91S8ETo6IbXLT9f0RsXU99u/mrG5GqRPkFOAr5IEV+WzhZxFxajPrZtZokr7VzuqIiNMaVpnylHqhr0dndT9fJY3K2j4i+kdEf2BHYGdJX21u1cwa7tUaD0hNvcc3q1J1VuqFvm7O6mYk3Q98LCLmtSofCPy5rFt0mnV2eUbdY0kJZALwo4h4vrm1WnVlX+jrM5Hup1frBAJv9Yv0akJ9zJpKUn9J3wEeIjXxj4iI47t6ApG0vaQNIuI+0g2wTgJeJ92Uqm4XUTqJdD9vFFxnttqR9ENgErAQ2Doivh0RLza5WvVyLsuO6Q8AJwM/J81ufV69grg5q5upGnL7tlVA74jw2Yh1G/n21K8Di1n+OqYuPwRd0oOVe4ZI+jkwNyK+nZcfiIht6xHHo7O6mYhoaXYdzDqLiFidW2NaJPWMiMXAaNJceRV1++53EjEzWz1dTpqZYh7wL9KkkkjaAo/OMjOzFcnDeTckjbx8NZe9G1g3d7ivegwnETMzK2p1bg80M7OSOYmYmVlhTiJmDSApJP2marmnpLn53tdmXZaTiFljvApsJWmtvPwxYE4T62NWF04iZo1zPfDx/Hwcy26AhKR1JF0g6V5J90sam8vfn8sekPSQpGFNqLdZm5xEzBrnCmA/Sb2B4cA9VetOBm6JiB2AjwA/lLQO8GXgrHx18UjqOOeRWT34YkOzBomIhyQNIZ2FXN9q9W7AJyX9V17uDWwK3AWcLGkw8PuImNqg6pp1iJOIWWNdC5wBfBgYUFUuYJ+IeKLV9o9LuofUDHa9pC9FxC0NqalZB7g5y6yxLgD+JyIeblV+I3B0vvMkkrbL/24OTI+InwLXkJrBzDoNJxGzBoqI2TkhtHYa6X4uD0l6NC8DfBZ4RNIDpJsKjW9MTc06xtOemJlZYT4TMTOzwpxEzMysMCcRMzMrzEnEzMwKcxIxM7PCnETMzKwwJxEzMyvMScTMzAr7f3floj3CY2xCAAAAAElFTkSuQmCC\n"},"metadata":{"needs_background":"light"}}],"execution_count":10},{"cell_type":"code","source":"grafico_df=data3[['total_stay','customer_type']].groupby('customer_type').count()\ngrafico_df\nimport seaborn as sns\nimport matplotlib.pyplot as plt\ngrafico_df.plot(kind='bar')\nplt.title('Distribucion de noches por mes')\nplt.xlabel('Tipo de cliente')\nplt.ylabel('Frecuencia')","metadata":{"id":"AWPfY6Re8THa","colab":{"height":377,"base_uri":"https://localhost:8080/"},"cell_id":"bd420055cde64e1ebd661b416dafb13f","outputId":"f002ff99-b223-4c02-f45c-d7f9df146c8a","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":330,"user_tz":180,"timestamp":1650392629719},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Text(0, 0.5, 'Frecuencia')"},"metadata":{},"execution_count":11},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"execution_count":11},{"cell_type":"markdown","source":"Histogramas de las variables:","metadata":{"id":"tjw4zBrL1KAY","cell_id":"62f2d0b612d042618f0a1f65da72eed0","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"import matplotlib.pyplot as plt\nfig = plt.figure(figsize = (20,12)) #Definimos el tamaño del grafico\ndata3.hist(ax = fig.gca()) #Realizamos el histograma de las variables","metadata":{"id":"oaSQ1wKW1KAZ","colab":{"height":837,"base_uri":"https://localhost:8080/"},"cell_id":"7c3d5daf420645fc9409a8aea251793d","outputId":"476bd4c9-486b-4af3-b1f8-8b7b9995ffa9","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":1077,"user_tz":180,"timestamp":1650392630787},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stderr","text":"/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:3: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared\n  This is separate from the ipykernel package so we can avoid doing imports until\n"},{"output_type":"execute_result","data":{"text/plain":"array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7fed04768050>,\n        <matplotlib.axes._subplots.AxesSubplot object at 0x7fed046f6c50>],\n       [<matplotlib.axes._subplots.AxesSubplot object at 0x7fed046b6fd0>,\n        <matplotlib.axes._subplots.AxesSubplot object at 0x7fed04670890>]],\n      dtype=object)"},"metadata":{},"execution_count":12},{"output_type":"display_data","data":{"text/plain":"<Figure size 1440x864 with 4 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\n"},"metadata":{"needs_background":"light"}}],"execution_count":12},{"cell_type":"code","source":"data3.deposit_type.unique()","metadata":{"id":"RMviQ65mAUxM","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"dc99b1a25dd24c3ca8f517448b5c1f6a","outputId":"e3f1c15a-d800-4ae3-d8b4-1e7b84338f85","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":5,"user_tz":180,"timestamp":1650392632078},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"array(['No Deposit', 'Refundable', 'Non Refund'], dtype=object)"},"metadata":{},"execution_count":13}],"execution_count":13},{"cell_type":"code","source":"data3.customer_type.unique()","metadata":{"id":"uhAut9lhAbvF","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"6a6055462a2f4b7f8718cb592ca887eb","outputId":"605af3b3-e97e-47b6-d8d2-4ea130021ed9","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":6,"user_tz":180,"timestamp":1650392632764},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"array(['Transient', 'Contract', 'Transient-Party', 'Group'], dtype=object)"},"metadata":{},"execution_count":14}],"execution_count":14},{"cell_type":"code","source":"#Hacemos dummies las variables!\ndata4=pd.get_dummies(data3, drop_first=False)","metadata":{"id":"_-jDTe0s1KAa","cell_id":"4c895356af634013a33ca1a6682f696f","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":444,"user_tz":180,"timestamp":1650392634058},"deepnote_cell_type":"code"},"outputs":[],"execution_count":15},{"cell_type":"code","source":"data4.head()","metadata":{"id":"U-yd6gAY1KAb","colab":{"height":317,"base_uri":"https://localhost:8080/"},"cell_id":"1db088fdce6d4b888ab80d6686fd0d04","outputId":"eee70cc9-8b68-427a-ab9e-ea7f0b38560f","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":344,"user_tz":180,"timestamp":1650392641580},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"   total_of_special_requests  required_car_parking_spaces  \\\n0                          0                            0   \n1                          0                            0   \n2                          0                            0   \n3                          0                            0   \n4                          1                            0   \n\n   arrival_date_day_of_month  total_stay  deposit_type_No Deposit  \\\n0                          1           0                        1   \n1                          1           0                        1   \n2                          1           1                        1   \n3                          1           1                        1   \n4                          1           2                        1   \n\n   deposit_type_Non Refund  deposit_type_Refundable  customer_type_Contract  \\\n0                        0                        0                       0   \n1                        0                        0                       0   \n2                        0                        0                       0   \n3                        0                        0                       0   \n4                        0                        0                       0   \n\n   customer_type_Group  customer_type_Transient  ...  \\\n0                    0                        1  ...   \n1                    0                        1  ...   \n2                    0                        1  ...   \n3                    0                        1  ...   \n4                    0                        1  ...   \n\n   arrival_date_month_January  arrival_date_month_July  \\\n0                           0                        1   \n1                           0                        1   \n2                           0                        1   \n3                           0                        1   \n4                           0                        1   \n\n   arrival_date_month_June  arrival_date_month_March  arrival_date_month_May  \\\n0                        0                         0                       0   \n1                        0                         0                       0   \n2                        0                         0                       0   \n3                        0                         0                       0   \n4                        0                         0                       0   \n\n   arrival_date_month_November  arrival_date_month_October  \\\n0                            0                           0   \n1                            0                           0   \n2                            0                           0   \n3                            0                           0   \n4                            0                           0   \n\n   arrival_date_month_September  hotel_City Hotel  hotel_Resort Hotel  \n0                             0                 0                   1  \n1                             0                 0                   1  \n2                             0                 0                   1  \n3                             0                 0                   1  \n4                             0                 0                   1  \n\n[5 rows x 25 columns]","text/html":"\n  <div id=\"df-72f101b9-2aca-447c-bb69-25446bbfc7e1\">\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>total_of_special_requests</th>\n      <th>required_car_parking_spaces</th>\n      <th>arrival_date_day_of_month</th>\n      <th>total_stay</th>\n      <th>deposit_type_No Deposit</th>\n      <th>deposit_type_Non Refund</th>\n      <th>deposit_type_Refundable</th>\n      <th>customer_type_Contract</th>\n      <th>customer_type_Group</th>\n      <th>customer_type_Transient</th>\n      <th>...</th>\n      <th>arrival_date_month_January</th>\n      <th>arrival_date_month_July</th>\n      <th>arrival_date_month_June</th>\n      <th>arrival_date_month_March</th>\n      <th>arrival_date_month_May</th>\n      <th>arrival_date_month_November</th>\n      <th>arrival_date_month_October</th>\n      <th>arrival_date_month_September</th>\n      <th>hotel_City Hotel</th>\n      <th>hotel_Resort Hotel</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\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>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>...</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>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\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>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>...</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>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>...</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>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>...</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>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>...</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>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 25 columns</p>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-72f101b9-2aca-447c-bb69-25446bbfc7e1')\"\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     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'block' : 'none';\n\n        async function convertToInteractive(key) {\n          const element = document.querySelector('#df-72f101b9-2aca-447c-bb69-25446bbfc7e1');\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  "},"metadata":{},"execution_count":16}],"execution_count":16},{"cell_type":"code","source":"#Separamos los datos de entrada de los de salida\nX_data=data4.drop('total_stay', axis=1)\ny_data=data4['total_stay']","metadata":{"id":"BHkfvFQM1KAc","cell_id":"ee03ddadd2cc4af0a8c1650e4be229cb","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":493,"user_tz":180,"timestamp":1650392644070},"deepnote_cell_type":"code"},"outputs":[],"execution_count":17},{"cell_type":"code","source":"#Separamos los datos en train y test\nfrom sklearn.model_selection import train_test_split\n\nX_train, X_test, y_train, y_test = train_test_split(X_data, y_data, test_size=0.3)","metadata":{"id":"Z47t5vrT1KAc","cell_id":"cb21ae7f14aa426d8db9c5b65d8254a4","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":286,"user_tz":180,"timestamp":1650392645450},"deepnote_cell_type":"code"},"outputs":[],"execution_count":18},{"cell_type":"code","source":"#Hypertuning utilizando grid search\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.ensemble import RandomForestRegressor \n\nrandom_forest = RandomForestRegressor() #Instanciamos el modelo","metadata":{"id":"JbgvI9431KAd","cell_id":"f1332d521fd0436cb1841bc6b34e4e38","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":674,"user_tz":180,"timestamp":1650392647262},"deepnote_cell_type":"code"},"outputs":[],"execution_count":19},{"cell_type":"code","source":"#Definimos los parámetros de búsqueda\nparams = {\n    'n_estimators' : [50,100,200],\n    'max_features': [2,4,5],\n    'criterion': ['squared_error', 'mse', 'absolute_error', 'poisson'],\n    'max_depth':[4,5]\n}\n\ngrid_random_forest = GridSearchCV(estimator = random_forest,\n                                  param_grid = params,\n                                  scoring = 'neg_mean_absolute_error',  # \n                                  cv = 5, \n                                  verbose = 1, #Muestra el resultado en pantalla\n                                  n_jobs = -1) # corrida en paralelo","metadata":{"id":"qyONXzET1KAd","cell_id":"ff6620120b824021848c90ae34a56199","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":2,"user_tz":180,"timestamp":1650392648259},"deepnote_cell_type":"code"},"outputs":[],"execution_count":20},{"cell_type":"code","source":"%%time\n#Entrenamos el modelo (Se demora bastante!!!!!!)\ngrid_random_forest.fit(X_train, y_train)","metadata":{"id":"CFrJP-sq1KAd","cell_id":"42d47e947231442798344448d6fb7353","deepnote_cell_type":"code"},"outputs":[],"execution_count":null},{"cell_type":"code","source":"#Obtenemos el mejor modelo!\ngrid_random_forest.best_estimator_","metadata":{"id":"OwLafBhD1KAe","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"b2f9e985f1cd449fb26475d27c883a7a","outputId":"5a6decd5-cc9c-4d7e-a286-a119fbe0d4ce","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":367,"user_tz":300,"timestamp":1632777268445},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\n                      max_depth=5, max_features=5, max_leaf_nodes=None,\n                      max_samples=None, min_impurity_decrease=0.0,\n                      min_impurity_split=None, min_samples_leaf=1,\n                      min_samples_split=2, min_weight_fraction_leaf=0.0,\n                      n_estimators=100, n_jobs=None, oob_score=False,\n                      random_state=None, verbose=0, warm_start=False)"},"metadata":{},"execution_count":36}],"execution_count":null},{"cell_type":"code","source":"grid_random_forest.best_params_","metadata":{"id":"S1m46oc6HK8w","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"257a938861e643858713e5e527251791","outputId":"e4063aeb-1629-439e-cbee-0933c4e96fca","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":358,"user_tz":300,"timestamp":1632777550613},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"{'criterion': 'mse', 'max_depth': 5, 'max_features': 5, 'n_estimators': 100}"},"metadata":{},"execution_count":45}],"execution_count":null},{"cell_type":"code","source":"random_forest_nuevo = RandomForestRegressor(criterion='mse',max_depth=5, max_features= 5, n_estimators=100) #Instanciamos el modelo","metadata":{"id":"fhZJhQxtILbo","cell_id":"d743b46209a448f0b52b178c76166935","deepnote_cell_type":"code"},"outputs":[],"execution_count":null},{"cell_type":"code","source":"random_forest_nuevo.fit(X_train,y_train)","metadata":{"id":"PH0bEGxEIVdF","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"e180df98c78e4de2a4389947edb9ee35","outputId":"d3973e9c-91a3-4d1f-fca7-b79ea89f66ff","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":2483,"user_tz":300,"timestamp":1632777637143},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\n                      max_depth=5, max_features=5, max_leaf_nodes=None,\n                      max_samples=None, min_impurity_decrease=0.0,\n                      min_impurity_split=None, min_samples_leaf=1,\n                      min_samples_split=2, min_weight_fraction_leaf=0.0,\n                      n_estimators=100, n_jobs=None, oob_score=False,\n                      random_state=None, verbose=0, warm_start=False)"},"metadata":{},"execution_count":47}],"execution_count":null},{"cell_type":"code","source":"X_train.shape","metadata":{"id":"wR5uuP1tIdMO","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"cfbc268dbd6346f29013cfbce135eeff","outputId":"8ddda6b4-476f-4731-ac4f-751fb3ad16f9","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":386,"user_tz":300,"timestamp":1632777661616},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"(83573, 24)"},"metadata":{},"execution_count":50}],"execution_count":null},{"cell_type":"code","source":"X_test=X_test.drop(columns=['Prediccion'])\nX_test","metadata":{"id":"7hqfXViJImVh","colab":{"height":454,"base_uri":"https://localhost:8080/"},"cell_id":"db494d802c084099843c0177f6fdbc1a","outputId":"4008815b-a739-41ac-e828-c78052eb5a79","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":369,"user_tz":300,"timestamp":1632777739101},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>total_of_special_requests</th>\n      <th>required_car_parking_spaces</th>\n      <th>arrival_date_day_of_month</th>\n      <th>deposit_type_No Deposit</th>\n      <th>deposit_type_Non Refund</th>\n      <th>deposit_type_Refundable</th>\n      <th>customer_type_Contract</th>\n      <th>customer_type_Group</th>\n      <th>customer_type_Transient</th>\n      <th>customer_type_Transient-Party</th>\n      <th>arrival_date_month_April</th>\n      <th>arrival_date_month_August</th>\n      <th>arrival_date_month_December</th>\n      <th>arrival_date_month_February</th>\n      <th>arrival_date_month_January</th>\n      <th>arrival_date_month_July</th>\n      <th>arrival_date_month_June</th>\n      <th>arrival_date_month_March</th>\n      <th>arrival_date_month_May</th>\n      <th>arrival_date_month_November</th>\n      <th>arrival_date_month_October</th>\n      <th>arrival_date_month_September</th>\n      <th>hotel_City Hotel</th>\n      <th>hotel_Resort Hotel</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>88645</th>\n      <td>0</td>\n      <td>0</td>\n      <td>7</td>\n      <td>1</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>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>115346</th>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</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>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>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>81707</th>\n      <td>0</td>\n      <td>0</td>\n      <td>21</td>\n      <td>0</td>\n      <td>1</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>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>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>14952</th>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</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>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>1</td>\n    </tr>\n    <tr>\n      <th>61982</th>\n      <td>0</td>\n      <td>0</td>\n      <td>29</td>\n      <td>1</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>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>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>21811</th>\n      <td>0</td>\n      <td>0</td>\n      <td>9</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>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>1</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    </tr>\n    <tr>\n      <th>108990</th>\n      <td>1</td>\n      <td>0</td>\n      <td>3</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>1</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>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>63933</th>\n      <td>0</td>\n      <td>0</td>\n      <td>25</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>1</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>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>96754</th>\n      <td>1</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</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>1</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>84834</th>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</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>1</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    </tr>\n  </tbody>\n</table>\n<p>35817 rows × 24 columns</p>\n</div>","text/plain":"        total_of_special_requests  ...  hotel_Resort Hotel\n88645                           0  ...                   0\n115346                          0  ...                   0\n81707                           0  ...                   0\n14952                           0  ...                   1\n61982                           0  ...                   0\n...                           ...  ...                 ...\n21811                           0  ...                   1\n108990                          1  ...                   0\n63933                           0  ...                   0\n96754                           1  ...                   0\n84834                           0  ...                   0\n\n[35817 rows x 24 columns]"},"metadata":{},"execution_count":53}],"execution_count":null},{"cell_type":"code","source":"#Predicción de casos nuevos\nrandom_forest_nuevo.predict(X_train)\nrandom_forest_nuevo.predict(X_test)","metadata":{"id":"Hyk_4-0Z1KAe","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"3429345d924e4fa7a1997fc90eb5833e","outputId":"43a62d26-9a17-4752-c06c-89a00f020071","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":851,"user_tz":300,"timestamp":1632777743534},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"array([3.11173552, 3.20761548, 2.66031522, ..., 2.75972258, 3.16871809,\n       3.17148881])"},"metadata":{},"execution_count":54}],"execution_count":null},{"cell_type":"code","source":"import numpy as np\nX_test1= X_test.copy()\nX_test1['Prediccion']=np.round(random_forest_nuevo.predict(X_test),0)\nX_test1","metadata":{"id":"bfB6C-WoHVgk","colab":{"height":454,"base_uri":"https://localhost:8080/"},"cell_id":"46115aace6b64f7bb687060c48d09031","outputId":"85f8b72d-d533-4dad-be90-0922eb8633ac","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":8,"user_tz":300,"timestamp":1632777813412},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>total_of_special_requests</th>\n      <th>required_car_parking_spaces</th>\n      <th>arrival_date_day_of_month</th>\n      <th>deposit_type_No Deposit</th>\n      <th>deposit_type_Non Refund</th>\n      <th>deposit_type_Refundable</th>\n      <th>customer_type_Contract</th>\n      <th>customer_type_Group</th>\n      <th>customer_type_Transient</th>\n      <th>customer_type_Transient-Party</th>\n      <th>arrival_date_month_April</th>\n      <th>arrival_date_month_August</th>\n      <th>arrival_date_month_December</th>\n      <th>arrival_date_month_February</th>\n      <th>arrival_date_month_January</th>\n      <th>arrival_date_month_July</th>\n      <th>arrival_date_month_June</th>\n      <th>arrival_date_month_March</th>\n      <th>arrival_date_month_May</th>\n      <th>arrival_date_month_November</th>\n      <th>arrival_date_month_October</th>\n      <th>arrival_date_month_September</th>\n      <th>hotel_City Hotel</th>\n      <th>hotel_Resort Hotel</th>\n      <th>Prediccion</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>88645</th>\n      <td>0</td>\n      <td>0</td>\n      <td>7</td>\n      <td>1</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>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>3.0</td>\n    </tr>\n    <tr>\n      <th>115346</th>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</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>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>1</td>\n      <td>0</td>\n      <td>3.0</td>\n    </tr>\n    <tr>\n      <th>81707</th>\n      <td>0</td>\n      <td>0</td>\n      <td>21</td>\n      <td>0</td>\n      <td>1</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>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>1</td>\n      <td>0</td>\n      <td>3.0</td>\n    </tr>\n    <tr>\n      <th>14952</th>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</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>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>1</td>\n      <td>5.0</td>\n    </tr>\n    <tr>\n      <th>61982</th>\n      <td>0</td>\n      <td>0</td>\n      <td>29</td>\n      <td>1</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>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>1</td>\n      <td>0</td>\n      <td>3.0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>21811</th>\n      <td>0</td>\n      <td>0</td>\n      <td>9</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>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>1</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>4.0</td>\n    </tr>\n    <tr>\n      <th>108990</th>\n      <td>1</td>\n      <td>0</td>\n      <td>3</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>1</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>1</td>\n      <td>0</td>\n      <td>3.0</td>\n    </tr>\n    <tr>\n      <th>63933</th>\n      <td>0</td>\n      <td>0</td>\n      <td>25</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>1</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>1</td>\n      <td>0</td>\n      <td>3.0</td>\n    </tr>\n    <tr>\n      <th>96754</th>\n      <td>1</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</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>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>3.0</td>\n    </tr>\n    <tr>\n      <th>84834</th>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</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>1</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>3.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>35817 rows × 25 columns</p>\n</div>","text/plain":"        total_of_special_requests  ...  Prediccion\n88645                           0  ...         3.0\n115346                          0  ...         3.0\n81707                           0  ...         3.0\n14952                           0  ...         5.0\n61982                           0  ...         3.0\n...                           ...  ...         ...\n21811                           0  ...         4.0\n108990                          1  ...         3.0\n63933                           0  ...         3.0\n96754                           1  ...         3.0\n84834                           0  ...         3.0\n\n[35817 rows x 25 columns]"},"metadata":{},"execution_count":58}],"execution_count":null},{"cell_type":"markdown","source":"Sólo nos restaría analizar las métricas de error, pero ese tema lo veremos en la sección correspondiente 😉","metadata":{"id":"LqxI1_KF1KAe","cell_id":"c64a8a0aa3f8431e9fa86834a69a3282","deepnote_cell_type":"markdown"}},{"cell_type":"markdown","source":"<a style='text-decoration:none;line-height:16px;display:flex;color:#5B5B62;padding:10px;justify-content:end;' href='https://deepnote.com?utm_source=created-in-deepnote-cell&projectId=4f9037d8-f2e9-4683-9ce3-67576f784ec7' target=\"_blank\">\n<img alt='Created in deepnote.com' style='display:inline;max-height:16px;margin:0px;margin-right:7.5px;' src='data:image/svg+xml;base64,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' > </img>\nCreated in <span style='font-weight:600;margin-left:4px;'>Deepnote</span></a>","metadata":{"created_in_deepnote_cell":true,"deepnote_cell_type":"markdown"}}],"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Ejemplo 3-Hypertuning.ipynb","provenance":[],"collapsed_sections":[]},"deepnote":{},"kernelspec":{"name":"python3","language":"python","display_name":"Python 3"},"varInspector":{"cols":{"lenVar":40,"lenName":16,"lenType":16},"kernels_config":{"r":{"library":"var_list.r","varRefreshCmd":"cat(var_dic_list()) ","delete_cmd_prefix":"rm(","delete_cmd_postfix":") "},"python":{"library":"var_list.py","varRefreshCmd":"print(var_dic_list())","delete_cmd_prefix":"del ","delete_cmd_postfix":""}},"window_display":false,"types_to_exclude":["module","function","builtin_function_or_method","instance","_Feature"]},"language_info":{"name":"python","version":"3.8.5","mimetype":"text/x-python","file_extension":".py","pygments_lexer":"ipython3","codemirror_mode":{"name":"ipython","version":3},"nbconvert_exporter":"python"},"deepnote_notebook_id":"23af332f1d69442ea3709d1f6ca375dd","deepnote_execution_queue":[]}}