01 - exploración de datos.ipynb

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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/lauratobon/Ai_Porject_2023/blob/main/01%20-%20exploraci%C3%B3n%20de%20datos.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fdcq0rGz2L5U"
      },
      "outputs": [],
      "source": [
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.ticker as mtick\n",
        "import matplotlib.pyplot as plt\n",
        "import missingno as msno\n",
        "#bibliotecas de machine learning\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.tree import DecisionTreeRegressor\n",
        "from sklearn.ensemble import RandomForestRegressor\n",
        "from sklearn.model_selection import cross_validate, ShuffleSplit\n",
        "\n",
        "from sklearn.model_selection import learning_curve\n",
        "from sklearn.metrics import mean_squared_error\n",
        "from sklearn.impute import SimpleImputer\n",
        "from sklearn.preprocessing import OneHotEncoder\n",
        "from sklearn.preprocessing import FunctionTransformer\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.compose import ColumnTransformer\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "from sklearn import utils\n",
        "from sklearn import preprocessing\n",
        "from sklearn.model_selection import train_test_split,KFold,GroupKFold\n",
        "import lightgbm as lgb\n",
        "import gc"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# install kaggle\n",
        "!pip install -q kaggle"
      ],
      "metadata": {
        "id": "S-fi0m8m4o7D"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#used to upload the kaggle API token json file\n",
        "from google.colab import files\n",
        "files.upload()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 90
        },
        "id": "wER5hvkX4swr",
        "outputId": "6dd5add6-19c5-4b2a-8774-f0759c2e67b4"
      },
      "execution_count": null,
      "outputs": [
        {
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              "      Upload widget is only available when the cell has been executed in the\n",
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              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
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              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
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              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
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              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
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              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
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              "  cancel.remove();\n",
              "\n",
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              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
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              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
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              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving kaggle.json to kaggle.json\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'kaggle.json': b'{\"username\":\"juandavidarismendy\",\"key\":\"4df590bf4ce3f6e0a95b9c5e15fb285c\"}'}"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# create a kaggle folder\n",
        "! mkdir ~/.kaggle"
      ],
      "metadata": {
        "id": "EroVW-U1422N"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# copy the kaggle.json to folder created\n",
        "! cp kaggle.json ~/.kaggle/"
      ],
      "metadata": {
        "id": "9mjKyBdU536O"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# permission for the json to act\n",
        "! chmod 600 ~/.kaggle/kaggle.json"
      ],
      "metadata": {
        "id": "GBZmMz1j6Br7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# to list all datasets in kaggle\n",
        "! kaggle datasets list"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qVQ6Z8c06F--",
        "outputId": "55dda2ce-8eaf-4b83-eae4-fb1963c8a140"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "ref                                                               title                                              size  lastUpdated          downloadCount  voteCount  usabilityRating  \n",
            "----------------------------------------------------------------  ------------------------------------------------  -----  -------------------  -------------  ---------  ---------------  \n",
            "salvatorerastelli/spotify-and-youtube                             Spotify and Youtube                                 9MB  2023-03-20 15:43:25           8977        328  1.0              \n",
            "ppb00x/country-gdp                                                Country_GDP                                         7KB  2023-04-07 06:47:36           1370         39  1.0              \n",
            "erdemtaha/cancer-data                                             Cancer Data                                        49KB  2023-03-22 07:57:00           4150         97  1.0              \n",
            "omartorres25/honda-data                                           Honda Cars Data                                   184KB  2023-03-28 04:19:11           1515         34  1.0              \n",
            "lokeshparab/amazon-products-dataset                               Amazon Products Sales Dataset 2023                 80MB  2023-03-26 10:45:19           4552         93  1.0              \n",
            "ulrikthygepedersen/fastfood-nutrition                             Fastfood Nutrition                                 12KB  2023-03-21 10:02:41           3689         71  1.0              \n",
            "ppb00x/credit-risk-customers                                      credit_risk_customers                              18KB  2023-04-12 08:28:28           1375         41  1.0              \n",
            "arnabchaki/data-science-salaries-2023                             Data Science Salaries 2023  💸                      25KB  2023-04-13 09:55:16           2321         66  1.0              \n",
            "kapturovalexander/nvidia-amd-intel-asus-msi-share-prices          NVIDIA, AMD, Intel, ASUS, MSI share prices (GPU)  902KB  2023-04-13 12:15:18            587         38  1.0              \n",
            "rkiattisak/student-performance-in-mathematics                     Student performance prediction                      9KB  2023-03-12 04:32:56           9543        206  1.0              \n",
            "ashishraut64/internet-users                                       Global Internet users                             163KB  2023-03-29 12:25:13           2455         62  1.0              \n",
            "rkiattisak/smart-watch-prices                                     Smart Watch prices                                  5KB  2023-04-12 06:04:23            714         23  1.0              \n",
            "arnabchaki/popular-video-games-1980-2023                          Popular Video Games 1980 - 2023 🎮                   1MB  2023-03-23 16:16:51           4062        113  1.0              \n",
            "ashishraut64/global-methane-emissions                             Global Emissions.                                  31KB  2023-03-27 09:02:51           2952         59  1.0              \n",
            "tayyarhussain/best-selling-game-consoles-of-all-time              Best-Selling Gaming Consoles Dataset                1KB  2023-04-01 10:59:00           1064         36  1.0              \n",
            "shrutiambekar/smartphone-specifications-and-prices-in-india       Smartphone Specifications and Prices in India      36KB  2023-04-13 06:13:13            547         23  1.0              \n",
            "kapturovalexander/bitcoin-and-ethereum-prices-from-start-to-2023  Bitcoin & Ethereum prices (from start to 2023)    149KB  2023-04-09 06:07:57            895         32  1.0              \n",
            "r1chardson/the-world-university-rankings-2011-2023                THE World University Rankings 2011-2023             1MB  2023-04-03 12:43:37           2209         51  1.0              \n",
            "dgoenrique/netflix-movies-and-tv-shows                            Netflix Movies and TV Shows                         2MB  2023-03-13 18:49:00           4179         99  1.0              \n",
            "dansbecker/melbourne-housing-snapshot                             Melbourne Housing Snapshot                        451KB  2018-06-05 12:52:24         113371       1249  0.7058824        \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!kaggle datasets download -d jessemostipak/hotel-booking-demand"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GH3Zq5M-6UqS",
        "outputId": "435e21b3-f780-470e-f2be-c41d84d5ee0e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading hotel-booking-demand.zip to /content\n",
            "\r  0% 0.00/1.25M [00:00<?, ?B/s]\n",
            "\r100% 1.25M/1.25M [00:00<00:00, 90.7MB/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!unzip hotel-booking-demand.zip"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9bxLCpOr7lnG",
        "outputId": "0aef1834-5d50-4cfb-a60e-8d99010d181a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  hotel-booking-demand.zip\n",
            "  inflating: hotel_bookings.csv      \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **1. Lectura y carga del dataset**"
      ],
      "metadata": {
        "id": "aMicdK2e8Ic1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# upload data\n",
        "data=pd.read_csv('hotel_bookings.csv')"
      ],
      "metadata": {
        "id": "KZGsNdxN78qh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# view the dataset\n",
        "data\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 661
        },
        "id": "ebrOp9ve8Viw",
        "outputId": "fa17348b-6f7a-4dcf-f8ec-6e70274bf717"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               hotel  is_canceled  lead_time  arrival_date_year  \\\n",
              "0       Resort Hotel            0        342               2015   \n",
              "1       Resort Hotel            0        737               2015   \n",
              "2       Resort Hotel            0          7               2015   \n",
              "3       Resort Hotel            0         13               2015   \n",
              "4       Resort Hotel            0         14               2015   \n",
              "...              ...          ...        ...                ...   \n",
              "119385    City Hotel            0         23               2017   \n",
              "119386    City Hotel            0        102               2017   \n",
              "119387    City Hotel            0         34               2017   \n",
              "119388    City Hotel            0        109               2017   \n",
              "119389    City Hotel            0        205               2017   \n",
              "\n",
              "       arrival_date_month  arrival_date_week_number  \\\n",
              "0                    July                        27   \n",
              "1                    July                        27   \n",
              "2                    July                        27   \n",
              "3                    July                        27   \n",
              "4                    July                        27   \n",
              "...                   ...                       ...   \n",
              "119385             August                        35   \n",
              "119386             August                        35   \n",
              "119387             August                        35   \n",
              "119388             August                        35   \n",
              "119389             August                        35   \n",
              "\n",
              "        arrival_date_day_of_month  stays_in_weekend_nights  \\\n",
              "0                               1                        0   \n",
              "1                               1                        0   \n",
              "2                               1                        0   \n",
              "3                               1                        0   \n",
              "4                               1                        0   \n",
              "...                           ...                      ...   \n",
              "119385                         30                        2   \n",
              "119386                         31                        2   \n",
              "119387                         31                        2   \n",
              "119388                         31                        2   \n",
              "119389                         29                        2   \n",
              "\n",
              "        stays_in_week_nights  adults  ...  deposit_type  agent company  \\\n",
              "0                          0       2  ...    No Deposit    NaN     NaN   \n",
              "1                          0       2  ...    No Deposit    NaN     NaN   \n",
              "2                          1       1  ...    No Deposit    NaN     NaN   \n",
              "3                          1       1  ...    No Deposit  304.0     NaN   \n",
              "4                          2       2  ...    No Deposit  240.0     NaN   \n",
              "...                      ...     ...  ...           ...    ...     ...   \n",
              "119385                     5       2  ...    No Deposit  394.0     NaN   \n",
              "119386                     5       3  ...    No Deposit    9.0     NaN   \n",
              "119387                     5       2  ...    No Deposit    9.0     NaN   \n",
              "119388                     5       2  ...    No Deposit   89.0     NaN   \n",
              "119389                     7       2  ...    No Deposit    9.0     NaN   \n",
              "\n",
              "       days_in_waiting_list customer_type     adr  \\\n",
              "0                         0     Transient    0.00   \n",
              "1                         0     Transient    0.00   \n",
              "2                         0     Transient   75.00   \n",
              "3                         0     Transient   75.00   \n",
              "4                         0     Transient   98.00   \n",
              "...                     ...           ...     ...   \n",
              "119385                    0     Transient   96.14   \n",
              "119386                    0     Transient  225.43   \n",
              "119387                    0     Transient  157.71   \n",
              "119388                    0     Transient  104.40   \n",
              "119389                    0     Transient  151.20   \n",
              "\n",
              "        required_car_parking_spaces  total_of_special_requests  \\\n",
              "0                                 0                          0   \n",
              "1                                 0                          0   \n",
              "2                                 0                          0   \n",
              "3                                 0                          0   \n",
              "4                                 0                          1   \n",
              "...                             ...                        ...   \n",
              "119385                            0                          0   \n",
              "119386                            0                          2   \n",
              "119387                            0                          4   \n",
              "119388                            0                          0   \n",
              "119389                            0                          2   \n",
              "\n",
              "        reservation_status reservation_status_date  \n",
              "0                Check-Out              2015-07-01  \n",
              "1                Check-Out              2015-07-01  \n",
              "2                Check-Out              2015-07-02  \n",
              "3                Check-Out              2015-07-02  \n",
              "4                Check-Out              2015-07-03  \n",
              "...                    ...                     ...  \n",
              "119385           Check-Out              2017-09-06  \n",
              "119386           Check-Out              2017-09-07  \n",
              "119387           Check-Out              2017-09-07  \n",
              "119388           Check-Out              2017-09-07  \n",
              "119389           Check-Out              2017-09-07  \n",
              "\n",
              "[119390 rows x 32 columns]"
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>0.00</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>0.00</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>75.00</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>75.00</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>98.00</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-03</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119385</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>23</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>30</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>394.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>96.14</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119386</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>102</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>31</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>225.43</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119387</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>34</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>31</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>157.71</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119388</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>109</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>31</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>89.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>104.40</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119389</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>205</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>29</td>\n",
              "      <td>2</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>9.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>151.20</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>119390 rows × 32 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4ce57069-69a2-4c45-bef4-b6b3c5f54db0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "            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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zOKde-cL8twA",
        "outputId": "2cf0a56c-151f-4fa4-96c5-fe38cfdabc93"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 119390 entries, 0 to 119389\n",
            "Data columns (total 32 columns):\n",
            " #   Column                          Non-Null Count   Dtype  \n",
            "---  ------                          --------------   -----  \n",
            " 0   hotel                           119390 non-null  object \n",
            " 1   is_canceled                     119390 non-null  int64  \n",
            " 2   lead_time                       119390 non-null  int64  \n",
            " 3   arrival_date_year               119390 non-null  int64  \n",
            " 4   arrival_date_month              119390 non-null  object \n",
            " 5   arrival_date_week_number        119390 non-null  int64  \n",
            " 6   arrival_date_day_of_month       119390 non-null  int64  \n",
            " 7   stays_in_weekend_nights         119390 non-null  int64  \n",
            " 8   stays_in_week_nights            119390 non-null  int64  \n",
            " 9   adults                          119390 non-null  int64  \n",
            " 10  children                        119386 non-null  float64\n",
            " 11  babies                          119390 non-null  int64  \n",
            " 12  meal                            119390 non-null  object \n",
            " 13  country                         118902 non-null  object \n",
            " 14  market_segment                  119390 non-null  object \n",
            " 15  distribution_channel            119390 non-null  object \n",
            " 16  is_repeated_guest               119390 non-null  int64  \n",
            " 17  previous_cancellations          119390 non-null  int64  \n",
            " 18  previous_bookings_not_canceled  119390 non-null  int64  \n",
            " 19  reserved_room_type              119390 non-null  object \n",
            " 20  assigned_room_type              119390 non-null  object \n",
            " 21  booking_changes                 119390 non-null  int64  \n",
            " 22  deposit_type                    119390 non-null  object \n",
            " 23  agent                           103050 non-null  float64\n",
            " 24  company                         6797 non-null    float64\n",
            " 25  days_in_waiting_list            119390 non-null  int64  \n",
            " 26  customer_type                   119390 non-null  object \n",
            " 27  adr                             119390 non-null  float64\n",
            " 28  required_car_parking_spaces     119390 non-null  int64  \n",
            " 29  total_of_special_requests       119390 non-null  int64  \n",
            " 30  reservation_status              119390 non-null  object \n",
            " 31  reservation_status_date         119390 non-null  object \n",
            "dtypes: float64(4), int64(16), object(12)\n",
            "memory usage: 29.1+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "sHkI8t6-8_AK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#checking for null values\n",
        "dict_={}\n",
        "for feature in data.columns:\n",
        "    dict_[feature]=data[feature].isnull().sum()\n",
        "pd.DataFrame(dict_,index=['null_values']).transpose()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "8YvFLNZp881Z",
        "outputId": "944ed4c8-02dd-4642-926a-97042419f85e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                null_values\n",
              "hotel                                     0\n",
              "is_canceled                               0\n",
              "lead_time                                 0\n",
              "arrival_date_year                         0\n",
              "arrival_date_month                        0\n",
              "arrival_date_week_number                  0\n",
              "arrival_date_day_of_month                 0\n",
              "stays_in_weekend_nights                   0\n",
              "stays_in_week_nights                      0\n",
              "adults                                    0\n",
              "children                                  4\n",
              "babies                                    0\n",
              "meal                                      0\n",
              "country                                 488\n",
              "market_segment                            0\n",
              "distribution_channel                      0\n",
              "is_repeated_guest                         0\n",
              "previous_cancellations                    0\n",
              "previous_bookings_not_canceled            0\n",
              "reserved_room_type                        0\n",
              "assigned_room_type                        0\n",
              "booking_changes                           0\n",
              "deposit_type                              0\n",
              "agent                                 16340\n",
              "company                              112593\n",
              "days_in_waiting_list                      0\n",
              "customer_type                             0\n",
              "adr                                       0\n",
              "required_car_parking_spaces               0\n",
              "total_of_special_requests                 0\n",
              "reservation_status                        0\n",
              "reservation_status_date                   0"
            ],
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              "    <tr>\n",
              "      <th>hotel</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>is_canceled</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>lead_time</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>arrival_date_year</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>arrival_date_month</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>arrival_date_week_number</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>arrival_date_day_of_month</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>stays_in_weekend_nights</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>stays_in_week_nights</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>adults</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>children</th>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>babies</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>meal</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>country</th>\n",
              "      <td>488</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>market_segment</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>distribution_channel</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>is_repeated_guest</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>previous_cancellations</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>previous_bookings_not_canceled</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>reserved_room_type</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>assigned_room_type</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>booking_changes</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>deposit_type</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>agent</th>\n",
              "      <td>16340</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>company</th>\n",
              "      <td>112593</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>days_in_waiting_list</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>customer_type</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>adr</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>required_car_parking_spaces</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_of_special_requests</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>reservation_status</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>reservation_status_date</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d674fe09-8c2a-4546-ad74-5d1a73d7c2db')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-convert {\n",
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              "    .colab-df-convert:hover {\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
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              "                                                     [key], {});\n",
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              "          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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#since company has approximately 95% null values it's better to drop it\n",
        "data.drop('company',axis=1,inplace=True)"
      ],
      "metadata": {
        "id": "a30F1Zw-9JDf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#for total number of guests\n",
        "data['Total_guests']=data['adults']+data['children']+data['babies']"
      ],
      "metadata": {
        "id": "NurbIZHL9O0Z"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VCv9FEV--E4O",
        "outputId": "5b00b0a8-d7cc-4383-bff9-4fd83e587c14"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(119390, 32)"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#creating a copy of the table to wirk with it \n",
        "data_set= data.copy()\n"
      ],
      "metadata": {
        "id": "GnqYL-I--Mz4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Se cuentan los valores faltantes de cada columna y se organizan en orden descendente.\n",
        "# Se muestran las primeras 8 columnas.\n",
        "data_set.isnull().sum().sort_values(ascending=False)[:8]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "giQrcSeL-xw2",
        "outputId": "3cc98b72-23f7-4c5e-c72a-7eb7fa499b63"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "agent                 16340\n",
              "country                 488\n",
              "Total_guests              4\n",
              "children                  4\n",
              "reserved_room_type        0\n",
              "assigned_room_type        0\n",
              "booking_changes           0\n",
              "deposit_type              0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_set"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 661
        },
        "id": "a669CubQ-5dO",
        "outputId": "ede20a17-1db3-4a66-9683-f5334ca66dbb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               hotel  is_canceled  lead_time  arrival_date_year  \\\n",
              "0       Resort Hotel            0        342               2015   \n",
              "1       Resort Hotel            0        737               2015   \n",
              "2       Resort Hotel            0          7               2015   \n",
              "3       Resort Hotel            0         13               2015   \n",
              "4       Resort Hotel            0         14               2015   \n",
              "...              ...          ...        ...                ...   \n",
              "119385    City Hotel            0         23               2017   \n",
              "119386    City Hotel            0        102               2017   \n",
              "119387    City Hotel            0         34               2017   \n",
              "119388    City Hotel            0        109               2017   \n",
              "119389    City Hotel            0        205               2017   \n",
              "\n",
              "       arrival_date_month  arrival_date_week_number  \\\n",
              "0                    July                        27   \n",
              "1                    July                        27   \n",
              "2                    July                        27   \n",
              "3                    July                        27   \n",
              "4                    July                        27   \n",
              "...                   ...                       ...   \n",
              "119385             August                        35   \n",
              "119386             August                        35   \n",
              "119387             August                        35   \n",
              "119388             August                        35   \n",
              "119389             August                        35   \n",
              "\n",
              "        arrival_date_day_of_month  stays_in_weekend_nights  \\\n",
              "0                               1                        0   \n",
              "1                               1                        0   \n",
              "2                               1                        0   \n",
              "3                               1                        0   \n",
              "4                               1                        0   \n",
              "...                           ...                      ...   \n",
              "119385                         30                        2   \n",
              "119386                         31                        2   \n",
              "119387                         31                        2   \n",
              "119388                         31                        2   \n",
              "119389                         29                        2   \n",
              "\n",
              "        stays_in_week_nights  adults  ...  deposit_type  agent  \\\n",
              "0                          0       2  ...    No Deposit    NaN   \n",
              "1                          0       2  ...    No Deposit    NaN   \n",
              "2                          1       1  ...    No Deposit    NaN   \n",
              "3                          1       1  ...    No Deposit  304.0   \n",
              "4                          2       2  ...    No Deposit  240.0   \n",
              "...                      ...     ...  ...           ...    ...   \n",
              "119385                     5       2  ...    No Deposit  394.0   \n",
              "119386                     5       3  ...    No Deposit    9.0   \n",
              "119387                     5       2  ...    No Deposit    9.0   \n",
              "119388                     5       2  ...    No Deposit   89.0   \n",
              "119389                     7       2  ...    No Deposit    9.0   \n",
              "\n",
              "       days_in_waiting_list customer_type     adr required_car_parking_spaces  \\\n",
              "0                         0     Transient    0.00                           0   \n",
              "1                         0     Transient    0.00                           0   \n",
              "2                         0     Transient   75.00                           0   \n",
              "3                         0     Transient   75.00                           0   \n",
              "4                         0     Transient   98.00                           0   \n",
              "...                     ...           ...     ...                         ...   \n",
              "119385                    0     Transient   96.14                           0   \n",
              "119386                    0     Transient  225.43                           0   \n",
              "119387                    0     Transient  157.71                           0   \n",
              "119388                    0     Transient  104.40                           0   \n",
              "119389                    0     Transient  151.20                           0   \n",
              "\n",
              "        total_of_special_requests  reservation_status  \\\n",
              "0                               0           Check-Out   \n",
              "1                               0           Check-Out   \n",
              "2                               0           Check-Out   \n",
              "3                               0           Check-Out   \n",
              "4                               1           Check-Out   \n",
              "...                           ...                 ...   \n",
              "119385                          0           Check-Out   \n",
              "119386                          2           Check-Out   \n",
              "119387                          4           Check-Out   \n",
              "119388                          0           Check-Out   \n",
              "119389                          2           Check-Out   \n",
              "\n",
              "        reservation_status_date Total_guests  \n",
              "0                    2015-07-01          2.0  \n",
              "1                    2015-07-01          2.0  \n",
              "2                    2015-07-02          1.0  \n",
              "3                    2015-07-02          1.0  \n",
              "4                    2015-07-03          2.0  \n",
              "...                         ...          ...  \n",
              "119385               2017-09-06          2.0  \n",
              "119386               2017-09-07          3.0  \n",
              "119387               2017-09-07          2.0  \n",
              "119388               2017-09-07          2.0  \n",
              "119389               2017-09-07          2.0  \n",
              "\n",
              "[119390 rows x 32 columns]"
            ],
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              "      <th></th>\n",
              "      <th>hotel</th>\n",
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              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
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              "      <td>2015-07-01</td>\n",
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              "      <td>7</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>2015-07-02</td>\n",
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              "      <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>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>98.00</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-03</td>\n",
              "      <td>2.0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119385</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>23</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>30</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>394.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>96.14</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-06</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119386</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>102</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>31</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>225.43</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119387</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>34</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>31</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>157.71</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119388</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>109</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>31</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>89.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>104.40</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119389</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>205</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>29</td>\n",
              "      <td>2</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>151.20</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>119390 rows × 32 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d5212ead-6bf5-49f5-a4b1-d756b00523f1')\"\n",
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            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_set[data_set['Total_guests']==0].value_counts().sum()"
      ],
      "metadata": {
        "id": "gkBYCTsT_ZYf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "364cc07b-f024-4a9a-b7dd-030cf1e3581f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "120"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#since it's not possible that someone will make bookings and the number of guests be zero\n",
        "no_guests=data_set['Total_guests']==0\n",
        "data_set=data_set[~no_guests]"
      ],
      "metadata": {
        "id": "7UjllWPvAA7W"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#dropping total guests\n",
        "data_set.drop('Total_guests',axis=1,inplace=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MQziPcaBAKkC",
        "outputId": "c67534ea-3684-4b5f-f8d0-2672f72ec6b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-23-efaee4568aa4>:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  data_set.drop('Total_guests',axis=1,inplace=True)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "-dvdZEY1AWpT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Si el ID de 'agent' o 'company' es nulo, se reemplaza con 0.\n",
        "data_set[['agent']] = data_set[['agent']].fillna(0.0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a_8NcnJm_wMU",
        "outputId": "cd18754b-9863-4537-a856-6d04f1253aa4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-24-ef08f99a058a>:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  data_set[['agent']] = data_set[['agent']].fillna(0.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_set"
      ],
      "metadata": {
        "id": "sS6JkdqyAhC-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 661
        },
        "outputId": "338ac3c0-134a-4b27-d05a-dc44838779c8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               hotel  is_canceled  lead_time  arrival_date_year  \\\n",
              "0       Resort Hotel            0        342               2015   \n",
              "1       Resort Hotel            0        737               2015   \n",
              "2       Resort Hotel            0          7               2015   \n",
              "3       Resort Hotel            0         13               2015   \n",
              "4       Resort Hotel            0         14               2015   \n",
              "...              ...          ...        ...                ...   \n",
              "119385    City Hotel            0         23               2017   \n",
              "119386    City Hotel            0        102               2017   \n",
              "119387    City Hotel            0         34               2017   \n",
              "119388    City Hotel            0        109               2017   \n",
              "119389    City Hotel            0        205               2017   \n",
              "\n",
              "       arrival_date_month  arrival_date_week_number  \\\n",
              "0                    July                        27   \n",
              "1                    July                        27   \n",
              "2                    July                        27   \n",
              "3                    July                        27   \n",
              "4                    July                        27   \n",
              "...                   ...                       ...   \n",
              "119385             August                        35   \n",
              "119386             August                        35   \n",
              "119387             August                        35   \n",
              "119388             August                        35   \n",
              "119389             August                        35   \n",
              "\n",
              "        arrival_date_day_of_month  stays_in_weekend_nights  \\\n",
              "0                               1                        0   \n",
              "1                               1                        0   \n",
              "2                               1                        0   \n",
              "3                               1                        0   \n",
              "4                               1                        0   \n",
              "...                           ...                      ...   \n",
              "119385                         30                        2   \n",
              "119386                         31                        2   \n",
              "119387                         31                        2   \n",
              "119388                         31                        2   \n",
              "119389                         29                        2   \n",
              "\n",
              "        stays_in_week_nights  adults  ...  booking_changes  deposit_type  \\\n",
              "0                          0       2  ...                3    No Deposit   \n",
              "1                          0       2  ...                4    No Deposit   \n",
              "2                          1       1  ...                0    No Deposit   \n",
              "3                          1       1  ...                0    No Deposit   \n",
              "4                          2       2  ...                0    No Deposit   \n",
              "...                      ...     ...  ...              ...           ...   \n",
              "119385                     5       2  ...                0    No Deposit   \n",
              "119386                     5       3  ...                0    No Deposit   \n",
              "119387                     5       2  ...                0    No Deposit   \n",
              "119388                     5       2  ...                0    No Deposit   \n",
              "119389                     7       2  ...                0    No Deposit   \n",
              "\n",
              "        agent days_in_waiting_list customer_type     adr  \\\n",
              "0         0.0                    0     Transient    0.00   \n",
              "1         0.0                    0     Transient    0.00   \n",
              "2         0.0                    0     Transient   75.00   \n",
              "3       304.0                    0     Transient   75.00   \n",
              "4       240.0                    0     Transient   98.00   \n",
              "...       ...                  ...           ...     ...   \n",
              "119385  394.0                    0     Transient   96.14   \n",
              "119386    9.0                    0     Transient  225.43   \n",
              "119387    9.0                    0     Transient  157.71   \n",
              "119388   89.0                    0     Transient  104.40   \n",
              "119389    9.0                    0     Transient  151.20   \n",
              "\n",
              "        required_car_parking_spaces  total_of_special_requests  \\\n",
              "0                                 0                          0   \n",
              "1                                 0                          0   \n",
              "2                                 0                          0   \n",
              "3                                 0                          0   \n",
              "4                                 0                          1   \n",
              "...                             ...                        ...   \n",
              "119385                            0                          0   \n",
              "119386                            0                          2   \n",
              "119387                            0                          4   \n",
              "119388                            0                          0   \n",
              "119389                            0                          2   \n",
              "\n",
              "        reservation_status reservation_status_date  \n",
              "0                Check-Out              2015-07-01  \n",
              "1                Check-Out              2015-07-01  \n",
              "2                Check-Out              2015-07-02  \n",
              "3                Check-Out              2015-07-02  \n",
              "4                Check-Out              2015-07-03  \n",
              "...                    ...                     ...  \n",
              "119385           Check-Out              2017-09-06  \n",
              "119386           Check-Out              2017-09-07  \n",
              "119387           Check-Out              2017-09-07  \n",
              "119388           Check-Out              2017-09-07  \n",
              "119389           Check-Out              2017-09-07  \n",
              "\n",
              "[119210 rows x 31 columns]"
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>4</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.00</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>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.00</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>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>304.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.00</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>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>240.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>98.00</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-03</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119385</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>23</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>30</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>394.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>96.14</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119386</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>102</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>31</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>225.43</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119387</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>34</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>31</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>157.71</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119388</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>109</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>31</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>89.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>104.40</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119389</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>205</td>\n",
              "      <td>2017</td>\n",
              "      <td>August</td>\n",
              "      <td>35</td>\n",
              "      <td>29</td>\n",
              "      <td>2</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>151.20</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2017-09-07</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>119210 rows × 31 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b94c4fa1-a895-4d87-b079-fe76abb39f42')\"\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-b94c4fa1-a895-4d87-b079-fe76abb39f42 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-b94c4fa1-a895-4d87-b079-fe76abb39f42');\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": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## Para valores faltantes de la columna 'country', se reemplazan por su moda.\n",
        "data_set['country'].fillna(data_set.country.mode().to_string(), inplace=True)\n",
        "\n",
        "## Para los valores faltantes de 'children', se reemplazan con su número promedio redondeado.\n",
        "data_set['children'].fillna(round(data_set.children.mean()), inplace=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6-skm9vsAjK0",
        "outputId": "19259645-e420-4c26-c242-2d4a591ff568"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-26-b76f6b6cdca2>:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  data_set['country'].fillna(data_set.country.mode().to_string(), inplace=True)\n",
            "<ipython-input-26-b76f6b6cdca2>:5: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  data_set['children'].fillna(round(data_set.children.mean()), inplace=True)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_set.isnull().sum().sort_values(ascending=False)[:8]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_96ZjMgyBB-U",
        "outputId": "9996ff5a-4344-48f9-e38d-0c0773f0cd85"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "hotel                          0\n",
              "is_repeated_guest              0\n",
              "reservation_status             0\n",
              "total_of_special_requests      0\n",
              "required_car_parking_spaces    0\n",
              "adr                            0\n",
              "customer_type                  0\n",
              "days_in_waiting_list           0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#double check of there are not 0 guesses in the dataset\n",
        "((data_set.adults + data_set.babies + data_set.children)==0).sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NL56FU1PBLQs",
        "outputId": "612dcbd3-7a99-411c-9c79-380606e0a366"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_set.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pM6RZamSB8_K",
        "outputId": "173950fb-2451-4a7b-ab25-e0a2c5ffe9d1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "hotel                              object\n",
              "is_canceled                         int64\n",
              "lead_time                           int64\n",
              "arrival_date_year                   int64\n",
              "arrival_date_month                 object\n",
              "arrival_date_week_number            int64\n",
              "arrival_date_day_of_month           int64\n",
              "stays_in_weekend_nights             int64\n",
              "stays_in_week_nights                int64\n",
              "adults                              int64\n",
              "children                          float64\n",
              "babies                              int64\n",
              "meal                               object\n",
              "country                            object\n",
              "market_segment                     object\n",
              "distribution_channel               object\n",
              "is_repeated_guest                   int64\n",
              "previous_cancellations              int64\n",
              "previous_bookings_not_canceled      int64\n",
              "reserved_room_type                 object\n",
              "assigned_room_type                 object\n",
              "booking_changes                     int64\n",
              "deposit_type                       object\n",
              "agent                             float64\n",
              "days_in_waiting_list                int64\n",
              "customer_type                      object\n",
              "adr                               float64\n",
              "required_car_parking_spaces         int64\n",
              "total_of_special_requests           int64\n",
              "reservation_status                 object\n",
              "reservation_status_date            object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Hay algunas columnas con tipos de datos inadecuados.\n",
        "# Las siguientes columnas se convierten de tipo float a entero:\n",
        "# {'children', 'company', 'agent'}\n",
        "data_set[['children', 'agent']] = data_set[['children', 'agent']].astype('int64')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d7jspEmICE6B",
        "outputId": "0809e04e-e3f3-43f4-b615-4bd14ed8826a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-30-8f8ecf77e793>:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  data_set[['children', 'agent']] = data_set[['children', 'agent']].astype('int64')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_set.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Shf_UW8pCcYE",
        "outputId": "d9ab6aa7-a0a0-4bf1-ff36-3aa6316da3fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "hotel                              object\n",
              "is_canceled                         int64\n",
              "lead_time                           int64\n",
              "arrival_date_year                   int64\n",
              "arrival_date_month                 object\n",
              "arrival_date_week_number            int64\n",
              "arrival_date_day_of_month           int64\n",
              "stays_in_weekend_nights             int64\n",
              "stays_in_week_nights                int64\n",
              "adults                              int64\n",
              "children                            int64\n",
              "babies                              int64\n",
              "meal                               object\n",
              "country                            object\n",
              "market_segment                     object\n",
              "distribution_channel               object\n",
              "is_repeated_guest                   int64\n",
              "previous_cancellations              int64\n",
              "previous_bookings_not_canceled      int64\n",
              "reserved_room_type                 object\n",
              "assigned_room_type                 object\n",
              "booking_changes                     int64\n",
              "deposit_type                       object\n",
              "agent                               int64\n",
              "days_in_waiting_list                int64\n",
              "customer_type                      object\n",
              "adr                               float64\n",
              "required_car_parking_spaces         int64\n",
              "total_of_special_requests           int64\n",
              "reservation_status                 object\n",
              "reservation_status_date            object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "acKfHvOtoQqw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Exploratory Data Analysis**\n"
      ],
      "metadata": {
        "id": "EZ8BDn7GpG_G"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#No of unique variables for each columns\n",
        "dict_={}\n",
        "for feature in data_set.columns:\n",
        "    dict_[feature]=data_set[feature].value_counts().shape[0]\n",
        "pd.DataFrame(dict_,index=['unique_counts']).transpose()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "t-WhSojpo-G4",
        "outputId": "8bc71e3c-d1d3-4c74-b183-675f1fddc519"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                unique_counts\n",
              "hotel                                       2\n",
              "is_canceled                                 2\n",
              "lead_time                                 479\n",
              "arrival_date_year                           3\n",
              "arrival_date_month                         12\n",
              "arrival_date_week_number                   53\n",
              "arrival_date_day_of_month                  31\n",
              "stays_in_weekend_nights                    17\n",
              "stays_in_week_nights                       33\n",
              "adults                                     14\n",
              "children                                    5\n",
              "babies                                      5\n",
              "meal                                        5\n",
              "country                                   178\n",
              "market_segment                              8\n",
              "distribution_channel                        5\n",
              "is_repeated_guest                           2\n",
              "previous_cancellations                     15\n",
              "previous_bookings_not_canceled             73\n",
              "reserved_room_type                          9\n",
              "assigned_room_type                         11\n",
              "booking_changes                            19\n",
              "deposit_type                                3\n",
              "agent                                     334\n",
              "days_in_waiting_list                      127\n",
              "customer_type                               4\n",
              "adr                                      8866\n",
              "required_car_parking_spaces                 5\n",
              "total_of_special_requests                   6\n",
              "reservation_status                          3\n",
              "reservation_status_date                   926"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9b6f0b56-0ffc-4da8-a5b5-d9ecf7b49a75\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
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              "        vertical-align: middle;\n",
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              "      <th></th>\n",
              "      <th>unique_counts</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>hotel</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>is_canceled</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
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              "      <th>lead_time</th>\n",
              "      <td>479</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>arrival_date_year</th>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
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              "      <th>arrival_date_month</th>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
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              "      <th>arrival_date_week_number</th>\n",
              "      <td>53</td>\n",
              "    </tr>\n",
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              "      <th>arrival_date_day_of_month</th>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>stays_in_weekend_nights</th>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
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              "      <th>stays_in_week_nights</th>\n",
              "      <td>33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>adults</th>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>children</th>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>babies</th>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>meal</th>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
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              "      <th>country</th>\n",
              "      <td>178</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>market_segment</th>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>distribution_channel</th>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>is_repeated_guest</th>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>previous_cancellations</th>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>previous_bookings_not_canceled</th>\n",
              "      <td>73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>reserved_room_type</th>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>assigned_room_type</th>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>booking_changes</th>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>deposit_type</th>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>agent</th>\n",
              "      <td>334</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>days_in_waiting_list</th>\n",
              "      <td>127</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>customer_type</th>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>adr</th>\n",
              "      <td>8866</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>required_car_parking_spaces</th>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_of_special_requests</th>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>reservation_status</th>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>reservation_status_date</th>\n",
              "      <td>926</td>\n",
              "    </tr>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Función para obtener los porcentajes de los diferentes valores\n",
        "def get_count(series, limit=None):\n",
        "    \n",
        "    '''\n",
        "    INPUT:\n",
        "        series: Pandas Series (Single Column from DataFrame)\n",
        "        limit:  If value given, limit the output value to first limit samples.\n",
        "    OUTPUT:\n",
        "        x = Unique values\n",
        "        y = Count of unique values\n",
        "    '''\n",
        "    \n",
        "    if limit != None:\n",
        "        series = series.value_counts()[:limit]\n",
        "    else:\n",
        "        series = series.value_counts()\n",
        "    \n",
        "    x = series.index\n",
        "    y = series/series.sum()*100\n",
        "    \n",
        "    return x.values,y.values"
      ],
      "metadata": {
        "id": "FCIvbA0wsJtF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Función para graficar los porcentajes de los valores únicos de una variable\n",
        "def plot(x, y, x_label=None, y_label=None, title=None, figsize=(7,5), type='bar'):\n",
        "    \n",
        "    '''\n",
        "    Función para graficar diagramas\n",
        "    INPUT:\n",
        "        x:        Array containing values for x-axis\n",
        "        y:        Array containing values for y-axis\n",
        "        x_lable:  String value for x-axis label\n",
        "        y_lable:  String value for y-axis label\n",
        "        title:    String value for plot title\n",
        "        figsize:  tuple value, for figure size\n",
        "        type:     type of plot (default is bar plot)\n",
        "        \n",
        "    OUTPUT:\n",
        "        Display the plot\n",
        "    '''\n",
        "    \n",
        "    sns.set_style('darkgrid')\n",
        "    \n",
        "    fig, ax = plt.subplots(figsize=figsize)\n",
        "    \n",
        "    ax.yaxis.set_major_formatter(mtick.PercentFormatter())\n",
        "    \n",
        "    if x_label != None:\n",
        "        ax.set_xlabel(x_label)\n",
        "    \n",
        "    if y_label != None:\n",
        "        ax.set_ylabel(y_label)\n",
        "        \n",
        "    if title != None:\n",
        "        ax.set_title(title)\n",
        "    \n",
        "    if type == 'bar':\n",
        "        sns.barplot(x=x, y=y, ax = ax)\n",
        "    elif type == 'line':\n",
        "        sns.lineplot(x=x,y=y, ax = ax, sort=False)\n",
        "        \n",
        "    \n",
        "    plt.show()"
      ],
      "metadata": {
        "id": "DK7Y5NgosOIe"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# x: Valores únicos de la columna 'is_canceled' (x=1, es cancelada / x=0, no cancelada)\n",
        "# y: Porcentaje de cada valor único de la columna 'is_canceled'\n",
        "x, y = get_count(data_set['is_canceled'])\n",
        "print('x: ', x, '\\ny: ', np.round_(y, decimals=3))\n",
        "plot(x, y, x_label='Reservas Canceladas (No = 0 | Sí = 1)', y_label='Porcentaje de reservas')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 501
        },
        "id": "slznJvynsRYc",
        "outputId": "be7aa201-3070-4f42-9a7a-341a8db6e88c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "x:  [0 1] \n",
            "y:  [62.923 37.077]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig=plt.figure(figsize=(24,10))\n",
        "ax=[None for _ in range(4)]\n",
        "ax[0]=plt.subplot2grid((3,2),(0,0))\n",
        "ax[1]=plt.subplot2grid((3,2),(0,1))\n",
        "ax[2]=plt.subplot2grid((3,2),(1,0))\n",
        "ax[3]=plt.subplot2grid((3,2),(1,1))\n",
        "sns.countplot(x='hotel',data=data_set,ax=ax[0],hue='is_canceled',palette='rainbow')\n",
        "sns.countplot(x='arrival_date_month',data=data_set,ax=ax[1],hue='is_canceled',palette='rainbow',order=['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December'])\n",
        "sns.countplot(x='meal',data=data_set,ax=ax[2],hue='is_canceled',palette='rainbow')\n",
        "sns.countplot(x='market_segment',data=data_set,ax=ax[3],hue='is_canceled',palette='rainbow')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 551
        },
        "id": "6DkFcVFoqN6C",
        "outputId": "b2ec3cc2-88da-45bb-8e26-362b07968d9f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='market_segment', ylabel='count'>"
            ]
          },
          "metadata": {},
          "execution_count": 36
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2400x1000 with 4 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- The proportion of bookings getting cancelled in city hotel in more than in resorts\n",
        "- The proportion of ratained cancelled bookings seems to be relatively stable throughout the month\n",
        "- The bookings with selected meal type 'FB' i.e., Full Board are most likely to get canceled"
      ],
      "metadata": {
        "id": "aWxPXJiLqrc4"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Q2ahZDpDqrO-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig=plt.figure(figsize=(24,15))\n",
        "ax=[None for _ in range(4)]\n",
        "ax[0]=plt.subplot2grid((3,2),(0,0))\n",
        "ax[1]=plt.subplot2grid((3,2),(0,1))\n",
        "ax[2]=plt.subplot2grid((3,2),(1,0))\n",
        "ax[3]=plt.subplot2grid((3,2),(1,1))\n",
        "sns.countplot(x='distribution_channel',data=data_set,ax=ax[0],hue='is_canceled',palette='rainbow')\n",
        "sns.countplot(x='reserved_room_type',data=data_set,ax=ax[1],hue='is_canceled',palette='rainbow')\n",
        "sns.countplot(x='is_repeated_guest',data=data_set,ax=ax[2],hue='is_canceled',palette='rainbow')\n",
        "sns.countplot(x='customer_type',data=data_set,ax=ax[3],hue='is_canceled',palette='rainbow')\n",
        "plt.tight_layout()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 787
        },
        "id": "KUHiQM6mrFto",
        "outputId": "96a7afde-c515-41c3-d41d-d4f1bf87aa17"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2400x1500 with 4 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Bookings made through Direct, corporate and GDS channel are typically kept however bookings through TA/TO, retained bookings and cancelled bookings are almost proportional.\n",
        "Retained and cancelled bookings for different room types are typically proportional.\n",
        "Repeated guests are much more likely to retain the bookings."
      ],
      "metadata": {
        "id": "AMg6AIqkrXh0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set_style('darkgrid')\n",
        "fig=plt.figure(figsize=(10,5))\n",
        "ax[0]=plt.subplot2grid((1,2),(0,0))\n",
        "ax[1]=plt.subplot2grid((1,2),(0,1))\n",
        "sns.kdeplot(x='lead_time',data=data_set,hue='is_canceled',fill=True,ax=ax[0])\n",
        "sns.kdeplot(x='days_in_waiting_list',data=data_set,hue='is_canceled',fill=True,ax=ax[1])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 482
        },
        "id": "XlJSHq11rh0J",
        "outputId": "76a3a111-1df3-4470-b2cb-816e8249b83a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='days_in_waiting_list', ylabel='Density'>"
            ]
          },
          "metadata": {},
          "execution_count": 38
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "NSUfIikYrxLh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "'lead_time' is typically lower for bookings that are retained, this suggests that the sooner the bookings are made customers are less likely to cancel it and lower the days in the 'days_in_waiting_list' less likely the bookings will get canceled"
      ],
      "metadata": {
        "id": "ZYCJGrWZry1l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Valores del estado de reservación\n",
        "data_set.reservation_status.unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9njtKl2aryhf",
        "outputId": "aa21905f-f417-41b7-bfb7-8f1d3ab5c131"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Check-Out', 'Canceled', 'No-Show'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "no_cancelled = data_set[data_set['is_canceled'] == 0]\n",
        "no_cancelled"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 661
        },
        "id": "GerHxXKTtQbS",
        "outputId": "f1e9522f-9bb2-4ba5-90bc-f84ab0b708a8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "               hotel  is_canceled  lead_time  arrival_date_year  \\\n",
              "0       Resort Hotel            0        342               2015   \n",
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              "2       Resort Hotel            0          7               2015   \n",
              "3       Resort Hotel            0         13               2015   \n",
              "4       Resort Hotel            0         14               2015   \n",
              "...              ...          ...        ...                ...   \n",
              "119385    City Hotel            0         23               2017   \n",
              "119386    City Hotel            0        102               2017   \n",
              "119387    City Hotel            0         34               2017   \n",
              "119388    City Hotel            0        109               2017   \n",
              "119389    City Hotel            0        205               2017   \n",
              "\n",
              "       arrival_date_month  arrival_date_week_number  \\\n",
              "0                    July                        27   \n",
              "1                    July                        27   \n",
              "2                    July                        27   \n",
              "3                    July                        27   \n",
              "4                    July                        27   \n",
              "...                   ...                       ...   \n",
              "119385             August                        35   \n",
              "119386             August                        35   \n",
              "119387             August                        35   \n",
              "119388             August                        35   \n",
              "119389             August                        35   \n",
              "\n",
              "        arrival_date_day_of_month  stays_in_weekend_nights  \\\n",
              "0                               1                        0   \n",
              "1                               1                        0   \n",
              "2                               1                        0   \n",
              "3                               1                        0   \n",
              "4                               1                        0   \n",
              "...                           ...                      ...   \n",
              "119385                         30                        2   \n",
              "119386                         31                        2   \n",
              "119387                         31                        2   \n",
              "119388                         31                        2   \n",
              "119389                         29                        2   \n",
              "\n",
              "        stays_in_week_nights  adults  ...  booking_changes  deposit_type  \\\n",
              "0                          0       2  ...                3    No Deposit   \n",
              "1                          0       2  ...                4    No Deposit   \n",
              "2                          1       1  ...                0    No Deposit   \n",
              "3                          1       1  ...                0    No Deposit   \n",
              "4                          2       2  ...                0    No Deposit   \n",
              "...                      ...     ...  ...              ...           ...   \n",
              "119385                     5       2  ...                0    No Deposit   \n",
              "119386                     5       3  ...                0    No Deposit   \n",
              "119387                     5       2  ...                0    No Deposit   \n",
              "119388                     5       2  ...                0    No Deposit   \n",
              "119389                     7       2  ...                0    No Deposit   \n",
              "\n",
              "       agent days_in_waiting_list customer_type     adr  \\\n",
              "0          0                    0     Transient    0.00   \n",
              "1          0                    0     Transient    0.00   \n",
              "2          0                    0     Transient   75.00   \n",
              "3        304                    0     Transient   75.00   \n",
              "4        240                    0     Transient   98.00   \n",
              "...      ...                  ...           ...     ...   \n",
              "119385   394                    0     Transient   96.14   \n",
              "119386     9                    0     Transient  225.43   \n",
              "119387     9                    0     Transient  157.71   \n",
              "119388    89                    0     Transient  104.40   \n",
              "119389     9                    0     Transient  151.20   \n",
              "\n",
              "        required_car_parking_spaces  total_of_special_requests  \\\n",
              "0                                 0                          0   \n",
              "1                                 0                          0   \n",
              "2                                 0                          0   \n",
              "3                                 0                          0   \n",
              "4                                 0                          1   \n",
              "...                             ...                        ...   \n",
              "119385                            0                          0   \n",
              "119386                            0                          2   \n",
              "119387                            0                          4   \n",
              "119388                            0                          0   \n",
              "119389                            0                          2   \n",
              "\n",
              "        reservation_status reservation_status_date  \n",
              "0                Check-Out              2015-07-01  \n",
              "1                Check-Out              2015-07-01  \n",
              "2                Check-Out              2015-07-02  \n",
              "3                Check-Out              2015-07-02  \n",
              "4                Check-Out              2015-07-03  \n",
              "...                    ...                     ...  \n",
              "119385           Check-Out              2017-09-06  \n",
              "119386           Check-Out              2017-09-07  \n",
              "119387           Check-Out              2017-09-07  \n",
              "119388           Check-Out              2017-09-07  \n",
              "119389           Check-Out              2017-09-07  \n",
              "\n",
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              "          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": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(24,10))\n",
        "corr=data_set.corr()\n",
        "sns.heatmap(corr,cmap='coolwarm_r',annot=True,annot_kws={'size':10})"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "T3Mzg26_toQu",
        "outputId": "90b95863-c4f4-4534-e549-c249608d9468"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-41-4a589bcd6b1f>:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  corr=data_set.corr()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 41
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2400x1000 with 2 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "6QkljBIdqNoM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "EZtR85Fkwm4E"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CCJrivd0vbRZ"
      },
      "source": [
        "# Preparación de los Datos\n",
        "\n",
        "Antes de pasar los datos por los modelos de *machine learning*, es necesario convertir sus variables categóricas a variables discretas."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_set.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dp6VJ3O9wi99",
        "outputId": "41fe2267-08fc-4fce-cf14-d9ee41dd3f3e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "hotel                              object\n",
              "is_canceled                         int64\n",
              "lead_time                           int64\n",
              "arrival_date_year                   int64\n",
              "arrival_date_month                 object\n",
              "arrival_date_week_number            int64\n",
              "arrival_date_day_of_month           int64\n",
              "stays_in_weekend_nights             int64\n",
              "stays_in_week_nights                int64\n",
              "adults                              int64\n",
              "children                            int64\n",
              "babies                              int64\n",
              "meal                               object\n",
              "country                            object\n",
              "market_segment                     object\n",
              "distribution_channel               object\n",
              "is_repeated_guest                   int64\n",
              "previous_cancellations              int64\n",
              "previous_bookings_not_canceled      int64\n",
              "reserved_room_type                 object\n",
              "assigned_room_type                 object\n",
              "booking_changes                     int64\n",
              "deposit_type                       object\n",
              "agent                               int64\n",
              "days_in_waiting_list                int64\n",
              "customer_type                      object\n",
              "adr                               float64\n",
              "required_car_parking_spaces         int64\n",
              "total_of_special_requests           int64\n",
              "reservation_status                 object\n",
              "reservation_status_date            object\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Listado de variables tipo categóricas de la base de datos\n",
        "columnas_categoricas = data_set.columns[data_set.dtypes == object]\n",
        "columnas_categoricas"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kjzpEEMOwvUv",
        "outputId": "cc068bc7-827c-4687-88ca-76d6d339e369"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['hotel', 'arrival_date_month', 'meal', 'country', 'market_segment',\n",
              "       'distribution_channel', 'reserved_room_type', 'assigned_room_type',\n",
              "       'deposit_type', 'customer_type', 'reservation_status',\n",
              "       'reservation_status_date'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "bd_2R8F3w6_0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "DHAVVv_Svryv"
      },
      "outputs": [],
      "source": [
        "# Función para transformar las variables de tipo categórico a tipo discreto\n",
        "\n",
        "def transform(dataframe):\n",
        "    \n",
        "    ## Import LabelEncoder from sklearn\n",
        "    from sklearn.preprocessing import LabelEncoder\n",
        "    \n",
        "    le = LabelEncoder()\n",
        "    \n",
        "    ## Select all categorcial features\n",
        "    categorical_features = list(dataframe.columns[dataframe.dtypes == object])\n",
        "    \n",
        "    ## Apply Label Encoding on all categorical features\n",
        "    return dataframe[categorical_features].apply(lambda x: le.fit_transform(x))"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Se hace una copia al dataframe\n",
        "data_set2 = data_set.copy()\n",
        "\n",
        "# Se transforman las variables de tipo categórico a tipo discreto\n",
        "data_set2 = transform(data_set2)\n",
        "print('data_set2.shape:', data_set2.shape)\n",
        "data_set2.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VTuNWm9cxG7T",
        "outputId": "154de3c1-e25c-4c55-9b68-6cb3c949301c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "data_set2.shape: (119210, 12)\n",
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 119210 entries, 0 to 119389\n",
            "Data columns (total 12 columns):\n",
            " #   Column                   Non-Null Count   Dtype\n",
            "---  ------                   --------------   -----\n",
            " 0   hotel                    119210 non-null  int64\n",
            " 1   arrival_date_month       119210 non-null  int64\n",
            " 2   meal                     119210 non-null  int64\n",
            " 3   country                  119210 non-null  int64\n",
            " 4   market_segment           119210 non-null  int64\n",
            " 5   distribution_channel     119210 non-null  int64\n",
            " 6   reserved_room_type       119210 non-null  int64\n",
            " 7   assigned_room_type       119210 non-null  int64\n",
            " 8   deposit_type             119210 non-null  int64\n",
            " 9   customer_type            119210 non-null  int64\n",
            " 10  reservation_status       119210 non-null  int64\n",
            " 11  reservation_status_date  119210 non-null  int64\n",
            "dtypes: int64(12)\n",
            "memory usage: 11.8 MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Se eliminan las columnas categóricas, para luego agregarle las columnas transformadas.\n",
        "data_set = data_set.drop(columnas_categoricas, axis=1)"
      ],
      "metadata": {
        "id": "_EAGx6KAyHMn"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Lb157ibYVRnW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data_set.info()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w1_xkVc0yN55",
        "outputId": "68754efe-1f00-49b4-b5db-b69c24a7f566"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 119210 entries, 0 to 119389\n",
            "Data columns (total 19 columns):\n",
            " #   Column                          Non-Null Count   Dtype  \n",
            "---  ------                          --------------   -----  \n",
            " 0   is_canceled                     119210 non-null  int64  \n",
            " 1   lead_time                       119210 non-null  int64  \n",
            " 2   arrival_date_year               119210 non-null  int64  \n",
            " 3   arrival_date_week_number        119210 non-null  int64  \n",
            " 4   arrival_date_day_of_month       119210 non-null  int64  \n",
            " 5   stays_in_weekend_nights         119210 non-null  int64  \n",
            " 6   stays_in_week_nights            119210 non-null  int64  \n",
            " 7   adults                          119210 non-null  int64  \n",
            " 8   children                        119210 non-null  int64  \n",
            " 9   babies                          119210 non-null  int64  \n",
            " 10  is_repeated_guest               119210 non-null  int64  \n",
            " 11  previous_cancellations          119210 non-null  int64  \n",
            " 12  previous_bookings_not_canceled  119210 non-null  int64  \n",
            " 13  booking_changes                 119210 non-null  int64  \n",
            " 14  agent                           119210 non-null  int64  \n",
            " 15  days_in_waiting_list            119210 non-null  int64  \n",
            " 16  adr                             119210 non-null  float64\n",
            " 17  required_car_parking_spaces     119210 non-null  int64  \n",
            " 18  total_of_special_requests       119210 non-null  int64  \n",
            "dtypes: float64(1), int64(18)\n",
            "memory usage: 18.2 MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_set[columnas_categoricas] = data_set2[columnas_categoricas]\n",
        "data_set2 = data_set.copy()\n",
        "data_set2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "JxPH3hSiyViM",
        "outputId": "2a94c7d3-6f8a-40c9-e18d-546dc71a794a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        is_canceled  lead_time  arrival_date_year  arrival_date_week_number  \\\n",
              "0                 0        342               2015                        27   \n",
              "1                 0        737               2015                        27   \n",
              "2                 0          7               2015                        27   \n",
              "3                 0         13               2015                        27   \n",
              "4                 0         14               2015                        27   \n",
              "...             ...        ...                ...                       ...   \n",
              "119385            0         23               2017                        35   \n",
              "119386            0        102               2017                        35   \n",
              "119387            0         34               2017                        35   \n",
              "119388            0        109               2017                        35   \n",
              "119389            0        205               2017                        35   \n",
              "\n",
              "        arrival_date_day_of_month  stays_in_weekend_nights  \\\n",
              "0                               1                        0   \n",
              "1                               1                        0   \n",
              "2                               1                        0   \n",
              "3                               1                        0   \n",
              "4                               1                        0   \n",
              "...                           ...                      ...   \n",
              "119385                         30                        2   \n",
              "119386                         31                        2   \n",
              "119387                         31                        2   \n",
              "119388                         31                        2   \n",
              "119389                         29                        2   \n",
              "\n",
              "        stays_in_week_nights  adults  children  babies  ...  meal  country  \\\n",
              "0                          0       2         0       0  ...     0      136   \n",
              "1                          0       2         0       0  ...     0      136   \n",
              "2                          1       1         0       0  ...     0       60   \n",
              "3                          1       1         0       0  ...     0       60   \n",
              "4                          2       2         0       0  ...     0       60   \n",
              "...                      ...     ...       ...     ...  ...   ...      ...   \n",
              "119385                     5       2         0       0  ...     0       16   \n",
              "119386                     5       3         0       0  ...     0       57   \n",
              "119387                     5       2         0       0  ...     0       44   \n",
              "119388                     5       2         0       0  ...     0       60   \n",
              "119389                     7       2         0       0  ...     2       44   \n",
              "\n",
              "        market_segment  distribution_channel  reserved_room_type  \\\n",
              "0                    3                     1                   2   \n",
              "1                    3                     1                   2   \n",
              "2                    3                     1                   0   \n",
              "3                    2                     0                   0   \n",
              "4                    6                     3                   0   \n",
              "...                ...                   ...                 ...   \n",
              "119385               5                     3                   0   \n",
              "119386               6                     3                   4   \n",
              "119387               6                     3                   3   \n",
              "119388               6                     3                   0   \n",
              "119389               6                     3                   0   \n",
              "\n",
              "        assigned_room_type  deposit_type  customer_type  reservation_status  \\\n",
              "0                        2             0              2                   1   \n",
              "1                        2             0              2                   1   \n",
              "2                        2             0              2                   1   \n",
              "3                        0             0              2                   1   \n",
              "4                        0             0              2                   1   \n",
              "...                    ...           ...            ...                 ...   \n",
              "119385                   0             0              2                   1   \n",
              "119386                   4             0              2                   1   \n",
              "119387                   3             0              2                   1   \n",
              "119388                   0             0              2                   1   \n",
              "119389                   0             0              2                   1   \n",
              "\n",
              "        reservation_status_date  \n",
              "0                           121  \n",
              "1                           121  \n",
              "2                           122  \n",
              "3                           122  \n",
              "4                           123  \n",
              "...                         ...  \n",
              "119385                      919  \n",
              "119386                      920  \n",
              "119387                      920  \n",
              "119388                      920  \n",
              "119389                      920  \n",
              "\n",
              "[119210 rows x 31 columns]"
            ],
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              "<p>119210 rows × 31 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-017eab4c-28bb-4338-b0d9-3ea800bb6482')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
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              "\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-017eab4c-28bb-4338-b0d9-3ea800bb6482 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-017eab4c-28bb-4338-b0d9-3ea800bb6482');\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": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_set2.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nv0-6VrVytQb",
        "outputId": "a07a4793-659d-4ccf-a809-fee0b8bfe037"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(119210, 12)"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    }
  ]
}