hotel_cancellation.ipynb

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  "metadata": {
    "colab": {
      "name": " hotel_cancellation.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyP275CaVtAvpPYLQKgLrWdN",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/loicmarx/datascience-projects/blob/main/hotel_cancellation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LVfDrVc94nvy"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dKq_yfVC5JSu"
      },
      "source": [
        "# Read the data\n",
        "df = pd.read_csv('/content/hotel_bookings.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QRKRaGla5ygh",
        "outputId": "46776439-c3cf-40b8-f06f-06cd0bdf2e0f"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(119390, 32)"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Wtde42In51fB",
        "outputId": "9b1e841b-b27d-4113-ed9a-9111085dd1b3"
      },
      "source": [
        "df.isna().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "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\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OZ0eCb4j58mm"
      },
      "source": [
        "def data_clean(df):\n",
        "  df.fillna(0,inplace=True)\n",
        "  print(df.isnull().sum())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Diqa-Fhh6gMZ",
        "outputId": "0fdb14bd-ae71-4376-eaf5-fbec3831ad18"
      },
      "source": [
        "data_clean(df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "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                          0\n",
            "babies                            0\n",
            "meal                              0\n",
            "country                           0\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                             0\n",
            "company                           0\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\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RzSpSobi6jLc",
        "outputId": "60e75608-6c54-4652-972d-6106afa294c0"
      },
      "source": [
        "list = ['adults', 'children', 'babies']\n",
        "for i in list:\n",
        "  print('{} has a unique values as {}'.format(i,df[i].unique()))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "adults has a unique values as [ 2  1  3  4 40 26 50 27 55  0 20  6  5 10]\n",
            "children has a unique values as [ 0.  1.  2. 10.  3.]\n",
            "babies has a unique values as [ 0  1  2 10  9]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "id": "zDgVImdj7aap",
        "outputId": "35bafe73-536f-4b2a-c0ba-d661f5336b6a"
      },
      "source": [
        "# Try to remove the noise\n",
        "# It is impossible that children , adults and babies are all equal to 0\n",
        "filter = (df['children']==0) & (df['adults']==0) & (df['babies']==0)\n",
        "df[filter]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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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>children</th>\n",
              "      <th>babies</th>\n",
              "      <th>meal</th>\n",
              "      <th>country</th>\n",
              "      <th>market_segment</th>\n",
              "      <th>distribution_channel</th>\n",
              "      <th>is_repeated_guest</th>\n",
              "      <th>previous_cancellations</th>\n",
              "      <th>previous_bookings_not_canceled</th>\n",
              "      <th>reserved_room_type</th>\n",
              "      <th>assigned_room_type</th>\n",
              "      <th>booking_changes</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>2224</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2015</td>\n",
              "      <td>October</td>\n",
              "      <td>41</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>SC</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>I</td>\n",
              "      <td>1</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>174.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient-Party</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>10/6/2015</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2409</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2015</td>\n",
              "      <td>October</td>\n",
              "      <td>42</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>SC</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>I</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>174.0</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>10/12/2015</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3181</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>36</td>\n",
              "      <td>2015</td>\n",
              "      <td>November</td>\n",
              "      <td>47</td>\n",
              "      <td>20</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>SC</td>\n",
              "      <td>ESP</td>\n",
              "      <td>Groups</td>\n",
              "      <td>TA/TO</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>C</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>38.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient-Party</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>11/23/2015</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3684</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>165</td>\n",
              "      <td>2015</td>\n",
              "      <td>December</td>\n",
              "      <td>53</td>\n",
              "      <td>30</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>SC</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Groups</td>\n",
              "      <td>TA/TO</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>A</td>\n",
              "      <td>1</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>308.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>122</td>\n",
              "      <td>Transient-Party</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>1/4/2016</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3708</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>165</td>\n",
              "      <td>2015</td>\n",
              "      <td>December</td>\n",
              "      <td>53</td>\n",
              "      <td>30</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>SC</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Groups</td>\n",
              "      <td>TA/TO</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>C</td>\n",
              "      <td>1</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>308.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>122</td>\n",
              "      <td>Transient-Party</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>1/5/2016</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <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>115029</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>107</td>\n",
              "      <td>2017</td>\n",
              "      <td>June</td>\n",
              "      <td>26</td>\n",
              "      <td>27</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>CHE</td>\n",
              "      <td>Online TA</td>\n",
              "      <td>TA/TO</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>A</td>\n",
              "      <td>1</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>100.80</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>6/30/2017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>115091</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2017</td>\n",
              "      <td>June</td>\n",
              "      <td>26</td>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>SC</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Complementary</td>\n",
              "      <td>Direct</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>E</td>\n",
              "      <td>K</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/1/2017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116251</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>44</td>\n",
              "      <td>2017</td>\n",
              "      <td>July</td>\n",
              "      <td>28</td>\n",
              "      <td>15</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>SC</td>\n",
              "      <td>SWE</td>\n",
              "      <td>Online TA</td>\n",
              "      <td>TA/TO</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>K</td>\n",
              "      <td>2</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>425.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>73.80</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/17/2017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116534</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2017</td>\n",
              "      <td>July</td>\n",
              "      <td>28</td>\n",
              "      <td>15</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>SC</td>\n",
              "      <td>RUS</td>\n",
              "      <td>Online TA</td>\n",
              "      <td>TA/TO</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>K</td>\n",
              "      <td>1</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient-Party</td>\n",
              "      <td>22.86</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/22/2017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117087</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>170</td>\n",
              "      <td>2017</td>\n",
              "      <td>July</td>\n",
              "      <td>30</td>\n",
              "      <td>27</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>BRA</td>\n",
              "      <td>Offline TA/TO</td>\n",
              "      <td>TA/TO</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>A</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>52.0</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>7/29/2017</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>180 rows × 32 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "               hotel  is_canceled  ...  reservation_status  reservation_status_date\n",
              "2224    Resort Hotel            0  ...           Check-Out                10/6/2015\n",
              "2409    Resort Hotel            0  ...           Check-Out               10/12/2015\n",
              "3181    Resort Hotel            0  ...           Check-Out               11/23/2015\n",
              "3684    Resort Hotel            0  ...           Check-Out                 1/4/2016\n",
              "3708    Resort Hotel            0  ...           Check-Out                 1/5/2016\n",
              "...              ...          ...  ...                 ...                      ...\n",
              "115029    City Hotel            0  ...           Check-Out                6/30/2017\n",
              "115091    City Hotel            0  ...           Check-Out                 7/1/2017\n",
              "116251    City Hotel            0  ...           Check-Out                7/17/2017\n",
              "116534    City Hotel            0  ...           Check-Out                7/22/2017\n",
              "117087    City Hotel            0  ...           Check-Out                7/29/2017\n",
              "\n",
              "[180 rows x 32 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ym3B5vdy73de"
      },
      "source": [
        "# Remove the noisy data\n",
        "data= df[~filter] # Negation of the filter so remove the noisy data"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FYBgkB7DfQ1M"
      },
      "source": [
        "Problem statement:\n",
        "1. From where location the guest are coming?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bHcsOKQtf_-o"
      },
      "source": [
        "# Determine from which country guest that cancelled are coming\n",
        "country_wise_data=data[data['is_canceled']==0]['country'].value_counts().reset_index() "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "_GnNRn9ziAUB",
        "outputId": "59e23aa3-7d81-40f0-d77e-c7081e8bedff"
      },
      "source": [
        "country_wise_data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>country</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>PRT</td>\n",
              "      <td>20977</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>GBR</td>\n",
              "      <td>9668</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>FRA</td>\n",
              "      <td>8468</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ESP</td>\n",
              "      <td>6383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>DEU</td>\n",
              "      <td>6067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>161</th>\n",
              "      <td>GUY</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162</th>\n",
              "      <td>BHS</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>163</th>\n",
              "      <td>BFA</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>164</th>\n",
              "      <td>SMR</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>165</th>\n",
              "      <td>TJK</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>166 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    index  country\n",
              "0     PRT    20977\n",
              "1     GBR     9668\n",
              "2     FRA     8468\n",
              "3     ESP     6383\n",
              "4     DEU     6067\n",
              "..    ...      ...\n",
              "161   GUY        1\n",
              "162   BHS        1\n",
              "163   BFA        1\n",
              "164   SMR        1\n",
              "165   TJK        1\n",
              "\n",
              "[166 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "x09AN7eUg8nU",
        "outputId": "e8e7ebb5-2f5e-40e6-aa39-fd952396f059"
      },
      "source": [
        "  # Change the columns name because they are shifted\n",
        "  country_wise_data.columns=['country', 'No of guests']\n",
        "  country_wise_data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>No of guests</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>PRT</td>\n",
              "      <td>20977</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>GBR</td>\n",
              "      <td>9668</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>FRA</td>\n",
              "      <td>8468</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ESP</td>\n",
              "      <td>6383</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>DEU</td>\n",
              "      <td>6067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>161</th>\n",
              "      <td>GUY</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162</th>\n",
              "      <td>BHS</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>163</th>\n",
              "      <td>BFA</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>164</th>\n",
              "      <td>SMR</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>165</th>\n",
              "      <td>TJK</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>166 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    country  No of guests\n",
              "0       PRT         20977\n",
              "1       GBR          9668\n",
              "2       FRA          8468\n",
              "3       ESP          6383\n",
              "4       DEU          6067\n",
              "..      ...           ...\n",
              "161     GUY             1\n",
              "162     BHS             1\n",
              "163     BFA             1\n",
              "164     SMR             1\n",
              "165     TJK             1\n",
              "\n",
              "[166 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d4lMlas-hrTk",
        "outputId": "b8e917c7-fdd8-4663-dbde-2b63e10383d7"
      },
      "source": [
        "!pip install folium"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: folium in /usr/local/lib/python3.7/dist-packages (0.8.3)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from folium) (2.23.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from folium) (1.19.5)\n",
            "Requirement already satisfied: branca>=0.3.0 in /usr/local/lib/python3.7/dist-packages (from folium) (0.4.2)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.7/dist-packages (from folium) (2.11.3)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from folium) (1.15.0)\n",
            "Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.7/dist-packages (from jinja2->folium) (2.0.1)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->folium) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->folium) (2021.5.30)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->folium) (1.24.3)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->folium) (3.0.4)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q05Josg_iVlU"
      },
      "source": [
        "import folium\n",
        "from folium.plugins import HeatMap"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gyrzXMKrigIJ"
      },
      "source": [
        "basemap= folium.Map()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h3YpntjailnP",
        "outputId": "09d7c827-264e-4b31-8040-252b63122f17"
      },
      "source": [
        "!pip install plotly"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: plotly in /usr/local/lib/python3.7/dist-packages (4.4.1)\n",
            "Requirement already satisfied: retrying>=1.3.3 in /usr/local/lib/python3.7/dist-packages (from plotly) (1.3.3)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from plotly) (1.15.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p3Psj1efXj3U",
        "outputId": "502c658d-3a1f-4bfd-9c1c-68980b12ac5a"
      },
      "source": [
        "!pip install plotly --upgrade"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: plotly in /usr/local/lib/python3.7/dist-packages (4.4.1)\n",
            "Collecting plotly\n",
            "  Downloading plotly-5.3.1-py2.py3-none-any.whl (23.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 23.9 MB 13 kB/s \n",
            "\u001b[?25hCollecting tenacity>=6.2.0\n",
            "  Downloading tenacity-8.0.1-py3-none-any.whl (24 kB)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from plotly) (1.15.0)\n",
            "Installing collected packages: tenacity, plotly\n",
            "  Attempting uninstall: plotly\n",
            "    Found existing installation: plotly 4.4.1\n",
            "    Uninstalling plotly-4.4.1:\n",
            "      Successfully uninstalled plotly-4.4.1\n",
            "Successfully installed plotly-5.3.1 tenacity-8.0.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "khbrqmetlPrq"
      },
      "source": [
        "import  plotly.express as px\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "9LH9q9exlTBu",
        "outputId": "96888566-1a9f-4486-9246-5780382395ab"
      },
      "source": [
        "# Can use either HeatMap or choropleth map \n",
        "map_guest= px.choropleth(country_wise_data,\n",
        "              locations=country_wise_data['country'],\n",
        "              color=country_wise_data['No of guests'],\n",
        "              hover_name=country_wise_data['country'],\n",
        "              title='Home country of guests')\n",
        "map_guest.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
              "<body>\n",
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          "metadata": {}
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      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FzEA14UqmKg5"
      },
      "source": [
        "Problem 2 : How much per night guest pay?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OBRY6FmpnggC"
      },
      "source": [
        "data2 = data[data['is_canceled']==0] #need a price distribution of each of room type"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
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        "id": "mNj7IUcCn8dQ",
        "outputId": "3a66fe93-e19d-4950-ea70-52af27f6b36d"
      },
      "source": [
        "data2.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['hotel', 'is_canceled', 'lead_time', 'arrival_date_year',\n",
              "       'arrival_date_month', 'arrival_date_week_number',\n",
              "       'arrival_date_day_of_month', 'stays_in_weekend_nights',\n",
              "       'stays_in_week_nights', 'adults', 'children', 'babies', 'meal',\n",
              "       'country', 'market_segment', 'distribution_channel',\n",
              "       'is_repeated_guest', 'previous_cancellations',\n",
              "       'previous_bookings_not_canceled', 'reserved_room_type',\n",
              "       'assigned_room_type', 'booking_changes', 'deposit_type', 'agent',\n",
              "       'company', 'days_in_waiting_list', 'customer_type', 'adr',\n",
              "       'required_car_parking_spaces', 'total_of_special_requests',\n",
              "       'reservation_status', 'reservation_status_date'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
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          "height": 449
        },
        "id": "86swmVNwnuXH",
        "outputId": "2dd3245d-484d-42b0-ffed-50ee102d5d2d"
      },
      "source": [
        "plt.figure(figsize=(12,8))\n",
        "sns.boxplot(x='reserved_room_type', y='adr', hue='hotel', data=data2) # adr is price, hue: we want the distribution both for the hotel\n",
        "plt.title('Price of room types per night and per person')\n",
        "plt.xlabel('Room type')\n",
        "plt.ylabel('Price(Euro)')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CdCW5GEbomyI"
      },
      "source": [
        "Problem Statement: \n",
        "1. How does the price vary by night "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L8tHMUpcq-Io"
      },
      "source": [
        "data_resort = data[(data['hotel']=='Resort Hotel') & (data['is_canceled']==0)]\n",
        "data_city = data[(data['hotel']=='City Hotel') & (data['is_canceled']==0)]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "kil0uq6PtBQM",
        "outputId": "c952a1c8-20f2-4c21-e29c-63480002fb14"
      },
      "source": [
        "data_resort.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>children</th>\n",
              "      <th>babies</th>\n",
              "      <th>meal</th>\n",
              "      <th>country</th>\n",
              "      <th>market_segment</th>\n",
              "      <th>distribution_channel</th>\n",
              "      <th>is_repeated_guest</th>\n",
              "      <th>previous_cancellations</th>\n",
              "      <th>previous_bookings_not_canceled</th>\n",
              "      <th>reserved_room_type</th>\n",
              "      <th>assigned_room_type</th>\n",
              "      <th>booking_changes</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Direct</td>\n",
              "      <td>Direct</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>C</td>\n",
              "      <td>C</td>\n",
              "      <td>3</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/1/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Direct</td>\n",
              "      <td>Direct</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>C</td>\n",
              "      <td>C</td>\n",
              "      <td>4</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/1/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>GBR</td>\n",
              "      <td>Direct</td>\n",
              "      <td>Direct</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>C</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/2/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>GBR</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>A</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>304.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/2/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>GBR</td>\n",
              "      <td>Online TA</td>\n",
              "      <td>TA/TO</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>A</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>240.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>98.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/3/2015</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          hotel  is_canceled  ...  reservation_status  reservation_status_date\n",
              "0  Resort Hotel            0  ...           Check-Out                 7/1/2015\n",
              "1  Resort Hotel            0  ...           Check-Out                 7/1/2015\n",
              "2  Resort Hotel            0  ...           Check-Out                 7/2/2015\n",
              "3  Resort Hotel            0  ...           Check-Out                 7/2/2015\n",
              "4  Resort Hotel            0  ...           Check-Out                 7/3/2015\n",
              "\n",
              "[5 rows x 32 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "93ID8HeCtDsf",
        "outputId": "fe973d99-851b-4cbe-8876-4c61e19989f2"
      },
      "source": [
        "resort_hotel = data_resort.groupby(['arrival_date_month'])['adr'].mean().reset_index() #reset_index() to build a dataframe\n",
        "resort_hotel"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>arrival_date_month</th>\n",
              "      <th>adr</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>April</td>\n",
              "      <td>75.867816</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>August</td>\n",
              "      <td>181.205892</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>December</td>\n",
              "      <td>68.410104</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>February</td>\n",
              "      <td>54.147478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>January</td>\n",
              "      <td>48.761125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>July</td>\n",
              "      <td>150.122528</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>June</td>\n",
              "      <td>107.974850</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>March</td>\n",
              "      <td>57.056838</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>May</td>\n",
              "      <td>76.657558</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>November</td>\n",
              "      <td>48.706289</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>October</td>\n",
              "      <td>61.775449</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>September</td>\n",
              "      <td>96.416860</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   arrival_date_month         adr\n",
              "0               April   75.867816\n",
              "1              August  181.205892\n",
              "2            December   68.410104\n",
              "3            February   54.147478\n",
              "4             January   48.761125\n",
              "5                July  150.122528\n",
              "6                June  107.974850\n",
              "7               March   57.056838\n",
              "8                 May   76.657558\n",
              "9            November   48.706289\n",
              "10            October   61.775449\n",
              "11          September   96.416860"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "CUAvLEgKtsT9",
        "outputId": "5cc462cf-6f45-4a1c-ae5e-ef3de9a82b87"
      },
      "source": [
        "city_hotel = data_city.groupby(['arrival_date_month'])['adr'].mean().reset_index() #reset_index() to build a dataframe\n",
        "city_hotel"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>arrival_date_month</th>\n",
              "      <th>adr</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>April</td>\n",
              "      <td>111.962267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>August</td>\n",
              "      <td>118.674598</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>December</td>\n",
              "      <td>88.401855</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>February</td>\n",
              "      <td>86.520062</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>January</td>\n",
              "      <td>82.330983</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>July</td>\n",
              "      <td>115.818019</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>June</td>\n",
              "      <td>117.874360</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>March</td>\n",
              "      <td>90.658533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>May</td>\n",
              "      <td>120.669827</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>November</td>\n",
              "      <td>86.946592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>October</td>\n",
              "      <td>102.004672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>September</td>\n",
              "      <td>112.776582</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   arrival_date_month         adr\n",
              "0               April  111.962267\n",
              "1              August  118.674598\n",
              "2            December   88.401855\n",
              "3            February   86.520062\n",
              "4             January   82.330983\n",
              "5                July  115.818019\n",
              "6                June  117.874360\n",
              "7               March   90.658533\n",
              "8                 May  120.669827\n",
              "9            November   86.946592\n",
              "10            October  102.004672\n",
              "11          September  112.776582"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "DGczZ2n_t8pG",
        "outputId": "0ee4745c-9e3f-47fe-997d-eb11b7d6ff8f"
      },
      "source": [
        "# We have 2 tables with 1 column in common so let's buid a common dataframe\n",
        "final = resort_hotel.merge(city_hotel, on='arrival_date_month')\n",
        "final.columns=['month','price_for_resort','price_for_city_hotel']\n",
        "final"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>month</th>\n",
              "      <th>price_for_resort</th>\n",
              "      <th>price_for_city_hotel</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>April</td>\n",
              "      <td>75.867816</td>\n",
              "      <td>111.962267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>August</td>\n",
              "      <td>181.205892</td>\n",
              "      <td>118.674598</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>December</td>\n",
              "      <td>68.410104</td>\n",
              "      <td>88.401855</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>February</td>\n",
              "      <td>54.147478</td>\n",
              "      <td>86.520062</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>January</td>\n",
              "      <td>48.761125</td>\n",
              "      <td>82.330983</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>July</td>\n",
              "      <td>150.122528</td>\n",
              "      <td>115.818019</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>June</td>\n",
              "      <td>107.974850</td>\n",
              "      <td>117.874360</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>March</td>\n",
              "      <td>57.056838</td>\n",
              "      <td>90.658533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>May</td>\n",
              "      <td>76.657558</td>\n",
              "      <td>120.669827</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>November</td>\n",
              "      <td>48.706289</td>\n",
              "      <td>86.946592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>October</td>\n",
              "      <td>61.775449</td>\n",
              "      <td>102.004672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>September</td>\n",
              "      <td>96.416860</td>\n",
              "      <td>112.776582</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        month  price_for_resort  price_for_city_hotel\n",
              "0       April         75.867816            111.962267\n",
              "1      August        181.205892            118.674598\n",
              "2    December         68.410104             88.401855\n",
              "3    February         54.147478             86.520062\n",
              "4     January         48.761125             82.330983\n",
              "5        July        150.122528            115.818019\n",
              "6        June        107.974850            117.874360\n",
              "7       March         57.056838             90.658533\n",
              "8         May         76.657558            120.669827\n",
              "9    November         48.706289             86.946592\n",
              "10    October         61.775449            102.004672\n",
              "11  September         96.416860            112.776582"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VbgF77oRyAGw",
        "outputId": "2cee1ead-0ce5-4793-8225-c424114dba75"
      },
      "source": [
        " # Need to sort the Month columns\n",
        " !pip install sort-dataframeby-monthorweek"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting sort-dataframeby-monthorweek\n",
            "  Downloading sort_dataframeby_monthorweek-0.4.tar.gz (2.8 kB)\n",
            "Building wheels for collected packages: sort-dataframeby-monthorweek\n",
            "  Building wheel for sort-dataframeby-monthorweek (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sort-dataframeby-monthorweek: filename=sort_dataframeby_monthorweek-0.4-py3-none-any.whl size=3441 sha256=fd696cdf9b27bdc85d46bb14995064a23bcc57290dac4bd2a5561c72d8c6ffee\n",
            "  Stored in directory: /root/.cache/pip/wheels/de/e1/ad/5fe265a9780676079c4b8caaaffaa8d5c4ab2f37cf823e8aa8\n",
            "Successfully built sort-dataframeby-monthorweek\n",
            "Installing collected packages: sort-dataframeby-monthorweek\n",
            "Successfully installed sort-dataframeby-monthorweek-0.4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ug7c6ggp0fUN",
        "outputId": "2557c7b7-76eb-4d9d-8535-d3feaab3eb8b"
      },
      "source": [
        "!pip install sorted-months-weekdays"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting sorted-months-weekdays\n",
            "  Downloading sorted_months_weekdays-0.2.tar.gz (2.7 kB)\n",
            "Building wheels for collected packages: sorted-months-weekdays\n",
            "  Building wheel for sorted-months-weekdays (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sorted-months-weekdays: filename=sorted_months_weekdays-0.2-py3-none-any.whl size=3247 sha256=62cc4fc09b6113a5efcb5411a0d28ccb5063ff4b2b831d7dc69d805cbc19d7ed\n",
            "  Stored in directory: /root/.cache/pip/wheels/4f/4f/78/3f1b8fc72651f7c766a6f73d667fccb12a8aabe240b38df7a4\n",
            "Successfully built sorted-months-weekdays\n",
            "Installing collected packages: sorted-months-weekdays\n",
            "Successfully installed sorted-months-weekdays-0.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PNFUHst_0lyK"
      },
      "source": [
        "import sort_dataframeby_monthorweek as sd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_34Xq9kC0snp"
      },
      "source": [
        "def sort_data(df, colname):\n",
        "  return sd.Sort_Dataframeby_Month(df, colname)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "T3x2ewYW1Byn",
        "outputId": "1189dfb4-c808-44dc-a5d3-a83e9be632a7"
      },
      "source": [
        "final = sort_data(final,'month')\n",
        "final"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>month</th>\n",
              "      <th>price_for_resort</th>\n",
              "      <th>price_for_city_hotel</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>January</td>\n",
              "      <td>48.761125</td>\n",
              "      <td>82.330983</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>February</td>\n",
              "      <td>54.147478</td>\n",
              "      <td>86.520062</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>March</td>\n",
              "      <td>57.056838</td>\n",
              "      <td>90.658533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>April</td>\n",
              "      <td>75.867816</td>\n",
              "      <td>111.962267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>May</td>\n",
              "      <td>76.657558</td>\n",
              "      <td>120.669827</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>June</td>\n",
              "      <td>107.974850</td>\n",
              "      <td>117.874360</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>July</td>\n",
              "      <td>150.122528</td>\n",
              "      <td>115.818019</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>August</td>\n",
              "      <td>181.205892</td>\n",
              "      <td>118.674598</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>September</td>\n",
              "      <td>96.416860</td>\n",
              "      <td>112.776582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>October</td>\n",
              "      <td>61.775449</td>\n",
              "      <td>102.004672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>November</td>\n",
              "      <td>48.706289</td>\n",
              "      <td>86.946592</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>December</td>\n",
              "      <td>68.410104</td>\n",
              "      <td>88.401855</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        month  price_for_resort  price_for_city_hotel\n",
              "0     January         48.761125             82.330983\n",
              "1    February         54.147478             86.520062\n",
              "2       March         57.056838             90.658533\n",
              "3       April         75.867816            111.962267\n",
              "4         May         76.657558            120.669827\n",
              "5        June        107.974850            117.874360\n",
              "6        July        150.122528            115.818019\n",
              "7      August        181.205892            118.674598\n",
              "8   September         96.416860            112.776582\n",
              "9     October         61.775449            102.004672\n",
              "10   November         48.706289             86.946592\n",
              "11   December         68.410104             88.401855"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7ITY6W-91cO0",
        "outputId": "41b3e398-1e1e-4d78-a1a9-a8d1049d65c5"
      },
      "source": [
        "final.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['month', 'price_for_resort', 'price_for_city_hotel'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0lxGlBWn2e7R",
        "outputId": "d5d9b40a-76c2-41d8-a0fa-f1e627824ef7"
      },
      "source": [
        "final['price_for_resort']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      48.761125\n",
              "1      54.147478\n",
              "2      57.056838\n",
              "3      75.867816\n",
              "4      76.657558\n",
              "5     107.974850\n",
              "6     150.122528\n",
              "7     181.205892\n",
              "8      96.416860\n",
              "9      61.775449\n",
              "10     48.706289\n",
              "11     68.410104\n",
              "Name: price_for_resort, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wLdDZhPg4Ag0",
        "outputId": "532ad11a-0086-4ec6-9afc-7ae745edd855"
      },
      "source": [
        "final['price_for_city_hotel']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      82.330983\n",
              "1      86.520062\n",
              "2      90.658533\n",
              "3     111.962267\n",
              "4     120.669827\n",
              "5     117.874360\n",
              "6     115.818019\n",
              "7     118.674598\n",
              "8     112.776582\n",
              "9     102.004672\n",
              "10     86.946592\n",
              "11     88.401855\n",
              "Name: price_for_city_hotel, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "780XV8nz1FlB"
      },
      "source": [
        "# Lineplot\n",
        "#px.line(final, x='month', y=(final['price_for_resort'],final['price_for_city_hotel']), title='Room price per night over the Months')\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "id": "3NS2GiUV7EcH",
        "outputId": "ebc86e08-911f-4712-fc0f-8481cf68815b"
      },
      "source": [
        "\n",
        "plt.figure(figsize=(20,8))\n",
        "plt.plot(final['month'],final['price_for_resort'],label='Resort')\n",
        "plt.plot(final['month'],final['price_for_city_hotel'],label='City_hotel')\n",
        "plt.grid(True)\n",
        "plt.legend()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f5d42562a50>"
            ]
          },
          "metadata": {},
          "execution_count": 37
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fdJhLl53XX0vzi/WTa8+TK5AJ+wD8j8vl0pAhQ5yOcVorV65UZmam0zF6Hf8HAgAAgF/6dFe57n51vQbGhmn+fb1fBrXJzkxV+bEGrdrpmX8ZBwD4BwohAAAA+J01u+0yaEDfMC24b4ri3FQGSdIlI+MVGx6sxblFbntOAABORiEEAAAAv7J2d7m++cf1Sunbx+1lkCQFBwXo+rQkvbf1oCpqG9363AAAtKEQAgAAgN9Y98VhffPV9UqOCdWC+yYrPtK9ZVCb7KxUNTS16N1NBxx5fgAAKIQAAADgF9bvOazZf1ynpOhQLZwzRf0jnTuDTHpqtIbGh7NsDADgGAohAAAA+LzP9hzW7FfWKTE6VAvvc7YMkiRjjGZkpmjdF4e1/3CNo1kAAP6JQggAAAA+bcPew7rrlXVKiArVovumqH+Us2VQmxszUiRJbzNLCADgAAohAAAA+KwNe4/orlfWq39U6zIxDymDJGlAbJgmD4nVktwiWZbldBwAgJ+hEAIAAIBPytl3RHe9sk7xkSFaeN8UJXhQGdRmRlaKdh86pvzCCqejAAD8DIUQAAAAfE7uviO66+V1iosI1sL7pigx2vPKIEm6enySQoICtDin0OkoAAA/QyEEAAAAn5K3/6i+8fI6xUYEa+Eczy2DJCkq1KXLxyRoaX6xGppanI4DAPAjFEIAAADwGfn7j+rrL69V33B7ZlBSdB+nI53VjKwUHalp1Ec7y5yOAgDwIxRCAAAA8AkbC4/qzpfXKibMpYVzpig5xvPLIEmaOiJe/cKDWTYGAHArCiEAAAB4vU2FFbrzD3YZtGjOBUrxkjJIklyBAbohI1kfbCtVRU2j03EAAH6CQggAAABebXNRhe74wxpF9XFp4X1TvKoMajMjM1UNzS36+6YDTkcBAPgJCiEAAAB4LbsMWqvIULsMSu0b5nSkbhmXEqXh/SNYNgYAcBsKIQAAAHiltjIoIiRIi+ZM0YBY7yyDJMkYoxlZKfps7xHtK69xOg4AwA9QCAEAAMDrbCmu0J0v+0YZ1OamjBQZIy3JLXI6CgDAD1AIAQAAwKtsLa7UHX9YqzBXoBbe5xtlkCQlx/TRlCH9tDi3UJZlOR0HAODjKIQAAADgNbYdqNQdf1ijPq5ALZwzRQP7+UYZ1GZGVor2ltcoZ99Rp6MAAHwchRAAAAC8wvYSe2ZQqCtQi+ZM0aB+4U5H6nFXj09SqCtAS3LZXBoA0LsohAAAAODxtpdU6vaX1io4MEAL7/PNMkiSIkKCdMWYRC3NP6D6pman4wAAfBiFEAAAADzajpIq3f7SWrkCjRbOmaLBcb5ZBrWZkZWiitpGfbi9zOkoAAAfRiEEAAAAj7XzYJVuf2mNggKMFs25QEN8vAySpIuGxykuIoRlYwCAXkUhBAAAAI/0eWsZFBhgtGjOFL8ogyQpKDBAN2Yka8X2Uh051uB0HACAj6IQAgAAgMcpKK3SrJfWyhh7mdjQ+AinI7nVjKwUNTZbWrbpgNNRAAA+ikIIAAAAHqWgtEoz562VMdLC+6ZomJ+VQZI0JilKoxIitSSHZWMAgN5BIQQAAACPUVBarZnz1kqyy6Dh/f2vDJIkY4yys1KUs++ovjh0zOk4AAAfRCEEAAAAj7CrrFqzXlojydKiOZP9tgxqc1NGioyRluQWOR0FAOCDKIQAAADguN1l1Zo1b40sy2qdGRTpdCTHJUaH6sJhcVqSWyjLspyOAwDwMRRCAAAAcNQXh45p1ktr1NxiacF9UzQigTKoTXZmivYfrtVne484HQUA4GMohAAAAOCYLw4d08x5n6qp2S6DRlIGneCqcYnq4wrU4hyWjQEAehaFEAAAAByx59AxzZq3Ro2tZdCoRMqgk4WHBOmqcYn6+8Zi1TU2Ox0HAOBDKIQAAADgdnvL7WVi9U3NWnDfZMqgM8jOTFFlXZNWbC91OgoAwIdQCAEAAMCt9pYf08x5a1TX2KwF903R6MQopyN5tAuHx6l/ZAjLxgAAPYpCCAAAAG6zr7xGs+atUW1js+bfO0XnJVEGnU1ggNFNmSlauaNUh481OB0HAOAjKIQAAADgFvsP12jWS2tU09is+fdO1phkyqDOys5MUVOLpaX5xU5HAQD4CAohAAAA9Lr9h2s0c94aVdc36fV7JmtscrTTkbzKeUlROi8pSotzWTYGAOgZZy2EjDGvGGNKjTGbTzr+XWPMdmPMFmPMb447/qgxpsAYs8MYc2VvhAYAAID3OL4Mmn/vZI1LoQzqjhmZKcrff1S7yqqdjgIA8AGdmSH0qqSrjj9gjJku6UZJ6ZZljZX0ROvxMZJmShrb+jX/zxgT2JOBAQAA4D0Kj9jLxKrqGimDztGNGckKMNISNpcGAPSAsxZClmWtknT4pMPfkfS4ZVn1rfdpOwfmjZIWWZZVb1nWF5IKJJ3fg3kBAADgJYqO1mrWS2tUWduo+fdOoQw6R/2jQnXRiHgtyS1SS4vldBwAgJfr7h5CIyVNNcasNcZ8ZIyZ1Ho8RdL+4+5X2HoMAAAAfqT4aK1mzvtUR2sa9fq9kzU+lTKoJ8zITFHR0Vqt33Py32sBAOgaY1ln/+uCMWawpGWWZY1rvb5Z0oeSHpI0SdIbkoZKelbSGsuyXm+938uS3rUs668dPOYcSXMkKSEhYcKiRYt64OU4r7q6WhEREU7H8BuMt3sx3u7HmLsX4+1ejLd7uXO8y2tb9Pi6OlU3WvrhpFANjfbPHQR6Y8zrmyw99GGNJicF6e5xIT362N6OnynuxXi7F+PtXr403tOnT99gWdbEjm4L6uZjFkpabNlt0jpjTIukOElFkgYcd7/U1mOnsCxrnqR5kjRx4kRr2rRp3YziWVauXClfeS3egPF2L8bb/Rhz92K83Yvxdi93jfeBilrNnLdGdS2BWvitycoYENPrz+mpemvMrzucr+VbSjTlwqkKdfln2dYRfqa4F+PtXoy3e/nLeHd3ydjbkqZLkjFmpKRgSYck/U3STGNMiDFmiKQRktb1RFAAAAB4tpKKOs2ct0aHqxv02j3n+3UZ1JtmZKWoqr5J72876HQUAIAX68xp5xdK+lTSKGNMoTHmHkmvSBraunRskaS7LNsWSW9K2irpn5IesCyruffiAwAAwBPYZdCnKq9u0J/uOV+ZA/s6HclnTRnaT4lRoVrM2cYAAOfgrEvGLMuadZqb7jzN/R+T9Ni5hAIAAID3OFhZp1kvrdGh6gb96e7zlUUZ1KsCA4xuykzRSx/v1qHqesVFsJcQAKDrurtkDAAAALDLoHlrVFpZpz/dPUkTBlEGucOMrBQ1t1haml/sdBQAgJeiEAIAAEC3lLbODDpYWac/3X2+JgyKdTqS3xiZEKmxyVFaksuyMQBA91AIAQAAoMtKq+wyqKSiTq/efb4mDqYMcrcZWanaWFihgtIqp6MAALwQhRAAAAC6pLTKXiZ2oKJOr37zfE2iDHLEDenJCgwwbC4NAOgWCiEAAAB0WllVvW5/aa0OVNTpj7Mn6fwhlEFOiY8M0dQRcXo7t0gtLZbTcQAAXoZCCAAAAJ1il0FrVHSkVq/MnqTJQ/s5HcnvzchKVXFFndZ8Ue50FACAl6EQAgAAwFkdqq7XHX9Yo8LWMmgKZZBHuGJMgiJCgrSEZWMAgC6iEAIAAMAZlVfX646X1mrf4Rq9PHuiLhhGGeQpQl2Bunpcot7dXKLahman4wAAvAiFEAAAAE6rvNreM2jv4WN65a5J+sqwOKcj4SQzslJVXd+k5VtLnI4CAPAiFEIAAADo0OFjDbrjD2u1p/yYXr5rkr4ynDLIE00eEquUmD5aksuyMQBA51EIAQAA4BSHjzXo9pfW6ItDdhl0IWWQxwoIMLoxI1kff35IpVV1TscBAHgJCiEAAACc4EjrzKAvDh3TH+6aqItGUAZ5uhlZKWpusfS3vGKnowAAvASFEAAAAL7UVgbtKqvWS9+YqKkj4p2OhE4Y3j9SaanRLBsDAHQahRAAAAAkSUdrGnTny2tV0FoGXTySMsibZGemaEtxpXaUVDkdBQDgBSiEAAAA8GUZ9HlpteZ9fYIuoQzyOtenJysowGhxbqHTUQAAXoBCCAAAwM9V1DTqzpfXamdJtX7/9QmaNqq/05HQDXERIbpkZLzeyS1Wc4vldBwAgIejEAIAAPBjFbUnlkHTKYO8WnZWikoq67Rmd7nTUQAAHo5CCAAAwE9V1Dbq6y+v1faSSr349SxNH00Z5O0uOy9BkSFBeiuHZWMAgDOjEAIAAPBDlXWN+sbLa7XtQKVevHOCLh2d4HQk9IBQV6CuTUvSPzeXqKahyek4AAAPRiEEAADgZyrrGvX1l9dp64FKvXDHBH31PMogX5KdmaKahmYt33LQ6SgAAA9GIQQAAOBH7JlB67S1uELP356ly8ZQBvmaSYNjlRLTh2VjAIAzohACAADwE1V1jbrrlXXaXGSXQVeMTXQ6EnpBQIDRjKwUfVJwSKWVdU7HAQB4KAohAAAAP1DbZOmuV9ZpU2GFnqMM8nnZmSlqsaR38oqdjgIA8FAUQgAAAD6uur5JT35Wp42FFXru9kxdNY4yyNcNjY9Q+oAYlo0BAE6LQggAAMCHWZalH/01X7srWvTsrExdNS7J6Uhwk5uzUrS9pErbDlQ6HQUA4IEohAAAAHzYwnX79Y9NJfraCJeuHk8Z5E+uS0tWUIDRktwip6MAADwQhRAAAICP2lFSpV8s3aKpI+J01RCX03HgZrHhwZo2qr/ezi1Sc4vldBwAgIehEAIAAPBBtQ3NenBBjiJDXXrq1gwFGON0JDjg5qwUlVbV65OCQ05HAQB4GAohAAAAHzR32RZ9Xlqtp29LV3xkiNNx4JBLz+uvqNAglo0BAE5BIQQAAOBjlm0s1sJ1+/WdacM0dUS803HgoJCgQF2blqx/bi7Rsfomp+MAADwIhRAAAIAP2X+4Ro++tUmZA2P08OUjnY4DD3BzVopqG5v1z80lTkcBAHgQCiEAAAAf0djcogcX5kpGemZmplyBvNWDNGFQXw2MDWPZGADgBLxLAAAA8BFPLN+h/P1H9fiMNA2IDXM6DjyEMUY3Zabok12HdKCi1uk4AAAPQSEEAADgA1btLNPvP9qt2ycP1LVpSU7HgYeZkZkiy5LeySt2OgoAwENQCAEAAHi50qo6PfxmnkYlROpn141xOg480OC4cGUNjNHinEJZluV0HACAB6AQAgAA8GItLZYefiNf1fVNevb2TIW6Ap2OBA+VnZWqnQertaW40ukoAAAPQCEEAADgxV5ctUurCw7p59eP1ciESKfjwINdn5YkV6Bhc2kAgCQKIQAAAK+1Ye8RPbl8p65NS9LMSQOcjgMPFxMWrEtH99c7ecVqam5xOg4AwGEUQgAAAF6oorZRDy3MVVJ0qH41Y7yMMU5HghfIzkzVoep6fVxwyOkoAACHUQgBAAB4Gcuy9MhbG3Wwsk7PzspUVKjL6UjwEtNHxysmzKUlOSwbAwB/RyEEAADgZRas26d3N5foP64cpcyBfZ2OAy8SEhSo69KStHxriarqGp2OAwBwEIUQAACAF9lRUqW5S7dq6og4zZk61Ok48ELZmamqa2zRu5tLnI4CAHAQhRAAAICXqG1o1oMLchQZ6tJTt2YoIIB9g9B1WQNjNLhfGMvGAMDPUQgBAAB4ibnLtqigrFr/e1uG4iNDnI4DL2WMUXZmqtZ8Ua6io7VOxwEAOIRCCAAAwAsszS/WwnX79e1LhumiEXFOx4GXy85MkWVJb+cySwgA/BWFEAAAgIfbf7hGP168SZkDY/Tw5SOdjgMfMLBfmCYN7qsluUWyLMvpOAAAB1AIAQAAeLDG5hY9uDBXMtIzMzPlCuTtG3pGdmaqCkqrtbmo0ukoAAAH8I4CAADAgz2xfIfy9x/Vr29O04DYMKfjwIdcOz5JwYEBeiun0OkoAAAHUAgBAAB4qI92lun3H+3W7ZMH6prxSU7HgY+JDnPpsjH9tTS/WI3NLU7HAQC4GYUQAACAByqtqtMP3szTqIRI/ey6MU7HgY/KzkxV+bEGffx5mdNRAABuRiEEAADgYVpaLD38Rr6q65v07O2ZCnUFOh0JPuqSkfHqG+bSWzmcbQwA/M1ZC8SBHecAACAASURBVCFjzCvGmFJjzOYObvuBMcYyxsS1XjfGmGeMMQXGmI3GmKzeCA0AAODLXly1S6sLDum/rx+rkQmRTseBDwsOCtAN6cl6b+tBVdY1Oh0HAOBGnZkh9Kqkq04+aIwZIOkKSfuOO3y1pBGtlzmSXjj3iAAAAP5jw94jenL5Tl2blqTbJg1wOg78QHZWqhqaWvTupgNORwEAuNFZCyHLslZJOtzBTU9L+pEk67hjN0p6zbKtkRRjjGEHRAAAgE6oqG3UQwtzlRQdql/NGC9jjNOR4AfSU6M1NC6cZWMA4Ge6tYeQMeZGSUWWZeWfdFOKpP3HXS9sPQYAAIAzsCxLj7y1UQcr6/TsrExFhbqcjgQ/YYzRjKwUrfvisPYfrnE6DgDATYxlWWe/kzGDJS2zLGucMSZM0oeSrrAsq8IYs0fSRMuyDhljlkl63LKs1a1f94Gk/7Qs67MOHnOO7GVlSkhImLBo0aIeeknOqq6uVkREhNMx/Abj7V6Mt/sx5u7FeLsX432iD/c16k9bG3TrKJeuGRLc44/PeLufN415WU2LfriqVjNGuHTDsJ7//nMHbxpvX8B4uxfj7V6+NN7Tp0/fYFnWxI5uC+rG4w2TNERSfus05lRJOcaY8yUVSTp+sXtq67FTWJY1T9I8SZo4caI1bdq0bkTxPCtXrpSvvBZvwHi7F+Ptfoy5ezHe7sV4t9tRUqVF76/WxSPj9fhdkxQQ0PNLxRhv9/O2Mf/L/k+Vd6ReT15yiVcuV/S28fZ2jLd7Md7u5S/j3eUlY5ZlbbIsq79lWYMtyxose1lYlmVZJZL+JukbrWcbmyKpwrIsdqcDAAA4jdqGZj24IEeRoS49eUt6r5RBQGfcnJWi3YeOKb+wwukoAAA36Mxp5xdK+lTSKGNMoTHmnjPc/R+SdksqkPSSpPt7JCUAAICPmrtsiwrKqvW/t2UoPjLE6TjwY1ePT1JIUICW5BQ6HQUA4AZnXTJmWdass9w++LjPLUkPnHssAAAA37c0v1gL1+3X/dOG6aIRcU7HgZ+LCnXpsjEJ+lt+sX5y7RgFB3Xr/DMAAC/BT3kAAAAH7D9cox8v3qTMgTH6/uUjnY4DSLKXjR2padRHO8ucjgIA6GUUQgAAAG7W2NyiBxfmSkZ6ZmamXIG8JYNnmDoiXv3Cg7Ukl2VjAODrePcBAADgZk8s36H8/Uf165vTNCA2zOk4wJdcgQG6Pj1Z728tVUVNo9NxAAC9iEIIAADAjT7aWabff7Rbd0weqGvGJzkdBzjFzVmpamhu0d83cbJgAPBlFEIAAABuUlpVpx+8madRCZH6r+vGOB0H6NC4lCgN7x/BsjEA8HEUQgAAAG7Q0mLp4TfyVV3fpGdvz1SoK9DpSECHjDHKzkzR+j1HtK+8xuk4AIBeQiEEAADgBi+u2qXVBYf039eP1ciESKfjAGd0U2aKjJGW5BY5HQUA0EsohAAAAHrZhr1H9OTynbouLUm3TRrgdBzgrFJi+mjKkH5aklsoy7KcjgMA6AUUQgAAAL2oorZRDy3MVXJMqH45Y7yMMU5HAjolOytFe8prlLPvqNNRAAC9gEIIAACgl1iWpUfe2qiDlXV6ZmamokJdTkcCOu3qcYkKdQWwuTQA+CgKIQAAgF6yYN0+vbu5RD+8cpQyB/Z1Og7QJZGhLl0xJlHLNh5QfVOz03EAAD2MQggAAKAXbC+p1NylW3XxyHjdN3Wo03GAbsnOStHRmkZ9uL3M6SgAgB5GIQQAANDDahua9eCCXEWGuvTkLekKCGDfIHinqcPjFBcRwrIxAPBBFEIAAAA9bO6yLdpVVq3/vS1D8ZEhTscBui0oMEA3ZiRrxfZSHa1pcDoOAKAHUQgBAAD0oKX5xVq4br++c8kwXTQizuk4wDnLzkxRY7OlpRsPOB0FANCDKIQAAAB6yL7yGv148SZlDYzR9y8f6XQcoEeMTY7SqIRILclh2RgA+BIKIQAAgB7Q2Nyi7y7KlYz0u5mZcgXyNgu+wRij7KwU5ew7qj2HjjkdBwDQQ3inAgAA0AOeWL5D+fuP6tc3p2lAbJjTcYAedWNGsoyRFucWOR0FANBDKIQAAADO0Uc7y/T7j3brjskDdc34JKfjAD0uKbqPLhwWp7dzi2RZltNxAAA9gEIIAADgHJRW1unhN/I0KiFS/3XdGKfjAL0mOzNF+w7XaMPeI05HAQD0AAohAACAbmppsfTwm/k61tCk527PVKgr0OlIQK+5alyi+rgC9VYOy8YAwBdQCAEAAHTTi6t2aXXBIf339WM1IiHS6ThArwoPCdJV4xL1943FqmtsdjoOAOAcUQgBAAB0w4a9R/Tk8p26Li1Jt00a4HQcwC2yM1NUWdekD7eXOh0FAHCOKIQAAAC6qKKmUQ8tzFVyTKh+OWO8jDFORwLc4sLhceofGcKyMQDwARRCAAAAXWBZlh5ZvFEHK+v07KwsRYW6nI4EuE1ggNFNmSlauaNUh481OB0HAHAOKIQAAAC6YMG6fXp3c4l+eOUoZQyIcToO4HbZmSlqarG0bGOx01EAAOeAQggAAKCTtpdUau7Srbp4ZLzumzrU6TiAI85LitLoxEiWjQGAl6MQAgAA6ISahiY9uCBXUX1ceurWdAUEsG8Q/NfNWanK339Uu8qqnY4CAOgmCiEAAIBOmLt0q3aVVevpWzMUFxHidBzAUTdmJCvASG/nMksIALwVhRAAAMBZLM0v1qL1+/WdS4bpohFxTscBHNc/KlQXDo/T4pwitbRYTscBAHQDhRAAAMAZ7Cuv0Y8Xb1LWwBh9//KRTscBPMbNWakqOlqr9XsOOx0FANANFEIAAACn0dDUou8uypUx0u9mZsoVyFsnoM0VYxMUFhyoJSwbAwCvxLsaAACA03hy+Q7l7z+qX9+cpgGxYU7HATxKWHCQrhqXqL9vPKC6xman4wAAuohCCAAAoAMf7SzT71ft1h2TB+rq8UlOxwE80s1Zqaqqb9L72w46HQUA0EUUQgAAACcprazTw2/kaVRCpP7rujFOxwE81pSh/ZQYFaolOSwbAwBvQyEEAABwnJYWS99/M0/HGpr03O2ZCnUFOh0J8FiBAUY3ZiZr5c4yHaqudzoOAKALKIQAAACO88JHu/RJQbl+ccNYjUiIdDoO4PFmZKaqucXS0vxip6MAALqAQggAAKDVhr1H9NR7O3VdWpJunTjA6TiAVxiVGKmxyVGcbQwAvAyFEAAAgKSKmkY9tDBXyTGh+uWM8TLGOB0J8BrZmSnaWFihgtIqp6MAADqJQggAAPg9y7L0yOKNOlhZp2dnZSkq1OV0JMCr3JCRrMAAo8VsLg0AXoNCCAAA+L35a/fp3c0l+tFVo5QxIMbpOIDX6R8Zqqkj4vROXrFaWiyn4wAAOoFCCAAA+LXtJZX6n2VbdfHIeN170VCn4wBeKzszRUVHa7X2i8NORwEAdAKFEAAA8Fs1DU16cEGuovq49NSt6QoIYN8goLuuGJOoiJAgLc4pdDoKAKATKIQAAIDfmrt0q3aVVevpWzMUFxHidBzAq/UJDtTV4xL17uYS1TY0Ox0HAHAWFEIAAMAvLc0v1qL1+3X/tGG6aESc03EAn5CdlaLq+ia9t+2g01EAAGdBIQQAAPzOvvIa/XjxJmUNjNH3LhvpdBzAZ0wZ0k/J0aEsGwMAL0AhBAAA/EpDU4u+uyhXxki/m5kpVyBvh4CeEhBgdFNmij7+/JDKquqdjgMAOAPeAQEAAL/y5PIdyt9/VL++OU0DYsOcjgP4nBlZKWpusfS3/GKnowAAzoBCCAAA+I2VO0r1+1W7deeUgbp6fJLTcQCfNLx/pNJSo1k2BgAejkIIAAD4hdLKOv3gzXyNTozUT68d43QcwKdlZ6ZoS3Gldh6scjoKAOA0KIQAAIDPa2mx9P0383SsoUnPzspUqCvQ6UiAT7s+PVmBAUaLc4qcjgIAOI2zFkLGmFeMMaXGmM3HHfutMWa7MWajMWaJMSbmuNseNcYUGGN2GGOu7K3gAAD0mKqDUv4bSjzwnrTzX1JRjlRRKDWxIaqveOGjXfqkoFy/uGGsRiREOh0H8HlxESGaNjJeb+cWqbnFcjoOAKADQZ24z6uSnpP02nHH3pP0qGVZTcaYX0t6VNJ/GmPGSJopaaykZEnvG2NGWpbV3LOxAQA4B82N0v61UsH79qVkkyRptCTteO7E+4ZGS+H9pYgEKSK+9fO2j/3bP0b0l4JC3P5ScHYb9h7WU+/t1PXpybp14gCn4wB+IzsrRR9sL9Wa3eW6cHic03EAACc5ayFkWdYqY8zgk44tP+7qGklfa/38RkmLLMuql/SFMaZA0vmSPu2RtAAAdNfRfVLBB3YBtPsjqaFKCgiSBkyRvvpzafhX9Wn+Dl0wbphUfVA6VipVl7V+LJWOldnFUXWZVF/R8XOERHdQGiWcVCDF2x9dfdz7+v1URU2jHlqYp+SYUD2WPU7GGKcjAX7jsvMSFBkSpMU5RRRCAOCBjGWdfQpnayG0zLKscR3ctlTSG5ZlvW6MeU7SGsuyXm+97WVJ71qW9dcOvm6OpDmSlJCQMGHRokXn8jo8RnV1tSIiIpyO4TcYb/divN2PMe++gOYGRVdsUezhHMUezlF4jX22m7qQeB2OzdLh2Cwd6Zum5qD20453drwDmhvkaqxQcMNRBTcclavxqIIbjnx5PbihovXYUbmaqjt8jKbAMDUEx6ghOEaNrugvP7cvfdXoar/eEuibM496+/vbsiw9n1ev3NJm/WRyqIbG+Pe+Qfw8cT/GXHplc73WHmjSM9PDFBLUu4Us4+1ejLd7Md7u5UvjPX369A2WZU3s6LbOLBk7LWPMTyQ1SZrf1a+1LGuepHmSNHHiRGvatGnnEsVjrFy5Ur7yWrwB4+1ejLf7MeZdYFnS4d32DKDP35P2rJaaaqXAEGnwhdLw+6Xhlyk0bqSSjVFyBw/RK+PdVG/PLmqbZVRdKh0rVVB1mYKOlSqsunUG0pHtUu2Rjh8jOKJ1ZtFpZhsdv2wtOLxn8/ei3v7+fn3NXn12cLN+fM1o3X3xsF57Hm/BzxP3Y8ylPgPLtWreGtX2G6krM1N69bkYb/divN2L8XYvfxnvbhdCxpjZkq6T9FWrfZpRkaTjF+enth4DAKDn1VdLez5u3wvoyB77eL/h0oS7pOGXSYMulILDzvgwvSooRIpOtS9n09Qg1RyyC6LW4ujkIkmHCqQ9n0i1hzt+DFf4iaXRl4VRB0VScITko0uotpdUau6yrbpkZLzuvWio03EAvzVpcKxSYvpocW6RburlQggA0DXdKoSMMVdJ+pGkSyzLqjnupr9JWmCMeUr2ptIjJK0755QAAEj2LKDSbVLBe3YBtPdTqaXRLkGGXCxd8KBdAsUOcTpp9wQFS1HJ9uVsmhulY4dO3evo+CLp8G5p3xqpplxSB0vEXWEnzTLqqEhqLZBCIr2mPKppaNKDC3IV3celJ29NV0CAd+SGF2uqP/HfXvVBqfao4spqpSODpZhBXvPvp6cFBBjNyErR8x8WqLSyTv2jQp2OBABoddZCyBizUNI0SXHGmEJJP5d9VrEQSe+1bs64xrKsb1uWtcUY86akrbKXkj3AGcYAAOek9qi0e2XrLKAPpKpi+3j/sdKU79gF0MAp/neGr0CXFJVkX86muckuhU63WXZ1qT27qnCdfT+r5dTHCAo9qSzqqEhqXdIWEuXoL79zl27VrrJq/fnuyYqL8LPvC/Sc5ib738fxZWv1wVOLn+pSqe5ohw8xTpK2PG5vOJ84XkpKkxLT7I9xI+1/x34gOzNFz64o0Dt5xbrvYmbsAYCn6MxZxmZ1cPjlM9z/MUmPnUsoAIAfa2mRDuS1nxGscL1kNdu/UA2bbhdAwy6Voll60GmBQVJkgn05m5bm1vKotINZR62/HB/dLxVtsH9Z7qg8Cgw5qTRq2//oxCIpqLHSfr6Antvs+W/5xVq0fr8emD5MF43grEY4SUuLvdyy+mDrpaz982Nl7QVPdenpZ9YFR7YWowlS//OkodOOK0cT2kvTkChtWP6GJiQHSSUbpQMbpc/+aO9tJtn/ThLG2AVR4ngpKV1KGOtV+4B11tD4CKUPiNHi3CIKIQDwIOe0qTQAAD3i2CFp1wp7M+hdK+x9dCQpOVOa+rBdAqVMtIsN9K6AwPZfaM+mpVmqOdzxXkdtv1RXFknFea3l0YmThi+SpE9kzygKjZH6RLd+jDnDx77t10OjT/ie2Fdeox8v3qQJg/rqe5eN7NFhgQezLHuGzvEzdjqaxdP2PdrR5PWgPu0lT+xQe9ZhRMKJZWZb6dOFPcmqokZIE6e1H2hplg59LpVskkry7ZJo29+knD/Zt5sAew+0tllEieOlxHQpvN+5jZEHuDkrRT97Z4u2HajUeUlRTscBAIhCCADghOYmqeiz9s2gi/MkWVJYnDT8q3YBNHS6vfwInisg0P5vFBFvz2w4k5YW+yxqx0q/nJnx+cY1GpEaby8LrDva/vFQQfv1ttkUp9NaJrWERuvoYaP/NaG6IG64XB/8o0tlEjyMZUkN1adZqnVcwdN2rLnh1McIcLUvY4xKlpIzTp3F0/a5uzZYDwiU+o+2L2m3tL/WisL2WUQlm6T9a6XNf23/uqiU40qi1qIoZqBX7Ut0XVqy5i7dqiW5RRRCAOAheCcEAHCPyuL2AmjXSqm+wv5reOr50vSf2EVQUoYUEOB0UvSGgAB7lkN4P3uZjaSiw/EacbZTujbWSXUVJxZGtUdOKZF27d2vuvoyTY6pVfi+DztXJgVHnlQYRXcwK6lvx7OVKJO6p7H2xJKno1k8bcu3GmtO/XoT0L7sMCJBih99YrHT9nl4vP3fzhsKE2OkmAH2ZfS17cdrDh9XErV+/Pxf7cs0Q2Pal5q1lUX9Rnjs92ZseLCmjeqvt3OL9J9XjVYgm70DgOM88/8YAADv11Rvn+GqbTPo0i328chkacwNrbOALrF/aQNOxxVqX86w/9HKHaWavXa97pwyUOffNL79hqb6U2cfnenj4d3t1zsqI44XHNGJ5W2thdLJpZOvbSTc1HDi/jsdzeJpK3nqKzt+jLB+7UXOgMmnzuBpm9kTFtuje055tLBYe3+iodPajzXUSKVbpQP57SXR+j9ITXX27UGhUv8xx21enW5f78Iyt950c1aK3t92UJ8UHNLFI5kBCgBOoxACAPScw1+0F0BfrJIaj9nLNgZdIF3+P3YJ1P887/irPbxCaWWdfvBmvkYnRuqn14458cagkM5vpn2ypnp7ZlJHxVHtETeVSR18dFeZ1NJs7+11yiyeDjZhrj3S8WOERrcXOUnpJ83gOf7zON8ryXpLcJiUOtG+tGlukso/P24mUb60ZYm04VX7dhNgn9EscfyJy87CYt0e/9Lz+isqNEhLcosohADAA1AIAQC6r6FG2vuJvRl0wfvS4V328ZhBUsYsuwAaPFUKiXA2J3xSS4ul77+Zp5qGZj13e6ZCXT04cyQopPOba5+sqaHzs5LqjtpFatv1xmNnfmxXePeKpNAYe6nRsfKzL9WqPmifYaujM8i5wtuLnLgR0uCLTtp8uXXPnvD+9swu9L7AILto73+elH6bfcyypKP77IKoZJNdFu39t7TpL+1fFz3guDOctZZE0am9WtiHBAXq2rRkvZ1bpP97U5PCQ/hVBACcxE9hAEDnWZZ0aGf7XkB7PpGa6+0z9AyZKk3+ll0CxQ5lFhB63Qsf7dInBeX69c3jNbx/pNNx2gUFn2OZdPKeSaffO0lH9kgHOlcmXaIA6aMOSp7AkPYiJ2agPfskvP+pe/OE96fc9RbGSH0H2Zfzrm8/fuzQifsSlWySdvxDkmXf3if2uIIo3f48bkSPLtO7OStFC9ft0z83l+jmCak99rgAgK6jEAIAnFldpfTFR+1LwSr228fjRkmT7rU3gx70FcnVx9mc8Csb9h7WU+/t1PXpybp14gCn4/ScoOD2M7d11RnLpKPat2uHBo2Z2Pr4Ce0ze0KjKXD9RXicNOxS+9Km4Zh0cMuJ+xKt/X37mduC+thnEfxyX6I0e1+ibv7MnzCorwbGhmlJbhGFEAA4jEIIAHAiy7L/atxWAO1fI7U02WdkGnqJNPUHdgkUM9DppPBTFTWNemhhnlJi+uix7HEylBm2s5RJX1grNWjKNPdmgucLDpcGnG9f2jQ32rNBjz/D2aa3pM9esW83gfa+RMeXRInjO3WSAGOMbspM0bMrPldJRZ0So1laCABOoRACANinN961wi6Adn1g7yEi2W/wv/Jdafjl9i8LbPwKh1mWpUcWb9TByjq99Z2vKCqU70mgxwW67FlBCWMlzbKPWZa9RPH4fYm+WCVtfKP966IHnlQSpUlRyafMQJuRmaJnPvhcb+cV6duXDHPbywIAnIhCCAD8UUuzVJxrzwL6/D2paIMky/7r7rBL7X2Ahl0qRSY6nRQ4wfy1+/Tu5hL9+JrRSh8Q43QcwH8YI8UOsS9jbmw/Xl0mleSfuC/R9r/ry32Jwvodt3l1upSYpsH9hilrYIyW5BTpWxcPZZYfADiEQggA/EXVQXv2T8H79myg2iOSjJQyQZr2iF0CJWf26OahQE/adqBSc5dt1SUj43XvRUOdjgNAspcoDr/MvrSpr2rdl2hje1m05gWppdG+3RWmF8NH6J/l/VX84ValjDq/dV8ilo8BgDtRCAGAr2pulPavbT8jWMkm+3h4f2nk1fY+QMMulcJinc0JdEJNQ5O+uzBX0X1cevLWdAUEMKMA8FghkdLAKfalTVODdGjHlzOJYovyNOPIakWsek9aJSkgyD5Zwcn7EoVGO/YyAMDXUQgBgC85us/eB6jgfWn3R1JDlf0me8AU6as/t/+CmzBOCghwOinQJXOXbtWusmq9fs9kxUWEOB0HQFcFBdsFT+J4SXcoSNJ/vLZOJXt36K2bwhVYutkui3atkPIXtn9dzKDWcii9vSyKTOTMeADQAyiEAMCbNdZJez9pL4EO7bCPRw+Qxt9sF0BDLuYvrPBqf8sv1qL1+/XA9GG6cHic03EA9JCbsgbq21vL9HHwJE376oz2G6oOtp7dLN+e3VqyUdq2tP328PjWcimtvSyKZRkpAHQVhRAAeBPLkg7vbt8Mes9qqalWCgyRBl8oTbjLLoHiRvLXU/iEfeU1+vHiTZowqK++d9lIp+MA6EHTR8crJsylxTlFmjaqf/sNkQlS5OXSiMvbj9VVSgc3t29efWCj9OlzUkuTfXtwhMZGjZPij0gjr5Jcfdz7YgDAC1EIAYCnq6+W9nzcvhfQkT328dhh7QXQoAul4DBHYwI9raGpRd9dmKMAI/1uZoZcgSx1BHxJSFCgrktL0l83FKq6vkkRIWf41SQ0Shr0FfvSpqleKttul0PFOYrauET6y2wpOEIafa00/hZp6DQp0NXLrwQAvBOFEAB4oqZ66bNXlJ63QFq1zT4ziyvcXv51wYP2htBMj4ePe3L5DuUXVujFO7OU2pfCE/BF2Zmpen3NPr276YBumTiga18cFGKfyj4pXcr6uj4Nv07TBgVJm/8qbX1H2viG1CdWGnuTNO5r0sAL2EMPAI5DIQQAnqZkk7R4jlS6Va7wQdKU79izgAZOsd/8An5g5Y5S/X7Vbt05ZaCuGpfkdBwAvSRrYIwG9wvT4pyirhdCJzOB0tBL7Ms1T9j7623+q5S/SPrsFSkqRRo3wy6HktJZWg3A71EIAYCnaGmWPvmd9OEv7VPB3/4XfVYcrGnTpjmdDHCr0so6/eDNfI1OjNRPrx3jdBwAvcgYo+zMVP3vBztVfLRWyTE9tPdPUIg0+hr7Ul8t7fyntOkv0poXpX8/K/UbbhdD478mxY3omecEAC/DnEkA8ATlu6Q/Xi198At734P710gjr3A6FeB2LS2Wvv9mnmoamvXc7ZkKdQU6HQlAL8vOTJFlSW/nFfXOE4RE2MXP7W9I/7FTuv53UmSS9NGvpecmSr+/WPrkGamisHeeHwA8FIUQADjJsuxp7C9OtTfGnPEH6ZZX7RlCgB964aNd+qSgXL+4YayG9490Og4ANxjYL0wTB/XV4pwiWZbVu08WFitNmC3NXiY9vFW68pf2UrP3/kt6eqz0ytXS+pelY+W9mwMAPACFEAA4papEmn+LtOz70oBJ0nc+ldJuYU8D+K0New/rqfd26vr0ZN0yMdXpOADcaEZWqgpKq7W5qNJ9TxqVLF3wgDTnQ+m7OdL0n0o15dLfH5aeHCm9/jV7/6H6KvdlAgA3ohACACdsXiz9vynSntX2xpd3LpGiU5xOBTimoqZRDy3MU0pMHz2WPU6GYhTwK9eOT1JwYIAW5zq0bKvfMOmSH0oPrJW+vdo+o2fZDmnJt6TfDpfe/Ia0banUWOdMPgDoBWwqDQDuVHtE+v/s3Xdc1fXix/HXl71BQEBBwT3ADYpajtRSG45smHuk2R42bta9t/G7t257Wbk1Sy1n2c4yLSdu3OTCvUVE9vf3x5dyVg4433Pg/Xw8zgMOfIE3nwg57/MZXw63Tj2JbgLdPtRmllLmmabJkzPWciAjmxnDWhDk42l3JBFxsGA/T9rVieDz1Xt5unMdPN1tet7aMCCqnnVr9y/YvdzajHr9LOsoe+8gqHMzJNwKVVqDux5OiYjr0m8wERFHSZsHc+6HUweh7Qi45lH9ISkCfLx0F9+s38+IznVoUCnE7jgiYpPujWP4OnU/C7ce4rrakXbHATc3qNzMunV8Cbb/DKkzrJlCqz8G//IQ3806raxSUy35FhGXo0ciIiIlLfcUfP8vWD4awmtBz0+gYiO7U4k4hY37Mnh+7gZa1yzPoGuq2B1HRGzUumZ5yvl5MnPlHucohM7m7gHV21m3G1+Hrd9Zs31XToJloyC4MtS71SqHIuNVDomIS1AhJCJSktKXW/sPHP0Nku+Dd1gkSAAAIABJREFUds+Cp6/dqUScQk6+yQNTVhHs68lrtzfAzU0PoETKMi8PN25uUJGpy9PJyM5z3uWjnj5Q9xbrlp0Bm7+CddOto+t/eQPK17aKoXq3QmhVu9OKiPwpbSotIlIS8nPhxxdh3PVQkAv9voCO/1EZJHKWjzfl8tuhTN68oyHhAd52xxERJ9C9cQy5+YV8vW6f3VEujU8QNLgTek+H4VvgxtfANxR+ehHebgSj2sLikZDhIt+PiJQpKoRERIrbwU0wtj0seAUa9IRhv0KVVnanEnEqs1ftYcHufO5rU52W1cPtjiMiTqJBTDBVw/2ZuXKP3VEun384JA2GgV/Dw6nQ4XkozIdv/wGv14EJN8GKCZB11O6kIiKACiERkeJTWAiL34MPW8GJ3XDHZOg6EnyC7U4m4lS+33CA4Z+toWY5Nx5ur1P2ROQMwzDo1iiapduPkn40y+44Vy6kErR8CO5ZCPenQOsn4eQ++OIheLUmfHKntcws95TdSUWkDFMhJCJSHI7vgok3w7dPQ7Xr4N4l1rG0InKOHzcd4N6PVxBfMYiHG/vgYdfR0iLitLo2igZgzmoXnCV0MeE1oO0/rGJoyHxoNhT2rYEZg+CV6jB9IGz6ylpuLiLiQNpUWkTkapgmrP4Evn7Sut/lPWjYS6eLiFzET5sPcs9HK6kdFcSkQc1YtfRXuyOJiBOqFOpH0yqhzFy1h/vaVscoLf+mGoZ1ymjFRtDhBdi12DqpbP1s6zh7nxBro+qEHhB3Dbi5251YREo5FUIiIlcq85A19XvzlxDbErq+D+Vi7U4l4pQWbDnE0I9WUCMygI8GNSXY10lPDxIRp9C9UTRPzVzHmt0naFgpxO44xc/NDeJaWrdO/4PffrLKodSZ1lH2AVGQ0N0qh6Ib64kmESkRKoRERK7Epi/h8wchJwOuf9E6Ut5NS19ELuaXrYe5e1IK1coHMHlQM0L8vOyOJCJOrnP9Cvzz8/XMWrm7dBZCZ3P3hJrXW7fcLNjyjTVjaPkYWDISylWBhFuhXg+IqGN3WhEpRVQIiYhcjuwM+OYpWP0xRNWDbl9AZF27U4k4rUVphxk8aTlVwv35eHAzyvmrDBKRvxfk40mHupF8sXYfI26si5dHGXnSxcuvaGZQdzh9HDbNtTaf/uV1WPgqRCZY5VDCrZqVLCJXrYz8ZhURKQbbF8L7LWHNFLh2OAz+UWWQyF9Ysu0IgyamUDnUj48HNyNUZZCIXIbujaI5eiqXn7ccsjuKPXxDoFFv6DsbHt1kLS3z9IN5z8Fb9WFMB1j6IWQetDupiLgoFUIiIn8nLxu+eRom3gTuHjDwO2j3LHjowa3In1m2/SgDJywnupwvHw9OJizA2+5IIuJiWtUsT5i/F7NW7bY7iv0CI63TyQZ/Dw+thXb/so6s//oJeK0WTOoKqyZbs4pERC6RloyJiPyVvath1lA4tAmSBkOH58HL3+5UIk4tZcdRBoxfRlSwD5/c3YzygSqDROTyebq7cXODinyybBcnsvII9tNm9IC1VOzaR63bwY3WkrLU6TDnPpj7CNS43tpvqGZH8PS1O62IODHNEBIRuZiCfPj5FRjTDrJPQO8ZcONrKoNE/sbKXcfoP345EUE+TLk7mYhAH7sjiYgL6944mtz8Qr5ct8/uKM4poo41a/nB1TB4HiQOgt3L4bP+8Ep1mDkEtnwHBXl2JxURJ6QZQiIi5zucZs0K2pNibdrY+VXwC7U7lYjTW51+nH5jlxEW4MWUu5OJDFIZJCJXp150MNUjApi1ajd3NatsdxznZRgQk2jdbvg/2PGLNWtowxxYOw18QyG+q3WMfeXmOhlVRAAVQiIiZ5imdcTrd8+ChzfcOtaaci0if2vt7uP0GbuUcv5WGRQVrDJIRK6eYRh0axTNK99uZteRLCqH+dkdyfm5uUPV1tat86uQNs8qh9ZMhZRxEBQN8d2g3m1QoYFVJolImaRqWEQEIGMvfNQNvhoOsS3g3iUqg0QuUeqeE/Qes5RgX0+mDEmmYoj2rBCR4tO1UTQAs1btsTmJC/Lwhtqdocc4GL7VerIrqp51Otmo1vBuIvz0Xzi81e6kImIDzRASkbLNNCF1Bnz5qLW+/sbXIXGgni0TuUQb9mbQe+xSAn08mXJ3MtEqg0SkmEWH+NK8ahizVu3mwXbVMfRv9JXxDrCe7KrXA7KOwsbPrQ2pf34Zfn4Joupbs4YSukNwjN1pRcQBNENIRMqurKMwfQDMGAThNeGeXyBpkMogkUu0cV8GvcYswc/TnSl3J1MpVEs5RKRkdGsczY4jWaxK17HqxcIvFJr0h/5z4dENcMN/wM0Dvn8W3oiHcZ2sZfSnjtidVERKkAohESmbtn4PI5vDxrnQ7p8w4BsIq2Z3KhGXsXn/SXqNWYq3hztThiRrXw8RKVGdEqLw9nBj5srddkcpfYIqQvP7YMhP8MBKaPsMZB2BLx+DV2vA5B7W/kM5J+1OKiLFTEvGRKRsycmE756BFeOhfB3o9RlUqG93KhGXsvXASXqNWYKHm8GUIcnEhvnbHUlESrlAH09uiI9i7tp9/POmeLw89Lx2iQirBq0fh1bD4UCqtaQsdaZ1+qqHD9S8wVpWVr2D3UlFpBioEBKRsmPXUusPmmM7oMUD1jNgnjoJSeRypB3MpOfopRiGVQZVCVcZJCKO0a1xNJ+v2ctPmw9yQ3yU3XFKN8OwNp+Oqgft/gW7l8O6z2D9LOsoe+8gaoS1gAZxUC7O7rQicoVUrYtI6ZefCz/8G8Z3BLMA+n8J17+oMkjkMm07lMldo5cAMOXuZlQrH2BzIhEpS66tHk54gLeWjTmamxtUbgY3vgqPbYbeM6H2jVTY9wO83Rhm3wuH0+xOKSJXQDOERKR0O7AeZg6FA+ugUR9r00SfILtTibicHYdP0XP0EgoKTaYOSaZ6RKDdkUSkjPFwd6NLw4pMWryD41m5hPh52R2p7HH3gOrtoHo7lvq2p7m5HFZMgDVTIL67tdQsoo7dKUXkEv3tDCHDMMYZhnHQMIzUs94WahjG94ZhbC16Wa7o7YZhGG8bhpFmGMZawzAal2R4EZE/VVgAv74Fo9pA5n64cwp0eVdlkMgV2HnEKoPyCkw+uTuZGpEqg0TEHt0aRZNXYDJ37T67o5R5OT7h0OlleHgdNL8fNn8NI5NhWm/Yt8bueCJyCS5lydgEoON5b3sKmGeaZg1gXtF9gE5AjaLbEOD94okpInIZju2ACTfB9/+EGtfDvUugdme7U4m4pPSjWfQctYTTeQVMHtSMWlEqg0TEPvEVg6gZGaBlY84kIAKuf8Eqhq4dDtt+hg9bwSd3wO4VdqcTkb/wt4WQaZoLgKPnvbkLMLHo9YlA17PePsm0LAFCDMOoUFxhRUT+kmnCionwfkvrZIyuH8Adk8E/3O5kIi5p97Es7hy1hFO5BXw8uBl1K2qGnYjYyzAMujeOYeWu4+w4fMruOHI2/zBo96xVDLUdAelLYcx1MKkr7FxkdzoRuYgr3VQ60jTN3+dp7gcii16PBtLPum530dtERErWyQMw5U744kGo2AiGLYKGPa1TMkTksu05fpqeo5dwMjuPjwc3I75isN2RREQA6NKwIoYBs1btsTuKXIxvCLR+wiqG2j8H+9fB+E4w/kbYNt96Ak9EnIJhXsL/kIZhxAFzTdNMKLp/3DTNkLPef8w0zXKGYcwFXjJN85eit88DnjRNM+Uin3MI1rIyIiMjm0ydOrUYvh37ZWZmEhCgU1ccRePtWM463uGHFlFr80jcCnPYVrUve6JvBKN0HKLorGNeWmm8LUezC/nv0mwy80weT/KharB7iXwdjbdjabwdT2Necv63/DSHskz+18oXo+jJH423Y13qeLsV5FBx77dUSp+Jd+4xTgTVYmfs7RwNbaIn7i6Dfr4dqzSNd9u2bVeYppl4sfdd6SljBwzDqGCa5r6iJWEHi96+B6h01nUxRW+7gGmao4BRAImJiWabNm2uMIpzmT9/PqXle3EFGm/HcrrxPn0cvn4S1k+FCg2h+yhqlK9FDbtzFSOnG/NSTuMNBzKyuePDxWQXuvPJkKY0qlyuxL6WxtuxNN6OpzEvOUcCd/PYZ2sIrNKAxLhQQOPtaJc33jdA3n9g9WSCf3mT+utesP52a/U41OpsHW0vf0k/345VVsb7Sv/P+xzoV/R6P2DOWW/vW3TaWDJw4qylZSIixWfbfGuvoHWfQesnYfAPUL6W3alEXNrBjGx6jlrCoZM5TBhYsmWQiMjV6JgQha+nOzO1bMx1ePpA0mB4YCXc8g5kn4BpveCDayB1hnVCrIg41KUcOz8FWAzUMgxjt2EYg4CXgA6GYWwF2hfdB/gK2AakAaOBe0sktYiUXXmnrVlBk7pYf1gM+h7aPg3unnYnE3FpB09m03P0EvZnZDNhYFOaxKoMEhHn5e/twQ3xkcxds5fsPBUJLsXDCxr3hftToNsoKMyD6QPhvWawegoU5NudUKTM+NslY6Zp9vyTd7W7yLUmcN/VhhIRuag9K2DWPXB4CzQdCu3/DV5+dqcScXmHM3PoNXope49nM2FAEklFyy9ERJxZ98YxzF69l582HaRTPR1s7HLcPaDBHVCvB2z8HBa8CrPvgZ9fgmsehQY9rfJIREqMFmuKiPMryIOf/gtjOkDuKegzGzr/T2WQSDE4UlQGpR/LYlz/JJpVDbM7kojIJWlZPZyIQG8tG3N1bu4Q3w2GLoQ7PwGfEOvU2LcbwbLRkJdtd0KRUkuFkIg4t0NbYGwH69miej2s4+SrtbU7lUipcPRULr3GLGXHkVOM7ZdE82oqg0TEdbi7GXRpWJGfNh3k6Klcu+PI1XJzg9o3wpD50GsGBEfDV8PhrQaw+D3rSUERKVYqhETEORUWwpL34cNr4dhOuG0idB8FviF2JxMpFY5n5dJ7zFK2HT7FmH6JtKwebnckEZHL1r1xDPmFJnPX7rU7ihQXw4Aa7WHgt9D3cwivAd8+DW/Wh4WvQ85JuxOKlBoqhETE+ZzYDR91hW+egiqt4N7FEN/V7lQipcaJrDx6j11K2sFMRvdN5Noa5e2OJCJyRepUCKJ2VCAzV2rZWKljGFC1NfSfCwO+gQoNYN5z8EYCzH8ZTh+zO6GIy1MhJCLOwzRhzVQY2QJ2p8DNb8Fdn0JglN3JREqNE6fz6DNuKVv2Z/Jhnya0rqkySERcW/fG0axOP86+zEK7o0hJiW0OfWbC4B8htgXM/481Y2je83DqiN3pRFyWCiERcQ6njsCnfWDWUIioA8N+hSb9rWeHRKRYZGTn0XfcMjbuy+D93o1pWzvC7kgiIletS8No3AyY81su1qHHUmrFNIGeU6wNqKu1tZaQvZkA346AkwfsTificlQIiYj9Nn8DI5Otl+3/DQO+gtAqdqcSKVUyc/LpP24Z6/ec4L27GtOuTqTdkUREikVkkA8Pt6/Jkn0FvPbdFrvjiCNUqA+3T4J7l0Dtm2DJSHirPnz1BJzQ8kGRS6VCSETsk3MSPn8AptwBARHWqRLXPGIdPyoixeb3MmjN7hO8e1cjro/XMkwRKV0euK46rWM8ePenND5astPuOOIoEbXh1tFwf4p1Gm3KWOtUsi8egmM77E4n4vQ87A4gImXUzkUw6x44vgtaPgxtnwYPb7tTiZQ6p3LyGTh+OavSj/NOz0Z0TKhgdyQRkWJnGAZ963rhGRjKP+ekUj7Am44JKr/LjLBq0OU9aPUE/PomrJoMKz+CBnfCNY9CeHW7E4o4Jc0QEhHHys+B756F8Z2t/YEGfA0dnlMZJFICsnLzGThhOSk7j/LmHQ3pXE9lkIiUXu5uBu/0bEyDmBAemrqKlB1H7Y4kjlYuFm56Ax5cDU2HQOoMeC8Jpg+CgxvtTifidFQIiYjj7FsLo9rAorehST+451fr1AgRKXancwsYPDGF5TuO8sYdDbm5QUW7I4mIlDhfL3fG9U8iOsSXQRNTSDt40u5IYofgaOj0Ejy8DprfD5u/tvarnNYb9q2xO52I01AhJCIlr7AAFr4Go6+DrCNw12fWkfLeAXYnEymVsvMKuHtSCou3HeG12xvQpWG03ZFERBwm1N+LiQOb4unuRr9xyzmQkW13JLFLQARc/4JVDLV6HLb9DB+2gk/ugN0r7E4nYjsVQiJSso78BuM7wbznoXZnGLYYal5vdyqRUis7r4AhH63g198O80qPBnRrFGN3JBERh6sU6seEAUkcz8ql37hlZGTn2R1J7OQfBtc9YxVDbUdA+lIYcx1M6mrtaylSRqkQEpGSYZqwfCx8cA0c2gTdx8BtE61/kEWkROTkFzBs8goWbDnEy93r06OJyiARKbsSooP5oE8T0g5mMnTSCnLyC+yOJHbzDYHWT1jFUPvn4ECq9cTl+Bth23zr71eRMkSFkIgUv4x98HEP+PJRqNTUmhVU/zZrE2kRKRE5+QXcO3klP20+xH+71+P2pEp2RxIRsd21Ncrzvx71WbztCMM/W0thoR7wC+AdCNc8DA+thRv+C0fSYFIXGNsBtnynYkjKDB07LyLFK3WmVQTlZUOnVyBpMLipexYpSbn5hdz/ySrmbTrIi10T6Nm0st2RREScRvfGMRzIyOHlbzYRFeTNiBvr2h1JnIWXHzS/FxIHwurJ8Mub8MltUKGBtedQrRv1d6yUaiqERKR4nD4GXw6H1OkQ3QS6fQjhNexOJVLq5RUU8sCUlXy/4QDPd4mnd3Ks3ZFERJzOPa2rciAjm9ELtxMZ5MPga6vaHUmciaeP9SRmo76wdpp1GMq03hBRF1oNh7pdwc3d7pQixU51p4hcvbR5MLIFbJhtbdQ38DuVQSIOkFdQyENTV/Ht+gP86+a69G0eZ3ckERGnZBgGz95Ul871onjxy418vmav3ZHEGXl4QeM+cH8KdBsFhfkwfSC81wxWT4GCfLsTihQrFUIicuVyT1mzgiZ3t9ZiD/re2qjPXZMPRUpafkEhj0xbzVfr9vPMjXUY0LKK3ZFERJyau5vB67c3pGlcKMM/XcOi3w7bHUmclbsHNLgD7l0Ct00AD2+YfQ+82wRWTIT8XLsTihQLFUIicmXSl8MH18Ly0ZB8Lwz9GaIb251KpEwoKDR57LM1zF27j6c719bSBxGRS+Tj6c7ovonEhvkxdNIKNu7LsDuSODM3d4jvBkMXwp1TwLccfPEgvN0Ilo229swUcWEqhETk8uTnwo8vwrjroSAX+n0BHf8Lnr52JxMpEwoKTYZ/toY5q/fyRMdaDGlVze5IIiIuJdjPk4kDm+Lv7UH/8cvYc/y03ZHE2bm5Qe3OcPdP0GsGBEfDV8Phrfqw6F1r1ryIC1IhJCKXzO/ULhjbHha8AvXvhGG/QpVWdscSKTMKC02emL6WWav2MPz6mtzbprrdkUREXFLFEF8mDEwiK7eAfuOWcTxLS4DkEhgG1GgPA7+1nhQNrwnfjYA368PC1yFbM87EtWijDxE5V2EBnNwHR7fDsR1n3baTuHcN+AbDHZOhzs02BxUpWwoLTZ6auZYZK3fzSPua3H+dNm4XEbkataOCGNUnkX7jljF4YgqTBzfDx1MnScklMAzrSdEqrWDXEuvJ0nnPwa9vQfIwaDbUWl4m4uRUCImURTmZcHznRUsfju+yloL9znCH4BgoF8feip2I6fk6BETYFFykbCosNBkxex2fpuzmweuq81B7lUEiIsWhebUwXr+jAQ9MWcVDU1cxslcT3N0Mu2OJK6mcDL1nwJ4VsOBVmP9fWPweNL0bku8D/zC7E4r8KRVCIqVRYSFk7r944XNsB5w6dO713kFQLg4i46H2jdbr5eKgXBWrDHL3BCBt/nxiVAaJOJRpmjw7J5Upy9K5r201HulQ0+5IIiKlyk31K3IwI4fn527g35+v5/ku8RiGSiG5TNFNoOcU2L/OKoYWvg5L3ofEgdDiQQiMtDuhyAVUCIm4qtysP5/lc2wnFOScudZwg6AYCI2DWp3OLXzKxVlTWvWHj4jTMU2Tf32+no+X7uKe1tUYfn0tPUgRESkBA6+pwoGMbD5csI0KIT7ao02uXFQ9uH0iHNwEC1+DJSNh+Rho3A9aPmg92SriJFQIiTgr04TMA1bJc07pU/R65oFzr/cKsAqe8rWg5g3nzfKpBB5ejv4OROQqmKbJc19sYNLindx9bRWe7KgySESkJD3ZsTYHMrL53zebiQz04dYmeuAuVyGiNtw6Gto8Bb+8DiljIWUcNOoF1zxi/Z0uYjMVQiJ2yjtt7dlz0dJnJ+SffQyqAUHR1j8eNTqcO8OnXBXwC9UsH5FSwjRNXvxyIxMW7WBgyyo83bmOyiARkRLm5mbwvx4NOJSZw5Mz1hIe6E3rmuXtjiWuLqwadHkPWj0Bv74JqybDyo+gwZ1wzaMQrtloYh8VQiIlyTSt/XouKHx2WKXPyX3nXu/pbxU8odWgevtzZ/mEVAIPbwd/AyLiaKZp8t+vNzH2l+30bxHHszepDBIRcRQvDzc+6N2E2z9cwrDJK5g2pDn1YoLtjiWlQblYuOkNaPU4/Po2rBgPa6ZAfHdoNRwi6tidUAryIDcTck/hdyrd2qLDy8/uVCVKhZDI1crP+ZNZPkW3vFPnXh9Y0Sp5qraF0Crnlj7+4ZrlI1KGmabJ/77dzKgF2+iTHMu/bq6rMkhExMECfTyZOCCJbiMXMWDCMmYOa0nlsNL9oFAcKKgidHoJrn0UFr8Ly8ZA6nSoc7NVFlVoYHdC52ea1mOw3FN/FDgXf/2v3nfqwvtnnbTcFKB+baiUZNu36QgqhET+jmlC1pEzBc/5S7sy9gLmmes9fM+UPFVbn1X4xEFILHj6OPo7EBEXYJomr323hffn/8ZdzSrz3C065UZExC4RQT5MHNiUHh8sou+4pcwY1oKwAM3UlmIUEAEdnoeWD1sbTy/9EDZ+ATU7WsVQTKLdCYuHaUJe1t+XMjkn/76wOfu+WXDpGbwCwMv/rFuAdahOcMzF3+flz/q0ncSHVi25cXESKoREAPJz4US6VfCcU/jstF7mnjz3+oAoq+CJu/bCWT4BEZrlIyKX7c0ftvLuT2ncmVSJF7sk4Oam3yMiInaqHhHA2H6J3DV6KQMnpjDl7mb4eenhkxQzv1C47hlofj8sGw1L3oMx7azVBK2fgNgWjstSWPAXRcyVzr45xTlPnv8Vw62okAk4t6AJiLygsPnr14vuewdYT9a7uV32UBzKmA/+YZf9ca5Gv9GkbDBNOH3szAld5y/tytgDZuGZ6929z5Q8cS0vnOVTyteSiohjvT1vK2/N28ptTWL4T7d6KoNERJxEk9hQ3unZiHsmr+D+T1Yxqk8TPNwv/8GlyN/yDYHWj0PyPbB8rLWcbHwniG1pzRg6v1M5a7+bv59Vkwk5mX9/3TkH2vwNN4+LlDf+1unGf1XS/NXrHj56Yt3BVAhJ6VGQVzTLZ8fFS5+cjHOv94+wCp7Kzc+b5RNnzQC6giZZRORyvfdTGq9/v4XujaN56db6KoNERJzM9fFRvNA1gRGzUhkxK5WXbq2nJb1ScrwD4ZqHoekQWDkRfn0LPupKsncErPa+6H43f8vD5+JFTEDEeW+/jNk3Hl4lNwbiMCqExLVknygqeqyyp+bmRbDzdavwObH73LWk7l7WbJ5ycVCp2bmlT0isNYVQRMRG78//jVe+3Uy3RtG80qMB7iqDREScUq9msRw4kc3bP6YRFezDIx1q2h1JSjsvP0geBk0GwOrJZCybiU/F2AtLGu+Avy5wPP3BXQ/75eL0kyHOpbAQTu49a4bP9nNfP33snMvDPYMgoibEJEG9284tfQIrapaPiDit0Qu28fI3m7ilQUVevU1lkIiIs3ukQ032ncjmrXlbiQzy4a5mle2OJGWBpw8kDWbDqepEtGljdxopZVQIiePlnT6zWfMfmzhvP7OJc0HOmWsNdwipZBU8dbueVfhYLxctWUkb/WIUERczZuE2/u+rjdxYvwKv364ySETEFRiGwX+61+NQZg7PzF5HRKA37etG2h1LROSKqRCS4meakHX0wtk9v+/pc3Lvudd7BVgFT/laUPMG6/Xfi5/gSuDuacM3ISJSMib8up0Xv9xIp4Qo3ryjoTYnFRFxIZ7ubozs1Zieo5Zw/5SVfHJ3Mo0rl7M7lojIFVEhJFemIB8ydl98WdexnRdu4BwQZZU8VdtYRU9olT9m+eAfrt3kRaRM+GjxDv79xQZuiI/k7Z6N8FQZJCLicvy8PBjbP4ke7y9i0ITlTB/WgmrltTeliLgeFULy53Iyz1vWddbrJ9KhMP/MtW6eUC7WKnkqNz+zrCu0io5pFxEBPl66k2fnrKd9nUje6dlYZZCIiAsLD/Bm4sCmdB+5iH7jljFzWAsignzsjiUicllUCJVlpgmZBy4se35//dShc6/3CbGKnooNIb7bufv5BFUEN3fHfw8iIi5g6rJdjJiVynW1I3ivVyO8PFQGiYi4utgwf8YPSOLOUUvoP34504YmE+ijrQ5ExHWoECrt8nPh+K6LLOvaYd3yss662IDgGKvkqdnx3GVdoVXAV+ujRUQu16cp6fxj1jra1CrP+70b4+2h8lxEpLSoHxPCyF6NGTQxhWGTVzKuf5JKfxFxGSqESoPTxy++rOvYTmufH7PwzLUevmcKnqptztrAuYp1mpeHtz3fg4hIKTR9xW6enLGWa6qH80HvJiqDRERKoTa1Inipez0en76WJ2es5bXbGuCm0yNFxAWoEHIFhYXWyVznn9b1++vZx8+93i/cKnkqJ5+7rCu0CgREagNnEREHmLVqN49PX0PLauGM7puIj6fKIBGR0uq2xEocyMjm1e+2EBnkw1OdatsdSUTkb6kQchZ5p88s4zr/5K7jO6Eg98y1hjuEVLaKnoTu5y7rKhcH3oF2fAciIlJkzuo9PPbpGpKrhKkMEhGvErr4AAAgAElEQVQpI+5rW539Gdl88PNvRAV5079lFbsjiYj8JRVCjmKakHXkIsu6iu6f3Hfu9V6BEBoHEbWhVqdzZ/oEVwJ3/acTEXFGc9fu5ZFpq0mKC2Vs/0R8vVQGiYiUBYZh8NwtCRzMyOG5uRuICPKhc70KdscSEflTahWKU0E+Pqf3w28/njvT5+gO637uyXOvD6xgFTxV257Zx+f34scvTEu7RERczFfr9vHQ1NUkxoYyrn8Sfl76Z1ZEpCxxdzN4u2cjeo1ZysPTVhPm70WzqmF2xxIRuSj9pVqcRjYj+UgaLC267+4FIbFWyRPb4qxlXVWsJV9efnamFRGRYvRN6n4enLKKhpVCGDcgCX9v/RMrIlIW+Xi6M7ZfIre+v4jBk1KYfk8LakVpSwcRcT76a7U4tXyYTZs3UTu56Mj2wArgpqUCIiKl3fcbDnD/JyupFxPMhAFJBKgMEhEp00L8vJg4sCndRy6i//hlzLy3BRWCfe2OJSJyDje7A5Qqjfuwv0IHqHItBMeoDBIRKQPmbTzAvR+vID46mIkDmxLo42l3JBERcQIx5fyYMKApmdn59B+3nBOn8+yOJCJyDhVCIiIiV+inzQcZNnkltaOCmDSwKUEqg0RE5Cx1KwbxYZ8mbDucyZBJKWTnFdgdSUTkD1dVCBmG8YhhGOsNw0g1DGOKYRg+hmFUMQxjqWEYaYZhTDMMw6u4woqIiDiLn7ccYuhHK6gRGcBHg5oS7KsySERELtSiejiv3taApduP8tinaygsNO2OJCICXEUhZBhGNPAgkGiaZgLgDtwJvAy8YZpmdeAYMKg4goqIiDiLX7YeZsikFKqVD2DyoGaE+Om5DxER+XNdGkYzonMdvly3j+fnbsA0VQqJiP2udsmYB+BrGIYH4AfsA64Dphe9fyLQ9Sq/hoiIiNNYlHaYQROXUyXcn48HN6Ocv8ogERH5e3e3qsqga6owYdEORi3YZnccEZErP2XMNM09hmG8CuwCTgPfASuA46Zp5hddthuIvuqUIiIiTmDJtiMMnLic2DA/Ph7cjFCVQSIichlGdK7DgYxs/vv1JiKDfOjaSA+VRMQ+xpVOVzQMoxwwA7gDOA58hjUz6N9Fy8UwDKMS8HXRkrLzP34IMAQgMjKyydSpU68oh7PJzMwkICDA7hhlhsbbsTTejqcxd6y/Gu/NRwt4bUU24T4GTzb1JdjbcHC60kc/346l8XY8jbljucp45xWavJaSzdZjhTzaxIf4cNc8mdhVxru00Hg7Vmka77Zt264wTTPxYu+74hlCQHtgu2mahwAMw5gJtARCDMPwKJolFAPsudgHm6Y5ChgFkJiYaLZp0+YqojiP+fPnU1q+F1eg8XYsjbfjacwd68/GO2XHUd76cRmVQv2ZMiSZiEAfx4crhfTz7Vgab8fTmDuWK413sxZ53P7BYt5fd5ppQxOJrxhsd6TL5krjXRpovB2rrIz31ewhtAtINgzDzzAMA2gHbAB+AnoUXdMPmHN1EUVEROyzctcx+o9fTlSQD1PuVhkkIiJXL8jHkwkDmhLk40H/8ctJP5pldyQRKYOuuBAyTXMp1hKxlcC6os81CngSeNQwjDQgDBhbDDlFREQcbnX6cfqNXUZ4gBef3J1MRJDKIBERKR5RwT5MHNiUnLwC+o1fxrFTuXZHEpEy5qpOGTNN81+madY2TTPBNM0+pmnmmKa5zTTNpqZpVjdN8zbTNHOKK6yIiIijrN19nD5jl1LO34spQ5KJClYZJCIixatGZCBj+yex+9hpBk1czuncArsjiUgZcrXHzouIiJQ6qXtO0HvMUoJ9PZkyJJkKwb52RxIRkVIqKS6Ut+9syKr04zwwZRX5BYV2RxKRMkKFkIiIyFnW7z1BrzFLCfTxZMrdyUSHqAwSEZGS1TGhAs/dEs8PGw/w7Jz1XOlJ0CIil+NqThkTEREpVdJPFvLImKX4e7kzdUgylUL97I4kIiJlRN/mcew/kc3I+b9RMdiHB9rVsDuSiJRyKoRERKRMKiw0yS0otG75hew6msX/lp3G39eHKSqDRETEBo/fUIv9Gdm89v0WIoN8uD2pkt2RRKQUUyEkIiIlpqDQJDffKlx+L1/y8s+UMGffz/vjbWc+Ju+s686+n/dHkWNe9HNecO0fn7eAvALrYwoKL5yOH+JtMGVIMrFh/jaMloiIlHWGYfDyrfU5nJnLP2ato3ygN21rR9gdS0RKKRVCIiIuzDRNq3S5oAwx/yhDci5ajlyskDH/8tq8cz7GJOciZc75X+8inctV8XAz8PJww9PdDS8PN7zOeunpYVgv3d0I9PH4432eZ7309vj9dQMvd/c/PuaPz3U0jSrhKoNERMQ+nu5ujOzVmJ6jlnDvxyuZMiSZhpVC7I4lIqWQCiERESe0ctcx3v0xje37TvPymoVnZracX9QUFFLc+05aZYkbnr8XLecUKWcKlWAvT7zczypozvqYs8uaM+WNcUFBc8F1F7zt3M/v5mYU7zd7nvnzt5Xo5xcREbkUAd4ejOufRPf3f2XghOXMHNaCOD1hISLFTIWQiIgTOXYql5e/2cTU5emUD/QmytsgMsQX7/PLkYsWLlYh4/3HbBn3Pz7mr2fLnD1rxg3DKNnSRURERP5e+UBvJg1sxq3vL6LvuGXMGNaC8oHedscSkVJEhZCIiBMoLDT5bEU6L329iYzsfO6+tgoPta9JyuJfaNMm0e54IiIiYoMq4f6M7ZfIXaOXMnDCcqYOScbfWw/hRKR4uNkdQESkrNuwN4MeHyziyRnrqB4RwJcPXsOIG+sSoD/4REREyrxGlcvxXq9GbNiXwb0frySvoNDuSCJSSqgQEhGxycnsPJ77Yj03vbOQHUeyePW2Bnw6tDm1o4LsjiYiIiJO5Lrakfxf1wR+3nKIp2aswyzuDQRFpEzS088iIg5mmiZfrN3Hi3M3cCgzh7uaVubxG2oR4udldzQRERFxUnc2rcyBjBze+GELFYJ9GH5DLbsjiYiLUyEkIuJAvx3K5J9zUvk17Qj1ooMZ3TeRBjpKVkRERC7Bg+2qsz/jNO/+lEZksA99kmPtjiQiLkyFkIiIA5zOLeC9n9L4cMFv+Hi680KXeO5qFot7CR+jLiIiIqWHYRi80CWBQydz+OecVMoHeNMxIcruWCLiorSHkIhICfthwwE6vPEz7/6Uxs31K/LjY23o0zxOZZCIiIhcNg93N97p2ZgGMSE8NHUVKTuO2h1JRFyUCiERkRKSfjSLwRNTGDwpBV9Pd6YOSeb1OxpSPtDb7mgiIiLiwny93BnXP4noEF8GTUwh7eBJuyOJiAtSISQiUsxy8wt576c0OrzxM7+mHeYfnWrz1UPXklw1zO5oIiIiUkqE+nsxcWBTPN3d6DduOQcysu2OJCIuRoWQiEgxWpR2mE5vLeCVbzfTpmYEPzzWmqGtq+Hprl+3IiIiUrwqhfoxYUASx7Ny6TduGRnZeXZHEhEXokcoIiLF4GBGNg9OWcVdY5aSV2AyfkASH/RpQnSIr93RREREpBRLiA7mgz5NSDuYydBJK8jJL7A7koi4CBVCIiJXIb+gkPG/bue6137mm9T9PNSuBt890oq2tSLsjiYiIiJlxLU1yvPKbfVZvO0Iwz9bS2GhaXckEXEBOnZeROQKrdx1jGdmpbJhXwatapbnuVviqRLub3csERERKYO6NYrhQEYOL329iaggb0bcWNfuSCLi5FQIiYhcpmOncnn5m01MXZ5OVJAPI3s1plNCFIahY+RFRETEPkNbVWX/iWxGL9xOZJAPg6+tanckEXFiKoRERC5RYaHJZyvSeenrTWRk5zOkVVUebFeDAG/9KhURERH7GYbBszfV5eDJbF78ciMRQT7c0qCi3bFExEnpUYyIyCVYv/cEz85OZeWu4yTFleOFrgnUjgqyO5aIiIjIOdzdDF6/vSGHTy5j+KdrCA/wokW1cLtjiYgT0qbSIiJ/4WR2Hs99sZ6b3/mFnUeyePW2Bnw6tLnKIBEREXFaPp7ujO6bSFy4H0MnrWDjvgy7I4mIE1IhJCJyEaZp8vmavbR77WcmLNrBXc0q8+NjbejRJEZ7BYmIiIjTC/bzZMKApvh7e9B//DL2HD9tdyQRcTIqhEREzpN2MJNeY5by4JRVRAb5MPvelrzYtR7Bfp52RxMRERG5ZBVDfJk4sClZuQX0G7eM41m5dkcSESeiQkhEpMjp3AJe+XYTnd5awLo9J3ihawKz72tJg0ohdkcTERERuSK1ogIZ3TeRXUeyGDwxhey8ArsjiYiTUCEkIgL8sOEA7V//mfd++o2bG1Tkx8fa0Cc5Fnc3LQ8TERER15ZcNYw37mjIil3HeGjqKgoKTbsjiTitgxnZTN6QUybKU50yJiJlWvrRLJ77Yj0/bDxIjYgApg5JJrlqmN2xRERERIrVjfUrcPBkXZ77YgP//nw9z3eJ176IImcpLDSZlpLOf77ayOncfFbuOlbqT+hTISQiZVJOfgFjFm7nnR+3YmDwj061GXhNFTzdNXFSRERESqcBLauw/0Q2Hy7YRlSwD/e1rW53JBGn8NuhTP4xcx3Lth8luWooXaNPl/oyCFQIiUgZ9GvaYZ6dk8q2Q6folBDFszfVpWKIr92xRERERErckx1rcyAjm1e+3UxkkA89msTYHUnENrn5hYxa8Btv/5iGj4cbL99aj9sTK/Hzzz/bHc0hVAiJSJlxICObF7/cyBdr9hIb5sf4AUm0rRVhdywRERERh3FzM/hfjwYcyszhqRlrKR/oTeua5e2OJeJwq3Yd46kZ69h84CQ31qvAv26pS0Sgj92xHEqFkIiUevkFhUxavJPXv99CbkEhD7WrwbA21fDxdLc7moiIiIjDeXm48UHvJtzx4RKGTV7BtCHNqRcTbHcsEYfIzMnn1W83M3HxDqKCfBjTN5H2dSPtjmULFUIiUqqt2HmMZ2ansnFfBq1qluf5W+KJC/e3O5aIiIiIrQJ9PJkwIIluIxcxYMIyZg5rSeUwP7tjiZSoeRsP8OzsVPZlZNM3OZbhN9Qi0MfT7li2USEkIqXS0VO5vPz1JqalpBMV5MP7vRrTMSFKp2mIiIiIFIkI8mHSoKbc+v4i+o5byoxhLQgL8LY7lkixO3Qyh+e+WM/ctfuoGRnA9Lta0CS2nN2xbKdCSERKlcJCk09T0nnpm01kZucztFVVHmxXA39v/boTEREROV+18gGM7ZfEXaOXMHBiClPuboafl/5uktLBNE0+S9nN/321kdO5BTzaoSb3tK6Gl4dOFgYVQiJSiqzfe4JnZqeyatdxmsaF8kLXBGpFBdodS0RERMSpNYktxzs9G3HP5BXc/8kqRvVpgoe7HjCLa9t++BRPz1zH4m1HaBoXyn+616N6RIDdsZyKCiERcXkZ2Xm8/t0WJi3eQTk/L167rQHdG0dreZiIiIjIJbo+PooXuiYwYlYqI2al8tKt9fS3lLikvIJCRi/cxls/bMXL3Y3/65ZAz6TKuLnp5/l8KoRExGWZpsnna/by4pcbOZyZQ+9msQy/vhbBfmV3YzgRERGRK9WrWSwHTmTz9o9pRAX78EiHmnZHErksa9KP89TMdWzcl0HH+Cie6xJPZFDZOkr+cqgQEhGXlHYwk3/OSWXRb0eoHxPMmL6JNKgUYncsEREREZf2SIea7M/I5q15W4kM8uGuZpXtjiTyt07l5PPad1uYsGg75QO9+bBPE26Ij7I7ltNTISQiLuV0bgHv/LiV0Qu34evpzgtdE7iraWXcNQVURERE5KoZhsH/davHoZM5PDN7HRGB3rSvG2l3LJE/NX/zQUbMSmXP8dP0Tq7MEx1rE1SGj5K/HCqERMRlfL/hAP/+fD17jp/m1sYx/KNzbcJ1NKqIiIhIsfJ0d+O9Xo3pOWoJ909ZySd3J9O4so7oFudyODOHF+ZuYM7qvVQr789n9zQnKS7U7lguRYWQiDi99KNZPPfFen7YeJCakQFMG5JMs6phdscSERERKbX8vDwY2z+JHu8vYtCE5Uwf1oJq5XVCk9jPNE1mrNzDi19u4FROPg+1q8G9bavh7eFudzSXo0JIRJxWTn4Boxds450f03B3M3i6c20GtKyCp45BFRERESlx4QHeTBzYlFvfX0S/ccuYOawFEdqgV2y088gpRsxK5Ze0wzSJLcdL3etRIzLQ7lguS4WQiDilX7Ye5p9zUtl2+BSd60Xx7E11qRDsa3csERERkTIlNsyfcf2TuHPUEvqPX860ockEan8WcbD8gkLG/LKdN3/YgoebGy90TaBXUx0lf7VUCImIUzmQkc2LX27kizV7iQ3zY8KAJNrUirA7loiIiEiZVT8mhJG9GjNoYgrDJq9kXP8kuyNJGZK65wRPzljL+r0ZdKgbyfNd4vVEcTFRISQiTiG/oJCJi3fyxvdbyC0o5OH2NbindTV8PLUWWERERMRubWpF8FL3ejw+fS1PzljLzRGm3ZGklMvKzeeN77cw9pfthAV4836vxnRMiMIwNCuouKgQEhHbrdh5lBGzUtm0/ySta5bn+S7xxIb52x1LRERERM5yW2IlDp7M4ZVvN7O/gjuxCZnaaFpKxIIthxgxex3pR0/Ts2llnupUm2BfLVUsbiqERMQ2R0/l8vLXm5iWkk6FYB8+6N2YG+LV+ouIiIg4q3vbVCMrN58P5/9Gu9d+5toa4fRrHkfb2hG4az8XuUpHT+Xy4twNzFy1h6rh/jpduISpEBIRhyssNJmWks7L32wiMzufoa2q8mC7Gvh761eSiIiIiDMzDIPHb6hNLfaxyzOGyUt2MXhSCjHlfOmTHMsdSZUI8fOyO6a4GNM0mb16Dy/M3UjG6TweuK4697Wtru0jSthVPfoyDCMEGAMkACYwENgMTAPigB3A7aZpHruqlCJSaqTuOcEzs1NZnX6cplVCebFrAjV1VKSIiIiISwnyNri/jbXn4/cbDjBx8Q7++/UmXv9+C10bRtO3RSzxFYPtjikuIP1oFiNmp7JgyyEaVQ7hpe71qRWlxweOcLVPx78FfGOaZg/DMLwAP+BpYJ5pmi8ZhvEU8BTw5FV+HRFxcRnZebz+3RYmLd5BqL8Xr9/egG6NorU8TERERMSFebi70aleBTrVq8Cm/RlMWryTWSv3MC0lncTYcvRrEUfHhCg83d3sjipOJr+gkAmLdvDad1twM+C5W+LpnRyrpYcOdMWFkGEYwUAroD+AaZq5QK5hGF2ANkWXTQTmo0JIpMwyTZPP1+zlxS83cjgzh97NYhl+fS2C/bQpnIiIiEhpUjsqiP90q8eTHWszfcVuPlq8gwemrCIi0Ju7mlXmrqaViQjysTumOIH1e0/w1Ix1rNtzgna1I3ihawIVQ3SUvKMZpnllxwUahtEQGAVsABoAK4CHgD2maYYUXWMAx36/f97HDwGGAERGRjaZOnXqFeVwNpmZmQQEaKd9R9F4O9bljvfezEI+2pDDxqOFVAlyo2+8F1WCtQ74cuhn3LE03o6l8XYsjbfjacwdS+PtWJcy3oWmSerhAn7Ylc/aQwW4G5AY6U77WE+qh7hppvhlKC0/3zkFJnPS8vhmRx4Bnga963iRFOXudD8LpWW8Adq2bbvCNM3Ei73vagqhRGAJ0NI0zaWGYbwFZAAPnF0AGYZxzDTNcn/1uRITE82UlJQryuFs5s+fT5s2beyOUWZovB3rUsc7Kzefd39MY/TCbfh6uvNEx9r0bFpZ0z+vgH7GHUvj7Vgab8fSeDuextyxNN6OdbnjvePwKT5aspNPU9I5mZ1PfMUg+jWP45aGFbVx8CUoDT/fv6Yd5ulZ69h5JIs7EivxdOc6TrtqoDSM9+8Mw/jTQuhq9hDaDew2TXNp0f3pWPsFHTAMo4JpmvsMw6gAHLyKryEiLsQ0Tb7fcIDnvtjAnuOnubVxDP/oXJvwAG+7o4mIiIiIjeLC/Xn2pro8dn1NZq/ay8RFO3hixlr+8/VG7kiqRO9msVQK9bM7ppSAY6dy+b+vNjJ9xW6qhPsz5e5kmlfTUfLO4IoLIdM09xuGkW4YRi3TNDcD7bCWj20A+gEvFb2cUyxJRcSppR/N4t+fr2fepoPUigzk06HNaVol1O5YIiIiIuJE/Lw8uKtZZXo2rcTS7UeZtHgHYxZuZ9SCbbSrHUm/FrFcUz3c6ZYQyeX7fS/R57/YwInTedzbphoPtquhGWFO5GpPGXsA+LjohLFtwADADfjUMIxBwE7g9qv8GiLixHLyCxi9YBvv/JiGu5vBiM516N8yTidJiIiIiMifMgyD5KphJFcNY9+J03yydBdTlu3ih7EHqFren37N4+jeOJpAH+dcUiR/bfexLJ6Zncr8zYdoEBPM5MHNqFMhyO5Ycp6rKoRM01wNXGwtWrur+bwi4hoWbj3Ev+asZ9vhU3SuF8WzN9WlQrBOBxARERGRS1ch2JfHrq/F/ddV56t1+5i4aCf/+nw9//tmE7c2iaFv81iqRwTaHVMuQUGhycRFO3j1u80A/POmuvRrEae9RJ3U1c4QEpEy6EBGNi/M3cDctfuIC/Nj4sCmtK5Z3u5YIiIiIuLCvD3c6dYohm6NYliTfpxJi3cydVk6kxbv5Jrq4fRtHku7OpEqF5zUxn0ZPDVzHWvSj9O2Vnle6JpATDntC+XMVAiJyCUrKDQZs3Abb/6wldyCQh5pX5OhratqHbCIiIiIFKsGlUJ4rVIIT3euzdTl6Xy8ZCdDPlpBdIgvvZNjuTOpEuX8veyOKUB2XgFvz9vKqAXbCPb15K07G3JLg4raB8oFqBASkXMUFpocy8rl4MkcDv1+y7Refrv6NLszN9KmVnmeuyWe2DB/u+OKiIiISCkWFuDNfW2rM7RVVX7YeJCJi3bw8jebePOHLdzSoCL9WsSREB1sd8wya9Fvh3l65jp2HMmiR5MYRnSuo6LOhagQEikjTuXkc+hkzllFT/YfRc/Zpc/hzFwKCs0LPt7X050wb/igdxNuiI9U4y8iIiIiDuPh7kbHhCg6JkSx5cBJJi3ewcyVe/hsxW4aVw6hX4s4OiVUwMtDB5s4womsPP7z1UampaQTG+bHx4Ob0bJ6uN2x5DKpEBJxYXkFhRzJzOXgyewzxc5Z5c7Zr2flFlzw8e5uBuEBXpQP9CYi0If4CsGUD/Q+9xZgvfT39mD+/Pm0SYiy4TsVEREREbHUjAzkxa71eKJjbaan7OajJTt5aOpqXgjYyF3NKtOrWWUig3zsjlkqmabJl+v28e/PN3AsK5d7WlfjoXY18PXSFhKuSIWQiJMxTZMTp/POXbJ1fslTdP/oqdyLfo5gX88/ypyGlUL+KHXOL3rK+Xnhpk35RERERMQFBfl4MvCaKvRvEcfCtMNMWrSDd37cysif0rghIYp+zeNIiiunme3FZO/x0zw7O5V5mw5SLzqYCQOStFzPxakQEnGQ07kFHM7M+evZPEX38wouXLLl7eH2R5kTG+ZHUpVylA/wuaDoCQ/wwttDDb2IiIiIlA1ubgata5andc3y7DqSxUdLdjBteTpfrt1HnQpB9GseS5eG0ZrFcoUKCk0+WryDV77dTKEJz9xYh/4t4vBw1/I8V6dCSOQqFBSaHDmVc97ePOftyVN0/2RO/gUfbxgQ5n+mzKkeEUhEkPdFZ/QEenvo2Q0RERERkb9QOcyPETfW5dEOtZizeg8TFu3gqZnr+O/Xm7g9MYY+yXFUDtNR6Jdq8/6TPDVzLat2HadVzfL8X9cEKoVq/EoLFUIi5zFNk5O/b8CccfEZPL+/fvRUDhfZf5lAbw9rtk6gN3UqBtH6vP14fr+F+nmpWRcRERERKWa+Xu7c2bQydyRV+v/27j28iurc4/j3JQQCuUG4JNwDSIKggIooFC32oFZra7XeUaTtqW1Pj6faenpqT21tq/Zo9bH28ainpSiKWm3RequgRdJWQa7K/a4JYE0AL5CAXLPOH2vtZIIQAoS9k8zv8zz72bNnz8xe+92zZ9a8s2YN80o/YvLsUia9UcrE19/lc8VdGT+qkDOO66zuEw5i5559/O/MtTz0t3VkZ6Rz7+VD+fKwHjpB3cIoISSxsWvvPrZU7Q6Jnp31Jnp27a3+1PzpaVaT0OnRIYNhvXLpkp1RJ9HTNbstnbPaqjmqiIiIiEgTYGaM6JvHiL55lG/dyRNzynhi7nqunTSXfp0zuWZkH75ySk9yMtJTXdQmY847H3Dzs0t4Z/N2Lj6pBz++YBB5upV8i6SEkDRr1c7xQZVP5mzadvA+eTZX7mLrJ3sOuIy8zDY1CZ3CwsyaBM/+l27ltktXRlxEREREpJkqyM3ge+cU853PHce0peVMnlXKz15Yzq+mr+Lik3swfmQhRfnZqS5mymz9ZA//8/JKnpy7nl557Xj0ayM4s6hLqoslx5ASQtIs7N1XTdmHO1hVXsnK8kpWl1eyqqKSsg92UD39r5+avl16Wk1CZ0DXLEb171TbiienbU1nzJ2y2pCuS7ZERERERGKjbes0LhzWgwuH9WDJxq1Mnl3K0/M3MuXN9Yzq34nxIwsZe3zX2HTt4Jxj2tJyfvr8MrZU7eK6M/txw9gBtG+jdEFLp19YmhTnHOXbdtYmfULiZ82mKnaHy7haGRR2yqQ4P5vBObsZPngAXXPqXrqV2VartoiIiIiI1O/EnrncfelQfnT+8Tw1bwNT3izjW1MW0D03g3Gn9+GKU3vRKattqot5zJRv3cktzy3l1eUVDO6ew++vPZUTe+pW8nGho2ZJma079rCqopJV5dvCs39s21l7N678nLYUF+Qwqn8nigtyGFiQzXFds8hI9330lJSUMOYzfVP1FUREREREpAXIy2zDt8f057oz+/HXFRU8OtvfZv2+GWv44pDuXDuqD0N6dkh1MRtNdbXj8bnruevlleyprubm8wby9dF9Y9MqSjwlhOSY27lnH2s3VdW09kkkfjPa7qMAABYnSURBVMq37ayZJjujNcX52XxxaHeKC7Ipzs+muCCbDu3VeZmIiIiIiCRHWivj3MEFnDu4gDUVlTz2ZhlTF2xk6sKNDOvVgWtH9eH8E7vRtnXzvYnMmopKbn5mCfPLPmL0cZ25/aIT6NMpM9XFkhRQQkgazb5qR9kH21ld4fv5SSSASrdsr7k1e5u0VvTvmsXI/p3qJH665Waow2YREREREWkyBuRn8/MLT+A/zy1m6oKNPDq7jBufWsTtL63gyhG9ueq03nTLbZfqYjbYrr37eGDmOh4oWUtm29bcc+lQLj5Zt5KPMyWE5LA559hUuaumn5+V5ZWsqtjGmoqqmtu1m0GfvPYU5WdzwYndKC7Iobggi8JOmWqGKCIiIiIizUZ2RjoTPtOX8SMLeWPdFibPKuP+mWt5oGQd5w7OZ/zIQk7rm9ekEyvzSz/kh88sYe2mKi4c1p1bLhhE5xbcN5I0jBJCUq9tO/fUJH0SLX9WV1Ty8Y7aW7h3yW7LwIJsrj69D8UF2TX9/KhXehERERERaSlatTLOGNCFMwZ0YcOHO5jyZhl/mLeBvywpZ2BBNuNHFvLlk7o3qeOgbTv3cOfLK3l8znp6dGjHw189lbOKu6a6WNJENJ01VVJq117fz09N0idc8vXPrbX9/GS1bU1RfhbnndCN4vys0Oonm7xM9fMjIiIiIiLx0SuvPTeffzw3jC3ihUX/5JFZpfzo2SX88uUVXDa8F9ec3ofCzqntl2f6snJ+8txSNlfu4uuj+/K9s4t0N2apQ2tDzFRXO9Z/uKNO586rKip5d8t29oWOftLTjP5dsji1b16dfn56dGjXpJtBioiIiIiIJFO7NmlcdmovLh3ekwVlHzF5dhmTZ5Uy6Y13GVPUhfGjCvnsgC60apW846iKbTv56XPLmLbMt1z67TXDGdqr5dwhTRqPEkItlHOOzVW7apM+IfGzpqKKT/bsq5mud+jn5/ODC3zypyCbvp0zSVc/PyIiIiIiIg1iZgwvzGN4YR6bvnA8j89ZzxNz1/PVh+dR2Kk9V5/eh0uH9yK3XfoxK0N1teMP8zbwy5dXsHtvNT/4fDHfOKOfju3koJQQagEqd+5hdYW/rbu/5Gsbq8or+SjSz0/nrDYUF2RzxYheDCzIprgghwFds9RkUEREREREpBF1zcngxrOL+M5ZxzFtWTmPzirltpdWcM8rq7no5B6MH9mHgQU5jfqZazdV8aNnljC39ENG9uvEHRefSN8UX7ImTZ+yAc3I7r3VrNtct5+fleWVvPfxJzXTtG+TRlF+NucOLqAo33fwXFSQrR7kRUREREREkqhN61Z8aWh3vjS0O0vf28qjs0uZumAjT8xZz2l985gwqpCzB+Uf1V2Yd++t5qG/reP+19bSrk0ad10yhEtP6amuPqRBlBBqgqqrHRs/+oSV5dvq3Nnrnc3b2Rv6+WndyujXJZOT+3TkqtN61yR/enRol9TrU0VERERERKR+J/TI5a5LhnLzecfz9PwNPPZmGd9+fCHdcjMYd1pvrhjR+7BP4i8o+4ibn1nM6ooqLhjSjZ9+cTBdstUQQBpOCaEU2xL6+alp8VNRyZqKSnbsru3np2fHdhTnZzP2+Pyafn76dc6iTWtdCyoiIiIiItJcdMxswzc/259/PaMfr63cxKOzS7n7ldX8ZsZaLhjSjfGjChl2iA6gq3bt5VfTVvLom2V0y8lg0oThfG5gfnK+gLQoSgglyfZde1kd7uyVaPGzqrySD7bvrpkmL7MNxfnZXDa8V03iZ0DXLLIzjl3HYyIiIiIiIpJcaa2Mswflc/agfNZuqmLKm2X8acFGnnnrPYb2zGX8yEK+MKQbGelpdeb76/IKbnluKeXbdnLtyEJuOreYLPULK0dIa04j21vtau7otSp07ryqopINH9b289MuPY2i/Cz+5fiu4VKvHIoLsumc1UbXeoqIiIiIiMTIcV2zuPVLg/n+OUU8+9Z7TJ5Vyvf/uIg7/rKCK0b0Ytxpffh4VzXfeXwhLy15n+L8bB4YdzIn9e6Y6qJLM6eEUCO6euIcZq/bwb5X/g74rG+/zpkM6dmBy07pRVGB7+enV8f26udHREREREREamRnpDN+ZCHXnN6HN9Z+wOTZpTxYso4HS9bRphVU2y5uOqeI687sr+5DpFEoIdSITurdgZx9WzlnxGCK8rPp3zWTtq3TDj2jiIiIiIiICGBmjB7QmdEDOrPhwx1MmVPG4tVl3H7VaPp1yUp18aQFUUKoEX3/nGJKSt5nzEk9Ul0UERERERERaeZ65bXn5vOOp6RdhZJB0ujUzkxEREREREREJGaUEBIRERERERERiRklhEREREREREREYkYJIRERERERERGRmFFCSEREREREREQkZpQQEhERERERERGJGSWERERERERERERiRgkhEREREREREZGYUUJIRERERERERCRmlBASEREREREREYkZJYRERERERERERGJGCSERERERERERkZhRQkhEREREREREJGaUEBIRERERERERiRklhEREREREREREYkYJIRERERERERGRmFFCSEREREREREQkZpQQEhERERERERGJGXPOpboMmNlmoCzV5WgknYEtqS5EjCjeyaV4J59inlyKd3Ip3smleCefYp5cindyKd7JpXgnV0uKdx/nXJcDvdEkEkItiZnNd84NT3U54kLxTi7FO/kU8+RSvJNL8U4uxTv5FPPkUryTS/FOLsU7ueISb10yJiIiIiIiIiISM0oIiYiIiIiIiIjEjBJCje+3qS5AzCjeyaV4J59inlyKd3Ip3smleCefYp5cindyKd7JpXgnVyzirT6ERERERERERERiRi2ERERERERERERiRgmhwMyqUl2Gls7M9pnZ25FHYT3TlphZi+/VPVXMzJnZlMjr1ma22cxebKTl6/90CGb25fA7DDyCeSea2aAwXGpmnRu/hC3PsV7vpS5tB1LjUHHX/vXwHM22+ig+8wYza5+sz0sGM/tvM1tmZotDHfC0I1jGGDMb1Yhliu3+08x6mtlzZrbGzNaZ2X1m1qae6Ru0TsZ5ux+2E/dEXt9kZremqCyx+B0ix5bLzGyRmX3fzFKS32jOMVdCKIXMrHWqy5BknzjnhkUepUezsMaIn5mlHe0ymqntwAlm1i68Pht473AWEMP1t7FdCbwenhvMzNKcc//qnFt+bIrVoh31ei8isXNE2+qjdAPQYhJCZjYSuAA42Tk3BBgLbDiCRY0BGi0hdDSacx3IzAx4Bvizc24AUARkAbfXM9sxXyebc0yDXcDFzT3J2Mx+h8Sx5WB8ne484KcpLtNhS3XMlRCKMLMsM5thZgvNbImZXRjGF5rZCjP7XchAvpI4oIieaTOzzmZWGpnnH2FZCxNnNMLZjX+Y2fPAcjP7uZndECnD7Wb23WR/91Qxs1PM7G9mtsDMpptZt8jb14Ss71IzGxGmv9XMHjOzN4DHzGyCmd0fWd6LZjYmDD9oZvPDb/azyDSlZnanmS0EfhieE+8NiL5u4f4CfCEMXwk8mXjDzEaY2Wwze8vMZplZcRg/wcyeN7PXgBnhP/Nw+L8sNrOvRJZxe8jWv2lm+cn8Yk2dmWUBo4GvA1eEcWPM7O9m9pKZrTKzhxJnOcysyszuMbNFwEjTGf6jcSTr/d/NbFhkutfNbGhSS91MhfX6xcjr+81sQhguNbOfRfa5A8P4TDObZGZzw29xYYqK32zVF/fIuK+Z2a8jr79hZvcmsZhNXj3b6oOt0+eb2cpQp/lNYrpQd7kpMs/SUE/MDNv8RWHc5Wb2H0B3YKaZzUzetz2mugFbnHO7AJxzW5xz/zxYHTDs4+6L1gHNtyr/FnBjGH+GmXUxs6lmNi88PhPmv9XMJpuvb5eZ2cVmdlfYzkwzs/RI2X4Qxs81s+PC/PUtt6YOmrToNb7PATudcw8DOOf2ATcCXwvr5N0h7ovN7PoDrZNmdmWI21IzuzO6cDO713zde4aZdQnj+ofYLwi/S2J7/0io78wB7kpeCI6JvfhOiG/c/43wf38txHSGmfU2s9ywfibqeplmtsHM0g8RrwfN163fCdujSeaPUx/Z7zNj9Ts45zYB1wH/bl6amf0q/IcXm9k3E9Oa2X+F9XeRmf1PGBffmDvn9PAda1cBrYGc8LozsBYwoBD/Jx8W3nsauDoMlwDDI/OUhuH2QEYYHgDMD8Nj8Gep+4bXhcDCMNwKWAd0SnU8jlGM9wFvh8ezQDowC+gS3r8cmBSJ6+/C8JnA0jB8K7AAaBdeTwDuj3zGi8CYMJwXntPC8oaE16XADyLzzIz8tncA16c6Vkn4LaqAIcCfgIzwm4wBXgzv5wCtw/BYYGok3hsjsb0T+HVkuR3DswO+GIbvAn6c6u/clB7AOOD3YXgWcEqI/06gX1hnXwUuicTzssj80e1OKdA51d+pOTyOYr2/NrGe48+kzk/1d2kOjxDvmviGcfcDE8JwaWJ7C/wbMDEM30HtPrYDsBrITPX3aS6PBsS9BBiObxGwDkgP42cBJ6a6/E3pUc+2+lOxDduUDdTW756MbFtuBW6KzLMUX//7CqGuE8bnhucWtV0P69rb4b/8APBZjrwOGI3jE8DoMNwbWBGZ7vXwGUOBHcB54b1ngS9H4vzfYXh85Peqb7k1ddDm+gD+A7j3AOPfAr6L30cm9oWJ+l7NOolPDq0HuuCPnV6LxNQB48LwTwh1dGAGMCAMnwa8FoYfwdfd01Idl0aIaxW+HlEK5AI3AbeG914Arg3DX8O3zgJ4Djgr8h9I7Afri9cf8MenFwLbgBPxx5ALqD2eicXvAFQdYNzHQD4+OfTjMK4tMB/oi29FNAtov986HtuYN6cmYclgwB1mdiZQDfTAr1AA7zrn3g7DC/A78vqkA/ebP6u8D38QkTDXOfcugHOu1Mw+MLOTwme95Zz7oFG+TdPziXMuepb9BOAE4FUzA38Q/H5k+icBnHN/N7McM+sQxj/vnPukAZ93mZldh99ZdQMGAYvDe09FppsIfNXMvoffGI847G/WDDnnFps/43YlvtVEVC4w2cwG4Ddw0bNprzrnPgzDYwlnTcMyPwqDu/EbOfD/l7MbtfDN35XAfWH4D+H1i/htwzsAZvYk/sz0n/DbkKkpKGeLc4Tr/R+BW8zsP/EVuUeSUth4eCY8LwAuDsPnAF+y2hYVGYSDsiSXrUVzzlWZb+15gZmtwCeGlqS6XE3MwbbVBzIQeCdRv8PXYa47xPKXAPeEFhYvOuf+cZTlbZLCunYKcAZwFr4OdhtHVgeMGgsMCvMD5Jhv1QXwsnNuj5ktCcueFsYvoW4d/snIc6KFXH3LbWgdtLkaAzzgnNsLEKnvRZ0KlDjnNgOY2eP4xN2f8cdPiTr2FOCZELtRwB8jMW0bWd4fnW+l1Ow557aZ2aP4pFt0PRlJ7T7uMWpbhDyFP/aYia9PP9CAeL3gnHNh3a5IbLfNbBl+3X6bmP8OwTnAEDO7JLzOxTfSGAs87JzbAX4dj3vMlRCqaxw+231K2ImU4iui4K8LTdgHJPqg2EvtpXcZkWluBCrwZyZa4c/8J2zf73Mn4s8uFQCTjuobNC8GLHPOjTzI++4gr6Pxi8Yfwm9gZn3xmflTnXMfhSZ90d8nuoyp+OtNXwMWtOCE3IE8D9yNrwB0ioz/BTDTOXdROHguiby3//p7IHtcSH/j/y/a1gRmlodvrn2imTl8RdUBL3HwdX5nU9hhtCCHtd4753aY2av4M0OX4VsJSMMccBsdkdi3RrcTBnzFObfqGJetJTtU3BMmAj8CVgIPH+tCNSf1bKufo2GxjTrg7+GcW21mJwPnA7eZ2Qzn3M8bo/xNTdiHlQAl4aDqOxxZHTCqFXC6cy5axyYceCUuT6s2s2idpJq6dRJ3gOH6ltuQOlBTtxy4JDrCzHLwiffSRv4sh4/nx9GTwvtpCTGN+jWwkIZtU5/HN0bIw9ctXgMyqT9eif1mNXWPT/dft6Ni8TuYWT98fWITvi5xvXNu+n7TnHuAWQ8VmxYdc/UhVFcusCkkg84C+jRgnlJqDw6iG9dc4H3nXDVwDb4icTDPAp/HZ9yn1zNdS7MK6GK+s0HMXzM7OPL+5WH8aGCrc27rAZZRCgwzs1Zm1ova1j05+D/ZVvP915x3sEKEHf504EHiVyGeBPzsAGeFc6ntbHdCPfO/iq/UAWBmHRu1dC3TJcBjzrk+zrlC51wv4F38mdMRZtbX/PXkl+ObvEvjO5L1fiLwG2BepCWcHFoZ/kx723CG/18aMM904HoLR1+hBa0cngbF3Tk3B+gFXEWkPy0BDr6tbsWBY7sK6Ge1d1C9PLKsUuBkgJAA6huGuwM7nHNTgF8lpgEqgexj9L2SzsyKQ8vLhGH4Fn+HWwfcPy6vANdHPudgB131uTzyPLsRl9uUzQDam9l4qLnByj341q/TgW9a6OQ2JCqgbuznAp8133dqGr7l3N/Ce62oPR66CnjdObcNeNfMLg3LNGvB/fCFVlVP4/seS5hFbYv6ccA/wrRVwDx8S8QXnXP7GilesfsdzPfZ8xD+Ui2HX5e/baHPMDMrMrNM/LHLVy3cNc/M8uIecyWEqOnZexfwODA8nLkYjz9jdih341e2t/B9CCU8AFxrvhPYgdSTAXTO7cY3FXw6Tq0Awve+BLgzxOlt6t49YmeI60PU3ahGvYGvoC3HH6wtDMtehL8WeiX+WvA3DlGcx/FZ3leO6Ms0U865jc653xzgrbuAX4b419e65zago/lOBRfhm4JL/a7EJ4Gjpobx8/D9UazAr9f7TyeN4EjWe+fcAvx143FLGh+RxH7VObcBXzFeGp7fasDsv8Bfrrc4NMf+xTEraAtzhHF/GnhDic5POdi2+goOENtwGdG/AdPMbAH+AHprZL68sD7/O74vHfD9UMw1s7fxLZVvC+N/G5Yz8xh8r1TIwl+Ou9zMFuMv4f8Jh18HfAG4yEKn0vjLcoab7zB2Ob7T6cPVMZTpu9R2BtwYy22ywsHyRcClZrYGvz7uxLcWnIjvH2hx+F2uCrPVrJPOufeBH+KPXRbhW9c/F6bbjj+5tRTfwi7R4m0c8PWwzGX4Frct2T3UPS68Hp+EWIxvKBC9gdBTwNXU7c7iaOMVl9+hXdgeLAP+ij+OS9xIaCL++HBhiMP/4fvGmoZvmTU/bHsTl6fHNuZW24IyvkKm7nfOuZT0HRNaAywELnXOrUlFGeLOfF8Vuc65W1JdFokn83fHu8k5d0GqyyKfFs7klwADQ8tPqUeq96txdSRxN38nrHudczOOXcniwcyyQn85BvwvsMY5pzu3HSYzK8HvD+enuiwiIi1d7FsImdm38M2kf5yizx+Ev5vZDCWDUsPMnsW3CLvvUNOKSPyEZvVz8HejUTLoEFK9X42rw427mXUws9X4Gz4oGdQ4vhHOOC/DX4L6fykuj4iISL3UQkhEREREREREJGZi30JIRERERERERCRulBASEREREREREYkZJYRERERERERERGJGCSERERERERERkZhRQkhEREREREREJGaUEBIRERERERERiZn/B9plIbqa3LjWAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1440x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zq5Z-6OQ7nho"
      },
      "source": [
        "Problem statement:\n",
        "1. Which are the most busy month or in which months Guest are high?\n",
        "2. How long do people stay at the hostels ?  "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "Mj-K43RZLRK0",
        "outputId": "45459fb7-747b-4c76-fe9b-9a239d7c87cc"
      },
      "source": [
        "# Check the data resort\n",
        "data_resort.head()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>children</th>\n",
              "      <th>babies</th>\n",
              "      <th>meal</th>\n",
              "      <th>country</th>\n",
              "      <th>market_segment</th>\n",
              "      <th>distribution_channel</th>\n",
              "      <th>is_repeated_guest</th>\n",
              "      <th>previous_cancellations</th>\n",
              "      <th>previous_bookings_not_canceled</th>\n",
              "      <th>reserved_room_type</th>\n",
              "      <th>assigned_room_type</th>\n",
              "      <th>booking_changes</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Direct</td>\n",
              "      <td>Direct</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>C</td>\n",
              "      <td>C</td>\n",
              "      <td>3</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/1/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Direct</td>\n",
              "      <td>Direct</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>C</td>\n",
              "      <td>C</td>\n",
              "      <td>4</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/1/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>GBR</td>\n",
              "      <td>Direct</td>\n",
              "      <td>Direct</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>C</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/2/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>GBR</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>A</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>304.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/2/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>GBR</td>\n",
              "      <td>Online TA</td>\n",
              "      <td>TA/TO</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>A</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>240.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>98.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/3/2015</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          hotel  is_canceled  ...  reservation_status  reservation_status_date\n",
              "0  Resort Hotel            0  ...           Check-Out                 7/1/2015\n",
              "1  Resort Hotel            0  ...           Check-Out                 7/1/2015\n",
              "2  Resort Hotel            0  ...           Check-Out                 7/2/2015\n",
              "3  Resort Hotel            0  ...           Check-Out                 7/2/2015\n",
              "4  Resort Hotel            0  ...           Check-Out                 7/3/2015\n",
              "\n",
              "[5 rows x 32 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "enBEjUsfLW6J",
        "outputId": "c0203a01-6173-4bc0-bb28-0825c1818d6a"
      },
      "source": [
        "#Count the number of arrival for the resort hotel\n",
        "rush_resort = data_resort['arrival_date_month'].value_counts().reset_index()\n",
        "rush_resort.columns=['month', 'no of guests'] # Shift the column name\n",
        "rush_resort"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>month</th>\n",
              "      <th>no of guests</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>August</td>\n",
              "      <td>3257</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>July</td>\n",
              "      <td>3137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>October</td>\n",
              "      <td>2575</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>March</td>\n",
              "      <td>2571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>April</td>\n",
              "      <td>2550</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>May</td>\n",
              "      <td>2535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>February</td>\n",
              "      <td>2308</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>September</td>\n",
              "      <td>2102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>June</td>\n",
              "      <td>2037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>December</td>\n",
              "      <td>2014</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>November</td>\n",
              "      <td>1975</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>January</td>\n",
              "      <td>1866</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        month  no of guests\n",
              "0      August          3257\n",
              "1        July          3137\n",
              "2     October          2575\n",
              "3       March          2571\n",
              "4       April          2550\n",
              "5         May          2535\n",
              "6    February          2308\n",
              "7   September          2102\n",
              "8        June          2037\n",
              "9    December          2014\n",
              "10   November          1975\n",
              "11    January          1866"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "GgKoqxFYMJrk",
        "outputId": "da4dd330-78e1-4893-e6cb-52a5143a42e9"
      },
      "source": [
        "rush_city = data_city['arrival_date_month'].value_counts().reset_index()\n",
        "rush_city.columns=['month', 'no of guests'] # Shift the column name\n",
        "rush_city"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>month</th>\n",
              "      <th>no of guests</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>August</td>\n",
              "      <td>5367</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>July</td>\n",
              "      <td>4770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>May</td>\n",
              "      <td>4568</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>June</td>\n",
              "      <td>4358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>October</td>\n",
              "      <td>4326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>September</td>\n",
              "      <td>4283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>March</td>\n",
              "      <td>4049</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>April</td>\n",
              "      <td>4010</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>February</td>\n",
              "      <td>3051</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>November</td>\n",
              "      <td>2676</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>December</td>\n",
              "      <td>2377</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>January</td>\n",
              "      <td>2249</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        month  no of guests\n",
              "0      August          5367\n",
              "1        July          4770\n",
              "2         May          4568\n",
              "3        June          4358\n",
              "4     October          4326\n",
              "5   September          4283\n",
              "6       March          4049\n",
              "7       April          4010\n",
              "8    February          3051\n",
              "9    November          2676\n",
              "10   December          2377\n",
              "11    January          2249"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Gp0GSdKdNA3k"
      },
      "source": [
        "# Merge the 2 dataframe together\n",
        "final_rush = rush_resort.merge(rush_city, on='month') # merge on the basis of month"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "wYxLENiSNVSY",
        "outputId": "cdccddce-9a73-4f5c-a9ea-ad5041385e43"
      },
      "source": [
        "final_rush\n",
        "final_rush.columns = ['month', 'no of guest in resort', 'no of guest in city hotel']\n",
        "final_rush"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>month</th>\n",
              "      <th>no of guest in resort</th>\n",
              "      <th>no of guest in city hotel</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>August</td>\n",
              "      <td>3257</td>\n",
              "      <td>5367</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>July</td>\n",
              "      <td>3137</td>\n",
              "      <td>4770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>October</td>\n",
              "      <td>2575</td>\n",
              "      <td>4326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>March</td>\n",
              "      <td>2571</td>\n",
              "      <td>4049</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>April</td>\n",
              "      <td>2550</td>\n",
              "      <td>4010</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>May</td>\n",
              "      <td>2535</td>\n",
              "      <td>4568</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>February</td>\n",
              "      <td>2308</td>\n",
              "      <td>3051</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>September</td>\n",
              "      <td>2102</td>\n",
              "      <td>4283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>June</td>\n",
              "      <td>2037</td>\n",
              "      <td>4358</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>December</td>\n",
              "      <td>2014</td>\n",
              "      <td>2377</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>November</td>\n",
              "      <td>1975</td>\n",
              "      <td>2676</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>January</td>\n",
              "      <td>1866</td>\n",
              "      <td>2249</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        month  no of guest in resort  no of guest in city hotel\n",
              "0      August                   3257                       5367\n",
              "1        July                   3137                       4770\n",
              "2     October                   2575                       4326\n",
              "3       March                   2571                       4049\n",
              "4       April                   2550                       4010\n",
              "5         May                   2535                       4568\n",
              "6    February                   2308                       3051\n",
              "7   September                   2102                       4283\n",
              "8        June                   2037                       4358\n",
              "9    December                   2014                       2377\n",
              "10   November                   1975                       2676\n",
              "11    January                   1866                       2249"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qWxYFk1wNpAs"
      },
      "source": [
        "final_rush = sort_data(final_rush, 'month')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QlSUkh8QSanW",
        "outputId": "25ae4faa-374c-4bde-f7f8-229d617efb8f"
      },
      "source": [
        "final_rush.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['month', 'no of guest in resort', 'no of guest in city hotel'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 288
        },
        "id": "rx7Ar_z0N7k3",
        "outputId": "1da07f1c-dd97-4559-a762-a1eeb7fe7294"
      },
      "source": [
        "# Need some trend so we plot\n",
        "plt.figure(figsize=(20,8))\n",
        "plt.plot(final_rush['month'],final_rush['no of guest in resort'],label=' No of guest in Resort')\n",
        "plt.plot(final_rush['month'],final_rush['no of guest in city hotel'],label='No of guess in City_hotel')\n",
        "plt.grid(True)\n",
        "plt.legend()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f5d424faa50>"
            ]
          },
          "metadata": {},
          "execution_count": 45
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8MTGlk4vSlYL"
      },
      "source": [
        "Select important Features using Co-relation for Machine-learning"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "id": "bRdra8thYKaL",
        "outputId": "f1d8700e-d797-4767-9562-90ad0a44f02b"
      },
      "source": [
        "#Check the data \n",
        "data.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>children</th>\n",
              "      <th>babies</th>\n",
              "      <th>meal</th>\n",
              "      <th>country</th>\n",
              "      <th>market_segment</th>\n",
              "      <th>distribution_channel</th>\n",
              "      <th>is_repeated_guest</th>\n",
              "      <th>previous_cancellations</th>\n",
              "      <th>previous_bookings_not_canceled</th>\n",
              "      <th>reserved_room_type</th>\n",
              "      <th>assigned_room_type</th>\n",
              "      <th>booking_changes</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Direct</td>\n",
              "      <td>Direct</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>C</td>\n",
              "      <td>C</td>\n",
              "      <td>3</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/1/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>PRT</td>\n",
              "      <td>Direct</td>\n",
              "      <td>Direct</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>C</td>\n",
              "      <td>C</td>\n",
              "      <td>4</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/1/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>GBR</td>\n",
              "      <td>Direct</td>\n",
              "      <td>Direct</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>C</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/2/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>GBR</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>A</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>304.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/2/2015</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>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>BB</td>\n",
              "      <td>GBR</td>\n",
              "      <td>Online TA</td>\n",
              "      <td>TA/TO</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>A</td>\n",
              "      <td>A</td>\n",
              "      <td>0</td>\n",
              "      <td>No Deposit</td>\n",
              "      <td>240.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>98.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>7/3/2015</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          hotel  is_canceled  ...  reservation_status  reservation_status_date\n",
              "0  Resort Hotel            0  ...           Check-Out                 7/1/2015\n",
              "1  Resort Hotel            0  ...           Check-Out                 7/1/2015\n",
              "2  Resort Hotel            0  ...           Check-Out                 7/2/2015\n",
              "3  Resort Hotel            0  ...           Check-Out                 7/2/2015\n",
              "4  Resort Hotel            0  ...           Check-Out                 7/3/2015\n",
              "\n",
              "[5 rows x 32 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 697
        },
        "id": "Uk_Xm5qhY3Ng",
        "outputId": "af2edd60-de75-4906-bbbb-baec40e61d7d"
      },
      "source": [
        "# Find correlation in the datable\n",
        "data.corr()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>is_canceled</th>\n",
              "      <th>lead_time</th>\n",
              "      <th>arrival_date_year</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>children</th>\n",
              "      <th>babies</th>\n",
              "      <th>is_repeated_guest</th>\n",
              "      <th>previous_cancellations</th>\n",
              "      <th>previous_bookings_not_canceled</th>\n",
              "      <th>booking_changes</th>\n",
              "      <th>agent</th>\n",
              "      <th>company</th>\n",
              "      <th>days_in_waiting_list</th>\n",
              "      <th>adr</th>\n",
              "      <th>required_car_parking_spaces</th>\n",
              "      <th>total_of_special_requests</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>is_canceled</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.292876</td>\n",
              "      <td>0.016622</td>\n",
              "      <td>0.008315</td>\n",
              "      <td>-0.005948</td>\n",
              "      <td>-0.001323</td>\n",
              "      <td>0.025542</td>\n",
              "      <td>0.058182</td>\n",
              "      <td>0.004851</td>\n",
              "      <td>-0.032569</td>\n",
              "      <td>-0.083745</td>\n",
              "      <td>0.110139</td>\n",
              "      <td>-0.057365</td>\n",
              "      <td>-0.144832</td>\n",
              "      <td>-0.046770</td>\n",
              "      <td>-0.083594</td>\n",
              "      <td>0.054301</td>\n",
              "      <td>0.046492</td>\n",
              "      <td>-0.195701</td>\n",
              "      <td>-0.234877</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>lead_time</th>\n",
              "      <td>0.292876</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.040334</td>\n",
              "      <td>0.127046</td>\n",
              "      <td>0.002306</td>\n",
              "      <td>0.085985</td>\n",
              "      <td>0.166892</td>\n",
              "      <td>0.117575</td>\n",
              "      <td>-0.037878</td>\n",
              "      <td>-0.021003</td>\n",
              "      <td>-0.123209</td>\n",
              "      <td>0.086025</td>\n",
              "      <td>-0.073599</td>\n",
              "      <td>0.002230</td>\n",
              "      <td>-0.013114</td>\n",
              "      <td>-0.085854</td>\n",
              "      <td>0.170008</td>\n",
              "      <td>-0.065018</td>\n",
              "      <td>-0.116624</td>\n",
              "      <td>-0.095949</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>arrival_date_year</th>\n",
              "      <td>0.016622</td>\n",
              "      <td>0.040334</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.540373</td>\n",
              "      <td>-0.000121</td>\n",
              "      <td>0.021694</td>\n",
              "      <td>0.031203</td>\n",
              "      <td>0.030266</td>\n",
              "      <td>0.054710</td>\n",
              "      <td>-0.013192</td>\n",
              "      <td>0.010281</td>\n",
              "      <td>-0.119905</td>\n",
              "      <td>0.029234</td>\n",
              "      <td>0.031416</td>\n",
              "      <td>0.056438</td>\n",
              "      <td>0.033682</td>\n",
              "      <td>-0.056348</td>\n",
              "      <td>0.198429</td>\n",
              "      <td>-0.013812</td>\n",
              "      <td>0.108610</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>arrival_date_week_number</th>\n",
              "      <td>0.008315</td>\n",
              "      <td>0.127046</td>\n",
              "      <td>-0.540373</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.066572</td>\n",
              "      <td>0.018629</td>\n",
              "      <td>0.016047</td>\n",
              "      <td>0.026567</td>\n",
              "      <td>0.005556</td>\n",
              "      <td>0.010417</td>\n",
              "      <td>-0.031125</td>\n",
              "      <td>0.035493</td>\n",
              "      <td>-0.021009</td>\n",
              "      <td>0.006311</td>\n",
              "      <td>-0.018225</td>\n",
              "      <td>-0.032912</td>\n",
              "      <td>0.022677</td>\n",
              "      <td>0.076281</td>\n",
              "      <td>0.001980</td>\n",
              "      <td>0.026202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>arrival_date_day_of_month</th>\n",
              "      <td>-0.005948</td>\n",
              "      <td>0.002306</td>\n",
              "      <td>-0.000121</td>\n",
              "      <td>0.066572</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.016225</td>\n",
              "      <td>-0.028362</td>\n",
              "      <td>-0.001754</td>\n",
              "      <td>0.014550</td>\n",
              "      <td>-0.000235</td>\n",
              "      <td>-0.006471</td>\n",
              "      <td>-0.027027</td>\n",
              "      <td>-0.000306</td>\n",
              "      <td>0.011266</td>\n",
              "      <td>0.000159</td>\n",
              "      <td>0.003667</td>\n",
              "      <td>0.022532</td>\n",
              "      <td>0.030291</td>\n",
              "      <td>0.008569</td>\n",
              "      <td>0.003026</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>stays_in_weekend_nights</th>\n",
              "      <td>-0.001323</td>\n",
              "      <td>0.085985</td>\n",
              "      <td>0.021694</td>\n",
              "      <td>0.018629</td>\n",
              "      <td>-0.016225</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.494175</td>\n",
              "      <td>0.094759</td>\n",
              "      <td>0.046135</td>\n",
              "      <td>0.018607</td>\n",
              "      <td>-0.086009</td>\n",
              "      <td>-0.012769</td>\n",
              "      <td>-0.042859</td>\n",
              "      <td>0.050191</td>\n",
              "      <td>0.162411</td>\n",
              "      <td>-0.080783</td>\n",
              "      <td>-0.054399</td>\n",
              "      <td>0.050670</td>\n",
              "      <td>-0.018520</td>\n",
              "      <td>0.073124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>stays_in_week_nights</th>\n",
              "      <td>0.025542</td>\n",
              "      <td>0.166892</td>\n",
              "      <td>0.031203</td>\n",
              "      <td>0.016047</td>\n",
              "      <td>-0.028362</td>\n",
              "      <td>0.494175</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.096214</td>\n",
              "      <td>0.044652</td>\n",
              "      <td>0.020373</td>\n",
              "      <td>-0.095302</td>\n",
              "      <td>-0.013976</td>\n",
              "      <td>-0.048873</td>\n",
              "      <td>0.080018</td>\n",
              "      <td>0.196777</td>\n",
              "      <td>-0.044437</td>\n",
              "      <td>-0.002026</td>\n",
              "      <td>0.066847</td>\n",
              "      <td>-0.024933</td>\n",
              "      <td>0.068738</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>adults</th>\n",
              "      <td>0.058182</td>\n",
              "      <td>0.117575</td>\n",
              "      <td>0.030266</td>\n",
              "      <td>0.026567</td>\n",
              "      <td>-0.001754</td>\n",
              "      <td>0.094759</td>\n",
              "      <td>0.096214</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.029409</td>\n",
              "      <td>0.017890</td>\n",
              "      <td>-0.140973</td>\n",
              "      <td>-0.007070</td>\n",
              "      <td>-0.108856</td>\n",
              "      <td>-0.041472</td>\n",
              "      <td>0.023370</td>\n",
              "      <td>-0.166182</td>\n",
              "      <td>-0.008365</td>\n",
              "      <td>0.224253</td>\n",
              "      <td>0.014438</td>\n",
              "      <td>0.123353</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>children</th>\n",
              "      <td>0.004851</td>\n",
              "      <td>-0.037878</td>\n",
              "      <td>0.054710</td>\n",
              "      <td>0.005556</td>\n",
              "      <td>0.014550</td>\n",
              "      <td>0.046135</td>\n",
              "      <td>0.044652</td>\n",
              "      <td>0.029409</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.023999</td>\n",
              "      <td>-0.032475</td>\n",
              "      <td>-0.024755</td>\n",
              "      <td>-0.021078</td>\n",
              "      <td>0.051000</td>\n",
              "      <td>0.050461</td>\n",
              "      <td>-0.042554</td>\n",
              "      <td>-0.033293</td>\n",
              "      <td>0.325057</td>\n",
              "      <td>0.056247</td>\n",
              "      <td>0.081747</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>babies</th>\n",
              "      <td>-0.032569</td>\n",
              "      <td>-0.021003</td>\n",
              "      <td>-0.013192</td>\n",
              "      <td>0.010417</td>\n",
              "      <td>-0.000235</td>\n",
              "      <td>0.018607</td>\n",
              "      <td>0.020373</td>\n",
              "      <td>0.017890</td>\n",
              "      <td>0.023999</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.008813</td>\n",
              "      <td>-0.007509</td>\n",
              "      <td>-0.006552</td>\n",
              "      <td>0.085605</td>\n",
              "      <td>0.030235</td>\n",
              "      <td>-0.009426</td>\n",
              "      <td>-0.010627</td>\n",
              "      <td>0.029043</td>\n",
              "      <td>0.037389</td>\n",
              "      <td>0.097939</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>is_repeated_guest</th>\n",
              "      <td>-0.083745</td>\n",
              "      <td>-0.123209</td>\n",
              "      <td>0.010281</td>\n",
              "      <td>-0.031125</td>\n",
              "      <td>-0.006471</td>\n",
              "      <td>-0.086009</td>\n",
              "      <td>-0.095302</td>\n",
              "      <td>-0.140973</td>\n",
              "      <td>-0.032475</td>\n",
              "      <td>-0.008813</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.082740</td>\n",
              "      <td>0.420642</td>\n",
              "      <td>0.013044</td>\n",
              "      <td>-0.051584</td>\n",
              "      <td>0.161871</td>\n",
              "      <td>-0.022057</td>\n",
              "      <td>-0.130807</td>\n",
              "      <td>0.077928</td>\n",
              "      <td>0.012963</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>previous_cancellations</th>\n",
              "      <td>0.110139</td>\n",
              "      <td>0.086025</td>\n",
              "      <td>-0.119905</td>\n",
              "      <td>0.035493</td>\n",
              "      <td>-0.027027</td>\n",
              "      <td>-0.012769</td>\n",
              "      <td>-0.013976</td>\n",
              "      <td>-0.007070</td>\n",
              "      <td>-0.024755</td>\n",
              "      <td>-0.007509</td>\n",
              "      <td>0.082740</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.152570</td>\n",
              "      <td>-0.027261</td>\n",
              "      <td>-0.018251</td>\n",
              "      <td>-0.001110</td>\n",
              "      <td>0.005941</td>\n",
              "      <td>-0.065974</td>\n",
              "      <td>-0.018540</td>\n",
              "      <td>-0.048488</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>previous_bookings_not_canceled</th>\n",
              "      <td>-0.057365</td>\n",
              "      <td>-0.073599</td>\n",
              "      <td>0.029234</td>\n",
              "      <td>-0.021009</td>\n",
              "      <td>-0.000306</td>\n",
              "      <td>-0.042859</td>\n",
              "      <td>-0.048873</td>\n",
              "      <td>-0.108856</td>\n",
              "      <td>-0.021078</td>\n",
              "      <td>-0.006552</td>\n",
              "      <td>0.420642</td>\n",
              "      <td>0.152570</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.011963</td>\n",
              "      <td>-0.046348</td>\n",
              "      <td>0.111220</td>\n",
              "      <td>-0.009416</td>\n",
              "      <td>-0.072335</td>\n",
              "      <td>0.047506</td>\n",
              "      <td>0.037775</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>booking_changes</th>\n",
              "      <td>-0.144832</td>\n",
              "      <td>0.002230</td>\n",
              "      <td>0.031416</td>\n",
              "      <td>0.006311</td>\n",
              "      <td>0.011266</td>\n",
              "      <td>0.050191</td>\n",
              "      <td>0.080018</td>\n",
              "      <td>-0.041472</td>\n",
              "      <td>0.051000</td>\n",
              "      <td>0.085605</td>\n",
              "      <td>0.013044</td>\n",
              "      <td>-0.027261</td>\n",
              "      <td>0.011963</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.038555</td>\n",
              "      <td>0.089768</td>\n",
              "      <td>-0.011916</td>\n",
              "      <td>0.026601</td>\n",
              "      <td>0.067490</td>\n",
              "      <td>0.055003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>agent</th>\n",
              "      <td>-0.046770</td>\n",
              "      <td>-0.013114</td>\n",
              "      <td>0.056438</td>\n",
              "      <td>-0.018225</td>\n",
              "      <td>0.000159</td>\n",
              "      <td>0.162411</td>\n",
              "      <td>0.196777</td>\n",
              "      <td>0.023370</td>\n",
              "      <td>0.050461</td>\n",
              "      <td>0.030235</td>\n",
              "      <td>-0.051584</td>\n",
              "      <td>-0.018251</td>\n",
              "      <td>-0.046348</td>\n",
              "      <td>0.038555</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.121333</td>\n",
              "      <td>-0.041182</td>\n",
              "      <td>0.015711</td>\n",
              "      <td>0.119282</td>\n",
              "      <td>0.060783</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>company</th>\n",
              "      <td>-0.083594</td>\n",
              "      <td>-0.085854</td>\n",
              "      <td>0.033682</td>\n",
              "      <td>-0.032912</td>\n",
              "      <td>0.003667</td>\n",
              "      <td>-0.080783</td>\n",
              "      <td>-0.044437</td>\n",
              "      <td>-0.166182</td>\n",
              "      <td>-0.042554</td>\n",
              "      <td>-0.009426</td>\n",
              "      <td>0.161871</td>\n",
              "      <td>-0.001110</td>\n",
              "      <td>0.111220</td>\n",
              "      <td>0.089768</td>\n",
              "      <td>-0.121333</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.022944</td>\n",
              "      <td>-0.127641</td>\n",
              "      <td>0.038638</td>\n",
              "      <td>-0.090790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>days_in_waiting_list</th>\n",
              "      <td>0.054301</td>\n",
              "      <td>0.170008</td>\n",
              "      <td>-0.056348</td>\n",
              "      <td>0.022677</td>\n",
              "      <td>0.022532</td>\n",
              "      <td>-0.054399</td>\n",
              "      <td>-0.002026</td>\n",
              "      <td>-0.008365</td>\n",
              "      <td>-0.033293</td>\n",
              "      <td>-0.010627</td>\n",
              "      <td>-0.022057</td>\n",
              "      <td>0.005941</td>\n",
              "      <td>-0.009416</td>\n",
              "      <td>-0.011916</td>\n",
              "      <td>-0.041182</td>\n",
              "      <td>-0.022944</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.040859</td>\n",
              "      <td>-0.030601</td>\n",
              "      <td>-0.082755</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>adr</th>\n",
              "      <td>0.046492</td>\n",
              "      <td>-0.065018</td>\n",
              "      <td>0.198429</td>\n",
              "      <td>0.076281</td>\n",
              "      <td>0.030291</td>\n",
              "      <td>0.050670</td>\n",
              "      <td>0.066847</td>\n",
              "      <td>0.224253</td>\n",
              "      <td>0.325057</td>\n",
              "      <td>0.029043</td>\n",
              "      <td>-0.130807</td>\n",
              "      <td>-0.065974</td>\n",
              "      <td>-0.072335</td>\n",
              "      <td>0.026601</td>\n",
              "      <td>0.015711</td>\n",
              "      <td>-0.127641</td>\n",
              "      <td>-0.040859</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.056510</td>\n",
              "      <td>0.172308</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>required_car_parking_spaces</th>\n",
              "      <td>-0.195701</td>\n",
              "      <td>-0.116624</td>\n",
              "      <td>-0.013812</td>\n",
              "      <td>0.001980</td>\n",
              "      <td>0.008569</td>\n",
              "      <td>-0.018520</td>\n",
              "      <td>-0.024933</td>\n",
              "      <td>0.014438</td>\n",
              "      <td>0.056247</td>\n",
              "      <td>0.037389</td>\n",
              "      <td>0.077928</td>\n",
              "      <td>-0.018540</td>\n",
              "      <td>0.047506</td>\n",
              "      <td>0.067490</td>\n",
              "      <td>0.119282</td>\n",
              "      <td>0.038638</td>\n",
              "      <td>-0.030601</td>\n",
              "      <td>0.056510</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.082718</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>total_of_special_requests</th>\n",
              "      <td>-0.234877</td>\n",
              "      <td>-0.095949</td>\n",
              "      <td>0.108610</td>\n",
              "      <td>0.026202</td>\n",
              "      <td>0.003026</td>\n",
              "      <td>0.073124</td>\n",
              "      <td>0.068738</td>\n",
              "      <td>0.123353</td>\n",
              "      <td>0.081747</td>\n",
              "      <td>0.097939</td>\n",
              "      <td>0.012963</td>\n",
              "      <td>-0.048488</td>\n",
              "      <td>0.037775</td>\n",
              "      <td>0.055003</td>\n",
              "      <td>0.060783</td>\n",
              "      <td>-0.090790</td>\n",
              "      <td>-0.082755</td>\n",
              "      <td>0.172308</td>\n",
              "      <td>0.082718</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                is_canceled  ...  total_of_special_requests\n",
              "is_canceled                        1.000000  ...                  -0.234877\n",
              "lead_time                          0.292876  ...                  -0.095949\n",
              "arrival_date_year                  0.016622  ...                   0.108610\n",
              "arrival_date_week_number           0.008315  ...                   0.026202\n",
              "arrival_date_day_of_month         -0.005948  ...                   0.003026\n",
              "stays_in_weekend_nights           -0.001323  ...                   0.073124\n",
              "stays_in_week_nights               0.025542  ...                   0.068738\n",
              "adults                             0.058182  ...                   0.123353\n",
              "children                           0.004851  ...                   0.081747\n",
              "babies                            -0.032569  ...                   0.097939\n",
              "is_repeated_guest                 -0.083745  ...                   0.012963\n",
              "previous_cancellations             0.110139  ...                  -0.048488\n",
              "previous_bookings_not_canceled    -0.057365  ...                   0.037775\n",
              "booking_changes                   -0.144832  ...                   0.055003\n",
              "agent                             -0.046770  ...                   0.060783\n",
              "company                           -0.083594  ...                  -0.090790\n",
              "days_in_waiting_list               0.054301  ...                  -0.082755\n",
              "adr                                0.046492  ...                   0.172308\n",
              "required_car_parking_spaces       -0.195701  ...                   0.082718\n",
              "total_of_special_requests         -0.234877  ...                   1.000000\n",
              "\n",
              "[20 rows x 20 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lxOJMaOKZSEU",
        "outputId": "6a70ba02-0276-4ea2-db09-a93a38a08236"
      },
      "source": [
        "# We want only the data related to the cancelation\n",
        "co_relation = data.corr()['is_canceled']\n",
        "co_relation"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "is_canceled                       1.000000\n",
              "lead_time                         0.292876\n",
              "arrival_date_year                 0.016622\n",
              "arrival_date_week_number          0.008315\n",
              "arrival_date_day_of_month        -0.005948\n",
              "stays_in_weekend_nights          -0.001323\n",
              "stays_in_week_nights              0.025542\n",
              "adults                            0.058182\n",
              "children                          0.004851\n",
              "babies                           -0.032569\n",
              "is_repeated_guest                -0.083745\n",
              "previous_cancellations            0.110139\n",
              "previous_bookings_not_canceled   -0.057365\n",
              "booking_changes                  -0.144832\n",
              "agent                            -0.046770\n",
              "company                          -0.083594\n",
              "days_in_waiting_list              0.054301\n",
              "adr                               0.046492\n",
              "required_car_parking_spaces      -0.195701\n",
              "total_of_special_requests        -0.234877\n",
              "Name: is_canceled, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8E0Y9bA-Zp8l"
      },
      "source": [
        "Based on this matrix, we can understand how each variable can impact the cancelation. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wyPMvD6GaBj2",
        "outputId": "56aeea15-5dae-4b25-d190-bdb1fd3d4387"
      },
      "source": [
        "co_relation.abs().sort_values(ascending=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "is_canceled                       1.000000\n",
              "lead_time                         0.292876\n",
              "total_of_special_requests         0.234877\n",
              "required_car_parking_spaces       0.195701\n",
              "booking_changes                   0.144832\n",
              "previous_cancellations            0.110139\n",
              "is_repeated_guest                 0.083745\n",
              "company                           0.083594\n",
              "adults                            0.058182\n",
              "previous_bookings_not_canceled    0.057365\n",
              "days_in_waiting_list              0.054301\n",
              "agent                             0.046770\n",
              "adr                               0.046492\n",
              "babies                            0.032569\n",
              "stays_in_week_nights              0.025542\n",
              "arrival_date_year                 0.016622\n",
              "arrival_date_week_number          0.008315\n",
              "arrival_date_day_of_month         0.005948\n",
              "children                          0.004851\n",
              "stays_in_weekend_nights           0.001323\n",
              "Name: is_canceled, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Yz4g80QeaJps"
      },
      "source": [
        "From this matrix, we can say that lead_time, total_of_special_requests, required_car_parking_spaces are the most criteria that impact cancelation. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L40n44lqachx",
        "outputId": "f747b5f3-2be3-47be-c53b-48b5bc2e0c84"
      },
      "source": [
        "# Group data with the basis of 'is_canceled', reservation_status\n",
        "data.groupby('is_canceled')['reservation_status'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "is_canceled  reservation_status\n",
              "0            Check-Out             75011\n",
              "1            Canceled              42993\n",
              "             No-Show                1206\n",
              "Name: reservation_status, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6R1cAusDef8G"
      },
      "source": [
        "We can go further and exclude some of the feature that are not relevent for the analysis."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ve-z0afwfaxI",
        "outputId": "3805582b-a1cb-4cc6-e1a1-ca5835346ba7"
      },
      "source": [
        "list_not = ['days_in_waiting_list', 'arrival_date_year']\n",
        "num_features=[col for col in data.columns if data[col].dtype!='O' and col not in list_not]\n",
        "num_features"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['is_canceled',\n",
              " 'lead_time',\n",
              " 'arrival_date_week_number',\n",
              " 'arrival_date_day_of_month',\n",
              " 'stays_in_weekend_nights',\n",
              " 'stays_in_week_nights',\n",
              " 'adults',\n",
              " 'children',\n",
              " 'babies',\n",
              " 'is_repeated_guest',\n",
              " 'previous_cancellations',\n",
              " 'previous_bookings_not_canceled',\n",
              " 'booking_changes',\n",
              " 'agent',\n",
              " 'company',\n",
              " 'adr',\n",
              " 'required_car_parking_spaces',\n",
              " 'total_of_special_requests']"
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "udB5gxlwfrtP",
        "outputId": "77e3f57a-b183-41ce-8416-0b1f680bdd18"
      },
      "source": [
        "# Same code as above in a different manner\n",
        "cols = []\n",
        "for col in data.columns:\n",
        "  if data[col].dtype!='O' and col not in list_not:\n",
        "    cols.append(col)\n",
        "cols"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['is_canceled',\n",
              " 'lead_time',\n",
              " 'arrival_date_week_number',\n",
              " 'arrival_date_day_of_month',\n",
              " 'stays_in_weekend_nights',\n",
              " 'stays_in_week_nights',\n",
              " 'adults',\n",
              " 'children',\n",
              " 'babies',\n",
              " 'is_repeated_guest',\n",
              " 'previous_cancellations',\n",
              " 'previous_bookings_not_canceled',\n",
              " 'booking_changes',\n",
              " 'agent',\n",
              " 'company',\n",
              " 'adr',\n",
              " 'required_car_parking_spaces',\n",
              " 'total_of_special_requests']"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SpjnSk2aiWIR",
        "outputId": "537b5c50-d576-4de5-b294-424f079cc4d5"
      },
      "source": [
        "data.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['hotel', 'is_canceled', 'lead_time', 'arrival_date_year',\n",
              "       'arrival_date_month', 'arrival_date_week_number',\n",
              "       'arrival_date_day_of_month', 'stays_in_weekend_nights',\n",
              "       'stays_in_week_nights', 'adults', 'children', 'babies', 'meal',\n",
              "       'country', 'market_segment', 'distribution_channel',\n",
              "       'is_repeated_guest', 'previous_cancellations',\n",
              "       'previous_bookings_not_canceled', 'reserved_room_type',\n",
              "       'assigned_room_type', 'booking_changes', 'deposit_type', 'agent',\n",
              "       'company', 'days_in_waiting_list', 'customer_type', 'adr',\n",
              "       'required_car_parking_spaces', 'total_of_special_requests',\n",
              "       'reservation_status', 'reservation_status_date'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ImclUWp9DnC4",
        "outputId": "adff6d44-d360-4656-b1de-13a6ee41e271"
      },
      "source": [
        "# exclude some irrelevent columns\n",
        "cat_not=[ 'arrival_date_year', 'assigned_room_type', 'booking_changes', 'reservation_status', 'country', 'days_in_waiting_list']\n",
        "cat_not"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['arrival_date_year',\n",
              " 'assigned_room_type',\n",
              " 'booking_changes',\n",
              " 'reservation_status',\n",
              " 'country',\n",
              " 'days_in_waiting_list']"
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0XxYNeY8EOaP",
        "outputId": "c97190f1-5b9b-4bac-864e-8506866b0559"
      },
      "source": [
        "cat_features = [col for col in data.columns if data[col].dtype=='O' and col not in cat_not]\n",
        "cat_features\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['hotel',\n",
              " 'arrival_date_month',\n",
              " 'meal',\n",
              " 'market_segment',\n",
              " 'distribution_channel',\n",
              " 'reserved_room_type',\n",
              " 'deposit_type',\n",
              " 'customer_type',\n",
              " 'reservation_status_date']"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lZDxUyKtEeir"
      },
      "source": [
        " "
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}