Nikunj_Sonule_(Group)_Hotel_Booking_Analysis_Capstone_Project.ipynb

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      "name": "Nikunj Sonule (Group) -Hotel Booking Analysis - Capstone Project.ipynb",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/nikunjsonule/hotel-booking-analysis/blob/main/Nikunj_Sonule_(Group)_Hotel_Booking_Analysis_Capstone_Project.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y06xIdG26kRF"
      },
      "source": [
        "## <b> Have you ever wondered when the best time of year to book a hotel room is? Or the optimal length of stay in order to get the best daily rate? What if you wanted to predict whether or not a hotel was likely to receive a disproportionately high number of special requests? This hotel booking dataset can help you explore those questions!\n",
        "\n",
        "## <b>This data set contains booking information for a city hotel and a resort hotel, and includes information such as when the booking was made, length of stay, the number of adults, children, and/or babies, and the number of available parking spaces, among other things. All personally identifying information has been removed from the data. </b>\n",
        "\n",
        "## <b> Explore and analyze the data to discover important factors that govern the bookings. </b>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gkZMk1FK0KlQ"
      },
      "source": [
        "# Context"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z4hSiL5A0OW-"
      },
      "source": [
        "Have you ever wondered when the best time of year to book a hotel room is? Or the optimal length of stay in order to get the best daily rate? What if you wanted to predict whether or not a hotel was likely to receive a disproportionately high number of special requests?\n",
        "\n",
        "This hotel booking dataset can help you explore those questions!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iQOvvyvr0TWq"
      },
      "source": [
        "# Content"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3Ay4gMMY0Wny"
      },
      "source": [
        "This data set contains booking information for a city hotel and a resort hotel, and includes information such as when the booking was made, length of stay, the number of adults, children, and/or babies, and the number of available parking spaces, among other things.\n",
        "\n",
        "All personally identifying information has been removed from the data."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TLMiINkP2eIJ"
      },
      "source": [
        " **Why Hotel booking analysis is important ?**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PH7uw6Hz2xup"
      },
      "source": [
        "Hotel data analytics refers to qualitative and quantitative processes and techniques used to enhance productivity, marketing strategies, occupancy rates, and yield. The hotel data is first extracted and then categorized to identify and analyze behavioral data and patterns. The techniques used can vary depending on the business requirements.\n",
        "Analyzing booking patterns shows the demand trends which you can use to implement dynamic pricing.\n",
        "\n",
        "Data is of two types: big and small, and both of these can be structured and unstructured. So, how do you use data to make better decisions for your hotel? The answer is hotel data analytics.\n",
        "Data analytics opens doors to limitless opportunities. In this dynamically evolving hotel industry, data analytics is a powerful technology that can help hotel owners make relevant business decisions. \n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BMzSkfyM0hGA"
      },
      "source": [
        "# We will analysis some problem statement realted to customer hotel bookings \n",
        "\n",
        "We have divide the analysis part in four parts for easy understanding -\n",
        "\n",
        "*   Booking analysis based on datasets available\n",
        "*   Cancellation analysis\n",
        "*   General analysis \n",
        "*   Analysis to understand for betterment of business perspective\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AjUgB853wisJ"
      },
      "source": [
        "# Firstly.....what we can do to understand"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WaKwvWMewv6U"
      },
      "source": [
        "To understand the problem and analysis it we have to look firstly to dataset. Dataset shows how data is been represent in column and rows, so whenever we create variable we can use those column and data for analysis."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P76Nbsm_XSRK"
      },
      "source": [
        "# The first step in EDA process is Data Preprocessing and Cleaning\n",
        "\n",
        "**Import Packages**\n",
        "\n",
        "First Import necessary packages and import the dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oIyOZguaa0W-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6c5524af-345c-43f5-80ca-ef145d9a7636"
      },
      "source": [
        "!pip install pycountry\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "import seaborn as sns\n",
        "import pycountry as pc\n",
        "import matplotlib.ticker as mtick\n",
        "import plotly.express as px\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pycountry\n",
            "  Downloading pycountry-20.7.3.tar.gz (10.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 10.1 MB 5.5 MB/s \n",
            "\u001b[?25hBuilding wheels for collected packages: pycountry\n",
            "  Building wheel for pycountry (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pycountry: filename=pycountry-20.7.3-py2.py3-none-any.whl size=10746883 sha256=3df240c464f642c2f603a4c610a8d152849200a4953051288b2ca8a28f443028\n",
            "  Stored in directory: /root/.cache/pip/wheels/57/e8/3f/120ccc1ff7541c108bc5d656e2a14c39da0d824653b62284c6\n",
            "Successfully built pycountry\n",
            "Installing collected packages: pycountry\n",
            "Successfully installed pycountry-20.7.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KREN0PjubC7Z"
      },
      "source": [
        "Now importing and display the dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GNTxkfU3bXNO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a6e5b68d-9a01-45e9-99b3-4ae3998fa4de"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SATt0AJjbkT8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "491b0717-06e6-4c7d-dd9f-e457aca33a83"
      },
      "source": [
        "#importing data and show first 5 rows\n",
        "data = pd.read_csv(\"/content/drive/MyDrive/Colab Notebooks/All project/EDA/Hotel Booking Analysis/Hotel Bookings.csv\")\n",
        "data.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "<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>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>737</td>\n",
              "      <td>2015</td>\n",
              "      <td>July</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>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>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>2015</td>\n",
              "      <td>July</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>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>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>2015</td>\n",
              "      <td>July</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>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>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>14</td>\n",
              "      <td>2015</td>\n",
              "      <td>July</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>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>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>98.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-03</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          hotel  is_canceled  ...  reservation_status  reservation_status_date\n",
              "0  Resort Hotel            0  ...           Check-Out               2015-07-01\n",
              "1  Resort Hotel            0  ...           Check-Out               2015-07-01\n",
              "2  Resort Hotel            0  ...           Check-Out               2015-07-02\n",
              "3  Resort Hotel            0  ...           Check-Out               2015-07-02\n",
              "4  Resort Hotel            0  ...           Check-Out               2015-07-03\n",
              "\n",
              "[5 rows x 32 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iT2ItpOtc3_s",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "11939fbe-3ec6-4b80-ef9d-e2c73fa3d0fa"
      },
      "source": [
        "# Columns in the datasets\n",
        "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": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LgtZNUgioBBQ"
      },
      "source": [
        "\n",
        "First copy the dataset, so our original dataset remains unchanged"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IFyGs782oCiS"
      },
      "source": [
        "# Using this data frame for all analysis\n",
        "hotel_data_copy= data.copy()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BDlF0IM9ocnM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "8840d496-742d-4954-80e0-a8bcfc74321d"
      },
      "source": [
        "hotel_data_copy.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "    }\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>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>737</td>\n",
              "      <td>2015</td>\n",
              "      <td>July</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>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>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>2015</td>\n",
              "      <td>July</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>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>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>2015</td>\n",
              "      <td>July</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>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>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>0</td>\n",
              "      <td>14</td>\n",
              "      <td>2015</td>\n",
              "      <td>July</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>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>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>98.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-03</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          hotel  is_canceled  ...  reservation_status  reservation_status_date\n",
              "0  Resort Hotel            0  ...           Check-Out               2015-07-01\n",
              "1  Resort Hotel            0  ...           Check-Out               2015-07-01\n",
              "2  Resort Hotel            0  ...           Check-Out               2015-07-02\n",
              "3  Resort Hotel            0  ...           Check-Out               2015-07-02\n",
              "4  Resort Hotel            0  ...           Check-Out               2015-07-03\n",
              "\n",
              "[5 rows x 32 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "A-I3gpU7oqQf"
      },
      "source": [
        "**Finding  number of null and missing values**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o_LpZ8oao3X6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "31f3c40e-6f7c-4e20-de8b-7b3117aaa4af"
      },
      "source": [
        "#Find out the data type of each column \n",
        "hotel_data_copy.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 119390 entries, 0 to 119389\n",
            "Data columns (total 32 columns):\n",
            " #   Column                          Non-Null Count   Dtype  \n",
            "---  ------                          --------------   -----  \n",
            " 0   hotel                           119390 non-null  object \n",
            " 1   is_canceled                     119390 non-null  int64  \n",
            " 2   lead_time                       119390 non-null  int64  \n",
            " 3   arrival_date_year               119390 non-null  int64  \n",
            " 4   arrival_date_month              119390 non-null  object \n",
            " 5   arrival_date_week_number        119390 non-null  int64  \n",
            " 6   arrival_date_day_of_month       119390 non-null  int64  \n",
            " 7   stays_in_weekend_nights         119390 non-null  int64  \n",
            " 8   stays_in_week_nights            119390 non-null  int64  \n",
            " 9   adults                          119390 non-null  int64  \n",
            " 10  children                        119386 non-null  float64\n",
            " 11  babies                          119390 non-null  int64  \n",
            " 12  meal                            119390 non-null  object \n",
            " 13  country                         118902 non-null  object \n",
            " 14  market_segment                  119390 non-null  object \n",
            " 15  distribution_channel            119390 non-null  object \n",
            " 16  is_repeated_guest               119390 non-null  int64  \n",
            " 17  previous_cancellations          119390 non-null  int64  \n",
            " 18  previous_bookings_not_canceled  119390 non-null  int64  \n",
            " 19  reserved_room_type              119390 non-null  object \n",
            " 20  assigned_room_type              119390 non-null  object \n",
            " 21  booking_changes                 119390 non-null  int64  \n",
            " 22  deposit_type                    119390 non-null  object \n",
            " 23  agent                           103050 non-null  float64\n",
            " 24  company                         6797 non-null    float64\n",
            " 25  days_in_waiting_list            119390 non-null  int64  \n",
            " 26  customer_type                   119390 non-null  object \n",
            " 27  adr                             119390 non-null  float64\n",
            " 28  required_car_parking_spaces     119390 non-null  int64  \n",
            " 29  total_of_special_requests       119390 non-null  int64  \n",
            " 30  reservation_status              119390 non-null  object \n",
            " 31  reservation_status_date         119390 non-null  object \n",
            "dtypes: float64(4), int64(16), object(12)\n",
            "memory usage: 29.1+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TWUztZFrsH4q",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2353902f-2591-4053-89c9-56b14dc8b162"
      },
      "source": [
        "hotel_data_copy.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(119390, 32)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r15Xv7TXsK5h"
      },
      "source": [
        "# droping unwanted columns \n",
        "hotel_data_copy.drop(['company','agent'], axis = 1,inplace = True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CueDmebtsXan",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "525dda6b-d5e0-4c8c-c20c-1de45c26bc5f"
      },
      "source": [
        "hotel_data_copy.info()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 119390 entries, 0 to 119389\n",
            "Data columns (total 30 columns):\n",
            " #   Column                          Non-Null Count   Dtype  \n",
            "---  ------                          --------------   -----  \n",
            " 0   hotel                           119390 non-null  object \n",
            " 1   is_canceled                     119390 non-null  int64  \n",
            " 2   lead_time                       119390 non-null  int64  \n",
            " 3   arrival_date_year               119390 non-null  int64  \n",
            " 4   arrival_date_month              119390 non-null  object \n",
            " 5   arrival_date_week_number        119390 non-null  int64  \n",
            " 6   arrival_date_day_of_month       119390 non-null  int64  \n",
            " 7   stays_in_weekend_nights         119390 non-null  int64  \n",
            " 8   stays_in_week_nights            119390 non-null  int64  \n",
            " 9   adults                          119390 non-null  int64  \n",
            " 10  children                        119386 non-null  float64\n",
            " 11  babies                          119390 non-null  int64  \n",
            " 12  meal                            119390 non-null  object \n",
            " 13  country                         118902 non-null  object \n",
            " 14  market_segment                  119390 non-null  object \n",
            " 15  distribution_channel            119390 non-null  object \n",
            " 16  is_repeated_guest               119390 non-null  int64  \n",
            " 17  previous_cancellations          119390 non-null  int64  \n",
            " 18  previous_bookings_not_canceled  119390 non-null  int64  \n",
            " 19  reserved_room_type              119390 non-null  object \n",
            " 20  assigned_room_type              119390 non-null  object \n",
            " 21  booking_changes                 119390 non-null  int64  \n",
            " 22  deposit_type                    119390 non-null  object \n",
            " 23  days_in_waiting_list            119390 non-null  int64  \n",
            " 24  customer_type                   119390 non-null  object \n",
            " 25  adr                             119390 non-null  float64\n",
            " 26  required_car_parking_spaces     119390 non-null  int64  \n",
            " 27  total_of_special_requests       119390 non-null  int64  \n",
            " 28  reservation_status              119390 non-null  object \n",
            " 29  reservation_status_date         119390 non-null  object \n",
            "dtypes: float64(2), int64(16), object(12)\n",
            "memory usage: 27.3+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OhkH0Ty8sg_8"
      },
      "source": [
        "**Creating childs column from babies and children**\n",
        "\n",
        "We can look after problem statement of adults and childs for analysis. So, we are adding new column named childs i.e merging both babies and children column."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e4qCjWVWsokg"
      },
      "source": [
        "hotel_data_copy['childs'] = hotel_data_copy['babies'] + hotel_data_copy['children']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tCC1-SkHszkL",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "de71d077-54da-4f1a-981c-3917d9e126c5"
      },
      "source": [
        "hotel_data_copy.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 119390 entries, 0 to 119389\n",
            "Data columns (total 31 columns):\n",
            " #   Column                          Non-Null Count   Dtype  \n",
            "---  ------                          --------------   -----  \n",
            " 0   hotel                           119390 non-null  object \n",
            " 1   is_canceled                     119390 non-null  int64  \n",
            " 2   lead_time                       119390 non-null  int64  \n",
            " 3   arrival_date_year               119390 non-null  int64  \n",
            " 4   arrival_date_month              119390 non-null  object \n",
            " 5   arrival_date_week_number        119390 non-null  int64  \n",
            " 6   arrival_date_day_of_month       119390 non-null  int64  \n",
            " 7   stays_in_weekend_nights         119390 non-null  int64  \n",
            " 8   stays_in_week_nights            119390 non-null  int64  \n",
            " 9   adults                          119390 non-null  int64  \n",
            " 10  children                        119386 non-null  float64\n",
            " 11  babies                          119390 non-null  int64  \n",
            " 12  meal                            119390 non-null  object \n",
            " 13  country                         118902 non-null  object \n",
            " 14  market_segment                  119390 non-null  object \n",
            " 15  distribution_channel            119390 non-null  object \n",
            " 16  is_repeated_guest               119390 non-null  int64  \n",
            " 17  previous_cancellations          119390 non-null  int64  \n",
            " 18  previous_bookings_not_canceled  119390 non-null  int64  \n",
            " 19  reserved_room_type              119390 non-null  object \n",
            " 20  assigned_room_type              119390 non-null  object \n",
            " 21  booking_changes                 119390 non-null  int64  \n",
            " 22  deposit_type                    119390 non-null  object \n",
            " 23  days_in_waiting_list            119390 non-null  int64  \n",
            " 24  customer_type                   119390 non-null  object \n",
            " 25  adr                             119390 non-null  float64\n",
            " 26  required_car_parking_spaces     119390 non-null  int64  \n",
            " 27  total_of_special_requests       119390 non-null  int64  \n",
            " 28  reservation_status              119390 non-null  object \n",
            " 29  reservation_status_date         119390 non-null  object \n",
            " 30  childs                          119386 non-null  float64\n",
            "dtypes: float64(3), int64(16), object(12)\n",
            "memory usage: 28.2+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mr9GpFbQ2CRs"
      },
      "source": [
        "In the real world, data is never 100% percent perfect, 100% accurate, and 100% complete. By nature, data is full of errors: omissions, inconsistencies, and duplicates.\n",
        "That’s why understanding the data quality process is important for many businesses trying to sort out their data."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1ZKrVvoJs4Ww"
      },
      "source": [
        "# Droping babies and children column as for further analysis we have taken childs column\n",
        "# droping unwanted columns \n",
        "hotel_data_copy.drop(['babies','children'], axis = 1,inplace = True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LGcTKd68uuqZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "565d5d00-95c8-4408-8049-72bed975b334"
      },
      "source": [
        "hotel_data_copy.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 119390 entries, 0 to 119389\n",
            "Data columns (total 29 columns):\n",
            " #   Column                          Non-Null Count   Dtype  \n",
            "---  ------                          --------------   -----  \n",
            " 0   hotel                           119390 non-null  object \n",
            " 1   is_canceled                     119390 non-null  int64  \n",
            " 2   lead_time                       119390 non-null  int64  \n",
            " 3   arrival_date_year               119390 non-null  int64  \n",
            " 4   arrival_date_month              119390 non-null  object \n",
            " 5   arrival_date_week_number        119390 non-null  int64  \n",
            " 6   arrival_date_day_of_month       119390 non-null  int64  \n",
            " 7   stays_in_weekend_nights         119390 non-null  int64  \n",
            " 8   stays_in_week_nights            119390 non-null  int64  \n",
            " 9   adults                          119390 non-null  int64  \n",
            " 10  meal                            119390 non-null  object \n",
            " 11  country                         118902 non-null  object \n",
            " 12  market_segment                  119390 non-null  object \n",
            " 13  distribution_channel            119390 non-null  object \n",
            " 14  is_repeated_guest               119390 non-null  int64  \n",
            " 15  previous_cancellations          119390 non-null  int64  \n",
            " 16  previous_bookings_not_canceled  119390 non-null  int64  \n",
            " 17  reserved_room_type              119390 non-null  object \n",
            " 18  assigned_room_type              119390 non-null  object \n",
            " 19  booking_changes                 119390 non-null  int64  \n",
            " 20  deposit_type                    119390 non-null  object \n",
            " 21  days_in_waiting_list            119390 non-null  int64  \n",
            " 22  customer_type                   119390 non-null  object \n",
            " 23  adr                             119390 non-null  float64\n",
            " 24  required_car_parking_spaces     119390 non-null  int64  \n",
            " 25  total_of_special_requests       119390 non-null  int64  \n",
            " 26  reservation_status              119390 non-null  object \n",
            " 27  reservation_status_date         119390 non-null  object \n",
            " 28  childs                          119386 non-null  float64\n",
            "dtypes: float64(2), int64(15), object(12)\n",
            "memory usage: 26.4+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "adSxnJR7vCTv"
      },
      "source": [
        "Now dataset contains 119390 columns and 29 rows"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ixgfLGd5u3eV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9a03505e-a37c-4ff2-97df-a43f2ad51be4"
      },
      "source": [
        "hotel_data_copy.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(119390, 29)"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zQALsPRWvPu7"
      },
      "source": [
        "Droping Duplicates from data set"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zqo3bkXZvUP4"
      },
      "source": [
        "# drop duplicate values in data frame\n",
        "hotel_data_copy = hotel_data_copy.drop_duplicates()\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v-fpVycBv-fp",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "90897d49-fdf7-43b0-c679-94b7e41676c9"
      },
      "source": [
        "hotel_data_copy.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(87369, 29)"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V1Iz_idzwFD6"
      },
      "source": [
        "Now we can find the missing values"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bNqW4llXwMdw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "962e874b-71f4-4e97-ef5b-5ad261b8e543"
      },
      "source": [
        "#check null values in Data frame\n",
        "hotel_data_copy.isnull().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",
              "meal                                0\n",
              "country                           452\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",
              "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",
              "childs                              4\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bl4tEWBwwbcI"
      },
      "source": [
        "# Droping null values from the dataset\n",
        "hotel_data_copy.dropna(inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uKM_nwRewn5i",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "279fda5f-b399-42e8-fc56-3571dbaed97c"
      },
      "source": [
        "# So after cleaning our datasets we have 86913 columns and 29 rows\n",
        "hotel_data_copy.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(86913, 29)"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SXlcMZiCxI2g"
      },
      "source": [
        "After cleaning the datasets we have following columns for analysis"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uyT2pE3JxUGt",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fe66b300-afe5-4e1e-fa96-21c824a3cc0a"
      },
      "source": [
        "hotel_data_copy.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', 'meal', 'country', 'market_segment',\n",
              "       'distribution_channel', 'is_repeated_guest', 'previous_cancellations',\n",
              "       'previous_bookings_not_canceled', 'reserved_room_type',\n",
              "       'assigned_room_type', 'booking_changes', 'deposit_type',\n",
              "       'days_in_waiting_list', 'customer_type', 'adr',\n",
              "       'required_car_parking_spaces', 'total_of_special_requests',\n",
              "       'reservation_status', 'reservation_status_date', 'childs'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zTEO5oIc2f0c"
      },
      "source": [
        "# Analysis based on bookings "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oBgaeqmI2SUS"
      },
      "source": [
        "**Analysis no. 1**\n",
        "\n",
        "How many total bookings were made by both the resort and city hotels ?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KYwmk4alxrPj",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 443
        },
        "outputId": "ae619ecf-8be1-42dd-c57b-e82098236503"
      },
      "source": [
        "fig, ax = plt.subplots(figsize = (12,5))\n",
        "sns.countplot(hotel_data_copy['hotel'])\n",
        "plt.title(' Hotels booked', weight='bold', size = 20)\n",
        "plt.xlabel('Hotel', size = 10)\n",
        "plt.ylabel('Reservation count', size = 10)\n",
        "\n",
        "for p in ax.patches:\n",
        "    height = p.get_height()\n",
        "    ax.text(p.get_x()+p.get_width()/2, height+500, '{:1.2f}''%'.format(height/hotel_data_copy.shape[0]*100),ha = \"center\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning:\n",
            "\n",
            "Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ebn_hL5DAn2i"
      },
      "source": [
        "The above bar chart shows that their are 61.44% and 38.56%, City Hotel and Resort Hotel are booked respectively. The reservation count of City Hotel is more as compared to Resort Hotel."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vTHHbGIMyneu"
      },
      "source": [
        "**Analysis no.2**\n",
        "\n",
        "Analysis based on year wise bookings takes place"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UjC5npCIzvvW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 463
        },
        "outputId": "a1a866cf-9c14-4244-ae9b-291668dc60ff"
      },
      "source": [
        "fig, ax = plt.subplots(figsize = (12,7))\n",
        "sns.countplot(x=hotel_data_copy['arrival_date_year'], palette = 'rocket_r')\n",
        "plt.title('Year wise Booking count', weight='bold',size = 20)\n",
        "plt.xlabel('Year',size = 10)\n",
        "plt.ylabel('Reservation Count',size = 10)\n",
        "for p in ax.patches:\n",
        "    height = p.get_height()\n",
        "    ax.text(p.get_x()+p.get_width()/2, height+ 1000, '{:1.2f}''%'.format(height/hotel_data_copy.shape[0]*100),ha = \"center\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "klhVgCC60m_3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 429
        },
        "outputId": "8ce478aa-b6b2-4a19-eb9c-9d78cd581f4b"
      },
      "source": [
        "fig, ax = plt.subplots(figsize = (12,7))\n",
        "\n",
        "x = hotel_data_copy.groupby('arrival_date_year')['arrival_date_year'].count()\n",
        "y = x.index.get_level_values(0)\n",
        "explode = (0, 0.05, 0)\n",
        "plt.title('Year wise Booking count', weight='bold',size = 15)\n",
        "\n",
        "plt.pie(x, labels=y, explode = explode, autopct='%1.0f%%',shadow=True, startangle=90, textprops={'fontsize': 13})\n",
        "plt.axis('equal')\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x504 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_cyQgdFzCyeP"
      },
      "source": [
        "In year wise booking 2016 is booked mostly by the customer with 48%, followed by 2017 with 36% and 2015 with 15%."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "10riVuVV1PCS"
      },
      "source": [
        "**Analysis no.3**\n",
        "\n",
        "Which are the categories of room booked by customer ?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZURSJL4r1gSK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        },
        "outputId": "b952a121-1915-424b-92c3-878697a7a194"
      },
      "source": [
        "fig, ax = plt.subplots(figsize = (12,7))\n",
        "\n",
        "\n",
        "x = hotel_data_copy.groupby('reserved_room_type')['reserved_room_type'].count().sort_values(ascending=False)\n",
        "y = x.index.get_level_values(0)\n",
        "\n",
        "sns.barplot(x = y, y=x, palette = 'colorblind')\n",
        "plt.title('Categories of room booked', weight='bold',size = 15)\n",
        "plt.xlabel('Room type reserved',size = 15)\n",
        "plt.ylabel('Reservation Count',size = 15)\n",
        "for p in ax.patches:\n",
        "    height = p.get_height()\n",
        "    ax.text(p.get_x()+p.get_width()/2, height+500, '{:1.2f}''%'.format(height/hotel_data_copy.shape[0]*100),ha = \"center\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ty_7dc_nFPsu"
      },
      "source": [
        "The most preferable reserved room type is category A with 64.62%, followed by room type category D with 19.99% and E with 6.91%. All other have minimum rate from 3.24% of F, G with 2.35%, B with 1.14%, C with 1.05%, H with 0.69% and L with 0.01%"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rBc-w0sF1uqo"
      },
      "source": [
        "**Analysis no.4**\n",
        "\n",
        "Through which market segment the customer have to wait more for confirming their booking ?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iUfzYQ5X1zOw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 405
        },
        "outputId": "4c40d11d-2868-4156-e874-536e771cf653"
      },
      "source": [
        "#This is a scatter plot for Market segment and days_in_waiting_list \n",
        "\n",
        "hotel_data_copy.plot.scatter(x='market_segment', y = 'days_in_waiting_list' , figsize = (10,6), title = 'Waiting time for Hotel booking with respect to market segment' , xlabel = 'Market segment', ylabel = 'Days in waiting list')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w2OO6VG3mmFp"
      },
      "source": [
        "The above plot is a scatter plot. Based on Market Segment we Observed that  waiting days for Groups are the highest and least for Aviation. Groups are the highest number of waiting days followed by Offline TA/TO of market segment with most number of waitings.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0AeeIBjV20Ec"
      },
      "source": [
        "# Analysis based on Cancellation"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GeDONkZL27DK"
      },
      "source": [
        "**Analysis no.5**\n",
        "\n",
        "Which were cancelled and non-cancelled bookings made by the customers ?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5S2qy-Tp3G-m",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        },
        "outputId": "9042d082-a0aa-4f05-f961-82d33ec3719c"
      },
      "source": [
        "fig, ax = plt.subplots(figsize = (12,7))\n",
        "\n",
        "x = hotel_data_copy.groupby('is_canceled')['is_canceled'].count()\n",
        "y = x.index.get_level_values(0)\n",
        "explode = (0, 0.05)\n",
        "plt.title('Cancellations', weight='bold', size = 15)\n",
        "labels = [r'0: Non-Cancelled', r'1: Cancelled']\n",
        "\n",
        "plt.pie(x, labels=y, explode = explode, autopct='%1.0f%%',shadow=True, startangle=90, textprops={'fontsize': 13})\n",
        "plt.axis('equal')\n",
        "plt.legend(labels, loc=\"best\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f177fc2aa50>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x504 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NKS0qb55rkBc"
      },
      "source": [
        "By Observing the above pie chart , we clearly get the conclusion that 28% of Booking were Cancelled ,and remaining 72% were Succesful (i.e Not- Cancelled). \n",
        "We have taken '0' for non-cancelled and '1' for cancellations."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UYzJOZxI329p",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 572
        },
        "outputId": "704ef8eb-0793-4983-cdc2-607ba4784b2e"
      },
      "source": [
        "fig, ax = plt.subplots(figsize = (12,7))\n",
        "sns.countplot(hotel_data_copy['is_canceled'], hue = hotel_data_copy['hotel'] )\n",
        "\n",
        "for p in ax.patches:\n",
        "    height = p.get_height()\n",
        "    ax.text(p.get_x()+p.get_width()/2, height+500, '{:1.2f}''%'.format(height/hotel_data_copy.shape[0]*100),ha = \"center\")  \n",
        "plt.title('Hotel-wise most cancellation', weight='bold', size = 15)\n",
        "\n",
        "plt.xlabel('Is_Cancelled', size = 15)\n",
        "plt.ylabel('Reservation Count', size = 15)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning:\n",
            "\n",
            "Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Reservation Count')"
            ]
          },
          "metadata": {},
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OUw8a8Qvs1ke"
      },
      "source": [
        "When we Observe the hotel wise cancellation , we find that Reservation Count of 42.99% of City Hotel were Cancelled, and 29.42% were cancelled for Resort Hotels.\n",
        "Also, there were no-cancellation of 9.14% and 18.45% of reservation count for City hotels and Resorts hotels.\n",
        "Here '0' is for non-cancellation and '1' is for cancellation.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YOaNlOIE_qUH"
      },
      "source": [
        "**Analysis no.6**\n",
        "\n",
        "Impact of lead time on cancellation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o4O-MvyW_x8t",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 538
        },
        "outputId": "45f6f5e3-cf72-42fe-fc8a-33b1a765c9b3"
      },
      "source": [
        "fig, ax = plt.subplots(figsize = (10,8))\n",
        "\n",
        "sns.boxplot(y = hotel_data_copy[\"lead_time\"], x = hotel_data_copy['is_canceled'])\n",
        "plt.title('Effect of lead time on cancellation', weight='bold',size= 15)\n",
        "plt.xlabel('Is_Cancelled',size = 15)\n",
        "plt.ylabel('Lead_time',size = 15)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Lead_time')"
            ]
          },
          "metadata": {},
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hkLu7_HuFCti"
      },
      "source": [
        "\n",
        "\n",
        " The image above is a boxplot. A boxplot is a standardized way of displaying the distribution of data based on a five number summary (“minimum”, first quartile (Q1), median, third quartile (Q3), and “maximum”). It can tell you about your outliers and what their values are. It can also tell you if your data is symmetrical, how tightly your data is grouped, and if and how your data is skewed.\n",
        "\n",
        " Lead time is the time that elapsed between the day when the booking were made and the actual day of checking in. from the box plot it seems that the cancellation normally occurs soon after booking. the chances of cancellation are actually less if sufficient time has elapsed after booking. There may be many reason for this including hotel cancellation policies among many others and this is true for both type of hotels.\n",
        "\n",
        "*   For non-cancellation the plot varies between 0(mimimum) to 280(maximum) and Q1 And Q3 for that is 1 - 110. Also, median is 30.\n",
        "*   For cancellation the plot varies between 0(mimimum) to 350(maximum) and Q1 And Q3 for that is 30 - 175. Also, median is 80.\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KtlZGVInAMSF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 638
        },
        "outputId": "5298d973-a4e1-4a63-d684-788c1bbf2a7b"
      },
      "source": [
        "\n",
        "sns.FacetGrid(hotel_data_copy, hue=\"is_canceled\", height = 6,aspect=1.5) \\\n",
        "   .map(sns.distplot, \"lead_time\") \\\n",
        "   .add_legend();\n",
        "plt.title('Effect of lead time on cancellation', weight='bold',size = 15)\n",
        "plt.xlabel('Is_Cancelled',size = 15)\n",
        "plt.ylabel('Lead_time',size = 15)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning:\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning:\n",
            "\n",
            "`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(26.95329861111111, 0.5, 'Lead_time')"
            ]
          },
          "metadata": {},
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 714.125x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bwejb8Hhu4cW"
      },
      "source": [
        " Dist plots helps us to check the distribuiton of the column feature. Basically it shows the distribution of a univariate set of observations.\n",
        " The lead time of non-cancelled i.e '0' is higher efficiency as compared to cancellation of the booking. The KDE (Kernel Density Estimation) shows the probabality density function is higher of non- cancelled but in cancellation the KDE lead time lie between 0.005 to 0.010.  "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R3rekx3lAPNb"
      },
      "source": [
        "**Analysis no. 7**\n",
        "\n",
        "Cancellation percentage by year"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZpTI3S3SAuqY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 548
        },
        "outputId": "78e48bd6-bbca-4b3a-bd5e-53fbf7da4d27"
      },
      "source": [
        "plt.figure(figsize=(30, 8))\n",
        "plt.subplot(1, 2, 1)\n",
        "\n",
        "sns.barplot(data = hotel_data_copy, x= 'arrival_date_year', y = 'is_canceled',hue = 'hotel' )\n",
        "plt.title('cancellation percentage by year',fontweight=\"bold\", size=25)\n",
        "\n",
        "plt.xlabel('year',size=20)\n",
        "plt.ylabel('cancellation percentage',size=20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'cancellation percentage')"
            ]
          },
          "metadata": {},
          "execution_count": 32
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 2160x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "38acZrPv8ZeR"
      },
      "source": [
        "Above Graph Describe the cancellation of Hotel year wise where we notice that in the year 2017 there are the most no. of cancellation of both resort and city hotel, followed by the year 2016, and lastly the year 2015 with the least no. of cancellations among the 3 years."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6d6Un2aHBEVr"
      },
      "source": [
        "**Analysis no.8**\n",
        "\n",
        "Which month have highest number of cancellation ?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SN_owtDDBVqf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "41be605c-6326-4c43-f62d-efe98c35490d"
      },
      "source": [
        "\n",
        "hotel_data_copy[hotel_data_copy['is_canceled'] == 1]['arrival_date_month'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "August       3616\n",
              "July         3192\n",
              "May          2442\n",
              "April        2404\n",
              "June         2352\n",
              "March        1829\n",
              "October      1637\n",
              "September    1636\n",
              "February     1414\n",
              "December     1373\n",
              "November     1051\n",
              "January      1037\n",
              "Name: arrival_date_month, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s2rjy3T4B3JC",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 623
        },
        "outputId": "c5fafe89-1c29-40ee-da0a-326eac123ac8"
      },
      "source": [
        "plt.figure(figsize = (20,10))\n",
        "ax = sns.countplot(x = 'arrival_date_month',hue = 'hotel', data = hotel_data_copy[hotel_data_copy['is_canceled'] == 1])\n",
        "ax.set_ylabel('number_of_cancelation')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'number_of_cancelation')"
            ]
          },
          "metadata": {},
          "execution_count": 34
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7gYRqkHX9IQ8"
      },
      "source": [
        "In this graph we found the cancellation with respect to months.\n",
        "\n",
        "Comparetively to City Hotels , Resort Hotels has less no. of Cancellations."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3ZOP-ir09XHy"
      },
      "source": [
        "CITY HOTEL CANCELLATIONS \n",
        "\n",
        "*   August month has the highest no. of cancellations (i.e it is more that 2000 cancellation).\n",
        "*   Followed by July, April, May, June, March, October, September, December and February.\n",
        "*   And the least no. of cancellations are made in the month of november and january (i.e which are approx. about 750 cancellations).\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AR98AVGh-zHY"
      },
      "source": [
        "RESORT HOTEL CANCELLATIONS\n",
        "\n",
        "*   August month has the highest no. of cancellations (i.e it is more that 1500 cancellation).\n",
        "*   Followed by July, June , May, April, September, October,March ,February and December.\n",
        "*   And, the least no. of cancellations are made in the month of november and january (i.e which are approx. between 250-350 cancellations).\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yfzD5Z12CGRd"
      },
      "source": [
        "**Analysis no.9**\n",
        "\n",
        "How deposit varies in terms of non-cancellation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ELM_GWvkCOr9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 537
        },
        "outputId": "489e75b6-14ec-4c58-fd2a-bfb9ed5838d1"
      },
      "source": [
        "\n",
        "deposit_df = hotel_data_copy.groupby('deposit_type')['is_canceled'].describe()\n",
        "plt.figure(figsize=(12, 8))\n",
        "sns.barplot(x=deposit_df.index, y=deposit_df[\"mean\"].values * 100)\n",
        "plt.title(\"Deposit varies in terms of non-cancellation\", fontsize=16)\n",
        "plt.xlabel(\"Deposit Type\", fontsize=16)\n",
        "plt.ylabel(\"Non-Cancellations [%]\", fontsize=16)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Non-Cancellations [%]')"
            ]
          },
          "metadata": {},
          "execution_count": 35
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wib2daAnAdFG"
      },
      "source": [
        "In the Above Graph,\n",
        "\n",
        "*   More than 80% of non - cancellation are non-refundable.\n",
        "*   Also, we see that  20-25% are refundable\n",
        "*   While approx. 30% people haven't deposit any money while booking.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fFN2Kti1GHnB"
      },
      "source": [
        "# General Analysis "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Fg4VJk6xGL1j"
      },
      "source": [
        "**Analysis no. 10**\n",
        "\n",
        "How much does guest pay for a room per night ?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ogududoEGWJ_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "4d679ab5-aefe-4145-d14a-abcf0cab9771"
      },
      "source": [
        "hotel_data_copy.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>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>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",
              "      <th>childs</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>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</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-01</td>\n",
              "      <td>0.0</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>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</td>\n",
              "      <td>Transient</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-01</td>\n",
              "      <td>0.0</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>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</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-02</td>\n",
              "      <td>0.0</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>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>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-02</td>\n",
              "      <td>0.0</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>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>0</td>\n",
              "      <td>Transient</td>\n",
              "      <td>98.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Check-Out</td>\n",
              "      <td>2015-07-03</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          hotel  is_canceled  ...  reservation_status_date  childs\n",
              "0  Resort Hotel            0  ...               2015-07-01     0.0\n",
              "1  Resort Hotel            0  ...               2015-07-01     0.0\n",
              "2  Resort Hotel            0  ...               2015-07-02     0.0\n",
              "3  Resort Hotel            0  ...               2015-07-02     0.0\n",
              "4  Resort Hotel            0  ...               2015-07-03     0.0\n",
              "\n",
              "[5 rows x 29 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7_HR_Z-FG6g9"
      },
      "source": [
        "#creating new dataframe so we can do our anlaysis non cancelled room only\n",
        "\n",
        "room_type_category = hotel_data_copy[hotel_data_copy['is_canceled']==0]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TITKb5VtHZqL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "outputId": "e4c0be89-8821-4074-b158-8a4599488563"
      },
      "source": [
        "#ploting box plot fro analysis\n",
        "\n",
        "plt.figure(figsize=(12,8))\n",
        "sns.boxplot(x='reserved_room_type', y ='adr',data = room_type_category,hue='hotel')\n",
        "plt.title('price of room types per night per person')\n",
        "plt.xlabel('Room Type')\n",
        "plt.ylabel('price')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jw_V6VciHl8J"
      },
      "source": [
        "We can see in the above figure that with repect to \"A\" category room it has highest price appox as outlier\n",
        "\n",
        "whereas with respect to 'G' category room of city hotel are much costlier than other"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "enrCzc5XHoPC"
      },
      "source": [
        "**Analysis no. 11**\n",
        "\n",
        "Which are the most busy month ?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q09w4d9hHxpK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 373
        },
        "outputId": "08398381-abda-4976-ec8a-055972820340"
      },
      "source": [
        "plt.figure(figsize=(20,5))\n",
        "\n",
        "sns.countplot(data = hotel_data_copy, x = 'arrival_date_month', hue = 'hotel', order = ['January', 'February', 'March', 'April', 'May', 'June', 'July',\n",
        "          'August', 'September', 'October', 'November', 'December']).set_title('Graph showing number of arrival per month',fontsize=20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Graph showing number of arrival per month')"
            ]
          },
          "metadata": {},
          "execution_count": 39
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "53NqcAiQIAUB"
      },
      "source": [
        "According to the above graph the most busy month is August\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7VmjfAP4IB2p"
      },
      "source": [
        "**Analysis no. 12**\n",
        "\n",
        "Which meals were most preferrable to the customer ?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GdTXKzegIPQg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 575
        },
        "outputId": "a5d82445-c1c2-4cac-cad9-31f1dcc9b996"
      },
      "source": [
        "# Enlarging the pie chart\n",
        "plt.rcParams['figure.figsize'] = 10,10\n",
        "\n",
        "#Making list of  not cancelled\n",
        "# Assigning labels and converting them to list \n",
        "\n",
        "labels = hotel_data_copy['meal'].value_counts().index\n",
        "\n",
        "# Assigning sizes and converting to list\n",
        "\n",
        "sizes = hotel_data_copy['meal'].value_counts().tolist()\n",
        "\n",
        "# Autopct enables you to display the percent value using python string formatting. .1f% will round off to the tenth place\n",
        "plt.pie(sizes,labels=labels,autopct='%0.1f%%')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jXdfK2urIkdM"
      },
      "source": [
        "\n",
        "We can see from above pie chart that most preferrable meal is BB(77.4% appx) i.e Bed and Breakfast"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KvKg9sL5Il8M"
      },
      "source": [
        "**Analysis no. 13**\n",
        "\n",
        "How long does guest stay at hotel on weekends and weekdays ?\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s_HUfP_jIxbU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 899
        },
        "outputId": "4b4dffaf-e03b-4425-c419-46e86ea9b1f2"
      },
      "source": [
        "plt.figure(figsize=(15, 15))\n",
        "plt.subplot(1, 2, 1)\n",
        "sns.countplot(data = hotel_data_copy, x = 'stays_in_week_nights',hue='hotel' ,palette='cool')\n",
        "plt.title(\"Number of stays on week nights\",fontweight=\"bold\", size=20)\n",
        "plt.grid()\n",
        "\n",
        "plt.subplot(1, 2, 2)\n",
        "sns.countplot(data = hotel_data_copy, x = 'stays_in_week_nights', hue='is_canceled', palette='rocket')\n",
        "plt.title('WeekStay vs Cancelation',fontweight=\"bold\", size=20)\n",
        "plt.grid()\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x1080 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dnbTZcqTJIz9"
      },
      "source": [
        "We can see from graph that most people are staying at hotel for 2 nights in week days\n",
        "\n",
        "And second graph is showing that most cancellation is done for room which is booked for 2 night stay and we also see that most booking were not cancelled for 1 night stay"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_YzqfSEMJLbc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "outputId": "a79b89c5-f619-4c38-8ada-65da11293c9e"
      },
      "source": [
        "plt.figure(figsize=(15, 8))\n",
        "plt.subplot(1, 2, 1)\n",
        "sns.countplot(data = hotel_data_copy, x = 'stays_in_weekend_nights',hue='hotel' ,palette='cool')\n",
        "plt.title(\"Number of stays on weekend nights\",fontweight=\"bold\", size=20)\n",
        "plt.grid()\n",
        "\n",
        "plt.subplot(1, 2, 2)\n",
        "sns.countplot(data = hotel_data_copy, x = 'stays_in_weekend_nights', hue='is_canceled', palette='rocket')\n",
        "plt.title('WeekendStay vs Cancelation',fontweight=\"bold\", size=20)\n",
        "plt.grid()\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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yTDmb22+ZpJyJ7vZbNIfPAo9qzeNUrW+rW9Nt30/zwpreDnqPb5X71db4rst2l//VSKvcm1rjmwe4X2uN61of5WxuJ/1bXepc2Rg/OsE0T2+Ne3dj3C9b4w5rld2jS73/tzF+HeUg8lRKYH0gXe4jcxjcwPhg6WHK1cFl9fsDlIBpa8ZOkpxV0x5olGuegL14EuvnpbVM+6TOhoajeyzXzeEaYLcu8zvp9tVyx7XGNYO8x7TG/UNj3M8a6d/o0p7mvmq0y/hXUK7wTrTd+0yrzEhr/EiP//1b6d3drjn8XqPMvzXSL6lpv9bKv1e3+nq0odk1/1M17Vdb8/v8Rv4p256wCcFhnecNdfNM4PxWuUlva1l//3rQBtrWPjbZ0PD4DS03mzC/yxrjVvZo72GtaexR09snhY7o8j9ojm/u71c20r/dKvfmVrlfnej3HPSw2b/nsJssv/zfNpL+dRLF2+/ae/Qkyq5ufH6oNe6mxuf2Jede/4c7cv3uaLe2vm9PuQozmXcE9npPzk+y++XwiezY+n7LBr6382+sN1PO4EDpwrg/cCTlqs+3gR9HxG9MZoIR8RRK0NnPk9eay8W5lBvKO+mLImLfxnQeoHSnACAzL6N0Lb6rJv0W5SzYOyndVlZHxL/02eyp+v1Xtr4/2Pg8me1Es2vp8yNiR0pwA+UKa+cpgy9ifJewH2XppgsbvzxPdtnq531RP83M9ro8Vevbytb3B1vfO7/79q309jag/X1jTdSefpeBZltv7jK+vTxuTFs25n2oJ1G6a/2CEmTsR+kmeDzl4OymiHjVRkxXU+Prjc9bUbqudbYPF2fmg3Vf+K2a9gLKSd/m6xWa05jMtmA6tx93MNbFuWlj2tfNysbnXtsPGL9edtteTLgNycwvZOYLKE/NPJASpF7Syvbq2l22bxHxR5SHtzyhj+zNfe7JlJMIAPMj4jmMde8D+E5mXj2JpjS7cr4iIp5A6V7Z2db8KDO/1cgzlduTVa3vv9k1V3dn0V8X1omOY1e2vvfa1raX2es3UOdk16ed+sgzFfM7WYM4xoJZ9t75YbznEIDM/FpEnEeJ+p/P+Huy2n7Z+Lxta9w8+veLCcZNNugCeFJEbN0KEOe28jS7V3ZW5K9RupH00mujeV+P9Im03wXzZMbuK+h8nyj/RsnMm4GRiPhVSv/1eZQneR1E2RE+jXIv10smMdk/ZPw9UW+ndE+4MyIeS4/fJ/OR+yA+UJMWU/rud3w2M+9ulflQRHystn0vSjeJ36fc57U15b6O8zLzGxto81T9/u1lNzdQby9fa3zekRLEb0W5ovpdygHc8ygHfs0DkmZQ2ekyNNnluT1v76GcMe/lJz3Sr6EE7ABvi4gHMvNdU9C+tn5/87ta39vbgPb3jTUVy8BdjO3kf6XL+PbyOJ1tGStctqFvioi/pRzI/QZlG7GQsu49ETg1Ir6cvh93JnSuSnUOkA5l7P655jZwlLJPfxKlS1lTMzhsbgtuoAQTvdzbpQyUe5YunqDcd3qkX0s5MTiHsq07JyL+IDN/vontW0+O3RvX2Q/1ynoX5TeD7tuLvrYhmXknZVt3HuV90h+gdDvt+DXG3lXcj2ZAdx/lfvyvZ+YDEXEgJdDq1o4bIuLzlPcrQjkx/LuNLB+bRBuo9dxMeRbAtnW6f9oYP+4+wCnennyV8c8CeCMbuFcSHnkH6LMbSWdQjlluysxfRsR3Gf+b9NLvtra9fuxJeTZDL838SXn43ETHwd1OojxiCud3srodY030fbqPsQZiaIPD6m8pN5FuRelX3kvz4GvniHhqZv4kIh5N6cs8U7ahnL36b4B6FeYVjfHXZL0ROyK+T3kACJSF9cPZej9hRGxTy/faqW2Mb7e+Hw78f7W+rSjdGjsepnRV22QR8UzKO61+Srk/o5P+V5Srh7D+hmIdY8v8Y1lf+8zV0rozhPE7sW6WAf9E2Sn8BmUn2TFuxxIRu8AjAe4369B5r+SddRqd9m8oOJyR37+XzLwpIprB1f+tfy/OzIci4huUncSzKFdUOy5oTOP+jVyem2d2AR7MLu/ji4gnU7oo/bQ9rvpXykHdn9fv74yIn2fm8ZvYvo31I8oBYuehEX8cESdmZufM46LuxWbEdxl7mNHvRcSemXk9QETsz/j1Yqq0d7rrrdu1F8Gq1sEt9YrDZTXb4yjL7WXt8ppemXlXRPyAsYO/VzdGf73H52aeFY2eB1C2BfvUz3OBL2XmNe166/vlOkHbjyknkzr7gR0p9/uta5XZlnI/c3vb2/E/lFcpnUo5gfQS4HMRcXCjF8LGtG9TXEIJXKCsl/OyPqgvIl5Aj94ytTfNu4BTsj5Mp6UduDYfYLfB9ZLx+9zrMvPLje8b2ue+n7Fl4FDGriKvpdzP1rfMfDgillF670DZh3YuKDxEuZ3nEVO8PTmbcqKy87DBV0TEu4B/qb3g2vXOz8zTWf945czMXFXz/RblHtSp1D4WeVdELG8Gv/UY9eF6MvxbjPXgC+DWzPx4e6IRsSflFVbtk6BtmzK/zWWx23I4kYsZf+x4aER8PDM7F5Xe2Mrfa7uwWRnq4DAzr4yIUxn/lK5u2mcHvx0RX6cc/D1tWhrXv49FxPMpO60/Znz3kCWNz+9hbIO4F3BVRJxFueT9BMrNxCP1855s4CzNJHyJcmVkr/r97+oZnvbTMqHc0D3RlZzJOB2YGxFfo3TnvZ3S/eYNjTztMzirGDsbfVhEPEi51+FnmbmMcnDQdG5EfIlyVfJPmEBmrq1PPesEQ50d1bWZ+fVW9ucBn46IiyhPzbyZsvF6AWOBYbf2dzNTv/9ELmAsOOxs0Ds7lm8ztqF9XE37JeWKQNOkl+fMvKLRWwDgH+q68z+UQPQplCeW/S4lID9rgnl4M6X7aOfg4x/rFcTOE28Htr5l5rqI+DhjT+h9OnBRRHyBcgAz4bI5YB9mLDjchrIt/W/K+nDENNXZ7pb1oYj4MmU5G83MSynduI+IiAsp91fdQul61O76NVXbRU3e1xkLDjuXwH7B+JMrl1EO/h/XyNMp2/QBxp7++xjg4oj4DOUgfBvKfv2FlB4eh1MeiPHLiPg3xp7K+xLgioj4IiXo2ZHyxMEX1un2fLpgZv53PVD+z5r0cso2/zU12Jx0+3rV1acljAWHc4BvRsRplBfZtw9umx5FuUJ7VET8mLL9voFy1WNvxgfoKxnfS6K9Xp4Y5QneD1EeOnQBZZ/7sjp+74j4FGWfOMIGev1k5jcj4nuU47Rm9+Iz2ifq+vQxylMjg/E9zc7OzNtbeadse1JPmh5KuYLY6bl2IuVJrOdRjv2eROlG/fuUQPV0ytNdm1fb3x8Rz6asG4dR/ndTJjOvioizKb2zoJzcuLpewV1DWWYPovQKupxyu82VjN1W8tGIOJjylOF1lGV7X0pQdyrl6b4T2ZT5bS6LO9cTAZ3Xt/x3ZvbsVp2Za+qxXefq7guBb0XEcsqxYfMkxo8p7wbe/M3UzY5TNdDlgTSt8bvS5X1ZrTyPZvy7c5rDF1rfD2uUO6w1bo8pGLeskX475cWi3dp1Aa2HxwDH0t+DMpr1jTbSRzfyf/B0Sv/zier8Gus/8bE5rysnWeeVG6gvgTe3yvxrj3xX1vHbUDZc3fK0n5x2XJc27cn4B80k8I4u+V7TR9v/lz6fXrUxvz8TPGhpCv43B3ep/6WN8e33EF7SYzobszw/qcv0uw2jG/otKDubr7TGHb2J7Rvt1oY6bqRVbqQx7glMvC2YcNns8fv2rK+Ptvasj/LqnW7tvI7x71Pr6yE3ddxxzfGtcY9i7H147aHzxNyT+/g/fXJjtn8OUzNQDizb/5Nvd8nX7X1jb+iS7w+Y+D2C6237KIFBr+V33NCqa2Vj3LJGevtJhp9i7CnJG9O+nutBH+vQqT2mfyPj30U32iizRz+/BeUY6yVd2tNrW3xyHf9Uej+Mpr3PHeky/UO7lNt3E5bBr3WZ3oIu+aZ8e0IJ/vp5GF5z+fpgjzyd1z2s9z/tYznpuYwxPe85bM/TSK//+ybM796MfyJtc5hf8xzWSt+jUf6xlFdXTDQP3d5rvLLbPG6ovtkwzKobIKdDZq5m7OxdrzwPUs5SfZJyBuRBSpBwGOUM0Uy5j3Ll532UrpO/oCxsJ1DeuTauu0tm/iPlbM5Syn0PD1BWiNspl/jfTelOt3IqG5mZ/0s5+/NOylXYu2u9P6OcDTuM8o6nqbyX5+8oG4rvUq4cPkg5I3kj5V19B2Tmh1tl/p4SIK6kS9/3LPdv7E/pBnp7nd6PKf3a/7ydv0v56ylPPetYRwmy2v6HcobybMqG8y5KUHk35cz4CZQdXM97TVr1zsTvP5FRxt/H23maW0f7LP/X6GJjlufMvINydvWNlDORt9YyP6fseD9PuQK3wXcDZukC9krGd8U9KSLetLHt21hZ3q/4AkpXqpsoy+YKSoB64ARFZ8KRlO3mNZR23ko5K78f43urTMlVuvp/Wki5it65H7Tt45SnAX+Nsv7fx9j/6kLKleI/m4r2aKN9k/X/d9261Y92SVsvX2Z+iXJV/92UV/Pcy9h29vuU9w8fxNi768jiTZT3wp5BWVYepOx7b6YsP8cx/p2jPWXmsYzdiw7lPXxLI2KrjWnfJjqc0rOluV4upWzDbupR5qeU7em7KF0nr6FcRX24tvcKyjbpGZnZbTv+KkpAfDvj9wkAZOZPKNu18yjr5P2U7e0f0erK2cMZjL93/Yqs73bcSO13DN5A2Ye2Tfn2JDO/Q3kYzaGUY5gbKL/HOsqVyfMpV5vf3ij2fyj/m+spy+hNlGctvIhyhX1KZekuOkKZt3Nru35BWRauoSyzqxr5r6PcQvJWynrbWXbupxxbnUE5tur0uNqQjZrfzLyCcpX74lr3pNRjpwMoPdPOp/yf11FO7lxK6Yb8zMxs9z7bbEWNYCVNgYg4kbLxAvh8Zr5yJtsjDVpEbJvrvxSbiHgu5WRO56TkMZn5nnY+SepXRHybEsBCef/l+2eyPdIwGOp7DqVBiIg9KF1K5zH+yW3upLQl+q+I2JlyZnklZT/zTMq9S53A8G7KVQtJmpR67+JOwIsZCwzvpntPHUmTZHAobbrDKN37ms7MzNHBN0WacVtTHjLxsh7j1wCvyvUf8iBJ/fhPxr8nF+Bd2XpllKSNY3AoTZ2HKfc8foJy36C0JTqdEiA+l/IE4cdQ7s34EeXeoo8YGEqaAj+n3Lf/vixPHJc0BbznUJIkSZI0/E8rlSRJkiRt2BbXrXSnnXbKPfbYo+/89913H9ttt930NWiA9QxLHYOqx3mZfXUMqp5hqWNQ9czWOi677LKfZebO09SkoTPZ/SPM3v/9bK1nWOoYVD3DUseg6nFeZl8dg6pnSveRM/2ixUEPz33uc3MyLrzwwknl31iDqGdY6hhUPc7L7KtjUPUMSx2Dqme21gFcmrNgv7O5DJPdP2bO3v/9bK1nWOoYVD3DUseg6nFeZl8dg6pnKveRdiuVJEmSJBkcSpIkSZIMDiVJkiRJGBxKkiRJkjA4lCRJkiRhcChJkiRJwuBQkiRJkoTBoSRJkiQJg0NJkiRJEgaHkiRJkiQMDiVJkiRJGBxKkiRJkjA4lCRJkiRhcChJkiRJwuBQkiRJkoTBoSRJkiQJg0NJkiRJEgaHkiRJkiQMDiVJkiRJwJyZbsBsd+dP13HmUbf3lfe1H9x5mlsjSdL0O+YZr+8r38KTj5zmlkiSBskrh5IkSZIkg0NJkiRJksGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSNFARsXtEXBgRV0fEVRHx1pp+XESsjojL63Bgo8w7I2JFRPw4Ig5opC+saSsi4phG+p4RcXFN/1REPGqwcylJ2hwZHEqSNFjrgL/OzL2A/YCjImKvOu59mfmsOpwLUMe9DvhtYCHwoYjYOiK2Bj4IvBzYC3h9YzrvqdN6GnAncMSgZk6StPkyOJQkaYAy8+bM/F79fC9wDbDrBEUOAs7IzAcz83pgBbBPHVZk5nWZ+RBwBnBQRMRX/cEAACAASURBVATwEuAztfypwMHTMzeSpGEyZ6YbIEnSlioi9gCeDVwMPA84OiIOBS6lXF28kxI4XtQotoqxYPLGVvq+wJOAuzJzXZf87foXA4sB5s6dy+joKAB7v2VBX+1fu3btI2WmyyDqGFQ9w1LHoOoZljoGVY/zMvvqGFQ9U1mHwaEkSTMgIh4HfBZ4W2beExGnACcAWf/+B/DG6WxDZi4BlgDMnz8/R0ZGADjm6I/0VX7hyUfSKTNdRkdHp72OQdUzLHUMqp5hqWNQ9Tgvs6+OQdUzlXUYHEqSNGARsQ0lMDw9Mz8HkJm3NsZ/FPhi/boa2L1RfLeaRo/0O4DtI2JOvXrYzC9JUk/ecyhJ0gDVewI/BlyTme9tpO/SyPZK4Mr6+RzgdRHx6IjYE5gHfBe4BJhXn0z6KMpDa87JzAQuBF5Tyy8Czp7OeZIkDQevHEqSNFjPA94AXBERl9e0d1GeNvosSrfSlcCRAJl5VUR8Gria8qTTozLzYYCIOBo4H9gaWJqZV9XpvQM4IyL+Cfg+JRiVJGlCBoeSJA1QZn4LiC6jzp2gzInAiV3Sz+1WLjOvozzNVJKkvtmtVJIkSZJkcChJkiRJMjiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJIlpDA4jYveIuDAiro6IqyLirTV9x4hYHhHX1r871PSIiJMiYkVE/DAintOY1qKa/9qIWNRIf25EXFHLnBQRMV3zI0mSJEnDbDqvHK4D/joz9wL2A46KiL2AY4ALMnMecEH9DvByYF4dFgOnQAkmgWOBfYF9gGM7AWXN86ZGuYXTOD+SJEmSNLSmLTjMzJsz83v1873ANcCuwEHAqTXbqcDB9fNBwGlZXARsHxG7AAcAyzNzTWbeCSwHFtZxT8jMizIzgdMa05IkSZIkTcKcQVQSEXsAzwYuBuZm5s111C3A3Pp5V+DGRrFVNW2i9FVd0rvVv5hyNZK5c+cyOjraf9u3e4A5+/6gr7yjoxv/c65du3ZS7dqS6xhUPc7L7KtjUPUMSx2DqmdY6pAkaUs37cFhRDwO+Czwtsy8p3lbYGZmROR0tyEzlwBLAObPn58jIyN9lz3rtK+y7uJn9pV35NCdN6Z5AIyOjjKZdm3JdQyqHudl9tUxqHqGpY5B1TMsdUiStKWb1qeVRsQ2lMDw9Mz8XE2+tXYJpf69raavBnZvFN+tpk2UvluXdEmSJEnSJE3n00oD+BhwTWa+tzHqHKDzxNFFwNmN9EPrU0v3A+6u3U/PBxZExA71QTQLgPPruHsiYr9a16GNaUmSJEmSJmE6u5U+D3gDcEVEXF7T3gW8G/h0RBwB3AAcUsedCxwIrADuBw4HyMw1EXECcEnNd3xmrqmf3wIsA7YFzquDJEmSJGmSpi04zMxvAb3eO7h/l/wJHNVjWkuBpV3SLwWesQnNlCRJkiQxzfccSpIkSZI2DwaHkiRJkiSDQ0mSJEmSwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpI0cBGxe0RcGBFXR8RVEfHWmr5jRCyPiGvr3x1qekTESRGxIiJ+GBHPaUxrUc1/bUQsaqQ/NyKuqGVOiogY/JxKkjYnBoeSJA3eOuCvM3MvYD/gqIjYCzgGuCAz5wEX1O8ALwfm1WExcAqUYBI4FtgX2Ac4thNQ1jxvapRbOID5kiRtxgwOJUkasMy8OTO/Vz/fC1wD7AocBJxas50KHFw/HwSclsVFwPYRsQtwALA8M9dk5p3AcmBhHfeEzLwoMxM4rTEtSZK6mjPTDZAkaUsWEXsAzwYuBuZm5s111C3A3Pp5V+DGRrFVNW2i9FVd0tt1L6ZciWTu3LmMjo4CsPdbFvTV9rVr1z5SZroMoo5B1TMsdQyqnmGpY1D1OC+zr45B1TOVdRgcSpI0QyLiccBngbdl5j3N2wIzMyMip7P+zFwCLAGYP39+joyMAHDM0R/pq/zCk4+kU2a6jI6OTnsdg6pnWOoYVD3DUseg6nFeZl8dg6pnKuuwW6kkSTMgIrahBIanZ+bnavKttUso9e9tNX01sHuj+G41baL03bqkS5LUk8GhJEkDVp8c+jHgmsx8b2PUOUDniaOLgLMb6YfWp5buB9xdu5+eDyyIiB3qg2gWAOfXcfdExH61rkMb05IkqSu7lUqSNHjPA94AXBERl9e0dwHvBj4dEUcANwCH1HHnAgcCK4D7gcMBMnNNRJwAXFLzHZ+Za+rntwDLgG2B8+ogSVJPBoeSJA1YZn4L6PXewf275E/gqB7TWgos7ZJ+KfCMTWimJGkLY7dSSZIkSZLBoSRJkiTJ4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSMGemGyBJkjRdjnnG6/vKt/DkI6e5JZI0+3nlUJIkSZJkcChJkiRJMjiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSmMbgMCKWRsRtEXFlI+24iFgdEZfX4cDGuHdGxIqI+HFEHNBIX1jTVkTEMY30PSPi4pr+qYh41HTNiyRJkiQNuznTOO1lwMnAaa3092XmvzcTImIv4HXAbwNPAb4aEU+voz8IvAxYBVwSEedk5tXAe+q0zoiIDwNHAKdM18xMtzt/uo4zj7p9g/le+8GdB9AaSZIkSVuaabtymJnfANb0mf0g4IzMfDAzrwdWAPvUYUVmXpeZDwFnAAdFRAAvAT5Ty58KHDylMyBJkiRJW5CZuOfw6Ij4Ye12ukNN2xW4sZFnVU3rlf4k4K7MXNdKlyRJkiRthOnsVtrNKcAJQNa//wG8cborjYjFwGKAuXPnMjo62n/Z7R5gzr4/6Cvv6OjG/5z91rMpdaxdu3ZS8z5b6xhUPc7L7KtjUPUMSx2DqmdY6pAkaUs30OAwM2/tfI6IjwJfrF9XA7s3su5W0+iRfgewfUTMqVcPm/m71bsEWAIwf/78HBkZ6bvNZ532VdZd/My+8o4cuvH3A/Zbz6bUMTo6ymTmfbbWMah6nJfZV8eg6hmWOgZVz7DUIUnSlm6g3UojYpfG11cCnSeZngO8LiIeHRF7AvOA7wKXAPPqk0kfRXlozTmZmcCFwGtq+UXA2YOYB0mSJEkaRtN25TAiPgmMADtFxCrgWGAkIp5F6Va6EjgSIDOviohPA1cD64CjMvPhOp2jgfOBrYGlmXlVreIdwBkR8U/A94GPTde8SJIkSdKwm7bgMDNf3yW5ZwCXmScCJ3ZJPxc4t0v6dZSnmUqSJEmSNtFMPK1UkiRJkjTLGBxKkiRJkgwOJUmSJEmDf8+hJEkSxzyj26MJ1rfw5COnuSWSpA6vHEqSJEmSDA4lSZIkSQaHkiRJkiS853CLcudP13HmUbdvMN9rP7jzAFojSZIkaTbxyqEkSZIkyeBQkiRJkmRwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSBi4ilkbEbRFxZSPtuIhYHRGX1+HAxrh3RsSKiPhxRBzQSF9Y01ZExDGN9D0j4uKa/qmIeNTg5k6StLkyOJQkafCWAQu7pL8vM59Vh3MBImIv4HXAb9cyH4qIrSNia+CDwMuBvYDX17wA76nTehpwJ3DEtM6NJGkoGBxKkjRgmfkNYE2f2Q8CzsjMBzPzemAFsE8dVmTmdZn5EHAGcFBEBPAS4DO1/KnAwVM6A5KkoWRwKEnS7HF0RPywdjvdoabtCtzYyLOqpvVKfxJwV2aua6VLkjShOTPdAEmSBMApwAlA1r//AbxxOiuMiMXAYoC5c+cyOjoKwN5vWdBX+bVr1z5SZrIGUccg69mS6hhUPcNSx6DqcV5mXx2Dqmcq6zA4lCRpFsjMWzufI+KjwBfr19XA7o2su9U0eqTfAWwfEXPq1cNm/nadS4AlAPPnz8+RkREAjjn6I321eeHJR9IpM1mDqGOQ9fRjdHR0KOoYVD3DUseg6nFeZl8dg6pnKuuwW6kkSbNAROzS+PpKoPMk03OA10XEoyNiT2Ae8F3gEmBefTLpoygPrTknMxO4EHhNLb8IOHsQ8yBJ2rx55VCSpAGLiE8CI8BOEbEKOBYYiYhnUbqVrgSOBMjMqyLi08DVwDrgqMx8uE7naOB8YGtgaWZeVat4B3BGRPwT8H3gYwOaNUnSZszgUJKkAcvM13dJ7hnAZeaJwIld0s8Fzu2Sfh3laaaSJPXNbqWSJEmSJINDSZIkSZLBoSRJkiSJPoPDiLignzRJkrYk7h8lScNkwgfSRMRjgMdSnqa2AxB11BOAXae5bZIkzUruHyVJw2hDTys9Engb8BTgMsZ2fvcAJ09juyRJms3cP0qShs6EwWFmvh94f0T8ZWZ+YEBtkiRpVnP/KEkaRn295zAzPxARvw/s0SyTmadNU7skSZr13D9KkoZJX8FhRPw38FTgcuDhmpyAOz9J0hbL/aMkaZj0FRwC84G9MjOnszGSJG1m3D9KkoZGv+85vBJ48nQ2RJKkzZD7R0nS0Oj3yuFOwNUR8V3gwU5iZv7RtLRKkqTNg/tHSdLQ6Dc4PG46GyFJ0mbquJlugCRJU6Xfp5V+fbobIknS5sb9oyRpmPT7tNJ7KU9fA3gUsA1wX2Y+YboaJknSbOf+UZI0TPq9cvj4zueICOAgYL/papQkSZsD94+SpGHS79NKH5HF54EDpqE9kiRtltw/SpI2d/12K31V4+tWlPc6/XxaWqRJO+rM2/vK99JpbockbWncP0qShkm/Tyt9RePzOmAlpeuMJElbMvePkqSh0e89h4dPd0MkSdrcuH+UJA2Tvu45jIjdIuKsiLitDp+NiN2mu3GSJM1m7h8lScOk3wfSfBw4B3hKHb5Q0yRJ2pK5f5QkDY1+g8OdM/PjmbmuDsuAnaexXZIkbQ7cP0qShka/weEdEfFnEbF1Hf4MuGM6GyZJ0mbA/aMkaWj0Gxy+ETgEuAW4GXgNcNg0tUmSpM2F+0dJ0tDo91UWxwOLMvNOgIjYEfh3yk5xs+S7ASVJU2Do9o+SpC1Xv1cOf6ez4wPIzDXAs6enSZIkbTbcP0qShka/weFWEbFD50s9M9rvVUdJkoaV+0dJ0tDodwf2H8B3IuLM+v21wInT0yRJkjYb7h8lSUOjr+AwM0+LiEuBl9SkV2Xm1dPXLEmSZj/3j5KkYdJ315e6s3OHJ0lSg/tHSdKw6PeeQ0mSJEnSEDM4lCRJkiQZHEqSJEmSDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkpjE4jIilEXFbRFzZSNsxIpZHxLX17w41PSLipIhYERE/jIjnNMosqvmvjYhFjfTnRsQVtcxJERHTNS+SJEmSNOym88rhMmBhK+0Y4ILMnAdcUL8DvByYV4fFwClQgkngWGBfYB/g2E5AWfO8qVGuXZckSZIkqU/TFhxm5jeANa3kg4BT6+dTgYMb6adlcRGwfUTsAhwALM/MNZl5J7AcWFjHPSEzL8rMBE5rTEuSJEmSNEmDvudwbmbeXD/fAsytn3cFbmzkW1XTJkpf1SVdkiRJkrQR5sxUxZmZEZGDqCsiFlO6qzJ37lxGR0fZd866/spu9wBz9v1BX3lHRzf+5+y3nm51TPW8bMp8rF27ltHR0Y0uP5vqcV5mXx2DqmdY6hhUPcNShyRJW7pBB4e3RsQumXlz7Rp6W01fDezeyLdbTVsNjLTSR2v6bl3yd5WZS4AlAPPnz8+RkRGOOvP2vhr80gd+wLqLn9lX3pFDd+4rXzdnnfbVvurpVsdUz8umzMfo6CgjIyMbXX421eO8zL46BlXPsNQxqHqGpQ5JkrZ0g+5Weg7QeeLoIuDsRvqh9aml+wF31+6n5wMLImKH+iCaBcD5ddw9EbFffUrpoY1pSZIkSZImadquHEbEJylX/XaKiFWUp46+G/h0RBwB3AAcUrOfCxwIrADuBw4HyMw1EXECcEnNd3xmdh5y8xbKE1G3Bc6rgyRJkiRpI0xbcJiZr+8xav8ueRM4qsd0lgJLu6RfCjxjU9ooSZIkSSoG3a1UkiRJkjQLGRxKkiRJkgwOJUmSJEkGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkDVxELI2I2yLiykbajhGxPCKurX93qOkRESdFxIqI+GFEPKdRZlHNf21ELGqkPzcirqhlToqIGOwcSpI2RwaHkiQN3jJgYSvtGOCCzJwHXFC/A7wcmFeHxcApUIJJ4FhgX2Af4NhOQFnzvKlRrl2XJEnrMTiUJGnAMvMbwJpW8kHAqfXzqcDBjfTTsrgI2D4idgEOAJZn5prMvBNYDiys456QmRdlZgKnNaYlSVJPBoeSJM0OczPz5vr5FmBu/bwrcGMj36qaNlH6qi7pkiRNaM5MN0CSJI2XmRkROd31RMRiSldV5s6dy+joKAB7v2VBX+XXrl37SJnJGkQdg6xnS6pjUPUMSx2Dqsd5mX11DKqeqazD4FCSpNnh1ojYJTNvrl1Db6vpq4HdG/l2q2mrgZFW+mhN361L/vVk5hJgCcD8+fNzZKRM7pijP9JXgxeefCSdMpM1iDoGWU8/RkdHh6KOQdUzLHUMqh7nZfbVMah6prIOu5VKkjQ7nAN0nji6CDi7kX5ofWrpfsDdtfvp+cCCiNihPohmAXB+HXdPROxXn1J6aGNakiT15JVDSZIGLCI+Sbnqt1NErKI8dfTdwKcj4gjgBuCQmv1c4EBgBXA/cDhAZq6JiBOAS2q+4zOz85Cbt1CeiLotcF4dJEmakMGhJEkDlpmv7zFq/y55Eziqx3SWAku7pF8KPGNT2ihJ2vLYrVSSJEmSZHAoSZIkSTI4lCRJkiRhcChJkiRJwuBQkiRJkoTBoSRJkiQJg0NJkiRJEgaHkiRJkiQMDiVJkiRJGBxKkiRJkjA4lCRJkiRhcChJkiRJwuBQkiRJkoTBoSRJkiQJg0NJkiRJEgaHkiRJkiRgzkw3QJIkbZ4evPF6Vrx1yQbzPe39nxhAayRJm8orh5IkSZIkg0NJkiRJksGhJEmSJAmDQ0mSJEkSPpBm2h115u195XvpNLdDkiRJkibilUNJkiRJksGhJEmSJMngUJIkSZKE9xxKkiTx4I3Xs+KtSzaY72nv/8QAWiNJM8Mrh5IkSZIkg0NJkiRJksGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJGDOTDdAkiSplwdvvJ4Vb12ywXxPe/8nBtAaSRpuXjmUJEmSJBkcSpIkSZIMDiVJkiRJGBxKkiRJkpih4DAiVkbEFRFxeURcWtN2jIjlEXFt/btDTY+IOCkiVkTEDyPiOY3pLKr5r42IRTMxL5IkSZI0DGbyyuGLM/NZmTm/fj8GuCAz5wEX1O8ALwfm1WExcAqUYBI4FtgX2Ac4thNQSpIkSZImZzZ1Kz0IOLV+PhU4uJF+WhYXAdtHxC7AAcDyzFyTmXcCy4GFg260JEmSJA2DmQoOE/hKRFwWEYtr2tzMvLl+vgWYWz/vCtzYKLuqpvVKlyRJkiRN0pwZqvf5mbk6In4FWB4RP2qOzMyMiJyqymoAuhhg7ty5jI6Osu+cdf2V3e4B5uz7g77yjo6u/3NOdT0zVUe/1q5dy+jo6EaXn031OC+zr45B1TMsdQyqnmGpQ5KkLd2MBIeZubr+vS0izqLcM3hrROySmTfXbqO31eyrgd0bxXeraauBkVb6aI/6lgBLAObPn58jIyMcdebtfbX1pQ/8gHUXP7OvvCOH7rxe2lTXM1N19Gt0dJSRkZGNLj+b6nFeZl8dg6pnWOoYVD3DUockSVu6gXcrjYjtIuLxnc/AAuBK4Byg88TRRcDZ9fM5wKH1qaX7AXfX7qfnAwsiYof6IJoFNU2SJEmSNEkzceVwLnBWRHTq/0RmfjkiLgE+HRFHADcAh9T85wIHAiuA+4HDATJzTUScAFxS8x2fmWsGNxuSJEmSNDwGHhxm5nXAen0bM/MOYP8u6Qkc1WNaS4GlU91GSZIkSdrSzKZXWUiSJEmSZojBoSRJs0hErIyIKyLi8oi4tKbtGBHLI+La+neHmh4RcVJErIiIH0bEcxrTWVTzXxsRi3rVJ0lSh8GhJEmzz4sz81mZOb9+Pwa4IDPnARfU7wAvB+bVYTFwCpRgEjgW2JfyRPBjOwGlJEm9GBxKkjT7HQScWj+fChzcSD8ti4uA7evroA4Almfmmsy8E1gOLBx0oyVJmxeDQ0mSZpcEvhIRl0XE4po2t77GCeAWypO/AXYFbmyUXVXTeqVLktTTTLzKQpIk9fb8zFwdEb8CLI+IHzVHZmZGRE5FRTX4XAwwd+5cRkdHAdj7LQv6Kv/gdk/gJ/NftsF8q+p0mwZRxyDr6cfatWsf+Y2nyyDqGFQ9w1LHoOpxXmZfHYOqZyrrMDiUJGkWyczV9e9tEXEW5Z7BWyNil8y8uXYbva1mXw3s3ii+W01bDYy00ke71LUEWAIwf/78HBkpRY45+iN9tfXF71jAUy9dvsF8T3vDJ9ZLG0Qdg6ynH6Ojo3R+4+kyiDoGVc+w1DGoepyX2VfHoOqZyjrsVipJ0iwREdtFxOM7n4EFwJXAOUDniaOLgLPr53OAQ+tTS/cD7q7dT88HFkTEDvVBNAtqmiRJPXnlUJKk2WMucFZEQNlHfyIzvxwRlwCfjogjgBuAQ2r+c4EDgRXA/cDhAJm5JiJOAC6p+Y7PzDWDmw1J0ubI4FCSpFkiM68Dntkl/Q5g/y7pCRzVY1pLgaVT3UZJ0vCyW6kkSZL0/7d37+FV1Xe+x99fAxqQDAiCB8ERVEQklw0RBZV7EUQLihdEOBDwUhS1TEcrhZFTOLYDU3qqFY7WpyoWI1CCt9IZlAoIHeVOgkEEtYLctKhAgwbl8ps/1sp+AiE3stbe2Tuf1/PkyV5r/9bv+1t7sfPlu64iouJQREREREREVByKiIiIiIgIKg5FREREREQEFYciIiIiIiKCikMRERERERFBxaGIiIiIiIig4lBERERERERQcSgiIiIiIiKoOBQRERERERFUHIqIiIiIiAgqDkVERERERAQVhyIiIiIiIoKKQxEREREREUHFoYiIiIiIiKDiUERERERERFBxKCIiIiIiIqg4FBEREREREVQcioiIiIiICCoORUREREREBKgX7wGIiIiISN1z5MgRdu3axeHDh0/5fuPGjdmyZUuoY4hFjMripKam0rp1a+rXrx/6OEQqo+JQpBKVJa+aSpbkF2YMJU4RkeSza9cu0tLSaNOmDWZW5v2ioiLS0tJCHUMsYlQUxznHV199xa5du2jbtm3o4xCpjIpDkUpUlrxqKlmSX1gxlDhFRJLT4cOHQ8uticLMaNasGfv27Yv3UEQAXXMoUqnDhw/TrFmzOp284qkkcYZ15FZEROJHuVWfgdQuKg5FqkB/uONLn7+IiIhI+FQciiSg7du3k56eXuX2ubm57Nmzp9J2OTk55OXl1WRoIiIip+3qq6+O9xCqZPny5dx4443VWqZXr16sW7cupBGJBEPFoUgdUNXiUEREJJ7efffdeA9BpE5TcSiSoI4dO8Y999xDx44due666yguLiY/P5+uXbuSmZnJzTffzP79+8nLy2Pjxo0MHz6cSCRCcXEx69evp2fPnmRnZ9O/f3/27t0b79URERGhUaNGAOzdu5cBAwYQiURIT09n5cqV5S6zePFiOnfuTFZWFn379gVgzZo1dOvWjU6dOnH11VezdetWAGbPns2QIUMYMGAA7dq147HHHquwn2+++YYxY8Zw5ZVX0qlTJ15//fUy8ctrU1xczB133EGHDh248847KS4uDuZDEgmRikORBPXRkl5fugAAHJNJREFURx8xbtw4Nm/eTJMmTVi4cCEjR45k+vTpbNq0iYyMDKZMmcKtt95Kp06dyM3NJT8/n3r16vHggw+Sl5fH+vXrGTNmDJMmTYr36oiIiES9/PLL9O3bl/z8fAoKCohEIqdst2/fPu655x4WLlxIQUEBCxYsAOCyyy5j5cqVbNy4kalTpzJx4sToMvn5+cyfP5/333+fV155hZ07d5bbzy9+8Qv69OnDmjVrWLZsGY888gjffPPNCWMor83TTz9Nw4YN2bJlCxMnTmT9+vUhfVoiwdGjLEQSVNu2baPJMjs7m08++YQDBw7Qs2dPAEaNGsVtt91WZrmtW7dSWFhIv379AO8IZMuWLWM3cBERkUp06dKFnJwczjjjDG666aZyi8NVq1bRo0eP6KOOmjZtCsDBgwcZNWoUH330EWbGkSNHosv07duXxo0bA9C+fXt27NjB/v37T9nPW2+9xRtvvMGMGTMA7w7mn3322QljKK/NihUreOihhwBIT08nMzMzkM9GJEwqDkUS1FlnnRV9nZKSwoEDB6q0nHOOjh078t5774U1NBERkRrp0aMHixcv5p133iEnJ4ef/OQnjBw5ssrLP/bYY/Tu3ZtXX32V7du306tXr+h7J+fPo0ePltuPc46FCxfSvn37E+Z/8cUXlbYRSUQ6rVQkSTRu3Jhzzjknel3GnDlzokcRGzVqRFFREeDtJd23b1+0ODxy5AibN2+Oz6BFREROYceOHbRo0YJ77rmHu+++mw0bNpyyXdeuXVmxYgWffvopAF9//TXgHTls1aoV4F1nWJny+unfvz9PPfUUzjkANm7cWGbZ8tr06NGDl19+GYAPPviATZs2VWndReJJRw5FksiLL77I2LFj+fbbb7nooot44YUXABg+fDhjx46lQYMGvPfee+Tl5fHQQw9x8OBBjh49yvjx4+nYsWOcRy8iIuJZvnw506dP56yzzqJRo0b84Q9/OGW75s2b8+yzzzJkyBCOHz9OixYtWLJkCT/96U8ZNWoUjz/+ODfccEOl8crr57HHHmP8+PFkZmZy/Phx2rZty6JFi05Ytrw29913H6NHj6ZDhw60a9eO7OzsQD4bkTCpOBRJQG3atKGwsDA6/fDDD0dfr1q1qkz7wYMHM2LEiOh0JBJhxYoVZdpVZe+qiIhIWA4dOgR4180PGTKEtLS0Spe5/vrruf7660+Y161bN7Zt2xadfvzxxwHveb45OTnR+QsWLIjGOFU/DRo04He/+12ZmL169YqeqlpemwYNGjBv3jwAioqKqrQuIvGm00pFRERERERERw5FREREpPa76qqr+O67706YN2fOHDIyMuI0IpHko+JQRERERGq91atXx3sIIklPp5WKiIiIiIiIikMRERERERFRcSgiIiIiIiKoOBRJCCkpKUQiEdLT0/nhD3/IgQMHQou1ffv26EN7T/Veenr6CfN+/vOfM2PGjAr7nD17Nnv27Kk0dk5ODnl5eVUfrIiISIwtXryY9u3bc8kllzBt2rR4D0ckULohjUg1jVuwL9D+pg1IrbRNgwYNyM/PB7xnP82aNYtJkyYFOg6Ao0ePRovDO++8M7B+Z8+eTXp6Oueff35gfYqISN02IX1YoP1NK5xbaZtjx44xbtw4lixZQuvWrenSpQuDBg3i8ssvD3QsIvGiI4ciCaZbt27s3r0bgE8++YQBAwaQnZ1N9+7d+fDDDwHvob7p6elkZWXRo0cPAA4fPszo0aPJyMigU6dOLFu2DPAKt0GDBtGnTx/69u3LhAkTWLlyJZFIhN/85jfVGlt+fj5du3YlMzOTm2++mf3795OXl8e6desYPnw4kUiE4uJi1q9fT8+ePcnOzqZ///7s3bs3wE9IREQkHGvWrOGSSy7hoosu4swzz+SOO+7g9ddfj/ewRAKjI4ciCeTYsWO8/fbb3HXXXQDce++9PPPMM7Rr147Vq1dz//33s3TpUqZOncqbb75Jq1atoqegzpo1CzPj/fff58MPP+S6665j27ZtAGzYsIFNmzbRtGlTli9fzowZM1i0aNEpx/DJJ58QiUSi059//jkPP/wwACNHjuSpp56iZ8+eTJ48mSlTpvDEE08wc+ZMZsyYwRVXXMGRI0d48MEHef3112nevDnz589n0qRJPP/882F+dCIiIjW2e/duLrjgguh069at9YgNSSoqDkUSQHFxMZFIhN27d9OhQwf69evHoUOHePfdd7ntttui7UoeDnzNNdeQk5PD7bffzpAhQ0hJSeGvf/0rDz74IACXXXYZF154YbQ47NevH02bNq3SWC6++OLoKa7gXXMIcPDgQQ4cOEDPnj0B7/TX0mMrsXXrVgoLC+nXrx/gFbwtW7as5iciIiIiIkFTcSiSAEquOfz222/p378/s2bNIicnhyZNmpxQqJV45plnWL16NX/+85/Jzs5m+fLlFfZ/9tlnhzTyspxzdOzYkffeey9mMUVERILQqlUrdu7cGZ3etWsXrVq1iuOIRIKlaw5FEkjDhg357W9/y69//WsaNmxI27ZtWbBgAeAVXQUFBYB36udVV13F1KlTad68Obt376Z79+7k5uYCsG3bNj777DPat29fJkZaWhpFRUXVHlvjxo0555xzWLlyJQBz5syJHkUs3Wf79u3Zt29ftDg8cuQImzdvrnY8ERGRWOvSpQsfffQRn376Kd9//z3z5s1j0KBB8R6WSGBUHIokmE6dOpGZmcncuXPJzc3lueeeIysri44dO0Yvin/kkUfIyMggPT2dq6++moyMDO6//36OHz9ORkYGQ4cOZfbs2Zx11lll+s/MzCQlJYWsrKxq35DmxRdf5JFHHiEzM5P8/HwmT54MeI+oGDt2LJFIhGPHjpGXl8ejjz5KVlYWkUiEd999t+YfjIiISMjq1avHzJkz6d+/Px06dOD222+nY8eO8R6WSGB0WqnUKlV9TMRtzUMeSAVmBRy8KkfpDh06dML0n/70p+jrxYsXl2n/yiuvlImRmprKCy+8UKZtTk4OOTk50en69euzdOnSU46jTZs2FBYWnjCv5JrDoqIiIpEIq1atKrPcLbfcwi233BKdjkQirFixoky72bNnnzKuiIjIyary6InKFBUVkZaWVq1lBg4cyMCBA2scW6Q20pFDERERERERUXEoIiIiIiIiKg5FREREREQEFYciIiIiIiKCikMRERERERFBxaGIiIiIiIigR1mIJITPP/+c8ePHs3btWpo0acJ5553HE088QaNGjXjooYfIy8sjPz+fPXv2VOv22rNnz2bdunXMnDkzOq9Xr17MmDGDK664otzlfvnLXzJx4sRK+2/Tpg3r1q3j3HPPrfKYRESkrAnpw6rUbsDMH4U8krptzJgxLFq0iBYtWpR5tJNIMlBxKFJNC8ZV7VmMVTVgWmqF7zvnuPnmmxk1ahTz5s0DoKCggC+++IJLL72UvLw8APLz81m3bl1Mnr1U1eJQREQkLB//+M5A+vnC/33Jky9X2jYnJ4cHHniAkSNHBhJbpLbRaaUitdyyZcuoX78+Y8eOjc7Lysqie/fubN++nfT0dL7//nsmT57M/PnziUQizJ8/n3bt2rFvn1fIHj9+nEsuuSQ6XVVz584lIyOD9PR0Hn30UQAmTJhAcXExkUiE4cOHA/DSSy/Rq1cvIpEIP/rRjzh27FhAay8iIlJ79OjRg6ZNm8Z7GCKhUXEoUssVFhaSnZ1dYZszzzyTqVOnMnToUPLz8xk6dCgjRowgNzcX8ArMrKwsmjdvXmbZkoKy5GfdunUA7Nmzh0cffZSlS5eSn5/P2rVree2115g2bRoNGjQgPz+f3NxctmzZwvz581myZAn5+fmkpKRE44qIiIhI4tBppVIl4xZU7YjTbWVrD4mTMWPGMHjwYMaPH8+cOXMYPXr0KdsNHTq0zDWHAGvXrqVXr17RgnL48OGsWLGCm2666YTl3377bdavX0+vXr0444wzKC4upkWLFuGslIiIiIiERsWhSC3XsWPH6HWF1XHBBRdw3nnnsXTpUjZs2MAf//jHEEbnXRM5atQoJk6cSFpaWigxRERERCR8Oq1UpJbr06cP3333Hc8++2x03qZNm1i5cuUJ7dLS0igqKjph3t13382IESO46aabSElJqVbcK6+8knfeeYcvv/ySY8eOMXfuXHr27AlA/fr1OXLkCAB9+/YlLy8vej3j119/zY4dO6q9niIiIiISXzpyKFLLmRmvvvoq48ePZ/r06aSmptKmTRueeOKJE9r17t2badOmEYlE+NnPfsbQoUMZNGgQo0ePZsSIEdWO27JlS6ZNm0bv3r1xznHDDTcwePBgAO69914yMzPp3Lkzubm5PP7449HTTevXr8+sWbO48MILa77yIiIJQI+ZqDuGDRvG8uXL+fLLL2ndujVTpkzhrrvuivewRAKj4lCkmm6bFeyFlScf7TuV888/v9zTQkues9S0aVPWrl17wnsFBQVkZWVx6aWXnnLZnJwccnJyTpi3fPny6Othw4YxbFjZ//RMnz6d6dOnR6eHDh3KwIEDy5xWun379vJWSUREpEaq8uiJyhQVFVXrkoi5c+fWOKZIbabiUCRJTZs2jaefflp3DhURERGRKtE1hyJJasKECezYsYNrr7023kMRERERkQSgI4ciIiIiSeK7nZ/y8Y+frbwhwZyWKSLJRUcORarAORfvIdRp+vxFRJKT/r7rM5DaRUcORSqRmprKV199RbNmzTCzeA+nznHO8dVXX5GamhrvoYiI1EhVj+rVlSN6yq/KcVL7qDiUQO3/7CgLxu2rUtua3PWzqnGCuLNo69at2bVrV/Q5fkE7fPhw6Ekh0WOkpqbSunXrUPoWEZH4qCy/Jnruqmoc5TipTRK+ODSzAcCTQArwe+fctDgPSZJM/fr1adu2bWj9L1++nE6dOoXWfzLFEJHqUY6U2qyy/JpMuUs5UhJFQl9zaGYpwCzgeuByYJiZXR7fUYmIiMSfcqSIiFRXQheHwJXAx865vznnvgfmAYPjPCYREZHaQDlSRESqJdFPK20F7Cw1vQu4Kk5jkQQxbkHVrh38QfHpX9dY1Rg1jRMLsfi8RCQUypFSbRPSh1WpXe9Hrzvtm+vEIkasJNO6iABYIt8+18xuBQY45+72p/83cJVz7oGT2t0L3OtPtge2ViPMucCXAQy3NsRJlhixiqN1qX0xYhUnWWLEKk5tjXGhc67O7o2oSo6sYX6E2rvta2ucZIkRqzjJEiNWcbQutS9GrOIEliMT/cjhbuCCUtOt/XkncM49C1TtibAnMbN1zrkrTm94tStOssSIVRytS+2LEas4yRIjVnGSJUYSqjRH1iQ/QnJt+2RZF31etS9GrOJoXWpfjFjFCTJGol9zuBZoZ2ZtzexM4A7gjTiPSUREpDZQjhQRkWpJ6COHzrmjZvYA8Cbebbqfd85tjvOwRERE4k45UkREqiuhi0MA59x/Av8ZYojTPt2mFsZJlhixiqN1qX0xYhUnWWLEKk6yxEg6SZIj9V2pfTFiFSdZYsQqjtal9sWIVZzAYiT0DWlEREREREQkGIl+zaGIiIiIiIgEQMVhBcxsgJltNbOPzWxCSDGeN7O/m1lhGP37MS4ws2Vm9oGZbTazH4cQI9XM1phZgR9jStAxSsVKMbONZrYoxBjbzex9M8s3s3UhxWhiZnlm9qGZbTGzbiHEaO+vQ8nPP8xsfAhx/sXf7oVmNtfMUkOI8WO//81BrsOpvoNm1tTMlpjZR/7vc0KI8St/228ys1fNrElNYlQQ5//6MfLN7C0zOz/oGKXe+1czc2Z2bhgxzOxB/zPbbGb/UZMYUjPKj9WOkzQ5Mhb50Y8Tao5Mpvzoxwk8R8YiP1YQJ9AcmSz5saI4geVI55x+TvGDd/H+J8BFwJlAAXB5CHF6AJ2BwhDXpSXQ2X+dBmwLel0AAxr5r+sDq4GuIa3PT4CXgUUhfmbbgXPD6t+P8SJwt//6TKBJyPFSgM/xnmsTZL+tgE+BBv70H4GcgGOkA4VAQ7xrpf8CXBJQ32W+g8B/ABP81xOA6SHEuA6o57+eXtMYFcT5p1KvHwKeCTqGP/8CvBuf7Kjpd6ec9ejtb/ez/OkWQf4b00+1to/yY/XjJE2OjEV+9OPELEcmcn70+w0lR8YiP1YQJ9AcmSz5sYJ1CSxH6shh+a4EPnbO/c059z0wDxgcdBDn3Arg66D7PSnGXufcBv91EbAF7w9WkDGcc+6QP1nf/wn8glYzaw3cAPw+6L5jycwa4325nwNwzn3vnDsQcti+wCfOuR0h9F0PaGBm9fCS056A++8ArHbOfeucOwq8AwwJouNyvoOD8f5jgv/7pqBjOOfe8tcFYBXeM+hqpJw4/yg1eTY1/F5W8DfrN8BPa9p/BTHuA6Y5577z2/y9pnHktCk/Vj+OcmQ1xCFHJnJ+hJByZCzyY3lxgs6RyZIfK4gTWI5UcVi+VsDOUtO7CCFhxJqZtQE64e21DLrvFDPLB/4OLHHOBR4DeALvC3Y8hL5Lc8BbZrbezO4Nof+2wD7gBf/0n9+b2dkhxCntDmBu0J0653YDM4DPgL3AQefcWwGHKQS6m1kzM2sIDOTEh3sH7Tzn3F7/9efAeSHGAhgD/FdYnZvZL8xsJzAcmBxC/4OB3c65gqD7LuVSvH8Dq83sHTPrEmIsqZjy4+n1nyw5Muz8CLHPkYmcHyG2OTLW+RFCzJFJkh8hwByp4rAOMbNGwEJg/El7SwLhnDvmnIvg7d250szSg+zfzG4E/u6cWx9kv+W41jnXGbgeGGdmPQLuvx7eKQFPO+c6Ad/gnZ4RCvMegD0IWBBC3+fg7UlsC5wPnG1mI4KM4ZzbgndayVvAYiAfOBZkjApiO0LYw1/CzCYBR4HcsGI45yY55y7wYzwQZN/+f0QmEkJSPUk9oCnQFXgE+KOZWcgxpY4IOz9CUuXIsPMjxDBHJnp+hPjlyLDzI4SfI5MkP0KAOVLFYfl2c+Jel9b+vIRkZvXxEl+uc+6VMGP5p34sAwYE3PU1wCAz2453GlMfM3sp4BhAdG9fyWH5V/FOowrSLmBXqT3HeXiJMCzXAxucc1+E0PcPgE+dc/ucc0eAV4Crgw7inHvOOZftnOsB7Me7NigsX5hZSwD/dyinMJpZDnAjMNxPsmHLBW4JuM+L8f7jU+B/N1sDG8zsfwUcZxfwin963hq8IyM1vrBfTovyYw0keo6MQX6E2ObIhM+PENMcGZP86PefQ+xyZCLnRwgwR6o4LN9aoJ2ZtfX3Kt0BvBHnMZ0Wf8/Bc8AW59z/CylG85I7SZlZA6Af8GGQMZxzP3POtXbOtcHbHkudc4HvgTOzs80sreQ13kXRgd4tzzn3ObDTzNr7s/oCHwQZ4yTDCOGUGd9nQFcza+j/W+uLd91OoMyshf/7n/GupXg56BilvAGM8l+PAl4POoCZDcA7/WuQc+7boPsvFaddqcnBBP+9fN8518I518b/bu7Cu8HH50HGAV7Du+AeM7sU7wYVXwYcQ6pG+bH6cZIiR8YiP0LMc2TC50eIaY4MPT9CbHJkEuVHCDJHuhreMSeZf/DO2d6Gd1e2SSHFmIt3HvoRvH80d4UQ41q8w/6b8E41yAcGBhwjE9joxygEJoe8bXoR3p3YLsK7+14BsDnEbR8B1vmf2WvAOSHFORv4Cmgc4vaYgvdHtRCYg3+3rIBjrMT7z0EB0DfAfst8B4FmwNvAR3h3/2oaQoyP8a7bKvlO1uguaRXEWehvl03An4BWQcc46f3t1PxupadajzOBl/x12QD0Cevfs36qtI2UH6sXJylyZKzyox8r9ByZLPnRjxN4joxFfqwgTqA5MlnyYwXrEliOND+IiIiIiIiI1GE6rVRERERERERUHIqIiIiIiIiKQxEREREREUHFoYiIiIiIiKDiUERERERERFBxKCIiIiIiIqg4lDrOzMabWcMYxJlqZj8IO04VxtHGzAJ/YLGZzTazW09juUFmNqGSNr3MbFE578Vk+4mI1EXKkYH1qxwpCUPFodR144HQ/3A65yY75/4SdpxE45x7wzk3rQZdxGT7iYjUUcqRcaQcKfGg4lDqDDM728z+bGYFZlZoZv8HOB9YZmbL/DZPm9k6M9tsZlP8eX3M7LVS/fQzs1fNLMXfG1hoZu+b2b9UEDu619DMtpvZFDPb4C93WQXLvW9mTczzlZmN9Of/wR9Hipn9yszWmtkmM/tRqWUfKTV/yin6vsjMNppZFzO72MwWm9l6M1tZMiZ/3L81s3fN7G+l1sHMbKaZbTWzvwAtKvnsT7nOZpZjZjP91xeb2Sr//cfN7FCpLhqZWZ6ZfWhmuX78h0pvv+psDxEROZFyZJm+lSOlTlJxKHXJAGCPcy7LOZcOPAHsAXo753r7bSY5564AMoGeZpYJLAMuM7PmfpvRwPNABGjlnEt3zmUAL1RjLF865zoDTwMPV9Duv4FrgI7A34Du/vxuwLvAXcBB51wXoAtwj5m1NbPrgHbAlf44s82sR0mnZtYeWAjkOOfWAs8CDzrnsv3x/P9SY2gJXAvcCJTswbwZaA9cDowErg5gnZ8EnvQ/y10nvdcJbw/o5cBFwDXOud9y4varyfYQEanrlCN9ypFSl6k4lLrkfaCfmU03s+7OuYOnaHO7mW0ANuIlm8udcw6YA4wwsyZ4See/8BLRRWb2lJkNAP5RjbG84v9eD7SpoN1KoIf/8zSQYWatgP3OuW+A64CRZpYPrAaa4SW86/yfjcAG4DJ/PkBz4HVguHOuwMwa4SWuBX4/v8NLdiVec84dd859AJznz+sBzHXOHXPO7QGWBrDO3YAF/uuXT3pvjXNul3PuOJBfzvI12R4iInWdcqRHOVLqtHrxHoBIrDjntplZZ2Ag8LiZvV36fTNri7e3rotzbr+ZzQZS/bdfAP4EHAYWOOeOAvvNLAvoD4wFbgfGVHE43/m/j1Hx93AFMA74Z2AS3t7IW/ESIoDh7c1886R16Q/8u3PudyfNbwMcBD7D29P5Ad5OogPOuUglYy2Jd7qqus6VjeGUy/vb7HS3h4hInaYcqRwpAjpyKHWImZ0PfOucewn4FdAZKALS/Cb/BHwDHDSz84DrS5b19/ztAf4N/1QMMzsXOMM5t9Cf3znoMTvndgLnAu2cc38D/oqXnFf4Td4E7jOz+v6YLjWzs/35Y/w9nphZKzMruebhe7wEOtLM7nTO/QP41Mxu89uan0AqsgIY6l/D0BLoXUn7qlgF3OK/vqOKy0S3Xyy2h4hIslKOVI4UAR05lLolA/iVmR0HjgD34Z2msdjM9jjnepvZRuBDYCfetQyl5QLNnXNb/OlWwAtmVrKT5WchjXs1kOK/Xgn8O14CBPg93ukjG8zMgH3ATc65t8ysA/CeN5tDwAi8PYo4574xsxuBJf5F7cOBp83s34D6wDygoIIxvQr0wdur+hnwXgDrOR54ycwmAYvx9t5W5ln87ecvH4vtISKSjJQjlSNFMO9UcRGpjHl3DNvonHsu3mNJRuY9i6nYOefM7A5gmHNucLzHJSIilVOODJdypMSKjhyKVIGZrcc7neZf4z2WJJYNzPT37h5A10KIiCQE5ciYUI6UmNCRQ5EAmdksvNtql/akc67CW0ab2WjgxyfN/m/n3Lggxxc2M3sVaHvS7EdPvhmAiIjUPcqRypFS+6k4FBEREREREd2tVERERERERFQcioiIiIiICCoORUREREREBBWHIiIiIiIigopDERERERERAf4HLV4G0OHJCv0AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nup9skPZJXvk"
      },
      "source": [
        "More number People prefer to stay at city hotel in weekend for 0,1 and 2 nights\n",
        "\n",
        "People staying for more than 2 night prefer to stay in Resort hotel\n",
        "\n",
        "In next graph we can see that we have less number of cancellation of booking for weekends"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KvrAbQhfJgbr"
      },
      "source": [
        "**Analysis no. 14**\n",
        "\n",
        "How many adults and childs guests arrived per month in each hotels?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TNBKK5p3LF_f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 861
        },
        "outputId": "48a83263-5ec5-4892-8277-0f0697881fc5"
      },
      "source": [
        "#Total bookings\n",
        "total_bookings = hotel_data_copy.groupby(['hotel','arrival_date_month'])['adults','childs'].sum().reset_index()\n",
        "total_bookings"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: FutureWarning:\n",
            "\n",
            "Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
            "\n"
          ]
        },
        {
          "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>arrival_date_month</th>\n",
              "      <th>adults</th>\n",
              "      <th>childs</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>April</td>\n",
              "      <td>9805</td>\n",
              "      <td>785.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>August</td>\n",
              "      <td>13188</td>\n",
              "      <td>1532.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>December</td>\n",
              "      <td>5688</td>\n",
              "      <td>522.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>February</td>\n",
              "      <td>6576</td>\n",
              "      <td>518.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>January</td>\n",
              "      <td>4801</td>\n",
              "      <td>333.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>July</td>\n",
              "      <td>11535</td>\n",
              "      <td>1201.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>June</td>\n",
              "      <td>9447</td>\n",
              "      <td>575.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>March</td>\n",
              "      <td>8989</td>\n",
              "      <td>462.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>May</td>\n",
              "      <td>9993</td>\n",
              "      <td>493.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>November</td>\n",
              "      <td>4999</td>\n",
              "      <td>182.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>October</td>\n",
              "      <td>7566</td>\n",
              "      <td>450.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>City Hotel</td>\n",
              "      <td>September</td>\n",
              "      <td>7623</td>\n",
              "      <td>382.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>April</td>\n",
              "      <td>5049</td>\n",
              "      <td>376.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>August</td>\n",
              "      <td>9463</td>\n",
              "      <td>1400.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>December</td>\n",
              "      <td>3711</td>\n",
              "      <td>273.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>February</td>\n",
              "      <td>4367</td>\n",
              "      <td>309.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>January</td>\n",
              "      <td>3237</td>\n",
              "      <td>157.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>July</td>\n",
              "      <td>8617</td>\n",
              "      <td>1205.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>June</td>\n",
              "      <td>5278</td>\n",
              "      <td>517.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>March</td>\n",
              "      <td>4541</td>\n",
              "      <td>276.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>May</td>\n",
              "      <td>5449</td>\n",
              "      <td>406.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>November</td>\n",
              "      <td>3459</td>\n",
              "      <td>125.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>October</td>\n",
              "      <td>5015</td>\n",
              "      <td>280.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Resort Hotel</td>\n",
              "      <td>September</td>\n",
              "      <td>4879</td>\n",
              "      <td>283.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           hotel arrival_date_month  adults  childs\n",
              "0     City Hotel              April    9805   785.0\n",
              "1     City Hotel             August   13188  1532.0\n",
              "2     City Hotel           December    5688   522.0\n",
              "3     City Hotel           February    6576   518.0\n",
              "4     City Hotel            January    4801   333.0\n",
              "5     City Hotel               July   11535  1201.0\n",
              "6     City Hotel               June    9447   575.0\n",
              "7     City Hotel              March    8989   462.0\n",
              "8     City Hotel                May    9993   493.0\n",
              "9     City Hotel           November    4999   182.0\n",
              "10    City Hotel            October    7566   450.0\n",
              "11    City Hotel          September    7623   382.0\n",
              "12  Resort Hotel              April    5049   376.0\n",
              "13  Resort Hotel             August    9463  1400.0\n",
              "14  Resort Hotel           December    3711   273.0\n",
              "15  Resort Hotel           February    4367   309.0\n",
              "16  Resort Hotel            January    3237   157.0\n",
              "17  Resort Hotel               July    8617  1205.0\n",
              "18  Resort Hotel               June    5278   517.0\n",
              "19  Resort Hotel              March    4541   276.0\n",
              "20  Resort Hotel                May    5449   406.0\n",
              "21  Resort Hotel           November    3459   125.0\n",
              "22  Resort Hotel            October    5015   280.0\n",
              "23  Resort Hotel          September    4879   283.0"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2zYLwDQfLhYA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a3759e28-5185-4c84-bc12-b7904ed5a6e5"
      },
      "source": [
        "# Only Resort bookings\n",
        "resort = total_bookings.loc[(total_bookings[\"hotel\"] == \"Resort Hotel\")]\n",
        "# Sort arrival date month column by month wise\n",
        "resort['arrival_date_month'] = pd.Categorical(resort['arrival_date_month'], ['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December'])\n",
        "resort.sort_values(by = 'arrival_date_month',inplace=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning:\n",
            "\n",
            "\n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:5: SettingWithCopyWarning:\n",
            "\n",
            "\n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fslSI7GvLsSO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2b185cc1-6341-46c5-83e0-61ec6016ba02"
      },
      "source": [
        "print(resort['adults'].max())\n",
        "print(resort['childs'].max())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "9463\n",
            "1400.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rRTZKOJGLxd3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 404
        },
        "outputId": "6e4728aa-9904-4aff-80c3-726658797f23"
      },
      "source": [
        "#Line plot for finding the number of adults and kids -Resort hotel\n",
        "resort.plot(x = 'arrival_date_month',y= ['adults','childs'],figsize=(10, 6), title = 'Number of adults and childs arrival per month in Resort', xlabel = 'Arrival Date', ylabel = 'Number of guest');"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "N9U8XwYR5vKN"
      },
      "source": [
        "Based on the line chart the adults are highly recommend to visit in the Resort Hotel, right from June month to August we have highest number of Adults. \n",
        "The childs are least to visit in Resort Hotel with their family. Throughout all the months the number of childs are normal according to data but from June month to August month the guest number of childs are increasing gradually.  "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QunEPTb7MEG3"
      },
      "source": [
        "# Business Perspective problem statement"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j1L0-THcMqWs"
      },
      "source": [
        "**Analysis no. 15**\n",
        "\n",
        "Booking and cancellation per market segment ?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bsz1573gMt4w",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 343
        },
        "outputId": "3b4173c0-c7a5-4bd3-a978-1f455c7b3b31"
      },
      "source": [
        "plt.figure(figsize=(18,10))\n",
        "plt.subplot(211)\n",
        "sns.countplot(data=hotel_data_copy,x='deposit_type',hue='market_segment')\n",
        "plt.title('Deposit Type for Market Segment')\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Deposit Type for Market Segment')"
            ]
          },
          "metadata": {},
          "execution_count": 140
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pXXQprdX7zis"
      },
      "source": [
        "We can see from above graph 1 that most the bookings are done through Online TA segment."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6oau6PUzNMJr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 326
        },
        "outputId": "279b60b5-e623-45fa-fea6-1f204cea8e87"
      },
      "source": [
        "plt.subplot(212)\n",
        "sns.countplot(data=hotel_data_copy,x='is_canceled',hue='market_segment')\n",
        "plt.title('Cancellation for Market Segment')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Qfe4SfR7NVtq"
      },
      "source": [
        "The above graph shows that most cancellation is also done through online TA segment only. So it precise clearly more about online TA to look up to market segment."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e-Sfnq15NYrX"
      },
      "source": [
        "**Analysis no. 16**\n",
        "\n",
        "Lets see how ADR(average daily rate) change over year, so that we can understand hotel industry is growing by renting their room.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0iJUAQ7VOf4R"
      },
      "source": [
        "\n",
        "Higher the ADR or rising ADR mean hotel is making money through renting , we can see in this bar plot that revenue generated by hotel industry is increasing year by year and also we can say that for each year the revenue is increasing till August month and after August the revenue is decreasing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AZI-CevbOhwN"
      },
      "source": [
        "# doing groupby operation to find average ADR for each year by hotel wise\n",
        "mean_adr_of_resort_city_hotel=hotel_data_copy.groupby(['hotel','arrival_date_year'])['adr'].mean().unstack()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fwkGHE7bO57f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 464
        },
        "outputId": "7b9d746e-c983-4e02-8034-6e317176d91d"
      },
      "source": [
        "# plotting bar plot for both hotels mean average daily rate by year wise\n",
        "ax=mean_adr_of_resort_city_hotel.plot.bar(figsize=(10,5),fontsize=16)\n",
        "ax.set_title('Mean ADR of city and resort hotel of year 2015,2016,2017 ',fontsize=16)\n",
        "ax.set_xlabel('Month_name',fontsize=15)\n",
        "ax.set_ylabel('MEAN ADR',fontsize=15)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'MEAN ADR')"
            ]
          },
          "metadata": {},
          "execution_count": 145
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "765L6r6wPHPK"
      },
      "source": [
        "In city hotel the growth in average daily rate is increasing year by year ,its mean that the hotel is growing their revenue year by year by renting room. In resort hotel also if we talk about year 2015 and year 2017 then growth is visible in bar chart."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mzKmMyR6PQ7s"
      },
      "source": [
        "**Analysis no. 17**\n",
        "\n",
        "Which is the most preferred business segment ?\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5qz6eQI0QLjI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 492
        },
        "outputId": "d73b612b-ddc6-4ecc-b378-772fa698cfea"
      },
      "source": [
        "# This is a Count plot for finding most prefered market segment \n",
        "fig_dims = (15, 6)\n",
        "fig, ax = plt.subplots(figsize=fig_dims)\n",
        "sns.countplot(hotel_data_copy.market_segment,hue= hotel_data_copy.hotel,ax=ax).set(title = 'Mostly prefered Hotel with respect to market Segment', xlabel = 'Market segmet' , ylabel ='Total Booking');"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning:\n",
            "\n",
            "Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gxAiYqpeB-ff"
      },
      "source": [
        "In the above graph , we observe that\n",
        "\n",
        "*   Online TA , has most no. of hotel Bookings, where they Mostly prefer City Hotel over Resort Hotel. (i.e booking done for City Hotel is almost 35000 & for Resort hotel it is almost half i.e 16000 bookings)\n",
        "*   Followed by Offline TA/TO  Where they also slightly prefer city Hotel more than Resort Hotel.\n",
        "*   Then Comes in line the Direct Market Segment and they prefer Resort hotel than City hotel.\n",
        "*   Later inline we have Groups, Corporate And Complementary Market Segments where they all slightly prefer city hotel over resort hotel.\n",
        "*   last in the line we have Aviation market segment where they only prefer city Hotel.\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yNlSou1iQoZt",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "55e227f7-e988-4bc9-9217-9d2311697495"
      },
      "source": [
        "hotel_data_copy.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(86913, 29)"
            ]
          },
          "metadata": {},
          "execution_count": 149
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s-Evhv_aQrI1"
      },
      "source": [
        "For both type of hotel, customer prefer 'online TA' segment for booking"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "75UhvI4RQtx2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7d7ec490-4fc4-43b1-eb7f-a09beafbef50"
      },
      "source": [
        "# Total booking done by Online TA\n",
        "hotel_data_copy.loc[hotel_data_copy['market_segment']=='Online TA'].hotel.value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "City Hotel      34984\n",
              "Resort Hotel    16549\n",
              "Name: hotel, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 151
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qZ32juZCeINo"
      },
      "source": [
        "# Conclusion\n",
        "\n",
        "That's how we have accomplished our team work in Hotel Booking Analysis project.\n",
        "\n",
        "Throughout the project we learn many new things right from taking problem statement to understand the technical side of a product to analysis. We deal with missing data and outliers, we tested some of the fundamental statistical assumptions. Python has helped a lot to understand with libraries. \n",
        "\n",
        " To deal with those data was really fun with many different analysis. Data cleaning and dealing with duplicate value was also most important to deal with correct methodology. Understand the dataset and predicting the solution of the problem from team work was also great big task. \n",
        "\n",
        " Hotel Booking Analysis helps hotel industry for marketing strategy, building customer loyalty, and enhancing productivity. It enables hotels to personalize experiences for their guests, introduce better hotel pricing strategies, and expand their customer base. It makes positive industry because -\n",
        "\n",
        "- Customer Data Analysis & Market Segmentation\n",
        "- Real-Time Data and Hotel Pricing Strategies\n",
        "- Managing Hotel Booking Channels\n",
        "and many more we can do to scale up in hotel industry.\n",
        "\n",
        "While working in the exploratory data analysis with team also helps us to work in team collaboration that shows how we should approach and divide a task. Maintaining a discipline in the task and precise to every point what we conclude."
      ]
    }
  ]
}