source_code.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "768be12c-8834-407e-9b58-b1c7941f9ee7",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "# Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b748374e-cbe5-4584-ad58-ff69b168e621",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bd4649c3-6f7a-457c-8e3b-4cb157aeecc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f83b9b1-7e9e-457d-833b-ab65ecd33add",
   "metadata": {},
   "source": [
    "## Load Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "15ec3486-5ecf-42e3-89b1-3bc9630d0eaf",
   "metadata": {},
   "outputs": [
    {
     "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_weekdays_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>...</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",
       "    </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>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>737</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>304.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>No Deposit</td>\n",
       "      <td>240.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Check-Out</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          hotel  is_canceled  lead_time  arrival_date_year arrival_date_month  \\\n",
       "0  Resort Hotel            0        342               2017          September   \n",
       "1  Resort Hotel            0        737               2017          September   \n",
       "2  Resort Hotel            0          7               2017          September   \n",
       "3  Resort Hotel            0         13               2017          September   \n",
       "4  Resort Hotel            0         14               2017          September   \n",
       "\n",
       "   arrival_date_week_number  arrival_date_day_of_month  \\\n",
       "0                        27                          1   \n",
       "1                        27                          1   \n",
       "2                        27                          1   \n",
       "3                        27                          1   \n",
       "4                        27                          1   \n",
       "\n",
       "   stays_in_weekend_nights  stays_in_weekdays_nights  adults  ...  \\\n",
       "0                        0                         0       2  ...   \n",
       "1                        0                         0       2  ...   \n",
       "2                        0                         1       1  ...   \n",
       "3                        0                         1       1  ...   \n",
       "4                        0                         2       2  ...   \n",
       "\n",
       "   booking_changes  deposit_type  agent company days_in_waiting_list  \\\n",
       "0                3    No Deposit    NaN     NaN                    0   \n",
       "1                4    No Deposit    NaN     NaN                    0   \n",
       "2                0    No Deposit    NaN     NaN                    0   \n",
       "3                0    No Deposit  304.0     NaN                    0   \n",
       "4                0    No Deposit  240.0     NaN                    0   \n",
       "\n",
       "  customer_type   adr  required_car_parking_spaces  total_of_special_requests  \\\n",
       "0      Personal   0.0                            0                          0   \n",
       "1      Personal   0.0                            0                          0   \n",
       "2      Personal  75.0                            0                          0   \n",
       "3      Personal  75.0                            0                          0   \n",
       "4      Personal  98.0                            0                          1   \n",
       "\n",
       "   reservation_status  \n",
       "0           Check-Out  \n",
       "1           Check-Out  \n",
       "2           Check-Out  \n",
       "3           Check-Out  \n",
       "4           Check-Out  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#load dataset from local\n",
    "df = pd.read_csv('hotel_bookings_data.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a735e75a-56c8-43a7-872b-e5e986cf3272",
   "metadata": {},
   "source": [
    "## Descriptive Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "91be1f9b-d716-40e6-b281-dd7a0e855583",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "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_weekdays_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  city                            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  booking_changes                 119390 non-null  int64  \n",
      " 20  deposit_type                    119390 non-null  object \n",
      " 21  agent                           103050 non-null  float64\n",
      " 22  company                         6797 non-null    float64\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",
      "dtypes: float64(4), int64(16), object(9)\n",
      "memory usage: 26.4+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ac36e44-59cd-49ab-a0c4-6406e1eab845",
   "metadata": {},
   "source": [
    "## Handle Missing Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b5e6e6d3-0fb5-4667-b981-4444c799a586",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "company                           112593\n",
       "agent                              16340\n",
       "city                                 488\n",
       "children                               4\n",
       "hotel                                  0\n",
       "is_repeated_guest                      0\n",
       "total_of_special_requests              0\n",
       "required_car_parking_spaces            0\n",
       "adr                                    0\n",
       "customer_type                          0\n",
       "days_in_waiting_list                   0\n",
       "deposit_type                           0\n",
       "booking_changes                        0\n",
       "previous_bookings_not_canceled         0\n",
       "previous_cancellations                 0\n",
       "market_segment                         0\n",
       "distribution_channel                   0\n",
       "is_canceled                            0\n",
       "meal                                   0\n",
       "babies                                 0\n",
       "adults                                 0\n",
       "stays_in_weekdays_nights               0\n",
       "stays_in_weekend_nights                0\n",
       "arrival_date_day_of_month              0\n",
       "arrival_date_week_number               0\n",
       "arrival_date_month                     0\n",
       "arrival_date_year                      0\n",
       "lead_time                              0\n",
       "reservation_status                     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check null values\n",
    "df.isnull().sum().sort_values(ascending = False) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4d58d522-cb1d-423a-bd8f-150f7295460e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "company                           94.306893\n",
       "agent                             13.686238\n",
       "city                               0.408744\n",
       "children                           0.003350\n",
       "hotel                              0.000000\n",
       "is_repeated_guest                  0.000000\n",
       "total_of_special_requests          0.000000\n",
       "required_car_parking_spaces        0.000000\n",
       "adr                                0.000000\n",
       "customer_type                      0.000000\n",
       "days_in_waiting_list               0.000000\n",
       "deposit_type                       0.000000\n",
       "booking_changes                    0.000000\n",
       "previous_bookings_not_canceled     0.000000\n",
       "previous_cancellations             0.000000\n",
       "market_segment                     0.000000\n",
       "distribution_channel               0.000000\n",
       "is_canceled                        0.000000\n",
       "meal                               0.000000\n",
       "babies                             0.000000\n",
       "adults                             0.000000\n",
       "stays_in_weekdays_nights           0.000000\n",
       "stays_in_weekend_nights            0.000000\n",
       "arrival_date_day_of_month          0.000000\n",
       "arrival_date_week_number           0.000000\n",
       "arrival_date_month                 0.000000\n",
       "arrival_date_year                  0.000000\n",
       "lead_time                          0.000000\n",
       "reservation_status                 0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum().sort_values(ascending = False)/len(df)*100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a935eea7-cb00-4188-93d2-c15edc9a527a",
   "metadata": {},
   "source": [
    "There are null values in `children`, `city`, `agent`, `company` columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5494cd69-5f9a-484d-bfef-b3bd945e1060",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>children</th>\n",
       "      <th>agent</th>\n",
       "      <th>company</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>119386.000000</td>\n",
       "      <td>103050.000000</td>\n",
       "      <td>6797.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.103890</td>\n",
       "      <td>86.693382</td>\n",
       "      <td>189.266735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.398561</td>\n",
       "      <td>110.774548</td>\n",
       "      <td>131.655015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>62.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>179.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>229.000000</td>\n",
       "      <td>270.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>535.000000</td>\n",
       "      <td>543.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            children          agent      company\n",
       "count  119386.000000  103050.000000  6797.000000\n",
       "mean        0.103890      86.693382   189.266735\n",
       "std         0.398561     110.774548   131.655015\n",
       "min         0.000000       1.000000     6.000000\n",
       "25%         0.000000       9.000000    62.000000\n",
       "50%         0.000000      14.000000   179.000000\n",
       "75%         0.000000     229.000000   270.000000\n",
       "max        10.000000     535.000000   543.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "null_numericals = ['children', 'agent', 'company']\n",
    "df[null_numericals].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "73bb365c-30f8-425d-a782-50244d4cded8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>118902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Kota Denpasar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>48590</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                 city\n",
       "count          118902\n",
       "unique            177\n",
       "top     Kota Denpasar\n",
       "freq            48590"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "null_categoricals = ['city']\n",
    "df[null_categoricals].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4cbb5265-a6b4-407c-bf87-f3c1004f659f",
   "metadata": {},
   "outputs": [
    {
     "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_weekdays_nights          0\n",
       "adults                            0\n",
       "children                          0\n",
       "babies                            0\n",
       "meal                              0\n",
       "city                              0\n",
       "market_segment                    0\n",
       "distribution_channel              0\n",
       "is_repeated_guest                 0\n",
       "previous_cancellations            0\n",
       "previous_bookings_not_canceled    0\n",
       "booking_changes                   0\n",
       "deposit_type                      0\n",
       "agent                             0\n",
       "company                           0\n",
       "days_in_waiting_list              0\n",
       "customer_type                     0\n",
       "adr                               0\n",
       "required_car_parking_spaces       0\n",
       "total_of_special_requests         0\n",
       "reservation_status                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#impute missing values with 0 for numericals and Unknown for categoricals\n",
    "df['children'].fillna(0, inplace = True)\n",
    "df['agent'].fillna(0, inplace = True) \n",
    "df['company'].fillna(0, inplace = True)\n",
    "df['city'].fillna('Unknown', inplace = True)\n",
    "\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "985373c3-d49b-441e-963b-bd3eddd25293",
   "metadata": {},
   "source": [
    "## Handle Odd Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "323ae244-7260-48e2-a718-e7ae2e3ae3ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Breakfast', 'Full Board', 'Dinner', 'No Meal', 'Undefined'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.meal.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9fde248c-ed36-4ac5-90d1-aa608f2424a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['meal'].replace('Undefined', 'No Meal', inplace = True) #replace undefined to no meal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0f1dc1d9-5d38-4271-a3cc-a079f1ebd095",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Breakfast', 'Full Board', 'Dinner', 'No Meal'], dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.meal.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8aba84f-bacf-4794-b5af-fa1f27dbbb38",
   "metadata": {},
   "source": [
    "## Handle Unnecessary Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "542c77a1-0d0e-4d05-a010-d4a796288e43",
   "metadata": {},
   "outputs": [
    {
     "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>guest</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reservation_status</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Canceled</th>\n",
       "      <td>43017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Check-Out</th>\n",
       "      <td>75166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>No-Show</th>\n",
       "      <td>1207</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    guest\n",
       "reservation_status       \n",
       "Canceled            43017\n",
       "Check-Out           75166\n",
       "No-Show              1207"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['guest'] = df['adults']+df['children']+df['babies']\n",
    "df.groupby('reservation_status').agg({'guest': 'count'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c50bdf21-8ecf-4341-b426-6d515ff0aac0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "180\n"
     ]
    }
   ],
   "source": [
    "print(df[df['guest']==0].shape[0])\n",
    "data = df[df['guest']>0].copy() #using data variabel for next analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ff9ed0e-32ea-4002-8aa3-1df2294c18d9",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "# Monthly Hotel Booking Analysis Based on Hotel Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "579e25d8-852d-4cdc-a3e3-c5be64a4d03a",
   "metadata": {},
   "outputs": [
    {
     "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_weekdays_nights', 'adults', 'children', 'babies', 'meal',\n",
       "       'city', 'market_segment', 'distribution_channel', 'is_repeated_guest',\n",
       "       'previous_cancellations', 'previous_bookings_not_canceled',\n",
       "       'booking_changes', 'deposit_type', 'agent', 'company',\n",
       "       'days_in_waiting_list', 'customer_type', 'adr',\n",
       "       'required_car_parking_spaces', 'total_of_special_requests',\n",
       "       'reservation_status', 'guest'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdb52e34-ea03-461b-949a-25eb927f4111",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Hotel Bookings by Month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "74588997-ba6a-43db-af86-fb3dc2ce522b",
   "metadata": {},
   "outputs": [
    {
     "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>nunique</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>4950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>7885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>7594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>4114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>4336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>8221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>7469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>3730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>6434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>7392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>8967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>8071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>3102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>3044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>3553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>2645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>2435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>3559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>3609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>2191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>3334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>3108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>4894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>4573</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel arrival_date_month  nunique  count\n",
       "0     City Hotel              April        2   4950\n",
       "1     City Hotel             August        2   7885\n",
       "2     City Hotel           December        2   7594\n",
       "3     City Hotel           February        2   4114\n",
       "4     City Hotel            January        2   4336\n",
       "5     City Hotel               July        2   8221\n",
       "6     City Hotel               June        2   7469\n",
       "7     City Hotel              March        2   3730\n",
       "8     City Hotel                May        2   6434\n",
       "9     City Hotel           November        2   7392\n",
       "10    City Hotel            October        3   8967\n",
       "11    City Hotel          September        3   8071\n",
       "12  Resort Hotel              April        2   3102\n",
       "13  Resort Hotel             August        2   3044\n",
       "14  Resort Hotel           December        2   3553\n",
       "15  Resort Hotel           February        2   2645\n",
       "16  Resort Hotel            January        2   2435\n",
       "17  Resort Hotel               July        2   3559\n",
       "18  Resort Hotel               June        2   3609\n",
       "19  Resort Hotel              March        2   2191\n",
       "20  Resort Hotel                May        2   3334\n",
       "21  Resort Hotel           November        2   3108\n",
       "22  Resort Hotel            October        3   4894\n",
       "23  Resort Hotel          September        3   4573"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make aggregat table with total bookings per month by hotel type\n",
    "hotel_per_month = data.groupby(['hotel', 'arrival_date_month'])['arrival_date_year'].agg(['nunique', 'count']).reset_index()\n",
    "hotel_per_month"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "261bd633-250b-4899-8682-1bcccf8d82da",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Data Normalize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3f9e0f40-76d3-447f-b7bb-2e1bb50839db",
   "metadata": {},
   "outputs": [
    {
     "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>nunique</th>\n",
       "      <th>count</th>\n",
       "      <th>average</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>4950</td>\n",
       "      <td>2475.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>7885</td>\n",
       "      <td>3942.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>7594</td>\n",
       "      <td>3797.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>4114</td>\n",
       "      <td>2057.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>4336</td>\n",
       "      <td>2168.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>8221</td>\n",
       "      <td>4110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>7469</td>\n",
       "      <td>3734.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>3730</td>\n",
       "      <td>1865.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>6434</td>\n",
       "      <td>3217.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>7392</td>\n",
       "      <td>3696.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>8967</td>\n",
       "      <td>2989.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>8071</td>\n",
       "      <td>2690.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>3102</td>\n",
       "      <td>1551.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>3044</td>\n",
       "      <td>1522.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>3553</td>\n",
       "      <td>1776.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>2645</td>\n",
       "      <td>1322.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>2435</td>\n",
       "      <td>1218.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>3559</td>\n",
       "      <td>1780.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>3609</td>\n",
       "      <td>1804.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>2191</td>\n",
       "      <td>1096.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>3334</td>\n",
       "      <td>1667.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>3108</td>\n",
       "      <td>1554.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>4894</td>\n",
       "      <td>1631.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>4573</td>\n",
       "      <td>1524.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel arrival_date_month  nunique  count  average\n",
       "0     City Hotel              April        2   4950   2475.0\n",
       "1     City Hotel             August        2   7885   3942.0\n",
       "2     City Hotel           December        2   7594   3797.0\n",
       "3     City Hotel           February        2   4114   2057.0\n",
       "4     City Hotel            January        2   4336   2168.0\n",
       "5     City Hotel               July        2   8221   4110.0\n",
       "6     City Hotel               June        2   7469   3734.0\n",
       "7     City Hotel              March        2   3730   1865.0\n",
       "8     City Hotel                May        2   6434   3217.0\n",
       "9     City Hotel           November        2   7392   3696.0\n",
       "10    City Hotel            October        3   8967   2989.0\n",
       "11    City Hotel          September        3   8071   2690.0\n",
       "12  Resort Hotel              April        2   3102   1551.0\n",
       "13  Resort Hotel             August        2   3044   1522.0\n",
       "14  Resort Hotel           December        2   3553   1776.0\n",
       "15  Resort Hotel           February        2   2645   1322.0\n",
       "16  Resort Hotel            January        2   2435   1218.0\n",
       "17  Resort Hotel               July        2   3559   1780.0\n",
       "18  Resort Hotel               June        2   3609   1804.0\n",
       "19  Resort Hotel              March        2   2191   1096.0\n",
       "20  Resort Hotel                May        2   3334   1667.0\n",
       "21  Resort Hotel           November        2   3108   1554.0\n",
       "22  Resort Hotel            October        3   4894   1631.0\n",
       "23  Resort Hotel          September        3   4573   1524.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make average by divide count per nunique \n",
    "hotel_per_month['average'] = round(hotel_per_month['count']/hotel_per_month['nunique'])\n",
    "hotel_per_month"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7b56a2c-a17e-4464-a8c2-4c72f0910c00",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Data Sort by Month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c7df13fb-c83a-4ae6-9c49-4b81cc0c334e",
   "metadata": {},
   "outputs": [
    {
     "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>nunique</th>\n",
       "      <th>count</th>\n",
       "      <th>average</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>4336</td>\n",
       "      <td>2168.0</td>\n",
       "      <td>Jan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>January</td>\n",
       "      <td>2</td>\n",
       "      <td>2435</td>\n",
       "      <td>1218.0</td>\n",
       "      <td>Jan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>4114</td>\n",
       "      <td>2057.0</td>\n",
       "      <td>Feb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>February</td>\n",
       "      <td>2</td>\n",
       "      <td>2645</td>\n",
       "      <td>1322.0</td>\n",
       "      <td>Feb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>3730</td>\n",
       "      <td>1865.0</td>\n",
       "      <td>Mar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>March</td>\n",
       "      <td>2</td>\n",
       "      <td>2191</td>\n",
       "      <td>1096.0</td>\n",
       "      <td>Mar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>4950</td>\n",
       "      <td>2475.0</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>3102</td>\n",
       "      <td>1551.0</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>3334</td>\n",
       "      <td>1667.0</td>\n",
       "      <td>May</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>6434</td>\n",
       "      <td>3217.0</td>\n",
       "      <td>May</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>7469</td>\n",
       "      <td>3734.0</td>\n",
       "      <td>Jun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>3609</td>\n",
       "      <td>1804.0</td>\n",
       "      <td>Jun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>8221</td>\n",
       "      <td>4110.0</td>\n",
       "      <td>Jul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>July</td>\n",
       "      <td>2</td>\n",
       "      <td>3559</td>\n",
       "      <td>1780.0</td>\n",
       "      <td>Jul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>7885</td>\n",
       "      <td>3942.0</td>\n",
       "      <td>Aug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>August</td>\n",
       "      <td>2</td>\n",
       "      <td>3044</td>\n",
       "      <td>1522.0</td>\n",
       "      <td>Aug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>8071</td>\n",
       "      <td>2690.0</td>\n",
       "      <td>Sep</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>September</td>\n",
       "      <td>3</td>\n",
       "      <td>4573</td>\n",
       "      <td>1524.0</td>\n",
       "      <td>Sep</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>4894</td>\n",
       "      <td>1631.0</td>\n",
       "      <td>Oct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>October</td>\n",
       "      <td>3</td>\n",
       "      <td>8967</td>\n",
       "      <td>2989.0</td>\n",
       "      <td>Oct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>7392</td>\n",
       "      <td>3696.0</td>\n",
       "      <td>Nov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>November</td>\n",
       "      <td>2</td>\n",
       "      <td>3108</td>\n",
       "      <td>1554.0</td>\n",
       "      <td>Nov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>7594</td>\n",
       "      <td>3797.0</td>\n",
       "      <td>Dec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>December</td>\n",
       "      <td>2</td>\n",
       "      <td>3553</td>\n",
       "      <td>1776.0</td>\n",
       "      <td>Dec</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel arrival_date_month  nunique  count  average month\n",
       "4     City Hotel            January        2   4336   2168.0   Jan\n",
       "16  Resort Hotel            January        2   2435   1218.0   Jan\n",
       "3     City Hotel           February        2   4114   2057.0   Feb\n",
       "15  Resort Hotel           February        2   2645   1322.0   Feb\n",
       "7     City Hotel              March        2   3730   1865.0   Mar\n",
       "19  Resort Hotel              March        2   2191   1096.0   Mar\n",
       "0     City Hotel              April        2   4950   2475.0   Apr\n",
       "12  Resort Hotel              April        2   3102   1551.0   Apr\n",
       "20  Resort Hotel                May        2   3334   1667.0   May\n",
       "8     City Hotel                May        2   6434   3217.0   May\n",
       "6     City Hotel               June        2   7469   3734.0   Jun\n",
       "18  Resort Hotel               June        2   3609   1804.0   Jun\n",
       "5     City Hotel               July        2   8221   4110.0   Jul\n",
       "17  Resort Hotel               July        2   3559   1780.0   Jul\n",
       "1     City Hotel             August        2   7885   3942.0   Aug\n",
       "13  Resort Hotel             August        2   3044   1522.0   Aug\n",
       "11    City Hotel          September        3   8071   2690.0   Sep\n",
       "23  Resort Hotel          September        3   4573   1524.0   Sep\n",
       "22  Resort Hotel            October        3   4894   1631.0   Oct\n",
       "10    City Hotel            October        3   8967   2989.0   Oct\n",
       "9     City Hotel           November        2   7392   3696.0   Nov\n",
       "21  Resort Hotel           November        2   3108   1554.0   Nov\n",
       "2     City Hotel           December        2   7594   3797.0   Dec\n",
       "14  Resort Hotel           December        2   3553   1776.0   Dec"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hotel_per_month['month'] = hotel_per_month['arrival_date_month'].str[:3] #get 3 first words of month\n",
    "hotel_per_month['month'] = pd.Categorical(hotel_per_month['month'], categories=['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']) #sort by categories\n",
    "hotel_per_month.sort_values('month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "bc2f464c-7dc7-49cc-9232-e6c329608e6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2017, 2018, 2019])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.arrival_date_year.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "862e133b-6dd1-4151-b1d0-8af61f9b9a3d",
   "metadata": {},
   "source": [
    "## Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "99e8ea83-1178-4398-beba-9023ebc7b750",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Gb7rXPoXFhn8Hrg7mc8HwA/BNdofin0v72czCF9blSZuJdNkiMrys37ZUZHr+91Q0PwnylJJuNFT2b1I6x61KBDcBwzdyzgr+nhQaVtajDCldL5HB+0GK6BlKidMYiu5AGb6ZYCrP0ESf+dqEotqixPfSpk8orVYkWohM1cZlfF8U/A3fxVuGf7bxQ+fcCjM7HP8MXpmcc8vKG6Bz7gEzexzYC98z6bb4Hvf2w9ecXGFmbzvnPiL5vp4V+R6W6r52SacqXUXFUlFG4J8tSxzjVfhnXkuzEL/tiYuqaMzRYZW5P0tTkcu/i6LnJfvjb9YkLvjGOeeitQuVKbw/W5pZvUhhakPSUHTaRyleEx/1ZTmWXW7OuYVmNoOiWrlwQTvd/ZCHf04y2TTRYQtLCW8q/mZWY+AtM+vhnEt7f4RruJ1zzsxKmnQRRc/atU0yPtk2VYTPKLqJsim+1vhb/DP24ec2LwUeD45dI/xvw3qcc/nAMWa2Mb6me/vgc1Sw/E3wtZ2JWunwcfua4jXQUYkbvYsiw8v6bUtFtuR/qUr2m1Ta9/L+JqVz3KrSQ/ibGw2AXc3sbIpaMyyjeI1jMhvjH4cJfw9bFPzN9P0gqEAp8bqHoBv94PsNZvadc+7d6ITBC+NXOuc+xr+jMuw0iteCnB4ZH52+MvU3s3Cz11Mj478I/m4UGvaj8++NTAgXNitUUDuE8x0WrOuow/wV2EKK3lu3J/6uerJ9fU0wTy2Kb98afMdIlSWTYsE5t9LM7sd3HgDwvHOu1BoO59xyM5tEUbOvo8xso0SzLzM7iOLvzKyotLuaovOsUQUtM1Vv4Tue2g5f63FdaFy6nfGk6xP8Kz3A3zz5RyIGM6uPfy4oYSG+4JMQvohNtg8nUHw/13fOrfceRTNrAfzNOTc5jfhTFqxn+9CguqH/090Pn+A7DQPoamY7Jpq9mtn2FG9uVlraPRTfPHZrfCuNd83sIFf578n8nKJOk7qaWXvn3GxY1/R060pa716R74ljsVFk+BPOuURBvMTfATPbBfjBOfcnvqYyMfwd/HOuAO3NrLVzbgF+X/89GL4Zvt+BPyLLrIW/8TMzGJR41jFR+OtvZsNDzV6jv21lijH/qyyfUfyc/4eZPRnaR6VdixQrFJtZI+fc8sj06Ry3KuOcm29mz1G0nXeGRr8YeqSoJKfiX1uUyHfCaX4pRU2ZM3o/iKcCpcTGOTfdzC6lKBNqBLxjZu/jM94V+OdGeuAf9D4N+Ng5962ZvUtR762nBL1GTsA/93FEaDVjnXNfV/7WrNMTyDWzD/CdLISfl5nknEv0hDadoh7edjWzkfie3brjez6rLPsB/zWzCcH6fsf/sHWjqDAJRXdS38T3nNgx+H61me3A+j2rgu+oZD6VJ5NiSbgH3+McFO/lrjS3UnSHtTnwhZm9gE//4QuQlfheFivCrxRdqA0ws5X45pDznXPDK2gdSTnn1prZvRS9zD3xvMti/HM4Vekp/E2IRLOoB4OeSxO9m+4QmvaOyPNQv+ILxQBHmNkwfC+hq5xz9wS1So9S1GPxP4IegMfgL47a4i+k98XX0j5fwdu2ZaiHypb4XoZbhMaHn29Mdz/cDhyDL2TUBj42s6fxz2X/g6JrChdMm5Rz7lczS7wDuG0Q73tm1j38XGMleIiiAmVd4BMzewafJs+oqJWEjkNDfJ5+YGj0YoJePFn/2b+3zOxN/I2AkynZUKBb8Fv5M76pYDP8uxATVuJ7jAX/apJj8C0DNgYmm9moYN5G+BrTA/Hp4SBgtnPudzN7HZ8eCLYjN1hn2r28Ek/+Vymcc3lm9gRFPTYfAIwzs/fwxzBcQJoOvB76Hq1Je87MxuNvhv7POTeDNI5bxW1dyu6m6LiFn2VM5WbhEDPbkaJeXsM3wJ4IPW6UDftBUu29Rx99KuuD/yHPp+ze1QaE5mmDb/pQ2vTfAhtH1hUeP3hDx7F+T4SvlxDLYiAnNN+2wbBk00Z7z+semm9weFwp+3R4aLo5oeHHp7CfZ1C8R9Yd8Bl0afO8T+jdeqzfe96AVOJLIa2UO5YNWV8J2zI4hXkGROZpFxl/UxnbsBz4e6rbkML+vqWE9XwXmiY3NDw3Mn/3DUmT+A4Woun9wTTyisElxVFKrNFzuSu+h+fS9v9zhHprDOY7p4Rp80PTNMC/pqWscyx6/MqVvkqYr7TPAmCXCtoP/0fxni2jn9WEelYtLY3gXxOwKDRuLiW/ry/lNFfG8X+0hLh/pPi7Ddd7h2UpxyE3xeOwBugXmq8uJf+ORX8HBofmSyWN3RyJsaz3+CXbz1viCz7Jphsb+T6gHPurSvO/UuKIzje8hOnmlLLuRvje3Uvbnp+ADpH52uJvNCWb/vgNPG4l7quKzGtD074fmXZKisss6XppMkEP/BuyH/Sp2o865ZHYOecexzc1uhx/N/8P/PNoK/GFhxfwBaGRoXnm4Z8dORff410e/kJmIf6u9wX4V3Sk03HAhrgd38nNZ/ga1kX496Pt7ZyblJjI+XdrdQPexj9rsBxfw3o0oR4XK8Gn+C77X8MXHBfhL3IW45s43RDEuq5HVufvlHbCd9zzWTDtavzF6Bh84ekQt35znQqXSbFsCOc7TTkAX0v1Mz69r8Dfxb4f39X6yxW4ymvxhco5pP98cNqC9BTt8bCqm7smYhkP7Iy/qJ2Ev5m1Gp/vvI7v2v9kV7x2Enzt1pX4YxTtxCax7ALn3JH42sHX8B1/JfKyn/Hn++VUbisE8Of0IvxzmkPxhcnvwhOkux+ccw/iW188jq9ZKKAorx4O7OmcS6lmKcgTj8SnffDP/401s1Q6qUnXWfiOyabij03i3ZDRXnoXVsC6HD5/nxasY0/n3LPrRvpnP3vgz4V5QTzT8c9SnlnKcm/D/9aMw6erFfhC/u/4NNbHOXdlsUD87+xu+Fq/74O41uB/Oz/H1zT1pKgDIZxzv+A7dxoexLcymPd8ir/Ps1xiyP8qTfBbcxj++fB38PtpNf61F1/iWwJ0cpFnxZ3vhfdv+F7ewz2gR5df7uMWg7sj31PtaO3v+Pf7zsCngbn47TzARZrLZsl+qNHM+ZK/iKTBzLrjfxASDnLO5cYSjEgGM7N/4t9LCb75d+fSphepDGbW0CXpidnMuuAvTBM32q9wzg2r0uBEslDw/HSiA7JVwBbBTf/odIMJPUPvfA+6Uk3oGUoREakUZrYJ/vmWLSjeGU/0jrZIVXnMzNrgO4uag78O6oR/l2yiMLmY9WvURSRgZg3wtfrNgEtCo55PVpiU6k8FShERqSy9gCcjwyYAz8QQiwj4zoQOoahTtKg8/PN7uigWKdkmFG+dBf7cuSaGWCQDqEApIiKVzeGfj3kVGJTk+USRqjICX6jsgu/crQH+ebdp+OcPH1ZhUqRcFuB75r/KOaf3QNZQeoZSRERERERE0qJeXkVERERERCQtKlCKiIiIiIhIWlSgFBERERERkbSoQCkiIiIiIiJpUYFSRERERERE0qICpYiIiIiIiKRFBUoRERERERFJiwqUIiIiIiIikhYVKEVERERERCQtKlBWEjMbYGYu9FljZr+Z2X/NrEOay7zQzP6eZPjgYB11NjzyUtd/lJlNNrOCYH0tSphuuJn9WoHrHWBmp2/A/IPNzKU43cHprqcqxB2jmeWaWW4Z07QL4tymgtftzOzGilxmknWUuX01nZnNMbPhFbSsFkFa2T3JuFwzG1cR6yll/RWadybLa4LlD05hXqW9mJhZ9+A49Yw7FomPmeUE53CrCl7ujmb2vpktCdLZMWVM39HMnjSzn8xspZktNrOPzex8M2sQTJNIs91D8yW9RtzA2EvMh83szCCGduVcZon5fjmWUebvUFzndSq/K8F1kjOzAVUYWqVSgbLynQB0BQ4ArgQ6A2PNrHkay7oQqNDMIlXBiTEC+A04FL9NS6to9QOAtAuU5XAdkNEFSrIjxnb4OCu0QFlFzgk+UrJjgRsqaFkt8Gkl7QuLLNAVeCzuIESkTDn4/KhCC5TAHfjfwxPx+cGHJU1oZicAXwO74PPZQ4G+wKfAEOCsYNKvgmV9FZr9QmK6RiynFlT/fL8sv+OP35txB1JRKrVGSwCY5JybGfz/iZnNBd4D9gXeji+sctscaAr81zn3UdzBiFQG59yUqlyfmdV3zq2synVuKOfc13HHkE2ccxPijkEkVWZmQF3n3Kq4Y6lGdgI+cs6NLm0iM9seeBp4CzjBObc6NPotM7sN2AHAObcEUN6SpYLf/Wp1/FRDWfWWBH/rhgeaWS8zG29mK4LmDa+Gm8aa2Rxga+CUUDPa4ZFltzezN80sP2gqMcjMyjzGZrapmT1tZvOD5hXfmlm/0PjBwJzg6+PBunNTWG7noJnGcjP7wczOTjLNXmY2Joh5mZmNNbO9QuNzgQOB/ULbnRsa397MRpjZvCD2SWZ2bFmxJYkj0Uzt6tB6BpvZxcFy20SmNzP70cxeCL4nmi+cY2Z3mNlfwXa/kaw5iJkNNLNvzDcfnm9mj5fVzKakGEPjDwz239JgX75jZrtElpFrZuPMrKeZfRXE+F2yfWZmfcxsWrD936eyX803v/kg+PpeKM7uwfi6ZnZj0FxlVfD3RjOrm3yJyVZhV5vZr8G58pGZ5SSZ6O9mNiHYvkVm9qKZbZXCwos1O7SiJjNHm9l9wbGab2bPWqTJt5nVMbPLzWxKcFznmdloM9sxsqy/m9mjZjYP+DM0f5lpwszONZ9P5AXbNcHMjkgSxw1mNiu0rHFmtn9kunKnwWC+Yk2NrKh5/z7mz8UlZjbXzO6xoHlWCctpB8wOvj4aSisDItOlklY7mdn/zGxhkC4+MbNuZW1LSHsrI+80sw5m9kqw31cE+75XWQu2JE1eUzm3zKyBmd0ZbHO+mf1hZq8n0lMwTZdg+b2TzD88OE9qlxLbYWb2qfnfnHwzm25mgyLTlLlvzWxPMxtlRefldDO7ycwaprG+Un8Lg2lSzsfKqZGVfZ43C6aZGxy/6Wb2bzOzYHztII1cE5pn1+A4jYss61czuzX0vZGZDTOz2ebzx9nm87tawfhNzGy1mZ0fDdzMLjOzQgv9VlkK+aD58/lZMzvdzKYBq4AjossPTZ9KHpT4PTzbzG4O0u7SYD2NzGw7879P+WY208xOTbKeVNJB0maPtv5vY6IJ4vZWwnluPt95MpjlByvKj9qVsi9K/T2zIM/Ht9rpn1hmScvD1zDWAc6JFCYBcM7Nc859El62Ff22ziHJNaKZHRf83ylJ/LlmVqGFGvP+HZwXq8zs9+B8aRaMb0cZ+X4q6bacmgf7YqH536cRZtY6Enep53VounR/B3oF6e4+M6tlSZq8WlGe3dnKvnbuaWZfm//9nmm++fHwIB0kpknpWqDCOOf0qYQPvpmmAzrgM4j6+LtUY/AXkc1C0/YC1uBrLo8GTgZmAvOAzYNpOuOryEcD+wSfbYNxg4N1fQdcDPQE7g6GnVZGnI2BGcG6BgJ/wzdtdcDAYJotgOODYTcE6+5YyjKH4wvOU/HNMw4BngvmPyg03W7ACmBisPzjgC+CYZ2CaTrim3R8E9rujsG4LYG/gu3uBxwGPAGsBY4OrWewT+ql7od9gvieDK1nC3zTlxXAZZHpDwum7x58bxd8/wV4Hf+DfFpwzGbg7/gm5h0KFAK345uznIZvSvwZULu8MQbjjgBWA68BvYPPp8BCYMvQMnKDmL4P9lkvfLpbDWwXmq5nsB8T2zIA+DmYN7eUGJvhm4w64LxQnM2C8c8F67o+2PbBwb54LoVzKrF/PwGOAU4CpgMLgFah6c4Opn0CODyYbir+R6xpGevIDW8f0D1Y1mzg3iDm84I08VRk3lHBtt0W7Ndj8E2dDoos6zd8E8hewDHlSRPBss8AeuDT4H3BMnuFprkayAcuwN+MOQrfVCp8TqSVBoN55wDDk+R1PwTHtSdwLT5PG1LKcurjm8864KZQWmlTzrS6O7AMGIfPRw4H/gesBLqUsS2DSSHvBDbD55E/BrEchc+L1wB/Ky2vCZY1uLznFtA8SCd9guN4bLD9C4FNQtN9DrwVWWcLYHl4vUm2fZtgH40I9u3B+Px6WHn3LT7vvgY4Moj1HOAP4IVyrq/M38LypI1UP6R4nuNvwn8c7JOLg+kS6eWm0HT/A94Pfb8gOB6rgMbBsA7BfH8LvtcJlr0AX7DogT+XC4DbQ8saDXyeZBsmA6+XNx/En8+/4c+BvsF6ty1lX6WSB7ULhv0EPBVM9298nvN0EOv5+GuDl/Hnw85ppIM5hPKiUs65wZRxngNt8Nc3Dp/WE/lR/VL2Ram/Z/jfw33w1ylvJpZZyvJmAJ+WM812D74nvUYM0tVvwAOR+XcM5h9Qxnpy8ed/nSSfgcEy2oWmvykYdl/ouOfj03Ytys73y5Nu1zv2JeyjX/DXTb3w5/VS4IM0zuty/Q4AdYLv/8Cf+9ckOUcGhIYNJ7Vr5474vPRj/HXGifhz6mdgTmi6Mq8FKvJT4QvUZ92BHBAkgujnN2DPyLRf4i/G6oSGtcdnTHeEhs0Bnk2yrkTiPS0yfDLwbhlxnksoUwoNH4PPBGsH37eLJv5Sljk8yQlQH/9D+Uho2ChgEdAiNKwZkAe8HBqWC4xLsp7Hg5O7dWT4e/imxsX2TwpxO+DGErZnJmChYS8DU0PfE5nDFKBWaPh+wfAzQtOtAQZF1pGY7pg0Y5wJjI0MawbMB+6K7MtCYPvQsLZBTFeFhn2SZFsSBdrcMmLsHkzXMzJ8FyI/9MHwa4Lhu6Ww7fMJLshC+7MQuCH43gRYDDwRmbc9PkO/sIx15JK8QBktPN6Hv9Cz4PvBwXTnp7BfXokMTytN4H8E6wDvAq+Fhr9B6PxJMt+GpsE5JC9QDolM9wYwo4xltQvmPbOEY5FKWh2L/wGuFxpWOxj2ahnrH0wKeSf+IjpakK2Nv6HxVXR5SdLt4ND3tM6tYH2N8BdD/47s/zXA1qFh5wfxblHK8hI3CZuVMk259y1gQbrshy8otC7H+lL9LUwpbaT6IfXz/EiS/A7iC/4rgY2C7//GF0brB99fBR7EX7AeFgw7O9iGJsH3/sGyD4gs+2p83tU2+H5KMF2H0DQ5wbATg+8p54P483k5oZsU5dhvJeVB7YJ43o9M/3IwvF9oWMsgrV6XRjqYQ/kKlGWd5wOC6cq8KUE5fs+AX5PFmWSZK4Dny5lmu0f2R0nXiIsp/tt5B/7mVMMy1pNL8mvZ8KddMG0r/HkwPLKMfsF0R0fSx5mR6cqbbkvdp6F9NDoyPHEO9SjneV2u3wH8uXFZkG6j29ouuk5Sv3Z+Dn/t2yg0bFN8XjUnNKzUa4GK/qjJa+U7FtgT2At/J2EKvi38TgBm1hh/F3ikCzVxcM7Nxl94HFiOdUUf7v0OKKuZwAHAb8653MjwZ/F37DqWY/1hy51zHyS+ON9efEYkngOAN5xzi0LTLcHf3U1lu3vhnzVYHFTt1zHfedA7QKdEE4sK8AD+Tl8P8E2E8Xd6Hkky7Sjn3NrEF+ebp/yKf/ga/B2nWsCISMyf4S8UDyhvcOafu9g2yTKXA+OTLPMH59wPoRj/wt882CpYXm18mo1uywSKmj6nIxHHs5Hhie+pHPO3nHPLQjHNwT+HkNi/XfEF6ei++AWYRhr7NxA9tybjM/qNg++H4n8IHk1hWa9EvqecJsw3cXzDzP7E/7AVBvOHm4J9ARxuZv8xs/3NrF666yunZPtoQ5opQdlptSE+3bwIrA1ti+FviqW6LWXlnQcAE1zR8/A459YAzwM5qeY15T23zOxEM/vMzBbhj/cy/EVX+Hi/gL8x98/QsLOAN51zpfW2PQmffl4ws+PNrG1k3Snv26C52DAzm4W/ACsEngmm3T7F9ZX3t7DUtJGmss7zA/CF5Oci0z0L1KMoH3ofaADsa75J5YH436VxFHWqdjDwpXMuP/jeC1+j92nkvHwX/4jMPsF0r+BrHfqH1t8ffyH+v+B7efPBCc65P0rcKyEp5kEJ0X4ipgV/30kMcM4txB+3LYPlV+Q1UVQ610glqYjfs6ryCP5mVF/wzemBU4GnnXMrUpj/G3y+Ff1Ee13fB38eRPfJC/i0UtY+qazf7/9Gvr+IP48T52uq53V5fwfuxNcIHu+cS7VjtlSunffBXwstD033O75VWlhZ1wIVSgXKyvedc+5L59wXzrnX8M03DH8HA/zdOcM3VYj6g/L1NpYX+b4S/6NWmlalrDsxPh0LkwyLxlPaulumsI62+KYEhZFP4pmU1iXMVy7Ouc/xzXIT7djPxGeOTyWZ/M8Shm0eihl8jWI07qZpxpxY5uNJlnlkkmVG0wkUPzYb4S9gStqWdCXSUvSYlyetpbp/x7D+vtiV9NNEsnMLivZZayAvxR/n6PanlCbMbEt8jVErfLOdffE/6qMpfl7dhO9B72iCJnTmu6DfqDzrS0OyfVQ/zWWVtMzEchPb2wp/h/ha1t+Wc4GWlsJz5EnWU568ykgtv4JynFtmdhQwEl8beDKwN/54zwvH5pwrwDfnOj24AOuGvxH4UGmBBBdFh+GvA54B/gieB0pc9JVn3z6Jzx/vwRcu9gT+FYxrkOL6yvtbWFbaSEdZ53kr/Hke7bAmmod9i69VOAjfFLEZvmfPD4CDgueyuuMLnglt8c/ARff158H41gDBReRL+GflLLhJ0Rd4MUgLiWVB6vlgsn2+nnLkQQnR64BVpQxPzF+R10RR6VwjlaQifs+ifsGngQrlnJuLfxwmcQ1zAj6+h1NcRH5wHVvsg78BEpZ0nwQ3BhZQ9j6prN/vYnlrcP4upOi6IdXzury/A33xNy3GlCPWVK6dN8XfhImK/q6UdS1QodTLaxVzzq0wsx/xzw+CTzwO2CTJ5JuQ/EezIuWR/M7iJqHxlbnukrY72UkVtQB/kgwrYfzcNONK5gHgYTPbHF+gfNE5l2zfbFzCsEnB/wuCv4eSfBsXJBlWlsQ8V5I84ypvb33z8Rl4SdsS/RFJVWJ/bQLMCg0vT1orKabfgv8T+2IA/vmqqMp61c18oJWZNUyhUOki31NNE73wz9WdGK55MrNGxRbuXCH+nBhmZpvgbyrcgb9DfVI51pcNFuHvLN+PfzZrPeGawA1QWl7lSC2/gvKdW32Amc65AYkB5jv7SHZR9iBwEf7Z6WPxtZ3vJJmumOBO+AdmVh/f5Pl64E3zHWcsIoV9G9R29MY3/bs7FOuu5Vxf3L+FqcjDn+f1IhefxfIw55wzsw/xtZBL8Y9gLDSz9/G1OvvhWwB9EFrGAvxzYieWsO45of+fwdcw7Q80xF9gPhNZFqSeD0bzpJKklAdtoPKkgwJ8DdI6FulspRJVxO9Z1BjgTDPbJNUa43J4AP/Kui74Fgwfu4rv1Ty8T9alu6CWsTVl75PK+v0ult8GNXUtKbpuSOm8pvy/Az3wLQzeNrPDQ60RNtTvFBW+w4ptZwrXAhVKNZRVLMh4t8XfZSZovjcROMFCvfGZ2db4u3+5odlX4n88KtKHwBZmtl9k+Mn4OyCV+RqFD/HV8U0TA4L/jyK17R6NL5h/n+zumSv/6xhWlbAe8E0aluKbRGxFyXf/jw/XiAT7dQt801Pwz3euBbYqIebZacQ4HX+xsXMJy/y2jGUWEzTh+CLJtuyNb/dflsR+j8aZeN1Mn8jwU4K/uSks+/CgSVQipnb45h+J/fsp/jhtV8K+mJ7COtLxLv4O5ZlpzJtqmkhctBUmZjSzHfAXp0k55/4ImtqMwT/zU571VYWS0kpKgvzzY6AT/hmWZHfRK8KHwD4W6vExyK9PAr4OmuqnEm95zq1G+JYQYf3xtYbR5c7Cp8FL8c8qPlqegrRzbqVz7n3gFnxHbe3LsW/rBzEVRhY7II31pfpbGJcP8ddNJ0SGn4LPm8eHhr2Pf9TlSIpqIifimy0PDqb/JDT9aHyzz6S1Qc65+aFpP8A/StE/+MzBH6uEysoHy50HlVc508FPFOVrCUdswOrLkx9VxO9Z1J3454AfsCS9M5vZRkmu1cJKvEYMzrdp+ALFfpTRgiFNE/DpOrpPTsJXYOWG4oT1Y62sdBu9SXMC/jxOnK+pntfl/R34Ht8SYXt8obJJmvFHTcBfC627kWP+UazyXgtUKNVQVr6coHrZ8HcRz8XfYb43NM21+Lb9b5jZA/hnZIbgn4m4PTTdFKCbmR2Jr2Kf7/wzZBtiOL4HqJfN7Gr8j9Qp+GZLZwUXQJXlBvyP7VgzG4a/w3M5/kfr+tB0U4BzzOwk/J3ApUHGMgjfHOgjM7sP/6PaEn+ybOOcO72c8UwBjjCz0fg7TXODpiKJmuXh+M4WJjvnom3VE5oCr5rZw/g70DfjOxd4OljOrGBb7zPfBfqH+LusW+L3+WMu1H4+1RjN7F/Aa8Gdt//ia0I2xv8A/+ycu6Oc++I6/AVqeFuGUNQEpDQz8BfCp5tZHv7HY7pz7jszex4YHNyx/BT/bMK1+I4IJqew7BXAu+a72q8fxLQE/0OMc26JmV0K3G+++/y38efR5vjnN3Kdc9HnJDaYc+4DM3sJuCNoFvY+vmnjAfhn2XJLmTfVNDEGv1+fNrPb8fnJEHzPbuHCyWv4Z16+wqeRzviahYfLub6q8Cf+rnQfM/sWf7E92zlXnlrSi/AXd++Y2eP4u7cb4Z/Dqu2cu6IC4rwTX0B6z8yuw6e5c/DvhCvvBWyq59Zo4BgzuxPfucIe+GaGi0pY7gP4Zm2F+ObvpTLfFf0B+OfQf8HvsyvxLTu+CyYrc9865xabf/XAxWb2Oz7vOZ2i5mTlWV+qv4UpsaJXFAxxzg0u7/xJvI1/DvKhIH/5Ht8T5ZnAzUkKfYk8YBj4Gwpm9hH+d+8jV7w1wwh8b8tjg/P7G3zt27b4JmvHuOCZKedrhkfga5rqAnc659bVMlZiPphSHlQBUk0HLwBPhM6RTpRyIyMFiRvo/zKzp/Dn0rcuyTs5K+j3LLrMH8zsH/hn9yaY2UP464fGQDf88b6e4jciovGXdo34IL730vn4ZtMVyjmXF6SLK81sGf5c3wlfKz+OomdYS8z3Kynd7mxmT+LTyw7Af4JljQ3Gp3pel/t3wDk31fyrXT7A56O9nHMb2lLqRvyNw3fMv5u0Pj7d/Ym/WQyUfS1Q4VwV9f5T0z4k7+X1L/yF5mFJpu+FvwuyAn8CvUaoF7dgmh3xdyGXB8sbHgwfHHyvE5l+OKEen0qJNdFcZj7+4v9bQr2wBdOUt5fXX5MMzyXSiyH+uaAx+E4GluGfz9grMs0m+IxpKZGeEPG1f4/hmy6swl/wvEfxXuQGk1ovr/vh74wWkLz3tq7B8H8lmbddMO4c/B3AecFxehN/9z06fX/8XaZlwbZPxfcoWGKvjGXFGMT3Bj7jKMAXsF8AukaOQbIec+ewfs9sffG1nyvxGeyxyY5hCXGehe9aezWhnujwF0g34u8sFwZ/byT0WpVSlunwPwRX4W98FODPh5wk0x6Oz8CXBMfhB3w35CW+7iZZGqXkHmsHEOrdLhhWB98j44wgLc4L0m2H0pZVnjSBv9M6Ldj27/F3godTvGe3i4PlLMDnJ9Px50Dd8q6vhDiLpRVK6BmR1M+7Y/AXQoWE8phyptWd8Gn9L3x6/RXfQcnhZax7MCnmnfhHA17F588Fwb7rlWx5SdJtNC8p89zCX6DfiC9wLccX/Dsn2/5g+trBdC+Wtc9D+cVr+MLdSnze+SLr/+6UuW/x+d/b+Dz6ryAdHUHxcz/V9aXyW5hS2gB2DmI4u4x90Z3Uz/Nmwfb9jj/PZ+BvNFqS5f5BqCfXYNi/k6WJYFyDIA1NC/ZRHr5GezDrp9HEtjlghxK2q8x8kBJ6Bi1lX6WSB7UjeS+eg0l+vq0XQ4rpoBb+xvJPwfa9gy+AR38bS1pvsbiDYdfhryfWRI99kn2R0u8ZKfbyGjm2w/EF9VXB9n+Mv75I9BzcnfV7eU16jRgav2kw/NZyxJJLknMtGHdmdB/hK0/+jc/fEtdk9xPp3ZkS8v1ypttS92loH/092J+LKGpptlFk2pTOa8rxO0DxXoq3D9LB+GBd7ZJs93BSv3Y+BP8o1Ur8tdZZ+A67vg5Nk9K1QEV9El1hi0gZzOw/+NrczVykaUPoTvg/Xeq9eYmIVAgzOwRf89nTFd15r9HMbCD+JtTWLtQjokhNZGb/xNdO7eBCPZVK9gua087Et4g6I44Y1ORVpAxm1hl/V+oC/LuAUnpeSkSkspnZtsA2+OZYX6kwWcyB+OagKkxKjWVmHfE1t0Pw749VYTLLmdm9+GbWc4HN8NenLfFNmmOhAqVI2V7BP4/4Dr45jIhIprgW/+Lwb/CvUZKAc+6UsqcSqfYewPen8Cm+Hw/Jfg3wz2ZvjG+i+zm+dUq5OmGsSGryKiIiIiIiImnRa0NEREREREQkLSpQVhIzG2xmlVb9m1h+0F11RSyve7C87hWxPNlwZvZecEwuiDuW8jKzAWaW0mtbzCwnSM/JXti+ITFsY2bDzexHM1tpZn+Z2Xgzu6Ei15NkvYPN7ODKXEcp624XpJl03ocpIiIiUm4qUIpkIDPbAkgUSrLxuagB+HfRpSIH/2xqhRUog5dgTwyWfT1wGP4dfp/i399Uma6j6NiJiIiIVGvqlEdiYWZ1gdVOD/GWpD/+hs9bwOFmtotz7rsy5pEiZ+Bfht3DObcgNHxk8OJkSZOZ1cY/f7867lhEREQkfqqhrEJm1szM7jOzuUETvOlm9m8zs8h0HczsFTNbZGYrzGyCmfVKYfm9zCw/WEeJx9bM2pjZc2a2JFjH00CLEqb9e7D+5cG0L5rZVkmm+6eZfRXEu9DMPjSzfYNxiWZ455jZLWY2F/8y1haprsPM+pjZ+2Y2L9jGr83s1CRxXGBmU0NxfGlmx6azTUmWbcHxmm5mq8zs92BfN4tM58zsRjM738xmm9nSYH/sXNY6Qk7FvzT6wtD3aDy5ZpabZPgcMxseGdYz2GcFZjbTzM4MmoPOCU2TtNlz0HzVmX/XZmLYycHy8oN0NNnMzkrEhe+uf79gPpcszsSygSeDrz+Epm8XjE/pnEmiFf6lw4uiI5xzayMx1DGzK81sWrCOuWZ2u5k1CE0TTsN3mG8+u9zM3ojsl8QNkqtD2zI4NP5AMxsbpIllZvaOme0SiSfXzMaZP58nBWn5azPbO4j1piDt5QXHsHGS7a9XWpyhdQ00s2+CdDHfzB63SNPjYBv+Y2ZXmNlsfI9yu5a040VERKRmUYGyipgv4L0JnAbcDhwFjAbuwL94OTHdZsA4oBO+e+cT8RfFb5rZ30pZ/j+A/wFDnXPnRi+aI14GjgSuAk4CVgP3Jlnm2cBLwBR8M8GzgF2AD82saWi624BHgK+CePsBHwHRQtrVwA7AQOBYoCDVdeDfszYKOAU4BngdeCyYPxHHKfh9+zxweDDtKEJNKcuxvmT+gz9e7+GP3y34pp1v2voF+H7AEfh3A50W7IvXLIVnXs1sb/x7L59xzv0AjAdOMV8zVG7m30H1JpAP9MEf9wtIs1mmme0PPAt8iD8WxwOPUnRT4hzga+BboGvwOaeExb0J3Bj8f0Jo+t9TPWdK8Dm+hnKkmR1gZvVLmfZZ4BrgOfwxuxlfwzkiybRXAtsHMf0L6AK8a77GnSB2gOGhbXkMwMyOAMbij0M/4GSgKfCxmW0ZWc92wK3AUPx+qY8/vx8ENsWnu+vxaTzZq2zKihMzGwrcD4wBjgYuBXoBbydJawOCfXNJ8HduknWKiIhITeSc06cSPsBgv3vXfT8ScMCAyHSP4WvrNgq+34Yv4G0XmqY2MB3/0upiy8c3W74MKATOTCGuQ4L5+kSGvx0M7x58bwIsBp6ITNceX0NxYfB9O2ANcEcp62wXLPsrglfVlGcdSZZXK9juR4FvQsPvC++jJPOltb5gmlbBcRoeGd4v2LajQ8Mc8ANQNzTs+GD4vikcoweCfbp58P2sYN5ekelygdwk888Jx4kvKM0DGoWGbYqvwZsTGtY9nAZCwwcEw9sF3y8B8srYhlxgXIrnSmL520WGp3TOlLBMAx4C1gbLWAl8DFwMNAhN1y0Y/4/I/KcEw3MiaXgKUCs03X7B8DMix//GJDHNBMZGhjUD5gN3RfZdIbBNaNjRwXLHROZ/GZid5FwrNc5gujXAoMjyEtMdE9meuUDDVI6nPvroo48++uhTsz6qoaw6B+Avbp+LDH8WqEdRzcYBwATn3MzEBM65NfhatxyLNK8E7gSGAMc75x5LIY6u+AvJlyLDX0gyXTNgRNDMrk5Qu/YLMC2IE6AnvoD3SArrftU5F35mMtV1YGbbm9nzZvYb/mK7EDgTX5OX8AV+H91rvolnozS3KZl98Mfp2cjwF/A3AA6MDH/POVcY+j45+Ftq09qgJq0P8L5z7rdg8Eh8gWi9Zq8p2gd4yzm3PDHAOfc7voOadHwBtDSzZ83sSDNrkeZyypLqObMe550NbIvvjOcl/M2P24DPzaxhMGkv/M2EUZE08W4ohrBRLlT775z7BPi1tFjAp98glmjaW46vgY6uZ4Zz7sfQ92nB33ci000DtkjSBLisOA/Bn7fReD4DliaJZ7RzbkVp2ygiIiI1kwqUVacVvlZnVWT4H6Hxib+/J5n/D3ytS8vI8L7Ad/hma6nYFFgYKewA/Bn53jb4O4aiAlzisyvQOhif+PtrCuuObldK6zCzJvhmpp2AK/C1SnsCT+CbAiY8DfwfsDf+wjvPzF4OPTuW6jYlkzg+xbbB+Y5JFrB+D6V5ke8rg78NKN1R+GP8ipm1CBXW3gF6J7mhkIpNgb+SDI8e85Q45z7EN8PcEngFmGdmY8xst3SWV4pUz5kSOedmO+fuc86dDGyBb6a8K75JK/g0UQ9YRvH0kNhf0TSRbJ/9CWxeRiiJtPc466e9I5OsZ2Hk+6pShtfBt2IoT5yJeGYmiadpkniS5UkiIiIi6uW1CuUBrcysXuQCeZPQ+MTfTVjfJvimZ9ELyh742pS3zexw51x+GXH8jq9dqhspVG4cmS7RM+YAfOcwUUuDv/ODv5vjm+WWJtqja6rr6ApsDXRzzo1LjIw+jxjUfj4MPGxmLYFD8c/ejcQXMlNdXzKJ47NJeN4ghtasX4BMV6IW8v7gE3UiwTN5+CaryQqY0YLW7xQVIMKix7wg+FsvMny9grZzbhS+Vq8JvqnsMGC0mW3hSn9+tzxSPWdS4pxbY2b/wTcR7xgMXoDf7m4lzBZ9VjC6zxLDJpWx+kTau5LkN3+iheYNVVaciXgOZf08JTw+Qb0xi4iISFKqoaw6H+L39wmR4afgLybHh6bbJ9JzZG185zlfO+eWROb/Hn9Bvz2+UNmkjDjG42szjosM7xP5/im+gLWdc+7LJJ9E4XEMvlniwDLWm0yq60g0XV1XAA4KjL1LWrBzbqFzbiTwX3ynO+VZXzIT8Mcpup9Owt+YyU1pi0thZm3xTTBfAw5K8vmD4s1efwJ2MLN6oWUcgK9hisZ+eLgJsJltin9eLuyn4O8ukeFHlBSzcy7fOfcGviC/KUWFz5VAw5Lmi0jU3kanT/WcWU+wfcnsGPxN1LiNxtcaNy8hTUQLlMeHO2Ays/3wNZ/hWFYl2Zbp+Gdbdy5hPd+WtC1pKivO9/Dn7VYlxDO7guMRERGRako1lFXnbXzvrQ+ZWRt8QfBw/HOANzvnEjV9d+Jr0N4zs+uAJfgeMneghAt759xU8696+AB4x8x6OeeS1rY5594zs3H4WryN8J3HnESkEOGcW2L+fX33B/G+je/QZnP884K5zrnnnHOzzOxO4KKgl9T/4Z/R3AuYFhTqkkp1HfiC4JJguuuAxvheOecDzRPLM7NH8AXG8fgmizvg3+f4bjnXlyzWPDO7HbjSzJbh3w+5E76H0nH43kg31Cn4c/LOoFlpMWb2FHCZmW0TPF/3Ar4g/4T514S0By4KtinsRnynQO8EPfLWB67FN4EMP2f3u5l9GGzjfPw+7IfvYTccx/X42q4P8DV4WwDnA5Occ/OCyaYA55jZScAsYGkpBfYpwd9/BdtYiO8hNtVzJpmrzb+25gV8rVwhsBu+dnIBwatKnHO5ZvY8vrb1DnzvsGvxndYcDlzunJsRWm5T4FUzexhog+8R9gd8c+vw9hxhZqPxtX9znXNzzexf+J5+6+FvdMwP9uO+wM/OuTtK2Z7yKjXO4LwdBtxnZh3whfcCfDPmQ4DHnHMflLRwMxsEDAK2dc79VNJ0IiIiUgNURM8++qz/IdLLazCsGb4n0t/xtRgzgH8T6vk0mK4D8Cq+YFCAr2GK9vA5mKCX19Cw7fHPMo4HmpUSWxt8Jz9L8a8keRpf25esh8/D8QWHJfgORH7AP7vYMTLd2fhCwEp8U8RcoGswrl2w7KS90KayDvwrLr4GVuALKOdH9zG+9i4XXxBaCczGF9CbpbNNSeK04HhND47f7/hmqdHlr9fLZ2gfDChl+ZPwz7RZCeN3CJYxODTsrCD+FfiCdxcivbwG0x0SLH8l8GMw3yv4Wu/wdFvgX8myCF8jehO+ABfu5fUI/DOdvwfL+wX/bOBmoeVsgi90Lw3mzS1j314H/Ia/GRFeV0rnTJLl7Y3v5fW7YFsKgZ/xr/PYNjJtLfxrVL7Bn2+Lg/9vwddcho/fOfjXlswL0s6bQPvI8vYDJgbLih6vrsAb+IJmQXCsXiA4V4Jpcon0kEsJ5xCRfKA8cQbT98fnL8vwrzOZGuzvLcpIz4n1titPvqiPPvroo48++lS/jzmnR2NEapqgafRM4E3n3BllTV/TBU3QZwP/dKn1piwiIiJSI6jJq0gNYGb34msw5wKb4WvkWgJ3xxmXiIiIiGQ3FShFaoYG+J5YN8Y3Hf0c6OkqvjMYEREREalBMrKXVzPLNbMCM8sPPtND4042s5/MbJmZvWpmrULjWpnZK8G4n8zs5MhyS5xXpDpzzv3TObeVc66+c66pc66Hc+7juOPKFs65Oc45U3NXERERkeIyskAZONc51yT4dAAws53xryfoj69pWQ48EJrnfnzty8b4HjMfDOZJZV4REREREREph4zslMfMcoFno7UBZnYTvlfBk4Pv2+J7JWyN7+p/IbCLC7r5N7NngN+cc1eUNq8r4RUbIiIiIiIiUrJMrqG82czmm9knwTsWAXbGd+cP+Hep4Wskdwg+q13xd8Z9E8xT1rwiIiIiIiJSTpnaKc/l+JeDrwL6AK+bWQ7QhPVf2r4Y/xLvNfj3CiYbRxnzFmNmA/EvjKdhw4Zdttxyy3S3o9KsXbuWWrUy+X5APLRf1qd9sj7tk+Iarf4Fh2NFnczL6+K0dq2jVi2LO4yM0Wj1r0E62SruUDKO8pT1aZ8Up3w2OeWzxWVyPjtjxoz5zrk2ycZlZIHSOfdZ6OtTZtYX/zL6fPyLzsOa4V+evraUcZQxb3T9jwCPAOyxxx7uyy+/TGMrKldubi7du3ePO4yMo/2yPu2T9WmfRIzpzqKFebQ4YnTckWSU3Anf032fncuesKb4+HgWLcmnxQnqHDpKecr6tE8ilM8mpXw2IoPzWTP7qaRx2XLryAEGfA90Sgw0s22A+sCM4FPHzLYPzdcpmIcy5hUREREREZFyyrgCpZm1MLPDzKyBmdUxs1OAA4DRwAjgKDPrZmaNgeuBl51zS51zy4CXgevNrLGZ7Qf0Bp4JFl3ivFW9jSIiGWXHi/ml8XFxRyGZbruBSici6VI+K6nI0nw2E5u81gVuBHbEPxc5DTgm1HPr2fjCYWtgDHBaaN5zgCeAv4AFwP85574HcM59X8a8IiI10xZHsWBGvbijkEy36aEs+Gly3FGIZCfls5KKLM1nM65A6ZybB+xZyvjngOdKGJcHHJPOvOVRWFjIr7/+SkFBwYYuKm3Nmzdn6tSpsa0/bg0aNGCLLbagbt26cYcikv2WTKfh6l+AXeOORDLZ0plBOhGRclM+K6nI0nw24wqU2eDXX3+ladOmtGvXDrN4eqZaunQpTZuu10FtjeCcY8GCBfz666+0b98+7nBEst/nZ9FhcR6+7zOREky6gg5L8oEz445EJPson5VUZGk+m3HPUGaDgoICWrduHVthsqYzM1q3bh1rDbGIiIiIiKhAmTYVJuOl/S8iIiIiEj8VKDNQkyZNin0fPnw45557bqnzvPrqq0yZMqXMZQ8ePJjbbrut2LD//Oc/5OTkkJOTQ+3atdf9f88995Q/eBERERERqTH0DGU18eqrr3LkkUfSsWPHcs979dVXc/XVVwO+MDtp0qQKjk5ERERERKoj1VBmmTlz5nDwwQfTtWtXevTowc8//8ynn37K//73Py699FJycnKYNWsWs2bNolevXnTp0oVu3boxbdq0cq1n0KBB3HXXXeu+X3311dx9993k5uZywAEHcMQRR9ChQwfOPvts1q5dC8C7775L165d2X333TnhhBPIz8+vyE0XkcqyyzX81KRv3FFIputwvtKJSLqUz0oqsjSfVYEyA61YsWJds9OcnBwGDRq0btx5553Hqaeeyvjx4znllFM4//zz2XfffTn66KO59dZbmTRpEttuuy0DBw7k3nvvZeLEidx2222cc8455Yrh9NNP5+mnnwZg7dq1vPDCC/Tr1w+Azz//nHvvvZcpU6Ywa9YsXn75ZebPn8+NN97ImDFj+Oqrr9hjjz244447Km6niEjl2aQnC+vvHncUkunaHqB0IpIu5bOSiizNZ9XkNQM1bNiwWLPT4cOH8+WXXwIwfvx4Xn75ZQoKCujfvz+XXXbZevPn5+fz6aefcsIJJ6wbtnLlynLF0K5dO1q3bs3XX3/Nn3/+SefOnWndujUAe+21F9tssw0Affv2Zdy4cTRo0IApU6aw3377AbBq1Sq6du1arnWKSEwWTqJJ4Sz0fjQp1aLvgnQiIuWmfFZSkaX5rAqU1dDatWtp0aLFBj8LeeaZZzJ8+HD++OMPTj/99HXDoz2smhnOOQ455BCef/75DVqniMRg4oVstyQPOCbuSCSTTR7MdkvygfK1eBERlM9KarI0n1WT1yyz77778sILLwAwYsQIunXrBkDTpk1ZunQpAM2aNaN9+/a8+OKLADjn+Oabb8q9rmOPPZbRo0fzxRdfcNhhh60b/vnnnzN79mzWrl3LyJEj2X///dlnn3345JNPmDlzJgDLli1jxowZG7StIiIiIiKS2VSgzDL33nsvTz75JF27duWZZ57h7rvvBqBPnz7ceuutdO7cmVmzZjFixAgef/xxOnXqxM4778xrr71W7nXVq1ePgw46iBNPPJHatWuvG77nnnty7rnnstNOO9G+fXuOPfZY2rRpw/Dhw+nbty+77bYbXbt2LXdHQCIiIiIikl3U5DUDRXtHHTBgAAMGDABg66235v3332fp0qU0bdp03TT77bffeu+hHD169HrLHjx4cMrrXrt2LRMmTFhX05nQrFkz3njjjfXmPfjgg/niiy9KXb6IiIiIiFQfqqGUpKZMmcJ2221Hjx492H777eMOR0REREREMpBqKCWpjh078uOPP643vHv37nTv3r3qAxKRytPpJn6c+BnZ11G5VKmOl/Pj9z8qnYikQ/mspCJL81kVKEVEaro2+7Kk3tK4o5BM13pPltRrEHcUItlJ+aykIkvzWTV5FRGp6eZ9SrNVU8qeTmq2BV8onYikS/mspCJL81kVKEVEarpvrmKbpU/GHYVkuinDlE5E0qV8VlKRpfmsCpQiIiIiIiKSFhUos9Sff/5Jnz592HbbbenSpQuHH344M2bMYO7cuRx//PEATJo0ibfeeqtcyx0+fDjnnntusWHdu3fnyy+/LHW+m266KaXlt2vXjvnz55crJhERERERyUwqUGYh5xwnn3wy3bt3Z9asWUycOJGbb76ZP//8k80224xRo0YB6RUo05VqgVJERERERKoPFSiz0AcffEDdunU5++yz1w3r1KkT3bp1Y86cOeyyyy6sWrWKQYMGMXLkSHJychg5ciTbb7898+bNA2Dt2rVst912676n6vnnn2fXXXdll1124fLLLwfgiiuuYMWKFeTk5HDKKacA8Oyzz7LXXnuRk5PDWWedxZo1aypo60VEREREJFOoQJmFvvvuO3Jyckqdpl69elx//fWcdNJJTJo0iZNOOol+/foxYsQIAMaMGUOnTp1o06bNevMmCqGJT6K569y5c7n88st5//33mTRpEl988QWvvvoqQ4cOpWHDhkyaNIkRI0YwdepURo4cySeffMKkSZOoXbv2uvWKSAbqchczm51d9nRSs+06WOlEJF3KZyUVWZrP6j2UG+jCC2HSpIpdZk4O3HVXxS4T4PTTT6d3795ceOGFPPHEE5x22mlJpzvppJO477771n3v3r07AF988QXdu3dfVwg95ZRT+OijjzjmmGOKzT927FgmTpzInnvuCcCKFSto27ZtxW+QiFSMljnk1/0z7igk07XYhfy6Lu4oRLKT8llJRZbmsypQZqGdd96ZkSNHlnu+Lbfcko033pj333+fzz//vNJqDZ1znHrqqdx8882VsnwRqWB/jKHlyq+AXeOORDLZXx/RcuVs4LC4IxHJPspnJRVZms+qQLmBKqMmsSwHH3wwl19+OY888ggDBw4E4Ntvv2Xx4sVsueWW66Zr2rQpS5cuLTbvmWeeSb9+/ejfvz+1a9cu13r32msvzj//fObPn0/Lli15/vnnOe+88wCoW7cuhYWF1K1blx49etC7d2/+/e9/07ZtW/Ly8li6dClbb731Bm65iFSK725k6/w84NS4I5FMNv0ets7PB66MOxKR7KN8VlKRpfmsnqHMQmbGc889x5gxY9h2223ZeeedufLKK9lkk02KTXfQQQcxZcqUdZ3yABx99NHk5+eX2Ny1NJtuuilDhw7loIMOolOnTnTp0oXevXsDMHDgQHbbbTdOOeUUOnbsyI033sihhx7KbrvtxiGHHMLvv/++4RsuIiIiIiIZRTWUWWrTTTflv//9b9Jx3333HQCtWrXiiy++KDbum2++oVOnTuy4445J5x0wYAADBgwoNiw3N3fd/3379qVv377rzTds2DCGDRu27vtJJ53ESSedtN50c+bMSbpeERERERHJPipQ1iBDhw7lwQcfVI+rIiIiIiJSIdTktQa54oor+Omnn9h///3jDkVERERERKoBFShFRGq6vR5mevPz445CMl3OUKUTkXQpn5VUZGk+qyavIiI1XbMOrKgzJ+4oJNM13Y4VdVbEHYVIdlI+K6nI0nxWNZQiIjXdr6/TumBC3FFIpvv9XaUTkXQpn5VUZGk+qwKliEhNN+12tlz2UtxRSKab+YjSiUi6lM9KKrI0n1WBMku1aNGCnJwcdtllF4466igWLVpUaeuaM2cOzz33XInjdtlll2LDBg8ezG233VbqMocPH87cuXPLXPeAAQMYNWpU6sGKiIiIiEiVUYEySzVs2JBJkybx3Xff0apVK+6///5KWc/q1atLLVCmK9UCpYiIiIiIZC4VKKuBrl278ttvvwEwa9YsevXqRZcuXejWrRvTpk0D4MUXX2SXXXahU6dOHHDAAQAUFBRw2mmnseuuu9K5c2c++OADwBf2jj76aA4++GB69OjBFVdcwccff0xOTg533nlnuWKbNGkS++yzD7vtthvHHnssCxcuZNSoUXz55Zeccsop5OTksGLFCiZOnMiBBx5Ily5dOOyww/j9998rcA+JiIiIiEhlUC+vWW7NmjWMHTuWM844A4CBAwfy0EMPsf322/PZZ59xzjnn8P7773P99dfzzjvvsPnmm69rHnv//fdjZkyePJlp06Zx6KGHMmPGDAC++uorvv32W1q1akVubi633XYbb7zxRtIYZs2aRU5Ozrrvf/zxB5dccgkA//jHP7j33ns58MADGTRoEEOGDOGuu+7ivvvu47bbbmOPPfagsLCQ8847j9dee402bdowcuRIrr76ap544onK23EiIiIiIrLBVKDcUBdeCJMmVewyc3LgrrtKnWTFihXk5OTw22+/sdNOO3HIIYeQn5/Pp59+ygknnLBuupUrVwKw3377MWDAAE488UT+/ve/AzBu3DjOO+88AHbccUe23nrrdQXKQw45hFatWqUU7rbbbsuk0D4YPHgwAIsXL2bRokUceOCBAJx66qnFYkuYPn063333HYcccgjgC8mbbrppSusWkQrQ9RmmfvohXeOOQzJbl7uZ+vV0pRORdCiflVRkaT6rAmWWSjxDuXz5cg477DDuv/9+BgwYQIsWLYoV7hIeeughPvvsM9588026dOnCxIkTS11+48aNKyny9Tnn2HnnnRk/fnyVrVNEQhpvycrabeKOQjJdo81ZWTsv7ihEspPyWUlFluazKlBuqDJqEitbo0aNuOeeezjmmGM455xzaN++PS+++CInnHACzjm+/fZbOnXqxKxZs9h7773Ze++9efvtt/nll1/o1q0bI0aM4OCDD2bGjBn8/PPPdOjQga+++qrYOpo2bcrSpUvLHVvz5s1p2bIlH3/8Md26deOZZ55ZV1sZXmaHDh2YN28e48ePp2vXrhQWFjJjxgx23nnnDd9BIlK2n0bSZsU3wK5xRyKZ7NfXaLPiF+CwuCMRyT7KZyUVWZrPqlOeaqBz587stttuPP/884wYMYLHH3+cTp06sfPOO/Paa68BcOmll7Lrrruyyy67sO+++9KpUyfOOecc1q5dy6677spJJ53E8OHDqV+//nrL32233ahduzadOnUqd6c8Tz31FJdeeim77bYbkyZNYtCgQYB/HcjZZ59NTk4Oa9asYdSoUVx++eV06tSJnJwcPv300w3fMSKSmh8eZPPlyZ+RFlln9jNKJyLpUj4rqcjSfFY1lFkq2gvq66+/vu7/0aNHrzf9yy+/vN6wBg0a8OSTT643fMCAAQwYMGDd97p16/L+++8njaNdu3Z89913xYYlnqEEyMnJYcKECevNd9xxx3HccccVm+6jjz5ab7rhw4cnXa+IiIiIiMRPNZQiIiIiIiKSFhUoRUREREREJC0qUIqIiIiIiEhaVKBMk3Mu7hBqNO1/kQq0/yi+b3lN3FFIptvrEaUTkXQpn5VUZGk+qwJlGho0aMCCBQtUqImJc44FCxbQoEGDuEMRqR4abERhreZxRyGZrn4rpRORdCmflVRkaT6rXl7TsMUWW/Drr78yb9682GIoKCio0QWqBg0asMUWW8Qdhkj18ONwNlk+Gb0fTUr100g2Wf4r2fZ+NJGMoHxWUpGl+awKlGmoW7cu7du3jzWG3NxcOnfuHGsMIlJN/DicTVbkARfHHYlksp9fZJMV+XFHIZKdlM9KKrI0n1WTVxEREREREUmLCpQiIiIiIiKSFhUoRUREREREJC0qUIqIiIiIiEhaVKAUEanpur/Ft61uiDsKyXRdn1E6EUmX8llJRZbmsypQiojUdHUasdZq7muIJEV1GiqdiKRL+aykIkvzWRUoRURquhkPsNny1+OOQjLdj8OVTkTSpXxWUpGl+awKlCIiNd3P/6Xtio/ijkIy3W9vKJ2IpEv5rKQiS/NZFShFREREREQkLSpQioiIiIiISFpUoBQREREREZG0qEApIiIiIiIiaVGBUkSkpuuZy6TWt8YdhWS6bqOUTkTSpXxWUpGl+awKlCIiIiIiIpIWFShFRGq6qbex5bJRcUchme6Hh5RORNKlfFZSkaX5bJ24AxARkZj99gatC/LijkIy3R9jaF2QH3cUItlJ+aykIkvzWdVQioiIiIiISFpUoBQREREREZG0qEApIiIiIiIiadEzlCIiNV3thqyx+nFHIZmudgPWWGHcUYhkJ+WzkooszWdVQykiUtMd9DaTW90YdxSS6fZ9VulEJF3KZyUVWZrPqkApIiIiIiIiaVGBUkSkppt8A1vnj4g7Csl00+5UOhFJl/JZSUWW5rN6hlJEpKb7cywtV+r9aFKGeZ/QcmX2vR9NJCMon5VUZGk+qxpKERERERERSYsKlCIiIiIiIpIWFShFREREREQkLXqGUkSkpqvfmsJaq+OOQjJdvZYU1tJ9aJG0KJ+VVGRpPpt9EYuISMXq9hLft7w27igk0+39qNKJSLqUz0oqsjSfVYFSRERERERE0qICpYhITTfpStovfSLuKCTTfX+z0olIupTPSiqyNJ/VM5QiIjXd/PE0X6X3o0kZ8ibSfFX2vR9NJCMon5VUZGk+qxpKERERERERSYsKlCIiIiIiIpIWFShFREREREQkLXqGUkSkpmu0BSuX6P6ilKHhpqxctjDuKESyk/JZSUWW5rNK2SIiNd2+zzK1xeVxRyGZbo97lU5E0qV8VlKRpfmsCpQiIiIiIiKSFhUoRURquokXst2Sh+KOQjLdt4OUTkTSpXxWUpGl+ayeoRQRqekWTqJJod6PJmVYPIUmhdn3fjSRjKB8VlKRpfmsaihFREREREQkLSpQioiISKnWroU//qzFrB+bcsUVMGYMrFgRd1QiIpIJVKAUERGREn35VV3267ER02bUYeXK2tx+OxxyCLRsCT16wM03w+efw5o1cUcqIiJx0DOUIiI1XdMdWL70V1rEHYdklPnza3HV4KY8NrwRbdusZbPtt6Zx03ksXAgff+xrKceMgauu8tO3aAHdu0PPnr6g2aEDmMW5BSIZRPmspKLJNixfnpd16UQFShGRmm7vR5jx/jtsFncckhFWr4aHH2/ENdc3Iz/f+Pe5yxh05VKaN7+Z3AmT6d4E/vY3/wH46y94/30YOxbeew9efdUP33zzosJljx6wmRKY1GTKZyUVnW9hxoTJWZdOVKAUERERAD7+pB7nXtScb7+rS4/uK7nntsV03Gl1qfO0bQt9+viPc/Djj75wOWYMvPEGPPWUn65jR1+w7NkTDjwQmjevgg0SEZFKpwKliEhN99lAdlj8K/BY3JFITH6bW4tLr2rG8y82YqstVzNqRB5/711QvMnq15exw+I84LASl2MG227rPwMH+s58vvmmqID52GNw771QuzbsuWdRDWbXrlC/fqVvpkh8lM9KKlLIZzORCpQiIjXd0hk0Wq33o9VEK1fCXfc14YZhTVi92hh05VIuvyifRo3c+hPn/0ij1eV7P1qtWtC5s/9ccolf34QJvnA5dqzv0OfGG6FhQ+jWraiAmZPj5xWpNpTPSirSyGczgQqUIiIiNdDod+tz/qXN+WFmHXofuYI7hi5hm/aV21Vr/fq+ueuBB8INN8DixfDhh0U1mJdd5qdr3RoOPrioiew226iDHxGRTKUCpYiISA3y4+za/PvyZvzvzYbssP1q3n5lAb0OXRlLLM2bw9FH+w/A3Lm+g59EDeaLL/rh7doVFS4PPtg/tykiIpkhoxuUmNn2ZlZgZs+Ghp1sZj+Z2TIze9XMWoXGtTKzV4JxP5nZyZHllTiviIhIdbZ8uTHohqZ07NKW9z+sz7AbljD5879iK0wms9lm0K8fDB8OP/8M06bB/ff7JrMvvQR9+8LGG0OnTnDRRfDWW5Cffa3DRESqlYwuUAL3A18kvpjZzsDDQH9gY2A58EBk+lXBuFOAB4N5UplXRKRmaplDft1t445CKolzMOqVBuy0extuGNqU449ZwfRJf3HZRfnUq1eOBTXvWKXpxMy/y/Kcc+Dll2H+fPj8c7jpJmjTBh54AI44Alq29M9fDhkC48ZBYWGVhSiSOuWzkooqzmcrSsY2eTWzPsAi4FNgu2DwKcDrzrmPgmmuBaaaWVNgLXAcsItzLh8YZ2b/wxcgryhtXufc0qrbMhGRDNPlLmYufoct4o5DKtyUqXU47+LmvP9hfTrtWsizj8+n236r0lvYbtczc/nk2NJJomfYPfeEK6+EFSvgk0+Knr8cMgQGD4YmTfwzmokmsrvsoucvJQMon5VUxJzPpisjC5Rm1gy4HjgYODM0amd8ARMA59wsM1sF7IAvUK52zs0ITf8NcGAK806sjO0QERGJw+LFxpCbmnLvQ41p2tRx/52LGHj6cupk5K9+eho29AXGnj19b7F5eZCbW1TAfPNNP13btkWFyx49YOutYw1bRKTaMeeSdA0eMzO7G5jrnBtmZoOB7Zxz/cxsLPCic+6h0LS/4Wsf1wTjNgmN+ydwinOue2nzOudyI+sfCAwE2Hjjjbu88MILlbWpacvPz6dJkyZxh5FxtF/Wp32yPu2T4nZa+B8KCwuZudHVcYeSUfKXFdCkcYO4wyiXtWvh3fc25ZFHt2fRonoccfhvnHnGTJo33/B2oDstGkrh6jXMbDt4wwOtAn/9VZ+vvmrJxIkt+eqrFuTl+Rddbr75cnbffRFduiwkJ2chzZuv3uB1KU9Zn/ZJccpnk8vGfLYyZXI+e9BBB010zu2RbFzG3as0sxygJ9A5yeh8oFlkWDNgKb6GsqRxZc1bjHPuEeARgD322MN179495firSm5uLpkYV9y0X9anfbI+7ZOIMYNZtDCP7vvsHHckGSV3wvdZtU8mfl2Xcy9qzoTP67HPXqu47475dOlcC98QpwJ8vIJFS/Kz6tw58UT/1zmYMiXRe2wjcnMb8frrm2HmO/xJ1F7uvz80alT+9ShPWZ/2SYTy2aSyLZ+tdFmYz0IGFiiB7kA74GfzDz00AWqbWUdgNNApMaGZbQPUB2bgC5R1zGx759wPwSSdgO+D/78vZV4REZGsNH9+La4a3JTHhjeibZu1DH94If1PXkGtTO92rwqZwc47+88FF/iOe778suj1JHfeCbfcAvXqwX77FTWR7dKFatVMWESkMmTiz80jwLZATvB5CHgTOAwYARxlZt3MrDH+OcuXnXNLnXPLgJeB682ssZntB/QGngmWW+K8VbdpIiIiFWP1arj/4UZs36ktTz7TiH+fu4zpk/7i1H4qTJalbl3o2hWuvdY/d7lwIbz9Npx/vv//mmtgn32gdWs45hi47z6YOtXXdIqISHEZd9/NObcc/0oPAMwsHyhwzs0D5pnZ2fjCYWtgDHBaaPZzgCeAv4AFwP85574Plvt9GfOKiIhkhY8/qce5FzXn2+/q0qP7Su65bTEdd9rwZwFrqsaNoVcv/wGYNw8++KCoBvO11/zwzTYr3sHP5pvHF7OISKbIuAJllHNucOT7c8BzJUybBxxTyrJKnFdEpMbaqCuLl/1Ii7jjkDL9NrcWl13djOf+24ittlzNqBF5/L13QdW8FqNVFxYX/FUj0kmbNv75y8QzmLNnF/Ue+/bb8EzQ9mnHHeGww6Bnz9rxBSvZQfmspCJL89mML1CKiEgly7mZ2XnvoLcpZK6VK+Gu+5pww7AmrF5tXHvFUq64OJ9GjaqwDebOVzJ76eQamU7at4czz/SftWth8uSi2st774Vff23PkUfGHaVkNOWzkooszWdVoBQREclgo9+tz/mXNueHmXXofeQK7hi6hG3ar4k7rBqrVi3o1Ml/Lr7YFzKffnozfvtNTWBFpGbSY/siIjXdx8ex88Ib4o5CIn6cXZveJ7bkb8e2xgzefmUBr45cGF9h8rN/Kp0kcc01vtbyppvijkQymvJZSUWW5rMqUIqI1HQrF1B37ZK4o5DA8uXGoBua0rFLW8bm1mfYDUuY/Plf9Dp0ZbyBrVqodJJEu3Zw+OF/8Oij8PPPcUcjGUv5rKQiS/NZFShFREQygHMw6pUG7LR7G24Y2pTjeq9g+qS/uOyifOrVizs6KU2/fj9hBv/5T9yRiIhUPRUoRUREYjZlah0OObI1J/RrRYvmjo/enc+IJxex+WZr4w5NUtC27UoGDoQnnvA9woqI1CQqUIqIiMRk8WLjosub0WmfNnz1TV3uu2MREz+ZR7f9VsUdmpTTlVdC7dpw441xRyIiUrVUoBQRqek27sHC+jlxR1GjrF0LTz3bkA45bbnr/sac/o/lzJj0F/86azl1MrX/9Tb7KZ2UYrPN4P/+D556CmbOjDsayTjKZyUVWZrPqkApIlLT7XotPzU5Je4oaoyJX9dlvx4bMeCslrRvt4YvPp7Pw/cuZqONMrx5647/Vjopw+WXQ716cEP2ddIolU35rKQiS/NZFShFRESqwPz5tTjrvObs2W0jZs+pzfCHF/LJ2Pl06VwYd2hSQTbZBP71L3j2WZg+Pe5oRESqhgqUIiI13Qd/Y9e8a+KOotpavRruf7gRO+S05fGnGnHhv5YxfdJfnNpvBbWy6Vf4035KJym47DJo2BCuvz7uSCSjKJ+VVGRpPptNP2UiIlIZ1qygtov5HYfV1Mef1KPLfm0496IW7N6pkG8/m8cdw5bQvLmLO7TyW1OgdJKCNm3gvPPg+edhypS4o5GMoXxWUpGl+awKlCIiIhXst7m1OOW0Fhxw6EYsWmy8+Gwe772xgI47rY47NKkCl1wCjRvDkCFxRyIiUvlUoBQREakgq1bBLXc0oUNOW156rSHXXrGUqV/N4/hjCzCLOzqpKq1bw4UXwn//C99+G3c0IiKVSwVKERGRCjD63frsuldbLr+2GT26r2TKxL+4/tqlNGqUhc1bZYNddBE0bw6DB8cdiYhI5crUt12JiEhV2fxIFqyYTou448hSP86uzb8vb8b/3mzI9tut5u1XFtDr0Ox7BqZMm/RkwarflU5S1LKlL1Redx189RXsvnvcEUmslM9KEitXwg8z6zB1eh2mzajDNquPZO4fa7j4OLKq0zYVKEVEarqdLuGX399h27jjyDLLlxtDb2/CLXc2oU4dx9Drl3DhufnUrx93ZJVk+7P5ZcFkpZNyuOACuOsuX0v5v//FHY3ESvlsjbZokTFtRh2mTvMFx6nT6zJ1eh1+nF2btWuLnodot/VltG27kIFLfQuHbKECpYiISDk4By+92oCLr2zGz7/U4eQTl3PLf5aw+WZr4w5NMkzz5r6Dnquvhi++gD33jDsiEakszvkO2aZNLyow+v/r8MeftddNV6+eY4ftVpOzWyF9T1jBTh1Ws+MOhXTYYQ2NGjlyJ0ymefPDYtyS8lOBUkSkphvTnZyFecDouCPJeFOm1uH8S5ozNrc+u+1SyLOPz6fbfqviDqtqfHw8OUvygey60InbeefBHXf4pq9vvRV3NBIb5bPVRmEhzPqxTrECY6LJan5+UTvV5s3XslOH1fzt0JXsuMNqdtqxkJ06rKbd1muoU1IJLEvzWRUoRUREyrB4sTHkpqbc+1BjmjRx3HfHIs46Y3nJFwUigaZN4bLL4PLLYfx46No17ohEJBX5+dFmqv4zc1YdVq8uaqa6+WZr2KnDak7rv9wXHDv4z8Ybr60xvXvrp1BERKQEa9fCM8815PJrm/HXvFqcOWA5/7luKW3aqHmrpO5f/4LbbvO1lO++G3c0IpLgHPz5Z61iBcZEk9VffytqplqnjmO7bVez4w6rOfaoAt9MtYP/3rSpevJWgVJERCSJ6TOacuWVGzHh83rss9cq3ngpjz12L4w7LMlCjRvDFVfAxRfDxx9Dt25xRyRSs6xZA7Pn1C5WYEwUIhctKmqm2qTJWnbcYTXdu61kpx1XB883rmbbbVZTr16MG5DhVKAUEREJWbMGrr2+KUNv35s2G63lyYcW8o9TVmRVF+6Sec4+G2691ddSvv9+3NGIVE8rVsD0GcULjFOn1WHGzDqsWlXU/nTjtmvYacfV9D1hxbpmqjt2KGSLzWtOM9WKpAKliEhNt9WJ/FUwRe9Hwz8refJpLXnrnQYccfivjHisNs2bqzkTAJsfyV+Fc5VO0tSoEVx5pX+VyAcfwEEHxR2RVCnlsxVq/vyiZqrhjnF++rk2zvkSYa1ajvbt1oQ6xilkpx19jWPLlhmar2dpPqsCpYhITbfDOcz99R12iDuOmE2fUZveJ7Vi1o91ePDuRey4y1SaN9857rAyxzYDmPvX5BqfTjbEwIEwbBgMGgQffYRqQmoS5bPltnYt/PxL7fV6Up06vQ7z5xc939iggaPD9qvZZ89VnNZ/9boax+23W02DBjFuQDqyNJ9VgVJEpKZbvZxariDuKGL11uj69D2tJfXrOd5/awHd9ltF7oS4o8owq1fU+HSyoRo08O+k/Ne/YMwYOOSQuCOSKqN8tkQrV8IPM0MFxmm+yer0H2qzYkXRswatW/vaxmOOLFjXk+qOHVaz9VZrqs8jCVmaz6pAKSJS0+Uezm419P1ozsGw25tw1eCm5OxWyKsjF7LVlmviDiszje/Pbkvygd5xR5LVzjijqJayZ0/VUtYYNTifLcm9DzZm2J378fvvDVm7tuhE2HorX1iMdoxTI3rXztJ8VgVKERGpkZYvN07/vxaMHNWQPscv5/EHF9OoUYY+VyPVRv36cM01vvnr6NHwt7/FHZFI1XtseCPOv6Q5u+6ykNP6rQlqHAvZYfs1NG6sfDjbqEApIiI1zs+/1OaYk1oy6du6DL1+CZddlK+aIqkyAwbAzTf7WspevVRLKTXL62/V56zzmnNYzwIuuXQiPffvGHdIsoGqS4tjERGRlHw0rh577L8Rs2bX4Y1ReVx+sQqTUrXq1oVrr4Uvv4Q33og7GpGq8+mEupzYvxW75xQyasRC6tRRbWR1oAKliIjUGA891ogeR7SmZUvH5x/O4/BeK+MOSWqo/v1h2219LaXTNbXUAFOn1eGoE1qzxeZrePOlPJo0UcKvLlSgFBGp6bYZwB8Nq3d3k6tWwdnnN+f/LmjBoT1W8lnuPDrsoM53ymWrE6p9OqlKderAddfBpEnw6qtxRyOVrgbks6X5bW4tDuvdirp1HO+8toC2bWtABzvpyNJ8VgVKEZGabpsB/NHo0LijqDR//VWLHke05uHHG3PFxUv534t5tGihO+PltvVJ1TqdxKFvX+jQwRcs1+r6unqr5vlsaRYtMnr1bs2ixbV4+5UFbNNeN/NKlKX5rAqUIiI1XcF86q5dHHcUleKrr+uyR7eNmPh1XZ57ciE3X7+U2rXLnk+SWJlXbdNJXBK1lJMnw6hRcUcjlaoa57OlKSiA3ie1YvoPdXj5uTw656yOO6TMlqX5rAqUIiI13bjj2XnhjXFHUeFeeLEB+x/SGoBx7y2g74krYo4oy30+sFqmk7ideCJ07AiDB8MaVdxUX9U0ny3NmjVwyukt+WhcfZ5+dCE9D14Vd0iZL0vzWRUoRUSkWlmzBq4c1JS+A1rRpXMhX348n907F8YdlkhStWv7wuTUqTByZNzRiFQM5+D8S5rz8msNuXPYYvqcUBB3SFKJVKAUEZFqY/Fi4+gTWjH09qacdcYyxr6pzh8k8x13HOy2GwwZAqvVIlCqgf/c0oQHHmnMpRfmc+G5y+IORyqZCpQiIlItTJ9Rm727b8S7Y+vz4N2LeOiexdSrF3dUImWrVcsXJmfMgOeeizsakQ3z2PBGXHt9M/r3Xc7QG5bEHY5UARUoRUQk6701uj57HdiGvLxajH1zAWefuTzukETKpXdv6NwZrr8eCtVCW7LU62/V56zzmnNYzwIef3ARtVTSqBF0mEVEarrt/4/fGh0ZdxRpcQ6G3d6EI49vxbbtV/PluPkcsL86fqgU7ftnbTrJBma+MDlrFjzzTNzRSIXL4nw2VeM/q8tJ/2jJ7jmFjBqxkLp1444oC2VpPqsCpYhITbf1ScxreGDcUZTb8uXGyQNacMWgZpx03ArGjVnAVluqm8xKs0XvrEwn2eSII2DPPeGGG2CV7otUL1maz6Zq6rQ6HHl8azbfbC1vvpRHkyZ6129asjSfVYFSRKSmW/YL9dfMizuKcvn5l9rs37M1I19qyNDrl/Dc8EU0aqQLmEq1/LesSyfZJlFLOWcODB8edzRSobIwn03Vb3Nr0euYVtSt43jnNXWEtkGyNJ+tE3cAIiISs/H92WlRHnBw3JGk5KNx9Tj+lJasXGW8MSqPw3utjDukmmHiBey0JB/oF3ck1dphh0HXrnDjjXDqqVC/ftwRSYXIsnw2VYsWGb16t2bholp8OHo+27RXK5ENkqX5rGooRUQkazz0WCN6HNGali0dn384T4VJqXYStZS//AKPPx53NCIlKyiA3ie1YvoPdXj5uTw65+idNzWVCpQiIpLxVq2Cs89vzv9d0IJDe6zks9x5dNhBd8KleurRA7p1g//8B1asiDsakfWtWQOnnN6Sj8bV5+lHF9LzYD30W5OpQCkiIhntr79q0eOI1jz8eGOuuHgp/3sxjxYt9LykVF+JWsq5c+GRR+KORqQ45+D8S5rz8msNuXPYYvqcUBB3SBIzFShFRCRjffV1XfbothETv67Lc08u5Obrl1K7dtxRiVS+7t3hoIPg5pthuV6rKhnkplub8MAjjbn0wnwuPHdZ3OFIBlCBUkSkptvxYn5pfFzcUaznhRcbsP8hrQEY994C+p6otn+x2m5gRqaT6uz66+HPP+HBB+OORDZYhuaz5fX4U424Zkgz+vddztAblsQdTvWTpfmsCpQiIjXdFkexoME+cUexzpo1cOWgpvQd0IounQv58uP57N65MO6wZNNDMyqd1AT77w+HHgrDhkF+ftzRyAbJsHw2Ha+/VZ+B5zbnsJ4FPP7gImqpFFHxsjSfVVIQEanplkyn4epf4o4CgMWLjaNPaMXQ25ty1hnLGPum3mmWMZbOzJh0UpMMGQLz5sH998cdiWyQDMpn0zH+s7qc9I+W7J5TyKgRC6lbN+6IqqkszWdVoBQRqek+P4sOi++JOwqmz6jN3t034t2x9Xnw7kU8dM9i6tWLOypZZ9IVGZFOapp99oHDD4dbboElamGYvTIkn03H1Gl1OPL41my+2VrefCmPJk3UKVqlydJ8VgVKERGJ3Vuj67PXgW3Iy6vF2DcXcPaZ6oVEJGHIEMjLg3vvjTsSqWl+m1uLXse0om4dxzuvqcWIJKcCpYiIxMY5GHZ7E448vhXbtFvDFx/P54D99T4zkbA99oCjj4bbboPFi+OORmqKRYuMXr1bs3BRLd5+ZQHbtNe7fyU5FShFRCQWy5cbJw9owRWDmnHicQV8MnY+W2+lCxaRZAYPhkWL4K67Yg5EaoSCAuh9Uium/1CHl5/Lo3PO6rhDkgymAqWIiFS5n3+pzf49WzPypYbcPGQJzw9fSKNGei5HpCSdO8Pf/w533OGbv4pUljVroN8ZLfloXH2efnQhPQ9WqxEpnQqUIiI13S7X8FOTvlW2uo8/qcce+2/ErNl1eH1UHldcko9Zla1e0tXh/CpNJ7K+wYN9xzx33BF3JFJuVZzPpss5OP+S5rz0akPuHLaYPicUxB1SzZKl+awKlCIiNd0mPVlYf/cqWdVDjzXi4MNb07Kl4/MP53FEr5VVsl6pAG0PqLJ0IsntuiuceCLcfTfMnx93NFIuVZjPboibbm3CA4805tIL87nw3GVxh1PzZGk+qwKliEhNt3ASTQpnVeoqVq2Cs89vzv9d0IJDe6zks9x5dNhBz0tmlUXfVXo6kbJddx0sW+Y76JEsUgX57IZ64qmGXDOkGf37LmfoDXpHTSyyNJ9VgVJEpKabeCHbLXmo0hb/11+16HFEax5+vDFXXLyU/72YR4sWel4y60weXKnpRFLTsSP07etfIfLXX3FHIymr5Hx2Q73xdn0GnteCw3oW8PiDi6ilEkI8sjSfVXIREZFK89XXddmj20ZM/Louzz25kJuvX0rt2nFHJZLdrrvO98J5yy1xRyLVwfjP6nJi/5Z07lTIqBELqVs37ogk26hAKSIileKFFxuw/yGtARj33gL6nrgi5ohEqocddoD+/eH+++H33+OORrLZ1Gl1OPL41my+2VrefCmPJk3UekTKTwVKERGpUGvWwJWDmtJ3QCu6dC7ky4/ns3vnwrjDEqlWrr0WCgth2LC4I5Fs9dvcWvQ6phV16zjeeW0BbduujTskyVIqUIqISIVZvNg4+oRWDL29KWedsYyxb+oiRaQybLstDBgADz0Ev/0WdzSSbRYtMv52TGsWLqrF268sYJv26iRN0qcCpYhITdfpJn5setoGL2b6jNrs3X0j3h1bnwfvXsRD9yymXr0KiE8yQ8fLKySdSMW55hrfIuDmm+OORMpUQflsRSgogN4ntWLajDq8/FwenXNWxx2SJGRpPqsCpYhITddmX5bU67hBi3hrdH32OrANeXm1GPvmAs4+c3kFBScZo/WeG5xOpGK1awdnnAGPPgo//xx3NFKqCshnK8KaNdDvjJZ8NK4+Tz+6kJ4Hr4o7JAnL0nxWBUoRkZpu3qc0WzUlrVmdg2G3N+HI41uxTbs1fPHxfA7YXxco1dKCL9JOJ1J5rrrK//3Pf+KNQ8qwAflsRXEOLri0OS+92pA7hy2mzwkFscYjSWRpPqsCpYhITffNVWyz9Mlyz7Z8uXHygBZcMagZJx5XwCdj57P1VnoOp9qaMiytdCKVa6ut4J//hCeegNmz445GSpRmPluRbrq1Cfc/3JhLL8znwnOXxRqLlCBL81kVKEVEpNx+/qU2+/dszciXGnLzkCU8P3whjRqpu3mROFx5JdSuDTfeGHckkqmeeKoh1wxpRr8+yxl6w5K4w5FqRgVKEREpl48/qcce+2/ErNl1eH1UHldcko9Z3FGJ1Fybbw5nnw1PPQUzZ8YdjWSaN96uz8DzWnBYzwKeeGgRtXT1LxVMSUpERFL20GONOPjw1rRs6fgsdz5H9FoZd0giAlxxBdSrBzfcEHckkknGf1aXE/u3pHOnQkaNWEjdunFHJNWRCpQiIlKmVavg7POb838XtOCQg1fyWe48duygruZFMsUmm8C//gXPPgvTp8cdjWSCadPrcOTxrdl8s7W8+VIeTZrosQSpHCpQiojUdF3uYmazs0sc/ddftehxRGsefrwxl1+0lNdH5dGihS5MapxdB5eaTiR+l10GDRvC9dfHHYmsp4x8tqL9NrcWh/VuRZ3ajndeW0DbtmurbN2yAbI0n1WBUkSkpmuZQ37dbZOO+urruuzRbSO+/Koezz25kKE3LKV27SqOTzJDi11KTCeSGdq0gfPOg+efhynZ9+aB6q2UfLaiLVpk/O2Y1uQtrMXbr+SxTXv1vp01sjSfVYFSRKSm+2MMLVd+td7gF15swP6HtAbgkzHz6XviiqqOTDLJXx8lTSeSWS65BBo3hiFD4o5Eiikhn61oBQVwTJ9WTJtRh1eez2P3zoWVvk6pQFmaz6pAKSJS0313I1vnP7/u65o1cOWgpvQd0IounQv58uP5uigRmH5PsXQimal1a7jwQvjvf2Hy5LijkXUi+WxlWLMG+p3Rkg8/rs/Tjy6k58GrKnV9UgmyNJ9VgVJERNZZvNg4+oRWDL29KWedsYyxb+rZG5Fsc9FF0KwZXHdd3JFIVXEOLri0OS+92pA7hy2mzwkFcYckNYgKlCIiAsD0GbXZu/tGvDu2Pg/evYiH7llMvXpxRyUi5dWypS9UvvIKfJV9reckDTfd2oT7H27MpRfmc+G5y+IOR2oYFShFRIQlS+uy14FtyMurxdg3F3D2mcvjDklENsCFF0KLFjB4cMyBSKV74qmGXDOkGf36LGfoDUviDkdqIBUoRURquN9+gx9nN2Wbdmv44uP5HLC/nrsRyXbNm/sOel5/Hb74Iu5opLK88XZ9Bp7XgsN6FvDEQ4uopSt7iYGSnYhIDfbSS3DwlQ/z8Fc38cnY+Wy9lbqXlxLkDGV68/PjjkLK4fzzoVUrPUuZEfZ6uMLPn/Gf1eXE/i3p3KmQUSMWUrduhS5e4pCl+awKlCIiNdTnn0O/ftC6XQcGnLuMRo1c3CFJJmu6HSvqbBl3FFIOTZvCZZfB22/D+PFxR1PDNetQoefPtOl1OPL41my+2VrefCmPJk2Uf1cLWZrPqkApIlIDzZkDRx0Fm24Kbz/2Opu5T+MOSTLd7+/SumBC3FFIOZ17LrRpo1rK2P36eoWdP3N/r8VhvVtRp7bjndfUE3e1kqX5rAqUIiI1zOLFcMQRsGoVvPkmNJ97O1sueynusCTTzXxE6SQLNW4MV1wB770HH38cdzQ12LSKyWcXLTJ69W5N3sJavP1KHtu012MK1UqW5rMqUIqI1CCFhXDCCTBjhn9+cqed4o5IRCrb2WfDJpuoljLbFRTAMX1aMW1GHV55Po/dOxfGHZIIoAKliEiN4Rycc46vqXjkETj44LgjEpGq0KgRXHklfPCB/0j2WbMG+p/Zkg8/rs/Tjy6k58HqjVsyhwqUIiI1xK23wmOPwVVXwWmnxR2NiFSlgQNhs81g0CB/c0myh3NwwaXNGfVKQ+4ctpg+JxTEHZJIMSpQiojUAKNGweWXw0knwQ03xB2NiFS1Bg3g6qth3DgYMybuaKQ8br6tCfc/3JhLL8znwnOXxR2OyHpUoBQRqeY++wz694euXWH4cNZ/8XXXZ5ja4rI4QpNs0uVupZMsd8YZsOWWqqWMRZr57BNPNeTqwc3o12c5Q29YUgmBSUbJ0nw2rQKlmakgKiKSBebMgaOP9k3dXnvN11Ksp/GWrKzdpqpDk2zTaHOlkyxXvz5ccw1MmACjR8cdTQ2TRj77xtv1GXheCw7rWcATDy1a/2agVD9Zms+mlDTN7Cwze8S8C4FlZvanmXWvzOBERCR9ixYVfz1Im5J+o34aSZsVH1ZlaJKNfn1N6aQaGDAA2rVTLWWVK2c+O+HzupzYvyWdOxUyasRC6tatxNgkc2RpPpvqvY5zgQ5AbeD6YFgb4ObKCEpERDZM+PUgL78MO+5YysQ/PMjmy9+ostgkS81+RumkGqhXD669Fr78Et7Q4aw65chnp02vwxHHtWbzzdby5kt5NGmikn+NkaX5bKoFynbANHyhsglwGPBfYOfKCUtERNKVeD3ImDHw6KNw0EFxRyQimaR/f9h2W9VSZqK5v9fisN6tqFPb8c5rC2jbdm3cIYmUKdUC5VqgJbBn8P/XwGLAKikuERFJU+L1IFdf7Zu3iYiE1a0L110HkybBq6/GHY0kLFpk9OrdmryFtXj7lTy2ab8m7pBEUpJqgfJb4DjgcWCyc24psC3wc2UFJiIi5Zd4PUifPnD99WVPLyI1U9++0KGDL1iuVSVY7AoK4Jg+rZg2ow6vPJ/H7p0L4w5JJGWpFijPB8YDXwDnmFk9YA3wbGUFJiIi5ZN4Pci++8KTTyZ5PYiISKBOHV+YnDwZXnop7mhqtjVroP+ZLfnw4/o8/ehCeh68Ku6QRMolpcsN59zXzrn9nXP7OOfGO+dWOecOc86pUx4RkQwQfj3Iq6+W8HqQkuw/iu9bXlNJkUm1sdcjSifVzIknQseOMHiwL9RIJSohn3UOLri0OaNeacidwxbT54SCGIKTjJGl+WydVCYys/NLGLUSmAF85JxTViQiEoOUXw9SkgYbUVireWWEJtVJ/VZKJ9VM7dq+MHniiTByJJx8ctwRVWMl5LM339aE+x9uzKUX5nPhuctiCEwySpbmsykVKIG7gNL6AZtkZoc75/7c8JBERCRVhYVw/PHwww/w7rtlvB6kJD8OZ5Plk4FdKzo8qU5+Gskmy3/Fd/Qu1cVxx8Guu8KQIb5gWSfVK0MpnyT57JNPN+Tqwc3o12c5Q29YEl9skjmyNJ9N9Qmbj/EFyvnAZ8C84PvnwCIgBxhS8eGJiEhJnIP/+z8YO9a/HqR79zQX9ONwNlnxXkWGJtXRzy8qnVRDtWr5wuSMGfDcc3FHU41F8tk33q7PP89twWE9C3jioUV65l28LM1nU02+X+ILkls45/YFtgQmAJ8G/38FHFJRQZnZs2b2u5ktMbMZZnZmaFwPM5tmZsvN7AMz2zo0rr6ZPRHM94eZXRRZbonziohkm1tugccfh2uugVNPjTsaEclWxxwDnTv7nqEL1blopZvweV1O7N+Szp0KGTViIXXrxh2RyIZJtUB5JvCXc64QIPj7F3CGc2458DqwWQXGdTPQzjnXDDgauNHMupjZRsDLwLVAK3xBd2RovsHA9sDWwEHAZWbWCyCFeUVEssaoUXDFFXo9iIhsODNfSzlrFjzzTNzRVG/TptfhiONas/lma3nzpTyaNCntiTKR7JBqgXIecLSZjTWz+8zsHaA3vlAJsBWwsKKCcs5975xbmfgafLYF/g5875x70TlXgC9AdjKzxFNDpwI3OOcWOuemAo8CA4JxZc0rIpIVJkwo/noQs7gjEpFsd+SRsMcecMMNvoMvqXiFhbXodUwr6tR2vPPaAtq21QtApXpItUB5Gf69kwcB/4dv3roGXwPYDNgJ+G9FBmZmD5jZcmAa8DvwFrAz8E1iGufcMmAWsLOZtQQ2DY8P/t85+L/EeSsybhGRyjR7NvTunebrQURESmDmWzvMmQPDh8cdTfWzejXMmt2UBXm1ePuVPLZpr5cjSPVhzqVW1W5m2wF98E1bfwNecM7NqsTYMLPaQFegOzAMeAiY55y7IjTNJ/iayLHAz0DDoAYSMzsEeNQ5187MHi9pXufc8Mh6BwIDATbeeOMuL7zwQqVtY7ry8/Np0qRJ3GFkHO2X9WmfrC9b90l+fh3OPbczeXn1uO++r9hqqxUVstxaawvIz19KoyYtKmR51UX+sgKaNFaJPaGWKyB/WQGNmpX3vTTVX7bmKVHOwXnndWbevPo888xn1KuXfnPM6rJPNtTatTBu3EaMfK4tv/zSiOsGT6dLl7y4w8oYymeLy+R89qCDDpronNsj2biUO4d2zs0EbqywqFJb5xpgnJn1w9eM5gPNIpM1A5YG4xLfCyLjKGPe6HofAR4B2GOPPVz3tLtOrDy5ublkYlxx035Zn/bJ+rJxnxQWwt/+BnPn+teDdO++d4UuP/f9d+i+jxpshOVO+F77JCJ3wuSsO3eqQjbmKSW56y445BCYOfNAzjkn/eVUp32SjlWr4Nlnfedp06fDttvClVd9xcX/2hTfoE5A+Wwy2ZjPptTk1cy2NLOnzOxbM/sx9KnUGsqQOvhnKL8HOoXiapwY7pxbiG8a2yk0X6dgHkqbt1IjFxHZQBX2epCSzHiAzZa/XsELlWrnx+FKJzVAjx7QrRv85z9QUFD29FJcfj7ceSdssw2ccQY0agQjR8KMNx7guE5PxB2eZLoszWdTfYbyeaAfsAvQLvKpUGbW1sz6mFkTM6ttZocBffFNWl8BdjGz48ysATAI+NY5Ny2Y/WngGjNrGXS2809geDCurHlFRDJSpb8e5Of/0nbFR5WwYKlWfntD6aQGSDxLOXcuPPxw3NFkj/nz4brrYKut4KKLYPvtYfRomDgRTjwRav2qfFZSkKX5bKpNXjvjn08cAizC97paWRy+eetD+ALvT8CFzrn/AZjZccB9wLP4d2P2Cc17HfBgMM8KYJhzbjSAc25eGfOKiGScF1/0rwfp21evBxGRqtG9Oxx0ENx8M/zzn76WTZL7+We44w7femT5cv9Oz8svh332iTsykaqTaoHyS+DnaOc1lcE5Nw84sJTxY4Ckr/oIXjVyevAp17wiIplmwgT4xz9gv/3giSf0ehARqTpDhsABB8CDD8LFF8cdTeaZOtW3Hnn2Wf/9lFPgssugY8d44xKJQ6oFyk+AS8xsITAJWJ0Y4Zx7uhLiEhGp0WbPhqOPhs03h1de0etBRKRqdevmO+cZNgzOOgvUYav32WcwdKh/bVPDhnDOOb6J69Zbxx2ZSHxSLVBegW+K+q8k41SgFBGpQIsWwRFH+PeWvfkmtMm83sNFpAYYMgT23Rfuv98346ypnIP33vMFyQ8+gJYtYdAgOO882GijuKMTiV+qBcqPqNznJkVEBN/V/HHHwcyZ/vUgHTpUwUp75jLp/XfoXgWrkizWbRSTJkxWOqlBunb1ryu65Rbf03Sz6MvXqrk1a+Dll31B8quvYLPN4Pbb/XOlTZuWc2HKZyUVWZrPplSgdM51r+Q4RERqvMTrQd5/H556qhJeDyIiUk5DhsBee8G998LVV8cdTdVYuRKeftoXpGfOhB12gMceg379oH79uKMTyTwlFijN7ADgV+fcj8H/STnnsq9vWxGRDDRsmO9859prfWc8VWbqbWy5bDqwaxWuVLLODw+x5bLfgcPijkSq0J57wlFHwW23wbnnQvPmcUdUeZYu9a9KueMO+P136NIFRo3yPbfWrr2BC1c+K6nI0ny2tBrKD4C7gIuBXJI3eXVlLENERFLw3//ClVf614MMGVLFK//tDVoX5FXxSiXr/DGG1gX5cUchMRgyBHbfHe66y79rsbqZNw/uvts/K7poEfTo4Wsoe/SowN61lc9KKrI0ny2tMPgLsDD4/2f0DKWISKUYP16vBxGRzNW5M/z9777m7vzzfac01cFPP/ma18cfh4ICOPZY/97fPfeMOzKR7FJigdI51y7Z/2Fm1qLCIxIRqUF+/BF694YttvDd0Ov1ICKSiQYP9h3U3H473Hhj3NFsmO++889HPvcc1KoF/fvDpZfCjnpTuUhaaqUykZk9lGTYZvjeX0VEJA0LFxZ/PYi6nxeRTLXrrnDiib5p6Pz5cUeTnvHj/ft9d93VF47PPx9mzfI1lCpMiqQvpQIlMNDMHkx8MbNtgU+AnSslKhGRam7VKjj+eH8x88orVfR6kJLUbsgaU9eFUobaDZROarjrroNly3wz0WzhHLz9Nhx4oH+n5qef+mdCf/rJN+HdcssqCkT5rKQiS/PZVAuU4wgKlWa2O/ApsDXwdKVFJiJSTYVfD/LYY/5CJ1YHvc3kVlnehk0q377PKp3UcB07+o7D7r0X/vor7mhKt3o1vPCCf/7z8MP94wV33eULkoMGQevWVRyQ8llJRZbms6kWKA8D3gPOAiYAbYAhzrnTKiswEZHqaujQmF4PIiKygQYN8h3Y3HJL3JEkV1DgX/3RoYMv/K5cCU8+6VuDXHABNG4cd4Qi1U+JBUozOyDxAfYEbgdmALWBp4APSns/pYiIrO+//4WrroKTT47h9SAlmXwDW+ePiDsKyXTT7lQ6ETp0gH79/Cs2fv897miKLF7s3+Xbrh2cfbZ/Jv2VV+D772HAAKhXL+YAlc9KKrI0ny3ttSG5lPyqkH8EH72HUkQkReHXgzz+eAa9HuTPsbRcqfejSRnmfULLldn3fjSpeNdeCyNG+ALcXXfFG8uffxa9Q3LJEjj0UP/qj+7dMyiPBeWzkposzWdLKwzq3ZMiIhVErwcRkepiu+3g1FPhoYf86zY237zqY5g9G2691T8+kOjk7PLLoUuXqo9FpKZL6T2UIiKSvvDrQd56S68HEZHsd8018PTTcPPNcN99Vbfeb7/1NaMjR/p3SJ56qi/U7rBD1cUgIsWl2ikPZtbczM40sxvM7Awza1GJcYmIVAvR14PookdEqoP27eGMM+DRR+Hnnyt/fePG+RtznTrB//4H//63r6V89FHlqyJxS6lAaWY7AFOAh4GrgEeA780szjeniYhkNOd85xAZ83qQktRvTWGtZnFHIZmuXkulEynmqqv835tuqpzlOwdvvAH77w/dusHnn8MNN/gC7K23xtPUNm3KZyUVWZrPplpDeRuwKfANMBKYFHzP0E6jRUTiN3So765+0KAMfz1It5f4vuW1cUchmW7vR5VOpJittoJ//tN3MjZ7dsUtd/Vq3+nPbrvBUUfBL7/APff4d0hecw20bFlx66oyymclFVmaz6ZaoNwHeNc5t7tz7mTnXBfgHaBr5YUmIpK9Ro4sej3I4MFxRyMiUjmuvBJq14YbK+Bd7CtWwAMPwPbb+1eTrF3rn9OcORPOOw8aNdrwdYhIxUu1QGnAqsiwVcFwEREJGT/edxSx//4Z9nqQkky6kvZLn4g7Csl039+sdCLr2Xxz37T/qad8wS8dixb5ZrNbbw3/+hdssgm89hpMngz9+0PduhUacjyUz0oqsjSfTbVAORE4wszGmtl9ZjYGOBL4svJCExHJPj/+CEcf7V8P8sorWfJ6kPnjab5qatxRSKbLm6h0IkldcQXUq+efbyyP33/3r/rYaiu4+mr/yo8PP4RPP/X5aK2Uu47MAspnJRVZms+meqpeBiwBDgLOAQ4Ovl9RSXGJiGSdxOtB1qzR60FEpObYZBM45xx49lmYPr3s6WfOhLPOgnbt4LbbfL759dfw9ttwwAFZ0KpDRIpJqUDpnPsW2Am4HHgw+NvROfdNJcYmIpI1Vq2C447zrwd59VV1Yy8iNctll/kWGddfX/I0X38NffpAhw4wfDicdpovgD7/POTkVFWkIlLRUm5M4Jz7A3gFeBl4xTn3e6VFJSKSRRKvB/ngA//M5AEHxB2RiEjVatvWd5zz/PMwZUrRcOd8M9a//Q1239233rj0UpgzBx56CLbbLraQRaSCpPoeyuZm9hYwHXgXmG5mb5tZ80qNTkQkC9x8c9HrQfr3jzuaNDTagpW11T5XytBwU6UTKdUll0DjxjBkiO+h9bXXYN99oXt3+Oor3/HOzz/7Vyptumnc0VYx5bOSiizNZ+ukON1/gF7AamA+sBFwKHAT8K/KCU1EJPONHOk7k8jq14Ps+yxT33+HjeOOQzLbHvcydcJkpRMp0UYbwQUXwH/+A+PH78Uvv/jnJO+/3zdvbdgw7ghjpHxWUpGl+WyqTV6PBL4DNnXObQZsCnwPHFFZgYmIZLpPPy16PcgTT6gjCRGRiy+GjTeGunXXMmIE/PCD77CnRhcmRaq5VAuUrYCJzrkFAMHficFwEZEa58cfoXdv2HJL/3qQ+vXjjmgDTLyQ7ZY8FHcUkum+HaR0ImVq2dI3a33ssS85+WSok2pbuOpO+aykIkvz2VRP8+lAHzObBUwDdgROwtdSiojUKAsXwuGH+2eE3nyzGrweZOEkmhTmxR2FZLrFU2hSmB93FJIF6tVTi431KJ+VVGRpPptqgfIm4CVgSGiYAUMrPCIRkQy2ahX8/e++hnLMGL0eRERERGq2VN9D+Qr+Ocp38DWUo4EjnXMvVWJsIiIZxTn/Mu7cXP/MpF4PIiIiIjVdyi3bnXNvAW9VYiwiIhntppv8y7ivuw769Ys7GhEREZH4lVlDaWb7m9mZZtbOzFqb2WNm9pGZDTWzbO6GQkQkZS+8ANdcA6ec4guU1UrTHVheZ4u4o5BM12QbpRORdCmflVRkaT5bag2lmZ0L3B18XQxMBroF3/cD6gIXV1p0IiIZ4NNPYcAA/3qQxx+vhp1N7P0IM95/h83ijkMyW+dbmDFhstKJSDqUz0oqsjSfLauG8uzg79dAc2B/4AXgEmApcGzlhSYiEr9Zs4peD/Lqq1n+ehARERGRClZWgXJr4Dnn3B7A88GwM5xzdwAvQtYVoEVEUrZwIRxxhH89yFtvQevWcUdUST4byA6L7y57OqnZvr5M6UQkXcpnJRVZms+W1SlPY+Cv4P95AM65FcH3fHyTVxGRaif6epDtt487okq0dAaNVuv9aFKG/B9ptDr73o8mkhGUz0oqsjSfTeW1If3M7CvgZAAz+yr8XUSkunEOBg7U60Ey1jt7wKLv/IF6Zy/In13ytNPuhG+uqrrYRESqA+WzUg6pvDakTfBJyAn97yo0GhGRDHDTTfDUU3o9SKVYtQje2hkOGQ+Ntyoa/u21sKYAOt9a9vwF86Dp9r53pMM+L336pTNgo303NOrifnkZZj4Cy37yMTTrCHvcCw03rdj1iIikQ/msVLGyCpSnVUkUIiIZ4vnn/etB+vWrhq8HyQSLv4c6jaHRlsWHL5kKmx1Z9vxLpkGTbaB2ir0jLZ0B255R/jhL8tNImHEP7PkgNN8VVi2E30dD3RYVtw4RkQ2hfFaqWKkFSufcU1UViIhI3D75BE47Dbp1g8ceq4avBylJyxzy83+iRVWsa/H30HSH9Xfukhmw087+f+fghwdg9lNQuBTaHuDvqNdt5i+Imu3op5vzPPzxHuzzRDDfWvjhfpj5KNSqA7tcB/lzoOmOsHI+fH0JLPwa1qyA1l1hj/ugblNYvQze2BF6fQkNNg7imUbXv/pA4Xio26Qozp9fgHb9oMVu/nv9VtAu8gTInBEw61FY8Qe02gO63AX1Nyo9BvB34r+9xo9fWwgtO8N+L5S+P2Y/A3+86y8cf/sf1KoHu9/lp6lozTuSv2JB1aQTkepG+azy2VRkaT6byjOUIiLV3qxZcMwxsNVW8MorNez1IF3uYmazs8ueriIs/g6adig+rGCevwPdvKP/PvUW+PMDOPB1+NvXsHaVf0YHggudnYL/pxTNA36aP8bAwWOgRy78+AQ0aOsvVAqXwjanw6Gfw6Gfwao8mPOsn69OY2i6HSyaXLSs72/i58Z9il/kANRqAD+94C8qVibpYGP6Pf7iY+8n4fBvoeEmMOUWP660GAAmXgAb94C/feM/O16cwv6YAnlfwSaHwt++9RdhP9yfypEov93+v737Do+qTPs4/r3pvVdBUQEBA4KCvWFX7IJdX9uKqOu69rK6uurq2tuudXV1LbtiV1BRROwFlF5FlN5bEloged4/npOdSQJkGDI552R+n+s6V5I5ZzL3nJzcM/c87Y7Ku05EqhrlWeXZVMQ0z6YyhlJEpEpbvjyxPMjQoVV4eZAoWDUZVv8KC4clbnNF0GBH/4Zj3RKY+S//RqX4U+ztjoVZwcpVq6ZA68MTv6u4m9X6ZTDjKTj0E//mBvybhhVj/PcNdvIb+G5crQ6CDSsTMTTp6d/otDkcln4HeT8zv+HVlJnct/ejMP3vMPFO/8l460NhjwcTn4xPfwwOGZZ4rA5nJCarKC+G1bPAFfqteh1ovmdq52OXy6F1X/9zw86w7Pvy/goiUpUpz24+BuXZjFBBKSJZraAA+veHX3/NguVBNuebc+i2cj7wcrmHbpPC9ZD3M+z5FDTtmbj91xf9izz4F+lGXf0nzsUKlvs3L85B3rTEp+W5UxLfL/nKv8jX3zFxv/VLE5+yz3sffvmnn6mwaIPvCtXr3sSxTXvBki/995Pugm7X4eZtYmWsOq1gtzv8tnI8fP87mP4P6HGbj6GoAEYmj1Fy0Lh7ajH0edx/8j7tYWhzFHS/pfzzkTu15AQbudN8V7dMGH0F3VauAI7KzO8XqcqUZ5VnUxHTPLvZgtLMLgPGOue+MbODgLnOuZmVF5qISGYlLw/y8st+7GRWWjOX2oWVsD5a3jT/KXmrg/yn5MXyf02MlSlYlhjrUmzBx9DuWFgzG6gO9drDmrngNkK9DsH9lkPtpKblog1+Eofut/o3IJPuDiZ4CN50fLw3NM5JHN+0px8/M2+of0PW/mSYN3nLz6fJbv5NSOGaIIaV0PZo2OuZssemEkPLA/y2fil8ey7MHuw/Qd/s+Zjjz0GDjol9qyb6GDJh7QJqF8ZvfTSRSFCeVZ5NRUzz7JbGUP4dGBB8PxK4POPRiIhUor/+1S8PcvvtcPbZYUeTBVZOhEa7lHyTA7BiXOIFv0kvP1Zl9W9+Eocp98P6JbDDGb7bUaNgXNCqyf5T8eJJJxp0hGWjIP8X2JAL426CtfP8MasmQ93t/KfsG1bBmKt9161GSZ8wN9rVP87EOyDnpk3PyDT97/4xCtf7bdZrsPRb2OH0IPbusPSbxBihDXmwYJj/5KK8GOZ/APkz/bEb86FglT8nWzofxRNnWNJL+aqJJcc7iUh2UZ5Vng3Blrq85gMnmVlu8PO+Zvbn0gc55+7ISGQiIhn0n//Arbf65UH+XCazSUasmuTH0CRbvwzWzk280WnaE3a5Ar442a+X1upAOGAw1KgbdL3qlvhdxd2swH8a3/4EGNkParf041+q1fFjaWqdAvOHwNAc/0ap9WG+21a1Won7V6/t3zRUr+/H62zKxjz46SpYtwhq1PPT2e//GjTbw+9v1ge6XAU/XOyfV81G0OYIaHsUbF9ODMt+8DMPbsjz3a52udx/ig6bPx+rJpf85H398mDtuFKTcYhI9lCeVZ4NgTnnNr3D7F3geGDTB4ABzjlXPUOxRUKfPn3c6NGjww6jjJEjR9K3b9+ww4gcnZeydE7Kevzxn7j22j3YZx/4+OMsm9F1U4b3ZeWK5TQ59qOwIwlPUQF8sr8fd9SsNwAjv5tE331yyrljFvlyACtz82ly6viwI4kc5dmydE5KUZ5Vnk1FhPOsmf3onOuzqX1baqE8BxgE7AJcBEwBfqj48EREKs+MGXDLLT3o0AHeekvFJAAt9mXV6pmxW/eqQk19CJrt+b83ObIJzXqzat3i7L5ORNKlPKs8m4qY5tnNFpTOuTzgfgAzqwF87Jz7T2UFJiJS0WbPhqODcfRaHiRJr3v4dfkwOoQdRxhWToCvTvVdvPZ6Luxooi3nJn7Nm5Cd14nItlKeVZ5NRUzzbErLhjjnLjCzxmb2O6AD8BvwpnNuZQZjExGpML/8AoceCqtWwT33TKBz5z3CDkmioEkPOG5q2FGIiFRdyrNVXkoFpZntAnwGJC3Qwh1mdqhzblpGIhMRqSBTpsBhh/k1J0eMgNzc3PLvlE2+7E/OikXA4LAjkSj7/mJyVqwibuujiUSC8qykIqZ5dkvLhiR7AGgLjANeA8YGP9+XmbBERCrGuHFw8MF+lvDPP4c91DBZ1vpl1CxSkS3lKFih60QkXcqzkoqY5tmUWiiBffBjKP+3iqeZfQjsm5GoREQqwA8/wFFHQcOG8Omn0Llz2BGJiIiIVC2ptlAaUFDqtoLgdhGRyPnySzj8cGjWzH+vYlJERESk4qXaQvkjcKyZfYpfPqQrcAjwcaYCExFJ1yefwIknQocOMHw4tGsXdkQiIiIiVVOqBeX1wOf4IrIvvmVyFXBjZsISEUnP++/DgAHQrRt8/DG0ahV2RDHQ+jBWrPk5duteSSVruT8r1i/SdSKSDuVZSUVM82yqy4aMN7NuwLnAjvhlQ152zi3IXGgiIltn8GA4+2zYfXf46CPf3VVS0ONWZi0Zxk5hxyHR1vUqZq2coOtEJB3Ks5KKmObZVFsocc4tBO7PYCwiIml78UW48ELYf38YMgQaNQo7IhEREZGqL+WCUkQkqp56Ci69FI44At5+G+rXDzuimPnsGHosXwq8G3YkEmXfnEOPlXnEbX00kUhQnpVUxDTPpjrLq4hIJD30kC8mjz8e3ntPxWRaCtdS3a0POwqJusJ1uk5E0qU8K6mIaZ5VQSkiseQc3HUXXHMNnHoqvPkm1KkTdlQiIiIi2WWrCkozq2Nmu2YqGBGRVDgHN98Mt94K//d/8OqrULNm2FGJiIiIZJ+UCkozq2tmzwH5wHgz28nMfjGzKzIbnohISUVFcOWV8Le/waBB8K9/QQ2NBhcREREJRaotlHcCFwTHm3PuV2AFcHamAhMRKa2wEAYOhMcfh6uvhieegGrquL/t2h3Hsjp7hx2FRF2bw3WdiKRLeVZSEdM8m+pbsQHA18CTSbeNA3ap8IhERDZhwwbfvfW553xX1wceALOwo6oiul3LnPoDwo5Coq7zIF0nIulSnpVUxDTPplpQNgVmAAVJt9UF9HZORDJu/Xo4/XQ/VvKee+COO1RMioiIiERBqiOPpgL9gDEAZvZ74CRgbEaiEhEJrF0Lp5wCH30Ejz4Kf/hD2BFVQcP70mvFcuCjsCORKPtyAL1y84nb+mgikaA8K6mIaZ5NtYXyr0BL4Ijg50eBOsDfMhGUiAhAfj4ceywMGwbPPqtiUkRERCRqUmqhdM69Z2bHAH8AOgC/Af9wzn2YwdhEJIutXAn9+sEPP8BLL8HZmgJMREREJHJSnmzfOTcMGJbBWEREAFi6FI46CiZMgMGDfZdXEREREYmelApKM3toM7vWA9OBN51zuRUWlYhkrYUL4fDD4Zdf4J13fCuliIiIiERTqi2UfwTcFvb/xcz6OudmbntIIpKt5syBww6D+fNh6FA49NCwI8oSO5zG4nWTaRJ2HBJt7Y5j8Yb5uk5E0qE8K6mIaZ5NdVKe1/AF5fjg+3HBz+8C04D2wJ2ZCFBEssPMmXDggbBoEXz8sYrJSrXLZcyvd3zYUUjU7Xy+rhORdCnPSipimmdTbaHcAHzinDum+AYz+xDIA3KA4cABFR+eiGSDqVN9y+S6dTBiBPTuHXZEWWbjGqq5dWFHIVG3ca2uE5F0Kc9KKmKaZ1NtoTwFqFXqthrAKc45B4wEWlVgXCKSJcaPh4MOgsJCGDlSxWQoRvZjt+W3hh2FRN235+o6EUmX8qykIqZ5NtUWyl+Bvmb2M76LayegMzAx2N8NWFzx4YlIVTZqlJ/NtV49+PRT6NIl7IhEREREZGuk2kJ5KZALdAT6AbsAq4BLzawRvjB9MiMRikiV9NVXvptrkybw5ZcqJkVERETiKKUWSufcV2a2I3Ac0A6YBwxxzq0KDjktM+GJSFU0fDiceCK0b+9bJtu3DzsiEREREUlHql1eCYrHV8ysIWAAZtZI60+KyNYYOhT694dddoFPPoHWrcOOSERERETSlVKXVzNrb2YfmNlqYCWwItiWZzA2Eali3ngDTjoJevSAzz5TMRkZO5/PwrpHhB2FRN0Op+o6EUmX8qykIqZ5NtUxlP8Ajgbq4lsnkzcRkXK99BKcfjrsvbfv8tq8edgRyf/sfD4L6x0ZdhQSdR1O13Uiki7lWUlFTPNsqgXlQcBPwL8BB+wN/AJcmKG4ZAu++gruvLMb99wDQ4bAb7+Bc2FHJbJ5zzwD550HffvCsGHQuHHYEUkJ65ZSs2hV+cdJdlu/XNeJSLqUZyUVMc2zqY6hrAd8C6wJfp4AfA7cDLyYgbhkCxYuhEmTGjNiROK2hg2he3e/9ejht+7doUWL8OIUAXjkEbjqKujXz3d5rVs37IikjK8GkLNiOfBR2JFIlP0wkJzcfDQPn0galGclFTHNs6kWlMuBBsBMfDfXwcC+QJ0MxSVbMGAAtGjxHXvs0ZeJE2HiRJgwwW9vvgnPPps4tk2bRHFZXGjuuqtf908k0/76V7jlFj8Jz6uvQq1aYUckIiIiIhUp1YJyItAb+CtwP375EIC3MxGUpKZRI9hvP78Vc863YE6YULLQfPJJWLfOH2MGHTuWLTQ7dYIaKc/7K7J5zvlC8u674Zxz4F//0rUlIiIiUhWl+hbvGKCac67AzPoC/YFFwOMZikvSZAZt2/rtyKQxvYWFMHNmosAsLjbffReKivwxtWtDt25lC8127fzvFUmFc76L66OPwsUXw1NPQbVUR2uLiIiISKyUW1CaWQ1gGPA18Gfn3FfAV5kOTCpW9erQubPfTjklcfvatTB1aslCc8QIPyNnsSZNEgVm8temTSv9aUjEFRXBpZf6SXiuvBIeflgfRoiIiIhUZeUWlM65jWbWFT9+UqqYunVh9939lmz5cpg0qWRr5quvwqqkiafatSs5AVCPHr6Fs45G1maljRvhggvg5Zfh5pvhrrtUTMZG50uZN3EcTcKOQ6Jtp3OZ9/McXSci6VCelVTENM+m2uX1DuAuM3sZ+MY5tyGDMUkENGsGBx7ot2LOwbx5ZbvNjhgBBQX+mGrVfCto6UJz5519K6lUTQUFcNZZflKou+6CP/0p7Ihkq3Q4nSW/NAk7Com69ieyZO6EsKMQiSflWUlFTPNsqgXlk/j1J0cAWKLZwTnnNNVGljCD9u39dswxids3boQZMxKF5oQJMHasLy6K18esW9fPLlu60GzTRq1YcbdunZ95eOhQ38X1j38MOyLZaqvnULtwSdhRSNStmafrRCRdyrOSipjm2a0pBjf1tl+lgFCjBnTt6rdTT03cvno1TJ5ccrbZjz6CF15IHNO8edm1M7t39zPYSvStXg0nnuhbqZ96Ci65JOyIJC3fnku3lcuBQ8OORKLsxyvplpsPnBN2JCLxozwrqYhpnk21oNwpo1FIlVS/Puy5p9+SLV1adlmTF16A/PzEMR06lC00u3bVOoZRsmoVHHssfPstvPginHtu2BGJiIiISGVLqaB0zs0CMLNdgE7OuQ8yGpVUaS1awCGH+K2YczBrVtlCc9gw36UWfEtoly5llzXp0EHLUlS25cvhqKN81+b//rdky7SIiIiIZI+UCkozawYMBg4BnJl1Bn4G7nbO/TmD8UmWMIMdd/Tb8ccnbi8ogOnTSxaa333ni5hiDRpATg7sthu0bduS3XeHxo0r+xlkj0WL4Igj/N/l7bfhuOPCjkhEREREwpJql9f78Z2+1wO1nHO/mtl3wPGACkrJmFq1EuMqk+XllV3W5PXXYeXKHO65Bw4+2Bemxx8PO6nDdoWZOxcOPxzmzIEhQ/z3IiIiIpK9Ui0ojwY+AqYBfwhumwycnomgRMrTsCHss4/fihUWwhNPjGHOnN15/3248kq/de+eKC732kvLl6Tr11/hsMP8GNhhw+CAA8KOSCpM12uYM/6n2K17JZWs00DmTJul60QkHcqzkoqY5tlUR57VBVaUuq0FUFCx4YCZ1Taz58xslpnlmdlYMzsmaf9hZjbVzNaY2Wdm1qHUfZ83s1wzW2hmV5f63Zu9r8Rf9erQo8cq7rsPpkyBn3+Ghx6Cli3hvvtgv/2gbVu48ELfVTN5EiDZsunT4aCDYOVK+PRTFZNVTvvjWVZnn/KPk+zW9khdJyLpUp6VVMQ0z6ZaUI4HjgP2BjCzB/DdXcdlIKYawBzgYKAxcAsw2Mx2NLMWwFvArUAzYDTwWtJ9bwc6Ax3w4z2vN7Ojg5jLu69UMZ06wVVX+SUtliyBV1/1XTTffhtOOcVPDnTMMfDEE74Lp2zaxIm+mFy/HkaOLDtrr1QBudOou1H/BFKOvBm6TkTSpTwrqYhpnk21oLwFqA3sg1978mqgCF/AVSjn3Grn3O3Oud+cc0XOuSHAr0Bv4BRgknPudefcuuDxe5pZ1+Du5wF3OudWOOemAM8C5wf7yruvVGFNm8KZZ/qicvFiX2RedhnMmAGXXw477AC77w5//jOMHg1FRWFHHA0//ujHo1avDl984Sc+kiroh0vosuqxsKOQqBt7o64TkXQpz0oqYppnUyoonXNfAX2AJ4EPgCeAPYPbM8rMWgO7AJOAHJJaRZ1zq4FfgBwzawq0pWSr6bjgPmzpvpmMX6KnZk2/ZMlDD/munFOmwL33+tli//pX3wLXvj0MHAjvvw9r1oQdcTi++QYOPdSPV/3iC78OqIiIiIhIslSXDTkFeN85d3mG4yn9uDWBV4AXnXNTzawBsKTUYauAhkCDpJ9L7yPYv7n7ln7cgcBAgNatWzNy5MhteBaZkZ+fH8m4wpbuedlrL7+tWlWT779vxjffNOeVV5rx7LM1qF27kN69V7DvvsvYd99lNG9e4UOHMyqdc/LTT03405960KLFeu67bxxz5qyvUt2C9f9TUq+VKykscoz8blLYoURK/up1OidJeuWu9teJ/nfKUE4pS+ekJOXZTVOeLSmueTbVWV7fAJaZ2WB8cfdDBmMCwMyqAS/hJ/75fXBzPtCo1KGNgLxgX/HP60rtK+++JTjnngGeAejTp4/r27dvuk8jY0aOHEkU4wpbRZyXE0/0XwsK4PPP4f33q/Peey148MEWAPTpAyec4GeN7dnTr6EZZVt7Tj78EP70J+jYEYYPr0ebNvtmLriQ6P+nlOFNWLliOX33UYeNZCO/m6RzkuzL+qzMzdf/ziYop5Slc1KK8uwmKc+WEtM8m+oYys+BpsClwLfBTKk3m9kOmQjKzAx4DmgN9HfObQh2TQJ6Jh1XH+iIHxu5AliQvD/4flJ5983Ec5D4q1ULjjgCHnvML5kxfrzvElujBtx2mx9z2aGDH4v50Uewbl35vzPq3nrLF9S77uon4GnTJuyIRERERCTKUh1DeQiwHXAF8CXQCbgTPwYxE54EugHHO+fWJt3+NtDdzPqbWR3gz8B459zUYP+/gVvMrGkw2c7FwAsp3ldks8ygRw+4+Wb49ltYsACeew5694YXX/SzxbZo4WeP/de//MQ/cfPqq3Daab4F9tNP/fORLNH9FmY1ODPsKCTquvxB14lIupRnJRUxzbOpdnnFObfYzJ7Hj0OsDuxP6i2cKQvWhrwEWA8stER/wkucc6+YWX/g78DLwPfAGUl3vw1fjM4C1gL3Ouc+CuJfUs59RVLWurVfz/LCC33L5IgRfgKf99/3y5KYwT77+G6xxx8POTnR7hr7z3/6SYgOPtg/hwYNyr+PVCFtDmdF7cKwo5Coa3UQK2Y2DTsKkXhSnpVUxDTPpjopz8nAafi1KOvhlw5ZgJ8wp0I552YFv39z+4cDm5xv0jm3Hrgw2LbqviLpqlMH+vXz2xNPwNix8N57vjC7+Wa/7bRTorg86CDfnTYqHnsMrrwSjj7ad3mtWzfsiKTSrRhLgw2/AD3CjkSibOXE4DoRka2mPCupiGmeTbWF8U3g9OD4/wLHANs7567PVGAicWTmx1bedptfz3LuXHj6aT8m8Zln/JjMli3h9NPh5Zdh2bJw4/3b33wxefLJ8M47Kiaz1o9/pFPuU2FHIVE34XZdJyLpUp6VVMQ0z6ba5fUL/PjE151z/5sV1cyaBpPhiMgmtGvnu5IOHOjXsxw+PNE1dvBgqFYN9t8/MWtsly6VE5dzvui9804480w/DrRmzcp5bBERERGpOlKdlKevc+5551yemdU0s1PM7G1gfobjE6ky6tXzheOzz8L8+fD99747bG4uXHcddO0Ku+wC11zjlyvZuDEzcTgH117ri8mLLoKXXlIxKSIiIiLpSXlSHTM70MyeBhYBrwMnAhEaCSYSH9WqwV57+aJu7Fj47Tf4+99h55391759oVUrOPts+O9/YeXKinncoiK/zMlDD8EVV/huuNWrV8zvFhEREZHss8Uur2bWBTgXOAvoUHxz8HU6MDBzoYlkjw4d4PLL/ZaXBx9/7LvFDh3ql/OoUcNP5lM8sU/Hjlv/GBs3wu9+57u33nAD3HNPtGeeFREREZHoK6+FcgpwE7AjsBK/3MYpwb7JzrkvMhaZSJZq2BD694cXXoCFC+Hrr3032IUL4aqroFMnvwzJjTf6fYUpzEK+YYNv7XzxRbjjDhWTUkrPu5nZ8IKwo5Co2/UGXSci6VKelVTENM+m2uX1J+AU59x5zrl3MhiPiCSpXh3228/PxjppEvzyCzzyCLRpAw8+CAcc4L8//3x4803fullaQUE1+vf3kwA98ADcequKSSml5X7k1to17Cgk6prvqetEJF3Ks5KKmObZ8grK2fgurrsDI8xsvpk9k/mwRGRTdt7ZL/Px6aewZIkfX3nUUX7dywEDoEUL//M//gGzZ/uZZf/0p+68/76/7Zprwn4GEklLvqFRweSwo5CoWzZK14lIupRnJRUxzbNbLCidczsCBwPP4bu8tgEuAhxwiJndk+H4RGQzmjRJrGe5eDGMHOkn2vntN/j97/24zO23h59+asq//uUn4xHZpHE3s3Pev8KOQqJu8r26TkTSpTwrqYhpni23y6tz7kvn3ECgLdAfeBcoABoD12c2PBFJRY0acPDBvkvrtGkwdSrcfz8ceCDcdtskzj8/7AhFREREpCra4iyvyZxzBcDbwNtm1hg4HTg7U4GJSPq6dPHbtdfCyJFLww5HRERERKqolNehTOacW+Wce8Y5d3BFByQiIiIiIiLxkFZBKSIiIiIiIqKCUkQk2/V+hBmNBoUdhURdj9t1nYikS3lWUhHTPJvyGEoREamimvYiv+aisKOIlqIiauTmwpq1UKc2VNPnrzTpTn5NF3YUIvGkPCupiGmeVUEpIpLtFg6n6fqfgB5hRxKeJctg9E8waozffhzLAatyE/vr1gm2ulCvLtSp47/Wretv39Rtxcdu6n6b+x01a4Z3Dsqz+Auarv8VOCrsSETiR3lWUhHTPKuCUkQk2028iw75y4Hzwo6kcqxfD+MmJorH0WPg11l+X/XqkNMVBpzAjFr16dS2Oaxd61sq163zX9euhbVJ369Ymbit+Ni168Cl8SlzjRrlF6ObK1j/d1udUoVucNv/vq+bXqvrtMfokJ8P3LT1z0sk22VbnpX0xDTPqqAUEZGqyzmY+Rv88JMvHEeNgfGTYMMGv79dW9hzd7joXP91992gfj0A5n43iU775KT/uOvXlyxEt1SUli5GSxSxwc8rV8H8hWWPL34uW6tOnZLFZ3mtqDmzqV1YBHPnQvv26T2miIhskW3cGHYIW00FpYiIVB3LV8DosYni8ccxsGyF31e/HvTuCVcM9MXjnrtD2zaZicPMF2N16mTm9yfbuDFRnKZVsG7i+JWryt7v6rXUdUCHDnD88TBoEBx5pMaXiohsq9lz4fV3oeY4Gq1ZC6tXQ/36YUeVMhWUIiISTwUFMHGKb30cFbRAzvjV7zODbl3guKN94dhnd9i1i+/SWtXUqAENG/gtk77sT+7SFTS6/mR47jl4913YcUcYOBAuvBBat87s44uIVCWLl8LbQ+D1d+DbUf62exuwtm0b6qUzZCJEKihFRCT6nINZc4Jxj0HxOHai71YK0LqVLxzPOR322gP26Jn5AivrGEW1asE998Dtt8M778BTT8HNN8Ntt8HJJ/tWy759fUEvIiIl5ebBex/61sjPvoTCQv/h5+03wIATYe41FOTmU69BvF6/VFCKiGS7vZ5m2ndfsnfYcSRblQs/jvWF4w8/+W6sS5b6fXXr+LGOl5wfdF3dA9pvpyIm03r9jWnjpvvrpHZtOP10v02dCk8/DS++CIMHwy67+MLyvPOgWbOwoxaJhijmWakc69bBR5/6lsgPP/UfhHbYHq66FE49Cbp3SxzbIinPxogKShGRbNeoC2tr/Bbe42/cCBOnJpbtGD0Gps1IzJLapRMceUhQPPaGnC7RXl6jqmrYibU11pa9vWtXePhhuPtueP1132p59dVw001w2mm+uNx3XxX8kt3CzrNSuTZuhM++8kXkex9CXj60bAEXng2nngh79d50Ttxcno04FZQiItlu7vs0X1dJ66M5B/PmJ5bsGPUTjBnvJ38BaNHMtziedhL02cNPotOkcebjkvIt+Jjm62ax2fXR6taF//s/v40b51stX34ZXnoJevTwheXZZ0Nj/T0lC1VmnpVwFBXB9z/6IvLN92HpMmjcCE461rdEHryfH/O+JeXl2YhSQSkiku2mPsj2q5cDF1f8787Lh5/GJVoeR42BhYv8vlq1oFd3uOBsX0TuuTvsuINasqJqxjNsvzofuK38Y3v2hCeegPvug//8B558Ei6/HK67Ds46yxeXvXtnPGSRyMhknpXwOAcTJvsxka+/A3Pm+dm9+x3ui8gjD9m62b63Js9GiApKERGpGIWFMGV6YtzjqDEwdbr/1Bag445w8P5+0pw9d4ceu/qiUqquBg3g4ovhd7+D0aN9d9hXXoF//hP69PGF5RlnxGp6fBERZv7mC8jB78DUn/0M4ocdDH++Ho4/OusmhVNBKSIi6VmwMNF1dfRP8NN4yF/t9zVt4pfqOKmf/9qnFzTXBC1Zywz23NNvDz7ou8I+9ZQvNK++Gs49Fy65xHeNFRGJogULfVfWwe/4SeMA9t8bHrkbTjoOWjYPM7pQqaAUEZHyrVnrxzoWF48//ATzFvh9NWv61sazT/XF4157QMed1HVVNq1JE/j9730X2K+/9mMtn30W/vEP2H9/32o5YMDWdRMTEcmE5Svg3Q98Efnlt76La8/ucNctMOAE2L5d2BFGggpKEREpqajIz7JaXDyOGgOTpvoureCnO993r2DW1d39i6ve/MvWMoMDDvDbww/7ZUeeesq3Vl55JZx/vm+13GWXsCMVkWyyeg0M/dh3af1kJGzYAJ12ghv/6MdFdukUbnwRpIJSRCSbOQcdH2Dhf1+lyV/u9cXjj2P94ssAjRpC715wzeW+eOyzB7RqEWbEEpbejzJlzDT2zcTvbtECrrkGrroKPvvMF5aPPQYPPQSHHupbLU88UWNuJb72fYkp33yemf8f2XYFBTB8JAx+F4YO871ytmsDgy6A00+GXj0qp9dNJvNsBqmgFBHJFuvXw5QpfkmH8eP913HjYOlSuoKfVCCnq18ja889/LZLR6hWLezIJQrqtWN99eWZfYxq1eCww/y2cCE8/zw884xfz7JVK7joIj/Jz047ZTYOkYpWf3vWV28ZdhSSrLAQvvrOz9D6zlBYsRKaNYEzToHTTvbjIyv79a8y8mwGqKAUEamKFi4sWzhOneoXWwbfRbV7dzjhBNizkF9dITudejvUqxtq2BJhc9+l5do5VNr6aG3awM03ww03wLBhvtXy3nvhb3+Do4/2rZb9+pW/rptIFMx6jZZrx6F1KEPmnF/KavA7foKdBQuhfj047mg47UQ49KBwe0JUdp6tIMrCIiJxVlDgWx2TC8fx42Hx4sQx7dvDbrvB8cf79QF32w06d068ER/el6YrlquYlC379SXarckH7q7cx61e3ReO/frBnDl+yZFnn/VdYNu39y2WF10E7TQ5hkTYz0/Sbs1y4PdhR5Kdpv7sx0S+/g788pufTO6oQ+HUP8MxR/iiMgrCyrPbSAWliEhcLFpUtnCcMsVPGABQuzbk5MCxxyYKx912g+bZO5W5VDHbbw9/+QvccgsMGeJbLW+7De64w39gMmgQHHGEumlLtOTlQW4e1deuhUVL/Dh0zYKdeXPm+e6sg9+GCZP9OT94f7jm93DCMX55K6kQKihFRKJmwwbfPTW5cBw3zheUxbbbzheN/fr5orFnTz8bprr/STaoWRNOPtlvv/ziWyyffx7eecePr7zkErjgAj/uUqSyrF7tP+SbNAkmTvRfJ02C2bPhT9AQ4LxefsjB9tvB9u1hh/awQ7uk79v7yWCUy9OzZBm8/b4vJL/5wd+25+5w31/glOOhbetw46uidLWKiIRpyZKyhePkyYlWx1q1fKvjMcckCsfddvOzYooIdOzox1X+5S/w9tu+1fLGG+HWW+GUU3yr5cEHq0VIKs6aNf5Dv+KCsXj79dfEMbVrQ9euflmcnBzY+VXyV+fT4MGLYfZcmDMXZs+DDz6BxUtK/v5q1XxRuUP7oNBsl/R98HNdDVH4n9w8eP8jPy7ysy/9ZDvddoHbrocBJ8LOO4YdYZWnglJEpDJs2ADTppWdKGfhwsQxbdv6gvGoo/zX4lbHmjXDi1skLmrXhjPO8NuUKX522BdegNdegy5dfGH5f/8HzZqFHanExbp1my4cZ870k7uAz89dusBee/lW8ZwcP+HZzjuXbGUc/jEbq1eDMy/Y9OPMmecLzDlzfcE5e66/7dsf4I0FiXWAi7VovunWze2D4rNJ46r9Icq6dTBshO/O+tEI//MO7eGPl/qZyrt3q9rPP2JUUIqIVLSlS0sWjcWtjgUFfn+tWrDrrnDkkYnCcbfdoGVIU8of8AaTvhrB/uE8usTFXs8w6cfJ8bhOunWDhx+Gu++GwYN9q+VVV8FNN/klSAYNgn320RtO8dav9x/4lS4cf/kFior8MTVq+A/49tgDzj3XF445OdCpU2of+m0pz9apA507+m1TNm6EBYuSCs2gdXP2XJg8LVFQJWvYYBOtm0nft24Zv7HGGzfCyK99Efn+R75lsmULOP9MX0Tu3Sf+/9NxyrNJVFCKiKRr40aYPr1sl9X58xPHtGnji8UjjkgUjl27RqvVsU4LNlRrHHYUEnW1m8XvOqlbF847z2/jxsHTT8NLL8G//+3/FwcNgrPPhkaNwo5UKkNBAfz8c6JgLB7nOGNGogWwenU/C/Zuu8GZZyYKx86dt205iW3JszVq+JbH7dv5tRFLc86PHSzduln8/XejYeWqkvepVavUOM6k1s0d2kO7ttF4nXIOvh/tu7O+NQSWLIVGDf2kOqeeBH33r1rjTeOYZ1FBKSKSmuXLyxaOkyb5T7bBv/B26+YXZC8uHHv2jMekIDNfoM2aCWh9NNmiWa/RZs1c4rY+2v/07AlPPOHXsvzPf3yr5WWXwXXXwVln+eJyjz3CjlIqwoYNvkgs3eI4fXpiLd5q1fz425wcGDAgUTh26eK7T1e0TOZZMz9zbKsW0LvXpo/JzSvbullcgA4bAYsWlzy+WjU/gc0O7aF9u013r83UUhvO+VlZX38X3njXx1inDhxzGJx2Mhx5iP+5KoppnlVBKSKSbONG/wl26bGO8+YljmnVyr85veKKROHYtWu4iyFvi5kv0GbtcuCasCORKJv9Om3W5ocdxbZr2BAGDvTrV44a5VstX37ZzxS7556+sDz9dKhfP+xIpTwbN/puqaULx2nTEhObmfnxjDk5fu3S4sKxa9fKLUrCzrONGvpxhd27bXr/unUwd37J1s05wZjOUT/B20MSxXix5k0TBWZy62Zx99pmTbeuC+rM34K1It+FKdN9a/GhB8Gt18FxR/nnUNXFNM+qoBSR7LViRdnCcdKkxFiUGjV8q+MhhyQKx549obWmHReJPTM/kcpee8GDD/qusE89BRddBFdf7SfwueQSX3xIuAoL/UQ4myoci3uJgF8ypngt3uTCsV5EFq2Psjp1oNPOftuUwkJYuCjRupnc2jl9BgwfCWvWlrxP/XolC8zkWWp3aA9tWlNr2TL4+7O+iBw9xt9vv73g4b/CycdDS62jHAcqKEUkexQWwlNP0ePll32L45w5iX0tW/pi8bLLEoVj166Z6fokItHSpInvcfD738PXX/vC8umn4fHH/bIPgwZB//5Vt5tdVBQVwW+/lSwaJ070M60mTzqzww6+WDzyyETh2K0bNGgQWuhVXvXq0G47v+27Z9n9zsGyFSXHcSa3do7+CZavLHmfmjXZd+NGf9/dcuCuW2DACb61U2JFBaWIZIc5c/zMfJ9/Tp0OHeDAA0vOsNqmTfxnhxORbWPmC8gDDoBHHvHLjjz9NJxzDlx5pV8WYuBAP0GLpK+oCGbPLtviOGWKX+OxWPv2vlg89NBE4bjrrr7bskSLGbRo5rfdd9v0MXn5Sd1pfevmb8vy2OnKi6BLp8qNVyqUCkoRqfreeMO/CSwogOefZ9SOO9L3kEPCjkpEoqxFC7j2Wt/99bPPfKvlI4/AAw/4ybcGDfJj8qIwE2ZUOec/zCtdOE6eDKtXJ45r29YXixdf7NdwLC4cG8dvtkvZgoYNYNcufgvM+m4SO6mYjD0VlCJSdeXn+1aF55/3k2288opvWRg5MuzIoqXvB4z//BMOCjsOibZ9X2L8qInZd51Uq+YLyMMOgwULfD555hk49VTfs+G882i3erUfi+1cyQ1Su21rjo3i/UvfVljIHuPGwdy5kJeXOJetW/ti8cILEy2OOTnQtGnF/b2iSnlWUhHTPKuCUkSqptGj/VIAM2b4xcz/8he1JGxOjXoUmcaGSTlq1NV10rYt/OlPcOON8NFHvjvs/ffTuaioch7fLLGV/nlbb6vg31nYsKGf2Ci5cGyexROsKM9KKmKaZ1VQikjVUlgI998Pt97qWw9GjIC+fcOOKtqmP8F2ayajdShli2a+wHZr5hO39dEyonp1P5PoscdCfj5fffopBxx4oN+XqUItZsaNHElf5d4E5VlJRUzzrApKEak65s71E++MHOkXqn76aWjWLOyoom/2YFqtXQ7cHHYkEmXzhtAqhuujZVyDBmxs3Fi5RrZMeVZSEdM8Wy3sAEREKsSbb/rZWkeNgueeg8GD9QZPREREJMNUUIpIvK1e7WcGHDAAOnaEMWP8hA8x7CImIiIiEjcqKEUkvn78EfbYw7dI3nijX5Bc68OJiIiIVBoVlCISP0VFcN99sO++voXy00/hnnugVq2wIxMRERHJKiooRSRe5s2DI4+EG26AE07wa78dckjYUcXb4SMZ2/z+sKOQqDvwDV0nIulSnpVUxDTPqqAUkfh45x0/8c6338I//wmvv66Jd0RERERCpIJSRKJv9Wq45BI4+WTYaSc/8c5FF2ninYoy5QG2X/1G2FFI1P38lK4TkXQpz0oqYppntQ6liETbmDFw5pkwfTpcfz3ceafGSla0eUNovm552FFI1C0cTvN18VsfTSQSlGclFTHNs2qhFJFoKiqCBx6AvfeGvDwYPhzuvVfFpIiIiEiEqIVSRKJn/nw47zxfRJ58Mjz7LDRvHnZUIiIiIlKKWihFJFrefddPvPPNN/DMM/DmmyomRURERCJKBaWIRMOaNTBoEJx0EnToAD/9BBdfrIl3KkP1uhRa7bCjkKirXkfXiUi6lGclFTHNsyooRSR8Y8ZA797w9NNw3XV+WZAuXcKOKnsc8iETmt0VdhQSdfu9rOtEJF3Ks5KKmOZZFZQiEp6iInjwQT/xTm6uHzN5332aeEdEREQkJlRQikg4FiyAo4+Ga6+FY4+F8ePhsMPCjio7TbiTDvmvhB2FRN3Uh3WdiKRLeVZSEdM8q1leRaTyvfceXHihHzf59NMaKxm2RZ/SdL3WR5NyLPmapuvjtz6aSCQoz0oqYppn1UIpIpVnzRq47DI48UTYYQc/8c7AgSomRURERGJKBaWIVI5x46BPH3jySd/N9dtvoWvXsKMSERERkW2gLq8SX2vWwLRpMHmy32bPpk2bNtCrFzRpEnZ0UqyoCB59FG680a8n+fHHcMQRYUclIiIiIhVABaVEX14eTJmSKByLt99+A+f8MTVqQLNmdF28GB5/3E/ycvbZ0K8f1KkTavhZbcECOP98X0SecAI89xy0aBF2VFJa7eZsqLYx7Cgk6mo1ZUM1dWwSSYvyrKQipnlWBaVEx/LlZQvHKVNgzpzEMbVq+fUJ99rLFyq77uq3Tp2gZk1+fPppek+dCv/9L7z1FjRuDAMG+OLy4IMhhv+ksTVkCFxwAaxe7bu5XnKJxkpG1YFvMmnEMPqGHYdE297PMum7CbpORNKhPCupiGmeVUEplcs5WLKkbGvjlCmwcGHiuHr1/Pi6gw9OFI277go77eRbIzcjr2tXGDQIHngARoyAV16B117zLWPt2sGZZ8JZZ/lusSpuMmPtWj9G8oknoGdP+M9/oFu3sKMSERERkQxQQSmZ4RzMn1+2aJw8GZYtSxzXqJEvNo45pmThuMMO29aaWKMGHHmk3558Et5/3xeXjzzii81u3Xyr5Vln+SJVKsb48b5onzwZrr4a7r4batcOOyopz9ib2ClvJvBw2JFIlE26h53yFgNHhR2JSPwoz0oqYppnVVDKtikqgtmzN1045uYmjmvWzBeK/fuXLBy32y7zLYX16sHpp/tt2TJ4/XVfXN5yi9/2288Xl6edpvF96Soqgscegxtu8H/rYcN8MS/xsPRbGhdofTQpx/IfaVwQv/XRRCJBeVZSEdM8q4JSUlNYCDNnli0ap0zxs60Wa9PGt/6de27JwrFly2h0MW3e3HeJHTQIZs2CV1/1xeXll8OVV8JRR/ni8oQToH79sKONh4UL/XjWYcPg+ON99+KWLcOOSkREREQqgQpKKamgAGbMKFk0Tp7sl+dYvz5x3Pbb+8Jx4MBE0ditm2+diosOHeCmm/xyFhMm+MLy1Vdh6FBfTJ58si8uDz98i+M2s9rQoX7inbw8P2Zy0KBofHAgIiIiIpVC75Kz1bp1iTUckwvHn3+GjcG01mZ+fGG3br7lrrhw7NrVj32sKsxgt938ds898OWXvrh8/XV4+WXf2nb66b643HtvFUzgJ9657jr4xz/8xDuvvuqvDRERERHJKiooq7r8fJg6texyHDNn+nFvANWr+2U3unXzrXLFhWOXLn78YTapVs3PLHvwwX49yw8/9MXls8/C3/8OHTv6iXzOPtufn2w0YYKfeGfSJLjqKl+Ea+KdeKvXnvW5WlJHylG3LetXrwg7CpF4Up6VVMQ0z6qgrCpWrSpbNE6e7McJFqtZ0xdBu+/uC6LiwrFzZxUEm1K7Npx0kt9WrfLrWr7yCtx1F9x5J/Tu7c/jGWdA27ZhR5t5zvki+/rroUkT+Ogj33It8bffy0wZMYzWYcch0dbncaZ8N0HXiUg6lGclFTHNsyoo42jmTNq+9x68/XaicJw/P7G/Th3f2rj//nDxxYnCceedfVEpW69xYz9W8IIL/Ln+7399cXn11X7NxUMP9cXlKadUre7AxRYt8s/9ww/huOPg+ec18Y6IiIiIqKCMpS++oMvDD0ODBr5QPOKIkjOqdujgu7FKZmy3nS8kr77adycunsznggvg0kv9TKdnnw1HH101Wn4/+MA/t9xc3+33sss0jrSq+fGPdMqdBfwj7Egkysb/mU65y4jb+mgikaA8K6mIaZ5VQRlHJ53Et/Xqse+pp+qNfdi6dvXdX++4A77/3heXr73mJ/Rp2hQGDPDF5YEH+vGZcbJune/e+vjj0KMHjBgBOTlhRyWZsGIsDTZofTQpx6rJNNgQv/XRRCJBeVZSEdM8G7N3uAJAkyasb9VKxWSUmME++/jia94836rXr58vMPv2hR13hBtugPHjw440NRMnwp57+udz5ZXwww8qJkVERESkDBWUIhWtZk045hi/5Mjixb6o7NEDHnzQL7HRowf87W8we3bYkZZVPPFOnz6wZIkfM/nII35croiIiIhIKSooRTKpfn2/zMjQobBggR+D2LAh3HSTH+t60EHw9NOwPALdYBYv9hPu/OEPcNhhvjX16KPDjkpEREREIkwFpUhladkSLr8cvvkGfvnFj71csgQGDYI2beDEE/34yzVrKj+2Dz/0LaeffupbKIcMgVatKj8OCUfDXVhTo33YUUjUNdhZ14lIupRnJRUxzbMqKEXCsPPOcMstfsmXH3+EK66AUaP8mpatW8N558HHH8PGjZmNY906P0ayXz9fQI4eDb//vcbnZpu9n2F64yvDjkKibvf7dJ2IpEt5VlIR0zyrglIkTGawxx5+fOWcOb6F8NRT4Z134KijoH17+OMffbHpXMU+9sSJsNde8NhjvpvrqFHQvXvFPoaIiIiIVGkqKEWionp1OPRQeP55WLQI3ngD9tsPnnzSF35du8Jf/gIzZmzb4zjnx3Luuad/nA8+gEcf1cQ72ez7geyy6tGwo5CoG3O9rhORdCnPSipimmdVUIpEUZ060L8/vPUWLFwIzz4L223nC8rOnWHvvX3L4qJFW/d7lyyBE07wXWwPOcRPvHPMMZl5DhIfedOpt3Fu2FFI1OXP1HUiki7lWUlFTPOsCkqRqGvaFH73O/jsM7/UyH33wfr1fuzjdtv5rrH//jfk5W359wwb5ife+eQTX4wOHerHa4qIiIiIpEkFpUictG8P110HY8f6MZA33ADTpvlJfFq39pP6vP8+FBT87y5WUABXXeWXAGnRwo+VvOIKTbwjIiIiIttMBaVIXOXkwN13w8yZ8OWXcP75MHy479K63XZw6aXw1lv0vuwyeOQRP3vrqFG+lVJEREREpAKooBSJu2rV4IAD4IknYP5830J5xBHw4ovQvz+1li3z60o+/jjUrRt2tBJFTXuRX7Nj2FFI1DXeVdeJSLqUZyUVMc2zNcIOQEQqUK1acNxxfsvLgy++YFRBAfsfe2zYkUmU9X6EGauGEb+llKVS7XYHM9ZM0HUikg7lWUlFTPOsWihFqqqGDeHYY9nQtGnYkYiIiIhIFaUWShGRbPfNOXRbOR94OexIJMpGX0G3lSuAo8KORCR+lGclFTHNsyooRUSy3Zq51C5cHnYUEnVrF1C7MD/sKETiSXlWUhHTPKsuryIiIiIiIpIWFZQiIiIiIiKSlkgWlGb2ezMbbWbrzeyFUvsOM7OpZrbGzD4zsw5J+2qb2fNmlmtmC83s6lTvKyIiIiIiIlsnkgUlMB+4C3g++UYzawG8BdwKNANGA68lHXI70BnoABwCXG9mR6d4XxGR7NRiX1bV6hZ2FBJ1zXrrOhFJl/KspCKmeTaSk/I4594CMLM+UGIpllOASc6514P9twNLzayrc24qcB5wvnNuBbDCzJ4Fzgc+SuG+IiLZqdc9/Lp8GOqyIVuUcxO/5k3QdSKSDuVZSUVM82xUWyg3JwcYV/yDc2418AuQY2ZNgbbJ+4Pvc8q7b4ZjFhERERERqZIi2UK5BQ2AJaVuWwU0DPYV/1x6X3n3LcHMBgIDAVq3bs3IkSO3KehMyM/Pj2RcYdN5KUvnpCydk5Jylv+ZLhs3MvK7v4QdSqTkr17HyO8mhR1GZOSsuIMuhYWMHFk77FAiRzmlLJ2TkpRnN015tqS45tm4FZT5QKNStzUC8oJ9xT+vK7WvvPuW4Jx7BngGoE+fPq5v377bGneFGzlyJFGMK2w6L2XpnJSlc1LK8GqsXJFP333UYSPZyO8m6Zwk+7KQlbn5+t/ZBOWUsnROSlGe3STl2VJimmfj1uV1EtCz+Aczqw90xI+NXAEsSN4ffD+pvPtmOGYREREREZEqKZIFpZnVMLM6QHWgupnVMbMawNtAdzPrH+z/MzA+aVKdfwO3mFlTM+sKXAy8EOwr774iIiIiIiKyFSJZUAK3AGuBG4Fzgu9vcc4tAfoDfwVWAHsDZyTd7zb8RDuzgM+B+51zHwGkcF8RERERERHZCpEcQ+mcux2/puSm9g0Hum5m33rgwmDbqvuKiGSt1oexYs3PNAk7Dom2lvuzYv0iXSci6VCelVTENM9GtYVSREQqS49bmdXg7LCjkKjrepWuE5F0Kc9KKmKaZ1VQioiIiIiISFoi2eVVREQq0WfH0GP5UuDdsCORKPvmHHqszAOOCjsSkfhRnpVUxDTPqoVSRCTbFa6lulsfdhQSdYXrdJ2IpEt5VlIR0zyrglJERERERETSooJSRERERERE0qKCUkRERERERNKiSXlERLJdu+NYtnZa7Na9kkrW5nCWFSzQdSKSDuVZSUVM86xaKEVEsl23a5lTf0DYUUjUdR6k60QkXcqzkoqY5lkVlCIiIiIiIpIWdXkVEcl2w/vSa8Vy4KOwI5Eo+3IAvXLzidv6aCKRoDwrqYhpnlULpYiIiIiIiKRFBaWIiIiIiIikRQWliIiIiIiIpEUFpYiIiIiIiKRFk/KIiGS7HU5j8brJsVv3SipZu+NYvGG+rhORdCjPSipimmfVQikiku12uYz59Y4POwqJup3P13Uiki7lWUlFTPOsCkoRkWy3cQ3V3Lqwo5Co27hW14lIupRnJRUxzbPq8ioiku1G9mM3rY8m5fn2XHbLzQdODDsSkfhRnpVUxDTPqoVSRERERERE0qKCUkRERERERNKiglJERERERETSooJSRERERERE0qKCUkQk2+18PgvrHhF2FBJ1O5yq60QkXcqzkoqY5lkVlCIi2W7n81lY78iwo5Co63C6rhORdCnPSipimmdVUIqIZLt1S6lZtCrsKCTq1i/XdSKSLuVZSUVM86zWoRQRyXZfDSBH66NJeX4YSE5uPnBa2JGIxI/yrKQipnlWLZQiIiIiIiKSFhWUIiIiIiIikhYVlCIiIiIiIpIWFZQiIiIiIiKSFhWUIiLZrvOlzKt3XNhRSNTtdK6uE5F0Kc9KKmKaZzXLq4hItutwOkt+aRJ2FBJ17U9kydwJYUchEk/Ks5KKmOZZtVCKiGS71XOoXbgk7Cgk6tbM03Uiki7lWUlFTPOsWihFRLLdt+fSbeVy4NCwI5Eo+/FKuuXmA+eEHYlI/CjPSipimmfVQikiIiIiIiJpUUEpIiIiIiIiaVFBKSIiIiIiImlRQSkiIiIiIiJpUUEpIpLtul7DnPr9w45Coq7TQF0nIulSnpVUxDTPapZXEZFs1/54lk2vFXYUEnVtj2TZrPitjyYSCcqzkoqY5lm1UIqIZLvcadTdOCfsKCTq8mboOhFJl/KspCKmeVYtlCIi2e6HS+iyajnQL+xIJMrG3kiX3Hzgd2FHIhI/yrOSipjmWbVQioiIiIiISFpUUIqIiIiIiEhaVFCKiIiIiIhIWlRQioiIiIiISFpUUIqIZLvutzCrwZlhRyFR1+UPuk5E0qU8K6mIaZ7VLK8iItmuzeGsqF0YdhQSda0OYsXMpmFHIRJPyrOSipjmWbVQiohkuxVjabDhl7CjkKhbOVHXiUi6lGclFTHNsyooRUSy3Y9/pFPuU2FHIVE34XZdJyLpUp6VVMQ0z6qgFBERERERkbSooBQREREREZG0qKAUERERERGRtKigFBERERERkbSooBQRyXY972ZmwwvCjkKibtcbdJ2IpEt5VlIR0zyrdShFRLJdy/3IrZUXdhQSdc33JLdWnbCjEIkn5VlJRUzzrFooRUSy3ZJvaFQwOewoJOqWjdJ1IpIu5VlJRUzzrApKEZFsN+5mds77V9hRSNRNvlfXiUi6lGclFTHNsyooRUREREREJC0qKEVERERERCQtKihFREREREQkLSooRUREREREJC0qKEVEsl3vR5jRaFDYUUjU9bhd14lIupRnJRUxzbNah1JEJNs17UV+zUVhRyFR16Q7+TVd2FGIxJPyrKQipnlWLZQiItlu4XCarv8p7Cgk6hZ/oetEJF3Ks5KKmOZZFZQiItlu4l10yP9P2FFI1E17TNeJSLqUZyUVMc2zKihFREREREQkLSooRUREREREJC0qKEVERERERCQtKihFREREREQkLSooRUSy3V5PM63xH8KOQqKu1990nYikS3lWUhHTPKt1KEVEsl2jLqyt8VvYUUjUNezE2hprw45CJJ6UZyUVMc2zaqEUEcl2c9+n+brvwo5Com7Bx7pORNKlPCupiGmeVUEpIpLtpj7I9qvfDDsKiboZz+g6EUmX8qykIqZ5VgWliIiIiIiIpEUFpYiIiIiIiKRFBaWIiIiIiIikRQWliIiIiIiIpEUFpYhIttv3JaY0uT7sKCTqej+q60QkXcqzkoqY5lmtQykiku3qb8/66i3DjkKirl471ldfHnYUIvGkPCupiGmeVQuliEi2m/UaLdd+HnYUEnVz39V1IpIu5VlJRUzzrApKEZFs9/OTtFszJOwoJOp+fUnXiUi6lGclFTHNsyooRUREREREJC0qKEVERERERCQtKihFREREREQkLSooRUREREREJC0qKEVEst0BbzCp6S1hRyFRt9czuk5E0qU8K6mIaZ5VQSkiku3qtGBDtcZhRyFRV7uZrhORdCnPSipimmdVUIqIZLuZL9BmzcdhRyFRN+s1XSci6VKelVTENM+qoBQRyXYzX6DN2k/CjkKibvbruk5E0qU8K6mIaZ5VQSkiIiIiIiJpUUEpIiIiIiIiaVFBKSIiIiIiImlRQSkiIiIiIiJpUUEpIpLt+n7A+GZ3hh2FRN2+L+k6EUmX8qykIqZ5VgWliEi2q1GPIqsTdhQSdTXq6joRSZfyrKQipnlWBaWISLab/gTbrXk/7Cgk6ma+oOtEJF3Ks5KKmOZZFZQiItlu9mBarf0i7Cgk6uYN0XUiki7lWUlFTPNs1hWUZtbMzN42s9VmNsvMzgo7JhERERERkTiqEXYAIfgHUAC0BnoBQ81snHNuUqhRiYiIiIiIxExWtVCaWX2gP3Crcy7fOfcV8B5wbriRiYiIiIiIxE9WFZTALsBG59z0pNvGATkhxSMiIiIiIhJb2dbltQGQW+q2VUDD5BvMbCAwMPgx38ymVUJsW6sFsDTsICJI56UsnZOydE5KqVGNNjWrt1sRdhxRsqGIZjWrsTzsOKJkQyFNN55mC8OOI4KUU8rSOSlFebYs5dmyIpxnO2xuR7YVlPlAo1K3NQLykm9wzj0DPFNZQaXDzEY75/qEHUfU6LyUpXNSls5JWWY2ekOhzkkyMxu9YaPOSTL972yazktZOidlKc+WpTxbVhz/d7Kty+t0oIaZdU66rSegCXlERERERES2UlYVlM651cBbwB1mVt/M9gdOBF4KNzIREREREZH4yaqCMnAZUBdYDPwHuDSmS4ZEuktuiHReytI5KUvnpCydk7J0TsrSOdk0nZeydE7K0jkpS+ekrNidE3POhR2DiIiIiIiIxFA2tlCKiIiIiIhIBVBBKVWSmZ1vZl+FHYeISFVnZi+Y2V1hxyEiIuFQQRlRZjbSzH4XdhxRYWa/mdlaM8tP2rYLO66wBOejwMxalLp9jJk5M9sxpNAiI/gfWmFmtcOOJSy6TrZMeXbLdH485ZKSzOwAM/vGzFaZ2XIz+9rM9gw7rigIPsyeYGZrzGyhmT1pZk1SuJ8zs06VEGKlCV5/FptZ/aTbfmdmI0MMK1RJ72XzzGxl8H80yMxiX4/F/glIVjneOdcgaZsfdkAh+xU4s/gHM+sB1EvnF5lZlVqTNiiUDgQccEKav6OqnJMKu05Esk1F5JKqxMwaAUOAx4FmQDvgL8D6MOOKAjO7BrgXuA5oDOyDXwj+EzOrFWZsIaoOXBl2EBFzvHOuIf7a+BtwA/BcuCFtOxWUEWdmTc1siJktCT4hHWJm7ZP2jzSzO4NPCPPM7OPSrRFVlZk1NrPnzGyBmc0zs7vMrHrJQ+zvwaeoU83ssNCCzYyXgP9L+vk84N/FP5jZsUFLVK6ZzTGz25P27Rh8InqRmc0GRlRa1JXj/4DvgBfw5wX4X9e8p8zsk+D/5XMz65C035nZ5Wb2M/BzpUedGdtynQw1syuSf5mZjTezkzMddGXaVBf55BaD4Lr5R3A+8szsezPrGE60la+881PFbS6XlGi9LX2OzOxIM5sWvP48EeSaqtDauwuAc+4/zrlC59xa59zHzrnxAGZ2oZlNCd6vDNtEfv2Dmc00s6Vmdn9VaJmB/xXafwGucM595Jzb4Jz7DTgN2BE4x8yqm9nNZvZLkEd+NLPtzeyL4NeMM9/76vRwnkVG3A9cu6lWWjPbz8xGBf8jo8xsv+D2081sdKljrzKz9yon5MrhnFvlnHsPOB04z8y6m1ltM3vAzGab2aLg/Urd4vuY2YlmNjZ4vf7FzI4O7xmUVCX+kau4asC/8J9k7ACsBf5e6pizgAuAVkAt4NrKDDBELwAbgU7A7sCRQPIL9t7AL0AL4DbgLTNrVskxZtJ3QCMz6xYU0mcALyftX41/M9QEOBa41MxOKvU7Dga6AUdlPNrK9X/AK8F2lJm1Ttp3NnAn/roYGxyT7CT8tbNrxqOsHNtynbwInFN8oJn1xLdIDM182JFzBv4NY1NgBvDXcMORSrKlXLJJwYe6bwA3Ac2BacB+mQyyEk0HCs3sRTM7xsyaFu8wsxOBm4FTgJbAl/jl2ZKdDPQB9sCvA35hpUSdefsBdfBrnf+Pcy4f+AA4Arga31ukH9AI/9zXOOcOCg7vGfS+eq3Sos680cBISr0vDd6LDQUew/+PPAQMNbPmwPtAFzPrnHSXs4BXKyPgyuac+wGYi+8J8Tf8hza98O9t2wF/BjCzvfAfBl+Hf70+CPitsuPdHBWUEeecW+ace9M5t8Y5l4d/E3NwqcP+5Zyb7pxbCwzGX4hV0Tvm+5yvNLMP8Un5j8651c65xcDD+Dd9xRYDjwSfFL6Gf1E/tvLDzqji1qcjgCnAvOIdzrmRzrkJzrmi4NPj/1D22rk9OH9rKy3iDDOzA/AfwAx2zv2I/1DhrKRDhjrnvnDOrQf+BOxrZtsn7b/HObe8Kp0T0r9O3gN2SXphPxd4zTlXUHmhR8bbzrkfnHMb8cVFr5DjkQxLIZdsTj9gknPureB6eQxYmLlIK49zLhc4AN8F+FlgiZm9FxTag/D5c0rwvO8GeiW3UgL3Bvl1NvAISd3xY64FsDR43qUtCPb/DrjFOTfNeeOcc8sqNcpw/Bm4wsxaJt12LPCzc+4l59xG59x/gKn47qBrgHcJro3g9acr/vWoqpqP70I+ELgq+B/Jw/8PFb+vvQh43jn3SfB6Pc85NzWkeMtQQRlxZlbPzJ42s1lmlgt8ATSxkl07k1+o1gANKjXIynOSc66Jc64JvsWxJrCguMgEnsa30hab50outDoLqGoT+byEf4NzPkndGAHMbG8z+8x8d+lV+Bf70t2h51RKlJXrPOBj59zS4OdXSeqqRtJzDj49Xk7J66IqnpO0rhPn3DrgNXx3rWr4F/iXKjPwCMmWPCsJ5eWSzdmOknnG4VsgqoSgYDzfOdce6I5/vo/gi+9Hk16TlwOGb2Uplpxfq9Jr8lKghW167H3bYP/2+A8lsopzbiJ+3O2NSTdvh//7J5tF4lp5lcSHDWcB7wSFZlXVDqiBn9/gx6T/oY/wrf0Q8etHBWX0XQN0AfZ2zjXCN3GDT9LZbA5+EoAWxUWmc66Rcy4n6Zh2ZpZ8nnbAfwpUZTjnZuEnXelHqa42+IT8HrC9c64x8BRlrxtHFRKMNTgNONj8DHsLgauAnkF3TfBJufj4BvhPBZOviyp1TmCbr5MX8d2ED8N3z/o28xFXutUkTVRkZm1CjCWKsu78pJBLSpwTIPmcLACS5zqw5J+rkqCF5AV8YTkHuCTpNbmJc66uc+6bpLsk9wapSq/J3+Lfk5ySfGPwGnMM8Cn+/GTN2OtSbgMuJlEwzsd/AJFsBxK9Zz4BWppZL3xhWSW7uwKYnyG5HfAOflhbTtL/T2PnXPGHl5G+flRQRl9D/AW2MuhzflvI8USCc24B8DHwoJk1MrNqZtbRzJK7dLYC/mBmNc3sVPxYwQ/CiDfDLgIOdc6tLnV7Q2C5c25d0Pc+la5acXcSUIgf/9gr2Lrhx/IUT0zTz/y097XwYym/c85VxVbJ0tK6ToICsgh4kKrbOjkOyDGzXmZWB7g95HiiJhvPz0lsOZeMBU4JehF1wv9/FRsK9DCzk4IWq8spWXDGlpl1NbNrLJgcMBgucCZ+rPZTwE1mlhPsaxy89ia7zvxkg9vjZ/+sEuMFnXOr8GOsHzezo4P3HTvihyHNxefOfwJ3mlln83YLxgwCLAJ2DiP2yuCcm4H/W/8huOkD/HCKs8yshvmJiHbFt2TinNsAvI6f1KcZvsCsUoL3rscB/wVeds6Nw3cjf9jMWgXHtDOz4jkungMuMLPDgve87cysazjRl6WCMtocvhtJXXx3ie/wzd/i/R9+EqLJwAr8JAhtk/Z/D3TGn7u/AgOq4ngF59wvzrnRm9h1GXCHmeXhxzAMrtzIQnEefkzxbOfcwuINP5HV2fguJa/iP5hZDvQmadKZqmwbr5N/Az0oOZlPVeGcc9OBO4Dh+Nl9v9ryXbJKtp6f8nLJw0ABvhB4kaTJvYIusqcC9wHL8G+UR1M1ltbIw09a9r2Zrca/L5kIXOOcexu/bMZ/gyE6E/Gtc8neBX7EF+RDqQLLJRRzzt2Hn5ToASAX/x5kDnBYMGb/IXx+/TjY/xz+/R34D2leDLo6nlbJoVeWO4D64OcHAY7D98JbBlwPHJfUvRz8a/XhwOubGZsaV+8Hr7dz8PM4PISfWBP8EiIzgO+C/6Hh+F6KxZP3XIDPPauAzynbyhsaKznETKLCzH4C7nDOvRN2LCJVhZm9AMx1zt0SdixxYmb/Bwx0zh0QdiwVSXl2y3R+KkYw/ngucLZz7rOw4wmLmTmgc9BaJSJViFooIyjoLtINGBN2LCKS3cysHr4V85mwY6lIyrNbpvOzbczsKDNrYma18a1Whm/NExGpclRQRoyZ3YvvDnFDMJGGiEgogrEbS/Dd+qrMpAjKs1um81Mh9sXPyLgUOB4/S3lVWopIROR/1OVVRERERERE0qIWShEREREREUmLCkoRERERERFJiwpKERERERERSYsKShEREREREUmLCkoRERERERFJiwpKERERERERSYsKShEREREREUmLCkoRERERERFJiwpKERERERERSYsKShEREREREUmLCkoRERERERFJiwpKERERERERSYsKShEREREREUmLCkoRERERERFJiwpKERGRzTCz283MmdkLW3m/Q4L73ZWh0LKKmdUws9/M7Gczqxl2PCIikqCCUkREIicoHlywHZB0+wFJt/9WwY9Z/Ht3rIBfdzewEXgs+N07mdkbwfNaZ2bzzOwZM2ua9PjVggJ2rpmtN7OxZtYvaX87M/vAzJYXx1oq/vOTnkPprW+6T8TMzjKzL81siZmtMbOJZnZRqWN2NLN3zSzfzFaZ2WAza5O0/0wzG2VmBZsq0M27xsymBednhpldWrzfObcReBzoBJyf7nMREZGKp4JSRESiblDS95du9qiIMLNewD7ACOfc4uDmDsBxwBTgVaARcDHwz6S7Xg/cBmwA/gt0Bd4zs5xgfwugMzB6Mw89GXg0aXs9uL0I+HUbntKRwI7AMOArIAf4p5kdD74QBoYCJwBfA2OAU4G3k37HbvgCe8ZmHuM64AGgIfAiUBN4wsxOTzrmv4ADLtmG5yIiIhVMBaWIiETZCmCAmbUws5bAgOC2EoIWstfNbIGZrTCzz8xs76T9I4OWsXvM7Iugpe1rM+sQ7E9u7ft1E616dc3suaAFboaZHb6FmI8Lvn6edNt0YCfn3DHOuQuBK4LbjwgevwZwbXDbAOfcecD9QHV8sYVzbpxzrjO+8CzDOfeDc+6PxRswJ9j1rnNu1hbiLc8jwI7OuXOcc0cmPa8jgq8nALsCE5xzRwGHAbOAfYrPoXPuJufcvsDHm3mMU4OvNznnLgGuDH6+Jen5zQN+AXont36KiEi4VFCKiEiUvQjUBi4MtlrAC8kHmFl9YAS+2JwefN8XGGFmHUv9vuvwhdYSYD+geIzjo0nH/Cv4eW7SbafiWxknAh2B57cQ827B1ynFNzjn5jvnFiQdUyv4WvwY2wPN8a2JPwW3FbdE9trCY22SmTUAirulPry190/mnBvrnCtMuql07LsHX38Mji/Et1JC6rGvKz7ezOoAewQ/71pqzGTxOd0dERGJBBWUIiISZZ/ju3JeAgwMvv+i1DHHAjsBM4FDnHP9gXeAeiSKqmJPO+fOBm4Pft4dIGjRK3ZH0MqX3D1zMr5F7szg5+3NrMVmYi4eF5m3qZ1m1gX4K754LG5tbB18XeOcK24tXR18Tac17gKgMfCTc+7LzR1kZo8kbWeV90vN7GpgX3zX1adKxZ6fdOjWxn4vUAj8EVgL3BrcXg1omXRcbvC1KSIiEgk1wg5ARESkHE8RTG5Doqtosh2Dr9Occ0XB91ODrx1KHVvccrYy+NogxRjGOuecma1Muq0BsHQTxxYf07D0DjPbE/gAXxBd6JwbEuxaFHytZ2bVgudRHNvCFGMsfgwD/hD8+Eg5h1+Z9P2L+PGdm/u9t+PHeM4EDnPOFRd3xbEnn8utit05N8TMegAnAnXxf6e38UXm8qRDGwVfV6bye0VEJPPUQikiIlH3b2ANvtXr35vY/1vwdZegmALoEnwtPXZwY/DVUVZxMbqp18Yt3a+08cHXbsk3mtkR+O64DYD+zrkXk3bPwRdO1YDewW17Bl/HpfCYyY7Dz4a6AHhtSwc65yxpO39TxwSzzz6BLybHAPs752YnHTK2ON5gttbqJLqsphS7mdV0zk1xzv3NOXcbiS6tXzvn1iUdWnxOxyAiIpGgFkoREYk059wqMzso+D43UTP+z1B84dgR+MzMlgIn47tObmmsY2lz8C2afzez6cCf0gx5CHAHcDB++RCCmVqH4McffgMcYmaHBMff4ZxbbmYP4rvCvm5mXwCn4Vvo7g9+Rwv8TKjNih+oePmNUsXgH4OvTzjnCtJ8DsnuxM+uW4Qv5G4M/gYznHN/B97Ftwjn4GeCrY0fE/qDc+6zIM6TgJOAvYLfeUAQ+1fOuX8CR5lfs3MUsAN+ZtkNwM1Jz7Ud/m88ptR4VBERCZEKShERiTzn3I9b2LfazA4F7gMOAOrgx17eVGocZHluwBdsRwPHkJiwZ2tjHWNm3wGHmlmrYOmQliQms9kv2Io9gm+dvBff3fNC4Az8BDR/cs5NDI5rAJxX6uGKfz4fwMy6A4fiJ7l5iorRLvhaLYit2OfA351zRcF6mY8Bh+Bbcd8k0e0W/OQ8ybF3DDbwS6fMC37/2cH9RwK3OOe+TrrPGYABT27zMxIRkQpjibH/IiIiUhGCAvdT4K/OuVvKO162LFhWZQa+1XJX59yGkEMSEZGACkoRERERERFJiyblERERERERkbSooBQREREREZG0qKAUERERERGRtKigFBERERERkbSooBQREREREZG0qKAUERERERGRtKigFBERERERkbSooBQREREREZG0/D8lmjWwbqnUngAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "sns.lineplot(x='month', y='average', hue='hotel', data=hotel_per_month, palette=['blue', 'red'])\n",
    "\n",
    "#set title, caption and legend\n",
    "plt.grid()\n",
    "plt.title('Comparison of Monthly Hotel Booking Based on Hotel Type', fontsize=20, fontweight='bold', pad=50)\n",
    "plt.text(x=-0.37,y=5065, s='Both of hotel type tend to be increase in the holiday season, however amount of City Hotel bookings \\nlook decrease on August to September.', fontsize=16)\n",
    "plt.legend(title='Hotel Type')\n",
    "\n",
    "#set label\n",
    "plt.xlabel('Month (2017 - 2019)', fontsize=12, fontweight='bold', labelpad=15)\n",
    "plt.ylabel('Average of Bookings', fontsize=12, fontweight='bold', labelpad=15)\n",
    "plt.ylim(0,5000)\n",
    "plt.tick_params(axis='both', which='major', labelsize=12)\n",
    "\n",
    "\n",
    "#set holiday season\n",
    "plt.axvline(x=4, color='orange', ls='--')\n",
    "plt.axvline(x=6, color='orange', ls='--')\n",
    "plt.stackplot([4, 5, 6], [5000], color='orange', alpha=0.1)\n",
    "plt.text(x=4.35, y=2500, s='$\\it{Holiday}$ $\\it{Season}$', fontsize=12, color='orange')\n",
    "\n",
    "#set holiday season\n",
    "plt.axvline(x=9, color='orange', ls='--')\n",
    "plt.axvline(x=11, color='orange', ls='--')\n",
    "plt.stackplot([9, 10, 11], [5000], color='orange', alpha=0.1)\n",
    "plt.text(x=9.35, y=2500, s='$\\it{Holiday}$ $\\it{Season}$', fontsize=12, color='orange');\n",
    "\n",
    "#save to image\n",
    "plt.savefig('Monthly Hotel Booking Based on Hotel Type.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d16b20b-497b-4e2f-b496-2fc15a1bbfa0",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Impact Analysis of Stay Duration on Hotel Bookings Cancellation Rates"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "551c6803-4f9f-4ba5-9688-200c491116ee",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Stays Duration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b389e8ec-0b56-4a95-a885-be52c20b8121",
   "metadata": {},
   "outputs": [
    {
     "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_weekdays_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>...</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>guest</th>\n",
       "      <th>stays_duration</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>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2.0</td>\n",
       "      <td>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>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2.0</td>\n",
       "      <td>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>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>304.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>240.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          hotel  is_canceled  lead_time  arrival_date_year arrival_date_month  \\\n",
       "0  Resort Hotel            0        342               2017          September   \n",
       "1  Resort Hotel            0        737               2017          September   \n",
       "2  Resort Hotel            0          7               2017          September   \n",
       "3  Resort Hotel            0         13               2017          September   \n",
       "4  Resort Hotel            0         14               2017          September   \n",
       "\n",
       "   arrival_date_week_number  arrival_date_day_of_month  \\\n",
       "0                        27                          1   \n",
       "1                        27                          1   \n",
       "2                        27                          1   \n",
       "3                        27                          1   \n",
       "4                        27                          1   \n",
       "\n",
       "   stays_in_weekend_nights  stays_in_weekdays_nights  adults  ...  agent  \\\n",
       "0                        0                         0       2  ...    0.0   \n",
       "1                        0                         0       2  ...    0.0   \n",
       "2                        0                         1       1  ...    0.0   \n",
       "3                        0                         1       1  ...  304.0   \n",
       "4                        0                         2       2  ...  240.0   \n",
       "\n",
       "   company days_in_waiting_list customer_type   adr  \\\n",
       "0      0.0                    0      Personal   0.0   \n",
       "1      0.0                    0      Personal   0.0   \n",
       "2      0.0                    0      Personal  75.0   \n",
       "3      0.0                    0      Personal  75.0   \n",
       "4      0.0                    0      Personal  98.0   \n",
       "\n",
       "  required_car_parking_spaces  total_of_special_requests  reservation_status  \\\n",
       "0                           0                          0           Check-Out   \n",
       "1                           0                          0           Check-Out   \n",
       "2                           0                          0           Check-Out   \n",
       "3                           0                          0           Check-Out   \n",
       "4                           0                          1           Check-Out   \n",
       "\n",
       "   guest  stays_duration  \n",
       "0    2.0               0  \n",
       "1    2.0               0  \n",
       "2    1.0               1  \n",
       "3    1.0               1  \n",
       "4    2.0               2  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create new column as stay duration\n",
    "data['stays_duration'] = data['stays_in_weekend_nights'] + data['stays_in_weekdays_nights']\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "002a74dc-b7bc-4fc2-a926-6ca0e28644b1",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Grouping Stays Duration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "91135484-658e-46fe-936c-6a683cf2f32a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(data['stays_duration'], binwidth=2);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "07118bab-631c-4ce1-8fec-e407fe3fc24f",
   "metadata": {},
   "outputs": [
    {
     "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_weekdays_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>...</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>guest</th>\n",
       "      <th>stays_duration</th>\n",
       "      <th>stays_duration_group</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>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>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>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>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>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          hotel  is_canceled  lead_time  arrival_date_year arrival_date_month  \\\n",
       "0  Resort Hotel            0        342               2017          September   \n",
       "1  Resort Hotel            0        737               2017          September   \n",
       "2  Resort Hotel            0          7               2017          September   \n",
       "3  Resort Hotel            0         13               2017          September   \n",
       "4  Resort Hotel            0         14               2017          September   \n",
       "\n",
       "   arrival_date_week_number  arrival_date_day_of_month  \\\n",
       "0                        27                          1   \n",
       "1                        27                          1   \n",
       "2                        27                          1   \n",
       "3                        27                          1   \n",
       "4                        27                          1   \n",
       "\n",
       "   stays_in_weekend_nights  stays_in_weekdays_nights  adults  ...  company  \\\n",
       "0                        0                         0       2  ...      0.0   \n",
       "1                        0                         0       2  ...      0.0   \n",
       "2                        0                         1       1  ...      0.0   \n",
       "3                        0                         1       1  ...      0.0   \n",
       "4                        0                         2       2  ...      0.0   \n",
       "\n",
       "   days_in_waiting_list customer_type   adr required_car_parking_spaces  \\\n",
       "0                     0      Personal   0.0                           0   \n",
       "1                     0      Personal   0.0                           0   \n",
       "2                     0      Personal  75.0                           0   \n",
       "3                     0      Personal  75.0                           0   \n",
       "4                     0      Personal  98.0                           0   \n",
       "\n",
       "  total_of_special_requests  reservation_status  guest  stays_duration  \\\n",
       "0                         0           Check-Out    2.0               0   \n",
       "1                         0           Check-Out    2.0               0   \n",
       "2                         0           Check-Out    1.0               1   \n",
       "3                         0           Check-Out    1.0               1   \n",
       "4                         1           Check-Out    2.0               2   \n",
       "\n",
       "   stays_duration_group  \n",
       "0                     0  \n",
       "1                     0  \n",
       "2                     1  \n",
       "3                     1  \n",
       "4                     2  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['stays_duration_group'] = np.where(data['stays_duration']>=20,20,np.where(data['stays_duration']>=15,15,data['stays_duration']))\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c71cf1f1-6f2c-4be2-b860-3a84dd514fb5",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Comparison Cancellation of Hotel Bookings Toward Duration on Hotel Type "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c7f78a7a-f696-4fb2-b5db-3ed047b361b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Check-Out', 'Canceled', 'No-Show'], dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.reservation_status.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "37808d53-234f-451d-8110-0ed48497f141",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\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>stays_duration_group</th>\n",
       "      <th>is_not_canceled</th>\n",
       "      <th>is_canceled</th>\n",
       "      <th>percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>251</td>\n",
       "      <td>13</td>\n",
       "      <td>4.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>1</td>\n",
       "      <td>9155</td>\n",
       "      <td>4103</td>\n",
       "      <td>30.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>2</td>\n",
       "      <td>10983</td>\n",
       "      <td>10432</td>\n",
       "      <td>48.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>3</td>\n",
       "      <td>11889</td>\n",
       "      <td>9482</td>\n",
       "      <td>44.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>4</td>\n",
       "      <td>7694</td>\n",
       "      <td>4853</td>\n",
       "      <td>38.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>5</td>\n",
       "      <td>3210</td>\n",
       "      <td>1775</td>\n",
       "      <td>35.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>6</td>\n",
       "      <td>1111</td>\n",
       "      <td>938</td>\n",
       "      <td>45.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>7</td>\n",
       "      <td>1245</td>\n",
       "      <td>808</td>\n",
       "      <td>39.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>8</td>\n",
       "      <td>205</td>\n",
       "      <td>176</td>\n",
       "      <td>46.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>9</td>\n",
       "      <td>119</td>\n",
       "      <td>93</td>\n",
       "      <td>43.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>10</td>\n",
       "      <td>80</td>\n",
       "      <td>116</td>\n",
       "      <td>59.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>11</td>\n",
       "      <td>33</td>\n",
       "      <td>46</td>\n",
       "      <td>58.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>12</td>\n",
       "      <td>33</td>\n",
       "      <td>30</td>\n",
       "      <td>47.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "      <td>26</td>\n",
       "      <td>63.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>14</td>\n",
       "      <td>26</td>\n",
       "      <td>71</td>\n",
       "      <td>73.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>15</td>\n",
       "      <td>27</td>\n",
       "      <td>55</td>\n",
       "      <td>67.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>20</td>\n",
       "      <td>8</td>\n",
       "      <td>62</td>\n",
       "      <td>88.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>371</td>\n",
       "      <td>10</td>\n",
       "      <td>2.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>1</td>\n",
       "      <td>6579</td>\n",
       "      <td>1168</td>\n",
       "      <td>15.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>2</td>\n",
       "      <td>4488</td>\n",
       "      <td>1729</td>\n",
       "      <td>27.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>3</td>\n",
       "      <td>3828</td>\n",
       "      <td>1865</td>\n",
       "      <td>32.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>4</td>\n",
       "      <td>3321</td>\n",
       "      <td>1505</td>\n",
       "      <td>31.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>5</td>\n",
       "      <td>1899</td>\n",
       "      <td>887</td>\n",
       "      <td>31.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>6</td>\n",
       "      <td>1205</td>\n",
       "      <td>592</td>\n",
       "      <td>32.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>7</td>\n",
       "      <td>4434</td>\n",
       "      <td>2161</td>\n",
       "      <td>32.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>8</td>\n",
       "      <td>509</td>\n",
       "      <td>265</td>\n",
       "      <td>34.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>9</td>\n",
       "      <td>408</td>\n",
       "      <td>220</td>\n",
       "      <td>35.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>10</td>\n",
       "      <td>699</td>\n",
       "      <td>240</td>\n",
       "      <td>25.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>11</td>\n",
       "      <td>240</td>\n",
       "      <td>74</td>\n",
       "      <td>23.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>12</td>\n",
       "      <td>89</td>\n",
       "      <td>68</td>\n",
       "      <td>43.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>13</td>\n",
       "      <td>75</td>\n",
       "      <td>25</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>14</td>\n",
       "      <td>630</td>\n",
       "      <td>186</td>\n",
       "      <td>22.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>15</td>\n",
       "      <td>55</td>\n",
       "      <td>52</td>\n",
       "      <td>48.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>20</td>\n",
       "      <td>97</td>\n",
       "      <td>73</td>\n",
       "      <td>42.94</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel  stays_duration_group  is_not_canceled  is_canceled  \\\n",
       "0     City Hotel                     0              251           13   \n",
       "1     City Hotel                     1             9155         4103   \n",
       "2     City Hotel                     2            10983        10432   \n",
       "3     City Hotel                     3            11889         9482   \n",
       "4     City Hotel                     4             7694         4853   \n",
       "5     City Hotel                     5             3210         1775   \n",
       "6     City Hotel                     6             1111          938   \n",
       "7     City Hotel                     7             1245          808   \n",
       "8     City Hotel                     8              205          176   \n",
       "9     City Hotel                     9              119           93   \n",
       "10    City Hotel                    10               80          116   \n",
       "11    City Hotel                    11               33           46   \n",
       "12    City Hotel                    12               33           30   \n",
       "13    City Hotel                    13               15           26   \n",
       "14    City Hotel                    14               26           71   \n",
       "15    City Hotel                    15               27           55   \n",
       "16    City Hotel                    20                8           62   \n",
       "17  Resort Hotel                     0              371           10   \n",
       "18  Resort Hotel                     1             6579         1168   \n",
       "19  Resort Hotel                     2             4488         1729   \n",
       "20  Resort Hotel                     3             3828         1865   \n",
       "21  Resort Hotel                     4             3321         1505   \n",
       "22  Resort Hotel                     5             1899          887   \n",
       "23  Resort Hotel                     6             1205          592   \n",
       "24  Resort Hotel                     7             4434         2161   \n",
       "25  Resort Hotel                     8              509          265   \n",
       "26  Resort Hotel                     9              408          220   \n",
       "27  Resort Hotel                    10              699          240   \n",
       "28  Resort Hotel                    11              240           74   \n",
       "29  Resort Hotel                    12               89           68   \n",
       "30  Resort Hotel                    13               75           25   \n",
       "31  Resort Hotel                    14              630          186   \n",
       "32  Resort Hotel                    15               55           52   \n",
       "33  Resort Hotel                    20               97           73   \n",
       "\n",
       "    percentage  \n",
       "0         4.92  \n",
       "1        30.95  \n",
       "2        48.71  \n",
       "3        44.37  \n",
       "4        38.68  \n",
       "5        35.61  \n",
       "6        45.78  \n",
       "7        39.36  \n",
       "8        46.19  \n",
       "9        43.87  \n",
       "10       59.18  \n",
       "11       58.23  \n",
       "12       47.62  \n",
       "13       63.41  \n",
       "14       73.20  \n",
       "15       67.07  \n",
       "16       88.57  \n",
       "17        2.62  \n",
       "18       15.08  \n",
       "19       27.81  \n",
       "20       32.76  \n",
       "21       31.19  \n",
       "22       31.84  \n",
       "23       32.94  \n",
       "24       32.77  \n",
       "25       34.24  \n",
       "26       35.03  \n",
       "27       25.56  \n",
       "28       23.57  \n",
       "29       43.31  \n",
       "30       25.00  \n",
       "31       22.79  \n",
       "32       48.60  \n",
       "33       42.94  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create aggregate table\n",
    "cancel_group = data.groupby(['hotel', 'is_canceled', 'stays_duration_group'])['arrival_date_year'].count().reset_index()\n",
    "cancel_pivot = pd.pivot_table(cancel_group,\n",
    "                              index=['hotel', 'stays_duration_group'],\n",
    "                              columns='is_canceled',\n",
    "                              values='arrival_date_year'\n",
    "                             ).reset_index()\n",
    "cancel_pivot.columns = ['hotel', 'stays_duration_group', 'is_not_canceled', 'is_canceled']\n",
    "cancel_pivot\n",
    "cancel_pivot['percentage'] = round(cancel_pivot['is_canceled'] / (cancel_pivot['is_not_canceled'] + cancel_pivot['is_canceled'])*100,2)\n",
    "cancel_pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e089ed20-bf54-431d-b1ae-344d52a5a0e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hotel</th>\n",
       "      <th>stays_duration_group</th>\n",
       "      <th>is_not_canceled</th>\n",
       "      <th>is_canceled</th>\n",
       "      <th>percentage</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>15</td>\n",
       "      <td>55</td>\n",
       "      <td>52</td>\n",
       "      <td>48.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>12</td>\n",
       "      <td>89</td>\n",
       "      <td>68</td>\n",
       "      <td>43.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>20</td>\n",
       "      <td>97</td>\n",
       "      <td>73</td>\n",
       "      <td>42.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>9</td>\n",
       "      <td>408</td>\n",
       "      <td>220</td>\n",
       "      <td>35.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>8</td>\n",
       "      <td>509</td>\n",
       "      <td>265</td>\n",
       "      <td>34.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>6</td>\n",
       "      <td>1205</td>\n",
       "      <td>592</td>\n",
       "      <td>32.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>7</td>\n",
       "      <td>4434</td>\n",
       "      <td>2161</td>\n",
       "      <td>32.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>3</td>\n",
       "      <td>3828</td>\n",
       "      <td>1865</td>\n",
       "      <td>32.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>5</td>\n",
       "      <td>1899</td>\n",
       "      <td>887</td>\n",
       "      <td>31.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>4</td>\n",
       "      <td>3321</td>\n",
       "      <td>1505</td>\n",
       "      <td>31.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>2</td>\n",
       "      <td>4488</td>\n",
       "      <td>1729</td>\n",
       "      <td>27.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>10</td>\n",
       "      <td>699</td>\n",
       "      <td>240</td>\n",
       "      <td>25.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>13</td>\n",
       "      <td>75</td>\n",
       "      <td>25</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>11</td>\n",
       "      <td>240</td>\n",
       "      <td>74</td>\n",
       "      <td>23.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>14</td>\n",
       "      <td>630</td>\n",
       "      <td>186</td>\n",
       "      <td>22.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>1</td>\n",
       "      <td>6579</td>\n",
       "      <td>1168</td>\n",
       "      <td>15.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>371</td>\n",
       "      <td>10</td>\n",
       "      <td>2.62</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel  stays_duration_group  is_not_canceled  is_canceled  \\\n",
       "32  Resort Hotel                    15               55           52   \n",
       "29  Resort Hotel                    12               89           68   \n",
       "33  Resort Hotel                    20               97           73   \n",
       "26  Resort Hotel                     9              408          220   \n",
       "25  Resort Hotel                     8              509          265   \n",
       "23  Resort Hotel                     6             1205          592   \n",
       "24  Resort Hotel                     7             4434         2161   \n",
       "20  Resort Hotel                     3             3828         1865   \n",
       "22  Resort Hotel                     5             1899          887   \n",
       "21  Resort Hotel                     4             3321         1505   \n",
       "19  Resort Hotel                     2             4488         1729   \n",
       "27  Resort Hotel                    10              699          240   \n",
       "30  Resort Hotel                    13               75           25   \n",
       "28  Resort Hotel                    11              240           74   \n",
       "31  Resort Hotel                    14              630          186   \n",
       "18  Resort Hotel                     1             6579         1168   \n",
       "17  Resort Hotel                     0              371           10   \n",
       "\n",
       "    percentage  \n",
       "32       48.60  \n",
       "29       43.31  \n",
       "33       42.94  \n",
       "26       35.03  \n",
       "25       34.24  \n",
       "23       32.94  \n",
       "24       32.77  \n",
       "20       32.76  \n",
       "22       31.84  \n",
       "21       31.19  \n",
       "19       27.81  \n",
       "27       25.56  \n",
       "30       25.00  \n",
       "28       23.57  \n",
       "31       22.79  \n",
       "18       15.08  \n",
       "17        2.62  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cancel_pivot[cancel_pivot['hotel']=='Resort Hotel'].sort_values('percentage', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2477259-0c0c-480a-8751-1f1196f32f8a",
   "metadata": {},
   "source": [
    "## Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1ce52998-3de7-457c-89de-1f5481d731f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# make new variable\n",
    "x = cancel_pivot['stays_duration_group']\n",
    "y = cancel_pivot['percentage']\n",
    "z = cancel_pivot['hotel']\n",
    "\n",
    "# distribution using barplot\n",
    "plt.figure(figsize=(15,10))\n",
    "sns.barplot(x=x, y=y, hue=z, data=cancel_pivot)\n",
    "plt.grid()\n",
    "\n",
    "# set title, caption, legend\n",
    "plt.title('MORE LONGER STAYS OF DURATION WILL AFFECT CANCEL BOOKINGS', fontsize=20, fontweight='bold', pad=50)\n",
    "plt.text(x=0.7, y=102, s='City Hotel was the highest cancel bookings rate than the Resort Hotel, almost 100%. However, Resort \\nHotel had the percentage less 50%.', fontsize=16)\n",
    "plt.tick_params(axis='both', which='major', labelsize=12)\n",
    "plt.legend(title='Hotel Type', loc='upper left')\n",
    "\n",
    "# set label and limitation\n",
    "plt.xlabel('Stays Duration', fontsize=12, fontweight='bold', labelpad=15)\n",
    "plt.ylabel('Percentage', fontsize=12, fontweight='bold', labelpad=15)\n",
    "plt.ylim(0,100)\n",
    "plt.xlim(0.5,)\n",
    "\n",
    "# annotate\n",
    "plt.axhline(y=0, color='orange', ls='--')\n",
    "plt.axhline(y=50, color='orange', ls='--')\n",
    "plt.stackplot([0,20], 50, colors=('orange',), alpha=0.3)\n",
    "plt.annotate('Highest Cancel Rate in \\nResort Hotel 48.60%', xy = (15.2, 48.6), xytext = (14, 55), arrowprops = dict(facecolor = 'orange', arrowstyle = '->', connectionstyle = 'arc3, rad=.2'), ha = 'center')\n",
    "\n",
    "# save file\n",
    "plt.savefig('Impact Analysis of Stay Duration on Hotel Bookings Cancellation Rates Visualization.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02a2989d-9dd4-47dd-b674-e60ad061e7d6",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Impact Analysis of Lead Time on Hotel Bookings Cancellation Rate"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4a3951e-d4ba-4211-aa3d-fa43622a3fa8",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Categories Lead Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ab0b6323-a9b7-49cf-a9d3-5ccac7b1078d",
   "metadata": {},
   "outputs": [
    {
     "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_weekdays_nights</th>\n",
       "      <th>adults</th>\n",
       "      <th>...</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>guest</th>\n",
       "      <th>stays_duration</th>\n",
       "      <th>stays_duration_group</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>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>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>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>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>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2017</td>\n",
       "      <td>September</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Personal</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Check-Out</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          hotel  is_canceled  lead_time  arrival_date_year arrival_date_month  \\\n",
       "0  Resort Hotel            0        342               2017          September   \n",
       "1  Resort Hotel            0        737               2017          September   \n",
       "2  Resort Hotel            0          7               2017          September   \n",
       "3  Resort Hotel            0         13               2017          September   \n",
       "4  Resort Hotel            0         14               2017          September   \n",
       "\n",
       "   arrival_date_week_number  arrival_date_day_of_month  \\\n",
       "0                        27                          1   \n",
       "1                        27                          1   \n",
       "2                        27                          1   \n",
       "3                        27                          1   \n",
       "4                        27                          1   \n",
       "\n",
       "   stays_in_weekend_nights  stays_in_weekdays_nights  adults  ...  company  \\\n",
       "0                        0                         0       2  ...      0.0   \n",
       "1                        0                         0       2  ...      0.0   \n",
       "2                        0                         1       1  ...      0.0   \n",
       "3                        0                         1       1  ...      0.0   \n",
       "4                        0                         2       2  ...      0.0   \n",
       "\n",
       "   days_in_waiting_list customer_type   adr required_car_parking_spaces  \\\n",
       "0                     0      Personal   0.0                           0   \n",
       "1                     0      Personal   0.0                           0   \n",
       "2                     0      Personal  75.0                           0   \n",
       "3                     0      Personal  75.0                           0   \n",
       "4                     0      Personal  98.0                           0   \n",
       "\n",
       "  total_of_special_requests  reservation_status  guest  stays_duration  \\\n",
       "0                         0           Check-Out    2.0               0   \n",
       "1                         0           Check-Out    2.0               0   \n",
       "2                         0           Check-Out    1.0               1   \n",
       "3                         0           Check-Out    1.0               1   \n",
       "4                         1           Check-Out    2.0               2   \n",
       "\n",
       "   stays_duration_group  \n",
       "0                     0  \n",
       "1                     0  \n",
       "2                     1  \n",
       "3                     1  \n",
       "4                     2  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "66abd7aa-7ca2-402b-bbd4-6c3350ea7492",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='lead_time', ylabel='Count'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SpueViCSpM4uIJKkzi4gkqTOLiCSpM4uIJKkzi4gkqTOLiCSpM4uIJKkzi4gkqTOLiCSps4EVkSQbkuxKck9f7MgkW5I80D6XtniSXJpkPMldSY7v22Z9a/9AkvV98Vcmubttc2mSDOpcJElTG+SVyBXAukmxC4Ebq2o1cGNbBjgVWN2m84DLoFd0gIuBE+m9T/3iicLT2ry9b7vJx3r2O8ABGx20UdJsG9gAjFX1xSSrJoVPB17f5q8Ebgbe0+JXVVUBtyRZkmRZa7ulqvYAJNkCrEtyM/CCqrqlxa8CzgA+O6jzGUkHOGAjOGijpNk17D6Ro6tqZ5v/FnB0m18OPNzXbnuL7S++fYr4lJKcl2Rrkq27d+8+uDOQJP3QnHWst6uOGtKxLq+qtVW1dmxsbBiHlKQFYdhF5JF2m4r2uavFdwAr+9qtaLH9xVdMEZckDdGwi8hGYOIJq/XA9X3xc9pTWicBj7fbXpuBU5IsbR3qpwCb27onkpzUnso6p29fkqQhGVjHepJP0usYPyrJdnpPWX0AuDbJucA3gTe35puA04Bx4HvA2wCqak+S9wO3t3bvm+hkB95J7wmwI+h1qC+sTnVJGgGDfDrr7H2sesMUbQs4fx/72QBsmCK+FXj5weQoSTo4/mJdktSZRUSS1JlFRJLUmUVEktSZRUSS1JlFZKE5wEEbHbBR0v4M7BFfjagDHLTxml99HQcyyv6PrljJjof/oUtmkuYhi4j270CLjqMESwuKt7MkSZ1ZRCRJnVlEJEmdWUQkSZ1ZRCRJnVlEJEmdWUQkSZ1ZRCRJnVlEJEmdWUQkSZ3NSRFJ8lCSu5PcmWRrix2ZZEuSB9rn0hZPkkuTjCe5K8nxfftZ39o/kGT9XJyLJnGAR2lBmcuxs36mqv6xb/lC4Maq+kCSC9vye4BTgdVtOhG4DDgxyZHAxcBaoIA7kmysqkeHeRKaxLG2pAVllG5nnQ5c2eavBM7oi19VPbcAS5IsA94IbKmqPa1wbAHWDTlnSVrQ5qqIFPC5JHckOa/Fjq6qnW3+W8DRbX458HDftttbbF9xSdKQzNXtrNdW1Y4kPwJsSfK1/pVVVUlqtg7WCtV5AMcc4z14SZotc3IlUlU72ucu4DPACcAj7TYV7XNXa74DWNm3+YoW21d8quNdXlVrq2rt2NjYbJ6KJC1oQy8iSZ6b5PkT88ApwD3ARmDiCav1wPVtfiNwTntK6yTg8XbbazNwSpKl7UmuU1pMkjQkc3E762jgM+2Vq4uBP6+qv05yO3BtknOBbwJvbu03AacB48D3gLcBVNWeJO8Hbm/t3ldVe4Z3GpoV7ZHgmfL1u9JoGXoRqaoHgZ+aIv5t4A1TxAs4fx/72gBsmO0cNUQ+EizNa6P0iK8kaZ6xiEiSOrOISJI6s4hofjnAsbkWH3r4AbV3PC/pwMzl2FnSgevQEX8g7Se2kTQzXolIkjqziEiSOrOISJP5ThRpxuwTkSbzB5DSjHklIknqzCIiSerMIiJJ6swiIh0sO+K1gNmxLh0sO+K1gHklIknqzCIiSerMIiJJ6swiIg3bgEcituNew2THujRsAx6J2I57DdO8vxJJsi7J/UnGk1w41/lIc+4Ar3S82tHBmNdXIkkWAR8Gfg7YDtyeZGNV3Tu3mUlz6ACvdMCrHXU3369ETgDGq+rBqvo+cDVw+hznJD37DbhfZ9BXRstXHuMbL2dJqmquc+gsyZnAuqr65bb8VuDEqrpgUrvzgPPa4k8A93c85FHAP3bcdlhGPcdRzw9GP8dRzw9GP8dRzw9GL8cfq6qxycF5fTtrpqrqcuDyg91Pkq1VtXYWUhqYUc9x1POD0c9x1POD0c9x1POD+ZEjzP/bWTuAlX3LK1pMkjQE872I3A6sTnJskkOBs4CNc5yTJC0Y8/p2VlXtTXIBsBlYBGyoqm0DPORB3xIbglHPcdTzg9HPcdTzg9HPcdTzg/mR4/zuWJckza35fjtLkjSHLCKSpM4sIjMwKkOrJNmQZFeSe/piRybZkuSB9rm0xZPk0pbzXUmOH0J+K5PclOTeJNuS/PoI5nh4ktuSfLXl+N4WPzbJrS2Xa9qDGiQ5rC2Pt/WrBp1jO+6iJF9JcsOI5vdQkruT3Jlka4uNzPfcjrskyXVJvpbkviSvGpUck/xE+283MT2R5F2jkt8BqSqn/Uz0Ouy/Dvw4cCjwVeC4OcrldcDxwD19sT8ALmzzFwIfbPOnAZ8FApwE3DqE/JYBx7f55wN/Dxw3YjkGeF6bPwS4tR37WuCsFv8I8Ktt/p3AR9r8WcA1Q/qufwP4c+CGtjxq+T0EHDUpNjLfczvulcAvt/lDgSWjlmM79iLgW8CPjWJ+0+Y/1wmM+gS8Ctjct3wRcNEc5rNqUhG5H1jW5pcB97f5jwJnT9VuiLleT29cs5HMEfhnwJeBE+n9Mnjx5O+c3pN/r2rzi1u7DDivFcCNwMnADe0fjpHJrx1rqiIyMt8z8ELgG5P/W4xSjn3HOgX4X6Oa33STt7Omtxx4uG95e4uNiqOrameb/xZwdJuf07zbbZVX0PtLf6RybLeK7gR2AVvoXWk+VlV7p8jjhzm29Y8DLxpwin8M/CfgB235RSOWH0ABn0tyR3rDCsFofc/HAruBP2u3Bf80yXNHLMcJZwGfbPOjmN9+WUSeRar3J8qcP7Od5HnAp4B3VdUT/etGIceqeqqq1tD7i/8E4KVzmU+/JP8G2FVVd8x1LtN4bVUdD5wKnJ/kdf0rR+B7Xkzv1u9lVfUK4J/o3R76oRHIkda39fPAX0xeNwr5zYRFZHqjPrTKI0mWAbTPXS0+J3knOYReAflEVX16FHOcUFWPATfRuz20JMnEj2/78/hhjm39C4FvDzCt1wA/n+QheqNSnwz81xHKD4Cq2tE+dwGfoVeMR+l73g5sr6pb2/J19IrKKOUIvSL85ap6pC2PWn7TsohMb9SHVtkIrG/z6+n1Q0zEz2lPdZwEPN53mTwQSQJ8HLivqv5oRHMcS7KkzR9Br8/mPnrF5Mx95DiR+5nAF9pfiANRVRdV1YqqWkXvf2tfqKpfHJX8AJI8N8nzJ+bp3dO/hxH6nqvqW8DDSX6ihd4A3DtKOTZn8/StrIk8Rim/6c11p8x8mOg9GfH39O6d//Yc5vFJYCfwf+n9pXUuvfvfNwIPAJ8HjmxtQ++FXV8H7gbWDiG/19K7/L4LuLNNp41Yjv8K+ErL8R7gd1r8x4HbgHF6txYOa/HD2/J4W//jQ/y+X8/TT2eNTH4tl6+2advE/ydG6Xtux10DbG3f9V8CS0cpR+C59K4aX9gXG5n8Zjo57IkkqTNvZ0mSOrOISJI6s4hIkjqziEiSOrOISJI6s4hIkjqziEgHIMl3Z2k//yHJf9/P+jOSHNe3/L4kPzsbx5Zmk0VEGk1n0BtGH4Cq+p2q+vzcpSNNzSIidZTk3Uluby8Jem9f/C/b6Lbb+ka4Jcnbkvx9ktvojZG1r/2+mt6gfP+5vbDoxUmuSHJmW/9Qkt9v67YmOT7J5iRfT/Ir0+UnzabF0zeRNFmSU4DV9AYeDLAxyeuq6ovAL1XVnjY21+1JPkXvpUjvBV5Jb7j2m+gNv/IMVfWlJBvpDXlyXTve5Gb/UFVrknwIuIJeUTqc3lAuH5kmP2nWWESkbk5p00QheB69f7S/CPxakje1+MoW/+fAzVW1GyDJNcC/OIjjTwwCeje9NzV+B/hOkifbAJP7y0+aNRYRqZsAv19VH/3/gsnrgZ+l97bB7yW5md4Vwmx7sn3+oG9+YnnxvvKTZpt9IlI3m4Ffai/gIsnyJD9C730ej7YC8lJ678OG3hse/3WSF7V3rvzCNPv/Dr331M92ftKs8kpE6qCqPpfkJ4G/a/0V3wX+PfDXwK8kuY/ee7Bvae13Jvld4O+Ax+gNk78/VwMfS/JrPP0ekdnIb9d+N5QOkEPBS5I683aWJKkzb2dJcyjJb/PM/pG/qKpL5iIf6UB5O0uS1Jm3syRJnVlEJEmdWUQkSZ1ZRCRJnf0/9NUOwsVtyacAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(x='lead_time', data=data, binwidth=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "8f1d9d7b-1b40-4fce-a23a-7a42821e99be",
   "metadata": {},
   "outputs": [],
   "source": [
    "lead_time = np.where(data['lead_time'] > 365, 366, data['lead_time'])\n",
    "bins = list(np.arange(0, max(lead_time)+30, 30))\n",
    "labels = [\"{0}-{1}\".format(str(bins[x]), str(bins[x+1])) for x in range(len(bins[:-1]))]\n",
    "data['lead_time_group'] = pd.cut(lead_time, bins=bins, include_lowest=True, labels=labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "2129b894-0d14-44bb-b6c4-d46c66c76bf1",
   "metadata": {},
   "outputs": [
    {
     "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>lead_time_group</th>\n",
       "      <th>is_not_canceled</th>\n",
       "      <th>is_canceled</th>\n",
       "      <th>percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>0-30</td>\n",
       "      <td>18060</td>\n",
       "      <td>5184</td>\n",
       "      <td>22.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>30-60</td>\n",
       "      <td>7266</td>\n",
       "      <td>4608</td>\n",
       "      <td>38.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>60-90</td>\n",
       "      <td>5210</td>\n",
       "      <td>3692</td>\n",
       "      <td>41.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>90-120</td>\n",
       "      <td>3956</td>\n",
       "      <td>3486</td>\n",
       "      <td>46.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>120-150</td>\n",
       "      <td>3064</td>\n",
       "      <td>2542</td>\n",
       "      <td>45.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>150-180</td>\n",
       "      <td>2442</td>\n",
       "      <td>2716</td>\n",
       "      <td>52.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>180-210</td>\n",
       "      <td>1800</td>\n",
       "      <td>1793</td>\n",
       "      <td>49.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>210-240</td>\n",
       "      <td>1224</td>\n",
       "      <td>1280</td>\n",
       "      <td>51.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>240-270</td>\n",
       "      <td>880</td>\n",
       "      <td>1237</td>\n",
       "      <td>58.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>270-300</td>\n",
       "      <td>660</td>\n",
       "      <td>1859</td>\n",
       "      <td>73.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>300-330</td>\n",
       "      <td>514</td>\n",
       "      <td>1604</td>\n",
       "      <td>75.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>330-360</td>\n",
       "      <td>218</td>\n",
       "      <td>1004</td>\n",
       "      <td>82.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>City Hotel</td>\n",
       "      <td>360-390</td>\n",
       "      <td>790</td>\n",
       "      <td>2074</td>\n",
       "      <td>72.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>0-30</td>\n",
       "      <td>13352</td>\n",
       "      <td>1984</td>\n",
       "      <td>12.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>30-60</td>\n",
       "      <td>3512</td>\n",
       "      <td>1566</td>\n",
       "      <td>30.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>60-90</td>\n",
       "      <td>2400</td>\n",
       "      <td>1275</td>\n",
       "      <td>34.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>90-120</td>\n",
       "      <td>1828</td>\n",
       "      <td>1159</td>\n",
       "      <td>38.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>120-150</td>\n",
       "      <td>1499</td>\n",
       "      <td>1032</td>\n",
       "      <td>40.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>150-180</td>\n",
       "      <td>1812</td>\n",
       "      <td>884</td>\n",
       "      <td>32.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>180-210</td>\n",
       "      <td>1296</td>\n",
       "      <td>770</td>\n",
       "      <td>37.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>210-240</td>\n",
       "      <td>1051</td>\n",
       "      <td>754</td>\n",
       "      <td>41.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>240-270</td>\n",
       "      <td>667</td>\n",
       "      <td>619</td>\n",
       "      <td>48.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>270-300</td>\n",
       "      <td>556</td>\n",
       "      <td>350</td>\n",
       "      <td>38.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>300-330</td>\n",
       "      <td>322</td>\n",
       "      <td>315</td>\n",
       "      <td>49.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>330-360</td>\n",
       "      <td>295</td>\n",
       "      <td>198</td>\n",
       "      <td>40.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Resort Hotel</td>\n",
       "      <td>360-390</td>\n",
       "      <td>337</td>\n",
       "      <td>214</td>\n",
       "      <td>38.84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           hotel lead_time_group  is_not_canceled  is_canceled  percentage\n",
       "0     City Hotel            0-30            18060         5184       22.30\n",
       "1     City Hotel           30-60             7266         4608       38.81\n",
       "2     City Hotel           60-90             5210         3692       41.47\n",
       "3     City Hotel          90-120             3956         3486       46.84\n",
       "4     City Hotel         120-150             3064         2542       45.34\n",
       "5     City Hotel         150-180             2442         2716       52.66\n",
       "6     City Hotel         180-210             1800         1793       49.90\n",
       "7     City Hotel         210-240             1224         1280       51.12\n",
       "8     City Hotel         240-270              880         1237       58.43\n",
       "9     City Hotel         270-300              660         1859       73.80\n",
       "10    City Hotel         300-330              514         1604       75.73\n",
       "11    City Hotel         330-360              218         1004       82.16\n",
       "12    City Hotel         360-390              790         2074       72.42\n",
       "13  Resort Hotel            0-30            13352         1984       12.94\n",
       "14  Resort Hotel           30-60             3512         1566       30.84\n",
       "15  Resort Hotel           60-90             2400         1275       34.69\n",
       "16  Resort Hotel          90-120             1828         1159       38.80\n",
       "17  Resort Hotel         120-150             1499         1032       40.77\n",
       "18  Resort Hotel         150-180             1812          884       32.79\n",
       "19  Resort Hotel         180-210             1296          770       37.27\n",
       "20  Resort Hotel         210-240             1051          754       41.77\n",
       "21  Resort Hotel         240-270              667          619       48.13\n",
       "22  Resort Hotel         270-300              556          350       38.63\n",
       "23  Resort Hotel         300-330              322          315       49.45\n",
       "24  Resort Hotel         330-360              295          198       40.16\n",
       "25  Resort Hotel         360-390              337          214       38.84"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hotel_lead_time = data.groupby(['hotel','lead_time_group', 'is_canceled'])['hotel'].count().reset_index(name='bookings')\n",
    "hotel_lead_time = pd.pivot_table(hotel_lead_time,\n",
    "                                 index = ['hotel','lead_time_group'], \n",
    "                                 columns = 'is_canceled', \n",
    "                                 values = 'bookings'\n",
    "                                ).reset_index()\n",
    "hotel_lead_time.columns = ['hotel', 'lead_time_group', 'is_not_canceled', 'is_canceled']\n",
    "hotel_lead_time['percentage'] = round(hotel_lead_time['is_canceled'] / ((hotel_lead_time['is_not_canceled'] + hotel_lead_time['is_canceled']))*100, 2)\n",
    "hotel_lead_time"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d8a2bf3-7abb-48de-94b0-55ec32f660f3",
   "metadata": {},
   "source": [
    "## Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e76863f6-f293-4a4a-94b4-b424f6abe2a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# make new variable\n",
    "x = cancel_pivot['stays_duration_group']\n",
    "y = cancel_pivot['percentage']\n",
    "z = cancel_pivot['hotel']\n",
    "\n",
    "# distribution using barplot\n",
    "plt.figure(figsize=(15,10))\n",
    "sns.barplot(x=x, y=y, hue=z, data=cancel_pivot)\n",
    "plt.grid()\n",
    "\n",
    "# set title, caption, legend\n",
    "plt.title('MORE LONGER STAYS OF DURATION WILL AFFECT CANCEL BOOKINGS', fontsize=20, fontweight='bold', pad=50)\n",
    "plt.text(x=0.7, y=102, s='City Hotel was the highest cancel bookings rate than the Resort Hotel, almost 100%. However, Resort \\nHotel had the percentage less 50%.', fontsize=16)\n",
    "plt.tick_params(axis='both', which='major', labelsize=12)\n",
    "plt.legend(title='Hotel Type', loc='upper left')\n",
    "\n",
    "# set label and limitation\n",
    "plt.xlabel('Stays Duration', fontsize=12, fontweight='bold', labelpad=15)\n",
    "plt.ylabel('Percentage', fontsize=12, fontweight='bold', labelpad=15)\n",
    "plt.ylim(0,100)\n",
    "plt.xlim(0.5,)\n",
    "\n",
    "# annotate\n",
    "plt.axhline(y=0, color='orange', ls='--')\n",
    "plt.axhline(y=50, color='orange', ls='--')\n",
    "plt.stackplot([0,20], 50, colors=('orange',), alpha=0.3)\n",
    "plt.annotate('Highest Cancel Rate in \\nResort Hotel 48.60%', xy = (15.2, 48.6), xytext = (14, 55), arrowprops = dict(facecolor = 'orange', arrowstyle = '->', connectionstyle = 'arc3, rad=.2'), ha = 'center')\n",
    "\n",
    "# save file\n",
    "plt.savefig('Impact Analysis of Stay Duration on Hotel Bookings Cancellation Rates Visualization.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "360916ae-f5f4-45b2-be24-d2e7e6c7e945",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "percentage = hotel_lead_time['percentage']\n",
    "lead_time = hotel_lead_time['lead_time_group']\n",
    "hotel = hotel_lead_time['hotel']\n",
    "\n",
    "plt.figure(figsize=(15,10))\n",
    "sns.barplot(x=lead_time, y=percentage, hue=hotel, data=hotel_lead_time)\n",
    "plt.grid()\n",
    "\n",
    "plt.title('BOTH HOTEL TYPE HAD DIFFERENT DISTRIBUTION OF LEAD TIME BASED \\nON CANCELLATION RATE', fontsize=20, fontweight='bold', pad=50)\n",
    "plt.text(x=-0.5, y=102, s='Increase of lead time City Hotel will affect to cancellation bookings. However, Resort Hotel had \\nfluctuative distribution', fontsize=16)            \n",
    "plt.tick_params(axis='both', which='major', labelsize=12)\n",
    "plt.legend(title='Hotel Type')\n",
    "\n",
    "plt.xlabel('Lead Time (30 Days)')\n",
    "plt.ylabel('Percentage')\n",
    "plt.ylim(0, 100)\n",
    "\n",
    "plt.savefig('Impact Analysis of Lead Time on Hotel Bookings Cancellation Rate Visualization.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "732c8bd7-a907-4d41-ad8e-5cd6de0acdd2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}