Audible_dataset_EDA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f3f7dbb3-e18f-4f81-a620-632d113e3144",
   "metadata": {},
   "source": [
    "**DATA PREPROCESSING**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51276080-e826-4b0f-bb67-595475ff6df0",
   "metadata": {},
   "source": [
    "https://www.kaggle.com/datasets/snehangsude/audible-dataset?select=audible_uncleaned.csv  (dataset link)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "a76de2eb-f42e-4e1e-b621-a40df7fbf67e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in c:\\users\\user\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (2.2.2)\n",
      "Requirement already satisfied: numpy>=1.26.0 in c:\\users\\user\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from pandas) (1.26.4)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in c:\\users\\user\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from pandas) (2.9.0.post0)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\user\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from pandas) (2024.1)\n",
      "Requirement already satisfied: tzdata>=2022.7 in c:\\users\\user\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from pandas) (2024.1)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\user\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "0738a935-a433-4ffc-9005-0290d598babe",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd #imported pandas as we will work on rows and columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "71245785-438e-42b7-acfe-d8d1f4e30a15",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('audible_uncleaned.csv') #importing uploaded dataset, pd.read_csv() for csv file, pd.read_json() for json file, pd.read_excel() for xlsx file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "0523b1c1-e166-44f6-b7af-8d14f27b69ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(87489, 8)"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape #gives info about the number of rows and columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "df183e45-61e6-4b8b-a305-ee78d47a0268",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.info of                                              name                     author  \\\n",
       "0                      Geronimo Stilton #11 & #12  Writtenby:GeronimoStilton   \n",
       "1                                The Burning Maze      Writtenby:RickRiordan   \n",
       "2                                    The Deep End       Writtenby:JeffKinney   \n",
       "3                            Daughter of the Deep      Writtenby:RickRiordan   \n",
       "4      The Lightning Thief: Percy Jackson, Book 1      Writtenby:RickRiordan   \n",
       "...                                           ...                        ...   \n",
       "87484                   Last Days of the Bus Club     Writtenby:ChrisStewart   \n",
       "87485                                    The Alps    Writtenby:StephenO'Shea   \n",
       "87486                        The Innocents Abroad        Writtenby:MarkTwain   \n",
       "87487                       A Sentimental Journey   Writtenby:LaurenceSterne   \n",
       "87488                                      Havana    Writtenby:MarkKurlansky   \n",
       "\n",
       "                        narrator                time releasedate language  \\\n",
       "0          Narratedby:BillLobely   2 hrs and 20 mins    04-08-08  English   \n",
       "1       Narratedby:RobbieDaymond   13 hrs and 8 mins    01-05-18  English   \n",
       "2          Narratedby:DanRussell    2 hrs and 3 mins    06-11-20  English   \n",
       "3      Narratedby:SoneelaNankani  11 hrs and 16 mins    05-10-21  English   \n",
       "4      Narratedby:JesseBernstein              10 hrs    13-01-10  English   \n",
       "...                          ...                 ...         ...      ...   \n",
       "87484    Narratedby:ChrisStewart   7 hrs and 34 mins    09-03-17  English   \n",
       "87485      Narratedby:RobertFass   10 hrs and 7 mins    21-02-17  English   \n",
       "87486       Narratedby:FloGibson   19 hrs and 4 mins    30-12-16  English   \n",
       "87487     Narratedby:AntonLesser    4 hrs and 8 mins    23-02-11  English   \n",
       "87488     Narratedby:FleetCooper     6 hrs and 1 min    07-03-17  English   \n",
       "\n",
       "                               stars   price  \n",
       "0         5 out of 5 stars34 ratings  468.00  \n",
       "1       4.5 out of 5 stars41 ratings  820.00  \n",
       "2       4.5 out of 5 stars38 ratings  410.00  \n",
       "3       4.5 out of 5 stars12 ratings  615.00  \n",
       "4      4.5 out of 5 stars181 ratings  820.00  \n",
       "...                              ...     ...  \n",
       "87484                  Not rated yet  596.00  \n",
       "87485                  Not rated yet  820.00  \n",
       "87486                  Not rated yet  938.00  \n",
       "87487                  Not rated yet  680.00  \n",
       "87488                  Not rated yet  569.00  \n",
       "\n",
       "[87489 rows x 8 columns]>"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.info #gives better information than shape attribute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "60dacd56-37aa-4671-b3ff-28e69e6e0965",
   "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>name</th>\n",
       "      <th>author</th>\n",
       "      <th>narrator</th>\n",
       "      <th>time</th>\n",
       "      <th>releasedate</th>\n",
       "      <th>language</th>\n",
       "      <th>stars</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Geronimo Stilton #11 &amp; #12</td>\n",
       "      <td>Writtenby:GeronimoStilton</td>\n",
       "      <td>Narratedby:BillLobely</td>\n",
       "      <td>2 hrs and 20 mins</td>\n",
       "      <td>04-08-08</td>\n",
       "      <td>English</td>\n",
       "      <td>5 out of 5 stars34 ratings</td>\n",
       "      <td>468.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Burning Maze</td>\n",
       "      <td>Writtenby:RickRiordan</td>\n",
       "      <td>Narratedby:RobbieDaymond</td>\n",
       "      <td>13 hrs and 8 mins</td>\n",
       "      <td>01-05-18</td>\n",
       "      <td>English</td>\n",
       "      <td>4.5 out of 5 stars41 ratings</td>\n",
       "      <td>820.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Deep End</td>\n",
       "      <td>Writtenby:JeffKinney</td>\n",
       "      <td>Narratedby:DanRussell</td>\n",
       "      <td>2 hrs and 3 mins</td>\n",
       "      <td>06-11-20</td>\n",
       "      <td>English</td>\n",
       "      <td>4.5 out of 5 stars38 ratings</td>\n",
       "      <td>410.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Daughter of the Deep</td>\n",
       "      <td>Writtenby:RickRiordan</td>\n",
       "      <td>Narratedby:SoneelaNankani</td>\n",
       "      <td>11 hrs and 16 mins</td>\n",
       "      <td>05-10-21</td>\n",
       "      <td>English</td>\n",
       "      <td>4.5 out of 5 stars12 ratings</td>\n",
       "      <td>615.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Lightning Thief: Percy Jackson, Book 1</td>\n",
       "      <td>Writtenby:RickRiordan</td>\n",
       "      <td>Narratedby:JesseBernstein</td>\n",
       "      <td>10 hrs</td>\n",
       "      <td>13-01-10</td>\n",
       "      <td>English</td>\n",
       "      <td>4.5 out of 5 stars181 ratings</td>\n",
       "      <td>820.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         name                     author  \\\n",
       "0                  Geronimo Stilton #11 & #12  Writtenby:GeronimoStilton   \n",
       "1                            The Burning Maze      Writtenby:RickRiordan   \n",
       "2                                The Deep End       Writtenby:JeffKinney   \n",
       "3                        Daughter of the Deep      Writtenby:RickRiordan   \n",
       "4  The Lightning Thief: Percy Jackson, Book 1      Writtenby:RickRiordan   \n",
       "\n",
       "                    narrator                time releasedate language  \\\n",
       "0      Narratedby:BillLobely   2 hrs and 20 mins    04-08-08  English   \n",
       "1   Narratedby:RobbieDaymond   13 hrs and 8 mins    01-05-18  English   \n",
       "2      Narratedby:DanRussell    2 hrs and 3 mins    06-11-20  English   \n",
       "3  Narratedby:SoneelaNankani  11 hrs and 16 mins    05-10-21  English   \n",
       "4  Narratedby:JesseBernstein              10 hrs    13-01-10  English   \n",
       "\n",
       "                           stars   price  \n",
       "0     5 out of 5 stars34 ratings  468.00  \n",
       "1   4.5 out of 5 stars41 ratings  820.00  \n",
       "2   4.5 out of 5 stars38 ratings  410.00  \n",
       "3   4.5 out of 5 stars12 ratings  615.00  \n",
       "4  4.5 out of 5 stars181 ratings  820.00  "
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()  #by default it shows top 5 entries but the number of entries can be changed by inserting the values in the function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "1026deed-a352-4903-86b1-87e94d2c8cb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>name</th>\n",
       "      <th>author</th>\n",
       "      <th>narrator</th>\n",
       "      <th>time</th>\n",
       "      <th>releasedate</th>\n",
       "      <th>language</th>\n",
       "      <th>stars</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>87479</th>\n",
       "      <td>Dear Bob and Sue</td>\n",
       "      <td>Writtenby:MattSmith,KarenSmith</td>\n",
       "      <td>Narratedby:DavidColacci,SusanEricksen</td>\n",
       "      <td>14 hrs and 48 mins</td>\n",
       "      <td>26-12-17</td>\n",
       "      <td>English</td>\n",
       "      <td>Not rated yet</td>\n",
       "      <td>1,055.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87480</th>\n",
       "      <td>Journey into Cyprus</td>\n",
       "      <td>Writtenby:ColinThubron</td>\n",
       "      <td>Narratedby:JonathanKeeble</td>\n",
       "      <td>11 hrs and 51 mins</td>\n",
       "      <td>01-01-18</td>\n",
       "      <td>English</td>\n",
       "      <td>Not rated yet</td>\n",
       "      <td>785.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87481</th>\n",
       "      <td>The Hills of Adonis</td>\n",
       "      <td>Writtenby:ColinThubron</td>\n",
       "      <td>Narratedby:JonathanKeeble</td>\n",
       "      <td>6 hrs and 52 mins</td>\n",
       "      <td>01-12-17</td>\n",
       "      <td>English</td>\n",
       "      <td>Not rated yet</td>\n",
       "      <td>679.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87482</th>\n",
       "      <td>The Bush</td>\n",
       "      <td>Writtenby:DonWatson,HamishHamilton</td>\n",
       "      <td>Narratedby:DonWatson</td>\n",
       "      <td>13 hrs and 16 mins</td>\n",
       "      <td>13-10-17</td>\n",
       "      <td>English</td>\n",
       "      <td>Not rated yet</td>\n",
       "      <td>1,328.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87483</th>\n",
       "      <td>We Stood upon Stars</td>\n",
       "      <td>Writtenby:RogerW.Thompson</td>\n",
       "      <td>Narratedby:JohnMcLain</td>\n",
       "      <td>5 hrs and 55 mins</td>\n",
       "      <td>02-05-17</td>\n",
       "      <td>English</td>\n",
       "      <td>Not rated yet</td>\n",
       "      <td>351.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87484</th>\n",
       "      <td>Last Days of the Bus Club</td>\n",
       "      <td>Writtenby:ChrisStewart</td>\n",
       "      <td>Narratedby:ChrisStewart</td>\n",
       "      <td>7 hrs and 34 mins</td>\n",
       "      <td>09-03-17</td>\n",
       "      <td>English</td>\n",
       "      <td>Not rated yet</td>\n",
       "      <td>596.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87485</th>\n",
       "      <td>The Alps</td>\n",
       "      <td>Writtenby:StephenO'Shea</td>\n",
       "      <td>Narratedby:RobertFass</td>\n",
       "      <td>10 hrs and 7 mins</td>\n",
       "      <td>21-02-17</td>\n",
       "      <td>English</td>\n",
       "      <td>Not rated yet</td>\n",
       "      <td>820.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87486</th>\n",
       "      <td>The Innocents Abroad</td>\n",
       "      <td>Writtenby:MarkTwain</td>\n",
       "      <td>Narratedby:FloGibson</td>\n",
       "      <td>19 hrs and 4 mins</td>\n",
       "      <td>30-12-16</td>\n",
       "      <td>English</td>\n",
       "      <td>Not rated yet</td>\n",
       "      <td>938.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87487</th>\n",
       "      <td>A Sentimental Journey</td>\n",
       "      <td>Writtenby:LaurenceSterne</td>\n",
       "      <td>Narratedby:AntonLesser</td>\n",
       "      <td>4 hrs and 8 mins</td>\n",
       "      <td>23-02-11</td>\n",
       "      <td>English</td>\n",
       "      <td>Not rated yet</td>\n",
       "      <td>680.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87488</th>\n",
       "      <td>Havana</td>\n",
       "      <td>Writtenby:MarkKurlansky</td>\n",
       "      <td>Narratedby:FleetCooper</td>\n",
       "      <td>6 hrs and 1 min</td>\n",
       "      <td>07-03-17</td>\n",
       "      <td>English</td>\n",
       "      <td>Not rated yet</td>\n",
       "      <td>569.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            name                              author  \\\n",
       "87479           Dear Bob and Sue      Writtenby:MattSmith,KarenSmith   \n",
       "87480        Journey into Cyprus              Writtenby:ColinThubron   \n",
       "87481        The Hills of Adonis              Writtenby:ColinThubron   \n",
       "87482                   The Bush  Writtenby:DonWatson,HamishHamilton   \n",
       "87483        We Stood upon Stars           Writtenby:RogerW.Thompson   \n",
       "87484  Last Days of the Bus Club              Writtenby:ChrisStewart   \n",
       "87485                   The Alps             Writtenby:StephenO'Shea   \n",
       "87486       The Innocents Abroad                 Writtenby:MarkTwain   \n",
       "87487      A Sentimental Journey            Writtenby:LaurenceSterne   \n",
       "87488                     Havana             Writtenby:MarkKurlansky   \n",
       "\n",
       "                                    narrator                time releasedate  \\\n",
       "87479  Narratedby:DavidColacci,SusanEricksen  14 hrs and 48 mins    26-12-17   \n",
       "87480              Narratedby:JonathanKeeble  11 hrs and 51 mins    01-01-18   \n",
       "87481              Narratedby:JonathanKeeble   6 hrs and 52 mins    01-12-17   \n",
       "87482                   Narratedby:DonWatson  13 hrs and 16 mins    13-10-17   \n",
       "87483                  Narratedby:JohnMcLain   5 hrs and 55 mins    02-05-17   \n",
       "87484                Narratedby:ChrisStewart   7 hrs and 34 mins    09-03-17   \n",
       "87485                  Narratedby:RobertFass   10 hrs and 7 mins    21-02-17   \n",
       "87486                   Narratedby:FloGibson   19 hrs and 4 mins    30-12-16   \n",
       "87487                 Narratedby:AntonLesser    4 hrs and 8 mins    23-02-11   \n",
       "87488                 Narratedby:FleetCooper     6 hrs and 1 min    07-03-17   \n",
       "\n",
       "      language          stars     price  \n",
       "87479  English  Not rated yet  1,055.00  \n",
       "87480  English  Not rated yet    785.00  \n",
       "87481  English  Not rated yet    679.00  \n",
       "87482  English  Not rated yet  1,328.00  \n",
       "87483  English  Not rated yet    351.00  \n",
       "87484  English  Not rated yet    596.00  \n",
       "87485  English  Not rated yet    820.00  \n",
       "87486  English  Not rated yet    938.00  \n",
       "87487  English  Not rated yet    680.00  \n",
       "87488  English  Not rated yet    569.00  "
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(10) #complementary to head() function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "c485906d-95b3-4c6f-8219-8a8a2eff0dac",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt #imported this library as we will plot a piechart\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "8ccc28d2-789e-458a-8e6c-9fa983c83748",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Count the occurrences of each rating\n",
    "rating_counts = df['stars'].value_counts()\n",
    "\n",
    "# Count the rated and 'Not rated yet' entries\n",
    "rated_count = rating_counts.drop('Not rated yet', errors='ignore').sum()\n",
    "not_rated_count = rating_counts.get('Not rated yet', 0)\n",
    "\n",
    "# Prepare data for pie chart\n",
    "labels = ['Not rated yet', 'Rated']\n",
    "sizes = [not_rated_count, rated_count]\n",
    "\n",
    "# Plot the pie chart\n",
    "fig, ax = plt.subplots(figsize=(8, 6))\n",
    "wedges, texts, autotexts = ax.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=140, colors=['lightcoral', 'skyblue'])\n",
    "\n",
    "# Add legend\n",
    "ax.legend(wedges, labels, title=\"Ratings\", loc=\"center left\", bbox_to_anchor=(1, 0, 0.5, 1))\n",
    "\n",
    "# Set title and equal aspect ratio\n",
    "ax.set_title('Ratings Distribution')\n",
    "ax.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "# Display the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "8cbd3773-a56c-4524-acae-ae5bf1ab592d",
   "metadata": {},
   "source": [
    "As we can see, lots of books are unrated, so we will remove them for further analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "52e9600f-f223-4276-b5aa-0f425d201d31",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df[df['stars']!='Not rated yet'].reset_index(drop=True)  #to remove entries where no ratings are there"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "edbf0b60-9d48-4d50-8925-975d67ed211f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(15072, 8)"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape #to check the shape after unrated entries are omitted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "b6c15670-d4c8-4143-8423-87f3ab99a849",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['stars'] = df['stars'].str.replace(r\"[a-zA-Z]\", '', regex=True).str.replace('  +', ' ', regex=True)  #Remove letters and extra spaces from 'stars'\n",
    "\n",
    "df[['avgrating', 'maxrating', 'numberofratings']] = df['stars'].str.split(' ', n=2, expand=True)  #Split 'stars' into three columns: 'avgrating', 'maxrating', 'numberofratings'\n",
    "\n",
    "df = df.drop(columns=['maxrating', 'stars'])  #Drop 'maxrating' and 'stars' columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "4762c964-a793-4534-b537-43a08354d95f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>author</th>\n",
       "      <th>narrator</th>\n",
       "      <th>time</th>\n",
       "      <th>releasedate</th>\n",
       "      <th>language</th>\n",
       "      <th>price</th>\n",
       "      <th>avgrating</th>\n",
       "      <th>numberofratings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Geronimo Stilton #11 &amp; #12</td>\n",
       "      <td>Writtenby:GeronimoStilton</td>\n",
       "      <td>Narratedby:BillLobely</td>\n",
       "      <td>2 hrs and 20 mins</td>\n",
       "      <td>04-08-08</td>\n",
       "      <td>English</td>\n",
       "      <td>468.00</td>\n",
       "      <td>5</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Burning Maze</td>\n",
       "      <td>Writtenby:RickRiordan</td>\n",
       "      <td>Narratedby:RobbieDaymond</td>\n",
       "      <td>13 hrs and 8 mins</td>\n",
       "      <td>01-05-18</td>\n",
       "      <td>English</td>\n",
       "      <td>820.00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Deep End</td>\n",
       "      <td>Writtenby:JeffKinney</td>\n",
       "      <td>Narratedby:DanRussell</td>\n",
       "      <td>2 hrs and 3 mins</td>\n",
       "      <td>06-11-20</td>\n",
       "      <td>English</td>\n",
       "      <td>410.00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Daughter of the Deep</td>\n",
       "      <td>Writtenby:RickRiordan</td>\n",
       "      <td>Narratedby:SoneelaNankani</td>\n",
       "      <td>11 hrs and 16 mins</td>\n",
       "      <td>05-10-21</td>\n",
       "      <td>English</td>\n",
       "      <td>615.00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Lightning Thief: Percy Jackson, Book 1</td>\n",
       "      <td>Writtenby:RickRiordan</td>\n",
       "      <td>Narratedby:JesseBernstein</td>\n",
       "      <td>10 hrs</td>\n",
       "      <td>13-01-10</td>\n",
       "      <td>English</td>\n",
       "      <td>820.00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>181</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         name                     author  \\\n",
       "0                  Geronimo Stilton #11 & #12  Writtenby:GeronimoStilton   \n",
       "1                            The Burning Maze      Writtenby:RickRiordan   \n",
       "2                                The Deep End       Writtenby:JeffKinney   \n",
       "3                        Daughter of the Deep      Writtenby:RickRiordan   \n",
       "4  The Lightning Thief: Percy Jackson, Book 1      Writtenby:RickRiordan   \n",
       "\n",
       "                    narrator                time releasedate language   price  \\\n",
       "0      Narratedby:BillLobely   2 hrs and 20 mins    04-08-08  English  468.00   \n",
       "1   Narratedby:RobbieDaymond   13 hrs and 8 mins    01-05-18  English  820.00   \n",
       "2      Narratedby:DanRussell    2 hrs and 3 mins    06-11-20  English  410.00   \n",
       "3  Narratedby:SoneelaNankani  11 hrs and 16 mins    05-10-21  English  615.00   \n",
       "4  Narratedby:JesseBernstein              10 hrs    13-01-10  English  820.00   \n",
       "\n",
       "  avgrating numberofratings  \n",
       "0         5             34   \n",
       "1       4.5             41   \n",
       "2       4.5             38   \n",
       "3       4.5             12   \n",
       "4       4.5            181   "
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head() #to check if the avgrating column data got preprocessed and new column has been formed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "b5fd123b-2a4f-4c94-aeca-5548aa7129b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['author'] = df['author'].str.replace('Writtenby:', '', regex=False)  #removing the string 'Writtenby:' in author column \n",
    "\n",
    "df['narrator'] = df['narrator'].str.replace('Narratedby:', '', regex=False) #removing the string 'Narratedby:' in narrator column\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "7dc94bca-ee7b-447d-a8a1-6d68bd8761da",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15067</th>\n",
       "      <td>Why We Fly</td>\n",
       "      <td>EvanRail</td>\n",
       "      <td>EvanRail</td>\n",
       "      <td>56 mins</td>\n",
       "      <td>23-06-14</td>\n",
       "      <td>English</td>\n",
       "      <td>100.00</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15068</th>\n",
       "      <td>River Town</td>\n",
       "      <td>PeterHessler</td>\n",
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       "      <td>14 hrs and 36 mins</td>\n",
       "      <td>04-05-10</td>\n",
       "      <td>English</td>\n",
       "      <td>836.00</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>15069</th>\n",
       "      <td>Figures in a Landscape</td>\n",
       "      <td>PaulTheroux</td>\n",
       "      <td>EdoardoBallerini</td>\n",
       "      <td>16 hrs and 44 mins</td>\n",
       "      <td>07-06-18</td>\n",
       "      <td>English</td>\n",
       "      <td>949.00</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>15070</th>\n",
       "      <td>Tower of London</td>\n",
       "      <td>iMinds</td>\n",
       "      <td>AbbeyHolmes</td>\n",
       "      <td>8 mins</td>\n",
       "      <td>23-12-09</td>\n",
       "      <td>English</td>\n",
       "      <td>33.00</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>15071</th>\n",
       "      <td>Tigers in the Snow</td>\n",
       "      <td>PeterMatthiessen</td>\n",
       "      <td>GeorgeGuidall</td>\n",
       "      <td>4 hrs and 54 mins</td>\n",
       "      <td>05-08-04</td>\n",
       "      <td>English</td>\n",
       "      <td>702.00</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name            author          narrator  \\\n",
       "15067              Why We Fly          EvanRail          EvanRail   \n",
       "15068              River Town      PeterHessler      PeterBerkrot   \n",
       "15069  Figures in a Landscape       PaulTheroux  EdoardoBallerini   \n",
       "15070         Tower of London            iMinds       AbbeyHolmes   \n",
       "15071      Tigers in the Snow  PeterMatthiessen     GeorgeGuidall   \n",
       "\n",
       "                     time releasedate language   price avgrating  \\\n",
       "15067             56 mins    23-06-14  English  100.00         5   \n",
       "15068  14 hrs and 36 mins    04-05-10  English  836.00         5   \n",
       "15069  16 hrs and 44 mins    07-06-18  English  949.00         4   \n",
       "15070              8 mins    23-12-09  English   33.00         5   \n",
       "15071   4 hrs and 54 mins    05-08-04  English  702.00         5   \n",
       "\n",
       "      numberofratings  \n",
       "15067              1   \n",
       "15068              1   \n",
       "15069              1   \n",
       "15070              1   \n",
       "15071              1   "
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail() #checking if the proper changes in narrator and author column took place"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "378353a5-b3f4-4d8b-91d0-379924c9f5d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns={'name':'Name','author':'Author','narrator':'Narrator','time':'Duration','language':'Language','price':'Price','avgrating':'Average rating','numberofratings':'Number of ratings','releasedate':'Release date'},inplace=True)\n",
    "#renaming every column for proper presentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "814644b5-f97b-4168-b799-4e159f8d7daf",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\user\\AppData\\Local\\Temp\\ipykernel_9564\\4044579650.py:2: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  df['Release date'] = pd.to_datetime(df['Release date'], errors='coerce')\n"
     ]
    }
   ],
   "source": [
    "# Convert the 'Release Date' column to default datetime format\n",
    "df['Release date'] = pd.to_datetime(df['Release date'], errors='coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "73624846-f608-4f25-b43e-391caa7cc24e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Name</th>\n",
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       "      <th>Duration</th>\n",
       "      <th>Release date</th>\n",
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       "      <th>15067</th>\n",
       "      <td>Why We Fly</td>\n",
       "      <td>EvanRail</td>\n",
       "      <td>EvanRail</td>\n",
       "      <td>56 mins</td>\n",
       "      <td>2014-06-23</td>\n",
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       "      <td>100.00</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
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       "      <th>15068</th>\n",
       "      <td>River Town</td>\n",
       "      <td>PeterHessler</td>\n",
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       "      <td>14 hrs and 36 mins</td>\n",
       "      <td>2010-04-05</td>\n",
       "      <td>English</td>\n",
       "      <td>836.00</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15069</th>\n",
       "      <td>Figures in a Landscape</td>\n",
       "      <td>PaulTheroux</td>\n",
       "      <td>EdoardoBallerini</td>\n",
       "      <td>16 hrs and 44 mins</td>\n",
       "      <td>2018-07-06</td>\n",
       "      <td>English</td>\n",
       "      <td>949.00</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>15070</th>\n",
       "      <td>Tower of London</td>\n",
       "      <td>iMinds</td>\n",
       "      <td>AbbeyHolmes</td>\n",
       "      <td>8 mins</td>\n",
       "      <td>2009-12-23</td>\n",
       "      <td>English</td>\n",
       "      <td>33.00</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15071</th>\n",
       "      <td>Tigers in the Snow</td>\n",
       "      <td>PeterMatthiessen</td>\n",
       "      <td>GeorgeGuidall</td>\n",
       "      <td>4 hrs and 54 mins</td>\n",
       "      <td>2004-05-08</td>\n",
       "      <td>English</td>\n",
       "      <td>702.00</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Name            Author          Narrator  \\\n",
       "15067              Why We Fly          EvanRail          EvanRail   \n",
       "15068              River Town      PeterHessler      PeterBerkrot   \n",
       "15069  Figures in a Landscape       PaulTheroux  EdoardoBallerini   \n",
       "15070         Tower of London            iMinds       AbbeyHolmes   \n",
       "15071      Tigers in the Snow  PeterMatthiessen     GeorgeGuidall   \n",
       "\n",
       "                 Duration Release date Language   Price Average rating  \\\n",
       "15067             56 mins   2014-06-23  English  100.00              5   \n",
       "15068  14 hrs and 36 mins   2010-04-05  English  836.00              5   \n",
       "15069  16 hrs and 44 mins   2018-07-06  English  949.00              4   \n",
       "15070              8 mins   2009-12-23  English   33.00              5   \n",
       "15071   4 hrs and 54 mins   2004-05-08  English  702.00              5   \n",
       "\n",
       "      Number of ratings  \n",
       "15067                1   \n",
       "15068                1   \n",
       "15069                1   \n",
       "15070                1   \n",
       "15071                1   "
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail() #checking the changes applied"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "a7f2bd5a-0bcd-4a11-892a-6252af206a91",
   "metadata": {},
   "outputs": [],
   "source": [
    "import re #importing regular expression library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "e6b2e049-fdd5-4773-b72c-e208e151653e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Function to convert Duration to minutes\n",
    "def convert_to_minutes(duration):\n",
    "    hours = 0\n",
    "    minutes = 0\n",
    "    \n",
    "    # Extract hours and minutes\n",
    "    hours_match = re.search(r'(\\d+)\\s*hrs?', duration)\n",
    "    minutes_match = re.search(r'(\\d+)\\s*mins?', duration)\n",
    "    \n",
    "    if hours_match:\n",
    "        hours = int(hours_match.group(1))\n",
    "    if minutes_match:\n",
    "        minutes = int(minutes_match.group(1))\n",
    "    \n",
    "    total_minutes = hours * 60 + minutes\n",
    "    return total_minutes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "af14116f-d119-431e-8944-4cbb856ae995",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Duration'] = df['Duration'].apply(convert_to_minutes) #applying the function to convert the Duration column data into minutes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "2967d6c1-43c9-461c-a0a2-7dc365a4bc36",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Author</th>\n",
       "      <th>Narrator</th>\n",
       "      <th>Duration</th>\n",
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       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Geronimo Stilton #11 &amp; #12</td>\n",
       "      <td>GeronimoStilton</td>\n",
       "      <td>BillLobely</td>\n",
       "      <td>140</td>\n",
       "      <td>2008-04-08</td>\n",
       "      <td>English</td>\n",
       "      <td>468.00</td>\n",
       "      <td>5</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Burning Maze</td>\n",
       "      <td>RickRiordan</td>\n",
       "      <td>RobbieDaymond</td>\n",
       "      <td>788</td>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>English</td>\n",
       "      <td>820.00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Deep End</td>\n",
       "      <td>JeffKinney</td>\n",
       "      <td>DanRussell</td>\n",
       "      <td>123</td>\n",
       "      <td>2020-06-11</td>\n",
       "      <td>English</td>\n",
       "      <td>410.00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Daughter of the Deep</td>\n",
       "      <td>RickRiordan</td>\n",
       "      <td>SoneelaNankani</td>\n",
       "      <td>676</td>\n",
       "      <td>2021-05-10</td>\n",
       "      <td>English</td>\n",
       "      <td>615.00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Lightning Thief: Percy Jackson, Book 1</td>\n",
       "      <td>RickRiordan</td>\n",
       "      <td>JesseBernstein</td>\n",
       "      <td>600</td>\n",
       "      <td>2010-01-13</td>\n",
       "      <td>English</td>\n",
       "      <td>820.00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>181</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Name           Author  \\\n",
       "0                  Geronimo Stilton #11 & #12  GeronimoStilton   \n",
       "1                            The Burning Maze      RickRiordan   \n",
       "2                                The Deep End       JeffKinney   \n",
       "3                        Daughter of the Deep      RickRiordan   \n",
       "4  The Lightning Thief: Percy Jackson, Book 1      RickRiordan   \n",
       "\n",
       "         Narrator  Duration Release date Language   Price Average rating  \\\n",
       "0      BillLobely       140   2008-04-08  English  468.00              5   \n",
       "1   RobbieDaymond       788   2018-01-05  English  820.00            4.5   \n",
       "2      DanRussell       123   2020-06-11  English  410.00            4.5   \n",
       "3  SoneelaNankani       676   2021-05-10  English  615.00            4.5   \n",
       "4  JesseBernstein       600   2010-01-13  English  820.00            4.5   \n",
       "\n",
       "  Number of ratings  \n",
       "0               34   \n",
       "1               41   \n",
       "2               38   \n",
       "3               12   \n",
       "4              181   "
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "689cc9aa-f801-4282-b21b-b754d4f6d6a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns={'Duration':'Duration in minutes'},inplace=True) #renaming the column to remove ambiguity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "fb175748-ad95-4a9b-8dd6-d22753f48b98",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Price'] = pd.to_numeric(df['Price'], errors='coerce') #converting the 'Price' column data into float by coercing if necessary to handle errors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "04277411-8845-436e-894d-f7ff747e05eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Price'] = df['Price'].fillna(0).astype(int) #converting 'Price' column to integers, handling necessary errors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "03c97915-d6e3-4cf9-9c22-e025ff8ddca3",
   "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>Name</th>\n",
       "      <th>Author</th>\n",
       "      <th>Narrator</th>\n",
       "      <th>Duration in minutes</th>\n",
       "      <th>Release date</th>\n",
       "      <th>Language</th>\n",
       "      <th>Price</th>\n",
       "      <th>Average rating</th>\n",
       "      <th>Number of ratings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15067</th>\n",
       "      <td>Why We Fly</td>\n",
       "      <td>EvanRail</td>\n",
       "      <td>EvanRail</td>\n",
       "      <td>56</td>\n",
       "      <td>2014-06-23</td>\n",
       "      <td>English</td>\n",
       "      <td>100</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15068</th>\n",
       "      <td>River Town</td>\n",
       "      <td>PeterHessler</td>\n",
       "      <td>PeterBerkrot</td>\n",
       "      <td>876</td>\n",
       "      <td>2010-04-05</td>\n",
       "      <td>English</td>\n",
       "      <td>836</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15069</th>\n",
       "      <td>Figures in a Landscape</td>\n",
       "      <td>PaulTheroux</td>\n",
       "      <td>EdoardoBallerini</td>\n",
       "      <td>1004</td>\n",
       "      <td>2018-07-06</td>\n",
       "      <td>English</td>\n",
       "      <td>949</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15070</th>\n",
       "      <td>Tower of London</td>\n",
       "      <td>iMinds</td>\n",
       "      <td>AbbeyHolmes</td>\n",
       "      <td>8</td>\n",
       "      <td>2009-12-23</td>\n",
       "      <td>English</td>\n",
       "      <td>33</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15071</th>\n",
       "      <td>Tigers in the Snow</td>\n",
       "      <td>PeterMatthiessen</td>\n",
       "      <td>GeorgeGuidall</td>\n",
       "      <td>294</td>\n",
       "      <td>2004-05-08</td>\n",
       "      <td>English</td>\n",
       "      <td>702</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Name            Author          Narrator  \\\n",
       "15067              Why We Fly          EvanRail          EvanRail   \n",
       "15068              River Town      PeterHessler      PeterBerkrot   \n",
       "15069  Figures in a Landscape       PaulTheroux  EdoardoBallerini   \n",
       "15070         Tower of London            iMinds       AbbeyHolmes   \n",
       "15071      Tigers in the Snow  PeterMatthiessen     GeorgeGuidall   \n",
       "\n",
       "       Duration in minutes Release date Language  Price Average rating  \\\n",
       "15067                   56   2014-06-23  English    100              5   \n",
       "15068                  876   2010-04-05  English    836              5   \n",
       "15069                 1004   2018-07-06  English    949              4   \n",
       "15070                    8   2009-12-23  English     33              5   \n",
       "15071                  294   2004-05-08  English    702              5   \n",
       "\n",
       "      Number of ratings  \n",
       "15067                1   \n",
       "15068                1   \n",
       "15069                1   \n",
       "15070                1   \n",
       "15071                1   "
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail() #checking the dataframe after applying the changes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "b26a12c0-7037-4a6e-81fe-ad587fea4939",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the DataFrame to a CSV file\n",
    "csv_file_path = 'Audible_clean_dataset.csv'\n",
    "df.to_csv(csv_file_path, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "48e77f9f-4f14-4dc4-a489-4a7755fe2af0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<a href='Audible_clean_dataset.csv' target='_blank'>Audible_clean_dataset.csv</a><br>"
      ],
      "text/plain": [
       "C:\\Users\\user\\Audible_clean_dataset.csv"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import FileLink #FileLink is a utility from IPython that creates a clickable link to a file in your Jupyter Notebook. \n",
    "\n",
    "# Display the download link\n",
    "FileLink(csv_file_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfd67fe4-419c-44bf-b757-2e892391764e",
   "metadata": {},
   "source": [
    "**EXPLANATORY DATA ANALYSIS (EDA)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "453e2cd2-ff63-4066-9c93-4c98b98cfadd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np #to deal with statistical parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "76cb64e0-59ef-4fd3-85cf-fb8620e6c058",
   "metadata": {},
   "outputs": [],
   "source": [
    "#function to display statistical measurements for future use\n",
    "def describe_series(series):\n",
    "    description = series.describe()\n",
    "    mode = series.mode()[0]\n",
    "    std_dev = series.std()\n",
    "    var = series.var()\n",
    "    quartiles = series.quantile([0.25, 0.5, 0.75])\n",
    "    iqr = quartiles[0.75] - quartiles[0.25]\n",
    "\n",
    "    summary = {\n",
    "        'Count': description['count'],\n",
    "        'Mean': description['mean'],\n",
    "        'Variance':var,\n",
    "        'Standard Deviation': std_dev,\n",
    "        'Minimum': description['min'],\n",
    "        '25% (Q1)': quartiles[0.25],\n",
    "        '50% (Median)': quartiles[0.5],\n",
    "        '75% (Q3)': quartiles[0.75],\n",
    "        'Maximum': description['max'],\n",
    "        'Mode': mode,\n",
    "        'Inter Quartile Range': iqr\n",
    "    }\n",
    "    return pd.Series(summary)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7fdad1e-47ef-4abe-8073-0d9d60fb71e5",
   "metadata": {},
   "source": [
    "**Finding most frequently appearing Author**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "6f159881-db2d-4aad-afe5-5df0745cf728",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The maximum number of books are written by P.G.Wodehouse\n"
     ]
    }
   ],
   "source": [
    "modes = df['Author'].mode()\n",
    "if len(modes) > 1:\n",
    "    print(f\"There are multiple modes: {', '.join(modes)}\")\n",
    "else:\n",
    "    print(f\"The maximum number of books are written by {modes[0]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fab8196-e06d-4a19-9ade-76a153a05036",
   "metadata": {},
   "source": [
    "**Finding most frequently appearing Narrator**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "fb96be6d-4c87-4664-a0f8-837287d36737",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The maximum number of books are narrated by SeanPratt\n"
     ]
    }
   ],
   "source": [
    "modes = df['Narrator'].mode()\n",
    "\n",
    "if len(modes) > 1:\n",
    "    print(f\"There are multiple modes: {', '.join(modes)}\")\n",
    "else:\n",
    "    print(f\"The maximum number of books are narrated by {modes[0]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f8f6cb7-1acf-42ec-919f-a983ee19e1ff",
   "metadata": {},
   "source": [
    "**Comparing similarity between Author and Narrator column**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "b86bf045-14c0-4f78-b5cd-91dea5a51b86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rWK/XIyUlBTqdDg0bNiz1OYwcOfKuW17GjRtX4rLbb5uTk4MbN26gY8eOEELg8OHD5T6Hin7edu3atVLriuRhGbQh2dnZJsXrTkOHDkWnTp0wevRoBAYGYtiwYVi1alWFimFoaGiFDhSpX7++yc8qlQr16tXDxYsXzV5GZVy6dAkhISEl1kfjxo2N19/u9jJxi7e3d7lfjpcuXUL9+vWNH9TlPY45zP09LV26FC1atICzszN8fX3h7++P3377DRkZGSWWeefzu/UlFhYWVurlt553TEwMAKBHjx7w9/c3+bdp0ybjwRZ3ExUVhUaNGmHlypXGy1auXAk/Pz/06NHDeNm7776LEydOICwsDPfeey9mzJhRbulJTk5GXl5eidcYADRs2LDM+1ZUbGwshBB48803S6yH6dOnA0CJdVGnTh2Tnyu6Lp2dnUvsSmDOa7I8y5cvx7333ouUlBTExsYiNjYWrVq1QmFhoXGToKWV9/5KTk5Gbm5uqb+3xo0bw2Aw4MqVKyaX37l+y1KV98qtYngr6633tKVed56enpg4cSJ+/vnnuxYvg8GABQsWoH79+nBycoKfnx/8/f1x7NixUp/D3daNg4NDqZuyL1++jFGjRsHHxwc6nQ7+/v7o2rUrAJS6/DtV9PO2Ir87sg7cZ9BGXL16FRkZGahXr95db+Pi4oKdO3di+/bt+O2337BhwwasXLkSPXr0wKZNm8z6K7si+/mZ624TY+v1erMyWcLdHkcIUSOPfztzfk/Lly/HqFGjMHDgQLz88ssICAiARqPB3LlzERcXV2KZd3t+5T3vWwV02bJlCAoKKnG720cV72bo0KGYPXs2bty4AXd3d/z8888YPny4yX2HDBmCLl264KeffsKmTZvw3nvv4Z133sGaNWvwwAMPlPsY1e3WepgyZcpdRx3vfO/d+V6p6Lqsjtd+TEwMDhw4AKD0MrNixQo8++yzAMp+X1ZUdby/zP0sstR7pTo/C27tO/jWW29h4cKFJa6fM2cO3nzzTTz99NOYNWsWfHx8oFarMXHixFL/mL/burl9hPEWvV6PXr16ITU1Fa+++ioaNWoENzc3xMfHY9SoUVWeg7I01fE9QtWLZdBG3Nqht7zNY2q1Gvfffz/uv/9+vP/++5gzZw5ef/11bN++HT179rT4GUtujYbcIoRAbGysyU7u3t7epU5We+nSJZNNRhXJFh4eji1btiArK8vkr9UzZ84Yr7eE8PBwHDt2DAaDweRDtqqPU97vafXq1YiMjMSaNWtM1sutUSpLubVpLyAgAD179qzUMoYOHYq33noLP/74IwIDA5GZmYlhw4aVuF1wcDDGjx+P8ePHIykpCa1bt8bs2bPvWgb9/f3h4uJS4jUGAGfPnq1U1ru59Tp0dHSs9HqwxLq8U0XfrytWrICjoyOWLVtWovTs3r0bH374IS5fvmyc9gRAifdmaaPdVf3c8Pf3h6ura6m/tzNnzkCtVpcYxTaXpd8rt97Tlnzd3RodnDFjRomDrYCbz6F79+746quvTC5PT083HrBTWcePH8e5c+ewdOlSjBgxwnj55s2bS9z2br/nmvq8JXm4mdgGbNu2DbNmzUKdOnXw+OOP3/V2qampJS67dSRdQUEBAMDNzQ1AyS+Ayvrmm29M9mNcvXo1EhISTL7g69atiz///BOFhYXGy3799dcSm4Uqku3BBx+EXq/Hxx9/bHL5ggULoFKpLDba9OCDD+L69esmm0GLi4vx0UcfQafTGTe1VIQ5v6dbX+S3j1bs378f+/btq/DjlSU6OhoeHh6YM2cOioqKSlx/a66+sjRu3BjNmzfHypUrsXLlSgQHB+O+++4zXq/X60tsigoICEBISIjx+ZZGo9EgOjoaa9euxeXLl42Xnz59Ghs3bjTn6ZktICAA3bp1wxdffIGEhIQS15uzHiyxLu9062hQc9+vK1asQJcuXTB06FAMHjzY5N/LL78MAPjuu+8AAB4eHvDz88POnTtNlvHpp5+WWG5VPzc0Gg169+6NdevWmexCkpiYiG+//RadO3eGh4dHpZcNWO69EhwcjJYtW2Lp0qUmr9vNmzfj1KlTlVomAEycOBFeXl6YOXNmies0Gk2JkckffvihxH6qlVHa+hFC4IMPPihx27v9nmvq85bk4ciglVm/fj3OnDmD4uJiJCYmYtu2bdi8eTPCw8Px888/lznJ9MyZM7Fz50707dsX4eHhSEpKwqeffopatWqhc+fOAG4WMy8vL3z++edwd3eHm5sb2rVrV+l9PHx8fNC5c2c89dRTSExMxMKFC1GvXj2T6W9Gjx6N1atXo0+fPhgyZAji4uKwfPlykx3OK5qtf//+6N69O15//XVcvHgRUVFR2LRpE9atW4eJEyeWWHZlPfvss/jiiy8watQoHDx4EBEREVi9ejX27NmDhQsXlrkP592Y83vq168f1qxZg4cffhh9+/bFhQsX8Pnnn6NJkybIzs62yHMDbhaCzz77DE8++SRat26NYcOGwd/fH5cvX8Zvv/2GTp06lfgCKM3QoUMxbdo0ODs745lnnjEZRc3KykKtWrUwePBgREVFQafTYcuWLThw4ADmz59f5nLfeustbNiwAV26dMH48eONRbxp06Y4duxYlZ//7T755BN07twZzZs3x5gxYxAZGYnExETs27cPV69exdGjR8u8v6XW5e1cXFzQpEkTrFy5Eg0aNICPjw+aNWuGZs2albjt/v37jVMglSY0NBStW7fGihUr8OqrrwK4+d78v//7P4wePRpt27bFzp07ce7cuRL3bdOmDQDg9ddfx7Bhw+Do6Ij+/fsby4M53n77bWzevBmdO3fG+PHj4eDggC+++AIFBQV49913zV7OnarjvTJ37lz07dsXnTt3xtNPP43U1FTj666yy/T09MSLL75Y6oEk/fr1w8yZM/HUU0+hY8eOOH78OFasWGGy5aSyGjVqhLp162LKlCmIj4+Hh4cHfvzxx1L3Tb31e54wYQKio6Oh0WgwbNiwGvu8JYlkHMJMJd2aTuHWP61WK4KCgkSvXr3EBx98YDKFyS13Ti2zdetWMWDAABESEiK0Wq0ICQkRw4cPF+fOnTO537p164yTgaKUSadLc7epZb777jsxdepUERAQIFxcXETfvn1Npiq4Zf78+SI0NFQ4OTmJTp06ib///rvEMsvKVtpkr1lZWWLSpEkiJCREODo6ivr165c5Ceqd7jblzZ0SExPFU089Jfz8/IRWqxXNmzcvdToOc6eWMef3ZDAYxJw5c0R4eLhwcnISrVq1Er/++muJ9VDR6VPuNoXR9u3bRXR0tPD09BTOzs6ibt26YtSoUSVOpXU3MTExxtfu7t27Ta4rKCgQL7/8soiKijJONhwVFSU+/fRTs5b9xx9/iDZt2gitVmv2pNNCVHzdCCFEXFycGDFihAgKChKOjo4iNDRU9OvXT6xevdp4m/KmgTJnXd6aIPhOpT2vvXv3Gp8/yphm5oUXXhAATKZuudOMGTMEAOOpLXNzc8UzzzwjPD09hbu7uxgyZIhISkoq9XFmzZolQkNDhVqtLnXS6TuV9v46dOiQiI6OFjqdTri6uoru3buLvXv3mtzGnGm2blfV98qt53Dn8/3xxx9F48aNhZOTk2jSpEmlJp2+U1pamvD09Cx1apnJkyeL4OBg4eLiIjp16iT27dt318/d0l67d3tNCXFzOqaePXsKnU4n/Pz8xJgxY4zT/9z+WVZcXCxeeOEF4e/vL1Qqlclrsaqft2TdVEJI2IOeiIiIiKwC9xkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWQSIiIiIFYxkkIiIiUjCWwRp28eJFqFQqHDlyRHaUKlmyZAm8vLxkxyAiIqIqqrEymJycjHHjxqF27dpwcnJCUFAQoqOjsWfPnpqKUONGjRqFgQMHyo5Bt4mIiMDChQtlxyAiIrIaDjX1QIMGDUJhYSGWLl2KyMhIJCYmYuvWrUhJSampCHatsLAQWq1WdoxqV9rzFEJAr9fDwaHGXs6KWd9ERGT/amRkMD09Hbt27cI777yD7t27Izw8HPfeey+mTp2Khx56yHi7999/H82bN4ebmxvCwsIwfvx4ZGdnG6+/tWny119/RcOGDeHq6orBgwcjNzcXS5cuRUREBLy9vTFhwgTo9Xrj/QoKCjBlyhSEhobCzc0N7dq1w44dO8rMXF6WGTNmoGXLlib3WbhwISIiIozXL126FOvWrYNKpYJKpTJ5zPPnz6N79+5wdXVFVFQU9u3bZ7KsH3/8EU2bNoWTkxMiIiIwf/58k+sjIiIwa9YsjBgxAh4eHnj22WdLfR4bNmxA586d4eXlBV9fX/Tr1w9xcXHG629ttl6zZk2ZeZYsWYLatWvD1dUVDz/8cLkl3pzlpqSkYPjw4QgNDYWrqyuaN2+O7777zmQ53bp1w/PPP4+JEyfCz88P0dHR2LFjB1QqFdavX482bdrAyckJu3fvRlxcHAYMGIDAwEDodDrcc8892LJli8myLl26hEmTJhl/J5Ze30RERDZH1ICioiKh0+nExIkTRX5+/l1vt2DBArFt2zZx4cIFsXXrVtGwYUMxbtw44/WLFy8Wjo6OolevXuLQoUPijz/+EL6+vqJ3795iyJAh4uTJk+KXX34RWq1WfP/998b7jR49WnTs2FHs3LlTxMbGivfee084OTmJc+fOVTrL9OnTRVRUVIn7hIeHCyGEyMrKEkOGDBF9+vQRCQkJIiEhQRQUFIgLFy4IAKJRo0bi119/FWfPnhWDBw8W4eHhoqioSAghxN9//y3UarWYOXOmOHv2rFi8eLFwcXERixcvNj5WeHi48PDwEPPmzROxsbEiNja21OexevVq8eOPP4qYmBhx+PBh0b9/f9G8eXOh1+uFEMKsPH/++adQq9XinXfeEWfPnhUffPCB8PLyEp6ennddf+Ys9+rVq+K9994Thw8fFnFxceLDDz8UGo1G7N+/37icrl27Cp1OJ15++WVx5swZcebMGbF9+3YBQLRo0UJs2rRJxMbGipSUFHHkyBHx+eefi+PHj4tz586JN954Qzg7O4tLly4JIYRISUkRtWrVEjNnzjT+Tiy9vomIiGxNjZRBIW6WEm9vb+Hs7Cw6duwopk6dKo4ePVrmfX744Qfh6+tr/Hnx4sUCgMkX8dixY4Wrq6vIysoyXhYdHS3Gjh0rhBDi0qVLQqPRiPj4eJNl33///WLq1Klm578zS3llUAghRo4cKQYMGGBym1sl6X//+5/xspMnTwoA4vTp00IIIR577DHRq1cvk/u9/PLLokmTJsafw8PDxcCBA83Of0tycrIAII4fP252nuHDh4sHH3zQZDlDhw41qwyWtdzS9O3bV0yePNn4c9euXUWrVq1MbnOrDK5du7bc59u0aVPx0UcfGX8ODw8XCxYsMLlNda5vIiIia1djB5AMGjQI165dw88//4w+ffpgx44daN26NZYsWWK8zZYtW3D//fcjNDQU7u7uePLJJ5GSkoLc3FzjbVxdXVG3bl3jz4GBgYiIiIBOpzO5LCkpCQBw/Phx6PV6NGjQADqdzvjvjz/+MNlceidzslRFixYtjP8fHBwMAMbMp0+fRqdOnUxu36lTJ8TExJhs/m7btm25jxMTE4Phw4cjMjISHh4exs3Yly9frlCedu3amdy+Q4cO5T52ecvV6/WYNWsWmjdvDh8fH+h0OmzcuLFEtjZt2pS67Duff3Z2NqZMmYLGjRvDy8sLOp0Op0+fLrG8O1lyfRMREdmamtvjHoCzszN69eqFXr164c0338To0aMxffp0jBo1ChcvXkS/fv0wbtw4zJ49Gz4+Pti9ezeeeeYZFBYWwtXVFQDg6OhoskyVSlXqZQaDAcDNgqDRaHDw4EFoNBqT291eIG9nTha1Wg0hhMn9ioqKzF4Xt2e+te/arczmcnNzK/c2/fv3R3h4OBYtWoSQkBAYDAY0a9YMhYWFFs9TmrKW+9577+GDDz7AwoULjftnTpw4sUS2uz3POy+fMmUKNm/ejHnz5qFevXpwcXHB4MGDSyyvssxZ31TDiguAoryb/y3O/+e/d/xscn0+IASgVgNqh3//qTQocnDBNtEWTg5qODlo4OSohpODGm5aB3i6OMLDxREatar8TERENqZGy+CdmjRpgrVr1wIADh48CIPBgPnz50OtvjlguWrVqio/RqtWraDX65GUlIQuXbqYdR9zsvj7++P69esQQhhLzp1zB2q1WpORJXM1bty4xJQ7e/bsQYMGDUoU2rKkpKTg7NmzWLRokfG57969u1J59u/fb3LZn3/+WeHl3GnPnj0YMGAAnnjiCQA3S+K5c+fQpEmTSi9v1KhRePjhhwHc/EPg4sWLJrcp7XdiqfVNFlCYC+QkAdnJN/+bk1zK///zc146AFHeEs2mdgvE2JQFd71epQJ0Wgd4uDjC885/rjf/G+jhjGBPZwR53vyvq1bqRywRkVlq5JMqJSUFjz76KJ5++mm0aNEC7u7u+Pvvv/Huu+9iwIABAIB69eqhqKgIH330Efr37489e/bg888/r/JjN2jQAI8//jhGjBiB+fPno1WrVkhOTsbWrVvRokUL9O3bt8R9zMnSrVs3JCcn491338XgwYOxYcMGrF+/Hh4eHsbbREREYOPGjTh79ix8fX3h6elpVubJkyfjnnvuwaxZszB06FDs27cPH3/8MT799NMKPXdvb2/4+vriyy+/RHBwMC5fvozXXnutQssAgAkTJqBTp06YN28eBgwYgI0bN2LDhg0VXs6d6tevj9WrV2Pv3r3w9vbG+++/j8TExEqXwfr162PNmjXo378/VCoV3nzzzRKjmxEREdi5cyeGDRsGJycn+Pn5WWx9kxnyM4HUOCDln3+pcUDaRSDrOpBzAyjKkRZNqB3Lvl4AWQXFyCooRnx6nlnL9HB2QJCnM4I8XRDscbMkhng5o7aPG+r6uyHAw9kS0YmIqqRGyqBOp0O7du2wYMECxMXFoaioCGFhYRgzZgz++9//AgCioqLw/vvv45133sHUqVNx3333Ye7cuRgxYkSVH3/x4sV4++23MXnyZMTHx8PPzw/t27dHv379Sr29OVkaN26MTz/9FHPmzMGsWbMwaNAgTJkyBV9++aXxNmPGjMGOHTvQtm1bZGdnY/v27cZ99srSunVrrFq1CtOmTcOsWbMQHByMmTNnYtSoURV63mq1Gt9//z0mTJiAZs2aoWHDhvjwww/RrVu3Ci2nffv2WLRoEaZPn45p06ahZ8+eeOONNzBr1qwKLedOb7zxBs6fP4/o6Gi4urri2WefxcCBA5GRkVGp5b3//vt4+umn0bFjR/j5+eHVV19FZmamyW1mzpyJsWPHom7duigoKIAQwmLrm/5RmAOknv+n8MX++/+pcTdH9ayUoZwyWBmZ+cXIzM/GucTsUq93d3JAhJ8bIv3dEOmnQ6S/G+r88zNHFYmopqjEnTu+ERGZK+0ScO3wzX8JR4Dks0BWguxUlVLg3RANE6bLjgHg5ibpIA9nNAh0R9MQDzQL9USzEE/U9nWVHY2I7BD/9CQi82TE/1v8bpW/XPs5g1B1jAxWlhBAQkY+EjLy8ce5f0dTPV0c0STYA81CbxbEpiGeiPRzg5oHthBRFbAMElFJ2UlA/CHT4pedKDtVtTKorf/jMCOvCPvOp2Df+X9LuKtWg+ahnrgnwgf31vFBm3BvuDlZ/3MhIuvBzcREBOSlARd2ARf+AM7/AaTEyE5U4zID70WLSxNlx6gyjVqFJsEe/5RDb9wT4QNfnZPsWERkxVgGiZSoMBe4vPdm8bvwB3D9OCCqPq+kLUsL6oRWF/8jO0a1qOvvhnvr+KB9pC+61PeHj5tWdiQisiIsg0RKoC8G4v/+t/xdPQDoLTMZt724EdwVbS+MlR2j2qlVQPNaXujawB/dGvqjZS0v7nNIpHAsg0T2KjMBOPMrELMJuLQXKCx9ehO6KTGkJ9qdf1p2jBrn7eqIzvX90a2BP+5r4A9/d25SJlIalkEie5J2ETj9C3Dq55ujfxY8Q4e9iw/tg05xVZ/X1JapVEDTEA/c3ygQDzQPQqMgj/LvREQ2j2WQyNYlnwNOr7tZAK8fk53GZl2u1R/3xQ6XHcOqRPq74cFmwXigeRCahph3BiUisj0sg0S2KOHozfJ3+hfgxlnZaezC+bBH0CNmsOwYVquOnxv6NAtC3+bBaBbKYkhkT1gGiWzFtcPA8dU39wNMuyg7jd05GzYE0TEDZcewCbV9XPFAsyD0jwphMSSyAyyDRNYsNxU4thI4vBxIPCE7jV07EfYY+sWUfr5yurtGQe54pHUoBrYKRYC7s+w4RFQJLINE1sZgAM5vu1kAz/wO6AtkJ1KEI2EjMDCmj+wYNkujVqFLfT8MblMLvZsEQeuglh2JiMzEcxYRWYu0S8CRFcCRb4GMK7LTKE4RPw6rRG8Q2HE2GTvOJsPb1REDWoZi6D1haBzMI5KJrB1HBolkKi64eRDIoW+ACzvBqWDk2Rv2LB6L6SY7ht1pUcsTT7QLx0MtQ+DsqJEdh4hKwTJIJEPSaeDvr4Fjq4D8dNlpCMCOsPEYFdNZdgy75e3qiGH31sYT7cMR6uUiOw4R3YZlkKimCAHEbAb+/BQ4v112GrrDploT8Gxse9kx7J5GrUKvxoEY2TECHer6yo5DROA+g0TVrzAXOPodsP9z4MY52WnoLgoEPw5rgt4gsOHkdWw4eR2NgtwxokMEHm4VChctNyETycKRQaLqkp10swD+/TWQlyY7DZXjx9CXMTmulewYiuTp4ohh94bhmc51OD0NkQT8U5jI0lLigL0fAke+47QwNoQjg/Jk5BXhiz/OY8meixjcphae61oXYT6usmMRKQY//YgsJf4gsHvhzTOECIPsNFRBhSyD0hUUG7Bi/2WsPHAFD0WFYHz3uqgX4C47FpHd46cfUVVd2gtsnwNc3CU7CVVBgYH7rFmLYoPAmsPx+OlIPHo3CcR/utdDi1pesmMR2S2WQaLKunYE2DYLiN0iOwlZQD5HBq2OEMDGk4nYeDIRXer74T/d66F9JI9AJrI0fvoRVVTSGWD77JuTRXOSaLuRL3j6NGu2K+YGdsXcQOd6fnilT0OOFBJZEMsgkbnSLgLb5wLHV3GfQDuUr+dmYluwO/YGdn98Aw80C8KU6Iao66+THYnI5rEMEpUnMwHY+S5waBlgKJKdhqpJvmAZtCXrT1zHplOJGNQ6FBN7NkAIz2pCVGksg0R3k5sK7JoPHPgKKM6TnYaqWb6BH4e2Rm8QWPX3Vaw9cg1Ptg/Hf7rXg4+bVnYsIpvDSaeJ7lSQDez9CNj3CVCYJTsN1ZBx7h9ifbKf7BhUBTonB4zpEoln74vkGU2IKoBlkOh2x34ANr8JZCXITkI1bKTrJ/gj1Vt2DLKAYE9nvPZAIwxoGSo7CpFNYBkkAoDEk8DvLwOX9shOQpIMcf4cf6V7yI5BFnRvhA+mP9QETUM8ZUchsmosg6Rs+Rk3J4w+8D/AUCw7DUnUz/FLnMjikan2Rq0Cht1bGy/3bghv7k9IVCqWQVImIYAjK4AtM4CcZNlpyAr0UH+F87k8ItVeebo44qVeDfBE+3Bo1CrZcYisCssgKc+1wzc3CV89IDsJWZEOYgkSCjhyZO8aBbljWv8m6FiXBwsR3cIySMqRmwpsnQkcWspJo6mEFsXfILOY08soxSOtQzGtXxN4ufIPACKWQbJ/QgAHFwNbZwF5qbLTkJWqV7AcxTwlnaL46bSY1r8pHooKkR2FSCqWQbJvaReBtf8BLu2WnYSsmFBpUCdvmewYJMn9jQLw9sPNEOzJfUZJmVgGyT4JcfMI4c3TgaIc2WnIygkHF9TJ/kp2DJJI5+SAV/s0xBPtw6FS8QATUhaWQbI/6ZeBdc8DF/6QnYRshHDyQJ2Mz2XHICvQNtwb/zeoBeoFcJohUg7uIEP25eAS4NOOLIJUIULNgwjopr8vpeHBD3fh420x0Bs4VkLKwJFBsg+Z14CfXwBit8hOQjZIrwtG3RvzZccgK9Mm3BsLhrREbV9X2VGIqhVHBsn2HfkW+LQ9iyBVmlA7yo5AVujgP6OEq/6+IjsKUbViGSTblZUIfDsMWDvu5mnliCrJwDJId5FdUIxXVh/DuOUHkZ5bKDsOUbVgGSTbdHIt8Gk74Nx62UnIDhi4zyCVY/2J64heuBO7Ynj6SrI/LINkW4oLgd+mAD+MBPLSZKchO8GRQTJHYmYBRnz9F9765STyi/Sy4xBZDMsg2Y60S8DXvYEDi2QnITvDMkjmEgJYvOciBny8BzGJWbLjEFkEyyDZhjO/A1/cB1w7LDsJ2SG9iuckpoo5m5iFAZ/swdrD8bKjEFUZyyBZN30xsPF14PvhQH667DRkp/QqjgxSxeUW6jFx5RG8sfY4CosNsuMQVRrLIFmvjHhgyYPAvo9lJyE7xzJIVbH8z8t49PO9uJqWKzsKUaWwDJJ1it0CfNEFuLJfdhJSAD33GaQqOno1A/0+2o3tZ5NkRyGqMJZBsi4GPbB1FrB8MJCbIjsNKUQxRwbJAtJzi/D0kgOYv+ksDDyVHdkQlkGyHtlJwDcDgF3zAPCDlGpOMXgACVmGEMBH22Lx5Nf7kZJdIDsOkVlYBsk6XD8BLOoBXNwlOwkpUDGPJiYL2xObgoc+3oPTCZmyoxCVi2WQ5Du3Cfi6D5DB83+SHBwZpOoQn56HQZ/txcaT12VHISoTyyDJtf8L4LthQCEnbyV5ilgGqZrkFurx3PKD+GhrjOwoRHfFMkhyGPTA7y8D618BBE/rRHKxDFJ1EgKYv/kcJnx3GAXF/Lwj68MySDWvIAv4dijw15eykxABAIqglR2BFODno9fw2CIeWELWh2WQalb6FeCraCB2s+wkREaF0MiOQApx8FIaBn66B7FJ3DWGrAfLINWcqwdvHjGcdFJ2EiIThdxMTDXoSmoeHv50L/bG3pAdhQgAyyDVlJM/AUv6AjmcnZ+sT6HgyCDVrKz8YoxacgC/H0+QHYWIZZBqwK75wA9PAcV5spMQlapQcGSQal5hsQHPf3sIy/+8JDsKKRzLIFWvja8DW2eCZxQha8aRQZLFIIA31p7Awi3nZEchBWMZpOphMAC/vAjs+1h2EqJyFYDnJia5Fm6JwbR1J3hOY5KCZZAsT18M/DQWOLhEdhIisxQYODJI8n2z7xJe+P4wCosNsqOQwrAMkmUVFwI/jASOr5KdhMhs+dxMTFbit2MJeHrJAeQUFMuOQgrCMkiWU5R389RyZ36VnYSoQgpYBsmK7I69geGL/kR6bqHsKKQQLINkGQVZwPJBQNxW2UmIKiyfm4nJyhy7moHHFu1HWg4LIVU/lkGqutxUYOlDwKU9spMQVUqBgVPLkPU5lZCJ4Yv+RCoLIVUzlkGqmuwkYEk/4Noh2UmIKi2PI4Nkpc5cz8Jji/7k+YypWrEMUuVlXAW+7sPTy5HNYxkka3azEO5nIaRqwzJIlZNxFVj8AJAaJzsJUZXl6VkGybqdTczC8EV/4gYLIVUDlkGquOxk4JuBQPpl2UmILCLPwI9Csn7nErMx/Ms/kZzFQkiWxU9Aqpi8dGD5w0BKjOwkRBbDzcRkK2KSsjF8EQshWRbLIJmvMBf4dghw/bjsJEQWlcvNxGRDYpOy8eRX+5GRVyQ7CtkJlkEyT3EhsPJx4Mp+2UmILC5Pz49Csi1nrmfhmSUHkFeolx2F7AA/Aal8Bj3w49NA3DbZSYiqBUcGyRb9fSkN41YcRJGe5zKmqmEZpLIJAax7Hjj9i+wkRNUmhyODZKN2nE3GS6uOwmAQsqOQDeMnIJVt/avA0W9lpyCqVhwZJFv2y9FrmPbzCdkxyIaxDNLdbXsb+OsL2SmIqpVQO8qOQFRly/+8jPmbzsqOQTaKZZBKt/cjYOd7slMQVT+NVnYCIov4aFssvtp9QXYMskEsg1TS4RXApjdkpyCqEULDkUGyH2//dgprD8fLjkE2hmWQTF3YCfzyouwURDWGm4nJnggBvPLjMRy4mCo7CtkQlkH6140YYOWTgIETmZJyCG4mJjtTWGzA2GUHcSklR3YUshEsg3RTTgqwYjCQny47CVGNEmqWQbI/qTmFeGrJAZ6lhMzCMkhAcQHw/WNA2kXZSYhqnIGbiclOnU/OwbjlnJSayscySEjbOBe48qfsGERSsAySPdsbl4I3fuIchFQ2lkGF+2hrDLr92QrXQvvIjkIkhUHlIDsCUbVa+fcVfLYjTnYMsmIsgwq24cR1vL/lHDKKHNDp/JPYHzZadiSiGseRQVKCdzeewfrjCbJjkJViGVSoU9cy8dKqIxD/nM5SCBWGxvTAkuA3IRyc5YYjqkF6HkBCCiAEMGnVEZy8liE7ClkhlkEFSskuwJhv/kZuob7EdTMuNMZr7nNgcPWXkIyo5ulVHBkkZcgvMmDc8kM8wphKYBlUGINB4MXvjyA+Pe+ut1mZEITB+tnI92lcg8mI5CjmPoOkIJdTczFp5RGIW5uFiMAyqDgLtpzD7tgb5d7uUIYOXW68huSQHjWQikgejgyS0mw7k4QPt8bKjkFWhGVQQbafScLH283/AEgudET7C0/jSNiIakxFJBdHBkmJPth6DjvOJsmOQVaCZVAhrqblYtJtB4yYSy/UGBjTB6tCX+U5XMku6cEySMpjEMDElUdwJTVXdhSyAiyDClBQrMf4FYeQnlv5nYZfiYvCDK85MLj4WDAZkXxF3ExMCpWeW4RxKw4iv6jkwYSkLCyDCjDzl1M4drXq0wksvRaKxzEbhd71LZCKyDoUc2SQFOxEfCbeXMszlCgdy6Cd++nwVazYf9liy9uX5omuaa8jNaizxZZJJFMRyyAp3A8Hr2LlAct9T5DtYRm0Y2evZ+G/ayz/F19CvhbtLo/DmbChFl82UU1jGSQC3vrlFM4nZ8uOQZKwDNqp/CI9Jnx3GHnVtC9IkUGFPjED8EvoSxBqfpmS7SoE9xkkyi3UY8L3h1FYbJAdhSRgGbRT72w4g7OJWdX+OC/EtcW7vrMgnDyr/bGIqkMRNLIjEFmFE/GZmL/prOwYJAHLoB3aeS4ZS/ZerLHH++xKOJ7SzEGRZ50ae0wiSykUHNkmuuXLXeexx4wTE5B9YRm0M2k5hZjyw9EKzydYVTtSvXF/5pvIDGxXsw9MVEWF3GeQyEgI4KVVR5CWUyg7CtUglkE789qaY0jKKpDy2JfznNHu6vM4H/aIlMcnqowCjgwSmUjMLMCrPx6THYNqEMugHVl14Ao2nkyUmiFPr0GPmMHYEvYChIovL7J+3ExMVNKmU4n41oLTkpF147e1nbiUkoO3fjkpO4bR6JgO+DjgLQitm+wodmfnpWL0/y4XIfOzoHorE2vP3P3MMs/9mgfVW5lY+GfZo8WfHShEi8+y4TE3Ex5zM9HhqxysjzFd7ksb8+HzTibCFmRhxTHT6344WYT+39nmaa0KBA8gISrNrF9PITaJ080oAcugHdAbBCauPIKcQus6pdD8S3Ux3mkuit1DZUexKzmFAlGBanzyoHOZt/vpdBH+vKpHiLuq3GXW8lDh/3o64eCzbvj7WTf0iNBgwPd5OJl08zX1y9kifHu8CJuedMO7PZ0x+pc83Mi9OQVFRr7A69sKys1jrVgGiUqXV6THlB+OwmCo4Z3QqcaxDNqBz3bE4vDldNkxSrU+2Q8P5s5Etn9r2VHsxgP1HfF2D2c83Pju8+PFZxrwwvp8rHjEBY5mvMv7N3TEg/UdUd9Xgwa+Gsy+3xk6LfDn1Ztl8PQNA7pFaNA2RIPhzR3h4aTChbSbXxCvbM7HuLaOqO1pmx8nBQaWQaK7OXIlHV/vuSA7BlUz2/z0JqPYpGx8uC1WdowynctxQbuESbhSq6/sKIpgEAJP/pSHlztq0TSg4kVHbxD4/kQRcoqADmE37x8VqMHf1/RIyxM4eE2PvCKBej5q7L5cjEPX9ZjQTmvpp1Fj8rnPIFGZ5m06i0spObJjUDViGbRhQgi89uMxm5gxPqdYgy6xj2N32FgIlL/Zkirvnd2FcFCjwgXteKIeujmZcHo7C8/9moefhrqgif/NMhhdzwFPtHDEPYuyMWpdHpYOdIGbFhj3Wz4+7+uCz/4uQsOPs9Hp6xzjpmVbkceRQaIy5RcZ8OqPxyBqes4yqjEsgzZs2Z+X8PelNNkxKuSJmK74KmgahIOL7Ch26eA1PT7YX4glA12gUlWsdDf0U+PIczrsH+2GcW21GLk2H6eS/y12M7o5I3aCO46P0+Hhxo6Yu6sQPes4wFEDvL2zALufcsXoVo4YsTbP0k+rWuWzDBKV68/zqVjBo4vtFsugjbqWnod3N9jmaYPevtgQk93mQu8WJDuK3dl1uRhJOQK1F2TDYWYmHGZm4lKGwORNBYhYWPbpCbUaFer5qNEmRIO5PZ0RFajGB3+WPvHsmRt6LD9ehFk9nLDjYjHuC9fA302NIU0dcSjBgKwC2xlBYBkkMs//rT+Da+m29ccemYc7y9ioN9aeQHZBsewYlbYmMQAx7rOwyu8DuNw4ITuO3XiyhSN6Rpq+raOX5+LJFo54quXdDzgpjUEABaVs8RVCYOyv+Xi/txN0WhX0BqDonz0Vbv1XbztdkJuJicyUXVCMqWuOY+nT98qOQhbGkUEbtO5IPLadSZIdo8qOZ7mhY+IruB7aW3YUm5JdKHDkuh5Hrt9sahfSDDhyXY/LGQb4uqrRLEBj8s9RDQTpVGjo92/puf+bHHz817+jflO35GPnpWJcTDfgeKIeU7fkY8dFPR5vXrJA/u9QEfxdVejf8OZ1nWo7YNuFYvx5tRgL9hWgib8aXs62s19ovp4fg0Tm+uNcMn48eFV2DLIwjgzamLScQsz85ZTsGBaTVuSADudH4od6oWh7ZbHsODbh72t6dF/67wTPL20qAFCAkVGOWDLQvH0x41INxnkCASApR2DET3lIyBbwdFKhRaAaG59wRa+6ph8RidkGzN5VgL3P/DuZ+L2hGkzu4IS+3+YhwE2FpWZmsBYcGSSqmJm/nkLXhv7w0znJjkIWohI8PMimvLTyCNYcjpcdo1q8HXkSjyfOg0ov59zKpEwPab/EsUyd7BhENuWR1qF4f0hL2THIQrh9xIbsi0ux2yIIAG+cb4rXPebA4OonOwopSG4xRwaJKmrNoXj8dSFVdgyyEJZBG6E3CKs693B1+TYhGIP1s1Hg01B2FFKIXAM/BokqY9q6EyjWW/88t1Q+fgraiOV/XsKZ62VPDWIvDmW4o0vKf3EjpJvsKKQAuTyAhKhSzlzPwpK9F2XHIAvgp6ANSMspxPubz8mOUaOSChzR7sJoHA97XHYUsnO5em4mJqqshVtikJSVLzsGVRHLoA14b9NZZOQVyY5R4/RCjf4xfbEm9GUIdcXmyCMyh1CpUcjNxESVll1QjHfW2+YJEOhf/BS0cievZeD7v5R9CqCX4lrhbe+3YXD2lh2F7I2mYudvJqKS1hy+isOXbevUqGSKZdDKzfj5JAyc/AdfxYdhhHoOCr3qyo5C9kTDEWeiqhLi5ncVZ6qzXSyDVmzdkXgcuMi/tm7ZneqJ7ulvIC2ok+woZCeEmiODRJZw9GoGVvPMJDaLZdBK5RYWY+7vZ2THsDrx+U5of3kczoYNkR2F7AD3RSWynAWbzyG/qJQTmpPVYxm0Uot2XsD1TB6hVZoCgxrRMQPxe61JECoeCUqVJ7iZmMhirmXkYymnmrFJLINWKDWnEP/bdV52DKs3PvYezPebBeHkLjsK2SgDRwaJLOrTHXGKnP3C1rEMWqFPtsciq6BYdgyb8PGVCIx2mIsij3DZUcgGsQwSWVZGXhE+3RErOwZVEMuglbmWnodlf16SHcOmbE3xQXT2dGQG3CM7CtkYAw8gIbK4JXsuIiEjT3YMqgCWQSuzcMs5FBbzXI8VdT7XGR3iX8SFWgNlRyEbYlBxZJDI0gqKDXh/k7LOmmXrWAatSGxSNn48FC87hs3K0avRPXYItoX9B0LFlzaVT8/NxETVYs3heJxLzJIdg8zEb0wrMm/jWeg5w3SVPR3TCZ8EzIBwdJMdhaycQeUgOwKRXdIbBN7dwOnRbAXLoJU4eiUdG05elx3Dbsy7VA8vOM9FsXuo7ChkxfTcTExUbbacTsLfF1NlxyAzsAxaiXf4F5TF/Zrsh355byHHv6XsKGSlilkGiarVB1tjZEcgM7AMWoH951OwNy5Fdgy7dCbbFe0TXsLVWg/KjkJWqJj7DBJVq10xN3DkSrrsGFQOlkEr8PF2zslUnbKKHdA59gnsC3sWAirZcciKFIP7DBJVt484Omj1WAYlO3Y1HbtibsiOoQjDY7phcfAbEA4usqOQleBmYqLqt/VMEk5ey5Adg8rAMijZJxwVrFEzLzTGy7o50LsFyI5CVoAjg0Q1g9911o1lUKKYxCxsOpUoO4birL4eiIeL3kaeb1PZUUiyIpZBohqx/sR1xHDeQavFMijRpzviIDitoBTHMnXonPwKEkN6yo5CEnFkkKhmCMHRQWvGMijJldRc/HL0muwYipZS6Ij2F57CobBRsqOQJBwZJKo5vxxLwMUbObJjUClYBiX5/I84FPNsI9IJocIjMb3xXchUCI1WdhyqYYUsg0Q1Rm8Q+HQHRwetEcugBEmZ+fjh4FXZMeg2U883xzTP2TC4+MqOQjWIZZCoZq09fA1JWfmyY9AdWAYl+Gr3BRQWG2THoDssuxaKYWI2CrwbyI5CNaRQsAwS1aRCvQHL912SHYPuwDJYw/IK9fj+wBXZMegu/kr3QNfU/yIl+D7ZUagGFEIjOwKR4nz712UUFOtlx6DbsAzWsJ8OxyMjr0h2DCrD9QIt2l8ai5Nhj8mOQtWs0MCRQaKadiO7EOuO8ABKa8IyWMOW7r0oOwKZocigQt+YflhbawqEmoXBXhUKjgwSybB4z0XZEeg2LIM1aG/cDZzlpJs2ZWJsa8z1eRsGZy/ZUaga5PMAEiIpTidkYl9ciuwY9A+WwRrEUUHb9OXV2hilnoMiz0jZUcjC8rmZmEiaxXsuyI5A/2AZrCHx6XnYcjpJdgyqpJ2pXrg/8w1kBLaXHYUsqMDAzcREsmw5nYgrqbmyYxBYBmvMN/suQs9Jpm3a5TxntL/6H8SGDZIdhSykgPsMEkljEMASbjGzCiyDNSC/SI+VnE7GLuTpNegZMwgba70IoeLbx9blcWSQSKpVB64gr5DTzMjGb7MasO5IPNJzOZ2MPRkb2w4L/WdCaHWyo1AVcGSQSK6sgmL8djxBdgzFYxmsASv2X5YdgarBB5cjMVb7fyj2CJMdhSqJI4NE8q3iljPpWAar2emETBy7miE7BlWTTTd8EJ09A9kBbWRHoUrI0/NoYiLZ/rqYivPJ2bJjKBrLYDXjvoL2Ly7XBe2uTcTlWv1lR6EKyjPwI5DIGqz6+6rsCIrGT8JqVFCsx9oj8bJjUA3IKdbgvtjh2Bk2DgIq2XHITLnF3ExMZA1+PHQVxXqD7BiKxTJYjTafSuSBIwozIqYLvgicDuHoKjsKmYEjg0TWITmrANvPJsuOoVj8JKxGP3DYW5H+71IDTHCZC70uWHYUKkeenh+BRNaCu1XJw0/CapKUmY/dsTdkxyBJfknyR7/8Wcj1ayE7CpUhl0cTE1mNHWeTkJSVLzuGIrEMVpOfDsfzjCMKdzrbFR0Sp+BaaB/ZUegusvUsg0TWotggsOYQ97OXgWWwmvAFTQCQUeSATuefxP6w0bKjUClyuZmYyKqsOcTdq2TgJ2E1OBGfgbOJWbJjkJUQQoWhMT3wTfAbEA7OsuPQP4TaAULwyG8ia3IuMRvn+P1Z41gGq8Evx67JjkBWaNqFJnjNfQ4Mrv6yoxAAaLSyExBRKX49yu/QmsYyWA1+53kW6S5WJgRhsH428n0ay45CakfZCYioFL/yO7TGsQxa2PGrGbiSmic7BlmxQxk6dLnxGpJDesiOomhCwzJIZI3OJ+fg1LVM2TEUhWXQwn4/wb9oqHzJhY5of+FpHK39pOwoiiXU3ExMZK1+5e5WNYpl0MLWc3ibzKQXagw49wBWhb4KwU2WNc7AfQaJrNZv/C6tUSyDFnTyWgYupuTKjkE25pW4KMzwmgODi4/sKIpiYAEnslqXUnJx/GqG7BiKwTJoQTxwhCpr6bVQPI7ZKPSuLzuKYrAMElm3X49zU3FNYRm0oN+PX5cdgWzYvjRPdE17HalBnWVHUQSDimWQyJr9dowDLDWFZdBCTidk4sKNHNkxyMYl5GvR7vI4nAkbKjuK3ePIIJF1u5qWh5PXuKm4JrAMWggPHCFLKTKo0CdmAH4JfQlC7SA7jt0yqLhuiazdjrPJsiMoAsughWw7myQ7AtmZF+La4l3fWRBOHrKj2KViTi1DZPW2neF3a01gGbSA5KwCnOQEmVQNPrsSjqc0c1HkGSE7it3Rc2SQyOodvpyGtJxC2THsHsugBew8lwwhZKcge7Uj1Ru9MqchM7Cd7Ch2Rc8DSIisnkEAf5zjpuLqxjJoATv4QqVqdjHPGe2uPo/ztR6WHcVuFHNkkMgmbOduWNWOZbCK9AaBXTEsg1T98vQa9Ih9FFvDXoBQ8a1bVcXgyCCRLfjjXDL0Bm5+q078RqmiI1fSkZ5bJDsGKcgzMR3wccBbEFo32VFsGkcGiWxDem4RDl9Okx3DrrEMVtEfHL4mCeZfqovxTnNR7B4qO4rNKgbLIJGt4FHF1YtlsIq4YyvJsj7ZDw/mzkS2f2vZUWxSETcTE9kMlsHqxTJYBSnZBTgWz9nRSZ5zOS5olzAJV2r1lR3F5hRxZJDIZpy5noWU7ALZMewWy2AV7Iq5wSllSLqcYg26xD6O3WFjIaCSHcdmFLIMEtmUvy6kyo5gt1gGq2D/hRTZEYiMnojpiq+CpkE4uMiOYhM4MkhkW/48z+/c6sIyWAX7+VcKWZm3LzbEZLe50LsFyY5i9QqFRnYEIqoAfudWH5bBSrqRXYDzyTmyYxCVsCYxAAMLZyHPr5nsKFaNI4NEtuVsYhZPTVdNWAYr6e+L/AuFrNfxLDd0THwF10N7yY5itQpYBolsihAcHawuLIOVxBckWbu0Igd0OD8Kf9d+WnYUq1RgYBkksjXcV796sAxW0gGODJINEEKFwed6YkXIfyE0TrLjWJUC7jNIZHP2n+d3b3VgGayE7IJinE7Ikh2DyGyvn2+G1z3mwODqJzuK1WAZJLI9Z65nIoOngLU4lsFK+PtiKk+aTTbn24RgDNbPRoFPQ9lRrAI3ExPZHoMA/uKWOYtjGawEbiImW3Uowx1dUv6LGyHdZEeRjiODRLbp4KU02RHsDstgJRy4yBci2a6kAke0uzAax8Melx1FqnwDyyCRLTp6JV12BLvDMlhBBoPASZ6PmGycXqjRP6Yv1oS+DKF2lB1HinyODBLZpBPxGRA8F6xFsQxW0PkbOcgp1MuOQWQRL8W1wtveb8Pg7C07So3L07MMEtmirIJixCVny45hV1gGK+jkNY4Kkn35Kj4MI9RzUOhVV3aUGpXHA0iIbNaRK/wutiSWwQo6wU3EZId2p3qie/obSA/qKDtKjckz8OOPyFYdv5ouO4Jd4adhBZ2Iz5QdgahaxOc7od3l8TgX9qjsKDWCB5AQ2a4T1/hdbEksgxXEzcRkzwoMavSOeRjra02EUNl3WcrT8+OPyFadTsiEgfP9Wgw/DSvgUkoOMvOLZccgqnbjYu/FfL9ZEE7usqNUmxw99xkkslW5hXqcv8GDSCyFZbACuImYlOTjKxEY7TAXRR7hsqNUixy9SnYEIqqC49yH32JYBivgBDcRk8JsTfFBdPZ0ZAbcIzuKxXFqGSLbdiYhS3YEu8EyWAEnucMqKdD5XGd0iH8RF2oNlB3FonK5zyCRTYtN4mZiS+GnYQXEJPKvEFKmHL0a3WOHYFvYfyBUtv+xIaDi0cRENo4TT1uO7X+q15DcwmJcz8yXHYNIqqdjOuGTgBkQjm6yo1SNRpmn4COyJ1fS8lBQzDOCWQLLoJku3MgBT4VIBMy7VA8vOM9FsXuo7CiVxzJIZPP0BoELN3Jkx7ALLINmOp/MFxzRLb8m+6Ff3lvI8W8pO0qlCI2T7AhEZAHcb9AyWAbNxDJIZOpMtivaJ7yE+NAHZEepMKHmyCCRPWAZtAyWQTNxckuikrKKHdAp7knsC3tWdpQKYRkksg9xHKixCJZBM3FkkOjuhsd0w9fBb0I4OMuOYhYDyyCRXeDIoGWwDJqJO6kSlW3mhcZ4WTcXercA2VHKJdRa2RGIyALOJ2fzHMUWwDJohsTMfGQX8JzEROVZfT0Qg4reRp5vU9lRysSRQSL7UFBsQHx6nuwYNo9l0Ayc2JLIfEcydeic/AoSQ3rKjnJXepZBIrtxjWWwylgGzXAlNVd2BCKbklLoiPYXnsKhsFGyo5SKI4NE9uNaBstgVbEMmuFaOs88QlRRQqjwSExvfBcyFUJjXfvo6VUsg0T2gt/RVccyaIbrGXyhEVXW1PPNMc1zNgwuvrKjGOlVDrIjEJGFcDNx1bEMmiGB5yQmqpJl10IxTMxGgXcD2VEAcGSQyJ6wDFYdy6AZrnN/BKIq+yvdA11T/4uU4PtkR0ExRwaJ7AY3E1cdy6AZEriZmMgirhdo0f7SWJwKGy41B0cGiewHRwarjmWwHDkFxcjK5xyDRJZSZFDhwZj+WBc6BUItZ4SumGWQyG5kFRQjK79IdgybxjJYDo4KElWPF+Na4/983oZw8qzxxy4CNxMT2RNuKq4alsFy8EhiourzxdXaGOUwB0WedWr0cVkGiewL5xqsGpbBciTwBUZUrf5I8cb9mW8iI7B9jT1mMcsgkV1JzS6UHcGmsQyWIymrQHYEIrt3Oc8Z7a/+B7Fhg2rk8TgySGRf0nJZBquCZbAcGXncKZWoJuTpNegZMwgba70IoarejyaWQSL7kp7L7+qqYBksRwZfYEQ1amxsOyz0nwmh1VXbYxSARxMT2ROODFYNy2A5ODJIVPM+uByJsdr/Q7FHWLUsv1BoqmW5RCQHRwarhmWwHOl5/GuDSIZNN3wQnT0D2QFtLL7sQsHNxET2hCODVcMyWI6MPE44TSRLXK4L2l2biMu1+lt0uYXgyCCRPUnjyGCVsAyWI5ObiYmkyinW4L7Y4dgZNg4CKosss4Ajg0R2JZ0jg1XCMlgO7jNIZB1GxHTBF4HTIRxdq7wsbiYmsi/cTFw1LINlKNYbkF3AzcRE1uL/LjXARNc50OuCq7ScAgM3ExPZk/wiA/KL9LJj2CyWwTJwVJDI+qxLDMBDBTOR69ei0svI58ggkd3JyufgTWWxDJYhky8sIqt0MssNHRKn4Fpon0rdP1/wo4/I3hQUc2SwsviJWIbcQpZBImuVUeSATuefxP6w0RW+b76em4mJ7E1BsUF2BJvFMlgGvrCIrJsQKgyN6YFvgt+AcHA2+375nHSayO4UFPE7u7JYBsvAFxaRbZh2oQlec58Dg6u/WbfPN3CfQSJ7w83ElccyWAa+sIhsx8qEIAzWz0a+T+Nyb5tv4Ecfkb3h1rzK4ydiGQr5wiKyKYcydOhy4zUkh/Qo83a5nFqGyO6wDFYey2AZCvV8YRHZmuRCR7S/8DSO1n7yrrfJLWYZJLI3BZxnsNJYBstQrBeyIxBRJeiFGgPOPYBVoa9CqB1LXJ/HzcREdiefI4OVxk/EMhQbWAaJbNkrcVF4y2s2DC4+JpfncmoZIrvDkcHKYxksQzE3ExPZvCXXauFxzEahVz3jZXksg0R2hwM4lccyWIYivrCI7MK+NE90T38daUGdAAA5en70EdkbtUp2AtvFT0QiUoT4fCe0vzwOZ8KGIpdlkMjuqFRsg5XFmVfL4MA/M4jsSoFBjT4xA2THIKJqoGEZrDT+eVwGDcsgERGRTeB3duWxDJbBUcMXFhERkS3gwGDlsQyWQaPm6iEiIrIFHBmsPLadMjjyhUVERGQT1BwarDSWwTLwrwwiIiLbwDJYeSyDZXDUcPUQERHZAg7gVB7bThn4wiIiIrINHL+pPK66MnCeQSIiItvg4sipkyuLZbAMWgeuHiIiIlugc2IZrCy2nTLonPnCIiIisgVuThrZEWwWy2AZ3J0dZUcgIiIiM3AAp/JYBsvgzhcWERGRTeBm4spjGSyDu5MDeAwJERGRdVOrAFcty2BlsQyWQaVSwY1/aRAREVk1NxbBKmEZLIcH9xskIiKyatxfsGpYBsvB/QaJiIisG7fiVQ3LYDk4MkhERGTdWAarhmWwHBwZJCIism7erhy4qQqWwXJ4uPAFRkREZM38dU6yI9g0lsFy+LppZUcgIiKiMvi7swxWBctgOQI9nGVHICIiojKwDFYNy2A5Ajz4AiMiIrJmAe4cuKkKlsFycGSQiIjIunFksGpYBsvBMkhERGTdWAarhmWwHIHcTExERGTVAlgGq4RlsByuWge4czJLIiIiq+Sq1XDS6SpiGTQDDyIhIiKyTtxEXHUsg2YI8uR+g0RERNYokEcSVxnLoBn4QiMiIrJOtXxcZEeweSyDZgj15guNiIjIGoV5u8qOYPNYBs0Q7usmOwIRERGVIsyHZbCqWAbNUMePLzQiIiJrVJtlsMpYBs0QwZFBIiIiqxTGfQarjGXQDL46J7g7cw4jIiIia+LsqEYQzxRWZSyDZqrjx9FBIiIiaxLh6waVSiU7hs1jGTQTNxUTERFZF343WwbLoJkiODJIRERkVfjdbBksg2biEcVERETWhd/NlsEyaCYORRMREVmXhkEesiPYBZZBM0X662RHICIion+oVUDDQHfZMewCy6CZPF0cEerFuYyIiIisQbivG1y0Gtkx7ALLYAU0DuZwNBERkTVoFMRRQUthGayAJiEsg0RERNaAAzSWwzJYAU34wiMiIrIKHBm0HJbBCmjKkUEiIiKrwJFBy2EZrIAwH1eeo5iIiEgydycH1PLmQZ2WwjJYQdxUTEREJFfDIHeek9iCWAYriAeREBERydUomPsLWhLLYAVxZJCIiEiuFrW8ZEewKyyDFdQs1FN2BCIiIkVrXdtbdgS7wjJYQQ0C3aFz4kEkREREMni5OqKuv5vsGHaFZbCCNGoVWtX2kh2DiIhIkVqFefHgEQtjGayENuEcniYiIpKB38GWxzJYCfdE+MiOQEREpEjcX9DyWAYroWWYFzRqDlETERHVJI1ahZbcVcviWAYrwc3JAY05xxEREVGNahjoDlctD+K0NJbBSmobzk3FRERENal1uJfsCHaJZbCS2kZwnwUiIqKaxINHqgfLYCVxZJCIiKhmtavjKzuCXWIZrKQgT2eE+bjIjkFERKQIkf5uCPHi9251YBmsgs71/GRHICIiUoQu/M6tNiyDVXBffX/ZEYiIiBShM79zqw3LYBV0rOfH+QaJiIiqmYNahfaR3Fe/urAMVoGniyOiannKjkFERGTXWoZ5wd3ZUXYMu8UyWEX3NeCwNRERUXXqXJ/7C1YnlsEqYhkkIiKqXjxgs3qxDFZRVC0veLpw6JqIiKg6uDs5oGWYl+wYdo1lsIo0ahU61eMkmERERNWhXaQvHDSsK9WJa9cCOMUMERFR9ejRKEB2BLvHMmgB3G+QiIjI8tQqoFeTQNkx7B7LoAWEeLmgaYiH7BhERER2pVVtb/i7O8mOYfdYBi2kd5Mg2RGIiIjsSm+OCtYIlkELiW7GFywREZElRTflQEtNYBm0kEZBHgj3dZUdg4iIyC40CNQhws9NdgxFYBm0IP4FQ0REZBn8Tq05LIMW1KcZX7hERESWwDJYc1gGLahVmBdCPJ1lxyAiIrJpoV4uaBbqKTuGYrAMWpBKpUKfZsGyYxAREdk0zi1Ys1gGLaxvCw5rExERVUX/KA6s1CSWQQtrXdsbwdxUTEREVCnhvq5oE+4jO4aisAxamEqlwoCWobJjEBER2SR+h9Y8lsFqMLgNX8hERESV8UgrfofWNJbBalAvwB1RtXgUFBERUUW0DPPiRNMSsAxWk0da15IdgYiIyKY80pqjgjKwDFaTh6JCoNVw9RIREZnDUaNCvxYhsmMoEttKNfF206J7I3/ZMYiIiGxC1wb+8HHTyo6hSCyD1YibiomIiMwzkAeOSMMyWI16NArgXzlERETlcHd2QM/GPOuILCyD1chRo0b/FpxFnYiIqCyDWteCs6NGdgzFYhmsZkPuCZMdgYiIyKo93q627AiKxjJYzZqGeKJ1bS/ZMYiIiKxSuzo+qB/oLjuGorEM1oARHSJkRyAiIrJKT7QPlx1B8VgGa8CDzYPhp+OBJERERLfz0zmhT7Mg2TEUj2WwBmgd1BjKfQeJiIhMDLsnDI48QYN0/A3UkMfbhUOjVsmOQUREZBXUKmA4DxyxCiyDNSTEywX3NwqQHYOIiMgq9GgUgFAvF9kxCCyDNYoHkhAREd30OA8csRosgzWoUz1fRPq7yY5BREQkVYSvK7rW95cdg/7BMliDVCoVnuRfQkREpHCju0RCzf3orQbLYA0b0jYMni6OsmMQERFJ4afTYnCbWrJj0G1YBmuYm5MDRnTg6CARESnTyA4RPA+xlWEZlOCpTnXgwjcCEREpjKtWgyc5IGJ1WAYl8HHTYkhbDpETEZGyDGkbBi9XnpHL2rAMSjLmvkg4cOdZIiJSCAe1CqO71JEdg0rBMihJLW9X9I8KkR2DiIioRjzYPBi1vF1lx6BSsAxK9FzXulBxcJCIiBRgbNdI2RHoLlgGJWoY5I4eDXmKOiIism9d6vuhaYin7Bh0FyyDko3vXld2BCIiomr14v31ZUegMrAMStYm3AcdIn1lxyAiIqoWXer7oW2Ej+wYVAaWQSswJbqB7AhERETVYmJPjgpaO5ZBK9Am3Ac9GnHfQSIisi9d6vuhTThHBa0dy6CVmNy7AY8sJiIiu/JSL275sgUsg1aiaYgnHmwWLDsGERGRRfRsHIBWtb1lxyAzsAxakZd6N4CGZyUhIiIbp1IBU6Ibyo5BZmIZtCJ1/XV4uFWo7BhERERV0r9FCBoFeciOQWZiGbQyL95fH1oNfy1ERGSbHNQqTOK+gjaFrcPKhPm4Yti9YbJjEBERVcpj7Wqjjp+b7BhUASyDVuj5HvXgptXIjkFERFQhHs4OmNSTo4K2hmXQCgW4O2N893qyYxAREVXIhPvrw9tNKzsGVRDLoJV6pnMdhPm4yI5BRERklghfV4zoECE7BlUCy6CVcnbU4L8PNJYdg4iIyCyvPdAYWgfWClvE35oVe6B5MNrV4Wl8iIjIurWP9EGfZkGyY1AlsQxauen9m4LzUBMRkbVSq4A3+jaRHYOqgGXQyjUJ8cDQe2rLjkFERFSqQa1roVmop+wYVAUsgzZgSu8GcHd2kB2DiIjIhKtWg5d52jmbxzJoA3x1TpjQo77sGERERCYm9qyPAA9n2TGoilgGbcSoThGoF6CTHYOIiAgA0CTYA093qiM7BlkAy6CNcNSoMefh5lDxYBIiIpJMrQLmPNIcDhrWCHvAHdFsyL11fDDsnjB899cV2VGIqBoJgx4Zu79F9qkdMOSkQaPzgVuz++HZcRhU//xFeOO3Bcg5sdXkfs51WiNwyMy7LvfqZ09Dn5lU4nJdq77w7T0OAJC6dRFyTmyFytEZXl1HQte0u/F2OWd2I+fEVgQMnm6Jp0k27PF24WgZ5iU7BlkIy6CNee2BxthyOgnJWQWyoxBRNcnc/yOyjqyHb99J0PrVRkFCDFLWfwC1kxs82j5kvJ1znTbwe3Div3d0cCxzucEjFwAGg/HnwhuXkLTyDbg16gQAyI3dj5zTfyBgyCwUp11DyvoP4FKnNTSunjAU5CB95zcIHPa2RZ8r2Z4Adye80ocHjdgTju/aGE8XR0zvz/mciOxZQfxpuNRrB9e698DBMxBujTrDJaIVChPOmdxO5eAIjc7733/OZe9XrHH1NLl9XuxfcPAKhlNYcwBAUcoVOIc1h1Nwfbg16QqV1hXFGYkAgLTti+He6kE4eARUz5MmmzGtfxO4O5f9hwfZFpZBG9SvRQjub8QPZCJ75RTaGPmXjqIoNR4AUJh0HvlXT8E5so3J7fIvH8eVjx5H/KKxSNn4CfR5mWY/htAXIefUDuha9DJuetb610Hh9Vjo87NRcD0WorgADt4hyL96EoWJcXBv099yT5JsUveG/ujXIkR2DLIwlRBCyA5BFRefnofe7/+BnEK97ChEZGFCGJD+xzfI3P8joFYDBgO87nsSnh2GGG+Tc+oPqByd4eAViOK0BKTv/AYqrTOCnpgHlVpT7mPknN6FG7+8h9Bxi+Hg7mu8PH33CuSc3AGVgxZeXR6HS917kLBkInz7TkJB/GlkHfoVGhcP+EQ/D61/eLU8f7JOLo4abJp0H8J8XGVHIQvjPoM2KtTLBS/1bohZv56SHYWILCz39C7knNoBv/5T4OgfjsLE80jbugganS90ze8HALg16Wq8vdY/Ao4BdXDti9HIv3wcLhEty32M7GOb4BLZxqQIAoBX58fh1flx48/pu7+Fc0RLqNQaZOxbiZCnP0Fe7F9I+e19BI/6wDJPmGzCiz3rswjaKW4mtmFPdYxAVC2eAojI3qTtWAzP9oPh1qQrtP4R0DXrAfd7BiDjzx/ueh9HryCoXTxQnJ5Q7vKLM5KQf+kodFHRZd6uKOUKck5th1eXJ5B/+TicazWDxtUTro26oDAxDoaC3Ao/N7JNrWp7YUyXSNkxqJqwDNowtVqFdwa3gNaBv0YieyKKCgCV6ftapVIDwnCXewDFmTdgyMuCxs2n3OVnH98MjasnXOrec/cMQiBl4yfw7jEaaq0LIAwQhuKbV976bxl5yH64OGow/9EoaNSc6NZesUXYuEZBHpjcq4HsGERkQS717kXG3pXIjTuA4oxE5J7bi8wDa+HaoAMAwFCYh7TtX6Mg/gyKMxKRd/EIktfMgoN3MFzqtDYuJ/H7/yLz4C8myxbCgOzjW+DW7P4y9y3MProRGhcPuNZrB+DWQS3HUBB/BpkH1sHRtzbU5Ry9TPbh1T4NEenP37U94z6DdmBMl0hsO5OE/RdSZUchIgvw6TkW6buWI3XTpzDkZkCj84Gu5QPw6jTs5g1UahQmXUD2ia0w5OdAo/OBS51W8OryBFS3zTVYlHYdTnccYZx/8Qj0mcnQteh118fX56QhY98qBD3xnvEyp5CG8Lj3YSStfgtqV0/49Z1k2SdNVqljXV+M7BghOwZVMx5NbCeupuXigYW7kFVQLDsKERHZAXcnB2yYdB9CvVxkR6Fqxs3EdqKWtyumcTJqIiKykGn9m7AIKgTLoB15tG0YopsGyo5BREQ2rmfjQDzaNkx2DKohLIN2Zu4jLeCnc5Idg4iIbJSPmxZzH2kuOwbVIJZBO+PjpsW7g/kmJiKiypn7SHP4u3NQQUlYBu1Qj0aBeKxdbdkxiIjIxozqGIHopkGyY1ANYxm0U9P6NUGjIHfZMYiIyEa0qOWJ/z7YWHYMkoBl0E45O2rw8WOt4aot/4T1RESkbO7ODvh4eGue0Uqh+Fu3Y/UCdHh7YDPZMYiIyMq9O6gFavu6yo5BkrAM2rlHWtfCo21qyY5BRERWakSHcDzQPFh2DJKIZVABZg1sxv0HiYiohKYhHni9L/cTVDqWQQVwdtTgsyfawN2Jp6ImIqKbdE4O+OSx1nBy4L7lSscyqBB1/Nzw7uAWsmMQEZGV+L9BzRHh5yY7BlkBlkEFeaB5MJ7pXEd2DCIikuy5rnXRr0WI7BhkJVgGFWbqA43QqZ6v7BhERCRJ94b+eCW6oewYZEVYBhXGQaPGp4+1QQSnECAiUpy6/m74YHgrqNUq2VHIirAMKpCnqyP+N/IeuDvzgBIiIqXwcHbAohFt4eHsKDsKWRmWQYWqF6DDR8NbQcO/DomI7J5aBXw4vBUi/XWyo5AVYhlUsG4NAzD1gUayYxARUTV7tU8jdGsYIDsGWSmWQYUb3SWSZyghIrJjA1uGYGzXurJjkBVjGSTMfrg52oZ7y45BREQWFlXLE/83iHPMUtlYBglaBzW+eLINQr1cZEchIiILCfd1xVej7oGzI88wQmVjGSQAgK/OCUueugeeLjzKjIjI1vm4abHkqXvhp3OSHYVsAMsgGdUPdMdXI9vC2ZEvCyIiW+XiqMFXI9uiDk81R2bitz6ZaBvhgw+HccoZIiJbpFGr8NHwVmhVm/uBk/lYBqmE3k2DMGtAM9kxiIiogmYNaIaeTQJlxyAbwzJIpXqsXW28eH992TGIiMhML/Soh8fa1ZYdg2wQyyDd1aReDfjBQkRkAwa3qYXJvRvKjkE2imWQyjRrQDP05iYHIiKr1aNRAP7vkeayY5ANYxmkMmnUKnw4vBXujfCRHYWIiO7QuZ4fPnuiNRw0/DqnyuOrh8rl7KjB10/dg1a1vWRHISKif9xbxweLRrSFkwMnlaaqYRkks+icHLD06XsRVctTdhQiIsVrVdsLX4+6By5aFkGqOpZBMpuHsyO+ebodmoZ4yI5CRKRYTUM8sOSpe6FzcpAdhewEyyBViKerI5Y/0w6NgtxlRyEiUpyGge5Y/kw7njqULIplkCrM202LFaPboUGgTnYUIiLFiPR3w4ox7eDtppUdhewMyyBViq/OCStGt0ekP899SURU3Wr7uOLb0e3hp3OSHYXsEMsgVZq/uxO+G9MeEb6usqMQEdmtSD83rBrbAUGezrKjkJ1iGaQqCfRwxsqxHVA/gJuMiYgsrUGgDt+Pbc8iSNVKJYQQskOQ7UvNKcTIr//C8fgM2VGIiOxC0xAPLHumHXy4jyBVM5ZBspis/CI8s/Rv/HUhVXYUIiKb1qq2F5Y8dS+PGqYawTJIFpVfpMe45Qex/Wyy7ChERDapUz1ffPlkW7hxHkGqISyDZHFFegMmrTyCX48lyI5CRGRTejYOxCePt+Ip5qhGsQxStTAYBF5fexzf/XVFdhQiIpswsGUI5j0aBQcNj+2kmsUySNVqzu+n8eXO87JjEBFZtWfvi8TUBxpBpVLJjkIKxDJI1e7LnXGYu/4M+EojIjKlVgEzHmqKER0iZEchBWMZpBqx/ngCJq06gvwig+woRERWwcVRgw+Ht0KvJoGyo5DCsQxSjTl0OQ3PfvM3bmQXyo5CRCSVn06Lr0beg6gwL9lRiFgGqWZdSc3FqMV/IS45R3YUIiIpIv3dsPSpexHmw1N5knVgGaQal5FbhLHL/8af5zk5NREpyz0R3lg0oi28XHlWEbIeLIMkRWGxAa+tOYY1h+JlRyEiqhF9WwTj/SFRnEOQrA7LIEm1cMs5LNwSIzsGEVG1UauAST0b4Pke9Th1DFkllkGSbv3xBEz54ShyCvWyoxARWZS7swM+GNYSPRrxiGGyXiyDZBViErMwdtlBnL/BA0uIyD7U9XfDohFtEemvkx2FqEwsg2Q1svKLMGnlUWw5nSg7ChFRlfRsHIgFQ6Pg7uwoOwpRuVgGyaoIIfDRtlgs3HIOBr4yicjGqFTAhB71MbFnfe4fSDaDZZCs0vYzSXjx+8PIzC+WHYWIyCw6Jwe8PyQKvZsGyY5CVCEsg2S1LqXkYOyygzhzPUt2FCKiMjUMdMcnj7dCvQB32VGIKoxlkKxabmEx3lh7gvMREpHVGn5vbUzv3wTOjpw/kGwTyyDZhLWH4/HG2hPILuBmYyKyDu7ODpj7SHP0axEiOwpRlbAMks24lJKDCd8dxtGrGbKjEJHCRYV54ePhrXh+YbILLINkU4r0BszbdBZf7jwPvnKJqKapVMCzXSIxJbohHDVq2XGILIJlkGzSrphkvLTqKJKzCmRHISKF8HXTYv6QKHRrGCA7CpFFsQySzUrJLsDkH45ix9lk2VGIyM51qe+H+Y9GIcDDWXYUIotjGSSbJoTAkr0X8c6GM8gvMsiOQ0R2RufkgP8+2BiPtastOwpRtWEZJLtwPjkbU344ikOX02VHISI70bGuL94d3AK1vHmQCNk3lkGyGwaDwKJd5/H+5nMoKOYoIRFVjqtWg9ceaIQn24fzlHKkCCyDZHdik7Lw8upjOMxRQiKqoHsjfPDeoy0Q7usmOwpRjWEZJLtkMAh8vecC5m86h7wivew4RGTlnB3VeDm6EZ7qGAG1mqOBpCwsg2TXLqXk4NUfj+HP86myoxCRlepY1xdvD2yGSH+d7ChEUrAMkt0TQmDV31fwzoazSM0plB2HiKyEn84Jb/ZrjAEtQ2VHIZKKZZAUIz23EO9sOIuVBy7DwFc9kWKpVcAT7cMxJbohPJwdZcchko5lkBTn6JV0vLH2BI7H8xzHRErTPNQTsx9uhha1vGRHIbIaLIOkSAaDwIq/LmPexrPIyCuSHYeIqpm7swOm9G6IJ9uH8wARojuwDJKipWQX4P/Wn8HqQ1fBdwKR/VGpgIeiQvB638YIcOep5IhKwzJIBODgpVTM+PkUNx0T2ZG24d54o18TtAzzkh2FyKqxDBL9QwiBn49ew3sbz+JqWp7sOERUSeG+rnitTyM80DxYdhQim8AySHSHwmIDvtl3ER9vj0V6LvcnJLIVXq6OeKFHfTzZPhxaB7XsOEQ2g2WQ6C4y8orw6fZYLNl7kec6JrJiWo0aIzqE44Ue9eHpyqliiCqKZZCoHPHpeZi38SzWHonnQSZEVkSlAh5sFoxX+jTkuYSJqoBlkMhMJ+IzMG/TWew4myw7CpGiqVRA7yaBePH+BmgS4iE7DpHNYxkkqqCjV9Lx4dYYbD2TJDsKkeL0bhKIF3vWR9MQT9lRiOwGyyBRJZ2Iz8AHW2Ow+VSi7ChEdq9n40BM7FkfzUJZAoksjWWQqIpOXsvAh1tjsOlUIvcpJLKw+xsFYGLPBmheiyWQqLqwDBJZyOmETHy0LQbrT1xnKSSqArUK6NUkEOO71UMUJ4wmqnYsg0QWFpuUha92X8CaQ/GckoaoArQOagxqHYoxXSIR6a+THYdIMVgGiapJSnYBVuy/jG/2XcKN7ALZcYislperIx5vVxujOtaBv7uT7DhEisMySFTNCor1+PnINXy1+wLOXM+SHYfIakT6u+HpTnUwqHUtuGg1suMQKRbLIFEN2hN7A//bdR47ziVzv0JSJJUK6FzPD091ikD3hgFQqVSyIxEpHssgkQSxSdlYsf8Sfjocz/MfkyL46bQY3CYMw+8N49lCiKwMyyCRRAXFemw4cR3f/3UFf15I4Wgh2RWVCugQ6YvH2tVG7yZB0DqoZUciolKwDBJZiYs3cvD9gStYffAqDzghm+brpsXgNrUw7N7aqOPHUUAia8cySGRlivQGbD2diO/+uoJdMckw8B1KNkCjVqFTPT8MblMLfZpyFJDIlrAMElmxa+l5+PXYNfx89BpOxGfKjkNUQsswLwxsGYJ+USHw03FaGCJbxDJIZCPOJ2fjl6MJ+PloPOKSc2THIQWL9HfDwJahGNAyhAeDENkBlkEiG3TyWgZ+OZqAX45eQ3x6nuw4pAAB7k7oHxWCgS1DeZ5gIjvDMkhkw4QQOHQ5Hb8dS8DWM4m4lJIrOxLZkXoBOvRsHIheTQLRKswLajXnBCSyRyyDRHYkNikLW04nYdvpJBy8nAY9jz6hCtCoVWhT2xs9mwSgV5MgHglMpBAsg0R2Ki2nEDvOJWHr6ST8cS4ZWfnFsiORFXLVatClvh96NQlCj0YB8HHTyo5ERDWMZZBIAYr0Bhy4kIrtZ5OwJzYFp69ncoJrhdKoVWhRyxOd6vqhYz1ftAn3hpMDzwtMpGQsg0QKlJpTiH1xKdgTdwP74lJw4QaPTrZnDQPd0bGeLzrV9UO7SB+4OzvKjkREVoRlkIiQmJmPP8+nYP+FVOw/n8Kpa2yYSgXU9dehTW1vdKzni451/eDvzvn/iOjuWAaJqISU7AIcu5qBI1fScfRqOo5dzUBqTqHsWFQKHzctWoZ5oVWYF1rW9kJUmBc8OPJnQqVS4aeffsLAgQMBAGfOnMGoUaNw5MgRNGrUCEeOHCn1MiW7ePEi6tSpg8OHD6Nly5ay41TakiVLMHHiRKSnp8uOYtUcZAcgIuvjq3NC90YB6N4owHjZldRcHLmSjmNX03H0SgZOXMtAbqFeYkrlcXZUo2Gg+83yV9sbrWp7KXbS51GjRmHp0qUAAAcHB/j4+KBFixYYPnw4Ro0aBbX639PhJSQkwNvb2/jz9OnT4ebmhrNnz0Kn0931MpkiIiIwceJETJw4sdofa9SoUUhPT8fatWur/bHIPDX5+wdYBonITGE+rgjzcUX/qBAAgN4gEJuUjbOJWYhNzMK5xGycS8rC5ZRcFHNKmyrRqFUI93VFoyB3NAh0N/43wteNc/3dpk+fPli8eDH0ej0SExOxYcMGvPjii1i9ejV+/vlnODjc/IoLCgoyuV9cXBz69u2L8PDwMi+rqMLCQmi1PBq7LEpZR6U9TyEE9Hq98XUpK0dpeCZxIqoUjVqFhkHueCgqBC/1bojPn2yDbZO74dTMPtgwsQs+HN4KE3rUQ5+mQajr7watAz9u7qRzckCjIHf0ahKIsV0j8f6QKPw2oTNOzYzGtsnd8OnjbTCxZwP0aRaMSH8di+AdnJycEBQUhNDQULRu3Rr//e9/sW7dOqxfvx5Lliwx3k6lUhlHvVQqFQ4ePIiZM2dCpVJhxowZpV4GAFeuXMGQIUPg5eUFHx8fDBgwABcvXjQud9SoURg4cCBmz56NkJAQNGzYsEL3mzdvHoKDg+Hr64v//Oc/KCoqAgB069YNly5dwqRJk6BSqaBS3f33/v7776N58+Zwc3NDWFgYxo8fj+zsbOP1M2bMKLGZd+HChYiIiDBev3TpUqxbt874WDt27DDe9vz58+jevTtcXV0RFRWFffv2mSzrxx9/RNOmTeHk5ISIiAjMnz/f5PqIiAjMmjULI0aMgIeHB5599tlSn8eGDRvQuXNneHl5wdfXF/369UNcXJzx+osXL0KlUmHNmjVl5lmyZAlq164NV1dXPPzww0hJSbnrujN3uSkpKRg+fDhCQ0Ph6uqK5s2b47vvvjNZTrdu3fD8889j4sSJ8PPzQ3R0NHbs2AGVSoX169ejTZs2cHJywu7duxEXF4cBAwYgMDAQOp0O99xzD7Zs2WKyrLv9/i21vu/EkUEisiitgxqNgjzQKMjD5HIhBJKzCnA1PQ9X0/JwNS0X8Wk3/z8+PQ/xaXnIK7Kvzc6OGhVCvFwQ5u36z8jqzf+v/c8oK+f0s7wePXogKioKa9aswejRo0tcn5CQgJ49e6JPnz6YMmUKdDodnnvuuRKXFRUVITo6Gh06dMCuXbvg4OCAt99+G3369MGxY8eMoy1bt26Fh4cHNm/eDABm32/79u0IDg7G9u3bERsbi6FDh6Jly5YYM2YM1qxZg6ioKDz77LMYM2ZMmc9XrVbjww8/RJ06dXD+/HmMHz8er7zyCj799FOz1teUKVNw+vRpZGZmYvHixQAAHx8fXLt2DQDw+uuvY968eahfvz5ef/11DB8+HLGxsXBwcMDBgwcxZMgQzJgxA0OHDsXevXsxfvx4+Pr6YtSoUcbHmDdvHqZNm4bp06ffNUdOTg5eeukltGjRAtnZ2Zg2bRoefvhhHDlyxGSTf1l59u/fj2eeeQZz587FwIEDsWHDhjIf83ZlLTc/Px9t2rTBq6++Cg8PD/z222948sknUbduXdx7773GZSxduhTjxo3Dnj17ANx8rQHAa6+9hnnz5iEyMhLe3t64cuUKHnzwQcyePRtOTk745ptv0L9/f5w9exa1a9e+6+/fkuv7TiyDRFQjVCoVAjycEeDhjNa1vUu9TUp2ARIzC5CaU4jU3EKkZt/2/zmFSMm++d+03EKk5RbV6BlWVCrAxVEDV60GOicHeLtp4eOqhY+bFj46LXzdtPDTOSHA3Rn+7k7wd3eCt6tjmaM6VD0aNWqEY8eOlXpdUFAQHBwcoNPpjJuPdTpdicuWL18Og8GA//3vf8bf4eLFi+Hl5YUdO3agd+/eAAA3Nzf873//M5Y8c+/n7e2Njz/+GBqNBo0aNULfvn2xdetWjBkzBj4+PtBoNHB3dy+xiftOt+9TFhERgbfffhvPPfec2WVQp9PBxcUFBQUFpT7WlClT0LdvXwDAW2+9haZNmyI2NhaNGjXC+++/j/vvvx9vvvkmAKBBgwY4deoU3nvvPZNy0qNHD0yePLnMHIMGDTL5+euvv4a/vz9OnTqFZs2amZXngw8+QJ8+ffDKK68Y8+zduxcbNmwodz2UtdzQ0FBMmTLFeNsXXngBGzduxKpVq0zKYP369fHuu+8af75VBmfOnIlevXoZL/fx8UFUVJTx51mzZuGnn37Czz//jOeff/6uv39Lru87sQwSkdXw1TnBV2f+NCiFxQbkFemRX6RHXqH+3/83XmZAfpEeAsCtSqZS/fMPKtzqabe+tLUaFVy1DnBz0sDF8eZ/XbUOcNXeLIEsdrZBCFHl39XRo0cRGxsLd3d3k8vz8/NNNl82b97cZJ8sc+/XtGlTaDT/TvYdHByM48ePVzjnli1bMHfuXJw5cwaZmZkoLi5Gfn4+cnNz4erqWuHl3alFixYmGQEgKSkJjRo1wunTpzFgwACT23fq1AkLFy6EXq83Pr+2bduW+zgxMTGYNm0a9u/fjxs3bsBgMAAALl++bFIGy8vz8MMPmyy3Q4cOZpXBspar1+sxZ84crFq1CvHx8SgsLERBQUGJ9dumTZtSl33n88/OzsaMGTPw22+/ISEhAcXFxcjLy8Ply5fLzGjJ9X0nlkEisllaBzW0Dmp4unAqFfrX6dOnUadOnSotIzs7G23atMGKFStKXOfv72/8fzc306O5zb2fo6Ppa1alUhkLkLkuXryIfv36Ydy4cZg9ezZ8fHywe/duPPPMMygsLISrqyvUajXunEHu1r6J5rg9562CXdGcd66j0vTv3x/h4eFYtGgRQkJCYDAY0KxZMxQWmk5pZYk8pSlrue+99x4++OADLFy40Lh/5sSJE0tku9vzvPPyKVOmYPPmzZg3bx7q1asHFxcXDB48uMTyKsuc9X0nlkEiIrIb27Ztw/HjxzFp0qQqLad169ZYuXIlAgIC4OHhUf4dqni/O2m1Wuj1Ze9De/DgQRgMBsyfP9+4X92qVatMbuPv74/r16+bjJbeOYeiOY9VmsaNGxv3j7tlz549aNCggcmoZ3lSUlJw9uxZLFq0CF26dAEA7N69u1J59u/fb3LZn3/+WeHl3GnPnj0YMGAAnnjiCQA3S+K5c+fQpEmTSi9v1KhRxlHM7OxskwOMgNJ/J5Za36Xh4X1ERGSTCgoKcP36dcTHx+PQoUOYM2cOBgwYgH79+mHEiBFVWvbjjz8OPz8/DBgwALt27cKFCxewY8cOTJgwAVevXrX4/e4UERGBnTt3Ij4+Hjdu3Cj1NvXq1UNRURE++ugjnD9/HsuWLcPnn39ucptu3bohOTkZ7777LuLi4vDJJ59g/fr1JR7r2LFjOHv2LG7cuGH2yOHkyZOxdetWzJo1C+fOncPSpUvx8ccfm+xfZw5vb2/4+vriyy+/RGxsLLZt24aXXnqpQssAgAkTJmDDhg2YN28eYmJi8PHHH5u1ibg89evXx+bNm7F3716cPn0aY8eORWJiYpWWt2bNGhw5cgRHjx7FY489VmJ0s7Tfv6XWd2lYBomIyCZt2LABwcHBiIiIQJ8+fbB9+3Z8+OGHWLduXZVHSlxdXbFz507Url0bjzzyCBo3boxnnnkG+fn5ZY74VfZ+d5o5cyYuXryIunXrmmxevl1UVBTef/99vPPOO2jWrBlWrFiBuXPnmtymcePG+PTTT/HJJ58gKioKf/31V4nyMGbMGDRs2BBt27aFv79/idGnu2ndujVWrVqF77//Hs2aNcO0adMwc+ZMk4MZzKFWq/H999/j4MGDaNasGSZNmoT33nuvQssAgPbt22PRokX44IMPEBUVhU2bNuGNN96o8HLu9MYbb6B169aIjo5Gt27dEBQUZDybTWW8//778Pb2RseOHdG/f39ER0ejdevWJrcp7fdvqfVdGp6OjoiIiEjBODJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQKxjJIREREpGAsg0REREQK9v+9UFm4QUe0YgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check where Author and Narrator are the same\n",
    "df['Same Author and Narrator'] = df['Author'] == df['Narrator']\n",
    "\n",
    "# Counting the number of same and different values\n",
    "same_count = df['Same Author and Narrator'].value_counts()\n",
    "\n",
    "# Plotting the pie chart\n",
    "plt.figure(figsize=(8, 8))\n",
    "plt.pie(same_count, labels=['Different author and narrator', 'Same author and narrator'], autopct='%1.1f%%', startangle=140)\n",
    "plt.title('Distribution of same vs different Author and Narrator')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "7c4f6c8e-1de3-44a6-929b-d4d46fb21081",
   "metadata": {},
   "source": [
    "As we can see, in most of the books, the authors and narrators are distinct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "4a938f69-ca74-49dc-bec3-c93ae16c059a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: plotly in c:\\users\\user\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (5.22.0)\n",
      "Requirement already satisfied: tenacity>=6.2.0 in c:\\users\\user\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from plotly) (8.3.0)\n",
      "Requirement already satisfied: packaging in c:\\users\\user\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from plotly) (24.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install plotly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "15cbec65-ea3d-4d59-a70b-d7612d9ec441",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go  #to plot graphs\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd8bb2b7-4377-4c39-935f-d5c7b79c3c38",
   "metadata": {},
   "source": [
    "**Analyzing Price column**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "1056da47-82b1-44a5-b2fb-7fd8eb0b5382",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Count                   15072.000000\n",
      "Mean                      487.675292\n",
      "Variance                94691.505333\n",
      "Standard Deviation        307.719849\n",
      "Minimum                     0.000000\n",
      "25% (Q1)                  233.000000\n",
      "50% (Median)              585.000000\n",
      "75% (Q3)                  703.000000\n",
      "Maximum                   999.000000\n",
      "Mode                        0.000000\n",
      "Inter Quartile Range      470.000000\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "#Finding 5-number theory and other values\n",
    "summary = describe_series(df['Price'])\n",
    "print(summary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "bb597e5b-14da-4943-bf58-292333c50eec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the boxplot for the Price column\n",
    "plt.figure(figsize=(8, 6))\n",
    "boxplot = df.boxplot(column=['Price'])\n",
    "plt.title('Box-plot of Prices')\n",
    "plt.ylabel('Price')\n",
    "\n",
    "# Calculate the IQR and determine the outliers\n",
    "Q1 = df['Price'].quantile(0.25)\n",
    "Q3 = df['Price'].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "outliers = df[(df['Price'] < (Q1 - 1.5 * IQR)) | (df['Price'] > (Q3 + 1.5 * IQR))]\n",
    "\n",
    "for index, row in outliers.iterrows():\n",
    "    plt.text(1.05, row['Price'], row['Price'], horizontalalignment='left', size='medium', color='black', weight='semibold')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2817487b-5e7b-4620-ad1e-a466b26f3064",
   "metadata": {},
   "source": [
    "As we can see, the box-plot has unequal whiskers, which is quite expected as most of the books will have a minimum cost, irrespective of its quality, units sold etc. Also, there are no outliers, meaning that not a single book is exceptionally cheap or expensive in comparison to every other book."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "9e607b35-2a6c-4229-860a-9eb430f691c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the Gaussian distribution\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.histplot(df['Price'], kde=True, bins=100, color='green', edgecolor='black')\n",
    "\n",
    "# Add title and labels\n",
    "plt.title('Gaussian Distribution of Prices')\n",
    "plt.xlabel('Price')\n",
    "plt.ylabel('Frequency')\n",
    "\n",
    "# Show plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0447b99d-992a-43aa-a339-24cd45c9f3ef",
   "metadata": {},
   "source": [
    "The histogram also gives similar results just like the box-plot, where most books are in the price range of 600-800"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07e3e6d4-eff4-4f69-a196-c2117fd3b8a6",
   "metadata": {},
   "source": [
    "**Analyzing Duration in minutes column**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "b98963a7-f8bd-4ee8-b3a7-32da76be28a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Count                    15072.000000\n",
      "Mean                       549.968617\n",
      "Variance                199546.355660\n",
      "Standard Deviation         446.706118\n",
      "Minimum                      1.000000\n",
      "25% (Q1)                   301.000000\n",
      "50% (Median)               476.000000\n",
      "75% (Q3)                   673.000000\n",
      "Maximum                   8595.000000\n",
      "Mode                       417.000000\n",
      "Inter Quartile Range       372.000000\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "summary = describe_series(df['Duration in minutes'])\n",
    "print(summary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "f9d9b1e7-2d61-41da-8305-cefa71a49bb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the boxplot for Duration in minutes column\n",
    "plt.figure(figsize=(8, 8))\n",
    "boxplot = df.boxplot(column=['Duration in minutes'])\n",
    "plt.title('Box-plot of Duration in minutes')\n",
    "plt.ylabel('Duration in minutes')\n",
    "\n",
    "# Annotate the outliers\n",
    "# Calculate the IQR and determine the outliers\n",
    "Q1 = df['Duration in minutes'].quantile(0.25)\n",
    "Q3 = df['Duration in minutes'].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "outliers = df[(df['Duration in minutes'] < (Q1 - 1.5 * IQR)) | (df['Duration in minutes'] > (Q3 + 1.5 * IQR))]\n",
    "\n",
    "for index, row in outliers.iterrows():\n",
    "    plt.text(1.05, row['Duration in minutes'], row['Duration in minutes'], horizontalalignment='left', size='medium', color='black', weight='semibold')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "61841eb8-924c-4a3a-b683-d283b7425e64",
   "metadata": {},
   "source": [
    "As expected, the durations of the books have many outliers on the higher side, which means that all books are having a minimum certain length and some books are however exceptionally long."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "3bd391fa-455a-4e34-87a9-6025bef640a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the Gaussian distribution\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.histplot(df['Duration in minutes'], kde=True, bins=70, color='skyblue', edgecolor='black')\n",
    "\n",
    "# Add title and labels\n",
    "plt.title('Gaussian Distribution of Duration in Minutes')\n",
    "plt.xlabel('Duration in Minutes')\n",
    "plt.ylabel('Frequency')\n",
    "\n",
    "# Show plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "db6012b5-7854-48c2-af7e-66a893c7e428",
   "metadata": {},
   "source": [
    "As we can see, some books are exceptionally long to read and therefore we get a skewed distribution towards the higher side of the duration."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79e3a855-4d18-4d21-8fcb-5cea7a2f7b89",
   "metadata": {},
   "source": [
    "**Analyzing Language column**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "62514a12-f687-40e2-a5e7-3b1722393842",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the countplot for the language column\n",
    "plt.figure(figsize=(15, 7))\n",
    "ax = sns.countplot(data=df, x='Language')\n",
    "plt.title('Count-plot of languages of books')\n",
    "plt.xlabel('Language')\n",
    "plt.ylabel('Count')\n",
    "plt.xticks(rotation=45)  # Rotate x labels if needed\n",
    "\n",
    "# Add count values on top of the bars\n",
    "for p in ax.patches:\n",
    "    ax.annotate(f'{p.get_height()}', (p.get_x() + p.get_width() / 2., p.get_height()),\n",
    "                ha='center', va='center', xytext=(0, 10), textcoords='offset points')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "545c994a-9588-41ba-a18e-f220e0e1b01a",
   "metadata": {},
   "source": [
    "As we can see, out of approximately 15700 books, 14590 books are in English, 321 books are in Hindi and rest of the languages are minor in magnitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "f4ffc427-ecbe-4a6a-b318-a5ae13427e9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tLapUKjEhIeGSS8e0d1mWJ554QgwICBCdnJzEwYMHizt37rzsx33lypWN9peWlnbJJW3effddMSwsTFSr1WK/fv3E7du3i3369BHHjh3baLuUlBRx5MiRolqtFv38/MRZs2aJGzduvGhZluPHj4sjR44UdTqd6O3tLd57770NS9z8+9jffPONGBcXJ6rVarF79+7imjVrxEmTJolxcXEXfTw+/fRTsU+fPqKTk5Po4uIiJiQkiP/973/FnJwcURRF8cCBA+Ktt94qhoaGimq1WvT19RUnTJgg7tu3r0UfbyJqPUEUbWSWMxERtYrZbIaPjw9uvPFGLFq0qMOP37NnT/j4+Fw074+IbA/n8BER2YHa2tqL5r198cUXKC4uvuRt8izJYDBcdEp48+bNOHz4sNWPTUSWwRE+IiI7sHnzZjz22GOYPHkyvLy8cODAAXz++eeIj4/H/v37W7XeYmulp6dj5MiRuP322xEYGIjk5GR8/PHHcHNzw9GjR5u8nR0R2QZetEFEZAfCw8MREhKCd999t+FijDvvvBNvvPGGVcseUL/US58+ffDZZ5/h3Llz0Gq1GD9+PN544w2WPSI7wRE+IiIiIgfHOXxEREREDo6Fj4iIiMjBsfAREREROTgWPiIiIiIHx8JHRERE5OBY+IiIiIgcHAsfERERkYNj4SMiIiJycCx8RERERA6OhY+IiIjIwbHwERERETk4Fj4iIiIiB8fCR0REROTgWPiIiIiIHBwLHxEREZGDY+EjIiIicnAsfEREREQOjoWPiIiIyMGx8BERERE5OBY+IiIiIgfHwkdERETk4Fj4iIiIiBwcCx8RERGRg2PhIyIiInJwLHxEREREDo6Fj4iIiMjBsfAREREROTgWPiIiIiIHx8JHRERE5OBY+IiIiIgcHAsfERERkYNj4SMiIiJycCx8RERERA6OhY+IiIjIwbHwERERETk4Fj4iIiIiB8fCR0REROTgWPiIiIiIHBwLHxEREZGDY+EjIiIicnAsfEREREQOjoWPiIiIyMGx8BERERE5OBY+IiIiIgfHwkdERETk4Fj4iIiIiBwcCx8RERGRg2PhIyIiInJwLHxEREREDo6Fj4iIiMjBsfAREREROTgWPiIiIiIHx8JHRERE5OBY+IiIiIgcHAsfERERkYNj4SMiIiJycCx8RERERA6OhY+IiIjIwbHwERERETk4Fj4iIiIiB8fCR0REROTgWPiIiIiIHBwLHxEREZGDY+EjIiIicnAKqQMQEbVHTZ0JFXoDqvQmVNYaUaE3oFpvgtEsQhRFiADMogiziPq3xYvflskEaJQyOKvk0CjlcFYp4KSUX/C2HE5KOWQyQeqXS0TUJix8RGQzag0mFJTrkV9Ri/zyWuSX61FQXouCCj1KqutQWWtEpd6Iir//rtIbYTSLHZZPragvhS4aJTy1KnhpVfD4+29PrQo+Lmr4uKjh66KBr4saHlpVh2UjImqKIIpix323JKJOrbBSj7TCKqSeq0RGcTXyyvQouKDcldUYpI5oUSq5DD4uagR7OCHMyxlhXtr6vz21CPVyhpuTUuqIRNRJsPARkUXV1JmQWliJtMIqpJ2rQmph/Z+0c5UorzVKHc+muDsrEebpjFAv7d9/OyPKR4tYf1fo1DwBQ0SWw8JHRG2WWVyNpOwyJGWX4Wh2Gc4UVCKvvBb8rtI+ggCEejqja4Ar4gNc6/8OdEWQu5PU0YjITrHwEVGLZBQ1LndHc8pQWu1Yp2BtnbuzEnH+Luga4Ib4ABd0C3RDrL8L5LyYhIiawcJHRBcpqzZgT3ox9p0tRlJWGY7llDvc/DpHoVXJ0SvUA33DPdE33AO9Qj3gpJJLHYuIbAwLHxGhrNqAXWlF2J1ajF2pRUjOK0cHXvxKFqSQCegW6Iorwj0bSqCXTi11LCKSGAsfUSdUWl2HXanF2J1WhF2pxTjJgufQIr21uCLcA4OivHF1Fx94crkYok6HhY+oE6gzmrE3vRh/JhfgrzOFOJlfwQsrOimZACQEu2NoFx8Mi/NFYpAbF5Qm6gRY+IgcVH55Lf5MLsCfJwuw/UwRKvVcEoUu5qlV4eoYbwyN9eXoH5EDY+EjciDJeeXYeCwfG0/kIym7jKN41CoyAUgMdsfQWB+MiPNDQrCb1JGIyEJY+IjsmCiK2JtegvVH8/D7iXxkFFdLHYkcSKinM8YnBmB8QgC6B7H8EdkzFj4iO3QspwyrD+Xg58M5yC2rlToOdQKR3tr68pcYgDh/V6njEFErsfAR2YmMomqsPpSNNYdzcLqgUuo41IlF++owPiEA1/YIQLSvi9RxiKgFWPiIbFhhpR5rD+dg9eEcHMwolToO0UVi/VxwXc9A3NQnGH6uGqnjENFlsPAR2Zhagwm/Hs3FTwdzsP1MIUxcII/sgFwmYGgXH0zpF4rhcb683RuRjWHhI7IRqecqsWJ3Bn44kMV71JJd83NVY1LvYEzpG4pQL2ep4xARWPiIJGUwmbHhWD5W7D6LnalFXEaFHIogAAMjvXBL3xCM7e4PtYL3+CWSCgsfkQSyS2vw9e4MfLsvE+cq9FLHIbI6D2clJvYKwtT+obzQg0gCLHxEHcRsFrH5VAGW78rA5pMFvHctdUqCAAzp4oN7rozElTHeUsch6jRY+IisrNZgwsp9mfjsrzScLeLCyETnxQe44p4rI3Bdz0Ao5TKp4xA5NBY+Iispqzbgi53pWLojHUVVdVLHIbJZfq5q3DkwHLf3D4Obs1LqOEQOiYWPyMJySmvw2bY0fLs3A1V1JqnjENkNZ5UcN/UJxt1XRiDMSyt1HCKHwsJHZCEn8yrwyZYU/HwkBwYTv6yI2komACPj/fCfYdHoGeIudRwih8DCR9ROe9KK8fGWFPx5soDLqhBZ2JAuPnh0ZAx6h3pIHYXIrrHwEbXR/rMlePu3k9iZWiR1FCKHd1WMN2aOjEGfME+poxDZJRY+olY6kVuOt387iU3JBVJHIep0rorxxhOjY3mql6iVWPiIWiitsArzNpzEuqRcnrolktjIeF88PioWXQNdpY5CZBdY+IiakVNag4W/n8YPB7Jg5GrJRDZDEIBx3QPw2KguiPbVSR2HyKax8BFdRmGlHh/8eQYrdmegzmiWOg4RXYZCJuC2/qF4bGQXeGhVUschskksfET/Umsw4aPNKfhsWyrX0SOyI64aBR4ZEYNpg8J55w6if2HhI7rA2iM5eP2XZGSX1kgdhYjaKMJbi1nj4jGqq5/UUYhsBgsfEYDkvHK8vOYYdqUWSx2FiCxkUJQXXpjQFfEBvLCDiIWPOrXS6jrM23AKX+3JgIkXZBA5HJkA3HxFCJ4YHQsfF7XUcYgkw8JHnZLJLOKr3WfxzsZTKKk2SB2HiKxMp1bgoWHRuOeqCM7vo06JhY86nd2pRXj55+M4kVsudRQi6mCxfi6Yc2MC+oTxVm3UubDwUadRVKnH7LXHsfpQjtRRiEhCMgG4rX8onh4bBxeNUuo4RB2ChY86hdWHsvHKz8dRXFUndRQishF+rmq8cl03jO0eIHUUIqtj4SOHlltWg+d/Osr73hLRZY3u6ofZ13eHv5tG6ihEVsOZq3Zq6dKlcHd3b/d+hg4dipkzZza8HR4ejgULFrR7v1ITRRFf7c7A6He2suwRUZM2HM/HyHe2YNmOdJh5tT45KI7w2aDp06ejtLQUq1atavT45s2bMWzYMJSUlECtVqOiogK+vr7tOtbQoUPRs2fPhpJ37tw5aLVaODs7t2u/UjpbVIVnfkjCztQiqaMQkZ3pGeKONyYlIM6fa/eRY+EIn51ycnJqd9m7FB8fH7steyaziEVbUzFmwVaWPSJqk0OZpbjuve34cPMZjvaRQ2Hhs1P/PqX78ssvo2fPnvjyyy8RHh4ONzc3TJkyBRUVFQ3bVFVV4c4774ROp0NAQADmzZt30X7t9ZTu6fwK3PjRDrz2ywnUGsxSxyEiO1ZnMuOt9ScxZdEuZJVUSx2HyCJY+BxISkoKVq1ahbVr12Lt2rXYsmUL3njjjYb3P/XUU9iyZQtWr16NDRs2YPPmzThw4ICEiS3jy11nce37f+FwZqnUUYjIgexJK8Y1C7bhxwNZUkchajeF1AHo0tauXQudTtfoMZPJ1ORzzGYzli5dChcXFwDAHXfcgU2bNuG1115DZWUlPv/8cyxfvhwjRowAACxbtgzBwcHWeQEdoKSqDv/94Qg2Hs+XOgoROagKvRGPf3cYm5ILMGdiAtycuW4f2ScWPhs1bNgwfPTRR40e2717N26//fbLPic8PLyh7AFAQEAACgrqr1BNSUlBXV0d+vfv3/B+T09PxMbGWjh5x9iRUojHvz2MvPJaqaMQUSew7kgu9qeX4O3JPXBljLfUcYhajYXPRmm1WkRHRzd6LCur6dMKSmXj3zwFQYDZ7Fjz2YwmM+ZtPIVPtqSA86mJqCPlldfijsW7MWNQBP47NhYapVzqSEQtxjl8nURUVBSUSiV2797d8FhJSQlOnTolYarWOVtUhUkf78RHm1n2iEgaoggs3p6G697/CyfzKpp/ApGNYOHrJHQ6He6++2489dRT+OOPP3D06FFMnz4dMpl9fAr8sD8L49/lhRlEZBtO5Vdi4gfb8dNBXtBB9oGndDuRuXPnorKyEtdeey1cXFzwxBNPoKysTOpYTaquM2LWj0lYdShH6ihERI3UGEx47NvD2Jdegpeu7QaVwj5+gabOiXfaIJuVeq4S93+5H6cLKqWOQkTUpB4h7vhoam8EujtJHYXoklj4yCatP5qHp1YeRoXeKHUUIqIW8dSqsOCWnri6i4/UUYguwsJHNsVkFjH3t5P4ZGsK+JlJRPZGJgCPjuiCR0ZEQxAEqeMQNWDhI9tRU4Lqtc9g3PHRSK/RSJ2GiKjNhsX6YP4tPeHurJI6ChEAFj6yFQXJwNdTgJI0lPgPRr+M/8Bg5m/HRGS/gj2c8PHtfdA9yE3qKERclsWepaenQxAEHDp0CACwefNmCIKA0tJSSXO1WvI64LORQEkaAMAjbzu+i94gcSgiovbJKqnB5I93Yv3RPKmjELHwWcPQoUMxc+ZMqx8nJCQEubm56N69u9WPZRWiCGx+E/hmKlDXeAHTXhnL8Hz4SYmCERFZRo3BhAdX7McnW1KkjkKdHAufHZPL5fD394dCYYfLKdZVAd/dCWyeA+DSswruLnobo72LOzYXEZGFiSLw+q/JePbHIzCaHOt2l2Q/WPgsbPr06diyZQsWLlwIQRAgCAJSUlJw9913IyIiAk5OToiNjcXChQsvet7EiRMxZ84c+Pn5wd3dHbNnz4bRaMRTTz0FT09PBAcHY8mSJQ3P+fcpXbtRngN8PgY4sabJzQRDFT6Qz0OQRt9BwYiIrOfrPZmYvmQvymsNUkehToiFz8IWLlyIgQMH4t5770Vubi5yc3MRHByM4OBgrFy5EsePH8eLL76IWbNm4bvvvmv03D/++AM5OTnYunUr3nnnHbz00kuYMGECPDw8sHv3bjzwwAO4//77kZVlx7fyKTgBfDYKyE9q0ebKsjSsCVgKucDfionI/v11phA3frgDmcXVUkehToaFz8Lc3NygUqng7OwMf39/+Pv7Q61W45VXXsEVV1yBiIgITJ06FTNmzLio8Hl6euLdd99FbGws7rrrLsTGxqK6uhqzZs1CTEwMnn32WahUKvz1118Svbp2St8OLB4LlLeusHrlbsHX0X9aKRQRUcc6U1CJGz7cjv1nS6SOQp0IC18H+eCDD9CnTx/4+PhAp9Ph008/RUZGRqNtunXrBpnsn/8SPz8/JCQkNLwtl8vh5eWFgoKCDsttMcdWAV/eANSWtunpfTMX48mwMxaNREQklcLKOty2aBd+Psz7hFPHYOGzIJPJBLP54lOP33zzDZ588kncfffd2LBhAw4dOoQZM2agrq6u0XZKpRIvv/wyevbsCQAQBAFKpbLRNoIgXPIYNm3Xx8D3MwBT2+fiCRDxUOlcDPXkb8RE5Bj0RjMe+eYgPtrMK3jJ+jp14auoqMDUqVOh1WoREBCA+fPnN1pSRa/X48knn0RQUBC0Wi369++PzZs3Nzx/6dKlcHd3x5o1a9C1a1eo1WpkZGRg9+7d2LVrF+68807odDrcd999iImJweTJk3HXXXchJiYGX331Faqr/5nDUVtbi3379mHevHk4cuQIEhIScOrUKXz00UcN2wwdOhTFxcVYs2YNPD090bdv3476ULWNKAIbXgDWPw2I7S+pgr4Cn6rmw1fNCc9E5BhEEXhzfTLe+DVZ6ijk4Dp14Xv88cexfft2rFmzBhs3bsS2bdtw4MABfP/990hISICbmxvmzZuHV199FUeOHMHkyZMxduxYnD59umEf1dXVePPNN/HZZ5/h2LFj8PX1hUKhwO7du5GSkoJNmzYhMTERSUlJ6NOnD2677TZMmzYNNTU1yMjIwPkbnZhMJri7u2Pq1KmIi4vDfffdh9zc3ItGASsrK6FSqbB7924888wzAIBdu3Z13AetpcwmYPXDwI53LbpbVekZ/Bz0JQSBN4ghIsfx8ZYUPPdTEsxmfm8j6+i0ha+iogLLli3D22+/jREjRqB79+5YsmQJTCYTEhMTkZycDIPBAJVKhaVLlyIqKgpPPvkkrrzyykZLoxgMBnz44Ye47bbb8Ouvv8LZ2Rlubm5QKBTYsWMHBgwYgMDAQABAZmYm/vvf/2LZsmXo1q0b9Ho9nn/+efj5+WHVqlWoqKjA119/jbKyMhQVFTUc48JFnFUqFbKzs/Haa69h0qRJAIDdu3d3zAetpYz6+jX2Di23yu79cn7Hl9FbrbJvIiKprNidgce+O8S1+sgqOl3hOz965+PjA4PBgAULFqCqqgrTp0/HtGnT4Orqit9//71hPl5dXR22b98OnU4HjUaDTZs2Ye7cufDy8sKCBQugVCqRmJgIACguLoYgCKirq7vkYshyuRyRkZHQarX44IMPAABvvfUWPDw8GopceXk5cnNzMWfOnIbnnT17FvHx8di2bRt8fX0RFBQEAAgPD8d1110HQai/5+zQoUMhiiLc3d2t/FFsgr4SWDEZSF5r1cMMzlqER0NTrXoMIqKOtvpQDh5Yvh+1BpPUUcjBdKrCl5ubi1tvvRV33XUXfvzxRwDA2LFjIYoiTCYTNm3ahKKiIhgMhoZTrQBgNptRVVUFvV4PrVaLrl27om/fvjh27BgMBgNkMhkyMjKwatUqAEBJSQnc3d0bitjq1asB1J+2BQCFQoH169cDAIxGI1JSUlBXVweTyQS5XA5vb29cffXVDcf/+eefcfLkSZjNZuTm5uLIkSMN77Opiziqi4EvrgfStlj9UIJoxsyyuRjsUWb1YxERdaTfTxRgxpK9qNIbpY5CDkQQL2w2Dur777/HK6+8gtOnT0Ov12Pw4MGorq7GwYMHMXLkSBw8eBByubzZ5U7kcnlDaWvJ401t19Rz3Nzc4Ofnh1OnTl12X9OmTcPSpUsxceJEuLu7Y+nSpc0e36oq8uqXXSk43qGH1XvEYlDRLBTVKZvfmIjIjvQIcceyGX3h7qySOgo5AIcf4btwVO/YsWPo378/9u3b17AG3vbt2zFv3jz4+fk1PEetVkOlavwFplQqLzuS9swzzzRaPw8AnJycLtruwm2mTp3a6H3nRwNlMhkUCgXy8vIavW/8+PEtebnSKM0AFo/p8LIHAOqSk/g55OsOPy4RkbUdzizFzZ/sREF5rdRRyAF0isJnNBpx4403IioqCjt37sSmTZug0+kgk8mg1+vxwAMP4NixYwDqy5VKpbqo8J0/zXu+tF04T+61115rVAY1Gg38/f2bzDVw4MBGb58vfGazGcXFxY3mAI4YMQJr166FRqNp/QfA2sqygWXXAiXpkkUIzF6PxTHbJTs+EZG1nMqvxORPdiK3rEbqKGTnHL7w9ejRAyNGjEBCQgImT56Mzz77DF27dkV4eDj69esHmUyG1157Dc7OzgDqi5fJZEJNzaW/uM4Xu9LS0obHxo8fD09Pz4a36+rqkJaWdtFzLxzh+7//+79Gb19YGFUqFXx8fBre3rFjB9atW4eYmJiL9rlq1SrpTueW5wLLJkha9s4blvUxHgw5K3UMIiKLO1tUjamLdqOggiN91HYOX/jkcjk2btyIX3/9FW5ubnjhhRcQFRWFsrIy1NbWwmg0Qq/Xo7KyEgAgiiJqamouGrE7z8XFBQAajcANGjQIRmPjybXnR+wux2g04vbbb7/k+/793GnTpuHOO+/EiRMnWvCKO0hFfn3ZK7aNK2UF0YSnKt7CFW4VUkchIrK41MIqTF20G0WVbb9jEXVuDl/4gPoCNXjwYDzxxBPo0aMHysrKcOjQIaSkpEAmk+HFF19s2DYqKgqiKEIURajVagD1p3P/7cJC+NVXX6Gqqqrh7RdffBHdunW76Dn/XqolMTHxkqdpAwICGr09c+ZMFBUVoU+fPg2PSXqRRuW5+tO4RbZ1b1tZbQm+1L0LNyWvbCMix3O6oBJTP9uN0uq65jcm+heHL3y7d+/GnDlzsG/fPmi1Wtxzzz1QKBRISEjAXXfdheuuuw6iKKJ79+4Nt0Y77/xdLi68mraion4EKTg4uOGx5OTkRtvU1dU1uhvHv8lkMgiCgKeeegq1tbUXFUFfX99Gb0+aNAkbN25Eba0NDOdXFdWXvcKTUie5JKeiY1gb9p3UMYiIrCI5rwJ3Lt6D8lreYpJax+ELn6urK7Zu3Ypx48ahS5cueP755zFv3ryGOXdDhgyByWSCv78/+vfvD1dX14bnnl+x5vwFGBfOucvIyGgYnXNycoJCoWh4/5w5c2AwGC4aqTs/T1Cj0UCpVDbs/8LTwVqtFrfcckvDMf39/dG3b1/ceuutSEpKarSfjlamL8PKv2YD52zo1PIlhGStxcfRNnb3ESIiCzmSVYbpi/dwnT5qlU6xDl9LTJ8+HaWlpQ2LJwP1d67o2bMnFixYIFkuW1FlqMK9G+5FUmES7nVLwCOH1kkdqUmiTIFXPV7D4uwQqaMQEVlFvwhPLJvRD04qudRRyA44/AhfSy1durRR2aN/6E16PLzpYSQV1o8wLipLwpu9J0icqmmC2Yjna+aip2ul1FGIiKxiT1ox7v1iH2/DRi3CwkdNMpqNeHLzk9iXv6/R48tLjuCV3uMhoumrkaUkqy7EV64fQKvgN0Mickx/nSnEg8v3w2CykVtsks3iKV26LFEU8fz257EmZc1lt7nWIwGvHlwPuWi7pSotZCKGnb5Z6hhERFYzsWcg5t/Ss9klwajz4ggfXda8ffOaLHsA8HNJEp7qNRoGme3eyzYicxXejd7X/IZERHZq1aEcvPFrstQxyIax8NEl7du6EsuOL2vRthtLjuGxHsNRJ1dbOVXbXZvzHqYG5Egdg4jIaj7ZmorFf118lycigIWPLqH8l1+gvf8lzD/eG0ILT/hvKT2BhxKvQo1KmiVjmiOYDZhd9xa6uVQ1vzERkZ16dd1xrD3CX27pYpzDR41U7dmDzLvvgfj33UXKh/XGQ/2PQS+0bI5eb7dofHhiL7R627zFWaVPb/TPeRxVJv6uQ0SOSaWQ4cu7+qF/pJfUUciG8KceNSjJq0LqB181lD0AcP3zABb/Hg0Ps1OL9nGg7AzujeuDMid3K6VsH925A/gpcrXUMYiIrKbOaMb9y/cj5RyXpaJ/sPARAKC6vBpr3z+Mne4TUXXV5EbvU+47ho9X+SDM6N6ifSWVp+LumAQUa72tkLT9umSuxNuRh6WOQURkNaXVBsxYshdFlXqpo5CNYOEjGAwGpK3eBrV6Fwx6E/Yqh6FkwiONthFOpuLtr1XoVRdwmb00drLiLGZEdsE5V39rRG63SfkLcJN/vtQxiIisJqO4GvdwYWb6GwsfYcPB9Uh3T0dXr27w8v0LgtyIg5WxyL3lfxAvWNNJzMrBrMUVGF0V2aL9plZmYXpIGHI9bO/2ZoJJjzeNcxGjrZE6ChGR1RzMKMXj3x0Cp+sTC18n996m03jyZzNSZAJSI0+ia9BgeLpuhZNWjxP5Hki9dQFE9T/z98SSUty7KBO3lcW3aP8Z1bmYFuCLTK9wK72CtpNX5uAH70+glnGFeiJyXL8k5eH9P85IHYMkxqt0O7H1R/Pw4Ir9EEVAEERM71uERNdiBKd3RdbZ3ag090R5kQ5+fnLEb3wZsuK8f56sUGDHHT2wwL9lc+F8NV5YVFSJyILTVno1bXc85FaMO32t1DGIiKxGJgCfTbsCw+P8pI5CEmHh66SO55Tjpo93oLqu8dyO8XHluDokD8HZEahKT0cxAlCU4wM3TyUSD74LZdrRRtufvqUfnos80KJjeqrd8WmpEbF5xy32OixlReAsPJfaXeoYRERW46JRYM3DVyLCWyt1FJIAC18nVFSpx3Xvb0d26aXnr/UJqsaNXfMQWOgJ9VkTsg11KMiMhEarQO/c76E5sLHR9ufG9cUjPQ7BhOY/lVxVLvikUobu2UkWeS2WIiqc8IjzG/i5wEfqKEREVhPjq8NPDw2GTq2QOgp1MM7h62RMZhEPfXXgsmUPAPZnO+PTPUFI8yhDeUwdYlx84RN4ELXVBuzxuhEVI+5stL3PL3vx+bZucDY3fz/d8roK3Ks14kBo73a/FksSjDWYL85FuFOt1FGIiKzmdEElnuBFHJ0SC18nM2/DSexKLW52u7NlaszfHoRUjRkZ0VmI802Et+92AAbsM/dH4Q1PN9re+a9D+Hx9GHzNzZ8qqDRU4QFVJXZF9Gvry7AKRUUWVvl9BqWM3wiJyHH9diwfH/zJizg6Gxa+TuSP5Hx8tCWlxdtX6BV4e2sAjumdkBZ5FF2CBsLLfTvU2jocKQlF5q1vQZT/c1pAfjgZ7690R4yx+dv51Jhq8bC8BFujBrXptViLe94OfB+9XuoYRERW9c7GU/gzuUDqGNSBOIevk8gqqcaE9/5CabWh+Y0v4cZuZRgYkI/QzBicSz+KUlNXlBXqEBwIRK+ZBVllWcO2gp8v3rnNGTs1Wc3uVyFT4E1FMEaf3NqmXNayOOAFzE5r2dIzRET2iBdxdC4sfJ1AndGMyZ/sxOHM0nbtp39oNa6PzUVwvj+M6YUoMHqhKMcHXj4KdPvrdShy0xu2FVxdsWxaINbqmj9tIBfkeFUdgWtP/NGufJYkKp3xoOZNrD/Hm48TkeOK8dVh1UODoeVFHA6Pp3Q7gTm/nGh32QOA3RnO+Hx/EFJ9CmGKc0aEzgTfkFQUnTPiQL9nURfXt2Fbsbwc0z5Nw11FzS91YhJNeF6fiu+7jWp3RksRDNV4TzYPwRreh5KIHNfpgkq8uPqY1DGoA7DwObh1R3KxdEe6xfaXUqzBgh2BOONUi6LoCnRx94dv0EFUlhuwJ+JuVA+8rmFbUa/H2M+T8Ex2r2b3axbNmF19CisSxlosa3spy9KxOmAJ5ALvxEFEjuuHA1lYfShb6hhkZSx8DiytsArP/HDE4vstrVHi7W3BOCrKkRGVhhi/RPj67oTZVIc9zmNRds0D/2xsMqH3F3sx92Tzy7CIEPFG5XF81mOcxTO3lVfuVnwbvUnqGEREVvX8T0eRWVwtdQyyIhY+B1VrMOHB5ftRoTdaZf8ms4APdwZgW5EHzkQcQ3joFfD12A21cy321yQgb/LLjbYP+3EPPt3XAwqx+U+5heVH8V7P8VbJ3RZ9Mpfi6TDbuyUcEZGlVOiNeOSbgzCaeEbDUbHwOahXfj6G5LwKqx/nuyQPrE4LRErESfhFdUOAy3G4eVfg+DkfpN82H2aVumFb9437sWRzLNxETbP7/bQsCXN7TbBm9BYTIOKBkrkY7lUidRQiIqs5mFGK+b+fkjoGWQmv0nVAvx/Pxz1f7OvQY8Z612JqjzyElLhDllqDvDodCnN8ERAgQ+wvL0BWVtiwrblrNJ4cX4IsRVkTe6x3i0cCnjvwC4QW3LbN2urcI3F1yYvI06ukjkJEZBUyAVh+T38MivKWOgpZGEf4HExxVR2e+bHj71N7srD+Yo7TrpWoiZchyk0B35AzyM014/DI12AMjWvYVnb8DOZ/q0F3g1+z+/22JAkv9B4HkyC3ZvwWUZWmYk3QlxAE6csnEZE1mEXgsW8PoaSqTuooZGEsfA5m1o9JKKyUZimR4hoV5m4LRLJMRE50AWI8g+EXdAilxQbsS3wM+h5DG7YVM7Lx8tIaDK0Ja3a/q0uS8Eyv0TDKpF8nyjdnE1ZEb5E6BhGR1eSX6/HU95a/4I+kxcLnQH7Yn4X1x/IkzWAwybBguz/2VuqQFnUakQFd4ee/B4a6Wuz2uwWVQ29t2NZcWIyHPsvD5PLYZve7vuQYHu85EnVydbPbWtvAzEWYGZoqdQwiIqv5/UQ+vtiZLnUMsiDO4XMQOaU1GLNgKypqrXNVbluMjK7EmPA8hGZHIi/9OIorE1FTpUYPlzPwXD3/nw2VSmyeloAPfZr/jXKwexwWHN0GjaHGismbJ6pdcYf8TfxV7CZpDiIia1ErZFj3yFWI9tVJHYUsgCN8DkAURTy58rBNlT0A+P2MDkuTgnEqKANesZEIdj8DV69yHCqLRvaU1yEKQv2GBgOGfn4QL51tfq2+7aXJeLDbIFSrpf0GJOjL8bl6PnxUbbs3MRGRrdMbzXj6hyMwmzku5AhY+BzAku3p2JFSJHWMSzqWr8H7O4OQ7F4MxLshwq0c3kH5OJnnipRb34VZ8/dNu0UR3b7ag4VHe6G5ayL2lZ3GvXF9UaGRdnRNXXIKP4eskDQDEZE17T9bYtG7NZF0WPjs3JmCSrz1W7LUMZqUX6XEW38FIllVh9I4PaI9NPALPoOMHBmOXT8PJp/ghm0Dft6Lz3YlQCM2fYHGkfIU3N2lB0qdPa0dv0n+2RuwNOYvSTMQEVnT2xtO8i4cDoCFz44ZTWY88d0h1Bpsf2X0OqMM8/4KwL4aJbKjshHtEwr/4MMoLDDi4JUvwhD9z/12XTYfxOINkfAyOze5zxMV6ZgRFY9Cl+aXd7GmIVkf46GQdEkzEBFZS3WdCU9b4Tad1LFY+OzYp9tScTir+cWLbcmS/T74pcAbKVEnERoQi4CA/aiprsXeLvejpt8/99BVHDiOj37yQqTRo8n9nanMxIywCOS5B1k7+mUJohlPVMxFP/dyyTIQEVnTjpQifL0nQ+oY1A68StdOZRZXY9T8LXYxuncpPYNqMblrHiLzAlGSmob8ijjoq53QS7YPrhsWN2wnBPrjzSkq7FPnNLm/IGc/fJabj+Bi6b4h1Xp1xcCCZ1BikH69QCIiS3NRK7Dh8asR4OYkdRRqA47w2akXVh+127IHAIeyNfhwVyCSffLhHOeHMI8MuHiWYp+hD85Neq5hOzEnD08vKceY6sgm95ddnY9pft5I84mydvTL0hQdx89h30p2fCIia6rQG/HcT0eljkFtxMJnh9YdycXmk+ekjtFu2RUqvL0tEMecq6GPVyHSowbegXlIKgpExm1vQ5TXj5SJJaW459MM3FHatcn9FdQWYrqXDqf84prczpqCs9bh0+hdkh2fiMia/kguwE8Hs6SOQW3AwmdnKmoNeOXnY1LHsJgqgxxv/xWAA6KAorhyRHvp4BdyBmdynHDq5ndh1rkDAMSaWly76DieyO3Z5P6K9SW4y12BY4HdrR/+MkZlf4C7gzIlOz4RkTXN/vm4ZLfwpLZj4bMzb/92EgUVjvWFJooCFu32xcZzbsiIyUCEXwgCQo4gJ9+EI9e8CWNQdP2GRiP6L92HOWeaXqC5rK4c9+rMOBTSq8ntrEUQTXiuei56u1VKcnwiImsqqTbgtXUnpI5BrcTCZ0eOZJXiy11npY5hNauPu2LFyUCcCktBUHAkggMPo7KiFvv7PAV9t0EN20Wv3IMPD/aEHMJl91VhqMR9mmrsCe/bEdEvIqspxHKX9+CisK27nxARWcKqQ9nYf7ZY6hjUCix8dsJkFjHrpyQ4+h1u9mWp8fG+ICQH5sIjOgRhvicBoQJ7Q+5E1ZWTGrbzXr8Pi7d2hU5UXXZfNcYa/EdRim1RAzsi+kWcC5Pwc/gPkhybiMiaRBF4ac0x3nbNjrDw2YllO9JxNLtzrPN2tkyFt//yw3G3UgjxHoj0zoezazH2qkagZMLDDds5bT+MRetC4G+6/H119SY9HkUBNsVc1RHRLxKetRrvR++V5NhERNZ0NLsc3+zlfGV7wcJnB/LKavHOxlNSx+hQFXol3twagAOCARWxRkR7G+AVmIODlfHIvWU2RKH+dK486STeW+mKOIP3ZfdlMBvwpCkbv8QN66j4jYzPeR93BGZLcmwiImt6e8NJlFUbpI5BLcDCZwde//UEKvWdby6YWZTho12+2FypRV6XQkR5u8Iv9AxO5Hsh7dYFEFUaAICYloFXvzRhcG3IZfdlFI14ti4NP3Ud2VHxGwhmA16pfQsJLlUdfmwiImsqrqrDvI0npY5BLcDCZ+MOZ5ZizeGm7zLh6FYeccd36b5IjTqLMP9ABIUexdl8GY7fuAAmz/r76Ir55zDzs0JcXxlz2f2YRTNeqjmNrxLGdFT0BrLqc/ja/UNo5fa7WDYR0aWs2J2BE7mdY8qRPWPhs3GvrTsB3vwO2J7uhE8OBSM5JAu+YUEICzqGklI9Dg19FYbwbgAAsaICt3+SgnuLEi67HxEiXq88gSWJ13RU9Aa6cwexOvKnDj8uEZE1mcwiXlrjOOvDOioWPhu2/mge9qTzsvfzzhQpMW+7H456FsGpiy/C/VNgMFVgX7dHUNu7/lStWFeHUZ8dxqzMptfge6fiGD7sMa4jYjcSnfkD3ok62OHHJSKypj1pxZ3+bJStY+GzUQaTGW+uT5Y6hs0prVXhrW2BOKiqhSleg2i/Qmi0RdjjNQkVw2+v38hsRs/lezEvuekFmj8qP4p3eo3vgNSN3ZC3ELcE5HX4cYmIrOn1X06guq7zzTe3Fyx8NurLnWeRVshJ/pdiNAt4b4cvttYqUBZXhWg/Mzz8srFPHIiiG/7bsF3IT3uwaE8iVKL8svtaUpqEOb0mQGxiEWdLE0x1mGOYiy7amg47JhGRteWW1WLR1jSpY9BlsPDZoLIaA97747TUMWzeVwc98UO2F7Ki8xDu5wL/0DM4XBKGrFvfhCirL3lumw5g8R8xcDNrLrufr0uP4OXe42AWOu7LQV6Zi++9PoaT3NRhxyQisrbPtqWipKpO6hh0CSx8Nuj9P06jhOsatcifKVp8ejQAZ8JyEBzkg9CwEzhd4IwzUxbCrHUFAKj2HMWna/wQanK/7H5+LEnCs73GwihTdFBywLVgL36MXNdhxyMisrYKvREfbj4jdQy6BBY+G5NZXI1lOx33frnWkHxOjXd2+eOIbyHcI3wQGXIKeSVGHB0/F0a/MACAcCIF875WIbHO77L7+aXkKJ7sORIG+eVv12Zp8Znf4PXIpA47HhGRtX2x8yzyymqljkH/wsJnY95Yn4w6I9dqa63CaiXe2uaPA9pyyLvoEB2YiZq6ChwY8BzqYvsCAMTMHLywtAbDq8Mvu59NJcfxSOJQ6BWXPwVsaVMK5mOiX0GHHY+IyJr0RjMWbuK0JFvDwmdDkrLKsO5IrtQx7FadSYb52wOw1QjUxovoElAOpeYc9kTejeoB1wIAxKJiPLgoB1PK4i67n79Kk/FQ9ytRrdI2PPb6Nj36LqqEy+vl8J1bgYnfVONkYdPz744VmDDpu2qEL6iA8Eo5FuzSX7TNiiMGhM49h2XP3QPz1o8avc9Ylo/sT++DWV/dmg8DEZHkVu7L5IWHNoaFz4Ys3NS57pdrLV8e8MKqAleciytDVIAAd69M7NFeg7Kx9wEAxOpq3PhpMv6voMdl97G77BTuj++HSk39PMAtZ414qK8Ku+7WYuMdzjCYgdHLq1FVd/lVsasNQKS7DG+M1MBfd/FVwIXVZtzzcw3eHqXBhqlOqEnagLqU3Q3vL9rwITyGTIdM7dzWDwURkSSMZrHT3QPe1rHw2Yij2WX4/QRP61nKhlM6fHbCF+mReQgPckFASAr263sgf/KL9RsYjbhq8QHMTrv8Wn2HylNwT2wvlDl7YP3tWkzvqUI3Xzl6+Mux9HoNMspE7M+9/Chf3yA55o7WYEp3JdSXWBkmtUSEm1rALd2V6Bskx/AwEVOE3wEAVce3QJAp4Bw7qF0fByIiqaw9koPjObzlmq1g4bMRnO9geUl5aryzJwDHAvLhG+qB8PCTOFHsg/Tb3oFZpQZEEXHf7MF7R3pBuMxA3bHyNMyI6oYinU+jx8v+Pjvr6dT29ftiPGWoNog4mGtCcY2IvdkmjFEdxlO++1G6bTk8Rz3Q5n0TEUlNFIG3N5yUOgb9jYXPBhzLKcPG4/lSx3BI+ZVKvPGXPw64lcA5ygNRoSnIKpHh5KQFMLt6AQD81u3F4h0J0IiXXpLldGUGpodHI98tEABgFkXMXF+LwSFydPe9/KLOzfFwErBsohPuXFWDfosqcWcPJcZEK7B/xRvod/VQGMvykbPkEeR8/h9UJf/V5uMQEUnlj+QC7OMtQm0CC58NeJeje1ZVa5Tj7W0B2A4DxDgluoTkoqKmCodHzYExJBYAoN16EIt/i4C3WXvJfaRXZWN6cDCyPUPx0LpaHC0w4ZubnNqd7YZ4JZIe1OHMIy54eagGW9KNSMrT45eBR1Cy5k14jrgXPhNnoejXd2GqKm338YiIOhpH+WwDC5/ETuSWYwNH9zrEZ/s88XOpM0rj69AluAqC8hz29XwctYlXAQAUB0/gwx88EGPwuuTzs6rzMOCXEqxOAf6cpkWwq2W/fPRGEf/5pRafTHDC2bPpcBWqoA3rBqVXMJSeQdDn8psmEdmfXanFOJBRInWMTo+FT2LvbjoN8fIXepKFrT3hgi9SvJAdU4TIQDl0bhnYG3AbqoZMqd/gTDrmrAD66YMaPU8UReR8mYO83fkIebEnTHHxFs/2v616jI1SoHeAHCYzYDLU4bvo+os4RLMRMHN9RiKyTx9tTpE6QqfHwieh5LxyrD+WJ3WMTmd/lgYL9gfgVPg5hIQ6wz8gFXtkV6H4upkAADE3H08tLsW4qqiG5+R+mYvSHaUIeSAEZbJy3A5gq3M0agz/tPU7f6rBs7//s7p8nUnEoTwTDuWZUGcCssvr3z5TfHFxO37OhG+PGTF7mBoAEOctg0wQcGj1p7i2YhUMRVlQBcRY5wNCRGRlv5/Ix5mCCqljdGqCKHJ8SSoPrTiAdUlcaFkqWqURDw8sRLdKF1Sll2HZuiPYfPhblJQXIlatxvMhIcj4T28s8ziGo9OPXnIffePckJlVjuIaEXIBGBQix+931s8DXLBLj8d+u3ix5SFhciyd6ITRX1Zj331auKiAq5ZU45krVZjQRdmw3dpTBjz0Sy30JgHRY6YjK/pG63wgiIg6wE19gvH25Muvf0rWxcInkdP5FRi9YCtP50pMEETc168IlX/twdyFn2LqiEfQNyYef379LDaUFmNddAxSp/fF3MBDjZ5nNpqR9loaVK4qvD0uCiOrT+FsqRnuGgE9/OUorDYjZH4lll7vhEgPGcZ/VY3F12saCt24FdW4p7cSN8YrL5HqYga3SFxd9iJyazvuPr9ERJaklAvY+t9hCHBr/wVv1Ho8pSuRRdtSWfZsgCgK+GS3Nxav+g2jx16NGdf0gs7FHzc99B00CiV+LC5G32X78Obpxgs0l24thbHSiOD/C8YnXQXk9B6EIeEK9PCvX6bl34sqD4uQ48S5+lO5XycZoJSjxWUPAJRlqVgTuAzC5RYMJCKycQaTiM+2pUkdo9PiCJ8Eiir1GPjGH6gzchK+LSjftxolmxZBkMsRHR2C/15/H7ROXfDBD4ugLEjChx71t1crHnMFbi3/E0U7SlCdUn9/W4WLAmaDGSp3FaYOCsUncbmYv6sOb26vQ1G1iJkDVHj+ajWu+LQSH413gkwAJnxdjeSHtIjwaP0afrtC7sGU08Mt+vqJiDqKViXH9meGw92ZZys6GgufBBb+fhrzf+c9BqV2bvUbqD65HeeHWrWJY+CqMaPs+HZ8/7/38ckPP+DI6VR8P2I0sravwQt5uUiqrYUIAEL9H5WPCsZSI/xu9kPuV7nA33daS/CVYVK8Aq9sqUOQKzA4RI5VySY4KYAZvZSYGKfEo+trYTABLw9V46auLRvtEyHgfd/ZmJcR1fzGREQ26LGRXfDoSF6E1tF4SreD1RnNWL77rNQxOr2zb12H6uS/cOF59aojv0Hsdj3qBA0+O7gWWlc5lMpa7HG/HrdmZ+PI+bIHACIAMxD8n2BAAHKX/1P2ACCpwAwvZwF9g2RwUgDfHjPBZAKUcuB/wzWY8n0NFozR4IebnXD3mhoUVLVstFeAiIfL3sIQL65pRUT2adnOdNTUXf4+5GQdLHwd7OfDOThXcfGVm9RxMhbeCoiXLlglmz6BOqwn1u/IxsmqQnj5eeCdVTNQbagDAMQqG4/EnVt9DuZaM3CJcfIfTxhxNNeM0+fvKiQDfrjZGWeKzTCagSHhCsR6y9HFS4bdWS3/5ifoK7BItQC+akOLn0NEZCuKq+rw7d4MqWN0Oix8HWzxdk5YlZpYW78WlNI7DADgefNLDe+ryz0NubM7jJUlOLTvJJRRMTidXT8iG+AZinef/xGBF5S+qiNVjfYtc/7nS2pXgYDav4ugVgmMi1Ygv0rEjd9Wo7hGxNazRgCAwQSYWjmxQlVyGmuClvMiDiKyS0t2pIMzyjoWC18H2pVahGM55VLH6NTqinMa/q30q58Hp1LpGh4TDXqYaipgLMuHaKhFqs+EhvdpVGbk1gIGrWfDY2ajGSGRHv+8Xf3PyKG8mwZmsX66n94I/JZixOSVNRgdpYBWCVz3dTVWnahDcqEZfQNbfwGHf85GLIv+q9XPIyKS2tmiamw9XSh1jE6Fha8DLf6Lo3tSq0re2vBvubMrIMhgqipFfS0DABFVR3+HaDLC9+bZkGv/KXN6hRFdwmshimYIgtDweH5a6UXHCbwzEJV7K//eI2AUAf3fZ20/2mfAgrFqVNQBd/9ci/fHaRDUxvvyXpX1CR4OSW/Tc4mIpLR8F+ezdySF1AE6i8ziavx+Il/qGHQBU1UZVP7RqD17+J8HZXLInd3h0mcC1IGxjbav9ozFiZAy6A3VDaci5IKAQ11iAUFA0m198WroAQDAsQeO1T9JCeDvqXZ+WiD/7zPAJbUiXNXApju16Onf+tG98wTRjMcr3sJ+j9exs8StzfshIupofyQXIKe0BoHuXIi5I3CEr4Ms2Z4OM6crSE4bd3XDv/VZR+HadyIqDv+GhqsuBDlEQy10CSMBAIVr5zVsX5Wdiv/O3YaK6n/m7alVWmT0GoUqkwkJK/Zg/vFeKPqzEOL5yXsXXItx27vXN/z7tzMmyAUBsV7t/xKU1ZZiidNCeKl4EQcR2Q+TWcQ3e3jxRkfhOnwdoLrOiP6vbUKF3ih1FAJw9s1/5uVpE0ejzmCE4cQfAACZsxt8J72IwjVvQaZ1hyBXQp/5z310BZUTxLqai/Z514Br8GRJ/Sn7rieT6/elqy9z5sr6eX2eozxRvLH+kl1vJ2DpRCeM79Lyu200JzvoGgxOucNi+yMisjZfFzV2PDMcCjnHn6yNH+EOsPZILsueDRE0Lg3/rjqyoaHsAQIC73ofeV8+AWNZPgxFWfC/7Q0o/f5ZIPTfZS86Ohx/zl+OQYMeRe7Nr2BMyhkAgJdCgUELesNz+D8XeJwvewCQ8oSnRcseAARl/4rPondYdJ9ERNZUUKHHhuOc7tQRWPg6wMp9mVJHoAuEPvo1IP9X2ZKr4X/H240u0nCOGQAACJw+HzKnf82PE2TwvekldPnPOyjuUosu0SXYmpGJTKMRagCfBgXjkzW+6H9dHAS1cMHzgLCZYZh1xQjUydUWf20jsj/CfcE8RUJE9oMXb3QMntK1srTCKgx7e7PUMciKvJ0NeLRvCaJztcjIlEMheiP2txchLymAEByIObfIcVCVe9HzBrjH4t1j2+FUV23RPGYnL9xknoMDZS7Nb0xEZAM2PTEEUT665jekNuMIn5V9x9E9h1dYrcT/tnthv3c1AqKNkDvl4vDw/8EY1hViVg5mLa7A6KrIi563q/QkHug6AFVqyxYzWU0RVujeg5uS0wiIyD6s2MUzE9bGwmdFJrOIHw9kSR2DOoDeKMfbO3ywWWWEa6QRnh5nsTfhEdT2HA6xpBT3LsrEbWXxFz3vQNkZ3BvXB2VO7hbN41R0FGvCvrfoPomIrOX7/ZmoNfD+utbEwmdFW04VIL+c983tTBbvd8cPVUqgiwlhwZnYH3AjKobfDrGmBhM/PYGZeT0uek5SeSrujklAsdbbolnCstbgo+g9Ft0nEZE1lNca8duxPKljODQWPiv6bi9H9zqjdck6fJLugsouBkRHF+Cocx8UTXwKMBoxaMl+vJba+6LnnKw4ixmRXVDgFmDRLGNz3se0wGyL7pOIyBp+PMDvVdbEwmclRZV6bErmpead1aEcNV7f74G8iFrExpYhTe6DrClvQJTJEfPtHnxwuBfkEBo9J7UyC9ODQ5DjEWKxHILZiJdq30Sia6XF9klEZA1/nSlEQUWt1DEcFguflfx0MBsGEy+A7szyqpR4ZYcnjvnVICKuFiUyE85MWQizkw4+v+zF59u6wdnceHmYzOo8TA/wRYZ3hMVyyKoL8bXbh9AqOD+GiGyXySxizaEcqWM4LBY+K1m5j6dzCagxKvD6Tm9s09bCu0sdoC7E0WvnweQbCue/DuHz9WHwNWsbPSe35hym+7gh1TfmMnttPe25Q/g54ieL7Y+IyBp+4Gldq2Hhs4KkrDKczK+QOgbZCFEU8MkeT6zRA+oYPdzdsnFg0HOo63IF5IeT8f5Kd8QYvRo951xtMWZ4OiE5oKvFckRm/ogF0Qcstj8iIks7kVuOk3n8+WkNLHxW8PMRDknTxVadcMFnuc4wdKlBcGAWDsZOR02/8UDqWcz5QsTA2uBG2xfrS3G3q4Ck4ESLZbg+911MCbh4EWgiIlux5jBH+ayBhc8K1h3hD1S6tL2ZTpib5ImiKD0iIgtxJGAkysbcCzG/AI9/XowJldGNti+vq8C9TnXYH9rHIscXTHV4re4txOkse3cPIiJL+fkwf4ZaAwufhR3MKEF2aY3UMciGnS1X4uVdXkgJqUV0bAVOa2NQcNMLEMvLMe3TNNxd3L3R9lXGajyoqsDOiH4WOb68Kh8rPT+Gk5wXcRCR7ckorsbBjBKpYzgcFj4LW8vRPWqBKoMc/9vuhd3ueoR0rUSBWoOzt82DySRizKIjeCa7V6Pta0y1eFhWjC3Rgy1yfJeCfVgVudYi+yIisjSO8lkeC58FiaKIX5P4SUotYxYFvLfHA+tEER7x1TA6VePU5AUw6zzQ+4u9mHuy8QLNdeY6zBRzsSH2aoscPzbzW7wZecQi+yIisqS1R3JgNnNpM0ti4bOgAxmlyCnjopHUOiuPueHzQg3kMZXQuhbgyJjXYAyOQdiPe/Dpvh5QifKGbY1mI/5ryMTP8cMtcuyb8+djkh8XCCci21JQoccBnta1KBY+C+J9AKmtdqY7Yd4pN1TG1MDXPwcH+82EPuEquG/cj8//7AI3UdOwrUk04bnaFKzsNqrdxxVMerxpfhtRzpx3SkS2ZeMJ/jJqSSx8FsTCR+1xpliFl/Z6IjvUiLCIAiRFT0LVVZOh3p2ET9b4I9jo1rCtCBGzq09iecLYdh9XUZGNH30WQS0zt3tfRESWsulEgdQRHAoLn4WcyC3H2SIudUHtU6GX45Wd7jjsbUR4fClO+vdDybWPQnb8DOZ/q0F3g1+j7d+sPI5FPca1+7hu+bvwQ9Sv7d4PEZGlnCmoRHphldQxHAYLn4WsP8rRPbIMk1mGd3Z74FcFENCtHDlufsi55X8wZ+bg5aU1GFoT1mj7d8uP4t2e49t93O6ZK/BqxLF274eIyFJ+52ldi2Hhs5ANx/lJSZb11REdvixXQdu1EnqdgNRbF8JUUYOHPsvD5PLYRtsuKkvCW70mtPuYt597BxN8Ctu9HyIiS2DhsxwWPgvIL6/FidxyqWOQA/oz1QnvpjjBEFsJtXsJjt8wD0a1KyZ/egr/Odf4lmtflh7Bq73HQ4TQ5uMJxhosEOYi3IlXmxOR9Pall6Cs2iB1DIfAwmcBW0+dkzoCObATRU545YAbzkXq4eVXgKThz8EQEo+hnx/ES2cbr9X3XUkSnu89DiZBfpm9NU9Rnomf/D6HUsY1sIhIWkaziD9P8uINS2Dhs4Ctp3kKjKyruFaBl3a646S/EQERRUjqcxdqe49Ct6/2YOHRXhAu6GZrSpLwdK/RMMoUbT6eR952fBe1wQLJiYjah6d1LYOFr53MZhF/neYIH1mfwSTDG7vdsdXZjIC4UpyMHoWKkdMQ8PNefLYrARrxn4L3W8kxPNZjJOrk6jYfr1fmMjwfftIS0YmI2mzLqXMwmLhsVHux8LVTUnYZSji/gDrQ4kMu+K4W8OxaiuzArjh34zNw2XwQizdEwsvs3LDd5tLj+L/Eq1GrdGrzse4uehujvYstEZuIqE0qao3Yk8bvQ+3FwtdOWzh/jySw/rQO7+Y4QRlfhkovF2Te+hbkh0/ho5+8EGn0aNhuR+lJPNhtEKrVujYdRzBU4QP5PARp9JaKTkTUaps5j6/dWPjaiRdskFSO5mswO8kVlVHVELz0OH3LfJhzivHmCjmu0Ac2bLev7DTujeuLcie3JvZ2ecqyNKwJWAq5wFMqRCSNnalFUkeweyx87VBea8ChzFKpY1AnVlCtwPN7XZEZUgeXgCKcuPZ/MIpOeHpJOcZURzZsd6Q8BffEJKJE69Wm43jlbsHX0X9aKjYRUasczylHWQ2nT7UHC1877DhTCKOZS1eQtOpMcsze6YZ9boB3eCGOXf0o9P6xuOfTDNxR2rVhuxMVZ3FXZBwKXfya2Nvl9c1cjCfDzlgqNhFRi5lFcB5fO7HwtcOWU1yOhWzHhwd0+NEsg1dcCU71moyqXmNx7aLjeCK3Z8M2ZyozMT0sAnnuwa3evwARD5XOxVDPEgumJiJqmV08rdsuLHztsI3LsZCNWXNSi48KVXDuWoKsmEEoHX0v+i/dh9fP/LNA89mqHEwPCkCmV1gTe7o0QV+BT1Xz4avmqRUi6lg7U1j42oOFr42ySqqRVVIjdQyii+zPVmPOSR1M8SUoDQlB3uSXEbVyDz482BPyv2+7ll2dj+m+XkjziWr1/lWlZ/Bz0JcQBE5nIKKOk5xXztustQMLXxvtP8vTWmS7siuUmLXPAwURtTAFyZE+dR48/0jC4q1doRNVAICC2kJM99LhpH98q/fvl/M7vozeaunYRESXZRaBXWkc5WsrFr42OsDCRzau1ijDy7tdkORphCqwAqcnvwXV8VwsWhcCf1P9unzF+hLc7SbHsaCEVu9/cNYiPBqaaunYRESXxXl8bcfC10b7M1j4yPaJooCFB1ywXiGDLrwYJ8c9C7FMwHsrXRFn8AYAlNWV4x6tEQdDerVq34JoxsyyuRjsUWaN6EREF9mVyit124qFrw2q64xIzq2QOgZRi6084YzPypXQxRQjZci9qHWNxKtfmjC4NgQAUGmowv2aauyO6Nuq/Qr6Mix2WgAvFefVEJH1JeeVo7S6TuoYdomFrw0OZZZy/T2yO7syNZiT6gTElSGzzzhUxI/EzM8KcX1lDACgxliDh+Sl2Bo1qFX7VRefxM8hX1sjMhFRI6II7OZ6fG3CwtcGnL9H9upsuQrPH9ahPKYCRfEJKBp+L27/JAX3FtXP4dOb9JiJfPze5apW7Tcwez0Wx2y3RmQiokaOZJVKHcEusfC1Aa/QJXtWWSfDC3tccCagDtURnsi+8UWMXHwUszLr5/AZzAY8ZczGurhhrdrvsKyPcX9whjUiExE1OJLFecNtwcLXSqIo4iDvn0t2zizK8PYBHbY5ixDDTUi/ZQ4SfziBecn1CzQbRSNm1aXhx64jW7xPQTTh6aq3cIUb57cSkfUczWbhawsWvlZKOVeJUi78SA7ii+NOWF4rhzyqEimTXkHgXzlYtCcRKlEOs2jGyzWnsSJhTIv3J6spxpe6d+GmNFoxNRF1ZiXVBmQWV0sdw+6w8LUST+eSo9mcrsG8LDXQpQKp42fC+ayIxX/EwM2sgQgRb1SewOLEa1q8P6eiY1gb9p0VExNRZ5fEUb5WY+FrpcOcO0AO6FSxCs8f06A6ugJZQ2+DCaH4dI0fQk3uAID5FcfwQc/xLd5fSNZafBy920ppiaiz4zy+1mPha6Xk3HKpIxBZRblegecP6JARWolz/a5CRchQzPtahcQ6PwDAx2VJeKdXy0vfmJwPcFdQprXiElEnlpRdKnUEu8PC1wqiKOJUfqXUMYisxmgW8MYBF+x2M6I0MRz5/e7EC0trMLw6HACwpDQJr/WeABFCs/sSzEY8XzMXPV35NUNElnU0m4MvrcXC1wpZJTWo1HMyOjm+xcec8KNZBn0XZ2SOfRwPLCnElLI4AMA3JUfwUu9xMAvNf/uQVRfiK9cPoFWYrB2ZiDqRshoDzhZVSR3DrrDwtUJyHpeboM7jt1Q1Fp6Toy7aiPSJszDx63z8X0EPAMBPJUl4ptdYGGWKZvfjXHgYayN+sHZcIupkOI+vdVj4WoHz96izOVaoxounnFAZXY2zNzyFgb+VY3Za/Vp9v5YcxRM9R8IgVzW7n4jMVXg3er+14xJRJ8L1+FqHha8VkvM5wkedT1GNHLMOOSMvrBo5E+5BxFEV3jvSC4II/FFyHP+XOBS1Sqdm93NtzruYGpDTAYmJqDPgWbfWYeFrhZP85KJOymCWYfZBHQ566ZE/fBx0ZaFYvCMBGlGB7aXJeKjbYFSrdU3uQzAbMLtuLuJ1XDCViNov5RwvCGsNFr4W0htNSCvkBFHq3D4+5ox1ShHnBvWEwXUAFv8WAW+zFnvKTuH+uL6o0Lg1+Xx5VT5Wen4ErdzcQYmJyFHllNag1sALwlqKha+FTudXwmQWpY5BJLk1KWosKlOiqGcQimJuwAc/eiDG4IVD5Sm4p0sPlDp7Nvl8XcF+/BS5uoPSEpGjMotAOq/UbTEWvhbi6VyifxzIV+B/aUoUxWuQM+BuvPadBv30QThekY67orqiUOfb5PO7ZK7E25GHOygtETmq1HMsfC3FwtdCJ3nBBlEjeVVyPHNUjawoEVmjH8DjPyoxrioKpyszMCM8CvlugU0+f1L+Atzkn99BaYnIEaVyHl+LsfC1EOfvEV3MYJLj5UPOOOJrRM41d2PqBh2mlXRDelU2pgUHIcsz9LLPFUx6vGmcixhtTQcmJiJHwhG+lmPha6HMYl5ZSHQ57x13wnqtiJxrJmLEPj88ldMT2dX5mO7vjXSfqMs+T16Zgx+8P4Faxos4iKj1UjgY02IsfC2UVcJRCKKm/HBGhSW1SuSOHIL4zC5481Rv5NcUYrqXDqf9Yi/7PNf8Pfgpal0HJiUiR8FTui3HwtcCJVV1vIcuUQvszlXgjSw5sgd1hbupHz4+0BNltWW4y12F44HdLvu8rplf47XIox2YlIgcQUWtEecq9FLHsAssfC2QWcLTuUQtlVGpwKyTCqQl+sPoPRafb4uHqbYW9+hEHArpednn3VYwH9f6nuu4oETkELgAc8uw8LVAZjFP5xK1RrVBgeeTNDgS5oTS+Jvw8aYY6GoF3K+pxd7wvpd8jmCswXxxLsKdajs4LRHZM15U2TIsfC3AET6i1hNFYN5xNX53lyOv32TM3RSDiGod/qMoxfbIAZd8jqIiC6v8PoNSxkXOiahlcsv4S2JLsPC1AK/QJWq7r86osAIy5A65Dk//FYu+VX74P+Ec/oi56pLbu+ftwPdR6zs4JRHZq3wWvhZh4WsBXqFL1D5bcpSYW6hA5rDRuOtgIq4ti8ATpmz8Gjf0ktv3yPwSL0ac6NiQRGSX8spZ+FqCha8FeEqXqP1SyhWYlSpD6uC+GJfWD/eci8czden4qevIS24/o/AdjPUp6uCURGRv8ln4WoSFrxmiKHKEj8hCKuvkePaEBgd7dkHP8iF4LqMnXqo5jW+6j75oW8FQhfdk8xCs4ZILRHR5LHwtw8LXjHOVetQZeRcAIksxmUW8cUyF30P94KsYgbdPXoE5lclYljj2om2VZelYHbAUcoFfg0R0aSXVBtQaTFLHsHksfM0oqqyTOgKRQ1pyWomvtG4QAkbjw6TBeK/8JD7qMe6i7bxyt+Db6E0SJCQie1FQzjMBzWHha0ZJFQsfkbVsyFbgnWpnVHYZgfcPXo2vS1OwoNf4i7brk7kUT4edliAhEdkDXrjRPBa+ZhSx8BFZ1YkSOZ7NUSOnx1DMTRqO3wsz8UavCRAhNGwjQMQDJXMx3KtEwqREZKtY+JrHwteMYhY+Iqsr0cvxdIoaxxIH4rnTY3C84Bxe6T0OZuGfb1FCXSU+Vs6Dv5pfk0TUWAELX7NY+JrBwkfUMQwmYHayAn9G9cD92degIqsKs3qNhUmQN2yjKk3FmqAvIQi8EwcR/SOPiy83i4WvGSx8RB3r0xQZvvKKwXXl4+CaZsJTvUbDIFM2vN83ZxNWRG+RMCER2ZrCSl600RwWvmaw8BF1vHXZAuYJAehrvg5dTjthZo/h0Cs0De8fmLkIM0NTJUxIRLakotYodQSbx8LXDBY+ImkcKZHj2VJ3BDmNxdUnfPFQwpWoUTkDqL+I49Gyt3ClZ5nEKYnIFlToWfiaw8LXDBY+IukU6gU8kaODyXMYbjgWjQfjBqBS4woAEPTl+Fy9AD4qg8QpiUhqHOFrHgtfM7gsC5G06ozArFQNkj0G4fYTPfBIzBUoc3IHAKhLTmJNyFfSBiQiyVXq+Ytfc1j4miCKIkqrWfiIbMF7ZxX41eUKTDk9AE+HX4FirTcAICD7NyyN+UvidEQkJY7wNY+Frwk1BhOMZi7/QGQrfsgR8KnQDTdkDsWrgb1R4BYAABiS9TEeDEmXNhwRSaaSha9ZLHxNqDXwhu1EtmZfiYBXKiMwrHAM3vXsjRyPUAiiGU9VzEU/93Kp4xGRBIxmETV1Jqlj2DQWvibojfzkIbJFObUC/lvgj24V47FMewUyvCMgqy3BF9p34aHkb/pEnVEF5/E1iYWvCRzhI7JdtSYBs7Ld4VozDqtVVyLFtws0Rcfxc9i3UkcjIglwHl/TWPiawBE+ItsmisDcbGfkV47EFsUwJAd0RXDWOnwavUvqaETUwVj4mqaQOoAt4wgfkX1YXqDE1bVXQuPlDEOwEqOyP8DdQUH4PDtE6mhE1EF44UbTOMLXBL2BI3xE9mJruRyL8vvhiGkCDgf3xHPVc9HbrVLqWETUQepM/JndFBa+JtQaOcJHZE/SqkW8ntENB02TcMQrCstd3oOLgr/1E3UGZv7IbhILXxM4wkdkfypNwKtp4dhkugUnNR74OfwHqSMRUQcwiVw3tyksfE3Qc4SPyC6ZReC9NH98VzsFpWIl3o/eJ3UkIrIykYWvSSx8TajlCB+RXfs6yx3vlE1BkHAKdwRmSx2HiKyIN8ZqGgtfE+pMHOEjsndbC7V4KmcSxromoZtLldRxiMhKTGx8TWLhIyKHd6ZKjQdTxuAO/zPQyvmLHJEjMvOUbpNY+JogFwSpIxCRhZQbBDyf0gO93SukjkJEVsDC1zQWvibIZSx8RI7EaAa2FblJHYOIrIDLsjSNha8JCjkLHxERkT3gCF/TWPiaIJfxw0NERGQPWPiaxkbTBM7hIyIisg/se01j4WsC5/ARERHZB6WclaYp/Og0QcHCR0REZBfUSlaapvCj0wQ5L9ogIiKyC2qFXOoINo2Frwmcw0dERGQfVApWmqbwo9MEntIlIiKyD2oWvibxo9MEJT95iIiI7IJGyVO6TWGjaYKzip88RERE9oA/s5vGwtcEF7VS6ghERETUAix8TWPha4JOo5A6AhEREbWAVsWf2U1h4WuCTs1PHiIiInvgxBG+JrHwNUGlkEHFlbuJiIhsmkIm8KKNZrDNNMPViaN8REREtoxTsJrHwtcMVydeuEFERGTLPLUqqSPYPBa+Zriz8BEREdk0b61a6gg2j4WvGe7O/K2BiIjIlnnp+LO6OSx8zeAIHxERkW1j4WseC18zOMJHRERk27x4SrdZLHzN4G8NREREts2bP6ubxcLXDH9XjdQRiIiIqAneOo7wNYeFrxkBbix8REREtsyLha9ZLHzNCHB3kjoCERERNYHTr5rHwtcMjvARERHZNq7D1zwWvmZolHK4O3NpFiIiIluklAtw48/pZrHwtQAv3CAiIrJN/jwT1yIsfC3A07pERES2KdTTWeoIdoGFrwX83XjhBhERkS1i4WsZFr4WCOQIHxERkU0K9dRKHcEusPC1AOcHEBER2SaO8LUMC18LBHItPiIiIpsU5sXC1xIsfC3ATyYiIiLbFMqf0S3CwtcCQe5OcFbJpY5BREREF3BzUsJVwzX4WoKFrwUEQUCENyeFEhER2RKegWs5Fr4WivbVSR2BiIiILhDCCzZajIWvhaJ9WPiIiIhsSRgLX4ux8LVQFEf4iIiIbApP6bYcC18L8ZQuERGRbYn1d5U6gt1g4WuhcC8t5DJB6hhEREQEQCYAsX4uUsewGyx8LaRSyLiaNxERkY0I99bCiUumtRgLXytE8cINIiIimxDP07mtwsLXCpzHR0REZBviA3g6tzVY+Fqhix8LHxERkS2ID+AIX2uw8LVCYrCb1BGIiIgILHytxcLXCpHeOujUCqljEBERdWpuTkoEujtJHcOusPC1gkwmoHsQf6MgIiKSUpw/5++1FgtfK/UIdpc6AhERUafG07mtx8LXSj1C3KWOQERE1Kl1ZeFrNRa+VuKFG0RERNJK4M/iVmPha6VgD2d4aVVSxyAiIuqUXDQK3lKtDVj42oCjfERERNLoHeoBGe9t32osfG2QyAs3iIiIJHFFmIfUEewSC18b9AjhCB8REZEUrgj3lDqCXWLhawOO8BEREXU8pVxAT66W0SYsfG3grVMj0kcrdQwiIqJOpWugG5xUcqlj2CUWvjYaFOUldQQiIqJOhfP32o6Fr40GRXlLHYGIiKhT6RvOwtdWLHxtNDDSCwKvCiciIuowvGCj7Vj42shDq+LCj0RERB0k3MsZ3jq11DHsFgtfO/C0LhERUcfoF8HRvfZg4WsHXrhBRETUMa6K8ZE6gl1j4WuH/pGekPP2LkRERFYllwm4moWvXVj42sFFo0T3IN51g4iIyJp6BLvBzVkpdQy7xsLXTjytS0REZF1DY32ljmD3WPjaiYWPiIjIuoZ04enc9mLha6e+4Z5w5m1eiIiIrMJLq0JiMKdPtRcLXztplHJcFcPlWYiIiKzhqhhvCLzTQbux8FnAqK7+UkcgIiJySENieTrXElj4LGBEnC+XZyEiIrIwQQCXY7EQFj4L8NCq0CeMN3QmIiKypIQgN3jxdmoWwcJnIaO7+kkdgYiIyKEM5dW5FsPCZyGjWPiIiIgsakx3zpG3FBY+Cwnz0qKLn07qGERERA4h0luLboFcjsVSWPgsiKN8REREljEuIUDqCA6Fhc+CRnN5FiIiIosYn8jCZ0ksfBaUGOwGP1deTURERNQekT5axAe4Sh3DobDwWZAgCBjTjaN8RERE7TGep3MtjoXPwib2CpI6AhERkV3j6VzLY+GzsN6hHgj3cpY6BhERkV2K9tUhzp+ncy2Nhc8KOMpHRETUNrw61zpY+KzgBhY+IiKiNuH8Petg4bOCMC8teoe6Sx2DiIjIrkT76hDr7yJ1DIfEwmclN/QOljoCERGRXZnEn51Ww8JnJdcmBkApF6SOQUREZBcUMgE39WHhsxYWPitxd1ZhaKyv1DGIiIjswvA4X/i48OYF1sLCZ0U38uINIiKiFrmlb4jUERwaC58VDY/3hatGIXUMIiIim+bnquZZMStj4bMitUKOa3sESh2DiIjIpt3UJxhyGee9WxMLn5XdMTBM6ghEREQ2SxCAW64IlTqGw2Phs7I4f1f0C/eUOgYREZFNGhjphVDektTqWPg6wO0c5SMiIrokXqzRMVj4OsA13f15qTkREdG/uDsrMba7v9QxOgUWvg6glMtwK3+DISIiamRizyCoFXKpY3QKLHwd5Lb+YVDwCiQiIiIA9Rdr8MLGjsPC10H83TQYGe8ndQwiIiKbcHWMD6J8dFLH6DRY+DrQnfxNhoiICABw15URUkfoVFj4OtCgaG9E+WiljkFERCSpKB8tro7xljpGp8LC18HuGMBRPiIi6tymD46AIHBee0cSRFEUpQ7RmVTqjRj4+iZU1BqljkJE1G5mfTVKty1H9emdMFeXQeUbCY+R90Ed0KVhG0NhJkq2LEFtxlFANEHpFQqfG56FwvXy904t37saFYd+gan8HGROrnCOHQyPIdMgKFQAgMpjf6J0yzKIdTXQJoyE54h7G55rLMtH/rcvIGDaAsjUXNDX1rg7K7HzmRFwUvHq3I6kkDpAZ6NTK3D7gDB8tDlF6ihERO1WtP49GM6dhfeEJyDXeaLq2J/I/+Z5BN7zIRQu3jCU5CJvxX+hSxwF9yunQlA5w1CYAUGuuuw+q45vRsmWpfAe9yjUQfEwFGej6JcFAADPEffCVF2G4vXvwWvcTCjc/VHw/SvQhPWAc3S/+kwbPoTHkOksezbqjgFhLHsS4CldCcwYHA6Vgh96IrJvZoMe1Se3w33YDGhCukPpEQj3K6dC6RGAioO/AgBKt34Bp6gr4DHsLqj8oqD0CIBzTH/Ite6X3a8++wQ0wfHQdh0KhZsfnCJ6wzn+atTlngYAGEvzIKidoY2/GuqALtCEJsJQlAkAqDq+BYJMAefYQVZ//dR6KoUM0waFSx2jU2LrkICviwaTegdJHYOIqH3MJkA0Q5ArGz0sKNTQZx2DKJpRk7oPCo9A5H/7AjLfm4rcLx5H9amdTe5WHRQPfV4K9DknAQCG0jzUpOyDU9QVAACFZxBEgx51+Skw1VSgLvcUVD7hMNVWonTbcniOesA6r5fabVLvIHjreOcpKfCUrkTuuzoK3+7NhJkzKInITsnUzlAHxqFsxzdQeoVArnVH1Ymt0OckQ+ERAHNVGcS6GpTv/h7uV90Bj6EzUJO2H+d+mgO/W+dAE5pwyf1quw6FqboceSueBiACZhN0Pa+B28CbAQByjQ7e4x9D4dp3IBrroO0+HE6RfVD4y0K49J4AY1k+Cn54FTAb4Tb4NmjjruzAjwpdjiAA91wVKXWMTouFTyIR3lqM7e6PX5LypI5CRNRmXhOeQNGvC5H94TRAkEHlHwVt/NXQ552BKJoBAE7RA+DadyIAQOUXCX32CVQc+vWyha824wjKdn0Hz9EPQh0YC2NJDop/X4TS7V/DffCtAADnLoPg3GXQBc9JguFcOjxH3Y+cT++D97VPQa71QO4Xj0MT0r3JU8jUMUbG+3GhZQmx8EnoP0OjWfiIyK4pPQLgf9sbMNfVwlxXDYXOE+dWvwmluz/kzq6ATA6ld+N7iSu9QqDPOn7ZfZZuWw5dt+Fw6TEGAKDyCYfZoEfx+vfhNugWCELj2Uii0YDiDR/Ba8LjMJbkQjSbGsqk0jMI+tyTcI7ub+FXTq316IgYqSN0apzDJ6HuQW4YFusjdQwionaTqTRQ6Dxhqq1ETdoBOMUMgCBXQu0fA2NxdqNtDcXZkDexJIto0Nef/7tAQ8m7xEpiZTu+gSayN9T+0YBorp9beH5fZiNgNrfjlZEljOrqh+5BblLH6NRY+CT28HD+xkNE9qsmdT9qUvfXX1iRdhD5Xz8LpWcwdAkjAQCu/W9E1YltqDi0HoaSHJTv/xk1Z/bApfe4hn0Urp2Hki1LG952iu6HioO/oOr4lob9lm5bDqfofhBkjZfzqCvMQFXyNrhfeTsAQOEZDAgyVBzegOqUvTAUZUEVwO+zUhIEYOZI/h9Ijad0JdYnzAMDI72wM7VI6ihERK1m1lejdOsyGCsKIde4wDl2ENyvvhOCvP7Hi3OXQfAa8x+U7VqJkk2fQuEZBJ8bZkET3K1hH8byc8AFp2ndBk0BIKB023KYKosgc3KDU3Q/eFx9R6Nji6KI4vXvw2P4PZCpNAAAmVINr3EzUbzxI4gmAzxHPQCFC2/hJaXRXf3QLZCje1LjnTZswI6UQty2aLfUMYiIiCxKEIB1/3cVuga6Sh2l0+MpXRswKMobg6O9pI5BRERkUWO6+rPs2QgWPhvx9Ng4qSMQERFZjCAAM0dx7p6tYOGzEYnB7hiX4C91DCIiIou4prs/4vw5umcrWPhsyJOjY6GQCc1vSEREZMMEAXh0RBepY9AFWPhsSKSPDpOvCJY6BhERUbuM6x6AWH8XqWPQBVj4bMyjI7pAo+R/CxER2SelXMATozm6Z2vYLGyMv5sG0waFSx2DiIioTW4fEIZI3jPX5rDw2aD/DImGq4ZrYhMRkX1xc1Lynrk2ioXPBrk5K/HA0CipYxAREbXKoyNi4O6skjoGXQILn426a3AE/FzVUscgIiJqkUhvLe4YGCZ1DLoMFj4bpVHK8eToWKljEBERtciz4+KhlLNW2Cr+z9iwm/oEo1eou9QxiIiImjQoygujuvpJHYOawMJnwwRBwKvXdwfXYiYiIlslE4DnxsdLHYOawcJn47oHueHWfqFSxyAiIrqkm/oEo1ugm9QxqBksfHbgqTGx8HBWSh2DiIioEa2K883tBQufHXB3VuG/Y+OkjkFERNTI/42Iga+rRuoY1AIsfHbilitC0COYQ+ZERGQb4gNccc+VEVLHoBZi4bMTMpmAV67vDoEXcBARkcRkAvD6jQlQcBkWu8H/KTvSM8QdN/cJkToGERF1cncMCEPPEHepY1ArsPDZmaeviYObEy/gICIiafi7avDkGF6oYW9Y+OyMp1aFZ6/hBRxERCSNl6/rChcNBx7sDQufHZrSLxRXxXhLHYOIiDqZkfF+GNs9QOoY1AYsfHbqjUmJ0KkVUscgIqJOQquSY/b13aSOQW3Ewmengtyd8AxP7RIRUQd5YnQsAt2dpI5BbcTCZ8em9g/FoCgvqWMQEZGDSwx2w/RB4VLHoHZg4bNjgiDgzUmJ0KrkUkchIiIHpVLIMPemHpDJuBCsPWPhs3Mhns54mqd2iYjISp4aHYtYfxepY1A7sfA5gDsGhKF/hKfUMYiIyMEMjPTCPVfx9mmOgIXPAQiCgLk39YCTkqd2iYjIMlw0Crx9cw8IvKenQ2DhcxChXs7471iufE5ERJYx+/puCOJVuQ6Dhc+BTB8Ujqu7+Egdg4iI7Nz4xADc0CtY6hhkQSx8DkQQBLxzcw/4uKiljkJERHbKz1WN1yZ2lzoGWRgLn4Px1qkx/+ae4JQLIiJqLUEA5t7UA+7OKqmjkIWx8DmgK2O88cCQKKljEBGRnblzQBinBjkoFj4H9cSoLugV6i51DCIishPRvjo8Oy5e6hhkJSx8Dkohl+HdKb3golFIHYWIiGycViXHx7f3hobLezksFj4HFuLpjDcnJUodg4iIbNzrkxIR7cu7aTgyFj4HNy4hALf2C5U6BhER2ahpA8NwXY9AqWOQlbHwdQIvXdsVXfx0UscgIiIb0zPEHc+N7yp1DOoALHydgEYpxwe39YZWxbkZRERUz1OrwodTe0OlYBXoDPi/3EnE+LlgHtfnIyIiADIBWHBLTwTy1mmdBgtfJzK2uz/+b3iM1DGIiEhij4yI4Xp7nQwLXyfz2MgYjOrqJ3UMIiKSyNVdfPAIf/nvdFj4OhlBEDD/lp6I8eVFHEREnU2QuxMW3tITMhnn93Q2LHydkE6twKd3XgFXLspMRNRpaFVyfHpnH3hoeZ/czoiFr5OK8Nbivdt6g7/kERE5PpkAvHtrL3QLdJM6CkmEha8TG9LFB/8dGyd1DCIisrJZ4+IxIp7ztzszFr5O7oEhUVxhnYjIgd3WPxT3XBUpdQySGAsf4a2bEtEjmMP8RESO5qoYb8y+rpvUMcgGsPARNEo5Pp/eF2FezlJHISIiC4n21eGDqb2hkPNHPbHw0d+8dWosm9EPXrx6i4jI7nlqVVg8rS9cNUqpo5CNYOGjBuHeWiye3hfOvOcuEZHdUilk+PSOPgjlWRu6AAsfNdIjxB0f3NYbCq7XQkRkl96clIArwj2ljkE2hoWPLjIszhev3dBd6hhERNRKz42Lxw29gqWOQTaIhY8u6Za+oXh0BO+1SERkLx4eFo17r+byK3RpLHx0WY+N6oIpfUOkjkFERM24c2AYnhwTK3UMsmEsfNSk125IwPA4X6ljEBHRZUzsGYhXuNYeNYOFj5oklwn44Lbe6BfBCcBERLZmZLwv3p7cA4LAC+2oaSx81CwnlRxLpvfFFWEeUkchIqK/DYj0xPu3cWFlahl+llCLaNUKLJnRFz1D3KWOQkTU6SUGu+GzaX2hUXLdVGoZFj5qMReNEl/c3Q8JQbzvLhGRVKJ9dVg2ox90aoXUUciOsPBRq7hqlFh+d390DXCVOgoRUacT5uWM5Xf3hwdvg0mtxMJHrebmrMTye/oj1s9F6ihERJ1GhLcW3943EP5uGqmjkB1i4aM28dSqsOLe/oj21UkdhYjI4UX6aPHNfQNY9qjNWPiozbx1anx1b39EemuljkJE5LCi/i57fq4se9R2LHzULr4uGnx93wCWPiIiK+jip8M39w2ErwvLHrWPIIqiKHUIsn+FlXrc/tluJOdVSB2FiMghdAt0xZd394cnL9AgC2DhI4spqzZg+tI9OJhRKnUUIiK71ivUHUtn9IObk1LqKOQgWPjIoqr0Rtz7xT7sSCmSOgoRkV3qH+GJxdP7Qst19siCWPjI4vRGEx5acRC/n8iXOgoRkV0ZGuuDj2/vwztokMWx8JFVmMwinvnhCFbuz5I6ChGRXbj5imDMuSGB98Ylq2DhI6t6/ZcT+GRrqtQxiIhs2qMjYvDYqC5SxyAHxsJHVvfp1hS8/msy+JlGRNSYQibgfxO7Y0q/UKmjkINj4aMO8cP+LDzz4xEYTPx0IyICAGeVHB/c1hvD4nyljkKdAAsfdZhdqUV4cPl+lFQbpI5CRCQpb50Ki6f3RWKwu9RRqJNg4aMOlV5YhbuW7UXquSqpoxARSSLSW4ulM/oh1MtZ6ijUibDwUYcrqzHgPyv2Y/sZrtVHRJ1Lr1B3fD6tL++eQR2O135Th3NzUmLZjH64rT8nKRNR5zE+IQBf3zvAocve0qVL4e7u3vD2yy+/jJ49e7boua3ZllqPhY8koZDLMOeGBLwwoStkgtRpiIisRyYA/x0biw+m9pZ0QeXp06dDEISL/owdO9Zqx3zyySexadMmq+2fWo73bSFJ3X1lBCK8nfHI14dQqTdKHYeIyKJcNQq8e2svDI21jStxx44diyVLljR6TK1WW+14Op0OOp3OavunluMIH0lueJwfvn9wIILcnaSOQkRkMTG+Oqx5+EqbKXtAfbnz9/dv9MfDwwMAIAgCPvvsM9xwww1wdnZGTEwM1qxZ0+j5a9asQUxMDDQaDYYNG4Zly5ZBEASUlpZe8nj/Pk27efNm9OvXD1qtFu7u7hg8eDDOnj3b6DlffvklwsPD4ebmhilTpqCiosKiH4POioWPbEKcvyvWPDwYV0Z7Sx2FiKjdxnTzw6qHBiPcWyt1lFZ55ZVXcPPNN+PIkSMYN24cpk6diuLiYgBAWloabrrpJkycOBGHDx/G/fffj+eee67F+zYajZg4cSKGDBmCI0eOYOfOnbjvvvsgCP/M60lJScGqVauwdu1arF27Flu2bMEbb7xh8dfZGbHwkc3w0qnxxV398MjwaAic10dEdkgQgMdHdcHHt/eBVm17s6bWrl3bcJr1/J85c+Y0vH/69Om49dZbER0djTlz5qCyshJ79uwBAHzyySeIjY3F3LlzERsbiylTpmD69OktPnZ5eTnKysowYcIEREVFIT4+HtOmTUNo6D8X8JnNZixduhTdu3fHVVddhTvuuINzAC3E9j4bqVOTyQQ8PjoWvcM88Ni3h7hIMxHZDRe1AvNv6YmRXf2kjnJZw4YNw0cffdToMU9Pz4Z/JyYmNvxbq9XC1dUVBQUFAICTJ0+ib9++jZ7br1+/Fh/b09MT06dPx5gxYzBq1CiMHDkSN998MwICAhq2CQ8Ph4uLS8PbAQEBDcen9uEIH9mkobG+WPfIVegZ4i51FCKiZkX76vDTQ4NtuuwB9SUuOjq60Z8LC59SqWy0vSAIMJvNFjv+kiVLsHPnTgwaNAjffvstunTpgl27dnXY8TszFj6yWYHuTlj5wEBMHxQudRQiosu65YoQ/PzwlYj2deyrUWNjY7Fv375Gj+3du7fV++nVqxeeffZZ7NixA927d8dXX31lqYjUBBY+smlKuQwvX9cN79/WCzobnA9DRJ2Xi0aB92/rhTdvSoSTSrr19VpDr9cjLy+v0Z/CwsIWPff+++9HcnIynn76aZw6dQrfffcdli5dCgCNLry4nLS0NDz77LPYuXMnzp49iw0bNuD06dOIj49vz0uiFmLhI7swITEQqx8ejFg/l+Y3JiKyst6h7vjlkaswITFQ6iitsn79egQEBDT6c+WVV7bouREREfj+++/x448/IjExER999FHDVbotWcvP2dkZycnJmDRpErp06YL77rsPDz30EO6///52vSZqGd5Ll+xKTZ0J/1t3HCt2Z0gdhYg6IZkAPDg0Co+N7AKFnGMmr732Gj7++GNkZmZKHYWawXNkZFecVHK8dkMCRnb1w9PfH0FBhV7qSETUSfi5qjH/5p4Y1InXC/3www/Rt29feHl5Yfv27Zg7dy4efvhhqWNRC3CEj+xWSVUdnluVhF+S8qSOQkQObnicL96e3AOeWpXUUST12GOP4dtvv0VxcTFCQ0Nxxx134Nlnn4VCwfEjW8fCR3bvp4NZeHH1MVTU8l68RGRZGqUMT4+Nw4zBEVJHIWoXFj5yCDmlNXhy5WHsSCmSOgoROYh+EZ54a1Ki3d0ejehSWPjIYYiiiMXb0/HW+mTojVyok4jaxlklx9Nj43DnwLAWLTdCZA9Y+MjhnM6vwGPfHcLR7HKpoxCRnRkc7YU3bkxEiKez1FGILIqFjxyS0WTG4u1pWPD7aVTXmaSOQ0Q2zkWtwKzx8bi1X6jUUYisgoWPHFp2aQ1eXHUUm5J5820iurShsT54/cYEBLg5SR2FyGpY+KhT+DUpFy//fAz55Vy3j4jquTkp8cKErripT7DUUYisjoWPOo2KWgPe/u0kvtx1FmZ+1hN1WoIA3NQ7GE9fEwdvXfO3BCNyBCx81OkczizFsz8m4XguL+og6mwSg93wynXd0CvUQ+ooRB2KhY86JZNZxJLtaXhn4yle1EHUCXhqVXhqTCxuuSIEMhmXWqHOh4WPOrW8slq89VsyfjqYDX4lEDkeuUzA1P6heGJULNyclVLHIZIMCx8RgKPZZfjfuuPYlVosdRQispB+4Z545fpuiA9wlToKkeRY+IgusOFYHt74NRmphVVSRyGiNvJzVePZa+IxsVeQ1FGIbAYLH9G/GExmLN91Fgs3nUZptUHqOETUQi4aBR4YEoW7BkfASSWXOg6RTWHhI7qMsmoD3vvjNL7YeRZ1Jt6bl8hWaZQyTBsUjv8MieY8PaLLYOEjasbZoiq8uT4Zvx7N44UdRDZEIRMw+YoQzBwZAz9XjdRxiGwaCx9RCx3LKcPC309j44l8Fj8iCQkCMD4hAE+MjkWEt1bqOER2gYWPqJVY/IikM6SLD54aE4vuQW5SRyGyKyx8RG10PKccCzedwobjLH5E1jYoyguPjIjBgEgvqaMQ2SUWPqJ2YvEjsg5BAMZ09ceDQ6PQI8Rd6jhEdo2Fj8hCWPyILEMpFzCxZxDuHxKFaF+d1HGIHAILH5GFnSmowOd/peOng1moNXA5F6KWclbJMaVvKO69OgIBbk5SxyFyKCx8RFZSUlWHFbvP4oudZ1FQoZc6DpHNcndWYtrAcEwfFA4PrUrqOEQOiYWPyMrqjGasPZKDz/9Kw7GccqnjENmMCG8t7hgQhin9QuCsUkgdh8ihsfARdaBdqUX4/K80bDqRDzO/8qgTkgn1S6vcOSgcQ7v4QBAEqSMRdQosfEQSSC+swtId6fhhfxYq9Eap4xBZnZuTEpP7BOOOgWEI8+JiyUQdjYWPSEI1dSasPZKDb/ZmYv/ZEqnjEFlcnzAPTO0finEJAdAo5VLHIeq0WPiIbMSp/Ap8vScDPx3MRmm1Qeo4RG3molHghl5BmNo/DLH+LlLHISKw8BHZHL3RhN+PF+D7/ZnYeroQJk72IzuglAsY0sUXN/QKwoh4X47mEdkYFj4iG1ZQXosfD2bj+/1ZOFNQKXUcoov0CfPAxF5BmJAQwCVViGwYCx+RnTieU45fknLxS1IuUgurpI5DnVikjxY39AzCxF5BCPF0ljoOEbUACx+RHTqRW1/+1iXlIvUcyx9Zn4+LGhMSA3BDryAkBrtLHYeIWomFj8jOncyrwLq/R/542pcsKcZXh1Fd/TCyqx96hbhzzTwiO8bCR+RATuVXYN2RXPx+Ih/Hc8vBr25qDblMQN9wD4yM98Oorn5cL4/IgbDwETmocxV6bDt9DltOncO204UorqqTOhLZIJ1agSFdfDCyqy+GxfrC3ZkXXhA5IhY+ok7AbBZxNKcMW07WF8CDmaVc7qWTkssEdA9yw8BILwyO9kL/CC+oFDKpYxGRlbHwEXVC5bUGbD9diC2nzmF7SiEyi2ukjkRWIhOA+ABXDIz0wsAoL/SL8ISLRil1LCLqYCx8RISC8lrsO1uCfekl2J9RguM5ZTCY+K3BHgkC0MXXBQOj6gvegAgvuDmz4BF1dix8RHSRWoMJhzJLsf9sCfalF+NARinKani7N1vkpVUhIdgNiUFuSAx2R69Qd3jp1FLHIiIbw8JHRM0SRRFnCiqx/2wJjueW40RuOZLzKlBRa5Q6WqfiolEgMdgNCUHuSAx2Q2KwG4I9uPAxETWPhY+I2iyrpBrJuRVIzivHibwKnMgtx9mial4Q0k5ymYBgDydE+egQ7atDt0BXJAa7I9zLmWvhEVGbsPARkUXVGkw4lV+B5NwKnDlXiYyiamSWVCOjuJojgv+iUysQ6aNFlI8OUef/9tUhzMsZaoVc6nhE5EBY+Iiow5RVG5BRXF/+zpfAzL//ZJfWONyFIh7OSvi7OcHfVf333xoEuGnqR+98dfBz1UgdkYg6CRY+IrIJZrOI0hoDiir1KKqqQ3FVXcO/iyr/frtK3/Dvkuo6dOSZY4VMgItGAReN8u+/6//tqlHC1UkBv7/L3IV/a5QcpSMi28DCR0R2S280odZght5Q/3et0YTa8/82mFBjqH9bbzDDYDZDgABBAAQAsr//IRcEKOQClHIZFLK//5YLcFYp4Ob0T8FzVimkfrlERG3GwkdERETk4Hg/HSIiIiIHx8JHRERE5OBY+IiIiIgcHAsfERERkYNj4SMiIiJycCx8RERERA6OhY+IiIjIwbHwERERETk4Fj4iIiIiB8fCR0REROTgWPiIiIiIHBwLHxEREZGDY+EjIiIicnAsfEREREQOjoWPiIiIyMGx8BERERE5OBY+IiIiIgfHwkdERETk4Fj4iIiIiBwcCx8RERGRg2PhIyIiInJwLHxEREREDo6Fj4iIiMjBsfAREREROTgWPiIiIiIHx8JHRERE5OBY+IiIiIgcHAsfERERkYNj4SMiIiJycCx8RERERA6OhY+IiIjIwbHwERERETk4Fj4iIiIiB8fCR0REROTgWPiIiIiIHBwLHxEREZGDY+EjIiIicnAsfEREREQOjoWPiIiIyMGx8BERERE5OBY+IiIiIgfHwkdERETk4Fj4iIiIiBwcCx8RERGRg2PhIyIiInJwLHxEREREDo6Fj4iIiMjBsfAREREROTgWPiIiIiIHx8JHRERE5OBY+IiIiIgcHAsfERERkYNj4SMiIiJycCx8RERERA6OhY+IiIjIwbHwERERETk4Fj4iIiIiB8fCR0REROTgWPiIiIiIHBwLHxEREZGDY+EjIiIicnAsfEREREQOjoWPiP6/3TqQAQAAABjkb32PrygCYE74AADmhA8AYE74AADmhA8AYE74AADmhA8AYE74AADmAsoxOaZ/2PuAAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting pie-chart for distribution of languages\n",
    "# Count the occurrences of each rating\n",
    "rating_counts = df['Language'].value_counts()\n",
    "\n",
    "# Plot the pie chart\n",
    "plt.figure(figsize=(8, 8))\n",
    "plt.pie(rating_counts, labels=rating_counts.index, autopct='%1.1f%%', startangle=140)\n",
    "plt.title('Distribution of languages')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "184966f3-ad53-4d49-bcde-36f4a4421a0a",
   "metadata": {},
   "source": [
    "As we can see, the pie-chart gets very clumsy because of inclusion of so many categories which are very small in proportion."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "1dd3debd-ceb7-48b9-bbac-8a25adb25564",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Count the occurrences of each rating\n",
    "rating_counts = df['Language'].value_counts()\n",
    "\n",
    "# Aggregate smaller categories into \"Other\" if necessary\n",
    "threshold = 80  # Combine ratings with counts less than or equal to this threshold\n",
    "other_count = rating_counts[rating_counts <= threshold].sum()\n",
    "rating_counts = rating_counts[rating_counts > threshold]\n",
    "rating_counts['Other'] = other_count\n",
    "\n",
    "# Plot the pie chart\n",
    "plt.figure(figsize=(7, 7))\n",
    "explode = (0.6,) * len(rating_counts)  # Explode all slices a little for better visibility\n",
    "plt.pie(rating_counts, labels=rating_counts.index, autopct='%1.1f%%', startangle=140, explode=explode)\n",
    "plt.title('Distribution of languages')\n",
    "plt.legend(rating_counts.index, title='Language', bbox_to_anchor=(1, 1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9250338e-fa30-4fd0-809b-3467c751cbcd",
   "metadata": {},
   "source": [
    "Here we have clubbed some languages together and have also applied spacing to give a clearer understanding without any clumsiness"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8493280e-596d-4302-ae0d-b468b6ad383b",
   "metadata": {},
   "source": [
    "**Analyzing Average rating column**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "401eb4cf-c8bb-469b-b7b8-0ecf708552cb",
   "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>Name</th>\n",
       "      <th>Author</th>\n",
       "      <th>Narrator</th>\n",
       "      <th>Duration in minutes</th>\n",
       "      <th>Release date</th>\n",
       "      <th>Language</th>\n",
       "      <th>Price</th>\n",
       "      <th>Average rating</th>\n",
       "      <th>Number of ratings</th>\n",
       "      <th>Same Author and Narrator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Geronimo Stilton #11 &amp; #12</td>\n",
       "      <td>GeronimoStilton</td>\n",
       "      <td>BillLobely</td>\n",
       "      <td>140</td>\n",
       "      <td>2008-04-08</td>\n",
       "      <td>English</td>\n",
       "      <td>468</td>\n",
       "      <td>5</td>\n",
       "      <td>34</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Burning Maze</td>\n",
       "      <td>RickRiordan</td>\n",
       "      <td>RobbieDaymond</td>\n",
       "      <td>788</td>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>English</td>\n",
       "      <td>820</td>\n",
       "      <td>4.5</td>\n",
       "      <td>41</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Deep End</td>\n",
       "      <td>JeffKinney</td>\n",
       "      <td>DanRussell</td>\n",
       "      <td>123</td>\n",
       "      <td>2020-06-11</td>\n",
       "      <td>English</td>\n",
       "      <td>410</td>\n",
       "      <td>4.5</td>\n",
       "      <td>38</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Daughter of the Deep</td>\n",
       "      <td>RickRiordan</td>\n",
       "      <td>SoneelaNankani</td>\n",
       "      <td>676</td>\n",
       "      <td>2021-05-10</td>\n",
       "      <td>English</td>\n",
       "      <td>615</td>\n",
       "      <td>4.5</td>\n",
       "      <td>12</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Lightning Thief: Percy Jackson, Book 1</td>\n",
       "      <td>RickRiordan</td>\n",
       "      <td>JesseBernstein</td>\n",
       "      <td>600</td>\n",
       "      <td>2010-01-13</td>\n",
       "      <td>English</td>\n",
       "      <td>820</td>\n",
       "      <td>4.5</td>\n",
       "      <td>181</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Name           Author  \\\n",
       "0                  Geronimo Stilton #11 & #12  GeronimoStilton   \n",
       "1                            The Burning Maze      RickRiordan   \n",
       "2                                The Deep End       JeffKinney   \n",
       "3                        Daughter of the Deep      RickRiordan   \n",
       "4  The Lightning Thief: Percy Jackson, Book 1      RickRiordan   \n",
       "\n",
       "         Narrator  Duration in minutes Release date Language  Price  \\\n",
       "0      BillLobely                  140   2008-04-08  English    468   \n",
       "1   RobbieDaymond                  788   2018-01-05  English    820   \n",
       "2      DanRussell                  123   2020-06-11  English    410   \n",
       "3  SoneelaNankani                  676   2021-05-10  English    615   \n",
       "4  JesseBernstein                  600   2010-01-13  English    820   \n",
       "\n",
       "  Average rating Number of ratings  Same Author and Narrator  \n",
       "0              5               34                      False  \n",
       "1            4.5               41                      False  \n",
       "2            4.5               38                      False  \n",
       "3            4.5               12                      False  \n",
       "4            4.5              181                      False  "
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "868df249-e2ef-45dd-9700-d92e88134e8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the boxplot for Average rating\n",
    "plt.figure(figsize=(8, 8))\n",
    "boxplot = df.boxplot(column=['Average rating'])\n",
    "plt.title('Box-plot of Average rating')\n",
    "plt.ylabel('Average rating')\n",
    "\n",
    "# Annotate the outliers\n",
    "# Calculate the IQR and determine the outliers\n",
    "Q1 = df['Average rating'].quantile(0.25)\n",
    "Q3 = df['Average rating'].quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "outliers = df[(df['Average rating'] < (Q1 - 1.5 * IQR)) | (df['Average rating'] > (Q3 + 1.5 * IQR))]\n",
    "\n",
    "for index, row in outliers.iterrows():\n",
    "    plt.text(1.05, row['Average rating'], row['Average rating'], horizontalalignment='left', size='medium', color='black', weight='semibold')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "39261245-921d-4762-801f-5f65193d92b7",
   "metadata": {},
   "source": [
    "As we can see, most of the books are rated 4.0 and above, the median being 4.5, and many are rated even full 5.0 and a very small fraction are rated below 2.5,and finally some very small number of books are rated 2.0 and below, which are outliers which implies that the processed dataset contains mostly decent quality books "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "4f587497-4615-480c-84a9-ab0ca0f57d42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Jj476//9Gk/AylpSkRFKSkv7/K+P/V6vVqFQqVHp6qf9V6aX+v57qX49TjxsYGmFkUhwjE5M0/zU2KY6hiQnGJsUxKmaCUfHiFDcvSXELC/T09JV+m4QQBYAUOkIIIYRAq9EQ+yKCqGdPiHn2lKhnT4kJf0ZcVBTxMVHER0cTHxNNQmwsWq1G6bgZUqn0MDE3x9TSClMLS0wtLDH7+/8trTAtaYmZVSlKWFtLQSREESdrdIQQQoi3RHxMNBGPHhL1NIyoZ0+IfvaU6GdPiH72jJjwZ6hTUpSOmG/09A0oaWuLhV1pLOzLYGFfBkv70ljYl6akrT16+lIECVHYSaEjhBBCFDHxMdE8u3+P8If3CX/4gPBHIYQ/fEB8dJTS0QoFPX19SljbYGFXmlJlHbCpUBGbChWxLl8BfQNDpeMJIbJJCh0hhBCiEHsR9piwW4E8uXeH5yH3eP7gPi9fRCgdq0jS0zfAqmw5bCpUxLZCRWwcK2HrWAmTEuZKRxNCpEMKHSGEEKKQSIiNJex2IKG3gwi9dZPQ4FskxEQrHeutZ2ZVClvHSthXcaJstZqUruqEoXExpWMJ8daTQkcIIYQogDQaNc/u3SX0ViChtwMJvRXIi7DHIN+2Czw9fX1sHStRploNylZzpmz1mphaWCodS4i3jhQ6QgghRAHx/MF9Qq5dIeTaFR7euEZi3EulI4lcUtLOnrLVaqR+OdekVFkHpSOJ//Dy8qJdu3a8ePECCwsLRbPExcUxdOhQjh07RkxMTIHIVBhJoSOEEEIoJPr5U0L8UwubkOtXZW3NW6SEtQ2OdevjWLc+FWrXw7i4qdKRCoXhw4ezbt06AAwMDChXrhz9+/dnxowZFCuW/emCbdu2pV69eixdulT3XFJSEhEREdjZ2aFSqXI7eo6sWrWK77//nuPHj2NtbZ1upr8Ls/8KDQ3F3t4+w76vXr3KuHHjOH/+PDY2NkyYMIHPP/88119DQSD30RFCCCHySXJCAveuXOK+/2Xu+/sRGRaqdCShkJjnz/D3PIK/5xH09PWxr1INx7ouVKzbALtKVVDp6SkdscDq3LkzHh4eJCcnc/HiRT744ANUKhXz589/o36NjIwyLRDyU3BwMM7OztSqVSvLtoGBgZib/7Mhhq2tbYZto6Oj6dixIx06dODnn3/G39+fDz/8EAsLC0aNGpUr2QsS+VskhBBC5KGXkS+46nmY3fN/4KePhrDPfQ5Xjh2SIkfoaNRqHgfe4PT2TWz6ZjKrRr3PgR8Xct3bk3jZbOIVxsbG2Nvb4+DgQK9evejQoQPHjh3THQ8PD2fw4MGULVuW4sWLU7t2bbZs2aI7Pnz4cLy9vVm2bBkqlQqVSsW9e/fw8vJCpVIRGRkJwNq1a7GwsODIkSM4OztjZmZG586dCQ395+9uSkoKn3zyCRYWFpQqVYovvviCDz74gF69emX6Gn7//Xdq1qyJsbExjo6OLF68WHesbdu2LF68mJMnT6JSqWjbtm2mfdna2mJvb6/70sukSN60aRNJSUmsWbOGmjVrMmjQID755BPc3d0zvUZhJYWOEEIIkcsiHj/Ed+9ONk+byi+jP+DYryu4c+k8KclJSkcThUB8TDQ3fbw5/NMSfv54KDtmfcuVY4eIi4pUOlqBc+3aNU6fPo2RkZHuuYSEBBo0aMCBAwe4du0ao0aNYujQofj6+gKwbNkymjVrxsiRIwkNDSU0NBQHh/TXTMXFxbFo0SI2bNjAyZMnCQkJYerUqbrj8+fPZ9OmTXh4eODj40N0dDR79uzJNPPFixcZMGAAgwYNwt/fn+nTpzNt2jTWrl0LwK5duxg5ciTNmjUjNDSUXbt2ZdpfvXr1KF26NO+++y4+Pj6Ztj1z5gytW7dO83516tSJwMBAXrx4kem5hZFMXRNCCCHekFarJfRWILcvnOX2+bO8ePxQ6UiiiNCo1YT4+xHi74fn/1ZR1rkGTk1aULVxc8ysSikdTxH79+/HzMyMlJQUEhMT0dPTY8WKFbrjZcuWTVOMTJgwgSNHjrB9+3YaN25MyZIlMTIyonjx4llOVUtOTubnn3+mcuXKAIwfP54ZM2boji9fvpyvvvqK3r17A7BixQoOHjyYaZ/u7u60b9+eadOmAeDk5MSNGzdYuHAhw4cPx8rKiuLFi2c5la506dL8/PPPNGzYkMTERFavXk3btm05d+4c9evXT/ecsLAwKlasmOY5Ozs73TFLy6K1O6AUOkIIIcRrCn/0gIC/ThBwypvoZ0+UjiOKOK1Ww8Mb13h44xrH1/5KmarVcWragqpNmmNunfG6jKKmXbt2rFq1ipcvX7JkyRIMDAzo27ev7rharWbOnDls376dR48ekZSURGJiIsWLF8/xtYoXL64rciC1uHj69CkAUVFRPHnyhMaNG+uO6+vr06BBAzQaTYZ9BgQE0LNnzzTPtWjRgqVLl6JWq9HX189WtmrVqlGtWjXd4+bNmxMcHMySJUvYsGFDtvoo6qTQEUIIIXLgZeQLbvp4c+OvEzy9G6x0HPG20mp5HBTA46AAvNavpmz1GtRo3Z7qzVthZJLzH+gLE1NTU6pUqQLAmjVrqFu3Lv/73/8YMWIEAAsXLmTZsmUsXbqU2rVrY2pqyqRJk0hKyvnUUUNDwzSPVSoVBXnD4saNG3Pq1KkMj9vb2/PkSdpfyvz9uKBsxJCbpNARQgghspCckMAt39Pc+OsEIdeuoM3kt7VCKOHRzRs8unmDE+t+pWrj5tRs057yteoqvk1yXtPT0+Prr79m8uTJDBkyBBMTE3x8fOjZsyfvv/8+ABqNhqCgIGrUqKE7z8jICLVa/UbXLlmyJHZ2dpw/f57WrVsDqaNJly5dol69ehme5+zs/MpaGh8fH5ycnLI9mpMRPz8/SpcuneHxZs2a8c0335CcnKwr4o4dO0a1atWK3LQ1kM0IhBBCiAyFXLvCweWLWDXqfQ6tdOf+1ctS5IgCLSUxkYC/TrBz1rf8Nv5DfLZtKPI7/PXv3x99fX1WrlwJQNWqVTl27BinT58mICCAjz/++JVRDEdHR86dO8e9e/d4/vx5plPNMjNhwgTmzp3L3r17CQwMZOLEibx48SLTAnPKlCl4enoyc+ZMgoKCWLduHStWrEizrig7li5dyt69e7l9+zbXrl1j0qRJHD9+nHHjxunarFixgvbt2+seDxkyBCMjI0aMGMH169fZtm0by5YtY/LkyTl/8YWAjOgIIYQQ/5IQG8t1b0+u/HlINhUQhVrM82ec3bWNs7u2UbZ6TWq2bU+1Zq0wKmaidLRcZWBgwPjx41mwYAFjxozh22+/5c6dO3Tq1InixYszatQoevXqRVRUlO6cqVOn8sEHH1CjRg3i4+O5e/fua137iy++ICwsjGHDhqGvr8+oUaPo1KlTpiMz9evXZ/v27Xz33XfMnDmT0qVLM2PGDIYPH56jayclJTFlyhQePXpE8eLFqVOnDn/++Weam4g+f/6c4OB/ptiWLFmSo0ePMm7cOBo0aIC1tTXfffddkbyHDoBKW5AnGgohhBD5JPR2IFeOHiLwzF+kJCUqHUeIPGFkUpxabTtQr3N3LO3LKB2nyNFoNDg7OzNgwABmzpypdJy3nhQ6Qggh3lrJiQkEnPLmyrGDsrGAeLuoVFSsWx+XLu/hWLd+kV/Lk1fu37/P0aNHadOmDYmJiaxYsQIPDw+uXLmCs7Oz0vHeelLoCCGEeOu8CH3E5cP7uXHyOIlxL5WOI4SiLEuXpV6nbtRq26HI79iW2x48eMCgQYO4du0aWq2WWrVqMW/ePN3mBEJZUugIIYR4a4TeDuT83t+5ff4sWq1sKiDEvxmZmFCjdXtcOnfHqkw5peMI8cak0BFCCFHk3bl8nvP7fufhjWtKRxGi4FOpqOTSkCa9B1DGSaZficJLCh0hhBBFkjolhZs+3lzYv5vnIfeUjiNEoeRQsw5Neg+gQu16SkcRIsek0BFCCFGkJCXE4+95hIsH9hIT/kzpOEIUCaWrVKNJnwFUqt9YNi4QhYYUOkIIIYqEpIR4Lh3cx8X9u0l4Gat0HCGKJJvyjjTuPYBqTVui0pP7zouCTQodIYQQhVpKUhJ+R/bju+934qOjsj5BCPHGLEuXpXHPftRo/Q56mdwcUwglSaEjhBCiUFKnJHPV8wi+u7cT+yJC6ThCvJUsS5ehxcChODVtKVPaRIEjhY4QQohCRaNRc93bk7O/byX62VOl4wghALtKVWntOpzyteoqHUUIHSl0hBBCFApajYabp09yZudmXoQ+VjqOECIdFeq40GrIcOwqVlY6ihBS6AghhCj4Qq5dwWvdbzyTbaKFKPhUKqo1a0XLQcOwsLNXOo14i0mhI4QQosCKDAvFe+P/uH3+rNJRhBA5pKdvQJ0OnWjWdzDFS1ooHUe8haTQEUIIUeAkxsVxdtdWLh/ahzolRek4Qog3YGRiQpPeA2nQrSf6BoZKxxFvESl0hBBCFBhajQb/E8fw2baBuKhIpeMIIXKRZekytB02kkr1GykdRbwlpNARQghRIDy8cY0T637j6b1gpaMIIfJQRZeGtPtgJJalyyodRRRxUugIIYRQVEzEc7zW/kbQOR+lowgh8om+gQENe/SlSZ8BGBoZKx1HFFFS6AghhFCEVqPB7+gBTm1dT1J8vNJxhBAKMLexpd0Ho6jSqKnSUUQRJIWOEEKIfPcs5B7HfllO6O1ApaMIIQqASvUb0f7DMZjb2CodRRQhUugIIYTINylJSZzZuZkL+3ejUauVjiOEKEAMi5nQasgH1OvYDZVKpXQcUQRIoSOEECJf3Pf348/VK4kMC1U6ihCiACvnXIuOoz/B0r6M0lFEISeFjhBCiDwVHxON1/rV3Dh5XOkoQohCwsDImBYD36dB156o9PSUjiMKKSl0hBBC5Jmgcz78+dtK4mOilY4ihCiESletRqfRkyhVzkHpKKIQkkJHCCFErkuMi+P4mlXc+OuE0lGEEIWcvqEhzfoOptF7fdHT11c6jihEpNARQgiRqx7c8OfwT0uIfvZU6ShCiCLEtmJluoz9FOvyjkpHEYWEFDpCCCFyRUpyMqe2rufSgb1otRql4wghiiADQyNaD/0Ql07dlY4iCgEpdIQQQryxZ/fvcnDFYp6H3FM6ihDiLVC5YRM6jZ6ISQlzpaOIAkwKHSGEEK9Nq9FwYf9ufLZvRJ2crHQcIcRbxMzSii7jp1C+Vl2lo4gCSgodIYQQryU2IpyDyxfx4Ia/0lGEEG8plUqPhu/1ocWA99E3MFA6jihgpNARQgiRY/f9/Ti4fBFxUZFKRxFCCOwrV6XbJ59jYV9a6SiiAJFCRwghRLZptVrO7trKmR1bZMMBIUSBYmRiwjtuo6nZpr3SUUQBIYWOEEKIbImPiebgisXc87uodBQhhMhQ7Xc68s6HYzAwNFQ6ilCYFDpCCCGy9DjoJvuXzicm/JnSUYQQIkv2VZx4b/LXlChlrXQUoSApdIQQQmTq0sG9eG/0QKNOUTqKEEJkW/GSFnSf+DkONesoHUUoRAodIYQQ6UqKj+PIqmUEnfNROooQQrwWPX19Wru60aBbL6WjCAVIoSOEEOIVkWGh7F4wg4hHD5SOIoQQb6x6izZ0/HgChsbFlI4i8pEUOkIIIdJ4cP0q+5bMIyEmWukoQgiRa2zKO/Le1G+xsLNXOorIJ1LoCCGE0LnqeQTP/62S9ThCiCKpmKkZXT/5jIr1GigdReQDKXSEEEKg0ajx3rCGSwf3Kh1FCCHylEpPj3fcRlOvY1elo4g8JoWOEEK85RLj4jiwbD535f44Qoi3SIPuvWnz/oeoVCqlo4g8IoWOEEK8xSKfhLFnwQzCH4YoHUUIIfJd1SbN6TJ+CoZGxkpHEXlACh0hhHhLPQy4xr7Fc4iXTQeEEG+x0lWq0euL7yhuXlLpKCKXSaEjhBBvocAzpzi0YhHqFNl0QAghStrZ0+fL6ViVKad0FJGLpNARQoi3jN/Rgxxf8zNarUbpKEIIUWAUMzWj59RvKVejltJRRC6RQkcIId4ip3ds4szOLUrHEEKIAknfwIBOoyfi3Kqd0lFELpBCRwgh3gJajQZPj1+4cvSA0lGEEKJgU6lo98Eo6nfpoXQS8Yak0BFCiCJOnZLMwRXuBJ35S+koQghRaLQYOJSmfQYqHUO8ASl0hBCiCEtKiGfvotmE+PspHUUIIQqdRu/1pbWrm9IxxGuSQkcIIYqouOgods2dzpM7t5SOIoQQhVbdd7vSfsQYubFoISSFjhBCFEGxEeFsn/kNLx4/VDqKEEIUejVataPT2Eno6ekrHUXkgBQ6QghRxMRGhLN9xte8CH2kdBQhhCgyqjRqRvdJn6NvYKh0FJFNUugIIUQREhPxnB0zvuZF6GOlowghRJFToY4LPad+g6FxMaWjiGyQQkcIIYoIKXKEECLvla1ek75f/YBhMSl2Cjo9pQMIIYR4czERz9n+w1dS5AghRB57dPM6exbOICUpSekoIgtS6AghRCEXE55a5ESGhSodRQgh3goh166yd/Fs1CnJSkcRmZBCRwghCjEpcoQQQhn3/C7yx5J5qFNSlI4iMiCFjhBCFFK6IueJFDlCCKGE4AvnOLh8ERqNWukoIh1S6AghRCEUFx3FjpnfSJEjhBAKCzp7isMrl6DVaJSOIv5DCh0hhChkkhLi2TV3utwnRwghCoiAU14c/XUFsplxwSKFjhBCFCIpycnsXTiLJ3duKR1FCCHEv1w7cRTPNT8rHUP8ixQ6QghRSGg1Gg4uX0jItStKRxFCCJGOK0cP4LNtg9IxxP+TQkcIIQqJP1f/xK1zp5WOIYQQIhNnd23j6p+HlY4hkEJHCCEKhVNbN3DVU75xCiFEYfDn/34i+OI5pWO89aTQEUVC27ZtmTRp0hv1sXbtWiwsLHIljxC56dLBvZzbvU3pGEIIIbJJq9Gwf9kCQm8FKh3lrSaFjhAK+uSTT2jQoAHGxsbUq1cvW+ckJCQwbtw4SpUqhZmZGX379uXJkyd5G1Qo5sZfJzixfrXSMYQQQuRQSmIiuxfM4EXYY6WjvLWk0BFCYR9++CEDBw7MdvtPP/2UP/74gx07duDt7c3jx4/p06dPHiYUSgm5doUjq5aBbFcqhBCFUnx0FLvmfE9cdJTSUd5KUuiIIiMlJYXx48dTsmRJrK2tmTZtWpr97BMTE5k6dSply5bF1NSUJk2a4OXllWmfq1atonLlyhgZGVGtWjU2bPhnJ5WpU6fSvXt33eOlS5eiUqk4fPifdRRVqlRh9eqMfxv/448/Mm7cOCpVqpSt1xgVFcX//vc/3N3deeedd2jQoAEeHh6cPn2as2fPZqsPUTiEP3rAPvc5aNQpSkcRQgjxBiKfhLJ7/g8kJyYoHeWtI4WOKDLWrVuHgYEBvr6+LFu2DHd39zRFxvjx4zlz5gxbt27l6tWr9O/fn86dO3PrVvr3I9m9ezcTJ05kypQpXLt2jY8//hg3NzdOnDgBQJs2bTh16hRqtRoAb29vrK2tdcXTo0ePCA4Opm3btrn2Gi9evEhycjIdOnTQPVe9enXKly/PmTNncu06Qllx0VHsmT+DxJcvlY4ihBAiF4TdDmL/0vloNGqlo7xVpNARRYaDgwNLliyhWrVquLq6MmHCBJYsWQJASEgIHh4e7Nixg1atWlG5cmWmTp1Ky5Yt8fDwSLe/RYsWMXz4cMaOHYuTkxOTJ0+mT58+LFq0CIBWrVoRExPD5cuX0Wq1nDx5kilTpugKHS8vL8qWLUuVKlVy7TWGhYVhZGT0yqYJdnZ2hIWF5dp1hHJSkpPZt3g2kU9ClY4ihBAiF925dJ4Ta39TOsZbRQodUWQ0bdoUlUqle9ysWTNu3bqFWq3G398ftVqNk5MTZmZmui9vb2+Cg4PT7S8gIIAWLVqkea5FixYEBAQAYGFhQd26dfHy8sLf3x8jIyNGjRrF5cuXiY2NxdvbmzZt2uTdCxZFUnxMFPHR0UrHEEIIkQf8juzH//hRpWO8NQyUDiBEfoiNjUVfX5+LFy+ir6+f5piZmdlr99u2bVu8vLwwNjamTZs2WFlZ4ezszKlTp/D29mbKlClvGj0Ne3t7kpKSiIyMTDOq8+TJE+zt7XP1WkIZJaysGTxrEfuXzuf+1ctKxxFCCJHLPP/3E6XKOVDGyVnpKEWejOiIIuPcubQ35jp79ixVq1ZFX18fFxcX1Go1T58+pUqVKmm+MioQnJ2d8fHxSfOcj48PNWrU0D3+e52Op6enbi1O27Zt2bJlC0FBQbm6PgegQYMGGBoa4unpqXsuMDCQkJAQmjVrlqvXEsopZmpGny+nU69TN6WjCCGEyGXqlBT2LZ5DTMRzpaMUeVLoiCIjJCSEyZMnExgYyJYtW1i+fDkTJ04EwMnJCVdXV4YNG8auXbu4e/cuvr6+zJ07lwMHDqTb32effcbatWtZtWoVt27dwt3dnV27djF16lRdm9atWxMTE8P+/fvTFDqbNm2idOnSODk5ZZr59u3b+Pn5ERYWRnx8PH5+fvj5+ZGUlASkbmhQvXp1fH19AShZsiQjRoxg8uTJnDhxgosXL+Lm5kazZs1o2rTpm76FogDR09en/YdjeOfD0aj05J9qIYQoSl5GvmDfotmk/P/3e5E35LtnOtq2bcukSZPeqI+1a9e+smC8qFCpVOzZs0fpGDqOjo48fPiQYcOGER8fT+PGjRk3bhwTJ05k1KhRunYeHh4MGzaMKVOmUK1aNXr16sX58+cpX758uv326tWLZcuWsWjRImrWrMkvv/yCh4dHmlEaS0tLateujY2NDdWrVwdSix+NRpOt9TkfffQRLi4u/PLLLwQFBeHi4oKLiwuPH6feXCw5OZnAwEDi4uJ05yxZsoTu3bvTt29fWrdujb29Pbt27Xqdt04UAi6dutPny+kYFzdVOooQQohcFBZ8i2O/Llc6RpGm0mrlTnT/1bZtW+rVq8fSpUtfu4+1a9cyadIkIiMjcy1XZq5cucK8efM4deoUz58/x9HRkdGjR+tGNDISERHBhAkT+OOPP9DT06Nv374sW7Ys03UrKpWK3bt306tXr9fOm5vvj6OjI5MmTXrj4jS3JSQkMHr0aC5evEhAQADdu3fPVoH4Op+JKPrCHz5gz4IZshubEEIUMW3e/5CGPeTG33lBRnSKiIsXL2Jra8vGjRu5fv0633zzDV999RUrVqzI9DxXV1euX7/OsWPH2L9/PydPnkwzCiJen1qtxsTEhE8++STNfW+yIp+JSE+pcg4Mmb2Ycs61lI4ihBAiF53cvJZ7Vy4pHaNIkkInAykpKYwfP56SJUtibW3NtGnT+PfgV2JiIlOnTqVs2bKYmprSpEkT3f1TMrJq1SoqV66MkZER1apVY8OGDbpjU6dOpXv37rrHS5cuRaVScfjwYd1zVapUSXMDzH/78MMPWbZsGW3atKFSpUq8//77uLm5ZTqlKSAggMOHD7N69WqaNGlCy5YtWb58OVu3btVNncpIaGgoXbp0wcTEhEqVKrFz507dMS8vL1QqVZrRGj8/P1QqFffu3cPLyws3NzeioqJQqVSoVCqmT5+e7nWCg4Pp2bMndnZ2mJmZ0ahRI/78889X2sXExDB48GBMTU0pW7YsK1euTHM8JCSEnj17YmZmhrm5OQMGDODJkycABAUFoVKpuHnzZppzlixZQuXKlXWPr127RpcuXTAzM8POzo6hQ4fy/HnGCwlNTU1ZtWoVI0eOzPaOaG/ymYiiz6SEOf2+nUWtdu8qHUUIIUQu0Wo0HFi2gKincj+83CaFTgbWrVuHgYEBvr6+LFu2DHd39zRFxvjx4zlz5gxbt27l6tWr9O/fn86dO3Pr1q10+9u9ezcTJ05kypQpXLt2jY8//hg3NzdOnDgB/LN7l1qdesdcb29vrK2tdcXTo0ePCA4OztEuXlFRUVhZWWV4/MyZM1hYWNCwYUPdcx06dEBPT++VHcz+a9q0afTt25crV67g6urKoEGDdPeXyUrz5s1ZunQp5ubmhIaGEhoammaB/7/FxsbStWtXPD09uXz5Mp07d6ZHjx6EhISkabdw4ULq1q3L5cuX+fLLL5k4cSLHjh0DQKPR0LNnTyIiIvD29ubYsWPcuXOHgQMHAqkbFTRs2JBNmzal6XPTpk0MGTIEgMjISN555x1cXFy4cOEChw8f5smTJwwYMCBbrzm73uQzEW8HfQMDOo2eSOv3P0Slkn/ChRCiKEh4Gcv+pfNRp6QoHaVIke+SGXBwcGDJkiVUq1YNV1dXJkyYwJIlS4DU0QEPDw927NhBq1atqFy5MlOnTqVly5Z4eHik29+iRYsYPnw4Y8eOxcnJicmTJ9OnTx8WLVoEQKtWrYiJieHy5ctotVpOnjzJlClTdIWOl5cXZcuWpUqVKtnKf/r0abZt25bplKewsDBsbW3TPGdgYICVlRVhYZn/VqF///589NFHODk5MXPmTBo2bMjy5dlbUGdkZETJkiVRqVTY29tjb2+f4fqTunXr8vHHH1OrVi2qVq3KzJkzqVy5Mvv27UvTrkWLFnz55Zc4OTkxYcIE+vXrp/u8PD098ff3Z/PmzTRo0IAmTZqwfv16vL29OX/+PJA6XWzLli26/oKCgrh48SKurq4ArFixAhcXF+bMmUP16tVxcXFhzZo1nDhxgqCgoGy97ux4k89EvF0a9ehDz8++wbCYidJRhBBC5IKw4Fv8tTn9nyPF65FCJwNNmzZFpVLpHjdr1oxbt26hVqvx9/dHrVbj5OSEmZmZ7svb25vg4OB0+wsICKBFixZpnmvRooVuFMTCwoK6devi5eWFv78/RkZGjBo1isuXLxMbG4u3t3e2dvGC1ClWPXv25Pvvv6djx46v+Q5k7r/3bGnWrFm2R3RyIjY2lqlTp+Ls7IyFhQVmZmYEBAS8MqKTWZ6AgAAcHBxwcHDQHa9RowYWFha6NoMGDeLevXucPXsWSB3NqV+/vm4ntStXrnDixIk0n/ffxzL6zIXIa5UbNGHwjAWUsLZROooQQohccPHAXoIvygyO3GKgdIDCKDY2Fn19fS5evIi+vn6aY2+yM1bbtm3x8vLC2NiYNm3aYGVlhbOzM6dOncLb25spU6Zk2ceNGzdo3749o0aN4ttvv820rb29PU+fPk3zXEpKChEREdleU5Ievf+/58e/1zQlJye/Vl9Tp07l2LFjLFq0iCpVqmBiYkK/fv1095nJLfb29rzzzjts3ryZpk2bsnnzZsaMGaM7HhsbS48ePZg/f/4r55YuXTpXc+TFZyKKLpsKFXGd7c7eRbMIvRWodBwhhBBv6PBPSxk6/0fM5ZdYb0xGdDLw3/UQZ8+epWrVqujr6+Pi4oJarebp06dUqVIlzVdGP4w6Ozvj4+OT5jkfHx9q1Kihe/z3Oh1PT880N5/csmULQUFBWa7PuX79Ou3ateODDz5g9uzZWb7GZs2aERkZycWLF3XPHT9+HI1GQ5MmTTI99++Rj38/dnZ2BsDGJvUvZmjoP9vg+vn5pWlvZGSkW4+UGR8fH4YPH07v3r2pXbs29vb23Lt3L0d5nJ2defDgAQ8ePNAdv3HjBpGRkWnef1dXV7Zt28aZM2e4c+cOgwYN0h2rX78+169fx9HR8ZXP3NQ09+5v8iafiXh7mVpYMuC7uVRvkb1RXyGEEAVXQmwMB35ciCYbPyeJzEmhk4GQkBAmT55MYGAgW7ZsYfny5bp70jg5OeHq6sqwYcPYtWsXd+/exdfXl7lz53LgwIF0+/vss89Yu3Ytq1at4tatW7i7u7Nr1640i/Bbt25NTEwM+/fvT1PobNq0idKlS+Pk5JRh3mvXrtGuXTs6duzI5MmTCQsLIywsjGfPnuna+Pr6Ur16dR49egSkFgCdO3dm5MiR+Pr64uPjw/jx4xk0aBBlypTJ9P3ZsWMHa9asISgoiO+//x5fX1/Gjx8PpO4O5+DgwPTp07l16xYHDhxg8eLFac53dHQkNjYWT09Pnj9/nuaGmP9WtWpVdu3ahZ+fH1euXGHIkCFoNJpX2vn4+LBgwQKCgoJYuXIlO3bs0H1eHTp0oHbt2ri6unLp0iV8fX0ZNmwYbdq0SbPov0+fPsTExDBmzBjatWuX5j0YN24cERERDB48mPPnzxMcHMyRI0dwc3PLtGC7ceMGfn5+REREEBUVhZ+fX5qiLzc/E/F2MzAyotsnn9F8gCv8a9qtEEKIwudx4A18tm9UOkahJ4VOBoYNG0Z8fDyNGzdm3LhxTJw4Mc3Cfg8PD4YNG8aUKVOoVq0avXr14vz585QvXz7d/nr16sWyZctYtGgRNWvW5JdffsHDwyPNKI2lpSW1a9fGxsZGt/6jdevWaDSaLNfn7Ny5k2fPnrFx40ZKly6t+2rUqJGuTVxcHIGBgWmmkW3atInq1avTvn17unbtSsuWLfn111+zfH9++OEHtm7dSp06dVi/fj1btmzRjY4YGhqyZcsWbt68SZ06dZg/fz6zZs1Kc37z5s0ZPXo0AwcOxMbGhgULFqR7HXd3dywtLWnevDk9evSgU6dO1K9f/5V2U6ZM4cKFC7i4uDBr1izc3d3p1KkTkHqD071792JpaUnr1q3p0KEDlSpVYtu2bWn6KFGiBD169NDtJPdvZcqUwcfHB7VaTceOHalduzaTJk3CwsJCN1UvPV27dsXFxYU//vgDLy8vXFxccHFx0R3Pzc9ECIBmfQfTfeIXGBgZKx1FCCHEG/Ddu1Pur/OGVNp/L6QQQghRJITdDmLPolm8fBGhdBQhhBCvqXhJC4YtWI6phaXSUQolGdERQogiyL6KE65z3LF1rJx1YyGEEAVSXFQkh39aonSMQksKHSGEKKJKWFkzaMZ8qjRqlnVjIYQQBdK9K5e4+udhpWMUSlLoCCHS8tsCGtnppagwNC7Ge1O+pnGv/kpHEUII8Zq8NvyPqKdPlI5R6EihI4T4x8lFsGc0bOoPCVFKpxG5RKVS0WrwB3QZNxl9Q0Ol4wghhMih5IR4jqxaiiytzxkpdIQQqQL2w/H/3x0v2BNWvwsRd5XNJHJVjdbv0P/b2ZiYl1Q6ihBCiBx6cMOfy4f3Kx2jUJFCRwgBYf6waxTwr98UPQ+E1e3h/mnFYoncV7Z6DVxnu2PtUEHpKEIIIXLory1reRH6SOkYhYYUOkK87eIiYKsrJL9M51g4rO8Jlzflfy6RZ0ra2jF45kIqujTMurEQQogCIyUxkcM/LUWbzs3Txauk0BHibabRwO8fQeT9jNuok2DvWDg6LbW9KBKMTIrT6/Np1O/aU+koQgghcuBxUAAXDuxROkahIIWOEG8zrzmp63Gy4/SPsO19SEpn5EcUSnp6+rT7YCTvjhyPnr6B0nGEEEJk0+ltGwl/+EDpGAWeFDpCvK0CD6Xuspajcw7A/zpB1MO8ySQUUadDZ/p+PYNipmZKRxFCCJENKclJHPllmezClgWVVt4hId4+EXfh1zavv4W0mR0M2gzlZI1HUfIi9BG758+Qha5C5JHjAbc56B9Iq6qO9HSpmeaYVqtl9V/nCQx7xvAWDahV1j7DfmISEjlw9SZBYc+IT06mkk0pernUxKaEqa7NPr8bnL/3ECN9fbrVqU79CmV1x648COXCvYeMaNUo91+kyFfvjppAnfadlI5RYMmIjhBvm+QE2D7sze6TE/sE1nYD/525l0sozrJ0WYbMWkz5WnWVjiJEkRMSEcmZOyGULlki3eN/Bd1FlY1+tFota30uEB4bx/CWDfn03VZYFjfhF+9zJKakAHD98RMuhzxmVOvGdK9bne0XrvIyMQmA+KRkDvkH0qd+rdx6aUJBf21eS1y03PcuI0Wu0Gnbti2TJk16oz7Wrl2LhYVFruQpaFQqFXv27FE6ho6joyNLly5VOsbb5dDnEHb1zftJSYDfR8CJOSADw0VGMTMz+n49gzodOisdRYgiIzE5hc1n/ejfsA4mRq/etPfRiyi8g+4yoFGdLPt6HvuS++GR9G1Qi/JWFtiam9GnQS2S1Wr8Qh4D8DQ6lso2VjhYWeBSvizFDAwIfxkHwIGrN2leuTyWpia5+yKFIhJiYzi5yUPpGAVWkSt0CqPw8HA6d+5MmTJlMDY2xsHBgfHjxxMdHZ3peREREbi6umJubo6FhQUjRowgNjY2z/MW5ULwb15eXvTs2ZPSpUtjampKvXr12LQp6y2WQ0JC6NatG8WLF8fW1pbPPvuMlP//DVuBcGUbXFqXu316z4edbpAcn7v9CsXo6evz7sjxtPtgJCo9+TYhxJvadekazqVtcbKzfuVYUoqaTef86F2/JuYmxbLsK0Wduvulgf4/fzf1VCoM9PS4+/wFAGUszHnwIoq4pGQeRkSRrNZgbWbK3WcRPHwRRcuqFXPplYmC4Lq3Jw9vXlc6RoEk38EKAD09PXr27Mm+ffsICgpi7dq1/Pnnn4wePTrT81xdXbl+/TrHjh1j//79nDx5klGjRuVT6qLt9OnT1KlTh99//52rV6/i5ubGsGHD2L8/4zsSq9VqunXrRlJSEqdPn2bdunWsXbuW7777Lh+TZyI8GA5Mzpu+r+8Gj64QE5Y3/QtF1O/ak95ffI+RSXGlowhRaF0OecyjyGi61qmW7vF9fjdwLGWZ6Zqcf7M1N8OiuAkHrwYSl5RMilrD8YBgouITiI5PAKCavQ31y5dl2Z+n2Hr+CoMa18VIX5/fL12jX4PanA6+z/xDXqzwPE1YVEyuvVahEK0Wz9U/oVGrlU5S4BTJQiclJYXx48dTsmRJrK2tmTZtWppdKRITE5k6dSply5bF1NSUJk2a4OXllWmfq1atonLlyhgZGVGtWjU2bNigOzZ16lS6d++ue7x06VJUKhWHDx/WPVelShVWr16dbt+WlpaMGTOGhg0bUqFCBdq3b8/YsWP566+/MswTEBDA4cOHWb16NU2aNKFly5YsX76crVu38vjx40xfS2hoKF26dMHExIRKlSqxc+c/6yy8vLxQqVRERkbqnvPz80OlUnHv3j28vLxwc3MjKioKlUqFSqVi+vTp6V4nODiYnj17Ymdnh5mZGY0aNeLPP/98pV1MTAyDBw/G1NSUsmXLsnLlyjTHQ0JC6NmzJ2ZmZpibmzNgwACePHkCQFBQECqVips3b6Y5Z8mSJVSuXFn3+Nq1a3Tp0gUzMzPs7OwYOnQoz58/z/A9+vrrr5k5cybNmzencuXKTJw4kc6dO7Nr164Mzzl69Cg3btxg48aN1KtXjy5dujBz5kxWrlxJUlJShuflC3Uy7PwQkvJwxO/xJfjtHQi9knfXEPmuYr0GDJm1iJK2dkpHEaLQiYyLZ+/l6wxpUg9Dff1Xjl9/9ITbT5/Ts16NbPepr6fH8OYNeB77ku/2HOXrXYcJfhZOdXsbVKp/Vvl0quXEV13bMbVTa2qXs+f4zdtUtbVGT0+FZ8BtxrVrRuNKDmzx9cuNlyoU9vzBfS7KvXVeUSQLnXXr1mFgYICvry/Lli3D3d09TZExfvx4zpw5w9atW7l69Sr9+/enc+fO3Lp1K93+du/ezcSJE5kyZQrXrl3j448/xs3NjRMnTgDQpk0bTp06hfr/K2lvb2+sra11xdOjR48IDg6mbdu22cr/+PFjdu3aRZs2bTJsc+bMGSwsLGjY8J9drzp06ICenh7nzp3LtP9p06bRt29frly5gqurK4MGDSIgICBb2Zo3b87SpUsxNzcnNDSU0NBQpk6dmm7b2NhYunbtiqenJ5cvX6Zz58706NGDkJCQNO0WLlxI3bp1uXz5Ml9++SUTJ07k2LFjAGg0Gnr27ElERATe3t4cO3aMO3fuMHDgQACcnJxo2LDhK9PKNm3axJAhQwCIjIzknXfewcXFhQsXLnD48GGePHnCgAEDsvWa/xYVFYWVlVWGx8+cOUPt2rWxs/vnB8JOnToRHR3N9esKDyn/OR1C/fL+OtGPYE0XCPgj768l8k2pcuUZMtudstWz/8OYEAIevogiNjGJpcdO8fmOg3y+4yB3nkVw6tY9Pt9xkKAnzwiPjWPanqO64wDrTl/kpxNnMuy3nFVJJndsxcxeHfmuR3tGtm7My6RkSpmmP/r6NDqWS/cf0bmWE8FPw6lobYVZMWPqOpTm0YtoEpIL0BRr8drO7NxC9POnSscoUIrkHeIcHBxYsmQJKpWKatWq4e/vz5IlSxg5ciQhISF4eHgQEhJCmTJlgNQRmcOHD+Ph4cGcOXNe6W/RokUMHz6csWPHAjB58mTOnj3LokWLaNeuHa1atSImJobLly/ToEEDTp48yWeffaZb9O/l5UXZsmWpUqVKprkHDx7M3r17iY+Pp0ePHhmOAAGEhYVha2ub5jkDAwOsrKwIC8t8+lD//v356KOPAJg5cybHjh1j+fLl/PTTT5meB2BkZETJkiVRqVTY22c+zF63bl3q1v1n96aZM2eye/du9u3bx/jx43XPt2jRgi+//BJILVx8fHxYsmQJ7777Lp6envj7+3P37l0cHBwAWL9+PTVr1uT8+fM0atQIV1dXVqxYwcyZM4HUUZ6LFy+yceNGAFasWIGLi0uaz3bNmjU4ODgQFBSEk5NTlq97+/btnD9/nl9++SXDNmFhYWmKHED3OKvPJE9ptfAy49GrXJf8ErYNhfbfQas8mion8l1x85L0nzabY7+u4Lp3Nm8yK8RbroqtNVM6tU7z3DbfK9iam9GuemVMjQxpWrlCmuOLj5zkvbo1qFEm61HUvzc2eBbzkocvIulc69XvZ1qtlp0X/elRrwbGhgZotVo02tR1PhqNVtdGFH7JiQmcWPsrPad+q3SUAqNIjug0bdo0zfBts2bNuHXrFmq1Gn9/f9RqNU5OTpiZmem+vL29CQ4OTre/gIAAWrRokea5Fi1a6EZBLCwsqFu3Ll5eXvj7+2NkZMSoUaO4fPkysbGxeHt7Zzo687clS5Zw6dIl9u7dS3BwMJMn580Pic2aNXvlcXZHdHIiNjaWqVOn4uzsjIWFBWZmZgQEBLwyopNZnoCAABwcHHRFDkCNGjWwsLDQtRk0aBD37t3j7NmzQOpoTv369alevToAV65c4cSJE2k+77+PZfSZ/9uJEydwc3Pjt99+o2bNmlm2L3BUKujzC/T5DYzN8+miWvD8AXaPgRSFp+2JXKNvYEjnsZ/Sasjw1D9XQohMFTM0oHTJEmm+jAz0MTUypHTJEpibFHvlOIClqQmlzP4ZnZl/yAv/h//8wuzKg1BuPw0nPDaOa4/C+NX7HLXK2FPN3uaVDOfuPMDU2Iia/184OVpbcftpOPfDX3Ay6C525mbp7gQnCqfb589y9/IFpWMUGEVyRCczsbGx6Ovrc/HiRfT/M1/WzOz17wretm1bvLy8MDY2pk2bNlhZWeHs7MypU6fw9vZmypQpWfZhb2+Pvb091atXx8rKilatWjFt2jRKly6dbtunT9MOT6akpBAREZHlSEtm9P5/h6V//3YnOTn5tfqaOnUqx44dY9GiRVSpUgUTExP69euX6+tV7O3teeedd9i8eTNNmzZl8+bNjBkzRnc8NjaWHj16MH/+/FfOTe+9/Tdvb2969OjBkiVLGDZsWJY5fH190zz391qiN/lMck2dAeDQGH4fCQ99s26fG65shhd3YeAmMC2VP9cUea5xz35YlinLoeWLSU5MUDqOEEXes5iXJPzre3F0fAL7/G4Qm5hIiWLFaFihLB1qVH3lvJiERDwDbjO+fXPdc+VLWdDaqRL/++s8ZsZGDGpcLz9egshH3hvXUKGuC3p6r64Le9sUyULnv2tUzp49S9WqVdHX18fFxQW1Ws3Tp09p1apVtvpzdnbGx8eHDz74QPecj48PNWr8M1+9TZs2rFmzBgMDAzp3Tr3/RNu2bdmyZQtBQUHZXp/zN40mdVg5MTEx3ePNmjUjMjKSixcv0qBBAwCOHz+ORqOhSZMmmfZ99uzZND+0nz17FhcXFwBsbFJ/GxQaGoqlpSWQuhnBvxkZGenWI2XGx8eH4cOH07t3byC14Lh37166ef772NnZGUh97x88eMCDBw90ozo3btwgMjIyzfvv6urK559/zuDBg7lz5w6DBg3SHatfvz6///47jo6OGBhk/4+8l5cX3bt3Z/78+dnaza5Zs2bMnj2bp0+f6qYVHjt2DHNz8zRZFWXpCG6HUreE/msxaPNhh5aQM/BbOxiyDWyd8/56Il9UbdSMkjMWsHvBDGLD83FqpBCF3Nh2zTI9vmhAtyyfa+VUkVZOWW8RXaKYMd90f+eV5zvWrErHmq8WRqJoCH8YwrXjx+R+aBTRqWshISFMnjyZwMBAtmzZwvLly5k4cSKQugbE1dWVYcOGsWvXLu7evYuvry9z587lwIED6fb32WefsXbtWlatWsWtW7dwd3dn165daRbht27dmpiYGPbv368ratq2bcumTZsoXbp0putADh48iIeHB9euXePevXscOHCA0aNH06JFCxwdHQHw9fWlevXqPHr0CEgtADp37szIkSPx9fXFx8eH8ePHM2jQIN3ao4zs2LGDNWvWEBQUxPfff4+vr69uzUyVKlVwcHBg+vTp3Lp1iwMHDrB48eI05zs6OhIbG4unpyfPnz8nLi4u3etUrVqVXbt24efnx5UrVxgyZIiugPs3Hx8fFixYQFBQECtXrmTHjh26z6tDhw7Url0bV1dXLl26hK+vL8OGDaNNmzZpNmLo06cPMTExjBkzhnbt2qV5D8aNG0dERASDBw/m/PnzBAcHc+TIEdzc3DIs2E6cOEG3bt345JNP6Nu3L2FhYYSFhREREaFrs3v3bt0UOICOHTtSo0YNhg4dypUrVzhy5Ajffvst48aNw9jYONPPJF/pG8A738DwA1DSIev2uSHyPvyvI9w6lj/XE/nC1rESrrPdsa8sPzAJIURBcnrHJpIS5P52RbLQGTZsGPHx8TRu3Jhx48YxceLENL+R9/DwYNiwYUyZMoVq1arRq1cvzp8/T/ny5dPtr1evXixbtoxFixZRs2ZNfvnlFzw8PNKM0lhaWlK7dm1sbGx0P/y2bt0ajUaT5focExMTfvvtN1q2bImzszOffvop7733Xpp7tsTFxREYGJhmGtmmTZuoXr067du3p2vXrrRs2ZJff/01y/fnhx9+YOvWrdSpU4f169ezZcsW3YiDoaEhW7Zs4ebNm9SpU4f58+cza9asNOc3b96c0aNHM3DgQGxsbFiwYEG613F3d8fS0pLmzZvTo0cPOnXqRP369V9pN2XKFC5cuICLiwuzZs3C3d2dTp06AaBSqdi7dy+Wlpa0bt2aDh06UKlSJbZt25amjxIlStCjRw/dTnL/VqZMGXx8fFCr1XTs2JHatWszadIkLCwsdFP1/mvdunXExcUxd+5cSpcurfvq06ePrk1UVBSBgYG6x/r6+uzfvx99fX2aNWvG+++/z7Bhw5gxY0ZGH0WeSNYkc/DOwawbVmgGo09BzT5Zt80NidGweSCcyXrTC1F4mFlaMWD6PKo1y94IuRBCiLz3MvIF5/f9rnQMxam0stWGEEXKj5d+5Df/32hbri0zWszAsphl1idd3gSHPs/b++z8W4Ph0HVx6uiSKBK0Wi1ndm7mzM4tSkcRQggBGBgb8+HSXyhhZa10FMVIoSNEEXLpySXcjrjptg61MbFhVstZNC/TPIszgfBg+P2j1Bt/5oeKrWHAejDJRiEmCo2bPt4cWbWMlGTZbU8IIZRWs00HOo+dpHQMxUihI0QREZsUS78/+vEo9lGa51WoGFpjKJPqT8JQP4stRNXJcGIO+CwF7avrqXJdqSoweBtYZ36PKVG4hN4OZO/CWbyMfKF0FCGEeKupVHq8P28pto6VlI6iiCK5RkeIt9Fc37mvFDkAWrSsv7Ee14Ou3Im6k3kn+obQ4XsYtg/My+ZR0n8Jvw2r28Md77y/lsg3patUY8hsd2ze0m+sQghRUGi1Grw3rlE6hmKk0BGiCPjz/p/sC96XaZuAiAAG7R/EjqAdWXdYsVXqRgXO7+VSwkwkRMLGPnDBI++vJfKNubUNg39YQOWGTZWOIoQQb7UQfz/u+l1UOoYiZOqaEIVcZEIkvfb2IjwhPNvnvOPwDj80/wGLYhZZN764Dg5/BckvXz9kdjUZA51mg9zkrMjQajT8tWWd7P4jhBAKsqtUhffnLlU6Rr6TER0hCrl55+flqMgBOP7gOH3/6Mu50HNZN27wAXx8EkrXfc2EOXBuFWwZBAnReX8tkS9Uenq0dnWj05hJ6Ofghr1CCCFyz5M7twm+6Kt0jHwnhY4QhZj3A28O3En/RrdZeRr3lFHHRuF+0Z1kTXLmja2rwIg/ofkngOq1rpdtt46m3lz0xf28vY7IV7XadqDft7MwKWGudBQhhHgrvY3b/8vUNSEKqZikGHrt6cXT+Kdv3FfNUjWZ33o+FcwrZN04+ATsGQMxoW983UwVt4ZBm6C8rPEoSiKfhLFnwQzCH4YoHUUIId46vb/4nkr1GykdI9/IiI4QhdTiC4tzpcgBuB5+nf5/9Gf3rd1ZN67cDkb7QLWuuXLtDMU9h3XvwZWteXsdka8s7OwZPHMhjnXrKx1FCCHeOmd2blY6Qr6SER0hCqHzYecZcWQEWnL/r2/HCh35vvn3mBtlY4rR+f/BkW8gJT7Xc6TR8lNo/z2o8njanMg3Go0ar3WruXz4D6WjCCHEW6X3l99TyeXtGNWRQkeIQiZJnUTffX25F30vz65hb2rP3JZzaWjfMOvGzwJh5wh44p9neQCo3h36/ApGpnl7HZGv/I4e5MTaX9Co1UpHEUKIt4J9FSdcZ7srHSNfyNQ1IQqZX67+kqdFDkDYyzBGHB3Bj5d+JEWTknljm2ow0hOajiVPNyq4uR/WdIaoV2+KKgqveh270ufLHzA2lQJWCCHyQ9jtIO5cPq90jHwhIzpCFCK3X9ym//7+WRcfuaiOdR3mtZ6HQwmHrBvf/hN2j4GXubN2KF1m9jB4M5RtkHfXEPku4vFDds//gciwPN7kQgghxFszqiMjOkIUIjPPzszXIgfg6vOr9P+jP/uC92XduEoHGHMaqnbMu0CxYeDRDa7tyrtriHxnVaYcQ2a741CzjtJRhBCiyAu7HcQ9v4tKx8hzUugIUUjsv7OfS08vKXLtl8kv+ebUN3x+8nNikmIyb2xmA647oMtCMCiWN4FS4mHnh+A1P2/6F4owMStB369nULt9J6WjCCFEkXd+fzZ2Wi3kZOqaEIXAy+SX9Njdg2fxz5SOQlmzssxtNRcXW5esGz+5Ab+PgKc38i5QrX7QcyUY5lFRJRRx8cAevDesQavVKB1FCCGKrGELV2BT3lHpGHlGRnSEKAR+ufJLgShyAB7FPsLtsBs/+f2EWpPFTll2NWDkCWg8Ku8CXdsJ67pDbB6uCxL5rkG3XvT6fBpGJiZKRxFCiCLr4v49SkfIUzKiI0QBdzfqLn329cn3tTnZ4WLrwtxWcylrVjbrxkFHYM/Y1BuB5oWSDjB4K9jXypv+hSKehdxjz4IZRD+TQlYIIXKbvqEhI1eswdTCUukoeUJGdIQo4PRUejSwK5g7jF1+epn++/pz8M7BrBs7dUrdqKBy+7wJE/UA1nSCwEN5079QhE15R1xnu1PGyVnpKEIIUeSok5PxO3pA6Rh5RkZ0hCgkPO97svDCQh7FFsz7yPSo1INvmn6DqWEW90PRauHsT/DnD6BOzP0gKj3oMB1aTMz9voViUpKTOfrLjwT8dULpKEIIUaSYlDBn1E9rMTAyUjpKrpNCR4hCJFGdyLrr61jtv5r4lHil47yinFk55reeTx2bbGwRHOYPO0fA88C8CVPvfei+BAyK3j/cb7Nzu7dzatuG1IJZCCFErnh35HjqdOisdIxcJ4WOEIXQk5dPWHJpCQfuFLzhZgOVAaPrjmZknZHoqbKYHZscD0e+hgtr8iZMhRYwcCMUt8qb/oUigs75cGilOymJeTAiKIQQbyGrsg4MX/wTKpVK6Si5SgodIQoxv6d+zPWdy43wPNy++TU1sGvAvFbzsDe1z7rxzQOwdzzER+R+EEtHGLIdbKrlft9CMU/u3GbPwpnERoQrHUUIIYqEPl9Op6JLQ6Vj5CopdIQo5DRaDXtv72XZpWWEJxSsH/rMjcz5rtl3dHLMxg0go0Nh98dw1zv3gxiXhP5roEqH3O9bKCY2Ipw9C2fx5M4tpaMIIUShV6GOC/2+mal0jFwlhY4QRURsUiw/X/mZTTc3FbitqHtV6cVXjb+iuGHxzBtqtXD6R/CcCZrk3A2h0ofO86BJHt7TR+S75KREDq9wJ+icj9JRhBCicFOp+OjH3yhpm42ZGIWEFDpCFDH3ou6x4PwC/nr0l9JR0qhgXoH5reZT07pm1o0f+8HvIyD8du4HafQRdJ4P+ga537dQhFar5fT2jZzdtU3pKEIIUag16T2QloOGKh0j10ihI0QRdfLhSRaeX8i96HtKR9Ex0DNgfL3xuNVyy3qjgqSXcOgLuLwh94NUagf914KJRe73LRQT8NcJjvzyI+rkXB4NFEKIt4SZVSlGrlyDnp6+0lFyhRQ6QhRhyZpkNt3YxC9XfyE2OVbpODpN7Jswu+Vs7Eztsm58Yy/s+wQSInM3hLUTDN4KpSrnbr9CUY+DbrJ30SzioiKVjiKEEIVSr8+nUblBE6Vj5AopdIR4CzyPf86Pl35kz+09aCkYf+VLGpfkh2Y/0L5C+6wbRz2CXaPg/qncDWFimbr9tGPL3O1XKCr6+VN2z5/B85B7SkcRQohCp3LDJvT6bJrSMXKFFDpCvEWuP7/OXN+5XHl2RekoOn2r9uWLxl9gYmCSeUONBnyWwIk5kJubLegZQnd3qD8s9/oUiktKiOfAsgXcuXRe6ShCCFGoqPT0GLXSAzOrUkpHeWNS6AjxltFqtRy4e4AlF5fwNO6p0nEAqFiyIvNbzce5lHPWjR9eTN2o4MXd3A3RbDy8OxP0slg7JAoNrUaD9yYPLu7frXQUIYQoVFoOGkaT3gOUjvHGpNAR4i0VlxzHav/VrLu+jiRNktJxMNQzZGL9iQyrMSzrOzMnxsLBz+DK5twN4dQZ+q4G4xK5269QlP/xo/y5+ic06oK17boQQhRUJe3sGbHst6y/HxdwUugI8ZZ7EPOARecXcfzBcaWjANCsdDPmtJqDtYl11o2v/Q5/fAqJUbkXwLYmDNkKFuVzr0+huAfXr7LPfS4JsTFKRxFCiEKh3zezqFCnntIx3ogUOkIIAM6GnmW+73xuR+bBvWtyyNLYkhktZtDWoW3WjSNDUjcqCDmTewFMbWDQZnBonHt9CsW9CHvMnvkziHj8UOkoQghR4FVr3pruEz9XOsYbkcnoQggAmpZuyo4eO/iy8ZeYG5krmuVF4gsmHJ/ArLOzSEhJyLyxRXkYfgDafg2qN9v3f6VvEo5LYyj2VTBNmrXAd9OcTNvv2LGD6tWrU6xYMWrXrs3BgwfTHF+0aBG2trbY2tqyePHiNMfOnTtHgwYNSEmR6VT5xdK+DINnLaJCHRelowghRIEXfOEcSfFxSsd4IzKiI4R4RWRCJCv8VrAzaCdqrVrRLFUsqjC/9XycLJ2ybvzAF37/CCLv5/g6264lM2xPPD93K0aTcvosPZvEjhvJBG74HNu+8+A/85RPnz5N69atmTt3Lt27d2fz5s3Mnz+fS5cuUatWLa5evUrTpk3Zv38/Wq2W7t274+vrS+3atUlJSaFRo0b8+uuvNGrUKMdZxZvRqNWcWPcrfkcOKB1FCCEKtC7jJlOj9TtKx3htUugIITIUGBHIPN95XHhyQdEcRnpGfNrgU96v8X7WjROi4cAU8N+eo2s0WR1LozL6rOiaus21RqvFYUksExob8eWoAdDrZzAqrms/cOBAXr58yf79+3XPNW3alHr16vHzzz+zfft23N3dOXv2bGr/TZowdepU+vfvz9y5cwkLC2PZsmU5yihy1+Uj+zmx9le0Go3SUYQQokByrNeAvl/9oHSM1yZT14RQ0LMVKwmbPQd1dLTSUdJVzaoaHp09WNRmEWVMyyiWI0mTxPzz8xnz5xjC48Mzb1zMHPr+Br1/BePsTcFLUmu5+FhDh0oGuuf0VCo6VDLgzEM13NgLHl0gOlR3/MyZM3To0CFNP506deLMmdS1QrVr1yYoKIiQkBDu379PUFAQtWrVIjg4GA8PD2bNmpXNVy/yikun7vT5cjrGxU2VjiKEEAVSiL8fcdG5uOFPPpNCRwiFJD9+TPhvv/FiwwaCO3XmxdZtBfY3y50cO7G3117G1hub9Y0989CpR6fou68vfz38K+vGdQfC6L+gXNZTw57HaVFrwc407fQ0O1MVYbH//5mE+sFv78BjPwDCwsKws7NL297OjrCwMACcnZ2ZM2cO7777Lh07dmTu3Lk4Ozvz8ccfs2DBAo4cOUKtWrVwcXHh5MmTWb8ekScc69Zn8MxFWNiVVjqKEEIUOBq1mqAzp5SO8dqk0BFCIU8XLUabmAiA+sULwqZP527ffsSdL5h3ci9mUIwxdcewr9c+Ojt2VixHeEI44zzHMc93HknqLO7/Y+kIboeh9edvvFEBADGPU0d2buzNVvPRo0cTGBhIYGAgo0ePZt26dZQoUYJmzZrx0UcfsXv3btzd3Rk0aBCJ//9nQeS/UuUcGDJ7MeWcaykdRQghCpzAM9n45WIBJYWOEAqIu3yZ6P/s0AWQGBDA/aHDePjppyQ/fqxAsqzZm9qzsM1C1nZeS3Wr6opk0KJlU8AmBh8YzO0XWWyHrW8A73yTujNbSQdO3k+hx5Y4yiyOQfVDNHtuJmNdXIW+Cp68TLtk8clLLRotvLvhJTYLYzCfG02zn59xZM4Q7C1NefLkCQCbNm3CwcGBKVOmoPnPqNy9e/dwcnLi7t27/PDDDyxfvpxz587h5ORE1apVadeuHcnJyQQFBeXqeyRyxqSEOf2+nUnNth2ybiyEEG+RRzdv8DLyhdIxXosUOkLkM61Wy5N58zJtE3PoMMFdu/FsxUo0CVlsr6yQBnYN2NZ9G981+w5LY0tFMgS9CGLwgcFsvbk168YVmsHoU7ws3Zy6dnqs7FpMd8hIX0WDMnp43vlnq2eNVovnnRSM9FW8W8mAg0OKc3GUKe0c9emxJY7qZjF4blzC87BHfPTRRyxatIiqVasSGxubZoOCsWPHMm/ePL777js+/fRTypUrh1qtJjk5WdcmJSUFtVrZ3e0E6BsY0nnMJFq7uqFSybdHIYQA0Go1BJ0tnNPX5F9yIfJZ9P79JFy5mmU7bUICz1esILhrV6IPHcqHZDmnp9Kjv1N/9vfZz/vO72OgMsj6pFyWoE5g9rnZTPCcwIuELH7jZGJBlznHmLVsDb3rpi3OJjc15rdLyazzSyLgmZox+xN4maxl1wATPm9hzHLfJNZcTmZO+2JULaVH+ZJ6HL4cwsz3m2FmWpyAgABu3rxJmzZtCAgIAGDLli0YGhpSokQJgoKCGDduHACNGjXi5s2bHDp0iF9//RV9fX2qVauWJ++PyLlG7/XlvanfYFhMufVoQghRkASd9VE6wmuR7aWFyEfapCRud+5MyuPQrBv/R/FGjbD75muKVVdmulh23Im8w/zz8zn9+LQi17cxsWFWy1k0L9M868bhwaisq7B7oAm9qhsCsMI3iYWnEwmL1VLPXo8fOxejSbnU4q3t2pc4WuixpmcxHJfG8nkLY+xMVXzlmUDwCy2VKjgwZ/5CvvrqK1atWkXjxo1p1KgRhw4donv37mzbto169erpLr969Wq+/fZbjI2N+emnn+jWrVtevCXiDTy9d4c9C2cS8/yZ0lGEEEJRKpUeo1atxczSSukoOSKFjhD5KGLTJp7MfINthfX1sejXD5tJEzGwVGa6WHacCDnBoguLCIkJyfdrq1AxtMZQJtWfhKG+YeZtVSp2Tx9IL46ANns73i3wSWTeqURujjfD1jR1UHx3QDLfeScTb2zD+26jmD59OiNGjKB27drUr1+fiRMnkpyczPTp0+nXr98bv0aRf15GvmDvolmE3gpUOooQQiiqw0fjqPtuF6Vj5IgUOkLkE01SEsHvdiTl/xewvwm9kiWxGTcOyyGDURnk/3Sx7EhWJ7P+xnp+vforcSlx+X59Zytn5rWeR6WSlTJso1Kp2L17N73qloLdH0P0o0z73OyfzMg/4tk7qHiae+7806EevDsT7+TaTJ06FW9vb6pUqcKWLVuwt7encePG3Lp1C1tb2zd9eSIfpSQlceTnZdz08VY6ihBCKKZSg8b0/vw7pWPkiKzRESKfRG7bnitFDoAmKoonc+Zwt3dvXp5WZppYVgz1DRlRewT7e+/nvcrvoUKV9Um5KCAigEH7B7EjaEfWjSu2gtGnwPm9DJtsvZbMR/vi2d7PJP0iB0CrIfHg14wd2odfflrJ7du3SUlJoU2bNlSrVg0nJyfOnTv3mq9IKMXAyIhun3xG8wGuoMrfP8dCCFFQhFy7QkpSFrd1KGCk0BEiH2gSEwn/9ddc7zfx1m1CPhzBg3HjSXrwINf7zw02xW2Y3XI2G7tupLZ17Xy9dnxKPDPOzGDSiUlEJWZxZ+fiVjBwA/T4EQyLpzm0xT8Zt73xbOlrQjenzKfDzTqZSOeysdS/PgN1bAQpKf/s5JacnCy7qxVizfoOpvvELzAwMlY6ihBC5LuUxEQe3PBXOkaOSKEjRD6I3LqVlGd5t6A51tOTO92689R9CZqXL/PsOm+ijk0dNnXdxKwWs7A2sc7Xa3uGeNJnXx/OhZ4jNjYWPz8//Pz8ALh79y5+fn6EhKSuJ/pq502GXW0CpesCqdPVhu2JZ3HHYjQpp09YrIawWA1RCa/O+r3xTM226ynMaGcM9/6i+umJ6Km0/O9//+PAgQPcvHmTRo0a5dvrFrmvWrOWDPx+LqaFbEGuEELkhjuXCuZNzTMia3SEyGOahARuv/su6mfP8+V6Bra22E6ZjPl776EqoNNsXia/5Nerv7LhxgaSNclZn5BL9FR6tIhvwarRq1459sEHH7B27VqGDx/OvXv38PrzKByfSdtRc/G+/+oozAd1DVnb65/th7VaLa084viypRHd/zXqs/+uEeP+1CNRrWLWrFl89NFHefPiRL6KiXjOnvkzeXovWOkoQgiRb0ra2vHR8v8pHSPbpNARIo+Fe6zl6fz5+X5dk3r1sPvma0xq5+90sZwIiQ5h4fmFeD30ytfr1ixVk/mt51PBvELWjYNPwJ4xEJPzLcF19Aygy3xoJEVOUZKcmMDB5Yu5ff6M0lGEECLfDF+8ilLlHJSOkS1S6AiRhzTx8dzu8C7q8HBlAqhUlOzVC9vJn2JgY6NMhmzweeTDgvMLuBN1J9+uaWJgwleNv6J31d5ZN34ZDvvGQ+DBN7to44+h81zQ03+zfkSBodVqObV1Pb57srHphRBCFAGt3/+QRj36KB0jW6TQESIPhf/vfzxduEjpGOiZmmI9dgxWQ4eiMjJSOk66UjQpbLm5hVV+q4hJjsm363as0JHvm3+PuZF51o3Pr4Yj30JK/OtfsEoH6OcBxbJxPVFoXPf25Nivy1H/a/MJIYQoihxq1GbA93OVjpEtUugIkUc0cXGpozkREUpH0TGqUAHbL7+gRLt2SkfJUERCBD9e+pHdt3ejyeZNPN9UadPSzGk5h4b2DbNu/PQm/P4RPHmDnWdsqsPgrWBV8fX7EAXOo5s32Lt4NvHRWezwJ4QQhZievj5jV2/GuLip0lGyJLuuCZFHIjZuKlBFDkDS/fs8HDOWkJGjSLxzV+k46bIqZsX05tPZ2m0r9W3r58s1Q1+GMuLoCH689CMpmix+I29bHUZ6QtOx8Lr3Bnp2E1a3h/sF8x5I4vWUrV4D19mLKVWuvNJRhBAiz2jUau5fvax0jGyRER0h8oA69iXBHTqgjoxUOkrGDA2xcnXFetxY9EuUUDpNhg7dPYT7RXfCXobly/XqWNdhXut5OJTIxkLL23/C7jHw8unrXUzfCLovBRfX1ztfFEhJ8XHsX7aAu5cvKB1FCCHyRL1O3Wj/4RilY2RJCh0h8kD4Gg+eLligdIxs0S9VCptJE7Ho2xeVXsEc5I1PiWfNtTV4XPMgUZ34yvGXgS95fvA58ffjSYlMofyE8pg3yHgNTGxALPfm33vl+WpLq2FoYYipoSnNw5qzY8kOYmNjcXNzw93dXdfu3r17dOzYkQsXLmCulwh7x8Kto6//Apt/Ah1+gAL6/ouc02jUeG9Yw6WDe5WOIoQQuc7aoQIfLFqpdIwsyXdVIXKZVq3mxcaNSsfINnV4OGHTvuNe/wHEXbqkdJx0mRiYMK7eOPb12se7Fd595bgmUUOx8sUoM7RMjvqtOq8q1ZZW030ZmBsAEBURxdIvl+IywoU9B/awceNG9u/frztv7NixzJs3D3NzczCzAdcd0GUBGBR7vRd4+kfY9j4kFcybvYqc09PTp90HI3l35Hj09A2UjiOEELnq+cMQ4mOilY6RJSl0hMhlMZ6eJD9+rHSMHEu4fp37Q1x5NGUqyWH5M00sp8qYlcG9rTtrOq3BydJJ93yJOiWw62uX6ShOegxKGGBoYaj7UumlrrlJepaEvok+dyveZW7oXFyauRAQEADAli1bMDQ0pE+f/2yt2eRjGHkcbJxf78UFHoD/dYKoh693viiQ6nToTN+vZ1DM1EzpKEIIkXu0Wh7evK50iixJoSNELnuxfoPSEd5I9IEDBHftxvNVq9AkvjpNrCBoZN+I7d23822Tb7Ewtnjtfm5/d5ubE29yd+FdXt76ZzTF2M4YTZKG+Pvx3A+7j9cZL+6b3ud5+HOmTZvGihUr0u/QriaM8oLGo14v0BN/+O0deChrO4qS8rXqMGT2YixLl1U6ihBC5JqHN64pHSFLUugIkYsSAgKIu1D4f0jVxsXxbNmP3OnWnegjb7D2JA/p6+kzsPpA9vfez+DqgzFQZX96kKGFIWU+KEP5CeUpP748hlaG3J13l/h7qffH0TfVp9zIcjz87SF3ZtyhZPOSeJt603RIU4aOHMrdu3dxcXGhVq1a7Ny58z+dF4OuC2HIdihunfMXFvsE1nYD/51ZtxWFhmXpsgyZtZjyteoqHUUIIXJFYSh0ZDMCIXLR46++Jmr3bqVj5LriTZti9/VXFHNyyrqxQm6/uM288/P4X6f/ZbkZQXruzL2DoZUhDh+nv9vay5svCdsWRu1ptbn95W12bd+Fvb09jRs35tatW9ja2r56UswT2DMGgj1f5yVBmy+h7Zeges1trEWBo1Gr8Vyziqt/HlY6ihBCvBGVSo+x/9tcoKfmyoiOELkkJTyc6AMHlI6RJ+LOnuVu7z6EzZhZYLfMrmJZhdUdVwNgZWKV4/OLVyxO0tOkdI9pkjU8Xv+YMh+UIeJRBFHxURzRO0K5SuVwcnLi3Llz6Xdawg7e/x06zUndSjqnvOfBzg8hOT7n54oCSU9fn3dHjqfdByML7C6HQgiRHVqthkc3bygdI1Pyr6wQueTFtm1ok9L/QblIUKt5sXkzwZ06E7F5M1q1WulEGfq6ydd84vIJJgYm2T4n/kE8hhaG6R57tu8ZZrXNMHE0QavRggb+uPMH/f/oT0x8DOrM3guVCpqNg488wbpaTl8KXN+VOpUt5knOzxUFVv2uPen9+XcYmRRXOooQQry2hwEFe/qaFDpC5AJtUhKRW7YqHSNfqKOieDJjJnd79+Hl2QxGMvJZbGwsfn5++Pn5AfDw/kMaaRqxqsEqulXqRtiOMB7++s9uZs+PPCf6UjSJTxJJeJhA6KZQXt54iVX7V0eCEh4lEOUbhV0fOwCMSxuDCiK8I7jx1w2CgoK4WfwmGq0m85Cl68DH3tDww5y/wEcX4bd2EHo15+eKAquiS0MGz1xISVs7paMIIcRreXjDX+kImZI1OkLkgqh9+3j8+RdKx1BEiY4dsf38c4zKKbejlJeXF+3atXvl+Q8++IC1a9fy3qD3OHv9LHZTU3+gfHbwGS+8XpD8Ihk9Iz2KORTDpqcNZs5p5xlrtVruzrmLdTdrzOv9s+Yn2i+a0A2haJO12Pa1xaqNFQ3sGjCv1TzsTe2zDnzzAOwdD/EROXuhhqbQ5xdw7pGz80SBFhcdxb7Fswv8FBAhhPgvPX19JqzdgYHRa0zPzgdS6AiRC+7260/CtYI9fJuXVMbGWH3ohvWoUeiZZH+6WH7SarXsub2HZZeWEZ4QnifXMDcy57tm39HJsVPWjaNDYffHcNc7h1dRQfvvoNXk18ooCiZ1SjJHf1nOjZPHlY4ihBA5MmT2YkpXeY2p2flACh0h3lDcpcvcHzJE6RgFgoG9PbZTplCyR3elo2QoNimWn6/8zKabm0jRpOTJNXpX6c2Xjb+kuGEW6y+0WvBZBsdngSY5ZxepOwR6LAODgvlbNPF6zu3Zwamt61P/bAghRCHQfsRY6nXsqnSMdEmhI8Qbevjpp8Qckq1i/82kfn3svvkak5o1lY6SoXtR91hwfgF/PforT/qvYF6B+a3mU9M6G+/B48vw+0cQfjtnFynfDAZuAtNSrxdSFEi3zp/h0PLFJCcmKB1FCCGyVKtdRzqN/kTpGOmSQkeIN5D89Cm332kPKXkzMlCo6elh0bcPNp9+ioFVzrd7zi8nH55k4fmF3Iu+l+t9G+gZML7eeNxquaGnymLvl6SXcOgLuLwhZxexqABDtoGt8+sHFQXO03t32L1gBrHhz5WOIoQQmbJxrMSw+T8qHSNdUugI8QbC/7eGpwsXKh2jQNMrUQLrcWOxcnVFZZj+9s1KS9YkszlgMz9f+ZnY5Nhc77+JfRNmt5yNnWk2dte6sRf2fQIJkdm/gLE59FsDVd997Yyi4Il9EcHehTMJC76ldBQhhMiQnr4BE9btwKAAfo+XQkeIN3DnvZ4kBgUpHaNQMKpUCbuvvsSsVSulo2Toefxzfrz0I3tu70FL7v7TWNK4JD80+4H2Fdpn3TjqEewaBfdPZf8CKn3oNBuajnn9kKLASU5K5MhPSwk8kzdTLIUQIje4znbHvoqT0jFeIYWOEK8p4eZN7vbqrXSMQsesbVvsvvoSowoVlI6SoevPrzPPdx5+z/xyve9+Tv34vNHnWd/MVKOBU+7gNRdysmlCAzfougj0Dd4sqCgwtFotZ3Zu5szOLUpHEUKIdHX4aCx13y14GxLIDUOFeE1Re/YqHaFQivXy4k73HjxZuBB17Eul46SrpnVNNnTdwNxWc7Etbpurfe8M2snA/QMJCA/IvKGeHrSeCh8eBcuK2b/ARQ/Y2AfiX7xZUFFgqFQqmvd3pdsnn2FgKLvsCSEKnid3criZTj6RER0hXoNWreZW27aon8lC4Tehb2ON7aRPKdmnNyqVSuk46YpLjmO1/2rWXV9HkiYp1/o11DNkYv2JDKsxLOvXnhgLBz+DK5uzf4FSVWDIdihV+c2CigIl9FYgexfN4mWkFLJCiILD1rEyQ+cvUzrGK6TQEeI1xP71Fw9GjlI6RpFRrHZt7L/5GpN69ZSOkqGHMQ9ZdGERniGeudpvs9LNmNNqDtYm1lk3vvY7/PEpJEZlr/NiFjBgPVRq80YZRcES/fwZexbM4Nn9u0pHEUIIIHVDgk/W70DfoGBtSJCjqWtt27Zl0qRJb3TBtWvXYmFh8UZ9FFQqlYo9e/YoHUPH0dGRpUuXKh2jSJJpa7krwd+fe4OH8PiLL0h++lTpOOkqV6IcS9st5beOv1HFokqu9Xsm9Ax99/XF+4F31o1r9YUxp1Lvn5MdCZGp09gueLxRRlGwmFvbMGjGAio3bKJ0FCGEAECjTuFF6GOlY7zirVqjEx4eTrly5VCpVERGRmbaNiIiAldXV8zNzbGwsGDEiBHExub+trP/VZQLwb8FBgbSrl077OzsKFasGJUqVeLbb78lOTnzO8OHhITQrVs3ihcvjq2tLZ999hkpCty/Rh37khjP3P2tvgC0WqL27uNO5y48//U3NEm5N00sNzUt3ZSdPXbyVeOvMDcyz5U+IxIiGH98PLPOziIhJYubRFqUh+EHoO3XqTutZUWTAvsnwaEvQaPOlbxCeUbFTOg55Rsa9uijdBQhhAAg4vFDpSO84q0qdEaMGEGdOnWy1dbV1ZXr169z7Ngx9u/fz8mTJxk1SqYq5QZDQ0OGDRvG0aNHCQwMZOnSpfz22298//33GZ6jVqvp1q0bSUlJnD59mnXr1rF27Vq+++67fEyeKubIEbQJcsfyvKKJi+OZuzt3uvcosAWlvp4+Q5yHcKD3AQZWG4h+dgqObNgWuI3BBwYT9CKLLcv19KHtF/Dh4dQbhmbHuVWwZRAkRL95UFEgqPT0aPP+h3QaPRF9A9llTwihrBePHykd4RU5LnRSUlIYP348JUuWxNrammnTpvHvZT6JiYlMnTqVsmXLYmpqSpMmTfDy8sq0z1WrVlG5cmWMjIyoVq0aGzb8c2fwqVOn0r17d93jpUuXolKpOHz4sO65KlWqsHr16iyvERkZydSpU7N8jQEBARw+fJjVq1fTpEkTWrZsyfLly9m6dSuPH2c+LBcaGkqXLl0wMTGhUqVK7Ny5U3fMy8vrldEkPz8/VCoV9+7dw8vLCzc3N6KiolCpVKhUKqZPn57udYKDg+nZsyd2dnaYmZnRqFEj/vzzz1faxcTEMHjwYExNTSlbtiwrV65MczwkJISePXtiZmaGubk5AwYM4MmTJwAEBQWhUqm4efNmmnOWLFlC5cr/LHC+du0aXbp0wczMDDs7O4YOHcrz5xkv0q9UqRJubm7UrVuXChUq8N577+Hq6spff2V8n4ijR49y48YNNm7cSL169ejSpQszZ85k5cqVJOXzb/6j9sq0tfyQHBLCw3HjCflwBIm3C+ZuLhbFLPi26bds676NRvaNcqXP25G3Gbx/MBtvbMy6sUNjGH0Kag/IXue3jsL/OsKL+28WUhQotdq9S79vZ2FSIndGGIUQ4nUUiRGddevWYWBggK+vL8uWLcPd3T1NkTF+/HjOnDnD1q1buXr1Kv3796dz587cupX+nZ13797NxIkTmTJlCteuXePjjz/Gzc2NEydOANCmTRtOnTqFWp065cLb2xtra2td8fTo0SOCg4Np27Zthplv3LjBjBkzWL9+PXp6Wb/kM2fOYGFhQcOGDXXPdejQAT09Pc6dO5fpudOmTaNv375cuXIFV1dXBg0aREBAFtvI/r/mzZuzdOlSzM3NCQ0NJTQ0NMPCLDY2lq5du+Lp6cnly5fp3LkzPXr0ICQkJE27hQsXUrduXS5fvsyXX37JxIkTOXbsGAAajYaePXsSERGBt7c3x44d486dOwwcOBAAJycnGjZsyKZNm9L0uWnTJoYMGQJAZGQk77zzDi4uLly4cIHDhw/z5MkTBgzI5g9ewO3btzl8+DBt2mS8YPrMmTPUrl0bO7t/7izfqVMnoqOjuX79erav9aaSHz8m7vz5fLuegJenT3OnV2/CZs9BHV0wRyOqWVVjTac1LG6zmDKmZd64vyRNEvPPz2fMn2MIjw/PvHExc+j7G/T+FYyz8YPuswD47R0IOfvGOUXBUc65FkNmu1OqXHmlowgh3lJFotBxcHBgyZIlVKtWDVdXVyZMmMCSJUuA1NEBDw8PduzYQatWrahcuTJTp06lZcuWeHikvxh20aJFDB8+nLFjx+Lk5MTkyZPp06cPixYtAqBVq1bExMRw+fJltFotJ0+eZMqUKbpCx8vLi7Jly1KlSvqLgxMTExk8eDALFy6kfPnsfQMICwvD1jbtvTMMDAywsrIiLCws03P79+/PRx99hJOTEzNnzqRhw4YsX748W9c1MjKiZMmSqFQq7O3tsbe3x8zMLN22devW5eOPP6ZWrVpUrVqVmTNnUrlyZfbt25emXYsWLfjyyy9xcnJiwoQJ9OvXT/d5eXp64u/vz+bNm2nQoAFNmjRh/fr1eHt7c/7/f5h3dXVly5Z/blIXFBTExYsXcXV1BWDFihW4uLgwZ84cqlevjouLC2vWrOHEiRMEBWU+/aZ58+YUK1aMqlWr0qpVK2bMmJFh27CwsDRFDqB7nNVnkpui9v0BslFh/ktJ4cWGDQR36syLrVvRajRKJ0pXR8eO7O21l7H1xmZ9Q9BsOPXoFH339eWvhxmPdurUHQij/4Jy2RhZinsO696DK1vfOKMoOCzs7Bk8cyGOdesrHUUI8RYqElPXmjZtmuaeD82aNePWrVuo1Wr8/f1Rq9U4OTlhZmam+/L29iY4ODjd/gICAmjRokWa51q0aKEbBbGwsKBu3bp4eXnh7++PkZERo0aN4vLly8TGxuLt7Z3pSMBXX32Fs7Mz77//fk5f6mtp1qzZK4+zO6KTE7GxsUydOhVnZ2csLCwwMzMjICDglRGdzPIEBATg4OCAg4OD7niNGjWwsLDQtRk0aBD37t3j7NnU3/5u2rSJ+vXrU716dQCuXLnCiRMn0nzefx/L6DP/27Zt27h06RKbN2/mwIEDuuK2IIv6TyEp8pf6xQvCpv/A3T59C+zIWjGDYoypO4Z9vfbRxbHLG/cXnhDOOM9xzPedT5I6i2malo7gdhhafwaqLP55VyfC7o/hzx+keC9CjIub0vvL73Hp3EPpKEKIt0xi3MsCd4+vXF29GBsbi76+PhcvXkRfP+3i3IxGJrKjbdu2eHl5YWxsTJs2bbCyssLZ2ZlTp07h7e3NlClTMjz3+PHj+Pv769bK/L2eyNramm+++YYffvjhlXPs7e15+p8tblNSUoiIiMDe3v61X8ff0+b+vaYpq53GMjJ16lSOHTvGokWLqFKlCiYmJvTr1y/X16vY29vzzjvvsHnzZpo2bcrmzZsZM2aM7nhsbCw9evRg/vz5r5xbunTpTPv+u8CqUaMGarWaUaNGMWXKlFf+7Pydw9fXN81zf68lepPPJCcSAgNJunMnX64lMpd48yb3hw6jRJfO2H32GYZl3ny6WG6zN7VnQZsFDKw+kPm+8wmIeP1feGjRsjFgI75hvsxvNZ8qlplsb61vAO98C5XfgV2jIOpB5p2fcofwW6lT34yKv3ZGUXDo6enzjtvHWJV14MTaX9CoZbc9IUT+iHj8EFMLS6Vj6OR4ROe/a1TOnj1L1apV0dfXx8XFBbVazdOnT6lSpUqar4x+GHV2dsbHxyfNcz4+PtSoUUP3+O91Op6enrq1OG3btmXLli0EBQVluj7n999/58qVK/j5+eHn56dbT/TXX38xbty4dM9p1qwZkZGRXLx4Uffc8ePH0Wg0NGmS+X0L/h75+PdjZ2dnAGxsbIDUDQv+5ufnl6a9kZGRbj1SZnx8fBg+fDi9e/emdu3a2Nvbc+/evRzlcXZ25sGDBzx48M8PQjdu3CAyMjLN++/q6sq2bds4c+YMd+7cYdCgQbpj9evX5/r16zg6Or7ymZuammb5Ov6m0WhITk5Gk8GUpGbNmuHv75+mAD127Bjm5uZpsualgroD2Nss5tBhgrt249mKlWgK6E54DewasLX7Vr5v9j1WxazeqK+gF0EMPjCYrTezMeWsQvPUjQpqZmP74YA/YE0niC5490AQr69ex670+fIHjHPwb7EQQryJgjZ9LceFTkhICJMnTyYwMJAtW7awfPlyJk6cCKQuXnd1dWXYsGHs2rWLu3fv4uvry9y5czlw4EC6/X322WesXbuWVatWcevWLdzd3dm1a1eaRfitW7cmJiaG/fv3pyl0Nm3aROnSpXFycsowb+XKlalVq5buq2LFikDqD/l/r8Px9fWlevXqPHr0SHesc+fOjBw5El9fX3x8fBg/fjyDBg2iTBa/Od6xYwdr1qwhKCiI77//Hl9fX8aPHw+k7g7n4ODA9OnTuXXrFgcOHGDx4sVpznd0dCQ2NhZPT0+eP39OXFxcutepWrUqu3btws/PjytXrjBkyJB0iwQfHx8WLFhAUFAQK1euZMeOHbrPq0OHDtSuXRtXV1cuXbqEr68vw4YNo02bNmk2YujTpw8xMTGMGTOGdu3apXkPxo0bR0REBIMHD+b8+fMEBwdz5MgR3NzcMizYNm3axPbt2wkICODOnTts376dr776ioEDB2JomHpH3d27d+umwAF07NiRGjVqMHToUK5cucKRI0f49ttvGTduHMbGxpl+Jrkl9k8pdAoibUICz1esILhrV6IPHVI6Trr0VHr0c+rHH73/4H3n9zFQvf5geoI6gdnnZjPBcwIvErKYImBiAf09oOdPYJTFqHrYVfi1HTy69NrZRMFToU49hsxajIV95iPsQgiRGyIeZzGLIJ/luNAZNmwY8fHxNG7cmHHjxjFx4sQ095fx8PBg2LBhTJkyhWrVqtGrVy/Onz+f4UYAvXr1YtmyZSxatIiaNWvyyy+/4OHhkWaUxtLSktq1a2NjY6P74bd169ZoNJpM1+dkV1xcHIGBgWmmkW3atInq1avTvn17unbtSsuWLfn111+z7OuHH35g69at1KlTh/Xr17NlyxbdiIOhoSFbtmzh5s2b1KlTh/nz5zNr1qw05zdv3pzRo0czcOBAbGxsWLBgQbrXcXd3x9LSkubNm9OjRw86depE/fqvLkCdMmUKFy5cwMXFhVmzZuHu7k6nTp0AUKlU7N27F0tLS1q3bk2HDh2oVKkS27ZtS9NHiRIl6NGjh24nuX8rU6YMPj4+qNVqOnbsSO3atZk0aRIWFhYZ7nBnYGDA/Pnzady4MXXq1OGHH35g/PjxaXbvi4qKIjAwUPdYX1+f/fv3o6+vT7NmzXj//fcZNmxYphsY5Kbk0FASbtzIl2uJ15PyOJRHn07m/tBhJPxnS/SCwtzInC8af8Hv7/1OizItsj4hE14Pvei7ry+nH5/OurGLK3x8EspksUg9Ngw8usL13W+UTRQsVmXKMWS2Ow41aisdRQhRxL0ILVgzA1RaraxCFSIrERs38eQ/RakowPT1sejXD5tJEzGwLDhzhf/L64EXC88vJCQmJMu2GVGhYliNYUysPxFDfcPMG6uT4cRs8FkG2sx2rlNB269Sb0oqigx1Sgqe//sJ/+NHlY4ihCiibMo7MmzhCqVj6EihI0Q23HdzI+6M3HeksNErWRKbceOwHDIYVQG9c3yyOpn1N9bzm/9vvEx++dr9OFs5M6/1PCqVrJR147t/pe64Fp3FXOpa/aDnSjAs9tq5RMFzYf9uTm70QJtpsSuEEDlXzKwE4/63JeuG+UQKHSGyoI6OJqh5C0hJUTqKeE1GVSpj99VXmLV4s+lieelZ3DOWXlrKH8F/oOX1/lk2MTDhs0af0d+pf9aN4yLgj4kQkMWW6eUawaDNYGabeTtRqNy5dJ4DPy4gKT5e6ShCiCLmkw2/Y2iUP+unsyKFjhBZiDpwgMdTpmbdUBR4Zu3bY/flFxj9695RBc3VZ1eZ5zsP/+f+r91H+/Lt+aH5D5Q0Lpl144vr4PCXkJz+xicAlHSAwVvBvtZrZxIFz7OQe+xZMIPoZ0+zbiyEENn04dJfsCxdVukYwGtsRiDE2+blyZNKRxC5JNbTkzvduvPUfQmal68/TSwv1bGpw6aum5jdcjY2Jjav1YdniCd99vXBN9Q368YNPkjdqKB03YzbRD1I3X46sGDuaidej015R1xnu1PGyVnpKEKIIiQmPFzpCDpS6AiRCa1GQ+xfp5SOIXKRNimJ8F9/JbhLV6L27qUgDmqrVCreq/we+3vv58NaH2Kol8UmA+l4GveUkcdGsuTiEpI1WdyY2LoqjPgTmk8AVOm3SYqFrUNSNzIQRUbxkhb0/24Ozq3aKR1FCFFExEY8VzqCjkxdEyIT8VeucG/goKwbikLLpG5d7L79BpPaBXfr3ZDoEBZeWIjXA6/XOr9mqZrMbz2fCuYVsm4cfAL2jIGY0IzbuLwP3ZdCVru8iULl3O7tnNq2AeTHAiHEG2g5aBhNeg9QOgYgIzpCZCrWW6atFXXxV65wb8BAHn/1NSnPnikdJ13lzcuz/J3l/NLhl+ztqvYf18Ov0/+P/uy+lY3741RuB6N9oFrXjNtc3gjre6ZuaCCKjCa9B9Dj0y8xyKebMAshiqaYiIIzdU1GdITIxN1+/Um4dk3pGCKf6JmaYj12DFZDh6IyMlI6TrpSNClsubmFVVdWEZMUk+PzO1boyPfNv8fcyDzrxudXw5FvISWDnbksK8KQbWBTLcc5RMH15M5t9iyYQewLKWSFEDlXuWETen02TekYgBQ6QmQoJTycWy1byTSOt5BRhQrYfvkFJdoV3HULEQkRLL+8nF23dqHJ4f1QSpuWZm6ruTSwa5B146c34feP4EkGu8AZl4T+HlClfY4yiIItNiKcPQtn8uTObaWjCCEKGduKlRk6r2Cs55Spa0JkIM7XV4qct1TS/fs8HDOWkJGjSLxzV+k46bIqZsX3zb5na7et1Letn6NzQ1+G8uGRD/nx0o+kaLK4P5RtdRjpCU3Hku5GBYlRsKk/+P6WowyiYDOzKsXA6fOo2qS50lGEEIVMXFSk0hF0ZERHiAyEzZrNi40blY4hlGZoiJWrK9bjxqJfooTSaTJ0+O5hFl9cTNjLsBydV8e6DvNaz8OhRDbuLXTrz9SNCl5mcN+VRh9B5/mgb5CjDKLg0mq1+GzbyLnd25SOIoQoJAyMjZm4/nelYwBS6AiRoTu9+5AYEKB0DFFA6Jcqhc2kiVj07YtKr2AOhsenxLPm2hrWXltLgjoh2+eZGprydZOvea/ye1k3jn0Ge8fCraPpH6/UDvqvBROLbF9fFHwBf53gyC8/ok7OYqtyIYQAJm3ajb6B8jtzSqEjRDrUMTEENWkKmpytfRBFX7EaNbD79huK18/ZdLH89Dj2MYsvLObo/QyKkQx0rdiVaU2nYWZklnXjc7/Ase8gJZ2CytoJBm+FUpVzdH1RsD0OCmDvotkFalqKEKJgGvPrRoqXtFA6hqzRESI98ZcvS5Ej0pVw4wb3h7jyaMpUksNyNk0sv5QxK8PitotZ02kNTpZO2T7v4N2D9PujH35P/bJu3ORjGHkcbJxfPfY8CFa3h3tys92ipIyTM65z3LEu76h0FCFEAZfwMlbpCIAUOkKkK+7CRaUjiAIu+sABgrt24/mqVWgSE5WOk65G9o3Y3n073zb5Fgtji2yd8yj2EcMPD2eV3yrUGnXmje1qwigvaDTy1WPxL2B9L7i0PqexRQFmbm3L4JkLqVS/kdJRhBAFWEKsFDpCFFhxF6XQEVnTxsXxbNmP3OnWnegjOZsmll/09fQZWH0g+3vvZ0j1IRiost4oQK1V89OVn3A74saj2EeZNzYsBt0WweBtUNw67TFNMuybAEe+kRHSIsSomAm9PptGg+69lY4ihCigEuNeKh0BkDU6QrxCk5REUMNGaJOSlI4iCpniTZti99VXFKuW/eli+e32i9vMOz+Pc6HnstW+hGEJvm36LV0rdc26ccyT1F3Zgj1fPebUBfquBuNsrP8RhYb/8aP8ufonNOostikXQrxVun7yGc4t2igdQwodIf4r7sIF7r8/VOkYorDS18dy4EBsPpmAvoWF0mky5BniyaLzi3gY+zBb7XtU6sE3Tb/B1NA084ZaLZz9Cf6cDur//LLArlbqJgUW2djKWhQaD65fZZ/7XBJiY5SOIoQoINqPGEu9jtn4BVkek6lrQvyHrM8Rb0St5sXmzQR36kzEpk1o1Vmsc1FI+/Lt2dtrL5+4fIKJgUmW7f+48wf9/+iP/zP/zBuqVNBsHHzkCdbV0h57cg1+ewce+L5BclHQONSsw5DZi7EsU07pKEKIAiJRNiMQomCS9TkiN6ijongycxZ3e/fh5dnsTRPLb0b6RoysM5L9vffTvVJ3VKgybf8g5gHDDg3j16u/otFmseamdB342BsauKV9/uVTWNsdru54w/SiILG0L8OQWYuoUMdF6ShCiAKgoOy6JlPXhPgXrUZDUOMmaArIbiGi6Cjx7rvYfvEFRuXKKh0lQ35P/ZjnO4/r4dezbNvArgHzWs3D3tQ+644D9qduShAfkfb51p9Bu29SR4FEkaBRqzm+9leuHD2gdBQhhILqduxGhxFjlI4hIzpC/FtiYKAUOSJPxBw7xp1u3Xi6bBma+Hil46Srnm09tnTbwozmMyhVrFSmbS8+uUjffX05cu9I1h07d4cxp6HifxamnlwIOz6ApLg3SC0KEj19fTqMGMM7bh+j0pMfMYR4W2lSkpWOAEihI0Qasj5H5CVtYiLhq34muEtXov7Yr3ScdKlUKnpX7c3+3vsZXnM4BnoZb0cdnRTNVO//a+++46OuDz+Ov29m750wQoCQhL1kBUFxgLhwI9U66qx1VK1Vf3bZZe2wQ1utddVarW1t7TJgAihDEAUJewbCJiQhe919f3+gkUggAZJ8bryej0ck9727770v4OXe9/l8P98H9K3F31JdcwdlJTpNuv6f0jnfleyuz7ev+6f04gypam8XPQP4gpHTL9JlD31bIeEdLF4BICB5feT4VIoOcJSGtR1P2QFOV8u+fdrz4IMquXaO6n3031ykO1L3j7lfb138liZnTD7hbd/a8pau/vfVHU95s9mk/Hulr8yTEgZ8vn3vqiOLFOxZdbqx4UMyR4zW7Md/qtiUNNNRAPQwT4tvLDnPMTrAUbZfdrka1q0zHSNgnLN1i/a082I3OzZWj6Uce2zHW4cr9ei+fW22uW02rcr+fPWuF8oP6YXyI8d63BwfrxvjP59i9Ul9vR7fv0+v982U01+O+7DbFXv5ZUq67z454+NNpzmu93a9pyc/fFIlVSXHvY3T7tRdI+7SjUNulN3WwedoTbXS/x6SVv7x822ucGnW76S8S7omNHxCfXWV3v7ZD7Vr/RrTUQD0kOxxk3TR1x82HYOiA3zG8ni0cdRoWY2NpqMEjPKWFh09eL25sVFf2VWql3r31hntTGl563ClfnTggP7TL6t1m01SovPI9KmNDQ2avXOHnsnoJUvSnbt36Y2+fZUdEqoWy9JVO0r03ZRUDQ3reLlkX2OPilLinXcq/ktzZHO5Or6DAc3eZr22/jX97pPfqab5+MeyjUsdpx/k/0ApESkd73TtP6R/3SM1VH66wSad/eiRhQoQMDwtzZr3+6e1dsG7pqMA6AH9x4zXpQ/+n+kYTF0DPtO0Ywclp4vFO51KOuprYW2NertcGhsWftz72KQ29/ms5EjStqYmZYeEaHxEhCZERCg7JETbmo6clPKF8nKNCQv3y5IjSd7qah144gltu+RS1bz/vuk47XLZXfry4C/rX7P+pVkDZh131GbZvmW6/F+Xq3BHYcc7HXzpkYUK+uZ/usGSir4v/f1WqYX/HwOFw+nS9Dvu1ZlzbpSto9E+AH6PxQgAH9O4aZPpCAGtybL0r6oqXRYTI9sJppXVeb2atnWLzt66RV/dvUubjyqf2SEhKmlq0p7mZu1ubtaOpiYNdIdoZ1OT3jpcqXuSEnviqXSrpm3bVHrLrSq97XY1lZSYjtOuxLBEfW/S9/TazNc0ImlEu7c53HhY9y64V99d+l3Vt3SwylxMhvTlf0lnPyZ9tvjB6jekly+Sag52bXgYNfbiy3XxA4/KFeqfH0gA6ByPjyxGwNQ14FMHf/UrlT3zW9MxAtb/qqr0jb17VNi/v5Kd7U/NWlVfrx2fjtrUeL16sfyQVtTX6+3Mfkr9dDrX65UVeqW8QpJ0fXycromN002lO3VtbJw8svR0WZmcNpseSU7RmPDjjxz5A5vLpbjrr1PiHXfKEem7q1f9e9u/9YuPfqEDdQfavb5fTD/95MyfKCc+p+Od7fpI+tvNUsX2I5dj+kjXviGl5HVhYph2oGSb/vHk46ouo8gCgahX7hBd/Z0fm45B0QE+U3rXXap5txNTbXBKbiktlcsmPdOrd6fv02xZunD7Ns2MjtbdiUnt3uYfhw+rsKZa305J1czt2/RG30ztb2nWN/bs1bysLLkD4FwejqREJd97n2Ium3XC0TCT6prr9Hzx83pl3Stq9Bw75cxld+meUffo+rzrO34OjdXSfx+UPvnzkcvuKOmKP0jZ53dDcphSW1mhfz75fe3dstF0FABdLC07R9c+/lPTMZi6BnymcSNT17rL7uZmLa2r1eUxsSd1P5fNptyQUO389DicL6poadEzh8r0aHKKVjfUK9PtVqbbrXHhEWqRpZLm9u/nbzwHy7T30UdVctXVql+1ynScdoW7wnX3qLv1j0v+oWl9ph1zfbO3WT9d8VPdNu82ldWXnXhnIVFHVl+7/A9SSIzUVC39+Rpp6dPdlB4mRMTG6apv/0gjZ1wkt58eWwegfd4W35i6RtEBJHlra9W8a5fpGAHrrcOVinc4NCUy8qTu57EsbW5qVJKz/ZNW/vjgAV0fF6dUl0te68gI0NH39QTYeHVDcbFKZl+rPQ89pOYD7U8TM61XVC89ddZT+v15v9eA2AHHXL9071Jd/vblWli6sOOdDb1CumOR1GeCZHmlgkekt++WPL5xkCtOn9Pt1tk33KbbfveKzrvtbqUNGNTxnQD4PJvdN2YfUHQASY1btkjM4uwWXsvSW4cP69KYmGPObfPNvXv084Ofv2F/pqxMi2trVdrUpHUNDXpo7x7taW5udyRoSW2tSpqadG1snCRpSGiotjc16b2aGv2lslJ2m0393O5ufW5GWJYO//NtbZs+Q2XPPifvcUa7TBufNl5/veiveviMhxXtjm5zXXlDue4qukvf/+D77U5zayO2j3TDf6Spj0g2h/Txy9IfZ0l15d2YHj3NHRqmoWefp2t/8DNd/+RvNHL6RQqNOLkPRgD4DsdxPqDsaRyjA0iqePNN7XvsW6ZjBKTFtbW6ZVep/tsvS5lfKB5f3rlDGS6XfpiWLkn68YH9mlddrTKPR9F2uwaHhuruxCTlhYa2uV+D16vLSkr0s/R05R513V8rK/XLsoNy22z6VkrqSY8g+SNXnz5Keegbipp27HQxX1HZUKnfrPqN/rrpr/JYbaczDIgdoCfOfELZcdkd72jnMunvX5Eqd0rxWdK1f5ESB3ZTapjW0tSkzcsWa3VRgXat42SjgD/pM2SYrnzsh6ZjUHQASdr3/R+o4tVXTccATlnExIlKeeRhhQw4drqYr9hYvlFPfPiEPtz3YZvtIY4Q3Tf6Ps3JndPxThqqpP98XSp+UwqNka58Wep/Vjclhq8o37NbxUUFWvdekeoOV5qOA6ADmcNH6fJHvmc6BkUHkKQd139ZdcuXm44BnB6nU3GzZyvpa3fJER3d8e0NmVsyVz9b8TPtqd3TZnt+Rr6+P+n7SghL6Hgnn7wh/fcBqblOmvGENPYr3ZQWvsTT0qKtHy1TcWGBdqxeJcvymo4EoB1Zo8/QrG+YnylD0QEkbRo/QZ7KStMxgC7hiItT0j13K/aqq2Tz0eW1Gz2NenHNi3phzQttTiiaEJqgxyc9rsm9Jne8k4oS6W9fkXZ9KJ1xmzT9R5Ld0X2h4VOqDh5Q8fx5WrNgnmoOdbCSH4AeNXDcRF389UdMx6DoAJ7KSm0aP8F0DKDLheTkKPXRRxQ+dqzpKMe1r3affr7i5/pfyf9at9lk05zcObpv9H1yOzpYUMLTIi38sfT+z6T+Z0tXvCiF+u5oFrqe1+tRyaqPtbqwQNtXfiivj5yRHQhmOZOmaObdD5qOQdEBGtat0/bLLjcdA+g2UTOmK+XBB+VKTzcd5bg+3v+xfrz8x1pfvr51W3Zctn5y5k/UP7Z/xzvYsUT6+62SO0Ka/boU368b08JX1VSUa+2Cd1U8f64O799nOg4QtAZPmabpd95nOgZFB6guKtKuO79qOgbQrWyhoUq4+WYl3PIV2b+wip2v8Fpe/X3z3/Xrlb9WecOR5aNDHaG6f8z9uibnmo53UF8p/fteaft70tWvSn0ndmte+C7LsrRzzScqLizQlg+XytPSYjoSEFSGTjtf5936NdMxKDpA+at/0v7vf990DKBHONPTlPLgg4qeMcN0lOOqaqrSb1f9Vq9vfF0t3iNvUKf2mqrvTfqe4kLjOt7Byj9Jcx+VzvuBNLITK7khoNVXV2nde0VaXVig8t2lpuMAQWH4eTN1zs13mI5B0QH2P/mkyv/wgukYQI8KHzNGKY8+otDcXNNRjmvb4W36yfKfaPGexZKkpLAkfT//+5qY3omRmkNbjyxU0G+yNO07ko8uyoCetXvDOhUXFWjjB4vU0tjByWoBnLLRMy/R1OtvMR2DogPs/vrXVfXf/3V8QyDQ2O2KvfJKJd17j5xxnRgpMWRB6QI9+eGT2lm9UzbZdH3e9bpn1D1yOVwnvqOnWZr/A+nQFmnWs0eO3wEkNdbVav2ihSouLNCBkq2m4wABZ+KVczThitmmY1B0gJJrZqt+1SrTMQBj7DExSvrqVxV37WzZnE7TcdrV7GnWH9f/Uc+tfk61zbXKjc/VE2c+oX4xnVh0YPv70tLfSDN/JsX06v6w8Cv7t23R6sJ3tGHxe2qqrzMdBwgIZ91wm0bNuMh0DIoOsHnKVLXs3286BmCce0B/pTz8sCInTTId5bjK6sv0i49+oX9t/ZdCnaF6cOyDujL7yo7vWFd+ZHRn+Gyp15juDwq/09zQoI1L39fqogLt3bTBdBzAr824637lTT7LdAyKDoKb1dKiDcOGS17Org18JnLaNKV88yG5e/c2HeW4ig8W68fLf6zVZas1rc80fXfidxUTEtPxHT9548h5dgb57mIMMK+sdIeKi+Zq3XtFaqipNh0H8DuzHvq2skaZP4cbRQdBrWnXbm095xzTMQCfY3O7Ff/lLyvx9ttkj/DNY1ssy9K/tv1LT330lGw2m36U/yOdkXZGx3cs2yKVbTpSdmy27g8Kv9XS3KzNy5eouLBApeuKJd4yAZ1yzfeeVMYg84vdUHQQ1Oo+/FA7rrvedAzAZzmTk5V8/9cVffHFsvloKahrrtOzq5/Va+tf07W51+qukXfJZe9goYKWJmn/GillsOQM6Zmg8GsV+/ZoTdFcrV1YqNrKCtNxAJ92w89+q4Re5mcFUHQQ1A6//bb2fOMh0zEAnxc2fLhS/u9RhQ0dajrKcZVWleonK36ig3UH9cSZT6hvdN+O79RQdWQqG9BJXo9HWz9apuKiuSpZ9bEsi6nPwBfd/uwfFRFrfjVPig6CWtnvntXBp54yHQPwDzabYi69VMlfv0/OpCTTaY5rye4l+vXKX+uqQVdp1sBZpuMggFWVHdSa+fO0ZsE8VZcdNB0H8Bn3/uktOZwdjKz3AIoOgtreb39HlW+8YToG4FfsERFKvPMOxV93nWxut+k47Wrxtuj1Da9r6+Gtum/0fYp2M2qD7mN5vSr55GOtLizQto+Xy+vxmI4EGOMMCdE9r/zNdAxJFB0EudLb71DNggWmYwB+yd23r5K/+ZCizjK/hOjxVDRU6M1Nb2ps6liNTB5pOg6CQG1lhdYuLFRxUYEq9+01HQfocZHxCbrtty+bjiGJooMgVzL7WtWvXGk6BuDXIiZPVsrDDyskqxMn7zRkU8UmldWV6Yy0M+S0++ZJURFYLMvSrnXFWl1YoM3Ll8jT3Gw6EtAjkvpk6vonf2M6hiSKDoLc1pkXqmnrVtMxAP/ncin+2muVeNdX5YiKMp3muPbU7FFSeFLHq7IBXai+plrr3yvS6sICHdq103QcoFv1GzlGl33zO6ZjSKLoIMhtyp8sT1mZ6RhAwHAkJCjp3nsUe/nlstntpuMAPmfPpvUqLpqrjUveV3Njg+k4QJcbNm26zr31LtMxJFF0EOQ2DB0mi+kEQJcLzctTyv89qvBRo0xHAXxSU32d1i9aqOKiudq/bbPpOECXmXTVlzT+8mtMx5BE0UEQ89bXa+NI3oQB3Sl65kwlP/iAXKmppqMAPutAyTatLizQhkUL1FhXazoOcFrOv+NeDZl6jukYkig6CGLN+/Zpy1TfXS0KCBS28HAl3vIVxd90k+whIabjAD6rubFBmz5YrNWFBdqzcZ3pOMApueLR76vvsBGmY0ii6CCItZSV6eAvfyVPTbW81TXyVlfLU1vT+r23rs50RCCguDIylPyNbyj6/PNMRwF83qFdpSouKtC694pUX11lOg7QaTf+4neKT+9lOoYkig5wXJbHI29Njbw1NfLUfFqEqquPXK6ulrem9si24xQlz6f3lddr+qkAPiV8/HilPPywQgdlm44C+DxPS7M2L1+q4qK52rnmE4m3bfBxd7/8V7lCQ03HkETRAbqVZVny1tbJW9u2KLUWoeqaExelT/8UCyYg0Dgcirv6aiXd/TU5YmNNpwH8QuX+fVozf67WLHhXtRXlpuMAxwiNiNRXX3jddIxWFB3AD3gbG49blLw11fKcsCgdGX2y6utNPw3gGI6YGCXe/TXFXXONbA6H6TiAX/B6PNr28YcqLirQ9lUfyWLmAHxEYp9MfdlHThYqUXSAoGE1N7dOpzt6at2RAvVZYWpnSl5NtTyfbvPW1jJtAt0iJDtbKY88oojx40xHAfxKdXmZ1syfpzXz56nq4AHTcRDk+o0Yrcse/q7pGK0oOgA6zfJ65a2tPbmiVF0tz6f3aZ2K5/GYfirwUVHnnqvkhx6Su1eG6SiAX7G8Xu0oXqXiwgJtWbFMXk+L6UgIQiPOn6lpN91hOkYrig6AHuetqzvJEaVjp+RZTU2mnwa6iS0kRPE33ajEW2+VPSzMdBzA79QdrtTahYUqLpqrir27TcdBEDnrhts0asZFpmO0ougA8EvepqbTKkqemhpZLCHu05ypqUq+/37FXHSh6SiA39q1bo1WFxVo8weL1dLMB0ToXpc/+rgyh400HaMVRQdA0PpsCfHPitLRU/I81R0VpU9LFUuId7uwUaOU8ugjChs82HQUwG811NRo3fvztaaoQAd3lpiOgwB1y9MvKjoxyXSMVhQdADgNrUuIf6EotRlpOlFRYgnxzrHbFXv5ZUq67z454+NNpwH82t4tG1VcWKANS95XcwMrcqJruEJC9bWX35TNZjMdpRVFBwB8gLeh4ZRXw/tsm9XQYPppdDt7VJQS77xT8V+aI5vLZToO4NeaGuq1YfFCFRfN1b4tm0zHgZ9Lzuyv6574pekYbVB0ACBAHLOE+BeL0mfff3Gk6ahzMXnr6vxiCXF3VpZSHv6mIidPNh0FCAgHd2zX6sICrV80X421tabjwA/lTJqimXc/aDpGGxQdAECrNkuId7YofWGRB28PLiEeOWWKUh7+ptyZmT3yeECga2lq0qZli1VcWKBd69eYjgM/MvHKOZpwxWzTMdqg6AAAupy3ru4Lizx0bkTp6GOXOruEuM3lUtz11ynxjjvliIzo5mcGBI/yPbtUXDRXaxcWqr7qsOk48HEX3vuQBk3wrVF2ig4AwCd5m5qOOtFsx0XJHhKi+JtvUmh2tunoQEDxtLRo64oPtLqwQDuKV/nF9Fb0vOue+JWSM7NMx2iDogMAAIBOOXxgv9bMn6s1C95VTfkh03HgI2w2u772yptyuUNMR2mDogMAAICT4vV6tH3lRyouKtC2jz+UxfnEglp8Rm/d+PPfmo5xDKfpAAAAAPAvdrtD/Uefof6jz1BN+SGtWfCu1syfq8MH9puOBgNSsgaYjtAuRnQAAABw2izL0s7iT7S6qEBbP1wqT0uL6UjoIVOvv0WjZ15iOsYxGNEBAADAabPZbOo7bIT6DhuhuqrDWvdekYoLC1S+Z5fpaOhmKf0Z0QEAAECQ2bVhrYoLC7Tpg8VqaWo0HQddzGaz62sv/UWu0FDTUY5B0QEAAEC3a6yr1fr3F2h1UYEOlmwzHQddxFcXIpAoOgAAAOhh+7ZuVnFhgTYsWaim+nrTcXAa8iafpRl33W86RrsoOgAAADCiuaFBG5a+p+LCAu3dvNF0HJyCs758i0Zd4HsLEUgUHQAAAPiAsp0lWl1UoPXvL1BDTbXpOOika777E2Xk5JmO0S6KDgAAAHxGS1OTNi9fouLCApWuKzYdByfgywsRSBQdAAAA+KiKvbtVXDRXaxcWqu5wpek4+ILE3n315Z8+bTrGcVF0AAAA4NM8LS3a9tFyrS4q0I5PVsqyvKYjQdKI82dq2k13mI5xXJwwFAAAAD7N4XRq4LiJGjhuoqrKDmjN/HlaM/9dVR86aDpaUOuVO9R0hBNiRAcAAAB+x/J6tf2Tj1RcWKBtH38or8djOlLQueO5VxUeE2s6xnExogMAAAC/Y7PblTVyrLJGjlVtZYXWLHhXa4rmqnL/XtPRgkJ8Rm+fLjkSIzoAAAAIEJZlqXTtahUXzdXm5UvkaW42HSlgDT93hs75yldNxzghRnQAAAAQEGw2m/oMGa4+Q4arvrpK696br+KiAh3atdN0tIDTK3eI6QgdYkQHAAAAAW33xvUqLizQxg/eV0tjo+k4AeH2Z/+oiNg40zFOiKIDAACAoNBYV6cNixdodWGBDmzfajqO34pLy9BNTz1rOkaHKDoAAAAIOvu3bVFx0VytX7RATfV1puP4laHTztd5t37NdIwOUXQAAAAQtJobG7Rx6SIVFxZoz6b1puP4hQvuul+5k88yHaNDFB0AAABA0qFdO1VcVKC1781XQ3WV6Ti+yWbTHc/+0eeXlpYoOgAAAEAbLc3N2rJ8iYqLCrRzbbHE2+VWqQOyNecHPzcdo1MoOgAAAMBxVO7bq+L5c7V2wbuqrawwHce4iVfO0YQrZpuO0SkUHQAAAKADXo9HWz9eruLCApWs+liW5TUdyYgv/egppWQNMB2jUyg6AAAAwEmoPlSmNfPnqXj+XFWXHTQdp8dExMXrtt++LJvNZjpKp1B0AAAAgFNgeb0qWb1SxUUF2rpiubyeFtORutWQs87T+bffbTpGpzlNBwAAAAD8kc1uV78Ro9VvxGjVVlZo7cJCrZk/VxV795iO1i2yRo81HeGkMKIDAAAAdKHStatVXDRXm5ctUUtzk+k4XcLhdOrOP/xZ7tAw01E6jREdAAAAoAv1HjxMvQcPU8ONNVr3fpGKCwtUVrrDdKzT0itvqF+VHIkRHQAAAKDb7d28UasLC7RxyXtqbmwwHeeknXXDrRo142LTMU4KRQcAAADoIU31ddqw+D2tLizQ/m2bTcfptK/8+nnFJKeajnFSKDoAAACAAQdKtqm4qEDrFy1QY22t6TjHldp/oOb88BemY5w0ig4AAABgUHNTozYtXaTiornavWGt6TjHmHLdzRpz4SzTMU4aRQcAAADwEYd2l6q4aK7WLSxUfXWV6TiSzaZbn3lRUfGJppOcNIoOAAAA4GM8Lc3a8uEHKi6aqx3FqyRDb9kzcgbrmu8+YeSxTxdFBwAAAPBhhw/sU3HRPK1dME81FeU9+tjTbrpDI86f2aOP2VUoOgAAAIAf8Ho92r5yhVYXFmj7yhWyvN5ufTyb3a7bn/2jwqNjuvVxugsnDAUAAAD8gN3uUP/R49R/9DhVl5dp7fx3VTx/nqoO7u+Wx+szZLjflhyJER0AAADAb1mWpR3Fq1RcWKCtKz6Qp6Wly/Z93u13a+hZ53XZ/noaRQcAAAAIAHVVh7V2YaGKi+aqYs+u09qXw+nU7c++qtDIyC5K1/MoOgAAAECA2bV+jYoLC7Rp2RK1NDWe9P2zRp+hWd/4Vjck6zkUHQAAACBANdTWaP3781VcNFcHd2zv9P0u/vojGjhuYjcm634UHQAAACAI7NuySauLCrRh8Xtqbqg/7u3CY2J16zMvyeH073XLKDoAAABAEGlqqNeGxe9pTdFc7d2y8ZjrR8+8VFOv/4qBZF2LogMAAAAEqYM7S1RcWKD1789XQ22NJOmGnz2jhF59DCc7fRQdAAAAIMi1NDVp87LF2rN5g6bddIfpOF2CogMAAAAg4NhNBwAAAACArkbRAQAAABBwKDoAAAAAAg5FBwAAAEDAoegAAAAACDgUHQAAAAABh6IDAAAAIOBQdAAAAAAEHIoOAAAAgIBD0QEAAAAQcCg6AAAAAAIORQcAAABAwKHoAAAAAAg4FB0AAAAAAYeiAwAAACDgUHQAAAAABByKDgAAAICAQ9EBAAAAEHAoOgAAAAACDkUHAAAAQMCh6AAAAAAIOBQdAAAAAAGHogMAAAAg4FB0AAAAAAQcig4AAACAgEPRAQAAABBwKDoAAAAAAg5FBwAAAEDAoegAAAAACDgUHQAAAAABx2k6AICuV7quXPNeXCt3mFMhYU65w5xyhzrlDnMc+f4424/e5gpxmH4aAAAAp4yiAwSghrpm1Vcf+TpVdrtNrjDHFwrRkVIU0vr959vcoUcVpdb7OGSz2brwmQEAAHQORQcIQM2NntPeh9drqbG2RY21Lae+E5vkDnEcVXw+G01yfKEQHW/bkRJldzDLFgAAnByKDhCAmhtOv+h0CUtqavCoqcEjVTSe8m6cbnvr1DpXB6WozdS8o0ahnC6m4gEAEEwoOkAAamo4jVEYH9TS5FVLU5PqDjed8j7sTttRRek40+2Oc7zS0dPzAACAf+C3NhCAWpp8ZETHh3hbrNM+bslmt8kd6mh7vFJ7xzAdU56O2h7qlM3OcUsAAHQ3ig4QgDwey3SEgGR5LTXWtaix7vSOW3K5j55i18ExTKFHTcU7aruD45YAADghig4QgCyKju+yjiwW0dzoUW3lqR+35HDZjzoWqe0xSyFfWEq87RS9z7e73By3BAAIXBQdIABZXopOoPM0e1Xf3KT6qtM4bslhO+a4JFd7peiYpcM/n4bnYglxAICPougAAchL0UEneD2WGmqb1VB7Gsct2SRXaNvy02Z06aiydKJtdo5bAgB0MYoOEIAY0UFPsSypqb5FTfUtqtFpLCEe4lBIaAfnV2rveKWjtjlcHLcEAPgcRQcIQPQc+JuWRo9aGj2qPY0lxB1Oe+sy4G3Op9TutrbbP9vmCuG4JQAIFBQdIACxGAGCkafFq/pq72ktIW632+QKdXSqFLW/zSl3iIMlxAHAB1B0gADEMTrAqfF21RLiIe2fY+nzVfE+P17J9YXFHj4bhbKzhDgAnBaKDhCAOEYHMMiSmhs8am7wSBWncdzSp0uIf/YVGuFUv2GJyj4jVe4wfn0DQEd4pQQCEEUH8H8tzV61NDep7qglxHeuLdfiv23RgNHJypuUrrQBseYCAoCPo+gAAYiaAwSuliavNizdpw1L9ykuLUJ5k9KUMz5NoZEu09EAwKfYLMviPREQYOY+v0abVxwwHQNAD3E47coakajc/HT1GhTHSVwBQIzoAAGJ84kAwcXT4tXmFQe0ecUBRSeFHRnlmZCmiJgQ09EAwBhGdIAAtOBPG7T2/T2mYwAwyG63qe/QBOXlp6vP4ATZWfIaQJBhRAcIQIzoAPB6LW3/pEzbPylTZFyIciamKW9SuqLiQ01HA4AewYgOEICWvrVFHxfsNB0DgI+x2aTeufHKy09X5vBEOThXD4AAxogOEIAcTt68ADiWZUk715Vr57pyhUW7lTM+VXmT0hWbEm46GgB0OUZ0gAD00Tsl+uAf20zHAOAn0gfGKi8/Xf1HJcnpcpiOAwBdghEdIADxRgXAydizuVJ7Nlfq/TecGjQuVXn56UrIiDQdCwBOC0UHCEAsRgDgVDTWtWj1/F1aPX+XUvpFKy8/XQPHpMgVwocnAPwPRQcIQByjA+B07d9epf3bq7Tozc0aOCZFefnpSsmMNh0LADqNogMEID59BdBVmhs8Wrdoj9Yt2qOEXpEanJ+u7DNSFBLuMh0NAE6IxQiAAFS6oVxvP7XKdAwAAcrpsqv/qGTl5acrfWCs6TgA0C5GdIAAFBrBJ60Auk9Ls1cbl+3TxmX7FJcartxJ6cqZkKqwSLfpaADQihEdIABVlzfolUeWmI4BIIjYnTb1G5akwfnp6pUbJ5vNZjoSgCDHiA4QgMIiGdEB0LO8LZa2fnxAWz8+oOjEUOVOTFfuxDRFxIaYjgYgSDGiAwSoZ7+2QC3NXtMxAAQxm92mvkMSlJefrr5DEmS3M8oDoOcwogMEqNBIl2oqGk3HABDELK+lktVlKlldpojYEOVMSFXepHRFJ4aZjgYgCDCiAwSoN36wXGWlNaZjAEBbNql3Tpzy8jPUb3gi5/0C0G0Y0QECFCuvAfBJllS6vkKl6ysUFuXSoHGpystPV1xqhOlkAAIMIzpAgCr4/Rpt+eiA6RgA0ClpA2I0OD9d/Ucly+nmpMcATh9FBwhQC/+8UWsW7jYdAwBOSki4U9ljU5Q3OV2JvaJMxwHgx5i6BgSo8GhO3AfA/zTWtah44W4VL9yt5L5RystP18CxKXKH8pYFwMlhRAcIUOuX7FXRK+tNxwCA0+YKcWjAmGTl5acrtV+M6TgA/AQfjwABKioh1HQEAOgSzY0erV+8V+sX71VCRoTy8tOVfUYqi64AOCFGdIAAdfhgnV597APTMQCgWzhcdvUfmaS8/HRlZMeZjgPABzGiAwSoyLhQySaJjzIABCBPs1eblu/XpuX7FZsSrtxJacoZn8bxiQBaMaIDBLCXHlqk2sNNpmMAQI+wO2zqNyxRefnp6p0bL5vdZjoSAIMY0QECWGR8KEUHQNDweixtXXlQW1ceVFR8qHInpSl3YtqREW4AQYcRHSCAFTy/RltWcNJQAMHLZrepz+B45U1KV+bQBNkddtORAPQQRnSAABYVz6eYAIKb5bW0o/iQdhQfUniMWzkT0pQ3KV0xSWGmowHoZozoAAGseMEuvff6JtMxAMC32KReg+KUl5+urBFJcjgZ5QECESM6QABjRAcA2mFJuzZUaNeGCoVGuDRofKry8tMVnxZhOhmALsSIDhDAKvbV6rXvLDMdAwD8Qlr/GOXlp6v/6GS53A7TcQCcJooOEMC8Hq+evWehvC38bw4AneUOcyp7bIry8tOV1CfKdBwAp4iiAwS4P39vmcr31JqOAQB+KalPlPLy05U9NkXuMGb8A/6EogMEuILfr9GWj1hiGgBOhzPEoQGjkzU4P12pWTGm4wDoBD6aAAJcHAfXAsBpa2n0aMOSvdqwZK/i0yOUNyldg8anKjTCZToagONgRAcIcFs+OqCC368xHQMAAo7DaVfWyCTl5acrIztWNpvNdCQAR2FEBwhwLJcKAN3D0+LV5g/3a/OH+xWTFKbcSWnKmZCmiJgQ09EAiBEdIOB5PF49d/dCeT38rw4A3c1utylzWKLy8tPVJy9eNjujPIApjOgAAc7hsCsmKUwV++pMRwGAgOf1Wtq26qC2rTqoyLgQ5U5MU+6kdE7gDBjAiA4QBN55rlhbPz5oOgYABCWbTeqdl6C8/DT1G5You8NuOhIQFBjRAYJAfFqEtoqiAwAmWJa0c+0h7Vx7SGHRbuVOSFXupHTFJoebjgYENEZ0gCCw/ZOD+u9vi03HAAB8xiZlZMcqLz9d/Ucky+FilAfoahQdIAjUHm7USw8tNh0DANCOkAinBo1LVV5+uhLSI03HAQIGRQcIEi8/vFg1FY2mYwAATiClX7Ty8tM1cEyKXCEO03EAv0bRAYLEO88Wa+tKjtMBAH/gDnVo4NgU5eWnK7lvtOk4gF+i6ABB4uOCHVr61lbTMQAAJymxd6TyJqUre1yqQsJYRwroLIoOECR2b6zQP36x0nQMAMApcrrtGjAqWbn56UofEGs6DuDzKDpAkGhqaNHz970n/o8HAP8XlxquvPx0DRqfqrBIt+k4gE+i6ABB5LXvLlPF3lrTMQAAXcTutClrRJLy8tPVa1CcbDab6UiAz6DoAEGk8OV12rB0n+kYAIBuEJ0YqtxJ6cqdmKaImBDTcQDjKDpAEFmzcJcW/nmT6RgAgG5kt9vUZ0iCBuenq8+QBNntjPIgOLF0BxBEUvvHmI4AAOhmXq+lktVlKlldpsi4EOVMSFPupDRFJ4SZjgb0KEZ0gCBiWZb+8MD7aqxtMR0FANCDbDapd268cielq9+IRDkcdtORgG5H0QGCzP+eLdY2ThwKAEErLMqlnPFpystPV2xKuOk4QLeh6ABBpnjBLr33OsfpAACk9IGxystPV/9RSXK6HKbjAF2KogMEmfI9tfrz95aZjgEA8CEh4U5lj0vV4Px0JWREmo4DdAmKDhCEXvzGItVVNZmOAQDwQcmZ0Rqcn64BY5LlDmXdKvgvig4QhOb+Ya02f7jfdAwAgA9zhTg0cGyK8ialK6VftOk4wEmj6ABBaO37u7XgTxtNxwAA+ImEjEjl5adr0LgUhYS7TMcBOoWiAwShwwfr9OpjH5iOAQDwM06XXf1HJSsvP03pA+NMxwFOiKIDBKlXHlmi6vIG0zEAAH4qNiVceZPSlTMhVWFRbtNxgGNQdIAgVfjKem1Ystd0DACAn7M7beo3LFF5+enqnRsvm81mOhIgiaIDBK0tHx1Qwe/XmI4BAAggUQmhypuUppwJ6YqMCzEdB0GOogMEqaaGFv3hgfflbeElAADQtWx2m/oOjldefrr6Dk2U3c4oD3oeRQcIYm//apVK15WbjgEACGARMW7lTExT3qR0RSeGmY6DIELRAYJY8YJdeu/1TaZjAACCgU3qNShOefnpyhqRJIfTbjoRAhxFBwhi1eUNeuWRJaZjAACCTFiUS4PGpSovP11xqRGm4yBAUXSAIPf695fr0K4a0zEAAEEqbUCM8vLTNWBUspxuh+k4CCAUHSDILXt7m1b8t8R0DABAkAsJd2rg2BTl5acrqXeU6TgIABQdIMgd2FGlN3+0wnQMAABaJfeNUl5+ugaOTZE71Gk6DvwURQcIcpZl6eWHl6i2stF0FAAA2nCGODRwTLLyJqUrNSvGdBz4GYoOAC340watfX+P6RgAABxXQkaEciela9C4VIVGuEzHgR+g6ABQ6bpyvf2rVaZjAADQIYfLrqwRSRqcn66MQXGm48CHUXQAyOu19NI3F6u+qsl0FAAAOi0mOUx5k9KVMyFN4dFu03HgYyg6ACRJ77+xSavn7zIdAwCAk2Z32JQ5LFF5+enqkxsvm91mOhJ8AEUHgCRp3/bD+tsTH5mOAQDAaYmKD1XOxDTlTkxTVHyo6TgwiKIDoNUfH1uqqoP1pmMAAHDabDapz+AE5eWnK3NoguwOu+lI6GEUHQCtOHkoACAQhce4lTMhTXmT0hWTFGY6DnoIRQdAq4p9tXrtO8tMxwAAoHvYpIzsOA3OT1fWiCQ5XIzyBDKKDoA23vjBcpWV1piOAQBAtwqNcGnQuFTl5acrPj3CdBx0A4oOgDZWztupJX/bYjoGAAA9JjUrRnn56RowJlkut8N0HHQRig6ANmoqGvXKI4vFKwMAINi4w5waODZFg/PTldQnynQcnCaKDoBj/POpldq1ocJ0DAAAjEnqE6W8/HRlj02RO8xpOg5OAUUHwDG2fHRABb9fYzoGAADGOd12DRidrLz8DKX1jzEdByeBogPgGB6PVy8/vET1VU2mowAA4DPi0yOUNyldg8alKjTSZToOOkDRAdCupW9t1ccFO0zHAADA5zicdg0al6Kzrss1HQUnwOLhANqVl58u2UynAADA93havGKkwPdRdAC0KyYpTL1z403HAADAJw2enGE6AjpA0QFwXEN4EQcA4BiJvSOVkhltOgY6QNEBcFyZwxIUHuM2HQMAAJ/CaI5/oOgAOC67w668SemmYwAA4DNcoQ5ln5FiOgY6gaID4ITy8tNlY1ECAAAkSbkT0+QO5QSi/oCiA+CEouJD1XdooukYAAAYZ7PbNPzs3qZjoJMoOgA6NOIcXtQBAMgakajoxDDTMdBJFB0AHcrIjlNy3yjTMQAAMGrEOX1MR8BJoOgA6JQR5/LiDgAIXin9opWaFWM6Bk4CRQdAp/QflazoxFDTMQAAMILRHP9D0QHQKXa7TcM4ABMAEISiEkKVNTLJdAycJIoOgE7Lm5SukAiW1AQABJfhZ/eW3c65FvwNRQdAp7lCHBrC2aABAEHEHeZU7qQ00zFwCig6AE7K0LN6yeHkpQMAEBzy8tM5Qaif4t0KgJMSEROi7HEppmMAANDtnC67RrLqqN+i6AA4aaPO6ysbc5UBAAFu8JkZCo92m46BU0TRAXDSYlPClT2WUR0AQOByuuwadX5f0zFwGig6AE7J2AszWYEGABCwGM3xfxQdAKckJilcg8anmo4BAECXYzQnMFB0AJyyMRdkyu5gVAcAEFgYzQkMFB0Apyw6MUy5Ezm3AAAgcDCaEzgoOgBOy+gZmZxXBwAQMBjNCRy8OwFwWqLiQ5WXn246BgAAp43RnMBC0QFw2kbP6CuHi5cTAIB/GzK1F6M5AYR3JgBOW0RMiIacmWE6BgAApyw0wqUxMxjNCSQUHQBdYvSMvgoJd5qOAQDAKRkzM1Mh4S7TMdCFKDoAukRYpFujZ2SajgEAwEmLSQ7TkCnMTAg0FB0AXWbYWb0UkxRmOgYAACdl4qwBcjh4Wxxo+BsF0GUcTrsmXjbAdAwAADotfWCsskYmmY6BbkDRAdClskYmKSM71nQMAAA6ZpMmXcEHdIGKogOgy026YqBsNtMpAAA4sYFjUpTcN9p0DHQTig6ALpfUJ0qDJqSZjgEAwHE5XHZNmNXfdAx0I4oOgG4x/pIsuUIcpmMAANCu4Wf3VlR8qOkY6EYUHQDdIiImRKPO72M6BgAAx4iMC9FoTg4a8Cg6ALrNiHP6KCqBT8sAAL4l/6qBcodykutAR9EB0G2cboemzB5kOgYAAK36Dk1Q/5HJpmOgB1B0AHSrvkMS1H8Uv1AAAOY5XXadeXW26RjoIRQdAN1u8tUD5Q5jigAAwKwxMzMVnRhmOgZ6CEUHQLeLiAnRhEuzTMcAAASxuLQIjTiXRXKCCUUHQI8YfGaGUvpxUjYAgBlTr82Ww8Fb32DC3zaAHmGz2XTWl3Jkt9tMRwEABJmc8alKHxhnOgZ6GEUHQI9JyIjUiHN7m44BAAgiIRFOTbxigOkYMICiA6BHjZ3ZT9GJnFsHANAz8q8YqLBIt+kYMICiA6BHcW4dAEBP6Tc8UTkT0kzHgCEUHQA9rs/gBOXlp5uOAQAIYKERLk2dk2M6Bgyi6AAwYtIVA5jCBgDoNlOuHaTwaKasBTOKDgAj3KFOnXNDnmwswgYA6GIDxiRrwOhk0zFgGKcqB2BM2oBYjTyvjz4u2Gk6CoLA3JV/1tvLn9fUIZfpiklflSQ99fbXtWXvJ21uNyn3Qs0+877j7seyLP1nxUtasuG/qm+sUVbqEF09+R4lx/SSJDV7mvTawp+puGSJosLjdHX+PcrpNbr1/u+uekPlNQd0Vf7XuuFZAgiPdnMsKCRRdAAYdsZFWdqxtlyHdtWYjoIAtuPABi1e/29lxGcdc93EnJm6cOwNrZddzpAT7uvdT17XwjVv6bqzHlJCVKr+/eFLevo/39T/XfWCXE63Fq//j0oPbtL9l/5aa0uX66XCH+pH1/9VNptNZVV7tXjDf/SNy37b1U8RwKfO+lKOQiNcpmPABzB1DYBRDqdd596YJ7uTOWzoHo3N9Xqp6IeafebXFRYSdcz1bmeIosPjW7/C3BHH3ZdlWZpf/HedP+pLGpY5SRkJ/XX9WQ/pcF2ZPilZJEnaX7FTQzMnKi0+U2cOvkQ1DZWqaTgsSXrj/V/q0nG3nvAxAJy6nAmpyhyWaDoGfARFB4BxCRmRGnfRsZ+0A13hjUW/1JA+49tMHzvaii2FeujlWfrBX27WP5c9r6bmhuPu61D1XlXVlSsnY1TrtrCQSGUm56pk/zpJUkZClrbuW6OmlkatL/1Q0eEJigyN0Yeb35XL6dLwfvld+wQBSJIi40M0+aps0zHgQ5i6BsAnjDy3j0qKy7R3y2HTURBAVmwpUmnZFn1j1jPtXj9mwNmKj0pRTHiC9pRv0z+X/V4HKkt1y/nfbff2VXUVkqSosLg226PC4lqvmzBohnYf2qYf/OUmRYTG6OZzHlNdY7X+s+Il3XPRz/Wv5S/oo63zlRidri9NfUCxEUld+IyB4GSz23TODXlyh/HWFp/jXwMAn/DZL6nXv79czQ0e03EQACpqDuhvS57WXTN/Ipez/SVm8/MubP0+IyFL0eEJ+vW/H9DBw3uUFHNq53pyOJy6evI9bbb9cf5PNGXILJWWbdHqksV6+Irn9O6qN/Tm4qd1y3nfOaXHAfC5sTMzlZEd1/ENEVSYugbAZ0QnhuksTu6GLrLz4CZV11fqib/drrufO1d3P3eutuz9RAvXvKW7nztXXu+xhToz+ci/v4NVu9vdZ3T4kTdS1fUVbbZX11e0XvdFm3av1L6KEk0ZfKk271mlwX3OUIgrTKP6T9XmPatO4xkCkKReOXEaMyPTdAz4IEZ0APiUgWNTtGtThda9v8d0FPi5QRmj9MiVz7fZ9uqCJ5US21vnjrhGdrvjmPvsOrRVkhQTHt/uPhOi0hQdHq+Nuz9Wr8QBkqT6plqVHFiv/LyLjrl9c0uT/rLoV/rytEdktztkWV55vEeu83hbZFne03mKQNALi3brnBvzZLOzoA2ORdEB4HMmXzVQ+7dV6dBulpzGqQt1hys9vl+bbW5nqCJCopUe308HD+/Rii2FGtxnnCJCo7X70Db9fekzGpA2TBkJ/Vvv8/gbN+jiM76i4f3yZbPZdNbQy/TOx39SUkwvJUSl6j8rXlRMeKKGZx67yMD/Pv6j8vqMU+/EgZKkrNQheuuDZzV+0PlauPYfykod0r0/BCCA2WzSuTflKSLmxEvCI3hRdAD4HKfLofNvGaw3f7RCzY0cr4Pu4XQ4tXH3x5pf/Dc1tTQoLiJZI/pN1vmjvtTmdvsrS1Xf9HnpPmf4NWpsbtCf3/u56ptq1D91qO684EfHHAe0p3y7Vm5dqG9e8WzrthFZZ2rznk/0i7fvU0pML90w7dHufZJAABs9I1O9c9offQUkyWZZlmU6BAC0Z9PyfZr3wjrTMQAAPiZ9YKwuuW+k7ExZwwmwGAEAn5V9RqqGTMkwHQMA4EPColw67+bBlBx0iKIDwKflXzlQyZnRpmMAAHyBTZp2Q54iYjkuBx2j6ADwaQ6nXdNvHaLQCJfpKAAAw8ZdlKW+gxNMx4CfoOgA8HlR8aE692aWDwWAYDZgdLLGXJBpOgb8CEUHgF/ok5egSZcPMB0DAGBAYu9Inf3lXNMx4GcoOgD8xvBpvZU3Kc10DABADwqLcumCO4bJ5T72JL/AiVB0APiVM68dpPSBsaZjAAB6gN1h0/RbhyoqPtR0FPghig4Av+Jw2DX9tiGKTuSXHgAEuslXZ/PhFk4ZRQeA3wmLdOuCO4fJFco0BgAIVEPOzNCQMzmXGk4dRQeAX0pIj9R5Nw2WjYXYACDgpA+MVf7VA03HgJ+j6ADwW5nDEjV+Vn/TMQAAXSg2JVzTbxsih4O3qTg9/AsC4NdGnddXORNSTccAAHSBsGi3LvracIVFuk1HQQCg6ADwe1O/lKPeefGmYwAAToMrxKGL7hqu6MQw01EQICg6APyew2HX9FuHKLlvlOkoAIBTYHfYNP22IUrqw+s4ug5FB0BAcIc6deHXhis2Jdx0FADASTr7uhz1yUswHQMBhqIDIGCERbp10d3DFRHD3G4A8BfjL83SoPFppmMgAFF0AASU6IQwXXT3CLnDnKajAAA6MHRKhkZPzzQdAwGKogMg4CRkRGrmncPkcPESBwC+KmtkkiZfnW06BgIY7wIABKT0gbE67+bBstk5oygA+JqMQbE696Y8XqPRrSg6AAJW1ogkTZnNp4UA4EvSBsRo5p3D5XQ5TEdBgKPoAAhogydnKP/KgaZjAAAkpfSL1oV3DZcrhJKD7kfRARDwhk/rrUlXDDAdAwCCWlKfqCOLxYSyWAx6BkUHQFAYcU4fTbycsgMAJiT0itTF94xQCCtiogdRdAAEjZHn9tGEy/qbjgEAQSU+PUKX3DNCoREu01EQZCg6AILKqPP6asIsyg4A9ITYlHBdcu9IhUVxImf0PIoOgKAz6vy+Gn9plukYABDQopPCdOl9IxUeTcmBGUyUBBCURk/PlOWVlr29zXQUAAg4canhuvieEYqIDTEdBUGMogMgaI25IFOSpWVvbzcdBQACxpHV1YYrLJKRHJhlsyzLMh0CAExaPb9U7/9ls8SrIQCclrQBMZr51eGsrgafQNEBAEmblu9T4Uvr5fXykggAp6JPXrym3z5ULjcnA4VvoOgAwKdKistU8NwatTR7TUcBAL/Sf1SSzr1psBxO1rmC76DoAMBR9m6p1H+eWa3GuhbTUQDAL+RMTNNZX8qR3W4zHQVog6IDAF9QtqtG//rVKtVVNZmOAgA+bdjZvZR/5UDZbJQc+B6KDgC04/DBer39y5WqKmswHQUAfNIZF/XT2Jn9TMcAjouiAwDHUXu4Uf/61Sod2l1rOgoA+Ay706azr8vVoHGppqMAJ0TRAYATaKxvUcHv16h0XbnpKABgXEi4UzNuH6qM7DjTUYAOUXQAoANej1fv/2Wz1izcbToKABgTnRSmC786THGpEaajAJ1C0QGATlo9v1SL3twii3PtAAgyqVkxuuDOoQqLdJuOAnQaRQcATsKONYc09/k1amrwmI4CAD1iwOhkTbshV04XJwKFf6HoAMBJOrS7Rv95ZrWqD7EiG4DANmp6X42/JIvlo+GXKDoAcArqqpr0v9+t1r5tVaajAECXszttmjJ7kPImpZuOApwyig4AnCJPs1eFr6zX5g/3m44CAF0mMi5E028dqpR+0aajAKeFogMAp2nl3J364B9b5WWRAgB+LmNQrM7/yhCFRbHoAPwfRQcAusCezZUqeH6N6g43mY4CAKdkxDm9NeGyAbLbOR4HgYGiAwBdpPZwo+Y+v1Z7NleajgIAneYKceis63I0cEyK6ShAl6LoAEAX8notffCPrVo5d6fpKADQodiUcE2/bYgS0iNNRwG6HEUHALrBtlUHVfjyejXVt5iOAgDt6jc8UefckCd3mNN0FKBbUHQAoJtUHqjTO8+t0aFdNaajAEAru8OmcRdnaeR5fTg/DgIaRQcAulFLk0fvvbFJ6xfvNR0FABSTHKbzbh6s5L4sHY3AR9EBgB6w9eMDmv+nDWqsZSobADNyJqbpzKuz5QpxmI4C9AiKDgD0kNrKRhW+vE6l6ytMRwEQRELCnZo6J0cDRiebjgL0KIoOAPQgy7K0umiXlv5jqzzNXtNxAAS4tAExOvemwYqKDzUdBehxFB0AMODQ7hrNe2GdDu1moQIAXc9ut2nMzEyNnpHJCUARtCg6AGCIp9mrpf/cqk8KSyVeiQF0kZikMJ1zY55Ss2JMRwGMougAgGG7NpSr8OX1qqloNB0FgB+z2W0afnYvjbs4S043Cw4AFB0A8AFN9S1a+tZWrXl/N6M7AE5afHqEzr4uVyn9WDYa+AxFBwB8yJ4tlVrw6gZV7KszHQWAH7A7bBo1va/GzMiUw2k3HQfwKRQdAPAxnmavVvyvRB8X7JDXw0s0gPYl9YnS2dfnKrFXpOkogE+i6ACAjzq0u0bzX92g/durTEcB4EMcLrvOuLCfRpzbhxXVgBOg6ACAD7O8llYv2KVl/9ym5kaP6TgADMvIjtXUOTmKTQk3HQXweRQdAPAD1eUNeu/PG1VSfMh0FAAGRMaFaOLlAzRwTIrpKIDfoOgAgB8pKS7T4r9uUeV+FisAgoHdadOIc/pozIxMuUJYMho4GRQdAPAzHo9Xq4t2acV/tqupgelsQKDqOyRB+VcNVGwy09SAU0HRAQA/VVfVpA/+uVUbluwVr+RA4IhOCtPkKwcqc1ii6SiAX6PoAICfO7izWu+/sUl7tx42HQXAaXC67Ro9PVMjz+0jh4tz4gCni6IDAAFi04f7tPTvW1VT0Wg6CoCTYLNJgyakadxF/RQZF2o6DhAwKDoAEECamzxaXVSqlXN3qrGuxXQcAB3oOzRBEy7tr4QMTvoJdDWKDgAEoMb6Fq2cu0Ori3Zx/h3AByVnRmviZf2VkR1nOgoQsCg6ABDA6qub9NH/dmjNe7vlafGajgMEvfj0CI27OEtZI5JMRwECHkUHAIJAdXmDVvxnuzYs3Sevl5d9oKdFJ4XpjAv7KXtsimx2m+k4QFCg6ABAEKncX6fl/9qmzR8dkHj1B7pdTFKYRk3vq5zxqbI7WEkN6EkUHQAIQof21Ojjgh3a8uEBRniAbpCQEanR0/uq/+hk2RnBAYyg6ABAEKs6VK9V75Zq/eI9amniGB7gdKX0i9aYGZmc7BPwARQdAIDqa5q0umiXihfuUmMty1IDJ6tXTpxGz8hUr0Gsogb4CooOAKBVc6NHa9/frU8KSznxKNARm9RvWKJGT89USr9o02kAfAFFBwBwDI/Hq03L9mvVuztVvqfWdBzAp7hDHcqZkKahU3spNiXcdBwAx0HRAQCc0O5NFVqzcLe2rToor4dfGQhecWkRGjolQ4PGp8od6jQdB0AHKDoAgE6pPdyodYv2aO37e1RbybQ2BAeb3abMoQkaelYv9c6JNx0HwEmg6AAATorX49X2T8pUvHC3dm+sMB0H6BahES7l5adp8JkZik4IMx0HwCmg6AAATlnFvloVL9ytjR/sU1M9q7XBv9lsUsagOOWMT1X/0clyuhymIwE4DRQdAMBpa2n2aPsnZdq4bJ9K15ZzElL4lZjkMOWMT9Og8amKig81HQdAF6HoAAC6VF1Vkzav2K9Ny/bpwI5q03GAdrnDnBowJlk549OU1j/GdBwA3YCiAwDoNuV7a7Vx2T5tWraP8/LAOJvdpt65ccoZn6Z+IxKZmgYEOIoOAKDbWZal3ZsqtWnZPm1fXaaGmmbTkRAk7HabMgbFKmtksrJGJCk82m06EoAeQtEBAPQor9fS3i2V2rbqoLavKlN1eYPpSAgwDpddvXPj1X9kkjKHJSo0wmU6EgADKDoAAKMO7qzWtlUHtW3VQZXvqTUdB37KFeJQn8EJ6j8qSX2HJHBCTwAUHQCA76g8UKftq8q0bdVB7d9+WPyGwolEJ4aqd268+gxOUJ/B8RxzA6ANig4AwCc11DZr98YKlW6o0K715Tp8sN50JBjmCnEoY1Cc+uTFq3duvGJTwk1HAuDDKDoAAL9Qdaheu9ZXqHRDuXZtqGBBgyBgs0lJfaLUOzdevfPildo/Rg6H3XQsAH6CogMA8DuWZamstEalG8q1e2OF9m09rKYGj+lYOE12h02JvaOUlhWj1P4xyhgUq7BIVkkDcGooOgAAv2d5LZXvrdXerYe1b+th7d12WFVMdfN5oREupWZFK7V/jNL6xyi5b7Scbo6zAdA1KDoAgIBUX9Ok/durdKCkSvtLqnSgpFoNtUx3M8XhtCsuLVxJfaKUmnWk2MSlRpiOBSCAUXQAAEGjqqxeh/bUqnxPjQ7tPvJnxb46eT38KuxK4TFuJfaKVEJG5JE/e0UqLiVcdo6vAdCDKDoAgKDm8XhVub9O5XtqdWh3Teuf1YcaWN66A+ExbsUkhSkmKUzx6UdKTWKvSIVFcVwNAPMoOgAAtMPj8aqmvEFVZQ2qKqtX1aEGVX/6Z9WhBtVXNZmO2O3sdpsiE0KPlJnEMEV/Wmpiko587+J4GgA+jKIDAMApaG7yqLqsQVWH6lVX1aT66ibVVzcf+bOm+fPLNU3ytvjWr1pniEPh0W6FR7kVHuM+8n2brxCFx7gVEeNmuhkAv0XRAQCgmzXWt6i+ukkNNc1qbvCoucmjlmaPWpq8amk68mdzk0ctjUdta/FKkmySZLPJZjtywXbkP59etskmyeawyRXikCvEIXeIU65Qx+eXQx1yhTpbv3eHOeUOdZr7YQBAD6HoAAAAAAg4jEcDAAAACDgUHQAAAAABh6IDAAAAIOBQdAAAAAAEHIoOAAAAgIBD0QEAAAAQcCg6AAAAAAIORQcAAABAwKHoAAAAAAg4FB0AAAAAAYeiA6BTpk6dqnvvvfe09vHSSy8pNja2S/L4GpvNpn/84x+mY7TKzMzUU089ZToGAADGUHQABDSbzXbM1+uvv37C+5SXl2vOnDmKjo5WbGysbr75ZtXU1HR71kAugu3ZsmWLoqKiOvWcd+7cqZkzZyo8PFzJycl68MEH1dLS0v0hAQB+y2k6AAB0txdffFHTp09vvdzRG+s5c+Zo7969mjdvnpqbm3XjjTfq1ltv1WuvvdbNSYNHc3OzZs+ercmTJ2vJkiUnvK3H49HMmTOVmpqqJUuWaO/evbr++uvlcrn0wx/+sIcSAwD8DSM6ADqtpaVFd911l2JiYpSYmKjHHntMlmW1Xt/Y2KgHHnhAGRkZioiI0Lhx47RgwYIT7vO3v/2t+vfvL7fbrUGDBumPf/xj63UPPPCALrzwwtbLTz31lGw2m955553WbQMGDNDzzz9/wseIjY1Vampq61doaOhxb7t+/Xq98847ev755zVu3Djl5+fr17/+tV5//XXt2bPnhI+zd+9ezZgxQ2FhYcrKytJf//rX1usWLFggm82mysrK1m2rVq2SzWZTSUmJFixYoBtvvFGHDx9uHXn6zne+0+7jbN26VZdccolSUlIUGRmpsWPH6t133z3mdtXV1Zo9e7YiIiKUkZGhp59+us31O3fu1CWXXKLIyEhFR0frqquu0v79+yVJmzZtks1m04YNG9rc5xe/+IX69+/fennNmjWaMWOGIiMjlZKSouuuu05lZWUn/DlJ0v/93/8pJydHV111VYe3nTt3rtatW6dXX31VI0aM0IwZM/T444/r6aefVlNTU4f3BwAEJ4oOgE57+eWX5XQ6tXz5cv3yl7/Uz3/+8zYl46677tLSpUv1+uuva/Xq1bryyis1ffp0bd68ud39vfXWW7rnnnt0//33a82aNbrtttt04403av78+ZKkKVOmaNGiRfJ4PJKkhQsXKjExsbU87d69W1u3btXUqVNPmPurX/2qEhMTdcYZZ+iFF15oU86+aOnSpYqNjdWYMWNat51zzjmy2+1atmzZCR/nscce0+WXX65PPvlEc+bM0TXXXKP169ef8D6fmThxop566ilFR0dr79692rt3rx544IF2b1tTU6MLLrhAhYWFWrlypaZPn66LLrpIO3fubHO7J598UsOHD9fKlSv1zW9+U/fcc4/mzZsnSfJ6vbrkkktUXl6uhQsXat68edq2bZuuvvpqSVJ2drbGjBmjP/3pT232+ac//UnXXnutJKmyslJnn322Ro4cqRUrVuidd97R/v37OywvRUVFevPNN48pXsezdOlSDR06VCkpKa3bzj//fFVVVWnt2rWd2gcAIAhZANAJU6ZMsXJzcy2v19u67aGHHrJyc3Mty7KsHTt2WA6Hw9q9e3eb+02bNs16+OGHLcuyrBdffNGKiYlpvW7ixInWLbfc0ub2V155pXXBBRdYlmVZFRUVlt1utz788EPL6/Va8fHx1o9+9CNr3LhxlmVZ1quvvmplZGScMPf3vvc9a9GiRdbHH39s/fjHP7ZCQkKsX/7yl8e9/Q9+8AMrOzv7mO1JSUnWM888c9z7SbJuv/32NtvGjRtn3XHHHZZlWdb8+fMtSVZFRUXr9StXrrQkWdu3b7cs69ifz8kYPHiw9etf/7r1ct++fa3p06e3uc3VV19tzZgxw7Isy5o7d67lcDisnTt3tl6/du1aS5K1fPlyy7Is6xe/+IXVv3//1us3btxoSbLWr19vWZZlPf7449Z5553X5jFKS0stSdbGjRvbzVlWVmb17t3bWrhwYaef8y233HLM49TW1lqSrP/+978nvC8AIHgxogOg08aPHy+bzdZ6ecKECdq8ebM8Ho+Ki4vl8XiUnZ2tyMjI1q+FCxdq69at7e5v/fr1mjRpUpttkyZNah0FiY2N1fDhw7VgwQIVFxfL7Xbr1ltv1cqVK1VTU6OFCxdqypQpJ8z82GOPadKkSRo5cqQeeughfeMb39CTTz55mj+J9k2YMOGYy50d0TkZNTU1euCBB5Sbm6vY2FhFRkZq/fr1x4zonCjP+vXr1bt3b/Xu3bv1+ry8PMXGxrbe5pprrlFJSYk++OADSUdGc0aNGqWcnBxJ0ieffKL58+e3+fv+7Lrj/Z3fcsstuvbaa3XmmWd2wU8CAIDjYzECAF2ipqZGDodDH330kRwOR5vrIiMjT3m/U6dO1YIFCxQSEqIpU6YoPj5eubm5WrRokRYuXKj777//pPY3btw4Pf7442psbFRISMgx16empurAgQNttrW0tKi8vFypqamn/Dzs9iOfK1lHTZtrbm4+pX098MADmjdvnn76059qwIABCgsL0xVXXNHlx6ukpqbq7LPP1muvvabx48frtdde0x133NF6fU1NjS666CI98cQTx9w3LS2t3X0WFRXp7bff1k9/+lNJR34eXq9XTqdTzz33nG666aZ2cyxfvrzNts+OJTqdvxMAQGBjRAdAp33xGJUPPvhAAwcOlMPh0MiRI+XxeHTgwAENGDCgzdfx3ozm5uZq8eLFbbYtXrxYeXl5rZc/O06nsLCw9VicqVOn6s9//rM2bdrU4fE5X7Rq1SrFxcW1W3KkI6MelZWV+uijj1q3FRUVyev1aty4cSfc92cjH0dfzs3NlSQlJSVJOrJgwdFZjuZ2u1uPRzqRxYsX64YbbtCsWbM0dOhQpaamqqSk5KTy5ObmqrS0VKWlpa3Xr1u3TpWVlW1+/nPmzNEbb7yhpUuXatu2bbrmmmtarxs1apTWrl2rzMzMY/7OIyIi2s2+dOlSrVq1qvXre9/7nqKiorRq1SrNmjWr3ftMmDBBxcXFbQrovHnzFB0d3SYrAABtmJ47B8A/TJkyxYqMjLTuu+8+a8OGDdZrr71mRUREWL/73e9abzNnzhwrMzPT+tvf/mZt27bNWrZsmfXDH/7Q+ve//21Z1rHHY7z11luWy+WynnnmGWvTpk3Wz372M8vhcFjz589vvU15ebllt9sth8PRemzIW2+9ZTkcDistLe2Emd9++23r97//vVVcXGxt3rzZeuaZZ6zw8HDrW9/6Vuttli1bZg0aNMjatWtX67bp06dbI0eOtJYtW2YtWrTIGjhwoDV79uwTPpYkKzEx0frDH/5gbdy40frWt75l2e12a+3atZZlWVZTU5PVu3dv68orr7Q2bdpk/fvf/7YGDRrU5hidxYsXW5Ksd9991zp48KBVW1vb7mPNmjXLGjFihLVy5Upr1apV1kUXXWRFRUVZ99xzT+tt+vbta0VHR1tPPPGEtXHjRus3v/mN5XA4rHfeeceyLMvyer3WiBEjrMmTJ1sfffSRtWzZMmv06NHWlClT2jxWVVWVFRYWZg0fPtyaNm1am+t2795tJSUlWVdccYW1fPlya8uWLdY777xj3XDDDVZLS8sJf16fae8Ynb///e/WoEGDWi+3tLRYQ4YMsc477zxr1apV1jvvvGMlJSW1HvsFAEB7KDoAOmXKlCnWnXfead1+++1WdHS0FRcXZz3yyCNtFidoamqyvvWtb1mZmZmWy+Wy0tLSrFmzZlmrV6+2LKv9N7XPPPOMlZWVZblcLis7O9t65ZVXjnns4cOHW6mpqa2XDx06ZNlsNuuaa645Yeb//e9/1ogRI6zIyEgrIiLCGj58uPW73/3O8ng8rbf5bJGAz8rGZ/ufPXu2FRkZaUVHR1s33nijVV1dfcLHkmQ9/fTT1rnnnmuFhIRYmZmZ1htvvNHmNosWLbKGDh1qhYaGWpMnT7befPPNYx779ttvtxISEixJ1re//e12H2v79u3WWWedZYWFhVm9e/e2fvOb31hTpkw5puh897vfta688korPDzcSk1NPWYRhh07dlgXX3yxFRERYUVFRVlXXnmltW/fvmMe76qrrrIkWS+88MIx123atMmaNWuWFRsba4WFhVk5OTnWvffe2+bfxYm092/ixRdftL74OVxJSYk1Y8YMKywszEpMTLTuv/9+q7m5uVOPAQAITjbLOsE6qwAAAADghzhGBwAAAEDAoegAAAAACDgUHQAAAAABh6IDAAAAIOBQdAAAAAAEHIoOAAAAgIBD0QEAAAAQcCg6AAAAAAIORQcAAABAwKHoAAAAAAg4FB0AAAAAAYeiAwAAACDg/D/n7PxNCnzkUwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting pie-chart for average ratings\n",
    "# Ensure the 'Average rating' column is of numerical type\n",
    "df['Average rating'] = pd.to_numeric(df['Average rating'], errors='coerce')\n",
    "\n",
    "# Define conditions for categorizing the ratings\n",
    "conditions = [\n",
    "    (df['Average rating'] < 1),\n",
    "    (df['Average rating'] < 2),\n",
    "    (df['Average rating'] < 3),\n",
    "    (df['Average rating'] < 4),\n",
    "    (df['Average rating'] < 5),\n",
    "    (df['Average rating'] == 5)\n",
    "]\n",
    "\n",
    "# Define the corresponding choices for each condition\n",
    "choices = [\n",
    "    'below 1.0',\n",
    "    'below 2.0 but above 1.0',\n",
    "    'below 3.0 but above 2.0',\n",
    "    'below 4.0 but above 3.0',\n",
    "    'below 5.0 but above 4.0',\n",
    "    'Rating of 5.0'\n",
    "]\n",
    "\n",
    "# Categorize the ratings based on conditions and choices\n",
    "df['Category'] = pd.cut(\n",
    "    df['Average rating'], \n",
    "    bins=[-float('inf'), 1, 2, 3, 4, 5, float('inf')], \n",
    "    labels=choices, \n",
    "    right=False\n",
    ")\n",
    "\n",
    "# Count the number of ratings in each category\n",
    "category_counts = df['Category'].value_counts(sort=False)\n",
    "\n",
    "# Define explode to separate slices\n",
    "explode = [0.3] * len(category_counts)  # Adjust explosion for each slice\n",
    "\n",
    "# Plotting the pie chart\n",
    "plt.figure(figsize=(8, 8))\n",
    "\n",
    "plt.pie(\n",
    "    category_counts, \n",
    "    labels=category_counts.index, \n",
    "    autopct='%1.1f%%', \n",
    "    startangle=140, \n",
    "    explode=explode\n",
    ")\n",
    "\n",
    "plt.title('Distribution of Ratings')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "2441f0b0-1b73-48fd-9249-a538ebe4146b",
   "metadata": {},
   "source": [
    "As we can see, most of the books are rated 4.0 and above, a large percentage are rated even full 5.0 and a very small fraction are rated below 3 and lower, which implies that the processed dataset contains mostly decent quality books. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf526ab9-39cc-4ae8-89ae-bd90d7432f05",
   "metadata": {},
   "source": [
    "**Analyzing Release date column**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "2e25ca42-3b87-4bc8-b4d3-cadd4d13b3c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Five-number summary for Release date:\n",
      "Minimum: 1998-12-27 00:00:00\n",
      "First Quartile (Q1): 2014-09-28 06:00:00\n",
      "Median: 2018-06-14 00:00:00\n",
      "Third Quartile (Q3): 2020-04-16 06:00:00\n",
      "Maximum: 2022-12-03 00:00:00\n"
     ]
    }
   ],
   "source": [
    "# Convert 'Release date' column to datetime\n",
    "df['Release date'] = pd.to_datetime(df['Release date'])\n",
    "\n",
    "# Compute five-number summary (Standard Deviation and Variance are not compatible with date datatype)\n",
    "min_date = df['Release date'].min()\n",
    "q1_date = df['Release date'].quantile(0.25)\n",
    "median_date = df['Release date'].median()\n",
    "q3_date = df['Release date'].quantile(0.75)\n",
    "max_date = df['Release date'].max()\n",
    "\n",
    "# Print the five-number summary\n",
    "print(\"Five-number summary for Release date:\")\n",
    "print(f\"Minimum: {min_date}\")\n",
    "print(f\"First Quartile (Q1): {q1_date}\")\n",
    "print(f\"Median: {median_date}\")\n",
    "print(f\"Third Quartile (Q3): {q3_date}\")\n",
    "print(f\"Maximum: {max_date}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "87f39a97-3b0e-4e25-aa84-13f18a2cdc2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting bar-graph for number of releases in year intervals\n",
    "# Create a new column for 5-year intervals\n",
    "df['5-Year Interval'] = (df['Release date'].dt.year // 5) * 5\n",
    "\n",
    "# Group by the 5-year intervals and count the number of entries\n",
    "interval_counts = df['5-Year Interval'].value_counts().sort_index()\n",
    "\n",
    "# Plot the bar graph\n",
    "plt.figure(figsize=(10, 6))\n",
    "interval_counts.plot(kind='bar', color='yellow')\n",
    "plt.xlabel('5-Year Interval')\n",
    "plt.ylabel('Number of Releases')\n",
    "plt.title('Number of Releases in 5-Year Intervals')\n",
    "plt.xticks(rotation=45)\n",
    "plt.grid(axis='y')\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00ce9414-e185-4b54-9200-9e33989a2236",
   "metadata": {},
   "source": [
    "As we can see in the processed dataset, it had books with the highest number of releases in 2015, followed by 2020, and least releases in 1995"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88b4a942-5334-4cce-9174-4b5da954157b",
   "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": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}