Investigate_a_Dataset (2).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "# Project: The Movie Database Analysis\n",
    "\n",
    "\n",
    "## Table of Contents\n",
    "<ul>\n",
    "<li><a href=\"#intro\">Introduction</a></li>\n",
    "<li><a href=\"#wrangling\">Data Wrangling</a></li>\n",
    "<li><a href=\"#eda\">Exploratory Data Analysis</a></li>\n",
    "<li><a href=\"#conclusions\">Conclusions</a></li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='intro'></a>\n",
    "## Introduction\n",
    "\n",
    "### Dataset Description  \n",
    "<p>This is an Imdb dataset containing <b>10866</b> rows and  <b>21</b> rows displaying over 10,000 movies with the vote counts, popularity and revenue. </p>\n",
    "\n",
    "**View column names below:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "      <th>original_title</th>\n",
       "      <th>cast</th>\n",
       "      <th>homepage</th>\n",
       "      <th>director</th>\n",
       "      <th>tagline</th>\n",
       "      <th>...</th>\n",
       "      <th>overview</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>release_date</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [id, imdb_id, popularity, budget, revenue, original_title, cast, homepage, director, tagline, keywords, overview, runtime, genres, production_companies, release_date, vote_count, vote_average, release_year, budget_adj, revenue_adj]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 21 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_movies.head(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question(s) for Analysis\n",
    "1. Does the popularity of the movie affect the revenue?\n",
    "2. Which year has the highest number of movies released?\n",
    "3. Which year had the highest  total number of vote count?\n",
    "4. Relationship between vote count and the popularity?\n",
    "5. The name of the movie with the highest  and lowest revenue?\n",
    "6. The name of the movie with the highest and lowest runtime?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing packages.\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style('darkgrid')\n",
    "% matplotlib inline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting pandas==0.25.0\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/1d/9a/7eb9952f4b4d73fbd75ad1d5d6112f407e695957444cb695cbb3cdab918a/pandas-0.25.0-cp36-cp36m-manylinux1_x86_64.whl (10.5MB)\n",
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      "\u001b[?25hRequirement already satisfied, skipping upgrade: pytz>=2017.2 in /opt/conda/lib/python3.6/site-packages (from pandas==0.25.0) (2017.3)\n",
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      "\u001b[31mtensorflow 1.3.0 requires tensorflow-tensorboard<0.2.0,>=0.1.0, which is not installed.\u001b[0m\n",
      "Installing collected packages: numpy, pandas\n",
      "  Found existing installation: numpy 1.12.1\n",
      "    Uninstalling numpy-1.12.1:\n",
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      "Successfully installed numpy-1.19.5 pandas-0.25.0\n"
     ]
    }
   ],
   "source": [
    "# Upgrade pandas to use dataframe.explode() function. \n",
    "!pip install --upgrade pandas==0.25.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='wrangling'></a>\n",
    "## Data Wrangling\n",
    "\n",
    " #### General Properties\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load your data and print out a few lines. Perform operations to inspect data\n",
    "#   types and look for instances of missing or possibly errant data.\n",
    "df_movies= pd.read_csv('tmdb-movies.csv') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>id</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "      <th>original_title</th>\n",
       "      <th>cast</th>\n",
       "      <th>homepage</th>\n",
       "      <th>director</th>\n",
       "      <th>tagline</th>\n",
       "      <th>...</th>\n",
       "      <th>overview</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>production_companies</th>\n",
       "      <th>release_date</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135397</td>\n",
       "      <td>tt0369610</td>\n",
       "      <td>32.985763</td>\n",
       "      <td>150000000</td>\n",
       "      <td>1513528810</td>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>Chris Pratt|Bryce Dallas Howard|Irrfan Khan|Vi...</td>\n",
       "      <td>http://www.jurassicworld.com/</td>\n",
       "      <td>Colin Trevorrow</td>\n",
       "      <td>The park is open.</td>\n",
       "      <td>...</td>\n",
       "      <td>Twenty-two years after the events of Jurassic ...</td>\n",
       "      <td>124</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Universal Studios|Amblin Entertainment|Legenda...</td>\n",
       "      <td>6/9/15</td>\n",
       "      <td>5562</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>1.392446e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76341</td>\n",
       "      <td>tt1392190</td>\n",
       "      <td>28.419936</td>\n",
       "      <td>150000000</td>\n",
       "      <td>378436354</td>\n",
       "      <td>Mad Max: Fury Road</td>\n",
       "      <td>Tom Hardy|Charlize Theron|Hugh Keays-Byrne|Nic...</td>\n",
       "      <td>http://www.madmaxmovie.com/</td>\n",
       "      <td>George Miller</td>\n",
       "      <td>What a Lovely Day.</td>\n",
       "      <td>...</td>\n",
       "      <td>An apocalyptic story set in the furthest reach...</td>\n",
       "      <td>120</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Village Roadshow Pictures|Kennedy Miller Produ...</td>\n",
       "      <td>5/13/15</td>\n",
       "      <td>6185</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>3.481613e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>262500</td>\n",
       "      <td>tt2908446</td>\n",
       "      <td>13.112507</td>\n",
       "      <td>110000000</td>\n",
       "      <td>295238201</td>\n",
       "      <td>Insurgent</td>\n",
       "      <td>Shailene Woodley|Theo James|Kate Winslet|Ansel...</td>\n",
       "      <td>http://www.thedivergentseries.movie/#insurgent</td>\n",
       "      <td>Robert Schwentke</td>\n",
       "      <td>One Choice Can Destroy You</td>\n",
       "      <td>...</td>\n",
       "      <td>Beatrice Prior must confront her inner demons ...</td>\n",
       "      <td>119</td>\n",
       "      <td>Adventure|Science Fiction|Thriller</td>\n",
       "      <td>Summit Entertainment|Mandeville Films|Red Wago...</td>\n",
       "      <td>3/18/15</td>\n",
       "      <td>2480</td>\n",
       "      <td>6.3</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.012000e+08</td>\n",
       "      <td>2.716190e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>140607</td>\n",
       "      <td>tt2488496</td>\n",
       "      <td>11.173104</td>\n",
       "      <td>200000000</td>\n",
       "      <td>2068178225</td>\n",
       "      <td>Star Wars: The Force Awakens</td>\n",
       "      <td>Harrison Ford|Mark Hamill|Carrie Fisher|Adam D...</td>\n",
       "      <td>http://www.starwars.com/films/star-wars-episod...</td>\n",
       "      <td>J.J. Abrams</td>\n",
       "      <td>Every generation has a story.</td>\n",
       "      <td>...</td>\n",
       "      <td>Thirty years after defeating the Galactic Empi...</td>\n",
       "      <td>136</td>\n",
       "      <td>Action|Adventure|Science Fiction|Fantasy</td>\n",
       "      <td>Lucasfilm|Truenorth Productions|Bad Robot</td>\n",
       "      <td>12/15/15</td>\n",
       "      <td>5292</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.839999e+08</td>\n",
       "      <td>1.902723e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>168259</td>\n",
       "      <td>tt2820852</td>\n",
       "      <td>9.335014</td>\n",
       "      <td>190000000</td>\n",
       "      <td>1506249360</td>\n",
       "      <td>Furious 7</td>\n",
       "      <td>Vin Diesel|Paul Walker|Jason Statham|Michelle ...</td>\n",
       "      <td>http://www.furious7.com/</td>\n",
       "      <td>James Wan</td>\n",
       "      <td>Vengeance Hits Home</td>\n",
       "      <td>...</td>\n",
       "      <td>Deckard Shaw seeks revenge against Dominic Tor...</td>\n",
       "      <td>137</td>\n",
       "      <td>Action|Crime|Thriller</td>\n",
       "      <td>Universal Pictures|Original Film|Media Rights ...</td>\n",
       "      <td>4/1/15</td>\n",
       "      <td>2947</td>\n",
       "      <td>7.3</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.747999e+08</td>\n",
       "      <td>1.385749e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       id    imdb_id  popularity     budget     revenue  \\\n",
       "0  135397  tt0369610   32.985763  150000000  1513528810   \n",
       "1   76341  tt1392190   28.419936  150000000   378436354   \n",
       "2  262500  tt2908446   13.112507  110000000   295238201   \n",
       "3  140607  tt2488496   11.173104  200000000  2068178225   \n",
       "4  168259  tt2820852    9.335014  190000000  1506249360   \n",
       "\n",
       "                 original_title  \\\n",
       "0                Jurassic World   \n",
       "1            Mad Max: Fury Road   \n",
       "2                     Insurgent   \n",
       "3  Star Wars: The Force Awakens   \n",
       "4                     Furious 7   \n",
       "\n",
       "                                                cast  \\\n",
       "0  Chris Pratt|Bryce Dallas Howard|Irrfan Khan|Vi...   \n",
       "1  Tom Hardy|Charlize Theron|Hugh Keays-Byrne|Nic...   \n",
       "2  Shailene Woodley|Theo James|Kate Winslet|Ansel...   \n",
       "3  Harrison Ford|Mark Hamill|Carrie Fisher|Adam D...   \n",
       "4  Vin Diesel|Paul Walker|Jason Statham|Michelle ...   \n",
       "\n",
       "                                            homepage          director  \\\n",
       "0                      http://www.jurassicworld.com/   Colin Trevorrow   \n",
       "1                        http://www.madmaxmovie.com/     George Miller   \n",
       "2     http://www.thedivergentseries.movie/#insurgent  Robert Schwentke   \n",
       "3  http://www.starwars.com/films/star-wars-episod...       J.J. Abrams   \n",
       "4                           http://www.furious7.com/         James Wan   \n",
       "\n",
       "                         tagline      ...       \\\n",
       "0              The park is open.      ...        \n",
       "1             What a Lovely Day.      ...        \n",
       "2     One Choice Can Destroy You      ...        \n",
       "3  Every generation has a story.      ...        \n",
       "4            Vengeance Hits Home      ...        \n",
       "\n",
       "                                            overview runtime  \\\n",
       "0  Twenty-two years after the events of Jurassic ...     124   \n",
       "1  An apocalyptic story set in the furthest reach...     120   \n",
       "2  Beatrice Prior must confront her inner demons ...     119   \n",
       "3  Thirty years after defeating the Galactic Empi...     136   \n",
       "4  Deckard Shaw seeks revenge against Dominic Tor...     137   \n",
       "\n",
       "                                      genres  \\\n",
       "0  Action|Adventure|Science Fiction|Thriller   \n",
       "1  Action|Adventure|Science Fiction|Thriller   \n",
       "2         Adventure|Science Fiction|Thriller   \n",
       "3   Action|Adventure|Science Fiction|Fantasy   \n",
       "4                      Action|Crime|Thriller   \n",
       "\n",
       "                                production_companies release_date vote_count  \\\n",
       "0  Universal Studios|Amblin Entertainment|Legenda...       6/9/15       5562   \n",
       "1  Village Roadshow Pictures|Kennedy Miller Produ...      5/13/15       6185   \n",
       "2  Summit Entertainment|Mandeville Films|Red Wago...      3/18/15       2480   \n",
       "3          Lucasfilm|Truenorth Productions|Bad Robot     12/15/15       5292   \n",
       "4  Universal Pictures|Original Film|Media Rights ...       4/1/15       2947   \n",
       "\n",
       "   vote_average  release_year    budget_adj   revenue_adj  \n",
       "0           6.5          2015  1.379999e+08  1.392446e+09  \n",
       "1           7.1          2015  1.379999e+08  3.481613e+08  \n",
       "2           6.3          2015  1.012000e+08  2.716190e+08  \n",
       "3           7.5          2015  1.839999e+08  1.902723e+09  \n",
       "4           7.3          2015  1.747999e+08  1.385749e+09  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_movies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10866 entries, 0 to 10865\n",
      "Data columns (total 21 columns):\n",
      "id                      10866 non-null int64\n",
      "imdb_id                 10856 non-null object\n",
      "popularity              10866 non-null float64\n",
      "budget                  10866 non-null int64\n",
      "revenue                 10866 non-null int64\n",
      "original_title          10866 non-null object\n",
      "cast                    10790 non-null object\n",
      "homepage                2936 non-null object\n",
      "director                10822 non-null object\n",
      "tagline                 8042 non-null object\n",
      "keywords                9373 non-null object\n",
      "overview                10862 non-null object\n",
      "runtime                 10866 non-null int64\n",
      "genres                  10843 non-null object\n",
      "production_companies    9836 non-null object\n",
      "release_date            10866 non-null object\n",
      "vote_count              10866 non-null int64\n",
      "vote_average            10866 non-null float64\n",
      "release_year            10866 non-null int64\n",
      "budget_adj              10866 non-null float64\n",
      "revenue_adj             10866 non-null float64\n",
      "dtypes: float64(4), int64(6), object(11)\n",
      "memory usage: 1.7+ MB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "id                         0\n",
       "imdb_id                   10\n",
       "popularity                 0\n",
       "budget                     0\n",
       "revenue                    0\n",
       "original_title             0\n",
       "cast                      76\n",
       "homepage                7930\n",
       "director                  44\n",
       "tagline                 2824\n",
       "keywords                1493\n",
       "overview                   4\n",
       "runtime                    0\n",
       "genres                    23\n",
       "production_companies    1030\n",
       "release_date               0\n",
       "vote_count                 0\n",
       "vote_average               0\n",
       "release_year               0\n",
       "budget_adj                 0\n",
       "revenue_adj                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Check if there are missing values in each column.\n",
    "df_movies.info()\n",
    "df_movies.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10866, 21)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#To know how many rows and columns are there in the dataset.\n",
    "df_movies.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Data Cleaning\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Dropping some column in the dataset using the .drop() function.**\n",
    ">**Note:** Missing value found in some columns. Instead of ignoring it, i'll rather fill in with the mean value. \n",
    "I also noticed that all data type seems okay except the **_release_date_** column. So, i'll change to an ISO standard using the **to.datetime() method.** "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_movies.drop(['cast', 'director','homepage', 'production_companies', 'tagline', 'overview', 'keywords'], axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "      <th>original_title</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>release_date</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135397</td>\n",
       "      <td>tt0369610</td>\n",
       "      <td>32.985763</td>\n",
       "      <td>150000000</td>\n",
       "      <td>1513528810</td>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>124</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>6/9/15</td>\n",
       "      <td>5562</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>1.392446e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76341</td>\n",
       "      <td>tt1392190</td>\n",
       "      <td>28.419936</td>\n",
       "      <td>150000000</td>\n",
       "      <td>378436354</td>\n",
       "      <td>Mad Max: Fury Road</td>\n",
       "      <td>120</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>5/13/15</td>\n",
       "      <td>6185</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>3.481613e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>262500</td>\n",
       "      <td>tt2908446</td>\n",
       "      <td>13.112507</td>\n",
       "      <td>110000000</td>\n",
       "      <td>295238201</td>\n",
       "      <td>Insurgent</td>\n",
       "      <td>119</td>\n",
       "      <td>Adventure|Science Fiction|Thriller</td>\n",
       "      <td>3/18/15</td>\n",
       "      <td>2480</td>\n",
       "      <td>6.3</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.012000e+08</td>\n",
       "      <td>2.716190e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>140607</td>\n",
       "      <td>tt2488496</td>\n",
       "      <td>11.173104</td>\n",
       "      <td>200000000</td>\n",
       "      <td>2068178225</td>\n",
       "      <td>Star Wars: The Force Awakens</td>\n",
       "      <td>136</td>\n",
       "      <td>Action|Adventure|Science Fiction|Fantasy</td>\n",
       "      <td>12/15/15</td>\n",
       "      <td>5292</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.839999e+08</td>\n",
       "      <td>1.902723e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id    imdb_id  popularity     budget     revenue  \\\n",
       "0  135397  tt0369610   32.985763  150000000  1513528810   \n",
       "1   76341  tt1392190   28.419936  150000000   378436354   \n",
       "2  262500  tt2908446   13.112507  110000000   295238201   \n",
       "3  140607  tt2488496   11.173104  200000000  2068178225   \n",
       "\n",
       "                 original_title  runtime  \\\n",
       "0                Jurassic World      124   \n",
       "1            Mad Max: Fury Road      120   \n",
       "2                     Insurgent      119   \n",
       "3  Star Wars: The Force Awakens      136   \n",
       "\n",
       "                                      genres release_date  vote_count  \\\n",
       "0  Action|Adventure|Science Fiction|Thriller       6/9/15        5562   \n",
       "1  Action|Adventure|Science Fiction|Thriller      5/13/15        6185   \n",
       "2         Adventure|Science Fiction|Thriller      3/18/15        2480   \n",
       "3   Action|Adventure|Science Fiction|Fantasy     12/15/15        5292   \n",
       "\n",
       "   vote_average  release_year    budget_adj   revenue_adj  \n",
       "0           6.5          2015  1.379999e+08  1.392446e+09  \n",
       "1           7.1          2015  1.379999e+08  3.481613e+08  \n",
       "2           6.3          2015  1.012000e+08  2.716190e+08  \n",
       "3           7.5          2015  1.839999e+08  1.902723e+09  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#To check\n",
    "df_movies.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#To count duplicates\n",
    "sum(df_movies.duplicated())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Drop duplicates and check \n",
    "df_movies.drop_duplicates(inplace = True)\n",
    "sum(df_movies.duplicated())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#replacing null values with their respective mean using the fillna()\n",
    "df_movies = df_movies.fillna(df_movies.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>imdb_id</th>\n",
       "      <th>popularity</th>\n",
       "      <th>budget</th>\n",
       "      <th>revenue</th>\n",
       "      <th>original_title</th>\n",
       "      <th>runtime</th>\n",
       "      <th>genres</th>\n",
       "      <th>release_date</th>\n",
       "      <th>vote_count</th>\n",
       "      <th>vote_average</th>\n",
       "      <th>release_year</th>\n",
       "      <th>budget_adj</th>\n",
       "      <th>revenue_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135397</td>\n",
       "      <td>tt0369610</td>\n",
       "      <td>32.985763</td>\n",
       "      <td>150000000</td>\n",
       "      <td>1513528810</td>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>124</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>2015-06-09</td>\n",
       "      <td>5562</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>1.392446e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76341</td>\n",
       "      <td>tt1392190</td>\n",
       "      <td>28.419936</td>\n",
       "      <td>150000000</td>\n",
       "      <td>378436354</td>\n",
       "      <td>Mad Max: Fury Road</td>\n",
       "      <td>120</td>\n",
       "      <td>Action|Adventure|Science Fiction|Thriller</td>\n",
       "      <td>2015-05-13</td>\n",
       "      <td>6185</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.379999e+08</td>\n",
       "      <td>3.481613e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>262500</td>\n",
       "      <td>tt2908446</td>\n",
       "      <td>13.112507</td>\n",
       "      <td>110000000</td>\n",
       "      <td>295238201</td>\n",
       "      <td>Insurgent</td>\n",
       "      <td>119</td>\n",
       "      <td>Adventure|Science Fiction|Thriller</td>\n",
       "      <td>2015-03-18</td>\n",
       "      <td>2480</td>\n",
       "      <td>6.3</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.012000e+08</td>\n",
       "      <td>2.716190e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>140607</td>\n",
       "      <td>tt2488496</td>\n",
       "      <td>11.173104</td>\n",
       "      <td>200000000</td>\n",
       "      <td>2068178225</td>\n",
       "      <td>Star Wars: The Force Awakens</td>\n",
       "      <td>136</td>\n",
       "      <td>Action|Adventure|Science Fiction|Fantasy</td>\n",
       "      <td>2015-12-15</td>\n",
       "      <td>5292</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.839999e+08</td>\n",
       "      <td>1.902723e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id    imdb_id  popularity     budget     revenue  \\\n",
       "0  135397  tt0369610   32.985763  150000000  1513528810   \n",
       "1   76341  tt1392190   28.419936  150000000   378436354   \n",
       "2  262500  tt2908446   13.112507  110000000   295238201   \n",
       "3  140607  tt2488496   11.173104  200000000  2068178225   \n",
       "\n",
       "                 original_title  runtime  \\\n",
       "0                Jurassic World      124   \n",
       "1            Mad Max: Fury Road      120   \n",
       "2                     Insurgent      119   \n",
       "3  Star Wars: The Force Awakens      136   \n",
       "\n",
       "                                      genres release_date  vote_count  \\\n",
       "0  Action|Adventure|Science Fiction|Thriller   2015-06-09        5562   \n",
       "1  Action|Adventure|Science Fiction|Thriller   2015-05-13        6185   \n",
       "2         Adventure|Science Fiction|Thriller   2015-03-18        2480   \n",
       "3   Action|Adventure|Science Fiction|Fantasy   2015-12-15        5292   \n",
       "\n",
       "   vote_average  release_year    budget_adj   revenue_adj  \n",
       "0           6.5          2015  1.379999e+08  1.392446e+09  \n",
       "1           7.1          2015  1.379999e+08  3.481613e+08  \n",
       "2           6.3          2015  1.012000e+08  2.716190e+08  \n",
       "3           7.5          2015  1.839999e+08  1.902723e+09  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Changing release_date dtype\n",
    "\n",
    "df_movies['release_date'] = pd.to_datetime(df_movies['release_date'])\n",
    "\n",
    "df_movies.head(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='eda'></a>\n",
    "## Exploratory Data Analysis\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "### Research Question 1 (Does the popularity of the movie affect the revenue?)\n",
    "<p>The higher the popularity, the higher the revenue?<p/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f38b14328d0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f38b1407f28>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f38b15065f8>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f38b13d1c88>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f38b15d1208>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f38b15d1240>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f38b15b3978>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f38b1563f98>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f38b14e6588>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f38b1506f28>,\n",
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       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f38b138d198>]], dtype=object)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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igJIILgUOAg4ElkbELi1sv6QpZGInSZJUT4uBwTtuy4FjG8pXZOZAZt4C9EXEfOAIYHVmbsjMjcBq4MhWN1rS1HAqpiRJUucbAL4VEQPAP2XmJcDumbkeIDPXR8TzS90FwLqGfftL2Ujl25kzZxa9vT1T0IUd6+ub3Zbz9vTMbNu5m6lb+gHd05dW9sPETpIkqfO9NjMfLMnb6oj4ySh1ZwxTNjBK+XY2b946wSZO3qZNW9py3r6+2W07dzN1Sz+ge/rS7H7Mmzd3xG1OxZQkSepwmflg+f0w8DWqZ+QeKlMsKb8fLtX7gT0adl8IPDhKuaQuYGInSZLUwSLi9yJi7uBn4HDgx8AqYEmptgS4pnxeBbwjImZExMHAY2XK5vXA4RGxS1k05fBSJqkLOBVTkiSps+0OfC0ioLp2uzwzr4uINcBVEXEy8ABwXKl/LdWrDu6let3BSQCZuSEiPgqsKfXOycwNreuGpKlkYidJktTBMvM+YL9hyh8FDhumfAA4ZYRjLQOWNbuNktrPxE7StBIRfcDngX2pFg14J5D4kl9JklRjPmMnabq5CLguM3+fagT8HnzJryRJqjkTO0nTRkQ8B3gdcClAZj6RmZvwJb+SJKnmnIopaTp5CfAI8IWI2A+4HfgAXfiSX2jPi3674YWy3dAHsB+SNN1MKrHzWRVJNdMLvAp4X2beGhEX8fS0y+HU9iW/0J4X/XbDC2W7oQ9gP8ZitBf9SlLdTHYqps+qSKqTfqA/M28t36+mSvR8ya8kSaq1CSd2PqsiqW4y85fAuigvg6JaJvxufMmvJEmquclMxfRZlSnULc8U2I/O0i39mKT3AV+KiGcB91G9uHcmvuRXkiTV2GQSO59VmUI+G9FZ7MeO1eVZlcy8E3j1MJt8ya8kSaqtyTxj57MqkiRJktQBJpzY+ayKJEmSJHWGyb7HzmdVJEmSJKnNJpXY+ayKJEmSJLXfZO/YSZIkqQUiogf4AfCLzDwmIvYCVgK7AncAb8/MJyJiFrACOAB4FHhTZq4txzgTOBl4Enh/Zvr4i9QlJvuCckmSJLXGB4B7Gr5fAFyYmYuAjVQJG+X3xsx8GXBhqUdE7A2cAOxD9c7gz5ZkUVIXMLGTJEnqcBGxEPgT4PPl+wzgUKpVyQGWA8eWz4vLd8r2w0r9xcDKzNyamfdTrXtwYGt6IGmqORVTkiSp830S+DAw+NLQ3YBNmbmtfO8HFpTPC4B1AJm5LSIeK/UXALc0HLNxn6fMmTOL3t723Mjr65vdlvP29Mxs27mbqVv6Ad3Tl1b2w8ROkiSpg0XEMcDDmXl7RBxSimcMU3VgB9tG2+cpmzdvnUgzm2LTpi1tOW9f3+y2nbuZuqUf0D19aXY/5s2bO+I2p2JKkiR1ttcCfxYRa6kWSzmU6g5eX0QMDtIvBB4sn/uBPQDK9ucCGxrLh9lHUs2Z2EmSJHWwzDwzMxdm5p5Ui598JzPfCnwXeGOptgS4pnxeVb5Ttn+nvHZqFXBCRMwqK2ouAm5rUTckTTETO0mSpHo6HTg1Iu6leobu0lJ+KbBbKT8VOAMgM+8CrgLuBq4DTsnMJ1veaklTwmfsJEmSaiIzbwRuLJ/vY5hVLTPzN8BxI+x/HnDe1LVQUrt4x06SJEmSas7ETpIkSZJqzsROkiRJkmrOxE6SJEmSas7ETpIkSZJqzsROkiRJkmrOxE6SJEmSas7ETpIkSZJqzsROkiRJkmrOxE6SJEmSas7ETpIkSZJqzsROkiRJkmqut90NkKRWi4ge4AfALzLzmIjYC1gJ7ArcAbw9M5+IiFnACuAA4FHgTZm5thzjTOBk4Eng/Zl5fet7IkmSVDGxkzQdfQC4B3hO+X4BcGFmroyIz1ElbBeX3xsz82URcUKp96aI2Bs4AdgHeCHw7Yh4eWY+2eqOSOp+EfFs4CZgFtW129WZudRBKUmNJj0VMyJ6IuLfIuLr5fteEXFrRPw0Iq6MiGeV8lnl+71l+54NxzizlGdEHDHZNknSSCJiIfAnwOfL9xnAocDVpcpy4NjyeXH5Ttl+WKm/GFiZmVsz837gXuDA1vRA0jS0FTg0M/cD9geOjIiDeXpQahGwkSphg4ZBKeDCUo8hg1JHAp8tMxgkdYFm3LFz5FtSnXwS+DAwt3zfDdiUmdvK935gQfm8AFgHkJnbIuKxUn8BcEvDMRv3ecqcObPo7W3fNVNf3+yWn7OnZ2ZbzttM3dAHsB/dJDMHgM3l607lZ4BqUOotpXw5cDbVNdfi8hmqQalPDx2UAu6PiMFBqZunvheSptqkEruGke/zgFMbRr4NMpI6TkQcAzycmbdHxCGleMYwVQd2sG20fZ6yefPWiTSzaTZt2tLyc/b1zW7LeZupG/oA9mMs5s2bu+NKHaLcWbsdeBnwGeBnTNGglKR6muwdu5aNfEtSE7wW+LOIOBp4NtVMg08CfRHRW2LXQuDBUr8f2APoj4he4LnAhobyQY37SFLTlZlM+0dEH/A14BXDVGvKoFQ7Zxu06+5st9wZ7pZ+QPf0pZX9mHBi1+qR7+k2pcm/zJ3FfnSHzDwTOBOgxK2/zsy3RsSXgTdSLUKwBLim7LKqfL+5bP9OZg5ExCrg8oj4BNUU8kXAba3si6TpKTM3RcSNwMFM0aBUO2cbtOsus3e4O0+39KXZ/RhtpsFk7ti1dOR7uk1p8i9zZ7EfO1anKU3DOB1YGRHnAv8GXFrKLwW+WKaIb6B6HpjMvCsirgLuBrYBp/hcsKSpEhHzgN+WpG5n4PVUaxV8FwelJBUTTuwc+ZZUZ5l5I3Bj+Xwfw6xqmZm/AY4bYf/zqJ4vlqSpNh9YXp6zmwlclZlfj4i7cVBKUjEV77Fz5FuSJKlJMvOHwCuHKXdQStJTmpLYOfItSZIkSe0z6ReUS5IkSZLay8ROkiRJkmrOxE6SJEmSas7ETpIkSZJqzsROkiRJkmrOxE6SJEmSas7ETpIkSZJqzsROkiRJkmrOxE6SJEmSas7ETpIkSZJqzsROkiRJkmrOxE6SJEmSaq633Q2QJEnSyCJiD2AF8ALgd8AlmXlRROwKXAnsCawFjs/MjRExA7gIOBrYApyYmXeUYy0BziqHPjczl7eyL5KmjnfsJEmSOts24LTMfAVwMHBKROwNnAHckJmLgBvKd4CjgEXl593AxQAlEVwKHAQcCCyNiF1a2RFJU8fETpIkqYNl5vrBO26Z+ThwD7AAWAwM3nFbDhxbPi8GVmTmQGbeAvRFxHzgCGB1Zm7IzI3AauDIFnZF0hQysZMkSaqJiNgTeCVwK7B7Zq6HKvkDnl+qLQDWNezWX8pGKpfUBXzGTpIkqQYiYg7wFeCDmfmriBip6oxhygZGKd/OnDmz6O3tmXA7J6Ovb3ZbztvTM7Nt526mbukHdE9fWtkPEztJkqQOFxE7USV1X8rMr5bihyJifmauL1MtHy7l/cAeDbsvBB4s5YcMKb9x6Lk2b97a3MaPw6ZNW9py3r6+2W07dzN1Sz+ge/rS7H7Mmzd3xG1OxZQkSepgZZXLS4F7MvMTDZtWAUvK5yXANQ3l74iIGRFxMPBYmap5PXB4ROxSFk05vJRJ6gLesZMkSepsrwXeDvwoIu4sZR8BzgeuioiTgQeA48q2a6ledXAv1esOTgLIzA0R8VFgTal3TmZuaE0XJE01EztJkqQOlpnfZ/jn4wAOG6b+AHDKCMdaBixrXuskdQqnYkqSJElSzZnYSZIkSVLNORVT0rQREXsAK4AXAL8DLsnMiyJiV+BKYE9gLXB8Zm4sCxZcRPWsyhbgxMGXBEfEEuCscuhzM3M5kiRJbTLhxM4LJEk1tA04LTPviIi5wO0RsRo4EbghM8+PiDOAM4DTgaOAReXnIOBi4KAS55YCr6Z6B9TtEbEqMze2vEeSJElMbirm4AXSK4CDgVMiYm+qC6IbMnMRcEP5DttfIL2b6gKJhgukg4ADgaVlCV5JaqrMXD84oJSZjwP3AAuAxcDggNJy4NjyeTGwIjMHMvMWoK+8K+oIYHVmbijJ3GrgyBZ2RZIkaTsTvmNX3oeyvnx+PCIaL5AOKdWWU7348nQaLpCAWyJi8ALpEMoFEkAZPT8SuGKibZOkHYmIPYFXArcCu5eYRnnR7/NLtQXAuobd+kvZSOXbmTNnFr29Pc1v/Bj19c1u+Tl7ema25bzN1A19APshSdNNU56xa8UFkiQ1S0TMAb4CfDAzfxURI1UdbnnxgVHKt7N589YJt7EZNm3a0vJz9vXNbst5m6kb+gD2YyzmzZs7JceVpHaYdGLXqguk6Tby3S0jlPajs3RLPyYjInaiillfysyvluKHImJ+GYyaDzxcyvuBPRp2Xwg8WMoPGVJ+41S2W5IkaTSTSuxaeYE03Ua+HWntLPZjx+ow8l0WcboUuCczP9GwaRWwBDi//L6mofy9EbGS6jngx0psux74WMPzwIcDZ7aiD5IkScOZzKqYXiBJqpvXAm8HfhQRd5ayj1DFq6si4mTgAeC4su1aqpV876VazfckgMzcEBEfBdaUeucMPicsSZLUDpO5Y+cFkqRayczvM/z0b4DDhqk/AJwywrGWAcua1zpJkqSJm8yqmF4gSZIkSVIHaMqqmJIkSdJkvebjNzX9mGtOe13Tjyl1IhM7SZKkDhYRy4BjgIczc99StitwJbAnsBY4PjM3ljUQLqJ6/GULcGJm3lH2WQKcVQ57bmYub2U/JE2tme1ugCRJkkZ1GXDkkLIzgBsycxFwQ/kOcBSwqPy8G7gYnkoEl1ItYHcgsLRh4TpJXcDETpIkqYNl5k3A0IXlFgODd9yWA8c2lK/IzIHMvAXoK6+fOgJYnZkbMnMjsJpnJouSaszETpIkqX52z8z1AOX380v5AmBdQ73+UjZSuaQu4TN2kiRJ3WO4FcsHRil/hjlzZtHb29PURrVTX9/sHdbp6Zk5pnqdrlv6Ad3Tl1b2w8ROkiSpfh6KiPmZub5MtXy4lPcDezTUWwg8WMoPGVJ+43AH3rx5a9Mb206bNm3ZYZ2+vtljqtfpuqUf0D19aXY/5s2bO+I2p2JKkiTVzypgSfm8BLimofwdETEjIg4GHitTNa8HDo+IXcqiKYeXMkldwjt2kiRJHSwirqC62/a8iOinWt3yfOCqiDgZeAA4rlS/lupVB/dSve7gJIDM3BARHwXWlHrnZObQBVkk1ZiJnSRJUgfLzDePsOmwYeoOAKeMcJxlwLImNk1SB3EqpiRJkiTVnImdJEmSJNWcUzElqUu95uM3Nf2Ya057XdOPKUmSJs87dpIkSZJUcyZ2kiRJklRzTsUcI6c0SZIkSepUJnaSJEnqWlMxOA8O0KvzmNhJkiRJGjNnsnUmn7GTJEmSpJrzjp0kSZI0TnW5azVVU1HVeUzsJEmSpA4wnZOwuiTKnczETpI0Zv6PV5KkzuQzdpIkSZJUcyZ2kiRJklRzHTMVMyKOBC4CeoDPZ+b5bW7SlHNKk1Rv0zFuSao345amk+l2rd0RiV1E9ACfAd4A9ANrImJVZt7d3pbVz3T7Cyy1i3GreYxbUmsYt6Tu1hGJHXAgcG9m3gcQESuBxYCBpgN40SUNy7jVwaZqZTljl2rOuCV1sU5J7BYA6xq+9wMHNVaYN2/ujLEebO35f9KkZklPmzdvbrub0BTd0o8OYNxSx+uWf+/d0o8OsMO4BWOPXcYtaWxaFcM6ZfGU4QLIQMtbIUljZ9ySVDfGLamLdUpi1w/s0fB9IfBgm9oiSWNh3JJUN8YtqYt1ylTMNcCiiNgL+AVwAvCW9jZJkkZl3JJUN8YtqYvNGBjojDvwEXE08Emq5XeXZeZ5EzhG7ZfwjYhlwDHAw5m5b7vbM1ERsQewAngB8Dvgksy8qL2tGp+IeDZwEzCLahDk6sxc2t5WTVxZDe0HwC8y85h2t6cbGLee1g2xqxviFnRX7DJuNV8z4lY5TkfEruFiT0TsClwJ7AmsBY7PzI0RMaO0+WhgC3BiZt5R9lkCnFUOe25mLi/lBwCXATsD1wIfyMyBkc4xiX4MG39q2pdhY1AZUFgJ7ArcAbw9M5+IiFml7wcAjwJvysy15VhnAicDTwLvz8zrS/mwf/9GOsdE+1KOuV0c6uR+dMpUTDKBWOfdAAAgAElEQVTz2sx8eWa+dIIXR4NL+B4F7A28OSL2bnY7W+Ay4Mh2N6IJtgGnZeYrgIOBU2r432MrcGhm7gfsDxwZEQe3uU2T8QHgnnY3opsYt7ZzGfWPXd0Qt6C7Ypdxq8kmG7eg42LXZTwz9pwB3JCZi4Abyneo2ruo/LwbuBieSgSXUi0kcyCwNCJ2KftcXOoO7nfkDs4xUSPFnzr2ZaQYdAFwYTnPRqpEh/J7Y2a+DLiw1KP0/wRgn9LWz0ZEzw7+/o10jskYGoc6th8dk9g1wVNL+JaMdnAJ31rJzJuADe1ux2Rl5vrBkaPMfJzqH8SC9rZqfDJzIDM3l687lZ/OuMU9ThGxEPgT4PPtbou20xVxC7ojdnVD3ILuiV3GrY7WMbFrhNizGFhePi8Hjm0oX1H+jdwC9EXEfOAIYHVmbih3qlZTJSPzgedk5s2ZOUB1N+bYHZxjov0YKf7UsS8jxaBDgatH6Mvg+a8GDit3JBcDKzNza2beD9xL9Xdv2L9/ZZ+RzjEhQ+PQDs7R9n50U2I33BK+tfsfcjeKiD2BVwK3trkp41ZGVO4EHqYKlLXrQ/FJ4MNU0zvUOYxbHarOcQu6JnYZtzpXp8eu3TNzPVQJE/D8Uj5Su0cr7x+mfLRzTNqQ+FPLvgyNQcDPgE2ZuW2Y8z/V5rL9MWC3CfRxt1HOMVFD49Bo52h7P7opsXMJ3w4UEXOArwAfzMxftbs945WZT2bm/lQrhx0YEbV7digiBp89uL3dbdEzGLc6UN3jFtQ/dhm3Ol5dY9dI7R5v+ZQZR/zp6L4MjUHAK0Y5f7P60tQ+jhCHRjtH2/vRTYmdS/h2mIjYiSo4fSkzv9ru9kxGZm4CbqSezxC9FviziFhLdZv/0Ij4l7a2SIOMWx2mm+IW1Dp2Gbc6W6fHrofK1EPK74dL+UjtHq184TDlo51jwkaIP7Xsy6CGGHQw1XTRwRX5G8//VJvL9udSTa8dbx//Y5RzTMQz4hDVHbyO7Uc3JXZPLeEbEc+iekhxVZvbNG2V+cGXAvdk5ifa3Z6JiIh5EdFXPu8MvB74SXtbNX6ZeWZmLszMPan+XXwnM9/W5mapYtzqIN0Qt6A7Ypdxq+N1euxaBSwpn5cA1zSUvyMiZpTFPB4rUw+vBw6PiF3KQiOHA9eXbY9HxMElPrxjyLGGO8eEjBJ/6tiX4WLQPcB3gTeO0JfB87+R6t/7QCk/ISJmlVUiFwG3McLfv7LPSOcYtxHi0Fs7uR9dk9iVeajvpfoLfQ9wVWbe1d5WjV9EXAHcXH2M/ohoxmo+7fBa4O1Uo6x3lp+j292ocZoPfDcifkj1j291Zn69zW1SF+mWuAVdE7u6IW6BsUtTrJNi1wix53zgDRHxU+AN5TtUS/zfR7V4xT8D/x0gMzcAH6X697IGOKeUAbyHauGMe6meE/tmKR/pHBM1UvypY19GikGnA6dGxL1Uz5FdWupfCuxWyk+lrMpZ/k5dBdwNXAecUqZ4jvb3b6RzNFPH9qNj3mMnSZIkSZqYrrljJ0mSJEnTlYmdJEmSJNWciZ0kSZIk1ZyJnSRJkiTVXO+Oq0jqZhGxDBh8CeeoLzGOiBcBy4E+oAc4IzOvnfpWStLTjFuS9EzesZN0GWN/efFZVMvxvpLqfSufnapGSdIoLsO4JUnb8Y6dNM1l5k0RsWdjWUS8FPgMMA/YAvxFZv4EGACeU6o9F3iwhU2VJMC4JUnD8Y6dpOFcArwvMw8A/pqnR7jPBt4WEf1UL0d9X3uaJ0nPYNySNK2Z2EnaTkTMAf4A+HJE3An8EzC/bH4zcFlmLgSOBr4YEcYRSW1l3JIkp2JKeqaZwKbM3H+YbSdTnmvJzJsj4tnA84CHW9g+SRrKuCVp2nPEStJ2MvNXwP0RcRxARMyIiP3K5geAw0r5K4BnA4+0paGSVBi3JAlmDAwMtLsNktooIq4ADqEawX4IWAp8B7iYairTTsDKzDwnIvYG/hmYQ7UgwYcz81vtaLek6cu4JUnPZGInSZIkSTXnVExJkiRJqjkTO0mSJEmqORM7SZIkSao5EztJkiRJqjkTO0mSJEmqORM7SZIkSao5EztJkiRJqjkTO0mSJEmqORM7SZIkSao5Ezu1RUTcGBHvmsT+d0XEIU1skqSaioizI+Jf2t0OSZLaqbfdDZAmIjP3GfwcEWcDL8vMt7WvRZIkSVL7eMdOtRIRDkZI04z/7kfnn4/UPfz3rMnwL4+IiLXAPwFvB+YD/wq8JzN/ExF/AZwO7Ap8H/irzHyw7DcAfAD4IPAc4AvA6Zn5u6F30SJiT+B+YKfM3Dbk/C8F/hnYDxgArgdOycxNDe27GHhr9TV+D7gXeBfV3+GPADMi4ljgZ8C5wBmZeUDDOU4D/igzj23Gn5mkqTXMv/tFwIXA64DNwIWZ+akR9j0Y+ASwN/Bz4AOZeWPZdhLwYWAh8AhwQWb+U9n2POAy4A+B3wF3AX9cYtoLgX8cy/nLsV4A3AfskZmPlrIDgOuAF2bmbyPincCHgBcAtwHvzsyfl7oXAX8OPBf4KfDBzPxe2XY2sC/wG+DPgFOBz+/4T1VSJxprvCtx6GfAgszcUPZ9JbAamD+GuDIAvAc4DXgecDnw3swc2NF1W0Q8lyquHk0VH78ALM3MJ6fyz0bj4x07DXorcATwUuDlwFkRcSjw98DxVAnfz4GVQ/b7r8CrgVcBi4F3TuDcM8p5Xgi8AtgDOHtInTcDfwL0NSaGmXkd8DHgysyck5n7AauAvSLiFQ37vw344gTaJql9Bv/d7wp8Dfh3YAFwGPDBiDhi6A4RsQD4BtUAz67AXwNfiYh5pcrDwDFUg1EnARdGxKvKttOAfmAesDvVoNFARMwE/udYzj8oM38J3EgVPwe9DVhZLr6OLcf/83K+7wFXNNRdA+xf+nA58OWIeHbD9sXA1UAf8KWR2iGpNnYY78rA+s3Af2vY7y3A1WOMK1DFv9dQDaYfT3XtNxbLgW3Ay4BXAodTDbCrg5jYadCnM3NdGQE6jyrAvBVYlpl3ZOZW4Ezgv5RRnEEXZOaGzHwA+GTZb1wy897MXJ2ZWzPzEaoRoT8eUu1TpX2/HsPxtgJXUl1EERH7AHsCXx9v2yS11acycx3V3al5mXlOZj6RmfdR3eU/YZh93gZcm5nXZubvMnM18AOqUWYy8xuZ+bPMHMjM/w/4FvBHZd/fUg1ivTgzf5uZ38vMAaqLoLGev9Fyno5DPVTxcXCA6S+Bv8/Me8pg1ceA/SPixaWd/5KZj2bmtsz8ODALiIZj35yZ/1r6uMO4KKnjjTXeXU651oqIGaX88rJt1LhSnJ+Zm8p123epBpBGFRG7A0dRzRz4z8x8mOqO4o5ioFrMqZgatK7h88+p7p69ELhjsDAzN0fEo1QjSGtH2W9cIuL5wKeoLq7mUg04bBylfWOxHLgiIs6immJ6VUn4JNXH4L/7FwMvjIhNDdt6qEajh3oxcFxE/GlD2U5UFzBExFHAUqqZCTOB2cCPSr3/l2q2wLciAuCSzDx/nOdvdA3wuYh4STnfY5l5W0M7L4qIjzfUn0EVX39epo+/iyqmDlDdYXxeQ93xxkRJnW2s8e5q4B/LtMxFVPHhew37jhhXyvdfNmzbAswZQ9teTBVH15fYCFX8NA51GBM7Ddqj4fOLgAfLz1OjPOXZtt2AXwzZ764h+wH8J9UF06AXjHLuv6cKTP9nZj5aphJ8ekidgVH2f8a2zLwlIp6gShbfUn4k1cvgv+11wP2ZuWgM+6wDvpiZfzF0Q0TMAr4CvAO4pkxd+leqCx8y83Gq6ZinlTv9342INeM8/1PKc8pXUc1++H22nw6+DjgvM58xjTIi/ojq2ebDgLvKM34bB9tZjBYTJdXPmOJdZm6KiG9RTaN8BXBFmVkwuO+wcWUMRrtuWwdsBZ43dJ0EdRYTOw06JSK+TjV68xGqqYw3ACsj4nLgHqpb+rdm5tqG/T4UEbdSjfh8gGoaJcCdwOkR8SLgMappnCOZW+psKs/HfGicbX8IeENEzMzM3zWUr6BKELdl5vfHeUxJneM24FcRcTrV3f0nqC5ods7MNUPq/guwpjz/9m2qUeaDqRZceoxqSuMjwLZy9+5w4McAEXEM8BOqxQl+BTxZfsZz/qFWlJ/nA/93Q/nngI9GxJ2ZeVdZmODwzPwyVUzcVtrZGxFnUN2xk9T9xhJvLqca/HkR1QDQoNHiyo6MeN2WmetLMvnxiPgbqgVd9gIWlint6hA+Y6dBl1M9a3Jf+Tk3M28A/oZqhHs91cIqQ+dTXwPcThUQvgFcClCea7kS+GHZPtrzbX9HtfjKY+UYXx1n2wcD1qMRcUdD+Rep5qq7aIpUY2XVtT+lehbkfuA/qFaBfO4wdddRLSzyEarEaB3VYNHMckfu/cBVVNO930K12NKgRVTJ4GaqBQo+m5k3juf8w7Tnf1GtIHdH46BYZn4NuIBq8OxXVMnlUWXz9cA3gf9NNX3qNzjlSZoWxhhvVlHFq4cy898b9h0truzovDu6bnsH8Czgbqr4eTXVM8nqIDMGBpzNMd2VZXbflZnfHud+A8CizLx3Kto1WRGxM9UKeK/KzJ+2uz2SpqeI+A5weWb6SgJJ0pRxKqa62XuANSZ1ktolIl7D06+DkSRpypjYqSuVu5AzAF9ILmnKRMQ3efp1CY0+RvV6gmOpXpD+eEsbJkmadpyKKUmSJEk15+IpkiRJklRztZmK+cgjj4/51uKcObPYvHn6vova/tv/dvR/3ry5M3Zca3rphrjVqe2Czm1bp7YLOrdtxq3OMtbY5d+n8bFd42O7hjda3OrKO3a9vT3tbkJb2X/7r/rp1P9undou6Ny2dWq7oHPb1qnt0ug69b+b7Rof2zU+ndou6NLETpIkSZKmExM7SZIkSao5EztJkiRJqjkTO0mSJEmqORM7SZIkSao5EztJkiRJqrnavMduPBb9zXVNP+aa017X9GNKkjSdvebjNzX9mP7/unW83pI6S1cmdpI0nIh4NnATMIsq/l2dmUsj4jLgj4HHStUTM/POiJgBXAQcDWwp5XeUYy0Bzir1z83M5a3riSRJ0vZM7CRNJ1uBQzNzc0TsBHw/Ir5Ztn0oM68eUv8oYFH5OQi4GDgoInYFlgKvBgaA2yNiVWZubEkvJEmShjCxkzRtZOYAsLl83an8DIyyy2JgRdnvlojoi4j5wCHA6szcABARq4EjgSumqu2SJEmjMbGTNK1ERA9wO/Ay4DOZeWtEvAc4LyL+FrgBOCMztwILgHUNu/eXspHKJWnCImIZcAzwcGbuW8p2Ba4E9gTWAsdn5saJTBWPiAOAy4CdgWuBD5SBK0ldwMRO0rSSmU8C+0dEH/C1iNgXOBP4JfAs4BLgdOAcYMYwhxgYpXw7c+bMore3Z0zt6umZSV/f7DHVbaVObRd0bts6tV3Q2W1rlpr37zLg08CKhrIzgBsy8/yIOKN8P52JTRW/GHg3cAtVYnck8E0kdYUdJnaOHknqRpm5KSJuBI7MzH8oxVsj4gvAX5fv/cAeDbstBB4s5YcMKb9x6Dk2b9465vb09c1m06YtY67fKp3aLujctnVqu6Cz29Ys4+nfvHlzp7Al45eZN0XEnkOKF/N0vFlOFWtOZ5xTxUu8e05m3lzKVwDHYmIndY2x3LG7DEePJHWBiJgH/LYkdTsDrwcuiIj5mbm+DE4dC/y47LIKeG9ErKSKaY+VetcDH4uIXUq9w6nu+klSs+2emesBSvx5fikf71TxBeXz0PJnGM9sg2Zrxh3XTr0zbbvGx3aN3w4TO0ePJHWR+cDy8pzdTOCqzPx6RHynJH0zgDuBvyr1r6WagXAv1SyEkwAyc0NEfBRYU+qdMxjfJKlFxjtVfExTyGF8sw2arRl3lDv1zrTtGh/bNbzRZhpM9Bm7lo8eSdJkZeYPgVcOU37oCPUHgFNG2LYMWNbUBkrSMz3UMKtgPvBwKR/vVPH+8nlofUldotmLp0zZ6FE7pwVAvR7G7uRbxK1g/6d3/yWpy6wClgDnl9/XNJSPeap4mWnweEQcDNwKvAP4x1Z2RNLUmmhi1/LRo3ZOC4DmTA1olXbfIm43+9+e/nfaIgSSVDcRcQXV9dLzIqKfan2C84GrIuJk4AHguFJ9IlPF38PTC9Z9Ex99kbrKRBM7R48kSZKaKDPfPMKmw4apO+6p4pn5A2DfybRRUucay+sOHD2SJEmSpA42llUxHT2SJEmSpA42s90NkCRJkiRNjomdJEmSJNWciZ0kSZIk1ZyJnSRJkiTVnImdJEmSJNWciZ0kSZIk1ZyJnSRJkiTVnImdJEmSJNXcDl9QLkndJCKeDdwEzKKKgVdn5tKI2AtYCewK3AG8PTOfiIhZwArgAOBR4E2ZubYc60zgZOBJ4P2ZeX2r+yNJkgTesZM0/WwFDs3M/YD9gSMj4mDgAuDCzFwEbKRK2Ci/N2bmy4ALSz0iYm/gBGAf4EjgsxHR09KeSJIkFSZ2kqaVzBzIzM3l607lZwA4FLi6lC8Hji2fF5fvlO2HRcSMUr4yM7dm5v3AvcCBLeiCJEnSM5jYSZp2IqInIu4EHgZWAz8DNmXmtlKlH1hQPi8A1gGU7Y8BuzWWD7OPJElSS/mMnaRpJzOfBPaPiD7ga8Arhqk2UH7PGGHbSOVPmTNnFr29Y5ud2dMzk76+2WOq20qd2i7o3LZ1arugs9vWLN3eP0kaiYmdpGkrMzdFxI3AwUBfRPSWu3ILgQdLtX5gD6A/InqB5wIbGsoHNe4DwObNW8fclr6+2WzatGWCPZk6ndou6Ny2dWq7oLPb1izj6d+8eXOnsCWS1FpOxZQ0rUTEvHKnjojYGXg9cA/wXeCNpdoS4JryeVX5Ttn+ncwcKOUnRMSssqLmIuC21vRCkiRpeyZ2kqab+cB3I+KHwBpgdWZ+HTgdODUi7qV6hu7SUv9SYLdSfipwBkBm3gVcBdwNXAecUqZ4SpIktZxTMSVNK5n5Q+CVw5TfxzCrWmbmb4DjRjjWecB5zW6jJEnSeHnHTpIkSZJqzsROkiRJkmrOqZiSJEkdLiL+B/Auqteq/Ag4ieqZ4ZXArsAdwNsz84mImAWsAA4AHgXelJlry3HOBE4GngTen5nXt7grkqaId+wkSZI6WEQsAN4PvDoz9wV6gBOAC4ALM3MRsJEqYaP83piZLwMuLPWIiL3LfvsARwKfjYixvWxTUseb1B07R48kSZJaohfYOSJ+C8wG1gOHAm8p25cDZwMXA4vLZ4CrgU9HxIxSvjIztwL3l9V+DwRublEfJE2hCd+xc/RIkiRp6mXmL4B/AB6gSugeA24HNmXmtlKtH1hQPi8A1pV9t5X6uzWWD7OPpJqb7DN2jh5JkiRNoYjYhep6aS9gE/Bl4Khhqg6U3zNG2DZS+XbmzJlFb297xtj7+mZP+hg9PTObcpxms13jY7vGb8KJXWb+IiIGR49+DXyLcYweRUTj6NEtDYd29EiSJOlprwfuz8xHACLiq8AfAH0R0VuuuxYCD5b6/cAeQH9E9ALPBTY0lA9q3Ocpmzdvnap+7NCmTVsmfYy+vtlNOU6z2a7xsV3Dmzdv7ojbJpzYTafRI2jOCFKrdPJIQivY/+ndf0nqQg8AB0fEbKrB9MOAHwDfBd5ItbbBEuCaUn9V+X5z2f6dzByIiFXA5RHxCeCFwCLgtlZ2RNLUmcxUzGkzegTNGUFqlXaPJLSb/W9P/0cbQZIkTVxm3hoRV1MtSrcN+DfgEuAbwMqIOLeUXVp2uRT4Ynm8ZQPVWgZk5l0RcRVwdznOKZn5ZEs7I2nKTCaxc/RIkiSpBTJzKbB0SPF9VOsSDK37G+C4EY5zHnBe0xsoqe0mvCpmZt5KtQjKHVSvOphJNXp0OnBqGSXaje1Hj3Yr5acCZ5Tj3AUMjh5dh6NHkiRJkjQuk1oV09EjSZIkSWq/yb7uQJJqIyL2AFYALwB+B1ySmRdFxNnAXwCPlKofycxryz5nUr2H80ng/Zl5fSk/EriI6h2en8/M81vZF0mSpEYmdpKmk23AaZl5R0TMBW6PiNVl24WZ+Q+NlSNib6pFB/ahegb42xHx8rL5M8AbqBaAWhMRqzLz7pb0QpIkaQgTO0nTRmauB9aXz49HxD2M/t7MxcDKzNwK3F+eER6can5vZt4HEBErS10TO3Wt13z8pnY3QZI0igkvniJJdRYRewKvBG4tRe+NiB9GxLLynk6okr51Dbv1l7KRyiVJktrCO3aSpp2ImAN8BfhgZv4qIi4GPgoMlN8fB94JzBhm9wGGHxQbGFowZ84sent7xtSmTn2xfKe2Czq3bZ3aLujstjVLt/dPkkZiYidpWomInaiSui9l5lcBMvOhhu3/DHy9fO0H9mjYfSHwYPk8UvlTNm/eOuZ2tevF8jvSqe2Czm1bp7YLOrttzTKe/s2bN3cKWyJJrWViJ2naiIgZVO/UvCczP9FQPr88fwfwX4Efl8+rgMsj4hNUi6csAm6jupO3KCL2An5BtcDKW1rTC0mSpGcysZM0nbwWeDvwo4i4s5R9BHhzROxPNZ1yLfCXAJl5V0RcRbUoyjbglMx8EiAi3gtcT/W6g2WZeVcrOyJJktTIxE7StJGZ32f45+au/f/Zu/t4u6ry0Pe/kGA0JrgBA8ZAja3pU4ErKAiceo7lgGBEarAFiVoMSLUvIL7QlpfrufHyoniuiGlVrEIksUBE1JJrU2KKcmnvEUQiokCfa4QUNqTEkgRNo8Hgvn/MscNis9bOflmve/++n8/+7LXGHHOuZ66191jzmXPMMYZZ5zLgsjrlq4dbT5IkqZ0cFVOSJEmSepyJnSRJkiT1OBM7SZIkSepxJnaSJEmS1ONM7CRJkiSpx5nYSZIkSVKPM7GTJEmSpB5nYidJkiRJPc7ETpIkSZJ6nImdJEmSJPW4aZ0OQJIkScOLiD7gauAQYAB4N5DAl4F5wAbgbZm5JSKmAEuBE4HtwBmZua5sZzHw4bLZSzNzeRt3Q1ILecVOkiSp+y0FbsnM3wEOBR4ALgBuzcz5wK3lOcCbgPnl573AVQARsQ+wBDgKOBJYEhF7t3MnJLXOuK7YefZIkiSptSJiL+D1wBkAmfkU8FRELASOKdWWA7cB5wMLgRWZOQDcERF9ETGn1F2bmZvLdtcCC4Ab2rUvklpnvF0xB88enRIRzwNmABdRnT26PCIuoDp7dD7PPnt0FNXZo6Nqzh4dQZUc3h0RqzJzyzhjk6RniYgDgRXAS4BfA5/PzKWlHfKElKRu9ZvAT4EvRsShwN3A+4H9M3MjQGZujIj9Sv25wCM16/eXskblkiaAMSd2nj2S1IN2Audl5rqImEV1ImktVTvmCSlJ3Woa8BrgfZl5Z0Qs5Zlul/VMqVM2MEz5s8ycOZ1p06aOKdDx6uubMe5tTJ26R1O202zGNTrGNXrjuWLX1rNHnWxkoDkNTbt08x9cO7j/k3v/h1PapsH26ecR8QBVe+MJKUndrB/oz8w7y/ObqBK7xyNiTjnemgNsqql/YM36BwCPlfJjhpTfNvTFtm3b0dTgR2Pr1u3j3kZf34ymbKfZjGt0jKu+2bNnNVw2nsSurWePOtnIQHMamnbp9B9cp7n/ndn/4RqabhQR84BXA3didyZJXSwz/z0iHomIyMwEjgPuLz+LgcvL75vLKquAcyJiJVVvgydL27YG+GjNgCknABe2c18ktc54Eru2nj2SpGaJiJnAV4EPZObPIqJR1bZ1Z+rWK63dGhd0b2zdGhd0d2zNMoH3733AdWVMgweBM6lGN78xIs4CHgZOLXVXU90bvJ7q/uAzATJzc0RcAtxV6l082PNAUu8bc2Ln2SNJvSgi9qRK6q7LzK+V4o53Z+rWK83dGhd0b2zdGhd0d2zNMpr966WeBpl5D9V9vUMdV6fuAHB2g+0sA5Y1NzpJ3WC889gNnj26FzgM+ChVQnd8RPwYOL48h+rs0YNUZ4++APw5VGePgMGzR3fh2SNJLVJGubwGeCAzP1mzaBXViSh47gmpd0XElIg4mnJCClgDnBARe5eTUieUMkmSpI4Y13QHnj2S1GNeB5wO/DAi7illF1GdgLI7kyRJ6lnjncdOknpGZv4L9e+PA09ISZKkHjberpiSJEmSpA4zsZMkSZKkHmdiJ0mSJEk9zsROkiRJknqciZ0kSZIk9TgTO0mSJEnqcSZ2kiRJktTjTOwkSZIkqceZ2EmSJElSjzOxkyRJkqQeZ2InSZIkST3OxE6SJEmSepyJnSRJkiT1uGmdDkCS2ikilgEnAZsy85BS9hHgPcBPS7WLMnN1WXYhcBbwNHBuZq4p5QuApcBU4OrMvLyd+yFJklTLxE7SZHMt8GlgxZDyKzPzE7UFEXEQsAg4GHgp8E8R8dtl8WeA44F+4K6IWJWZ97cycEmSpEbsiilpUsnM24HNI6y+EFiZmTsy8yFgPXBk+VmfmQ9m5lPAylJXkiSpI0zsJKlyTkTcGxHLImLvUjYXeKSmTn8pa1QuSZLUEXbFlCS4CrgEGCi/rwDeDUypU3eA+ifFBoYWzJw5nWnTpo4ogKlT96Cvb8ZI422bbo0Luje2bo0Luju2Zpno+ydJjZjYSZr0MvPxwccR8QXgG+VpP3BgTdUDgMfK40blu2zbtmPEMfT1zWDr1u0jrt8u3RoXdG9s3RoXdHdszTKa/Zs9e1YLI2m+iJgKfA94NDNPioiXU3UF3wdYB5yemU9FxHSq+4gPB54ATsvMDWUbdQeEktT7xp3Y2chI6nURMSczN5anbwV+VB6vAq6PiE9SDZ4yH/gu1ZW8+aW9e5RqgJV3tDdqSZPQ+4EHgL3K849TDfy0MiI+R3UsdVX5vSUzXxERi0q90xoNCJWZT7d7RyQ1XzPusRtsZAYNNjLzgS1UjQvUNDLAlaXe0FHnFgCfLcmiJDVdRNwAfKd6GP0RcXDT8IMAACAASURBVBbwPyPihxFxL/DfgQ8CZOZ9wI3A/cAtwNmZ+XRm7gTOAdZQtX83lrqS1BIRcQDwZuDq8nwKcCxwU6myHDi5PF5YnlOWH1fqNxoQStIEMK4rdjWNzGXAh2oamcEz18uBj1CdPVpYHkPVyHx6aCMDPBQRg43Md8YTmyTVk5lvr1N8zTD1L6Nq44aWrwZWNzE0SRrOp4C/Agb7j+4LbC0nmuDZgzjtGuApM3dGxJOl/lzgjpptOvCTNIGMtyumjYwkSVILRcRJwKbMvDsijinFjQZ3Gm7ZcOvsMpqBn5qtGYPfdOsgQcY1OsY1emNO7CZTIwO9NcpWN//BtYP7P7n3X5ImoNcBb4mIE4HnU91j9ymgLyKmlRPqtYM4DQ781B8R04AXUc3fOdyAULuMZuCnZmvG4D7dOkiQcY2OcdU33KBP47liN2kaGWhOQ9Munf6D6zT3vzP732ujy0lSr8jMC4ELAcrJ9L/IzHdGxFeAU6gGrVsM3FxWWVWef6cs/1ZmDkREowGhJE0AYx48JTMvzMwDMnMe1eAn38rMdwLfpmpEoH4jAzWNTClfFBHTywhzNjKSJEm7dz7VGAfrqW5vGbxf+Bpg31L+IeACaDwgVNujltQSrZjH7nxgZURcCnyfZzcyXyqNzGaqZJDMvC8iBhuZndjISJIk1ZWZtwG3lccPUmdUy8z8JXBqg/XrDgglqfc1JbGzkZEkSZKkzmnFFTtJktRBr73i9k6HIElqs2ZMUC5JkiRJ6iATO0mSJEnqcSZ2kiRJktTjvMdOkqQO8n44SVIzeMVOkiRJknqciZ0kSZIk9Ti7YkqaVCJiGXASsCkzDyll+wBfBuYBG4C3ZeaWiJgCLAVOBLYDZ2TmurLOYuDDZbOXZubydu6HJElSLa/YSZpsrgUWDCm7ALg1M+cDt5bnAG8C5pef9wJXwa5EcAlwFHAksCQi9m555JIkSQ2Y2EmaVDLzdmDzkOKFwOAVt+XAyTXlKzJzIDPvAPoiYg7wRmBtZm7OzC3AWp6bLEqSJLWNiZ0kwf6ZuRGg/N6vlM8FHqmp11/KGpVLkiR1hPfYSVJjU+qUDQxT/iwzZ05n2rSpI3qhqVP3oK9vxuiia4NujQu6N7ZujWuy8L2XNFmZ2EkSPB4RczJzY+lquamU9wMH1tQ7AHislB8zpPy2oRvdtm3HiAPo65vB1q3bRxd1G3RrXNC9sXVrXJPFaN772bNntTASSWovu2JKEqwCFpfHi4Gba8rfFRFTIuJo4MnSVXMNcEJE7F0GTTmhlEmSJHWEV+wkTSoRcQPV1bYXR0Q/1eiWlwM3RsRZwMPAqaX6aqqpDtZTTXdwJkBmbo6IS4C7Sr2LM3PogCySJEltY2InaVLJzLc3WHRcnboDwNkNtrMMWNbE0CRJksbMrpiSJEmS1ONM7CRJkiSpx5nYSZIkSVKPM7GTJEmSpB5nYidJkiRJPW7Mo2JGxIHACuAlwK+Bz2fm0ojYB/gyMA/YALwtM7dExBRgKdXQ4duBMzJzXdnWYuDDZdOXZubyscYlSZI0kXjMJWkkxnPFbidwXma+EjgaODsiDgIuAG7NzPnAreU5wJuA+eXnvcBVAKVRWgIcBRwJLCkT/kqSJMljLkkjMObELjM3Dp79ycyfAw8Ac4GFwODZn+XAyeXxQmBFZg5k5h1AX0TMAd4IrM3MzZm5BVgLLBhrXJIkSROJx1ySRqIpE5RHxDzg1cCdwP6ZuRGqhigi9ivV5gKP1KzWX8oalUuSJKlGO465Zs6czrRpU5sf/Aj09c0Y9zamTt2jKdtpNuMaHeMavXEndhExE/gq8IHM/FlENKo6pU7ZwDDlz9LJRgaa09C0Szf/wbWD+z+5919qpddecXunQ9Ak1q5jrm3bdow5xvHaunX7uLfR1zejKdtpNuMaHeOqb/bsWQ2XjSuxi4g9qRqY6zLza6X48YiYU84czQE2lfJ+4MCa1Q8AHivlxwwpv23oa3WykYHmNDTt0uk/uE5z/zuz/8M1NJKk8WnnMZek3jSeUTGnANcAD2TmJ2sWrQIWA5eX3zfXlJ8TESupbtp9sjREa4CP1ty8ewJw4VjjkiTJK2uaSDzmkjQS47li9zrgdOCHEXFPKbuIqnG5MSLOAh4GTi3LVlMNu7ueaujdMwEyc3NEXALcVepdnJmbxxGXJEnSROIxl6TdGnNil5n/Qv2+2gDH1ak/AJzdYFvLgGVjjUWSmiEiNgA/B54GdmbmEWOZJ0qSmsljLkkjMZ557CRpIvrvmXlYZh5Rno9qnihJkqROMLGTpOGNdp4oSZKktjOxk6RnDADfjIi7I+K9pexZ80QBu5snSpIkqe2aMkG5JE0Qr8vMx8okv2sj4l+Hqbvb+aBGM/9mt84/2K1xQXfHps7xb0LSZGViJ0lFZj5Wfm+KiK8DRzL6eaJ2Gc38m906/2K3xgXdHZs6ZzR/E86/KWkisSumJAER8cKImDX4mGp+px/xzDxR8Nx5ot4VEVMi4mjKPFFtDluSJAnwip0kDdof+HpEQNU2Xp+Zt0TEXYxinihJkqROMLGTJCAzHwQOrVP+BKOcJ0qSJKnd7IopSZIkST3OxE6SJEmSepxdMSVJHfXaK27vdAiSJPU8r9hJkiRJUo/zip0kacS8uiZJUnfyip0kSZIk9TgTO0mSJEnqcSZ2kiRJktTjvMdOkrrA/P9xS6dDkCRJPcwrdpIkSZLU40zsJEmSJKnHmdhJkiRJUo8zsZMkSZKkHtc1g6dExAJgKTAVuDozL+9wSJI0LNstSb2m29ut115xe9O3edd5r2/6NqVu1BWJXURMBT4DHA/0A3dFxKrMvL+zkT3DhkZSrV5otySplu2WNLF1S1fMI4H1mflgZj4FrAQWdjgmSRqO7ZakXmO7JU1gXXHFDpgLPFLzvB84qkOxtI1XAaWeNinbLUk9bVK2W6043moVj+M0Ht2S2E2pUzZQ+2T27Fn16tS14fI3jzugXjd79qxOh9BR7v/k3v82sd2S1Gt2227ByNsu262Jo1uPG4xrdLqlK2Y/cGDN8wOAxzoUiySNhO2WpF5juyVNYN1yxe4uYH5EvBx4FFgEvKOzIUnSsGy3JPUa2y1pApsyMPCcK/AdEREnAp+iGn53WWZeNoZtdPUQvq0QEcuAk4BNmXlIKdsH+DIwD9gAvC0zt3QqxlaJiAOBFcBLgF8Dn8/MpZNo/58P3A5MpzpJc1NmLilf2CuBfYB1wOnlJnk12XDtVoP/zUOBzwEzqf4235mZPyvLXgX8LbAX1d/zazPzlxFxOHAt8AJgNfD+zBxXwz2a2CLincBf1qz+KuA1mXlPs2MbZVx7AlcDr6H6+1+RmR8r6zT9u2CUsT2P6rM8guqzfH9m3lbWafZ7Nqp2MCKmUL03JwLbgTMyc13Z1mLgw2XTl2bm8jbG9TvAF6k+z/89Mz9Rs61J993eSmM53trdZxAR06k+78OBJ4DTMnNDk0MfS1xnAP8XVRIL8OnMvLrFMT2nrRiyvOH/YIfjOga4GXioFH0tMy9uQ1x124ohddr+no0wrmPowHs2nG7piklmrs7M387M3xpjUjc4hO+bgIOAt0fEQc2OswtdCywYUnYBcGtmzgduLc8nop3AeZn5SuBo4OzymU+W/d8BHJuZhwKHAQsi4mjg48CVZf+3AGd1MMYJbTft1rU893/zauCCzPzfgK9TEqaImAb8HfCnmXkwcAzwq7LOVcB7gfnlZ+g2x2LEsWXmdZl5WGYeBpwObMjMe1oU24jjAk4Fppfyw4E/iYh5LfwuGE1s7wEo5ccDV0TE4Pdts9+z0baDb6p57feWeAZPCC6hGkjjSGBJROzdxrg2A+cCn6jdyCT+bm+Z0R5vjfAzOAvYkpmvAK6k+h5qqVH8bXx5sA1rdVJXXMvw/9d1/wfb4Fp23978c8171a4EpVFbUasT79lI4oLOvGcNdU1i1wSTcgjfzLyd6gux1kJg8EzrcuDktgbVJpm5cfCMTWb+HHiAasSvybL/A5m5rTzds/wMAMcCN5XyCbv/3a7B/2ZQXWUFWAv8YXl8AnBvZv6grPtEZj4dEXOAvTLzO+Wqzgqa8HmOMrZabwduAGhFbKOMawB4YUmKXwA8BfyMFn0XjDK2g6iSFjJzE7AVOKJF79lo28GFVFc3BzLzDqCvxPVGYG1mbi49HNYyjqRztHFl5qbMvItnTmgMmpTf7V1mJJ9B7ed6E3BcucrS6bjarkFbUavR/2Cn4+qIYdqKWm1/z0YYV9eZSIldvSF8u/4DaJH9M3MjVH+YwH4djqflImIe8GrgTibR/kfE1Ii4B9hEdSD2E2BrZu4sVSbz/0E3+hHwlvL4VJ4ZxOC3gYGIWBMR6yLir0r5XKrPcFArP89GsdU6jZLYtTG2RnHdBPwnsBF4GPhEZm6mvd8FjWL7AbAwIqaVrtGHl2Utfc9G2A42en9a9r6Ns332u73zRvIZ7KpTvn+eBPbtgrgA/jAi7o2Im0r3uk7r5r/p/xIRP4iIf4yIg9v94kPailodfc+GiQs6/J4NNZESuxEN4auJJyJmAl8FPpDlfqXJIjOfLl3kDqA6e/nKOtX8P+ge76bqznE3MIvqKhNU94j9V+Cd5fdbI+I42tuuNYoNgIg4CtiemT8qRe2KrVFcRwJPAy8FXg6cFxG/2ca4hottGdWBx/eo7mX6X1TdeloW2yjawUYxtCS2JrTPfrd33kg+g058TiN5zf8bmJeZrwL+iWeuKnZSt/5NrwNeVm7v+Bvg79v54rtpKzr2nu0mro6+Z/VMpMTOIXyf8fjgJerye1OH42mZMoDCV4HrMvNrpXjS7P+gzNwK3EbVD7yvdE+Dyf1/0HUy818z84TMPJzqytdPyqJ+4P/JzP/IzO1Ug2q8ppQfULOJln2ew8Q2aBHPXK0bjLnlsQ0T1zuAWzLzV6W74/9LNVhJ274LGsWWmTsz84PlnouFQB/wY1r0no2yHWz0/jT9fWtS++x3e+eN5DPYVad8/7yI1nf7221cpVv7jvL0C1RXzzutK/+mM/Nng7d3ZOZqYM+IeHE7XrtBW1GrI+/Z7uLq5HvWyERK7HYN4VtGJFsErOpwTJ2yClhcHi+mGrFnwin9968BHsjMT9Ysmiz7Pzsi+srjFwBvoOoD/m3glFJtwu5/L4qI/crvPahGH/xcWbQGeFVEzCgHRb8H3F+6qv08Io4uf+/vokWf5zCxDZadSnUPC7CrG13LYxsmroeBYyNiSkS8kOqkxr/Sxu+CRrGVz/GF5fHxwM7MbMnnOYZ2cBXwrvK+HQ08WeJaA5wQEXuXQVNOKGXtiqsRv9s7bySfQe3negrwrRzn6L3NiGvIfVhvofqO7LRG/4MdFREvGbwvMiKOpMoRnmjD6zZqK2q1/T0bSVydes+G0y3z2I1bZu6MiHOovogGh/C9r8NhtVxE3EA1gt6LI6KfalSzy4EbI+IsqoOfUzsXYUu9jmqUvh+W+8wALmLy7P8cYHkZGWwP4MbM/EZE3A+sjIhLge9TNUxqswb/mzMj4uxS5WtUw7uT1XDvn6Q6UBkAVmfmP5R6f8Yzw+P/Y/lpW2zF64H+zHxwyKaaGtso4/pMefwjqm46X8zMe8t2mv5dMMrY9gPWRMSvqYZZP71mU83+PEfbDq6mGjJ8PdWw4WcCZObmiLiE6m8Q4OJyz2Jb4oqIl1B1Xd0L+HVEfAA4KKvpIybdd3s3aXR8FREXA9/LzFVU3zNfioj1VFfqFnVJXOdGxFuoukJvBs5odVwN2oo9S8yfo8H/YBfEdQrwZxGxE/gFsKgNyTk0bit+oya2TrxnI4mrU+9ZQ10zj50kSZIkaWwmUldMSZIkSZqUTOwkSZIkqceZ2EmSJElSjzOxkyRJkqQeN2FGxZQkSZKkbhQRy4CTgE2Zechu6r4MWAbMphrR9Y8ys393r+EVO0mSJElqrWuBBSOs+wlgRWa+CrgY+NhIVvKKnSRJkiS1UGbeHhHzassi4reo5mWdTTVH33sy81+Bg4APlmrfBv5+JK/hFTtJkiRJar/PA+/LzMOBvwA+W8p/APxhefxWYFZE7Lu7jXnFTpIkSZLaKCJmAr8LfCUiBounl99/AXw6Is4AbgceBXbubpsmdpIkSZLUXnsAWzPzsKELMvMx4A9gVwL4h5n55Eg2KEmSJElqk8z8GfBQRJwKEBFTIuLQ8vjFETGYp11INULmbpnYSZIkSVILRcQNwHeqh9EfEWcB7wTOiogfAPcBC0v1Y4CMiP8P2B+4bCSvMWVgYKDpgUuSJEmS2scrdpIkSZLU40zsJEmSJKnHmdhJkiRJUo8zsZMkSZKkHmdiJ0mSJEk9zsROkiRJknqciZ0kSZIk9TgTO0mSJEnqcSZ2kiRJktTjTOw0qUTEtRFxaXn83yIiOx2TpN4SEfdFxDGdjkOSpFrTOh2A1CmZ+c9AdDoOSd0rIq4F+jPzw4NlmXlw5yKSNBFExEeAV2TmH3U6Fk0cXrGbhCLChF7SpGB7J0njZ1vaG6YMDAx0Oga1QURsAK4C3kl1lWo+cCXwemAbcGVm/nVEvBT4CTA3MzeXdV8NrAXmZOavIuLdwF8CLwG+C7w3M/+t1B0A/gw4D3gxcD1wTmYODD07FRHzgIeAPTNzZ0S8CPgkcCLwa+CLwJLMfHqY/fot4AvAocAAsAY4OzO31sR+Tdnf1aXO+sz8cOlK9XeZecAY31ZJXahOe/c8YH5mri/Lr6VchRtsB6jaw/OBp4GLMvOLEfFe4DNU7cZTwLcz8/fL9v84M/+ptGsHAzuAhcAG4A/LzwdL+VmZ+c3y2qNu5yR1r4i4ADgiM0+pKVsKTAEuBz4H/FdgM/DxzPxCRCwAVpU6O4CfZOahzT4OGi62zDx3uNeLiDOA91Ad5y0GPluWD3fM9RqqY65XALeUbf54sMdDRJwEXArMA+4H/jQz7x3F263d8Ird5PJ24M3APsDXgR8Ac4HjgA9ExBsz8zHgO1QHJYPeAdxUkrqTgYuAPwBmA/8M3DDkdU4CXkv1j/824I0jjG85sJOqQXg1cALwx7tZZwrwMeClwCuBA4GPAETE84C/B75U9vkrQ/ZL0sQ12N71jaDuS4AXUbWHZwGfiYi9M/PzwHXA/8zMmZn5+w3W/32qdmZv4PtUBzt7lO1dDPxtTd2xtHOSutcNwIkRsRdAREylOva5vizrpzpGOQX4aEQcl5m3AB8FvlzalkPLtpp6HLSb2EbyekcBDwL7AZcN91rlmOvrwLVUx1w3AG8d3FBJ+pYBfwLsS9UuroqI6bvZP42Cid3k8teZ+QhwCDA7My/OzKcy80GqMzCLSr3rqQ6KiIgppXywEfgT4GOZ+UBm7qRqmA6LiJfVvM7lmbk1Mx8Gvg0ctrvAImJ/4E3ABzLzPzNzE9UZ9EXDrZeZ6zNzbWbuyMyfUp15+r2y+GhgT+BTmfmrzLwJuGt3sUiaEP46Mx/JzF+MoO6vgItLO7GaqhfDaO6//efMXFPaxK9QnfS6PDN/BawE5kVE31jbOUndq/RYWgecXIqOBbYDj1JdqTs/M3+ZmfcAVwOn19tOK46DGsWWmXeM8PUey8y/ycydmfmLERxzTaNqe3+VmV+juto36D3A32bmnZn5dGYup7paefRw+6fRsb/s5PJI+f0y4KURsbVm2VSqq28ANwF/U7plzqe63P7PNesujYgratadQnVm+t/K83+vWbYdmDmC2F5GlYRtjNh1PLVHTcx1RcR+wF8D/w2YVdbZUha/FHg0M2v7G/8bkiaDYduOIZ4oSdmgkbZbgx6vefwL4D9quk4NJpYzqdqkUbdzkrre4AnxFVS9nK6n+n/fnJk/r6n3b8ARDbbRiuOgRrGN9PWe9dpjOOaqXf9lwOKIeF9N2fPKemoSE7vJZfCf7RHgocycX69S6Zf9TarL9a8Ebqj5R30EuCwzrxvD6/8nMKPm+UtqHj9CdebmxUMOsHbnY1T79arMfKJ0Ff10WbYRmBsRU2ri/w2qewglTWy1BxfbeW7b0z+G7YzXWNs5Sd3tK8AVEXEAVffD/0J15X+fiJhVk9z9BtWVPHhu29KK46BGsY309YbGONpjrgN55phr8PjxslHsm0bJrpiT03eBn0XE+RHxgoiYGhGHRMRra+pcD7yL6p6062vKPwdcGBEHQzUQQEScOsLXvQd4fUT8Rrlh98LBBZm5EfgmVeOzV0TsERG/FRG/12hjxSyqxnNrRMylGtRl0Heo+o6fGxHTIuIPgCNHGKukieMe4B2lrVvAM12HRuJx4DebEcQ42jlJXax0S7yNanCRh8rtKo8A/wv4WEQ8PyJeRXUP7+CJ8cepumnvUbbRiuOgurGN4/V2d8z1NHBOOeZayLOPub4A/GlEHBURUyLihRHx5oiYtZv90yiY2E1CpYvQ71Pd+/YQ8B9U/b5fVFNtFVU3zMcz8wc1634d+DiwMiJ+BvyIqo/2SF53LfBl4F7gbuAbQ6q8i+qy/P1Ul/ZvAubsZrP/J/Aa4EngH4Cv1bzeU1SDvJxRtnda7XJJk8b7qdq8rVQjZf79KNa9BjgoIrZGxGjWa2Qs7Zyk7nc98AaefTL87VQjQD5GNbDIknIsBNWVNIAnImJdedzU46DdxDaW1xvJMddZVG3tH1Ed5+0oy79HdZ/dp8trrac6PlMTOd2BJq2IOBa4OjObcjZekiRJlYi4E/hcZn6x07FMFt5jp8nsEKorlpIkSRqH0o0zqXqCvRN4FdV8dmoTEzt1vYj4HNUl/aH+LjP/dIzbXAq8hWrSTUmSpK7UiuOgFgngRqpRgH8CnFLu5VOb2BVTkiRJknqcg6dIkiRJUo8zsZMkSZKkHtcz99j99Kc/H3Gf0Zkzp7Nt245WhjNqxjRy3RhXN8YE3RXX7NmzpnQ6hm7T6+3WSBl7Zxj7+Nlu1TeatmssuuXzbwX3rTf10r4N125NyCt206ZN7XQIz2FMI9eNcXVjTNC9cWn0evmzNPbOMHb1qon8+btvvWmi7NuETOwkSZIkaTIxsZMkSZKkHtcz99hJkiRNRhHxfOB2YDrVsdtNmbkkIq4Ffg94slQ9IzPviYgpwFLgRGB7KV9XtrUY+HCpf2lmLm/fnkhqJRM7SZKk7rYDODYzt0XEnsC/RMQ/lmV/mZk3Dan/JmB++TkKuAo4KiL2AZYARwADwN0RsSozt7RlLyS1lImdJElSF8vMAWBbebpn+Rlu5MqFwIqy3h0R0RcRc4BjgLWZuRkgItYCC4AbWhW7pPaZkInd/P9xS9O3edd5r2/6NiWplV57xe1N36ZtodQZETEVuBt4BfCZzLwzIv4MuCwi/g/gVuCCzNwBzAUeqVm9v5Q1Kn+WmTOnt3SUwKlT96Cvb0bLtt9J3bhvrTgu/vElC5q+zU7qxs9tLCZkYidJkjSRZObTwGER0Qd8PSIOAS4E/h14HvB54HzgYqDePFcDw5Q/S6vn8+rrm8HWrdtb+hqdMpH3rdZE28de+txmz57VcNluE7uIWAacBGzKzENK2T7Al4F5wAbgbZm5ZSw360bE4cC1wAuA1cD7S9cBSZIk1cjMrRFxG7AgMz9RindExBeBvyjP+4EDa1Y7AHislB8zpPy2VsYrqX1GcsXuWuDTwIqasguAWzPz8oi4oDw/n7HdrHsV8F7gDqrEbgHwj0hSC0TEB4E/pmqLfgicCcwBVgL7AOuA0zPzqYiYTtX2HQ48AZyWmRvKdi4EzgKeBs7NzDVt3hVJk0REzAZ+VZK6FwBvAD4eEXMyc2M5sX4y8KOyyirgnIhYSXU89mSptwb4aETsXeqdQHXVT9IEsNt57DLzdmDzkOKFwODwuMupGpPB8hWZOZCZdwCDN+u+kXKzbknm1gILyrK9MvM75SrdipptSVJTRcRc4FzgiNIDYSqwCPg4cGVmzge2UCVslN9bMvMVwJWlHhFxUFnvYKqTUZ8t979IUivMAb4dEfcCd1EdU30DuC4ifkh1kurFwKWl/mrgQWA98AXgzwHKoCmXlG3cBVw8OJCKpN431nvs9s/MjQDlDNB+pXy0N+vOLY+HlktSq0wDXhARvwJmABuBY4F3lOXLgY9Q9SZYWB4D3AR8upwZXwisLIMUPBQR64Ejge+0aR8kTSKZeS/w6jrlxzaoPwCc3WDZMmBZUwOU1BWaPXjKaG/WHdFNvND6EZp2Z7wj5XTjaDvdGBN0Z1zdGBN0b1zdKjMfjYhPAA8DvwC+STXK3NbM3Fmq1Z5g2nVSKjN3RsSTwL6l/I6aTY97ZLle+Szrxdgrsddj7J3Ry7FLUrcaa2L3eE2/7jnAplI+2pt1+8vjofWfo9UjNO3OeEfK6cbRdroxJujOuLoxJuiuuIYbpalblPtKFgIvB7YCX6G6N3iowRNMbRtZrps+y+HUi7FXYq/H2DujW2LvhXZLkkZqt/fYNbAKWFweLwZuril/V0RMiYijKTfrAmuAEyJi73JgdQKwpiz7eUQcXbo3vatmW5LUbG8AHsrMn2bmr4CvAb9LdT/w4Imu2hNMu05WleUvorrnuNFJLEmSpI7YbWIXETdQ3TcSEdEfEWcBlwPHR8SPgePLcxjbzbp/Blxd1vkJjogpqXUeBo6OiBnlZNJxwP3At4FTSp2hJ6sGT2KdAnyr3LuyClgUEdMj4uVUIwF/t037IEmS9By77YqZmW9vsOi4OnVHfbNuZn4POGR3cUjSeGXmnRFxE9WUBjuB71NN6vsPwMqIuLSUXVNWuQb4UhkcZTPVSJhk5n0RcSNVUrgTOLtMHixJktQRzR48RZK6WmYuoZpXs9aDVKNaDq37S+DUBtu5DLis6QFKkiSNwVjvsZMkSZIkdQkTO0mSJEnqcSZ2kiRJktTjTOwkSZIkqceZ2EmSJElSjzOxkyRJkqQeZ2InSZIkST3OeewkSZK6WEQ8H7gdmE517HZTlZhoywAAIABJREFUZi6JiJcDK4F9gHXA6Zn5VERMB1YAhwNPAKdl5oayrQuBs4CngXMzc02790dSa3jFTpIkqbvtAI7NzEOBw4AFEXE08HHgysycD2yhStgov7dk5iuAK0s9IuIgYBFwMLAA+GxETG3rnkhqGRM7SZKkLpaZA5m5rTzds/wMAMcCN5Xy5cDJ5fHC8pyy/LiImFLKV2bmjsx8CFgPHNmGXZDUBiZ2kiRJXS4ipkbEPcAmYC3wE2BrZu4sVfqBueXxXOARgLL8SWDf2vI660jqcd5jJ0mS1OUy82ngsIjoA74OvLJOtYHye0qDZY3Kn2XmzOlMm9a6HppTp+5BX9+Mlm2/kybyvtWaaPs4UT43EztJkqQekZlbI+I24GigLyKmlatyBwCPlWr9wIFAf0RMA14EbK4pH1S7zi7btu1o3Q5QJQVbt25v6Wt0ykTet1oTbR976XObPXtWw2V2xZQkSepiETG7XKkjIl4AvAF4APg2cEqpthi4uTxeVZ5Tln8rMwdK+aKImF5G1JwPfLc9eyGp1bxiJ0mS1N3mAMvLCJZ7ADdm5jci4n5gZURcCnwfuKbUvwb4UkSsp7pStwggM++LiBuB+4GdwNmli6c0Kq+94vamb/Ou817f9G1ONiZ2kiRJXSwz7wVeXaf8QeqMapmZvwRObbCty4DLmh2jpM6zK6YkSZIk9TgTO0mSJEnqcSZ2kiRJktTjTOwkSZIkqceZ2EmSJElSjxvXqJgR8UHgj4EB4IfAmVRD8q4E9gHWAadn5lMRMR1YARwOPAGclpkbynYuBM4CngbOzcw144lLkiRJkiaTMV+xi4i5wLnAEZl5CDCVap6UjwNXZuZ8YAtVwkb5vSUzXwFcWeoREQeV9Q4GFgCfLfO0SJIkSZJGYLxdMacBL4iIacAMYCNwLHBTWb4cOLk8XlieU5YfFxFTSvnKzNyRmQ8B66kzJ4skSZIkqb4xd8XMzEcj4hPAw8AvgG8CdwNbM3NnqdYPzC2P5wKPlHV3RsSTwL6l/I6aTdeus8vMmdOZNq1zF/L6+maMa/2pU/cY9zaarRtjgu6Mqxtjgu6NS5IkSe015sQuIvamutr2cmAr8BXgTXWqDpTfUxosa1T+LNu27RhboE2ydev2ca3f1zdj3Ntotm6MCbozrm6MCborrtmzZ3U6BEmSpElrPF0x3wA8lJk/zcxfAV8DfhfoK10zAQ4AHiuP+4EDAcryFwGba8vrrCNJkiRJ2o3xJHYPA0dHxIxyr9xxwP3At4FTSp3FwM3l8arynLL8W5k5UMoXRcT0iHg5MB/47jjikiRJkqRJZcyJXWbeSTUIyjqqqQ72AD4PnA98KCLWU91Dd01Z5Rpg31L+IeCCsp37gBupksJbgLMz8+mxxiVJkiRJk8245rHLzCXAkiHFD1JnVMvM/CVwaoPtXAZcNp5YJGkkIqIPuBo4hOp+3ncDCXwZmAdsAN6WmVtKb4SlwInAduCMzFxXtrMY+HDZ7KWZuRxJkqQOGVdiJ0k9aClwS2aeEhHPo5qq5SLg1sy8PCIuoOpRcD7VgFDzy89RwFXAURGxD9VJrSOoksO7I2JVZm5p/+5Imugi4kBgBfAS4NfA5zNzaUR8BHgP8NNS9aLMXF3WuZBqDuGngXMzc00pX0DVDk4Frs7My9u5L5Jax8RO0qQREXsBrwfOAMjMp4CnImIhcEypthy4jSqxWwisKPcD3xERfRExp9Rdm5mby3bXAguAG9q1L5ImlZ3AeZm5LiJmUZ1MWluWXZmZn6itHBEHAYuAg4GXAv8UEb9dFn8GOJ5q8Lq7ykmp+9uyF5JaysRO0mTym1Rntr8YEYdSzb35fmD/zNwIkJkbI2K/Un/X/JvF4DybjcqfZTTzb/bKnIT1YuyV2Osx9s7o5dg7obRPg23UzyPiAeq0OTUWAiszcwfwUBnfYPA2mfWZ+SBARKwsdU3spAnAxE7SZDINeA3wvsy8MyKWUgZyaqBt829205yEw6kXY6/EXo+xd0a3xN6L829GxDzg1cCdwOuAcyLiXcD3qK7qbaFK+u6oWa325NPQk1JHtTpmSe1hYidpMukH+suovlCN7HsB8HhEzClX6+YAm2rq15tns59num4Olt/WwrgliYiYCXwV+EBm/iwirgIuoTqxdAlwBdWAUI1OPtUbDf05J6VG09tgLCbyFduJvG+t1sn3baJ8biZ2kiaNzPz3iHgkIiIzk2fm37yfap7Ny3nu/JvnlO5KRwFPluRvDfDRiNi71DsBuLCd+yJpcomIPamSuusy82sAmfl4zfIvAN8oTxudlGKY8l1G09tgLLrlim0rTOR9a7VOvm+99LkN19PAxE7SZPM+4LoyIuaDwJlUZ7FvjIizgId5ZmqW1VRTHaynmu7gTIDM3BwRlwB3lXoXDw6kIknNVqZeuQZ4IDM/WVM+Z/D+YOCtwI/K41XA9RHxSarBU+YD36W6kjc/Il4OPEo1wMo72rMXklrNxE7SpJKZ91BNUzDUcXXqDgBnN9jOMmBZc6OTpLpeB5wO/DAi7illFwFvj4jDqLpTbgD+BCAz74uIG6l6I+wEzs7MpwEi4hxgDdV0B8sy87527oik1jGxkyRJ6mKZ+S/Uv29u9TDrXAZcVqd89XDrSepd9W6ilSRJkiT1EBM7SZIkSepxJnaSJEmS1ONM7CRJkiSpx5nYSZIkSVKPM7GTJEmSpB5nYidJkiRJPc7ETpIkSZJ6nImdJEmSJPU4EztJkiRJ6nEmdpIkSZLU40zsJEmSJKnHTRvPyhHRB1wNHAIMAO8GEvgyMA/YALwtM7dExBRgKXAisB04IzPXle0sBj5cNntpZi4fT1ySJEmSNJmM94rdUuCWzPwd4FDgAeAC4NbMnA/cWp4DvAmYX37eC1wFEBH7AEuAo4AjgSURsfc445IkSZKkSWPMV+wiYi/g9cAZAJn5FPBURCwEjinVlgO3AecDC4EVmTkA3BERfRExp9Rdm5mby3bXAguAG8YamyRJ0kQREQcCK4CXAL8GPp+ZS8vJcXtJSQLGd8XuN4GfAl+MiO9HxNUR8UJg/8zcCFB+71fqzwUeqVm/v5Q1KpckSRLsBM7LzFcCRwNnR8RB2EtKUo3x3GM3DXgN8L7MvDMilvJMg1LPlDplA8OUP8vMmdOZNm3qmAJthr6+GeNaf+rUPca9jWbrxpigO+Pqxpige+OSJDVPOVE+eNL85xHxANVJcHtJSdplPIldP9CfmXeW5zdRJXaPR8SczNxYGpFNNfUPrFn/AOCxUn7MkPLbhr7Ytm07xhHq+G3dun1c6/f1zRj3NpqtG2OC7oyrG2OC7opr9uxZnQ5Bkia8iJgHvBq4kyG9pCKiKb2kWn0yfSKflJzI+9ZqnXzfJsrnNubELjP/PSIeiYjIzASOA+4vP4uBy8vvm8sqq4BzImIlVReAJ0sjtAb4aE1XgBOAC8calyRJ0kQUETOBrwIfyMyfRUSjquPqJdXqk+nddFKy2SbyvrVaJ9+3XvrchjuRPt5RMd8HXBcR9wKHAR+lSuiOj4gfA8eX5wCrgQeB9cAXgD8HKN0BLgHuKj8XD3YRkCRJEkTEnlRJ3XWZ+bVS/HjpHcUoeknVK5c0AYxrHrvMvAc4os6i4+rUHQDObrCdZcCy8cQiSZI0EZVRLq8BHsjMT9YsWoW9pCQV40rsJEmS1HKvA04HfhgR95Syi6gSuhsj4izgYeDUsmw11VQH66mmOzgTql5SETHYSwrsJSVNKCZ2kiRJXSwz/4X698eBvaQkFeO9x06SJEmS1GEmdpIkSZLU40zsJEmSJKnHmdhJkiRJUo9z8BRJkiSpC7z2its7HYJ6mImdpEknIqYC3wMezcyTIuLlwEpgH2AdcHpmPhUR04EVwOHAE8BpmbmhbONC4CzgaeDczFzT/j2RJEmq2BVT0mT0fuCBmucfB67MzPnAFqqEjfJ7S2a+Ariy1CMiDgIWAQcDC4DPlmRRkiSpI0zsJE0qEXEA8Gbg6vJ8CnAscFOpshw4uTxeWJ5Tlh9X6i8EVmbmjsx8iGoS4CPbsweSJEnPZWInabL5FPBXwK/L832BrZm5szzvB+aWx3OBRwDK8idL/V3lddaRJElqO++xkzRpRMRJwKbMvDsijinFU+pUHdjNsuHW2WXmzOlMmzayHppTp+5BX9+MEdXtpHox9krs9Rh7Z/Ry7JLUrUzsJE0mrwPeEhEnAs8H9qK6gtcXEdPKVbkDgMdK/X7gQKA/IqYBLwI215QPql1nl23bdow4sL6+GWzdun3UO9Ru9WLsldjrMfbO6JbYZ8+e1ekQJKlp7IopadLIzAsz84DMnEc1+Mm3MvOdwLeBU0q1xcDN5fGq8pyy/FuZOVDKF0XE9DKi5nzgu23aDUmSpOfwip0kwfnAyoi4FPg+cE0pvwb4UkSsp7pStwggM++LiBuB+4GdwNmZ+XT7w5YkaWJoxRx+d533+qZvs5uZ2EmalDLzNuC28vhB6oxqmZm/BE5tsP5lwGWti1CSKhGxDBi8R/iQUvYR4D3AT0u1izJzdVlWd57NiFgALAWmAldn5uXt3A9JrWViJ0mS1N2uBT4NrBhSfmVmfqK2YMg8my8F/ikifrss/gxwPNV9wndFxKrMvL+VgUtqH++xkyRJ6mKZeTtVd/CRaDTP5pHA+sx8MDOfAlaWupImCBM7SZKk3nRORNwbEcsiYu9S1mieTefflCY4u2JKkiT1nquAS6jm0LwEuAJ4N43n2ax3Mv8582/C6ObgHIuJPI/hRN63XjTSz2KifG4mdpIkST0mMx8ffBwRXwC+UZ4ON8/mbuffhNHNwTkW3TKPYStM5H3rRSP9LHrpcxtu/k0TO0mSpB4TEXMyc2N5+lbgR+XxKuD6iPgk1eApg/NsTgHml7k3H6UaYOUd7Y1aUiuNO7GLiKnA94BHM/Ok0mCsBPYB1gGnZ+ZTETGdajSnw4EngNMyc0PZRt1heSVJkia7iLgBOAZ4cUT0A0uAYyLiMKrulBuAP4Hh59mMiHOANVTTHSzLzPvavCuSWqgZV+zeDzwA7FWef5xq+N2VEfE5qoTtqvJ7S2a+IiIWlXqnNRqW18l+JUmSIDPfXqf4mmHq151ns8xzt7qJoUnqIuMaFTMiDgDeDFxdnk8BjgVuKlWWAyeXxwvLc8ry40r9RsPySpIkSZJGYLzTHXwK+Cvg1+X5vsDWzNxZntcOpbtrmN2y/MlS3+F3JUmSJGkcxtwVMyJOAjZl5t0RcUwpbjTE7nDLhltnl1YPvbs74x0CtRuHUe3GmKA74+rGmKB745IkSVJ7jeceu9cBb4mIE4HnU91j9ymgLyKmlatytUPpDg6/2x8R04AXAZsZfljeXVo99O7ujHcI1G4cRrUbY4LujKsbY4Luimu44XclSZLUWmPuipmZF2bmAZk5j2rwk29l5juBbwOnlGqLgZvL41XlOWX5tzJzoJQviojpZUTNwWF5JUmSJEkjMN577Oo5H/hQRKynuoducNSma4B9S/mHgAugGpYXGByW9xZqhuWVJEmSJO1eUyYoz8zbgNvK4wepM6plZv4SOLXB+nWH5ZUkSZIk7V4rrthJkiRJktrIxE6SJEmSepyJnSRJkiT1OBM7SZIkSepxJnaSJEmS1ONM7CRJkiSpx5nYSZIkSVKPa8o8dpIkSWqNiFgGnARsysxDStk+wJeBecAG4G2ZuSUipgBLgROB7cAZmbmurLMY+HDZ7KWZubyd+yGptbxiJ0mS1N2uBRYMKbsAuDUz5wO3lucAbwLml5/3AlfBrkRwCXAUcCSwJCL2bnnkktrGxE6SJKmLZebtwOYhxQuBwStuy4GTa8pXZOZAZt4B9EXEHOCNwNrM3JyZW4C1PDdZlNTD7IopSV1g/v+4pdMhSOot+2fmRoDM3BgR+5XyucAjNfX6S1mjckkThImdJEnSxDGlTtnAMOXPMXPmdKZNm9rUoGpNnboHfX0zWrb9TprI+9aLRvpZTJTPzcROkiSp9zweEXPK1bo5wKZS3g8cWFPvAOCxUn7MkPLb6m1427YdTQ+2Vl/fDLZu3d7S1+iUibxvvWikn0UvfW6zZ89quMx77CRJknrPKmBxebwYuLmm/F0RMSUijgaeLF021wAnRMTeZdCUE0qZpAnCK3aSJo2IOBBYAbwE+DXw+cxc6rDhkrpZRNxAdbXtxRHRTzW65eXAjRFxFvAwcGqpvpqqzVpP1W6dCZCZmyPiEuCuUu/izBw6IIukHmZiJ2ky2Qmcl5nrImIWcHdErAXOoBo2/PKIuIBq2PDzefaw4UdRDRt+VM2w4UdQ3aNyd0SsKiPNSVJTZebbGyw6rk7dAeDsBttZBixrYmiSuohdMSVNGpm5cfCKW2b+HHiAalQ4hw2XJEk9zcRO0qQUEfOAVwN3MmTYcMBhw6X/v737D7K0Kg88/m26cdZxBpsfI+IMyRCdPIpU0IA4kZTFgkFAliERFKMwEIwVi4g/SClYbk0KJcFdFalNJEsAnYkoIJIw2RCQBV02tUqQkSwL5ElNYMI0jECYGWQkQgZ7/3hPD5fm9o/p7tv3nu7vp6qr3/e8733vc8/cOfc+fc57jiSpKg7FlDTvRMQi4NvAxzLzJxEx1qnTmja801OGd0O76aBrniba2Luj5tglqVeZ2EmaVyJiT5qk7urMvKEUd2Ta8E5PGd4N7aaDrmma6NGMvTt6Jfbxpg2XpNo4FFPSvFFmubwSeCAzv9RyyGnDJUlS1eyxkzSfHAmcDtwbEfeUsk/jtOGSJKlyU07sXA9KUm0y8+9of38cOG24JEmq2HSGYo6sB/UGYCVwTkQcTLP+022ZuQK4rezDi9eD+hDNelC0rAf1VuAIYE0Z2iRJkiRJmoQpJ3auByVJkiRJvWFG7rEbbz2oiJiR9aC6PW34dKdl7sWpnXsxJujNuHoxJujduCRJkjS7pp3YzdZ6UN2eNny60zL3ytTOrXoxJujNuHoxJuituJw2XJIkqXumtdzBeOtBleOTXQ+qXbkkSZIkaRKmnNi5HpQkSZIk9YbpDMV0PShJkiRJ6gFTTuxcD0qSJKm7ImIT8DTwPLAzMw+fyprCkuo3rXvsJEmS1HX/MTPflJmHl/3dWlNY0twwI8sdSJIkqWesAo4q22uB7wGfomVNYeAHETEYEQeMLFOl3fOWL97R7RCkFzGxkyRJqtcw8J2IGAb+e2Zezu6vKfyixK7Tawe7Bqtmy2TfZ3PlPWliJ0mSVK8jM/PRkrzdGhH/OM65PbF2cC+twaq5bbLvs5rek+OtG+w9dpIkSZXKzEfL78eBvwSOYPfXFJY0B5jYSZIkVSgiXhERi0e2adYC/n/s/prCkuYAh2JKkiTVaX/gLyMCmu9038jMmyPiLnZjTWFJc4OJnSRJUoUy80Hg0DblT7KbawpLqp9DMSVJkiSpciZ2kiRJklQ5EztJkiRJqpyJnSRJkiRVzsROkiRJkipnYidJkiRJlXO5A0mSJElzzlu+eMeMX/Ou894+49ecKfbYSZIkSVLlTOwkSZIkqXIOxZQkSdKc1YnheFIvssdOkiRJkipnYidJkiRJlXMo5iTNt1l1JEmSJNWjZxK7iDgOuBToB67IzIu7HJIkjct2S1JtbLekuasnhmJGRD/wp8DxwMHA+yLi4O5GJUljs92SVBvbLWlu65UeuyOAjZn5IEBEXAOsAu7valQd5vBOqWq2WzPEdkuaNT3fbjmDpTR1vZLYLQU2t+wPAW/tUixV80uXNGtstyTVxnZLmqZO/fFhJr5v90pi19embLh1Z8mSxe3OaWvTxe+adkDqriVLFnc7hJfoxZigd+OaB2y35oia/w8Zu3bThO0W7F7bNVVj/fvbFkpT1xP32NH8xejAlv1lwKNdikWSJsN2S1JtbLekOaxXeuzuAlZExEHAI8BpwG93NyRJGpftlqTa2G5Jc1hP9Nhl5k7g94FbgAeA6zLzvu5GJUljs92SVBvbLWlu6xsefsnQ6ipMtA5LRCwA1gGHAU8C783MTT0Q15nAf6X5SxnAn2TmFR2O6SrgRODxzDykzfG+EvMJwDPAmZm5ocsxHQXcCDxUim7IzAs7HNOBNO+ZVwM/By7PzEtHnTOrdTXJmI5ilutKM6fX15Qa6z0YEfsA1wLLgU3AezJzWzfak4mUKd5/CDySmSeW3oprgH2ADcDpmflctz43xhIRg8AVwCE090H9DpBUUO8R8XHggzRx3wucBRxABfWuzpjM51ntRrc13Y5nprRrizLz+92Nama0a6sy82fdjWrqeqLHbndNch2Ws4Ftmfk64BLg8z0SF8C1mfmm8tPRpK74GnDcOMePB1aUnw8Bl/VATAD/u6WeZiNR2Qmcl5lvAFYC57T595vtuppMTDD7daUZUMmaUmO9B88HbsvMFcBtZR+6055M5KM0vRMjPg9cUmLfRvN5AV343JjApcDNmfl64FCa19Dz9R4RS4FzgcPLH+76aYb81VLv6ozJfp7VbHRbM1e0a4uqN05bVa0qEzta1mHJzOdo/gK4atQ5q4C1Zft64JjyF81uxzXrMvMOYOs4p6wC1mXmcGb+ABiMiAO6HNOsy8wtI3/hzsynaRqupaNOm9W6mmRMqldPthmtxnkPtraxa4GTy/astyfjiYhlwLto/to80ut+NM3nArw09tn+3GgrIvYC3g5cCZCZz2Xmdiqpd5p7+F8eEQPAQmALFdS7Omeuf56NbmvminHaorlidFtV9WRCtSZ27dZhGd047DqnjCl/Cti3B+ICeHdE/N+IuL4MTei2ycY9234tIv4hIv42It44m08cEcuBNwN3jjrUtboaJyboYl1pWnr1/15bo96D+2fmFmi+sAGvKqf12mv6MvBJmqFf0HwObC+fC/Di+LrxuTGWXwKeAL4aET+KiCsi4hVUUO+Z+QjwBeBhmoTuKeBu6qh3zYIJPs9qNbqtmSvGaouq166tyszvdDeq6ak1sZvMOiyTWqtlhk3mOf8aWJ6ZvwL8T174K2U3daOuJrIB+MXMPBT4b8BfzdYTR8Qi4NvAxzLzJ6MOd6WuJoipa3WlaevF/3ttTfAebNUzrykiRu7jvbuleLz4eiZ2mr8i/ypwWWa+GfgpLwy7bKdnYo+IvWl64Q4CXgO8gmao6Gi9WO/qsN1oS6oxRlszV+xuW1SNdm1VRHygu1FNT62J3WTWYdl1TulefSWdH/o3YVyZ+WRmPlt2/5zmZvFu67l1bTLzJ5m5o2zfBOwZEft1+nkjYk+aD5yrM/OGNqfMel1NFFO36kozouf+77UzxnvwsZGhfuX346W8l17TkcBJEbGJZpjr0TR/VR8snwvw4vi68bkxliFgKDNHejSup/lyVUO9vwN4KDOfyMx/B24A3kYd9a4OmsRnbK1e0tZExNe7GtHMGastmgvGaquqVWtit2sdloh4Gc2NjutHnbMeWF22TwFuz8xO/wVwwrhG3fNwEr1xA+p64IyI6IuIlTRd0Vu6GVBEvHrkHouIOILmvfpkh5+zj2YM+QOZ+aUxTpvVuppMTN2oK82YybRlXTXOe7C1jV1NMzPrSHlPtCeZeUFmLsvM5TR1e3tmvh/4Ls3nArw09tn+3GgrM38MbI6IKEXHAPdTQb3TDGtaGRELy/tnJPaer3d1ziQ/Y6s0RltTdc/PiHHaormgXVvVC9/Lp6xXFijfLZm5MyJG1mHpB67KzPsi4kLgh5m5nqbx+IuI2Ejzl7+Oz3IzybjOjYiTaGaH2gqc2em4IuKbwFHAfhExBKwB9iwx/xlwE80U2Rtppsk+qwdiOgX4cETsBP4NOG0WPuiPBE4H7o2Ie0rZp4FfaIlrtutqMjF1o640A8ZqM7oc1mhjvQcvBq6LiLNpPhxPLcdmvT2Zgk8B10TE54AfUSYFoAufGxP4CHB1SfofpKnLPejxes/MOyPiepph4jtp6vhy4G+oo97VGW3bkjLSRL2tXVtUvXHaqmpVu46dJEmSJKlR61BMSZIkSVJhYidJkiRJlTOxkyRJkqTKmdhJkiRJUuWqnBVT0syJiKuAkcVVD5ng3F8ErgKW0Mxe94HMHOp8lJIkSRqPPXaSvgYcN8lzvwCsy8xfAS4E/rhTQUmSJGny7LGT5rnMvCMilreWRcRrgT+l6Zl7BvjdzPxH4GDg4+W07wJ/NYuhSpIkaQz22Elq53LgI5l5GPAHwFdK+T8A7y7bvwksjoh9uxCfJEmSWthjJ+lFImIR8DbgWxExUryg/P4D4E8i4kzgDuARYOdsxyhJkqQXM7GTNNoewPbMfNPoA5n5KPBbsCsBfHdmPjXL8UmSJGkUh2JKepHM/AnwUEScChARfRFxaNneLyJG2o0LaGbIlCRJUpeZ2EnzXER8E/h+sxlDEXE28H7g7Ij4B+A+YFU5/SggI+KfgP2Bi7oQsiRJkkbpGx4e7nYMkiRJkqRpsMdOkiRJkipnYidJkiRJlTOxkyRJkqTKmdhJkiRJUuVM7CRJkiSpciZ2kiRJklQ5EztJkiRJqpyJnSRJkiRVzsROkiRJkipnYidJkiRJlTOx026JiD+MiK93O46piIgzI+Lvuh2HJEmSNNNM7CRJkiSpcn3Dw8PdjkFdEBHnA4dn5iktZZcCfcDFwJ8Bvw5sBT6fmX8eEccB68s5zwL/nJmHRsQrgS8BJwA/B74KrMnM5yeI4XeBTwDLgM3ABzJzQ0S8AbgMeBPwCHBBZq4vj/ke8PXMvKLsnwl8MDN/vewPAx8GzgP2A74B/D7weuBHwJ7AvwE7M3NwarUnSZIk9RZ77OavbwInRMReABHRD7yHJhH6JjAEvAY4BfijiDgmM28G/gi4NjMXZeah5VprgZ3A64A3A8cCHxzvySPiVOAPgTOAvYCTgCcjYk/gr4HvAK8CPgJcHRGxG6/tROAtwKHlNb0zMx8Afg/4fondpE6SJEldJkngAAAVvklEQVRzhondPJWZ/wJsAE4uRUcDz9D0kP068KnM/Flm3gNcAZze7joRsT9wPPCxzPxpZj4OXAKcNkEIHwT+S2belZnDmbmxxLQSWARcnJnPZebtwP8A3rcbL+/izNyemQ8D36Xp+ZMkSZLmrIFuB6Cu+gZNwrQO+O2y/xpga2Y+3XLevwCHj3GNX6QZ3rilpVNtD5qhleM5EPjnNuWvATZn5s9HPf/SCa7X6sct28/QJIqSJEnSnGViN799C/hiRCwDfhP4NWAHsE9ELG5J7n6BpicPYPRNmZtp7rfbLzN37sZzbwZe26b8UeDAiNijJbn7BeCfyvZPgYUt5796N57TG0olSZI0J5nYzWOZ+USZjOSrwEPlPjQi4v8AfxwRfwD8MnA28IHysMeA3xhJvDJzS0R8hyZB/M80ieFBwLLM/F/jPP0VwJfK8gMbaJK8fwfupEnePhkRXwSOBP4TzT1zAPcAvxURV9D07p1dYpqMx4BlEfGyzHxuko+RJEmSep732OkbwDvK7xHvA5bT9J79Jc0Ml7eWY98qv5+MiA1l+wzgZcD9wDbgeuCA8Z40M78FXFSe92ngr4B9SsJ1Es19e/8KfAU4IzP/sTz0EuA5miRtLXD1brzW24H7gB9HxL/uxuMkSZKknuZyB5IkSZJUOXvsJEmSJKly3mOnjomIP+OFe/NafT0zf2+245EkSZLmKodiSpIkSVLlHIopSZIkSZWrZijmE088PamuxUWLFrBjx7OdDmfG1BSvsXZOTfGOFeuSJYv7uhCOJEmSmIM9dgMD/d0OYbfUFK+xdk5N8dYUqyRJ0nwx5xI7SZIkSZpvTOwkSZIkqXImdpIkSZJUORM7SZIkSaqciZ0kSZIkVc7ETpIkSZIqV806drvjLV+8Y8avedd5b5/xa0qSJEnSTJgwsYuIq4ATgccz85BStg9wLbAc2AS8JzO3RUQfcClwAvAMcGZmbiiPWQ18plz2c5m5tpQfBnwNeDlwE/DRzJzUYuSSJEmSpMkNxfwacNyosvOB2zJzBXBb2Qc4HlhRfj4EXAa7EsE1wFuBI4A1EbF3ecxl5dyRx41+LkmSJEnSOCZM7DLzDmDrqOJVwNqyvRY4uaV8XWYOZ+YPgMGIOAB4J3BrZm7NzG3ArcBx5dhemfn90ku3ruVakiRJkqRJmOo9dvtn5haAzNwSEa8q5UuBzS3nDZWy8cqH2pS/xKJFCxgY6J8wsP7+zswHMzi4sCPX7e/fo2PXnmnG2jk1xVtTrJIkSfPFTE+e0tembHgK5S+xY8ezkwqgU184t29/piPXHRxc2LFrzzRj7Zya4h0r1iVLFnchGkmSJMHUlzt4rAyjpPx+vJQPAQe2nLcMeHSC8mVtyiVJkiRJkzTVxG49sLpsrwZubCk/IyL6ImIl8FQZsnkLcGxE7F0mTTkWuKUcezoiVpYZNc9ouZYkSZIkaRIms9zBN4GjgP0iYohmdsuLgesi4mzgYeDUcvpNNEsdbKRZ7uAsgMzcGhGfBe4q512YmSMTsnyYF5Y7+NvyI0mSJEmapAkTu8x83xiHjmlz7jBwzhjXuQq4qk35D4FDJopDkiRJktReZ6aQlCRJkiTNGhM7SZIkSaqciZ0kSZIkVc7ETpIkSZIqZ2InSZIkSZUzsZMkSZKkypnYSZIkSVLlTOwkSZIkqXImdpIkSZJUORM7SZIkSaqciZ0kSZIkVc7ETpIkSZIqZ2InSZIkSZUzsZMkSZKkypnYSZIkSVLlTOwkSZIkqXImdpIkSZJUORM7SZIkSaqciZ0kSZIkVc7ETpIkSZIqZ2InSZIkSZUbmM6DI+LjwAeBYeBe4CzgAOAaYB9gA3B6Zj4XEQuAdcBhwJPAezNzU7nOBcDZwPPAuZl5y3TikiRJkqT5ZMo9dhGxFDgXODwzDwH6gdOAzwOXZOYKYBtNwkb5vS0zXwdcUs4jIg4uj3sjcBzwlYjon2pckiRJkjTfTHco5gDw8ogYABYCW4CjgevL8bXAyWV7VdmnHD8mIvpK+TWZ+WxmPgRsBI6YZlySJEmSNG9MObHLzEeALwAP0yR0TwF3A9szc2c5bQhYWraXApvLY3eW8/dtLW/zGEmSJEnSBKZ8j11E7E3T23YQsB34FnB8m1OHy+++MY6NVf4iixYtYGBg4hGa/f2dmQ9mcHBhR67b379Hx64904y1c2qKt6ZYJUmS5ovpTJ7yDuChzHwCICJuAN4GDEbEQOmVWwY8Ws4fAg4EhsrQzVcCW1vKR7Q+ZpcdO56dVFCd+sK5ffszHbnu4ODCjl17phlr59QU71ixLlmyuAvRSJIkCaZ3j93DwMqIWFjulTsGuB/4LnBKOWc1cGPZXl/2Kcdvz8zhUn5aRCyIiIOAFcDfTyMuSZIkSZpXpnOP3Z00k6BsoFnqYA/gcuBTwCciYiPNPXRXlodcCexbyj8BnF+ucx9wHU1SeDNwTmY+P9W4JEmSJGm+mdY6dpm5BlgzqvhB2sxqmZk/A04d4zoXARdNJxZJkiRJmq86M9OIJEmSJGnWmNhJkiRJUuVM7CRJkiSpciZ2kiRJklQ5EztJkiRJqpyJnSRJkiRVzsROkiRJkipnYidJkiRJlTOxkyRJkqTKmdhJkiRJUuVM7CRJkiSpciZ2kiRJklQ5EztJkiRJqpyJnSRJkiRVzsROkiRJkipnYidJkiRJlTOxkyRJkqTKmdhJkiRJUuVM7CRJkiSpciZ2kiRJklQ5EztJkiRJqpyJnSRJkiRVbmA6D46IQeAK4BBgGPgdIIFrgeXAJuA9mbktIvqAS4ETgGeAMzNzQ7nOauAz5bKfy8y104lLkiRJkuaT6fbYXQrcnJmvBw4FHgDOB27LzBXAbWUf4HhgRfn5EHAZQETsA6wB3gocAayJiL2nGZckSZIkzRtTTuwiYi/g7cCVAJn5XGZuB1YBIz1ua4GTy/YqYF1mDmfmD4DBiDgAeCdwa2ZuzcxtwK3AcVONS5IkSZLmm+kMxfwl4AngqxFxKHA38FFg/8zcApCZWyLiVeX8pcDmlscPlbKxyiVJkiRJkzCdxG4A+FXgI5l5Z0RcygvDLtvpa1M2PE75iyxatICBgf4Jg+rv78x8MIODCzty3f7+PTp27ZlmrJ1TU7w1xSpJkjRfTCexGwKGMvPOsn89TWL3WEQcUHrrDgAebzn/wJbHLwMeLeVHjSr/3ugn27Hj2UkF1akvnNu3P9OR6w4OLuzYtWeasXZOTfGOFeuSJYu7EI0kSZJgGvfYZeaPgc0REaXoGOB+YD2wupStBm4s2+uBMyKiLyJWAk+VIZu3AMdGxN5l0pRjS5kkSZIkaRKmtdwB8BHg6oh4GfAgcBZNsnhdRJwNPAycWs69iWapg400yx2cBZCZWyPis8Bd5bwLM3PrNOOSJEmSpHljWoldZt4DHN7m0DFtzh0GzhnjOlcBV00nFkmSJEmarzoz04gkSZIkadaY2EmSJElS5UzsJEmSJKlyJnaSJEmSVDkTO0mSJEmqnImdJEmSJFXOxE6SJEmSKmdiJ0mSJEmVM7GTJEmSpMqZ2EmSJElS5UzsJEmSJKlyJnaSJEmSVDkTO0mSJEmqnImdJEmSJFXOxE6SJEmSKmdiJ0mSJEmVM7GTJEmSpMqZ2EmSJElS5UzsJEmSJKlyJnaSJEmSVDkTO0mSJEmqnImdJEmSJFVuYLoXiIh+4IfAI5l5YkQcBFwD7ANsAE7PzOciYgGwDjgMeBJ4b2ZuKte4ADgbeB44NzNvmW5ckiRJkjRfzESP3UeBB1r2Pw9ckpkrgG00CRvl97bMfB1wSTmPiDgYOA14I3Ac8JWSLEqSJEmSJmFaiV1ELAPeBVxR9vuAo4HryylrgZPL9qqyTzl+TDl/FXBNZj6bmQ8BG4EjphOXJEmSJM0n0+2x+zLwSeDnZX9fYHtm7iz7Q8DSsr0U2AxQjj9Vzt9V3uYxkiRJkqQJTPkeu4g4EXg8M++OiKNKcV+bU4cnODbeY3ZZtGgBAwMTj9Ds7+/MfDCDgws7ct3+/j06du2ZZqydU1O8NcUqSZI0X0xn8pQjgZMi4gTgPwB70fTgDUbEQOmVWwY8Ws4fAg4EhiJiAHglsLWlfETrY3bZsePZSQXVqS+c27c/05HrDg4u7Ni1Z5qxdk5N8Y4V65Ili7sQjSRJkmAaQzEz84LMXJaZy2kmP7k9M98PfBc4pZy2GrixbK8v+5Tjt2fmcCk/LSIWlBk1VwB/P9W4JEmSJGm+6cS4xU8Bn4iIjTT30F1Zyq8E9i3lnwDOB8jM+4DrgPuBm4FzMvP5DsQlSZIkSXPStNexA8jM7wHfK9sP0mZWy8z8GXDqGI+/CLhoJmKRJEmSpPmmMzONSJIkSZJmjYmdJEmSJFXOxE6SJEmSKmdiJ0mSJEmVM7GTJEmSpMqZ2EmSJElS5UzsJEmSJKlyJnaSJEmSVDkTO0mSJEmqnImdJEmSJFXOxE6SJEmSKmdiJ0mSJEmVM7GTJEmSpMqZ2EmSJElS5UzsJEmSJKlyJnaSJEmSVDkTO0mSJEmqnImdJEmSJFXOxE6SJEmSKmdiJ0mSJEmVM7GTJEmSpMqZ2EmSJElS5Qam+sCIOBBYB7wa+DlweWZeGhH7ANcCy4FNwHsyc1tE9AGXAicAzwBnZuaGcq3VwGfKpT+XmWunGpckSZIkzTfT6bHbCZyXmW8AVgLnRMTBwPnAbZm5Arit7AMcD6woPx8CLgMoieAa4K3AEcCaiNh7GnFJkiRJ0rwy5cQuM7eM9Lhl5tPAA8BSYBUw0uO2Fji5bK8C1mXmcGb+ABiMiAOAdwK3ZubWzNwG3AocN9W4JEmSJGm+mfJQzFYRsRx4M3AnsH9mboEm+YuIV5XTlgKbWx42VMrGKn+RRYsWMDDQP2Es/f2duW1wcHBhR67b379Hx64904y1c2qKt6ZYJUmS5otpJ3YRsQj4NvCxzPxJRIx1al+bsuFxyl9kx45nJxVPp75wbt/+TEeuOzi4sGPXnmnG2jk1xTtWrEuWLO5CNJIkSYJpzooZEXvSJHVXZ+YNpfixMsSS8vvxUj4EHNjy8GXAo+OUS5IkSZImYcqJXZnl8krggcz8Usuh9cDqsr0auLGl/IyI6IuIlcBTZcjmLcCxEbF3mTTl2FImSZIkSZqE6QzFPBI4Hbg3Iu4pZZ8GLgaui4izgYeBU8uxm2iWOthIs9zBWQCZuTUiPgvcVc67MDO3TiMuSZIkSZpXppzYZebf0f7+OIBj2pw/DJwzxrWuAq6aaiySJEmSNJ91ZgpJSZIkSdKsMbGTJEmSpMqZ2EmSJElS5UzsJEmSJKlyJnaSJEmSVDkTO0mSJEmqnImdJEmSJFXOxE6SJEmSKmdiJ0mSJEmVM7GTJEmSpMqZ2EmSJElS5UzsJEmSJKlyJnaSJEmSVDkTO0mSJEmqnImdJEmSJFXOxE6SJEmSKmdiJ0mSJEmVM7GTJEmSpMqZ2EmSJElS5UzsJEmSJKlyA90OoBZv+eIdM37Nu857+4xfU5IkSdL8Y4+dJEmSJFWuZ3rsIuI44FKgH7giMy/uckiSJEmSVIWeSOwioh/4U+A3gCHgrohYn5n3dzeyznJ4pyRJkqSZ0BOJHXAEsDEzHwSIiGuAVcCcTuw6wWRRkiRJmn96JbFbCmxu2R8C3tp6wpIli/sme7FNF79rhsLSaEuWLO52CJNWU6xQV7w1xSpJkjQf9MrkKe2StuFZj0KSJEmSKtQrid0QcGDL/jLg0S7FIkmSJElV6ZWhmHcBKyLiIOAR4DTgt7sbkiRJkiTVoW94uDdGPEbECcCXaZY7uCozL5rCNbq+ZEJEHAisA14N/By4PDMvjYh9gGuB5cAm4D2ZuS0i+krMJwDPAGdm5oZyrdXAZ8qlP5eZazsUcz/wQ+CRzDyxJNjXAPsAG4DTM/O5iFhQXtthwJPAezNzU7nGBcDZwPPAuZl5S4diHQSuAA6hGa77O0DSg3UbER8HPljivBc4CziAHqjbiLgKOBF4PDMPKWUz9h6NiMOArwEvB24CPpqZvdHYSJIkzUG9MhSTzLwpM385M187xaRuZMmE44GDgfdFxMEzHeck7ATOy8w3ACuBc0oc5wO3ZeYK4LayT4l3Rfn5EHAZ7PqSvYZmEpkjgDURsXeHYv4o8EDL/ueBS0qs22iSCsrvbZn5OuCSch7l9Z0GvBE4DvhK+ffohEuBmzPz9cChJe6eq9uIWAqcCxxeEqd+mjrqlbr9Wrleq5msx8vKuSOPG/1ckiRJmkE9k9jNgF1LJmTmczS9IqtmO4jM3DLSm5GZT9MkHktLLCO9QmuBk8v2KmBdZg5n5g+AwYg4AHgncGtmbs3MbcCtdODLcUQsA95F0wtG6Z05Grh+jFhHXsP1wDHl/FXANZn5bGY+BGyk+feY6Vj3At4OXAmQmc9l5nZ6tG5phjq/PCIGgIXAFnqkbjPzDmDrqOIZqcdybK/M/H7ppVvXci1JkiR1wFxK7NotmbC0S7EAEBHLgTcDdwL7Z+YWaJI/4FXltLHinq3X82XgkzTDRgH2BbZn5s42z7srpnL8qXL+bMX6S8ATwFcj4kcRcUVEvIIerNvMfAT4AvAwTUL3FHA3vVu3MHP1uLRsz0bMkiRJYm4ldj21ZEJELAK+DXwsM38yzqljxd3x1xMRI/dY3T2JeMY7Nlt1PwD8KnBZZr4Z+CkvDBdsp5t1uzdNT9dBwGuAV9AMaRzrebtdt+PZ3dh6IWZJkqR5ZS4ldj2zZEJE7EmT1F2dmTeU4sfKEDXK78dL+Vhxz8brORI4KSI20QxdPZqmB2+wDB8c/by7YirHX0kznG+26n4IGMrMO8v+9TSJXi/W7TuAhzLzicz8d+AG4G30bt3CzNXjUNmejZglSZLE3Ersdi2ZEBEvo5lwYv1sB1Hui7oSeCAzv9RyaD2wumyvBm5sKT8jIvoiYiXwVBkGdwtwbETsXXp/ji1lMyYzL8jMZZm5nKa+bs/M9wPfBU4ZI9aR13BKOX+4lJ8WEQvKjJorgL+fyVhLvD8GNkdElKJjgPvpwbqlGYK5MiIWlvfESKw9WbdtYphyPZZjT0fEyvLaz2i5liRJkjqgV9axm7bM3BkRv0/zZXNkyYT7uhDKkcDpwL0RcU8p+zRwMXBdRJxN86X/1HLsJppp5DfSTCV/FkBmbo2Iz9IkrAAXZuboyS465VPANRHxOeBHlMlKyu+/iIiNNL1Jp5VY74uI62gSl53AOZn5fIdi+whwdUneH6Sprz3osbrNzDsj4nqaJQ120tTj5cDf0AN1GxHfBI4C9ouIIZrZLWfyPfphXlju4G/LjyRJkjqkZ9axkyRJkiRNzVwaiilJkiRJ85KJnSRJkiRVzsROkiRJkipnYidJkiRJlTOxkyRJkqTKmdhJkiRJUuVM7CRJkiSpciZ2kiRJklS5/w9AUYGPi+Dv/wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38aded8b38>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#df_movies.plot(x = 'popularity', y = 'revenue', kind = 'scatter')\n",
    "df_movies.hist(figsize = (15, 15))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I needed to get more insights on all the numeric columns in the dataset. So, i created a histogram using the hist() function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f38b130b7b8>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38b1219f60>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_movies.plot(x = 'revenue', y = 'popularity', kind = 'scatter', figsize = (9,6), alpha = 0.5, s = 60)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Reasoning section:** The points are seen closer to each other, viewing from the x - axis but not neccesary forming a straight line. Therefore, there's a weak positive correlation here. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Research Question 2  (Which year has the highest number of movies released?)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_movies['release_year'] = df_movies['release_date'].apply(lambda x: x.year)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "release_year\n",
       "1972     40\n",
       "1973     55\n",
       "1974     47\n",
       "1975     44\n",
       "1976     47\n",
       "1977     57\n",
       "1978     65\n",
       "1979     57\n",
       "1980     78\n",
       "1981     82\n",
       "1982     81\n",
       "1983     80\n",
       "1984    105\n",
       "1985    109\n",
       "1986    121\n",
       "1987    125\n",
       "1988    145\n",
       "1989    137\n",
       "1990    132\n",
       "1991    133\n",
       "1992    133\n",
       "1993    178\n",
       "1994    184\n",
       "1995    175\n",
       "1996    204\n",
       "1997    192\n",
       "1998    210\n",
       "1999    224\n",
       "2000    227\n",
       "2001    242\n",
       "2002    266\n",
       "2003    281\n",
       "2004    307\n",
       "2005    364\n",
       "2006    408\n",
       "2007    438\n",
       "2008    496\n",
       "2009    533\n",
       "2010    489\n",
       "2011    540\n",
       "2012    588\n",
       "2013    659\n",
       "2014    700\n",
       "2015    629\n",
       "2060     32\n",
       "2061     31\n",
       "2062     32\n",
       "2063     34\n",
       "2064     42\n",
       "2065     35\n",
       "2066     46\n",
       "2067     40\n",
       "2068     39\n",
       "2069     31\n",
       "2070     41\n",
       "2071     55\n",
       "Name: original_title, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie_year = df_movies.groupby('release_year')['original_title'].count()\n",
    "movie_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38b15da7b8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Creating a funtion\n",
    "def barh_plot(x , y , z):\n",
    "    x.plot(kind = 'barh', figsize = (15, 15), color = 'blue')\n",
    "    plt.title(y)\n",
    "    plt.xlabel (z, fontsize = 15)\n",
    "    plt.ylabel ('release_year', fontsize = 15)\n",
    "    \n",
    "barh_plot(movie_year, 'Year vs. Number of movies', 'count')\n",
    "\n",
    "#You can use the code below for the same result\n",
    "# movie_year.plot(kind = 'barh', figsize = (15, 15), color = 'blue')\n",
    "# plt.title('Year vs. Number of movies')\n",
    "# plt.ylabel('release_year', fontsize = 15, )\n",
    "# plt.xlabel('count', fontsize = 15)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Reasoning Section:** Here, 2014 seems to be the year with the highest number of movies released. 2015 and 2013 are clearly seen to be the second best."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Research Question 3  (Which year had the highest  total number of vote count?)\n",
    "<p>Here, 2013 had the highest total number of vote counts, while 1966 seems to be year with the lowest.<p/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "release_year\n",
       "1972      5433\n",
       "1973      5173\n",
       "1974      5207\n",
       "1975      6088\n",
       "1976      4720\n",
       "1977      8031\n",
       "1978      4898\n",
       "1979      8830\n",
       "1980     10898\n",
       "1981      7480\n",
       "1982     11385\n",
       "1983      9886\n",
       "1984     15371\n",
       "1985     13761\n",
       "1986     13675\n",
       "1987     15064\n",
       "1988     14576\n",
       "1989     18657\n",
       "1990     21575\n",
       "1991     17006\n",
       "1992     19447\n",
       "1993     24284\n",
       "1994     37591\n",
       "1995     35810\n",
       "1996     26031\n",
       "1997     40985\n",
       "1998     40042\n",
       "1999     53447\n",
       "2000     46206\n",
       "2001     63058\n",
       "2002     62904\n",
       "2003     68425\n",
       "2004     79200\n",
       "2005     73336\n",
       "2006     76083\n",
       "2007     90391\n",
       "2008    102562\n",
       "2009    119689\n",
       "2010    130039\n",
       "2011    135439\n",
       "2012    183539\n",
       "2013    214486\n",
       "2014    206262\n",
       "2015    182422\n",
       "2060      2481\n",
       "2061      2405\n",
       "2062      2392\n",
       "2063      2816\n",
       "2064      3137\n",
       "2065      1820\n",
       "2066      1460\n",
       "2067      3102\n",
       "2068      4217\n",
       "2069      1733\n",
       "2070      2011\n",
       "2071      5081\n",
       "Name: vote_count, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year_vote_count = df_movies.groupby('release_year')['vote_count'].sum()\n",
    "year_vote_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38b20137b8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "barh_plot(year_vote_count, 'Year by Votecount', 'Vote_count')\n",
    "\n",
    "#You can use the code below for the same result\n",
    "# year_vote_count.plot(kind = 'barh', figsize = (15, 15))\n",
    "# plt.title('Year by Votecount')\n",
    "# plt.ylabel('release_year', fontsize = 15)\n",
    "# plt.xlabel('Vote_count', fontsize = 15)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Reasoning section:** The year 2013 is seen to have the highest total number of vote counts for all movies released in that year. The year 2012, 2014 and 2015 also had higher vote count."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Research Question 4 (Relationship between vote count and the popularity popularity of a movie?)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Popularity vs. Vote Count')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f38b1141198>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_movies.plot(x = 'vote_count', y = 'popularity', kind = 'scatter', figsize = (8,8), alpha = 0.7)\n",
    "plt.title('Popularity vs. Vote Count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Reasoning Section**: Most of the points are seen together moving to the right of the x - axis and a straight line can be drawn in the plot. Therefore, there's a strong positive correlation.</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Research Question 5 (The name of the movie with the highest  and lowest revenue?)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1386    Avatar\n",
      "Name: original_title, dtype: object\n"
     ]
    }
   ],
   "source": [
    "maximium = df_movies['revenue'].max()\n",
    "max_revenue = df_movies.original_title[df_movies['revenue'] == maximium]\n",
    "print(max_revenue)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "48                                              Wild Card\n",
      "67                                               Survivor\n",
      "74                                 Mythica: The Darkspore\n",
      "75                         Me and Earl and the Dying Girl\n",
      "92                               Mythica: The Necromancer\n",
      "93                                                   Vice\n",
      "100                                          Frozen Fever\n",
      "101                                             High-Rise\n",
      "103                              Spooks: The Greater Good\n",
      "116                    The Scorpion King: The Lost Throne\n",
      "122                                                Everly\n",
      "133                                     Louder Than Bombs\n",
      "140                   Dragonheart 3: The Sorcerer's Curse\n",
      "143                                  Brothers of the Wind\n",
      "145                                         Bone Tomahawk\n",
      "147                                        Pawn Sacrifice\n",
      "149                                              Momentum\n",
      "151                                         Pay the Ghost\n",
      "152                                            The Voices\n",
      "154                              Il racconto dei racconti\n",
      "156                                   Queen of the Desert\n",
      "158                                      Miss You Already\n",
      "159                                             Kung Fury\n",
      "164                               Kidnapping Mr. Heineken\n",
      "165                                      The Ridiculous 6\n",
      "166                                   Kill Me Three Times\n",
      "169                                              45 Years\n",
      "174                                       Jenny's Wedding\n",
      "175                                           Descendants\n",
      "176                                            Tumbledown\n",
      "                               ...                       \n",
      "10834                                 Return of the Seven\n",
      "10836                                      Walk Don't Run\n",
      "10837                                        The Blue Max\n",
      "10838                                   The Professionals\n",
      "10839               It's the Great Pumpkin, Charlie Brown\n",
      "10840                                   Funeral in Berlin\n",
      "10841                                        The Shooting\n",
      "10842                  Winnie the Pooh and the Honey Tree\n",
      "10843                                            Khartoum\n",
      "10844                                       Our Man Flint\n",
      "10845                                     Carry On Cowboy\n",
      "10846                         Dracula: Prince of Darkness\n",
      "10847                                    Island of Terror\n",
      "10849                                              Gambit\n",
      "10850                                              Harper\n",
      "10851                                           Born Free\n",
      "10852                      A Big Hand for the Little Lady\n",
      "10853                                               Alfie\n",
      "10854                                           The Chase\n",
      "10855                             The Ghost & Mr. Chicken\n",
      "10856                                  The Ugly Dachshund\n",
      "10857                                        Nevada Smith\n",
      "10858    The Russians Are Coming, The Russians Are Coming\n",
      "10859                                             Seconds\n",
      "10860                                 Carry On Screaming!\n",
      "10861                                  The Endless Summer\n",
      "10862                                          Grand Prix\n",
      "10863                                 Beregis Avtomobilya\n",
      "10864                              What's Up, Tiger Lily?\n",
      "10865                            Manos: The Hands of Fate\n",
      "Name: original_title, Length: 6016, dtype: object\n"
     ]
    }
   ],
   "source": [
    "minimium = df_movies['revenue'].min()\n",
    "min_revenue = df_movies.original_title[df_movies['revenue'] == minimium]\n",
    "\n",
    "print(min_revenue)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Reasoning Section:** I made use of the min() and max() function to find the movies with the highest and lowest revenue. Avatar is the movie with the highest revenue and the result above are the movies that had the lowest revenue."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Research Question 6  (The name of the Movies with the highest and lowest runtime?)\n",
    "<p>The movie, \"The story of film: An Odyssey\" has the highest runtime of 900 minutes. <p/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3894    The Story of Film: An Odyssey\n",
      "Name: original_title, dtype: object :Runtime = 900\n"
     ]
    }
   ],
   "source": [
    "# movie with highest runtime.\n",
    "maxi= df_movies['runtime'].max()\n",
    "max_runtime = df_movies.original_title[df_movies['runtime'] == maxi]\n",
    "print(max_runtime, ':Runtime =', maxi)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b><p>The following list below show all movies with a runtime of 0 minutes. <p/></b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "92           Mythica: The Necromancer\n",
      "334                           Ronaldo\n",
      "410                    Anarchy Parlor\n",
      "445     The Exorcism of Molly Hartley\n",
      "486                If There Be Thorns\n",
      "595                         Deep Dark\n",
      "616                      The Outfield\n",
      "1241                        Dance-Off\n",
      "1289                        Treehouse\n",
      "1293                         Tim Maia\n",
      "1849                     Spectacular!\n",
      "2315             Listen to Your Heart\n",
      "2370                  Freshman Father\n",
      "3329         Grande, grosso e Verdone\n",
      "3794             Toi, moi, les autres\n",
      "3857                         Cell 213\n",
      "3884                           eCupid\n",
      "4063           Madea's Family Reunion\n",
      "4138               A Time for Dancing\n",
      "4829                             Rags\n",
      "4944              How to Fall in Love\n",
      "5216            Madea's Class Reunion\n",
      "5695                 Skinwalker Ranch\n",
      "5920           The Food Guide to Love\n",
      "5938                      Go Goa Gone\n",
      "5992                 Amiche da morire\n",
      "6040            The Vatican Exorcisms\n",
      "6383         The 12 Dogs of Christmas\n",
      "6552                  Quatre Ã©toiles\n",
      "6934                    Jean-Philippe\n",
      "8874                  Mission Kashmir\n",
      "Name: original_title, dtype: object :Runtime = 0\n"
     ]
    }
   ],
   "source": [
    "# movie with highest runtime.\n",
    "mini= df_movies['runtime'].min()\n",
    "min_runtime = df_movies.original_title[df_movies['runtime'] == mini]\n",
    "print(min_runtime, ':Runtime =', mini)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Reasoning Section:** I made use of the min() and max() function to find the movies with the highest and lowest runtime. The Story of Film: An Odyssey is the movie with the highest runtime of 900 minutes and the result above are the movies that had the lowest runtime of 0 minutes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='conclusions'></a>\n",
    "## Submitting your Project "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Limitation: \n",
    "Null values were found in this dataset which could create an inaccurate analysis. So, i simply replaced all null values with their respective mean using the mean() function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "In this analysis, i discovered the following:\n",
    "<li>In the movie industry, 2015 had the highest revenue/income.</li>\n",
    "<li>The year 2014 had the highest number of movie released. Although, 2013 and 2015 were the second best.</li>\n",
    "<li>The number of vote count does not neccessary determine the popularity of the movie.</li>\n",
    "<li>The year 2013, had the highest number of vote count.</li>\n",
    "<li>In the movie industry, 2015 had the highest revenue/income.</li>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from subprocess import call\n",
    "call(['python', '-m', 'nbconvert', 'Investigate_a_Dataset.ipynb'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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